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0d836a0461e9c21fa7a25622115de55b81ceb446 | Estimation of Presentations Skills Based on Slides and Audio Features | This paper proposes a simple estimation of the quality of student oral presentations. It is based on the study and analysis of features extracted from the audio and digital slides of 448 presentations. The main goal of this work is to automatically predict the values assigned by professors to different criteria in a presentation evaluation rubric. Machine Learning methods were used to create several models that classify students in two clusters: high and low performers. The models created from slide features were accurate up to 65%. The most relevant features for the slide-base models were: number of words, images, and tables, and the maximum font size. The audio-based models reached up to 69% of accuracy, with pitch and filled pauses related features being the most significant. The relatively high degrees of accuracy obtained with these very simple features encourage the development of automatic estimation tools for improving presentation skills. |
1627ce7f1429366829df3d49e28b8ecd7f7597b5 | Diplomat: Using Delegations to Protect Community Repositories | Community repositories, such as Docker Hub, PyPI, and RubyGems, are bustling marketplaces that distribute software. Even though these repositories use common software signing techniques (e.g., GPG and TLS), attackers can still publish malicious packages after a server compromise. This is mainly because a community repository must have immediate access to signing keys in order to certify the large number of new projects that are registered each day. This work demonstrates that community repositories can offer compromise-resilience and real-time project registration by employing mechanisms that disambiguate trust delegations. This is done through two delegation mechanisms that provide flexibility in the amount of trust assigned to different keys. Using this idea we implement Diplomat, a software update framework that supports security models with different security / usability tradeoffs. By leveraging Diplomat, a community repository can achieve near-perfect compromise-resilience while allowing real-time project registration. For example, when Diplomat is deployed and configured to maximize security on Python’s community repository, less than 1% of users will be at risk even if an attacker controls the repository and is undetected for a month. Diplomat is being integrated by Ruby, CoreOS, Haskell, OCaml, and Python, and has already been deployed by Flynn, LEAP, and Docker. |
69613390ca76bf103791ef251e1568deb5fe91dd | Satellite Image Classification Methods and Techniques: A Review | Satellite image classification process involves grouping the image pixel values into meaningful categories. Several satellite image classification methods and techniques are available. Satellite image classification methods can be broadly classified into three categories 1) automatic 2) manual and 3) hybrid. All three methods have their own advantages and disadvantages. Majority of the satellite image classification methods fall under first category. Satellite image classification needs selection of appropriate classification method based on the requirements. The current research work is a study on satellite image classification methods and techniques. The research work also compares various researcher's comparative results on satellite image classification methods. |
456f85fb61fa5f137431e6d12c5fc73cc2ebaced | Biometric Gait Authentication Using Accelerometer Sensor | This paper presents a biometric user authentication based on a person’s gait. Unlike most previous gait recognition approaches, which are based on machine vision techniques, in our approach gait patterns are extracted from a physical device attached to the lower leg. From the output of the device accelerations in three directions: vertical, forward-backward, and sideways motion of the lower leg are obtained. A combination of these accelerations is used for authentication. Applying two different methods, histogram similarity and cycle length, equal error rates (EER) of 5% and 9% were achieved, respectively. |
4e116ae01d873ad67fb2ab6da5cb4feeb24bbcb5 | Decision making regarding Smith-Petersen vs. pedicle subtraction osteotomy vs. vertebral column resection for spinal deformity. | STUDY DESIGN
Author experience and literature review.
OBJECTIVES
To investigate and discuss decision-making on when to perform a Smith-Petersen osteotomy as opposed to a pedicle subtraction procedure and/or a vertebral column resection.
SUMMARY OF BACKGROUND DATA
Articles have been published regarding Smith-Petersen osteotomies, pedicle subtraction procedures, and vertebral column resections. Expectations and complications have been reviewed. However, decision-making regarding which of the 3 procedures is most useful for a particular spinal deformity case is not clearly investigated.
METHODS
Discussed in this manuscript is the author's experience and the literature regarding the operative options for a fixed coronal or sagittal deformity.
RESULTS
There are roles for Smith-Petersen osteotomy, pedicle subtraction, and vertebral column resection. Each has specific applications and potential complications.
CONCLUSION
As the magnitude of resection increases, the ability to correct deformity improves, but also the risk of complication increases. Therein, an understanding of potential applications and complications is helpful. |
80ca5505a9ba00e91283519a75e01840a15a74bf | dCompaction: Delayed Compaction for the LSM-Tree | Key-value (KV) stores have become a backbone of large-scale applications in today’s data centers. Write-optimized data structures like the Log-Structured Merge-tree (LSM-tree) and their variants are widely used in KV storage systems like BigTable and RocksDB. Conventional LSM-tree organizes KV items into multiple, successively larger components, and uses compaction to push KV items from one smaller component to another adjacent larger component until the KV items reach the largest component. Unfortunately, current compaction scheme incurs significant write amplification due to repeated KV item reads and writes, and then results in poor throughput. We propose a new compaction scheme, delayed compaction (dCompaction), that decreases write amplification. dCompaction postpones some compactions and gather them into the following compaction. In this way, it avoids KV item reads and writes during compaction, and consequently improves the throughput of LSM-tree based KV stores. We implement dCompaction on RocksDB, and conduct extensive experiments. Validation using YCSB framework shows that compared with RocksDB dCompaction has about 30% write performance improvements and also comparable read performance. |
131e4a4a40c29737f39e8cb0f4e59864ca1a1b34 | LaneQuest: An accurate and energy-efficient lane detection system | Current outdoor localization techniques fail to provide the required accuracy for estimating the car's lane. In this paper, we present LaneQuest: a system that leverages the ubiquitous and low-energy inertial sensors available in commodity smart-phones to provide an accurate estimate of the car's current lane. LaneQuest leverages hints from the phone sensors about the surrounding environment to detect the car's lane. For example, a car making a right turn most probably will be in the right-most lane, a car passing by a pothole will be in a specific lane, and the car's angular velocity when driving through a curve reflects its lane. Our investigation shows that there are amble opportunities in the environment, i.e. lane “anchors”, that provide cues about the car's lane. To handle the ambiguous location, sensors noise, and fuzzy lane anchors; LaneQuest employs a novel probabilistic lane estimation algorithm. Furthermore, it uses an unsupervised crowd-sourcing approach to learn the position and lane-span distribution of the different lane-level anchors. Our evaluation results from implementation on different android devices and 260Km driving traces by 13 drivers in different cities shows that LaneQuest can detect the different lane-level anchors with an average precision and recall of more than 90%. This leads to an accurate detection of the exact car's lane position 80% of the time, increasing to 89% of the time to within one lane. This comes with a low-energy footprint, allowing LaneQuest to be implemented on the energy-constrained mobile devices. |
3cbf0dcbc36a8f70e9b2b2f46b16e5057cbd9a7d | Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance | Fine-grained sense distinctions are one of the major obstacles to successful Word Sense Disambiguation. In this paper, we present a method for reducing the granularity of the WordNet sense inventory based on the mapping to a manually crafted dictionary encoding sense hierarchies, namely the Oxford Dictionary of English. We assess the quality of the mapping and the induced clustering, and evaluate the performance of coarse WSD systems in the Senseval-3 English all-words task. |
528fa9bb03644ba752fb9491be49b9dd1bce1d52 | SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity | Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. This paper presents the results of the STS pilot task in Semeval. The training data contained 2000 sentence pairs from previously existing paraphrase datasets and machine translation evaluation resources. The test data also comprised 2000 sentences pairs for those datasets, plus two surprise datasets with 400 pairs from a different machine translation evaluation corpus and 750 pairs from a lexical resource mapping exercise. The similarity of pairs of sentences was rated on a 0-5 scale (low to high similarity) by human judges using Amazon Mechanical Turk, with high Pearson correlation scores, around 90%. 35 teams participated in the task, submitting 88 runs. The best results scored a Pearson correlation>80%, well above a simple lexical baseline that only scored a 31% correlation. This pilot task opens an exciting way ahead, although there are still open issues, specially the evaluation metric. |
d87ceda3042f781c341ac17109d1e94a717f5f60 | WordNet : an electronic lexical database | WordNet is perhaps the most important and widely used lexical resource for natural language processing systems up to now. WordNet: An Electronic Lexical Database, edited by Christiane Fellbaum, discusses the design of WordNet from both theoretical and historical perspectives, provides an up-to-date description of the lexical database, and presents a set of applications of WordNet. The book contains a foreword by George Miller, an introduction by Christiane Fellbaum, seven chapters from the Cognitive Sciences Laboratory of Princeton University, where WordNet was produced, and nine chapters contributed by scientists from elsewhere. Miller's foreword offers a fascinating account of the history of WordNet. He discusses the presuppositions of such a lexical database, how the top-level noun categories were determined, and the sources of the words in WordNet. He also writes about the evolution of WordNet from its original incarnation as a dictionary browser to a broad-coverage lexicon, and the involvement of different people during its various stages of development over a decade. It makes very interesting reading for casual and serious users of WordNet and anyone who is grateful for the existence of WordNet. The book is organized in three parts. Part I is about WordNet itself and consists of four chapters: "Nouns in WordNet" by George Miller, "Modifiers in WordNet" by Katherine Miller, "A semantic network of English verbs" by Christiane Fellbaum, and "Design and implementation of the WordNet lexical database and search software" by Randee Tengi. These chapters are essentially updated versions of four papers from Miller (1990). Compared with the earlier papers, the chapters in this book focus more on the underlying assumptions and rationales behind the design decisions. The description of the information contained in WordNet, however, is not as detailed as in Miller (1990). The main new additions in these chapters include an explanation of sense grouping in George Miller's chapter, a section about adverbs in Katherine Miller's chapter, observations about autohyponymy (one sense of a word being a hyponym of another sense of the same word) and autoantonymy (one sense of a word being an antonym of another sense of the same word) in Fellbaum's chapter, and Tengi's description of the Grinder, a program that converts the files the lexicographers work with to searchable lexical databases. The three papers in Part II are characterized as "extensions, enhancements and |
1528def1ddbd2deb261ebb873479f27f48251031 | Clustering WordNet word senses | This paper presents the results of a set of methods to cluster WordNet word senses. The methods rely on different information sources: confusion matrixes from Senseval-2 Word Sense Disambiguation systems, translation similarities, hand-tagged examples of the target word senses and examples obtained automatically from the web for the target word senses. The clustering results have been evaluated using the coarsegrained word senses provided for the lexical sample in Senseval-2. We have used Cluto, a general clustering environment, in order to test different clustering algorithms. The best results are obtained for the automatically obtained examples, yielding purity values up to 84% on average over 20 nouns. |
2445089d4277ccbec3727fecfe73eaa4cc57e414 | (Meta-) Evaluation of Machine Translation | This paper evaluates the translation quality of machine translation systems for 8 language pairs: translating French, German, Spanish, and Czech to English and back. We carried out an extensive human evaluation which allowed us not only to rank the different MT systems, but also to perform higher-level analysis of the evaluation process. We measured timing and intraand inter-annotator agreement for three types of subjective evaluation. We measured the correlation of automatic evaluation metrics with human judgments. This meta-evaluation reveals surprising facts about the most commonly used methodologies. |
3764e0bfcc4a196eb020d483d8c2f1822206a444 | LSTM-Based Hierarchical Denoising Network for Android Malware Detection | Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN), a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequences are too long for LSTM to train due to the gradient vanishing problem. Hence, HDN uses a hierarchical structure, whose first-level LSTM parallelly computes on opcode subsequences (we called them method blocks) to learn the dense representations; then the secondlevel LSTM can learn and detect malware through method block sequences. Considering that malicious behavior only appears in partial sequence segments, HDN uses method block denoise module (MBDM) for data denoising by adaptive gradient scaling strategy based on loss cache. We evaluate and compare HDN with the latest mainstream researches on three datasets. The results show that HDN outperforms these Android malware detection methods,and it is able to capture longer sequence features and has better detection efficiency thanN-gram-based malware detection which is similar to our method. |
41bb7d4546fbc95d55342b621f95edad3b06717e | A Study on False Channel Condition Reporting Attacks in Wireless Networks | Wireless networking protocols are increasingly being designed to exploit a user's measured channel condition; we call such protocols channel-aware. Each user reports the measured channel condition to a manager of wireless resources and a channel-aware protocol uses these reports to determine how resources are allocated to users. In a channel-aware protocol, each user's reported channel condition affects the performance of every other user. The deployment of channel-aware protocols increases the risks posed by false channel-condition feedback. In this paper, we study what happens in the presence of an attacker that falsely reports its channel condition. We perform case studies on channel-aware network protocols to understand how an attack can use false feedback and how much the attack can affect network performance. The results of the case studies show that we need a secure channel condition estimation algorithm to fundamentally defend against the channel-condition misreporting attack. We design such an algorithm and evaluate our algorithm through analysis and simulation. Our evaluation quantifies the effect of our algorithm on system performance as well as the security and the performance of our algorithm. |
fe025433b702bf6e946610e0dba77f7dd16ae821 | Extreme-angle broadband metamaterial lens. | For centuries, the conventional approach to lens design has been to grind the surfaces of a uniform material in such a manner as to sculpt the paths that rays of light follow as they transit through the interfaces. Refractive lenses formed by this procedure of bending the surfaces can be of extremely high quality, but are nevertheless limited by geometrical and wave aberrations that are inherent to the manner in which light refracts at the interface between two materials. Conceptually, a more natural--but usually less convenient--approach to lens design would be to vary the refractive index throughout an entire volume of space. In this manner, far greater control can be achieved over the ray trajectories. Here, we demonstrate how powerful emerging techniques in the field of transformation optics can be used to harness the flexibility of gradient index materials for imaging applications. In particular we design and experimentally demonstrate a lens that is broadband (more than a full decade bandwidth), has a field-of-view approaching 180 degrees and zero f-number. Measurements on a metamaterial implementation of the lens illustrate the practicality of transformation optics to achieve a new class of optical devices. |
9b9da80c186d8f6e7fa35747a6543d78e36f17e8 | HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users | We introduce hand movement, orientation, and grasp (HMOG), a set of behavioral features to continuously authenticate smartphone users. HMOG features unobtrusively capture subtle micro-movement and orientation dynamics resulting from how a user grasps, holds, and taps on the smartphone. We evaluated authentication and biometric key generation (BKG) performance of HMOG features on data collected from 100 subjects typing on a virtual keyboard. Data were collected under two conditions: 1) sitting and 2) walking. We achieved authentication equal error rates (EERs) as low as 7.16% (walking) and 10.05% (sitting) when we combined HMOG, tap, and keystroke features. We performed experiments to investigate why HMOG features perform well during walking. Our results suggest that this is due to the ability of HMOG features to capture distinctive body movements caused by walking, in addition to the hand-movement dynamics from taps. With BKG, we achieved the EERs of 15.1% using HMOG combined with taps. In comparison, BKG using tap, key hold, and swipe features had EERs between 25.7% and 34.2%. We also analyzed the energy consumption of HMOG feature extraction and computation. Our analysis shows that HMOG features extracted at a 16-Hz sensor sampling rate incurred a minor overhead of 7.9% without sacrificing authentication accuracy. Two points distinguish our work from current literature: 1) we present the results of a comprehensive evaluation of three types of features (HMOG, keystroke, and tap) and their combinations under the same experimental conditions and 2) we analyze the features from three perspectives (authentication, BKG, and energy consumption on smartphones). |
4e0e664450094cc786898a5e1ef3727135ecfcd8 | Accurate nonrigid 3D human body surface reconstruction using commodity depth sensors | 1Department of Computer Science, School of Engineering and Applied Science, Institute for Computer Graphics, The George Washington University, 800 22nd Street NW Suite 3400, Washington, DC 20052, USA 2Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, The George Washington University, 800 22nd Street NW Suite 7680, Washington, DC 20052, USA 3Department of Computer Science, School of Engineering and Applied Science, and Department of Pediatrics, School of Medicine and Health Sciences, Institute for Computer Graphics, The George Washington University, 800 22nd Street NW Suite 5830, Washington, DC 20052, USA |
de0597313056b05fd7dd6b2d5e031cfb96564920 | Transductive Adversarial Networks (TAN) | Transductive Adversarial Networks (TAN) is a novel domain-adaptation machine learning framework that is designed for learning a conditional probability distribution on unlabelled input data in a target domain, while also only having access to: (1) easily obtained labelled data from a related source domain, which may have a different conditional probability distribution than the target domain, and (2) a marginalised prior distribution on the labels for the target domain. TAN leverages a fully adversarial training procedure and a unique generator/encoder architecture which approximates the transductive combination of the available sourceand target-domain data. A benefit of TAN is that it allows the distance between the sourceand target-domain label-vector marginal probability distributions to be greater than 0 (i.e. different tasks across the source and target domains) whereas other domain-adaptation algorithms require this distance to equal 0 (i.e. a single task across the source and target domains). TAN can, however, still handle the latter case and is a more generalised approach to this case. Another benefit of TAN is that due to being a fully adversarial algorithm, it has the potential to accurately approximate highly complex distributions. Theoretical analysis demonstrates the viability of the TAN framework. |
620c1821f67fd39051fe0863567ac702ce27a72a | Modeling, simulation, and development of a robotic dolphin prototype | Abilities of sea animals and efficiency of fish swimming are a few of the impressive solutions of nature. In this paper, design, modeling, simulation and development studies of a robotic dolphin prototype, entirely inspired by the bottlenose dolphin (Tursiops truncatus), are presented. The first section focuses on the design principles and core design features of the prototype. In the second section, modeling and simulation studies which consist of hydrodynamics, kinematics and dynamical analysis of the robotic dolphin are presented. Dynamical simulations of the underwater behavior of the prototype are included in this section. The third section focuses on the general prototype development from mechanical construction to control system structure. Finally in the last section, experimental results obtained through the development of the prototype are discussed. |
7da851a9d67b6c8ee7e985928f91ee577c529f2e | An Empirical Comparison of Topics in Twitter and Traditional Media | Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster news feed that covers mostly the same information as traditional news media. In This paper we empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to compare these Twitter topics with topics from New York Times, taking into consideration of topic categories and types. We find that although Twitter and New York Times cover similar categories and types of topics, the distributions of topic categories and types are quite different. Furthermore, there are Twitter-specific topics and NYT-specific topics, and they tend to belong to certain topic categories and types. We also study the relation between the proportions of opinionated tweets and retweets and topic categories and types, and find some interesting dependence. To the best of our knowledge, ours is the first comprehensive empirical comparison between Twitter and traditional news media. |
0b3983a6ad65f7f480d63d5a8d3e9f5c9c57e06a | Binary Rewriting of an Operating System Kernel ∗ | This paper deals with some of the issues that arise in the context of binary rewriting and instrumentation of an operatin g system kernel. OS kernels are very different from ordinary application code in many ways, e.g., they contain a significant amount of hand-written assembly code. Binary rewriting is an attractive approach for processing OS kernel code for several reasons, e.g., it provides a uniform way to handl e heterogeneity in code due to a combination of source code, assembly code and legacy code such as in device drivers. However, because of the many differences between ordinary application code and OS kernel code, binary rewriting techniques that work for application code do not always carry over directly to kernel code. This paper describes some of the issues that arise in this context, and the approaches we have taken to address them. A key goal when developing our system was to deal in a systematic manner with the various peculiarities seen in low-level systems code, and reason about the safety and correctness of code transformation s, without requiring significant deviations from the regular d evelopmental path. For example, a precondition we assumed was that no compiler or linker modifications should be required to use it and the tool should be able to process kernel binaries in the same way as it does ordinary applications. |
c4cfdcf19705f9095fb60fb2e569a9253a475f11 | Towards Context-Aware Interaction Recognition for Visual Relationship Detection | Recognizing how objects interact with each other is a crucial task in visual recognition. If we define the context of the interaction to be the objects involved, then most current methods can be categorized as either: (i) training a single classifier on the combination of the interaction and its context; or (ii) aiming to recognize the interaction independently of its explicit context. Both methods suffer limitations: the former scales poorly with the number of combinations and fails to generalize to unseen combinations, while the latter often leads to poor interaction recognition performance due to the difficulty of designing a contextindependent interaction classifier.,,To mitigate those drawbacks, this paper proposes an alternative, context-aware interaction recognition framework. The key to our method is to explicitly construct an interaction classifier which combines the context, and the interaction. The context is encoded via word2vec into a semantic space, and is used to derive a classification result for the interaction. The proposed method still builds one classifier for one interaction (as per type (ii) above), but the classifier built is adaptive to context via weights which are context dependent. The benefit of using the semantic space is that it naturally leads to zero-shot generalizations in which semantically similar contexts (subject-object pairs) can be recognized as suitable contexts for an interaction, even if they were not observed in the training set. Our method also scales with the number of interaction-context pairs since our model parameters do not increase with the number of interactions. Thus our method avoids the limitation of both approaches. We demonstrate experimentally that the proposed framework leads to improved performance for all investigated interaction representations and datasets. |
39cc0e6c1b85d052c998a1c5949fe51baa96f0c5 | Effective resource management for enhancing performance of 2D and 3D stencils on GPUs | GPUs are an attractive target for data parallel stencil computations prevalent in scientific computing and image processing applications. Many tiling schemes, such as overlapped tiling and split tiling, have been proposed in past to improve the performance of stencil computations. While effective for 2D stencils, these techniques do not achieve the desired improvements for 3D stencils due to the hardware constraints of GPU.
A major challenge in optimizing stencil computations is to effectively utilize all resources available on the GPU. In this paper we develop a tiling strategy that makes better use of resources like shared memory and register file available on the hardware. We present a systematic methodology to reason about which strategy should be employed for a given stencil and also discuss implementation choices that have a significant effect on the achieved performance. Applying these techniques to various 2D and 3D stencils gives a performance improvement of 200-400% over existing tools that target such computations. |
a98242e420179d2a080069f5a02c6603fb5cfe3d | Zero-Current Switching Switched-Capacitor Zero-Voltage-Gap Automatic Equalization System for Series Battery String | The series battery string or supercapacitor string automatic equalization system based on quasi-resonant switched-capacitor converter is presented in this paper. It realizes the zero-voltage gap between cells and allows maximum energy recovery in a series battery system or supercapacitor system. It not only inherits the advantage of conventional switched-capacitor battery cell balancing system, but also overcomes the drawback of conduction loss, switching loss, and finite voltage difference among battery cells. All switches are MOSFET and controlled by just a pair of complementary signals in synchronous trigger pattern and the resonant tanks operate alternatively between the two states of charging and discharging. Zero-current switching and zero-voltage gap are achieved in this paper. Different resonant tank designs can meet the needs of different balancing time to meet the needs of different energy storage devices. Experimental results indicate that the efficiency of the system is high exceeding 98%. The system is very suitable for balancing used in battery management system. |
dcaeb29ad3307e2bdab2218416c81cb0c4e548b2 | End-to-end Speech Recognition Using Lattice-free MMI | We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models. By end-to-end training, we mean flat-start training of a single DNN in one stage without using any previously trained models, forced alignments, or building state-tying decision trees. We use full biphones to enable context-dependent modeling without trees, and show that our end-to-end LF-MMI approach can achieve comparable results to regular LF-MMI on well-known large vocabulary tasks. We also compare with other end-to-end methods such as CTC in character-based and lexicon-free settings and show 5 to 25 percent relative reduction in word error rates on different large vocabulary tasks while using significantly smaller models. |
6b4593128ddfcbe006b51de0549596f24e724ff0 | Counting of cigarettes in cigarette packets using LabVIEW | The proposed work presents a technique for an automated count of cigarette in cigarette packets. Proposed work is based on application of image processing techniques in LabVIEW platform. An objective of the proposed work is to count the number of cigarettes in a packet. National Instrument's Smart camera is used to capture images of cigarette packets moving in packaging line and process the data to fulfill the above objective. The technique was subjected to offline testing on more than 50 number of cigarette packets and the results obtained are found to be satisfactory in all cases. |
5d7e3fb23f2a14ffdab31f18051c9b8ff573db4e | LQR, double-PID and pole placement stabilization and tracking control of single link inverted pendulum | This paper presents the dynamic behaviour of a nonlinear single link inverted pendulum-on-cart system based on Lagrange Equation. The nonlinear model linearization was presented based on Taylor series approximation. LQR, double-PID and simple pole placement control techniques were proposed for upright stabilization and tracking controls of the system. Simulations results for the various control techniques subjected to a unity magnitude pulse input torque with and without disturbance were compared. The performances of the proposed controllers were investigated based on response time specifications and level of disturbance rejection. Thus, the performance of LQR is more reliable and satisfactory. Finally, future work suggestions were made. |
15fc8ce6630616cce1681f049391bdb4e186192b | Defect Detection in Textures through the Use of Entropy as a Means for Automatically Selecting the Wavelet Decomposition Level | This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and statistical textures. Two main features are presented. One of the new features is an original use of the normalized absolute function value (NABS) calculated from the wavelet coefficients derived at various different decomposition levels in order to identify textures where the defect can be isolated by eliminating the texture pattern in the first decomposition level. The second is the use of Shannon's entropy, calculated over detail subimages, for automatic selection of the band for image reconstruction, which, unlike other techniques, such as those based on the co-occurrence matrix or on energy calculation, provides a lower decomposition level, thus avoiding excessive degradation of the image, allowing a more accurate defect segmentation. A metric analysis of the results of the proposed method with nine different thresholding algorithms determined that selecting the appropriate thresholding method is important to achieve optimum performance in defect detection. As a consequence, several different thresholding algorithms depending on the type of texture are proposed. |
29fbadeb12389a2fee4f0739cfc62c0ea9399de1 | The influence of futures markets on real time price stabilization in electricity markets | Markets can interact with power systems in ways that can render an otherwise stable market and an otherwise stable power system into an unstable overall system. This unstable system will be characterized not only by fluctuating prices that do not settle to constant values, but, more worrisome, it creates the possibility of inducing slow electromechanical oscillations if left unchecked. This will tend to happen as a result of "price chasing" on the part of suppliers that can react (and over-react) to changing system prices. This paper examines the role that futures markets may have on the clearing prices and on altering the volatility and potential instability of real time prices and generator output. |
ecfc4792299f58390d85753b60ee227b6282ccbc | Ubiquitous enterprise service adaptations based on contextual user behavior | Recent advances in mobile technologies and infrastructures have created the demand for ubiquitous access to enterprise services from mobile handheld devices. Further, with the invention of new interaction devices, the context in which the services are being used becomes an integral part of the activity carried out with the system. Traditional human–computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information captured from mobile user behavior. Instead of redesigning or adapting existing enterprise services in an ad hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of such adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to ubiquitous service adaptation, where mobile users may execute a more concise version or modified procedure of the original process according to their behavior under different contexts. The process view also serves as the key mechanism for integrating user interface views and data views. Based on this model, we analyze the design and implementation issues of some common ubiquitous access situations and show how to adapt them systematically into a context-aware application by considering the requirements of a ubiquitous enterprise information system. |
edd6b6cd62d4c3b5d288721510e579be62c941d6 | Conditional image generation using feature-matching GAN | Generative Adversarial Net is a frontier method of generative models for images, audios and videos. In this paper, we focus on conditional image generation and introduce conditional Feature-Matching Generative Adversarial Net to generate images from category labels. By visualizing state-of-art discriminative conditional generative models, we find these networks do not gain clear semantic concepts. Thus we design the loss function in the light of metric learning to measure semantic distance. The proposed model is evaluated on several well-known datasets. It is shown to be of higher perceptual quality and better diversity then existing generative models. |
7a050d2f0c83a65996e1261b52e6523f24d0bac2 | Reactance-domain ESPRIT algorithm for a hexagonally shaped seven-element ESPAR antenna | A direction-of-arrival (DoA) method that combines the reactance-domain (RD) technique and the ESPRIT algorithm is proposed for use with the 7-element electronically steerable parasitic array radiator (ESPAR) for the estimation of noncoherent sources. Simulations show that the method could resolve up to three incoming signals with an estimation performance that depends on the signal's angle of arrival. Moreover, the method is compared with the Cramer-Rao lower bound (CRB) and the MUSIC asymptotic error variance, both modified for the RD technique. Numerical comparison between this lower bound and the MUSIC algorithm confirmed that the proposed method can achieve the CRB and provide high-precision DoA estimation with a level of performance that is sufficient for many DoA finding applications. The proposed method could be demonstrated by means of experiments on DOA estimation conducted in an anechoic chamber. |
f512a4ae0f6b2d8d03c54a6405d2697a74f7256a | A quick MST-based algorithm to obtain Pathfinder networks (∞,n-1) | Network scaling algorithms such as the Pathfinder algorithm are used to prunemany different kinds of networks, including citation networks, randomnetworks, and social networks. However, this algorithm suffers from run time problems for large networks and online processing due to its O(n4) time complexity. In this article, we introduce a new alternative, the MST-Pathfinder algorithm, which will allow us to prune the original network to get its PFNET(∞, n −1) in justO(n2 · logn) time.Theunderlying idea comes from the fact that the union (superposition) of all the Minimum Spanning Trees extracted from a given network is equivalent to the PFNET resulting from the Pathfinder algorithmparameterized by a specific set of values (r = ∞ and q = n −1), those usually considered in many different applications. Although this property is well-known in the literature, it seems that no algorithm based on it has been proposed, up to now, to decrease the high computational cost of the original Pathfinder algorithm.We also present a mathematical proof of the correctness of this new alternative and test its good efficiency in two different case studies: one dedicated to the post-processing of large random graphs, and the other one to a real world case in which medium networks obtained by a cocitation analysis of the scientific domains in different countries are pruned. |
b49af9c4ab31528d37122455e4caf5fdeefec81a | Smart homes and their users: a systematic analysis and key challenges | Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home—functional, instrumental, socio-technical; (2) users and the use of the smart home—prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home—hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns—privacy and control—that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified. |
c4a3da33ac6bcc9acd962f3bbb92d2387a62aed2 | Mobile application for Indonesian medicinal plants identification using Fuzzy Local Binary Pattern and Fuzzy Color Histogram | This research proposed a new mobile application based on Android operating system for identifying Indonesian medicinal plant images based on texture and color features of digital leaf images. In the experiments we used 51 species of Indonesian medicinal plants and each species consists of 48 images, so the total images used in this research are 2,448 images. This research investigates effectiveness of the fusion between the Fuzzy Local Binary Pattern (FLBP) and the Fuzzy Color Histogram (FCH) in order to identify medicinal plants. The FLBP method is used for extracting leaf image texture. The FCH method is used for extracting leaf image color. The fusion of FLBP and FCH is done by using Product Decision Rules (PDR) method. This research used Probabilistic Neural Network (PNN) classifier for classifying medicinal plant species. The experimental results show that the fusion between FLBP and FCH can improve the average accuracy of medicinal plants identification. The accuracy of identification using fusion of FLBP and FCH is 74.51%. This application is very important to help people identifying and finding information about Indonesian medicinal plant. |
de704a0347322014abc4b3ecc27e86bdc5fac2fd | KNOWLEDGE ACQUISITION AND CYBER SICKNESS : A COMPARISON OF VR DEVICES IN VIRTUAL TOURS | SCIENCE JOURNAL 2015 | JUNE | SCIENCE JOURNAL | 613 |
b648d73edd1a533decd22eec2e7722b96746ceae | weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming | Selective weed treatment is a critical step in autonomous crop management as related to crop health and yield. However, a key challenge is reliable and accurate weed detection to minimize damage to surrounding plants. In this letter, we present an approach for dense semantic weed classification with multispectral images collected by a micro aerial vehicle (MAV). We use the recently developed encoder–decoder cascaded convolutional neural network, SegNet, that infers dense semantic classes while allowing any number of input image channels and class balancing with our sugar beet and weed datasets. To obtain training datasets, we established an experimental field with varying herbicide levels resulting in field plots containing only either crop or weed, enabling us to use the normalized difference vegetation index as a distinguishable feature for automatic ground truth generation. We train six models with different numbers of input channels and condition (fine tune) it to achieve $\sim$0.8 F1-score and 0.78 area under the curve classification metrics. For the model deployment, an embedded Graphics Processing Unit (GPU) system (Jetson TX2) is tested for MAV integration. Dataset used in this letter is released to support the community and future work. |
7d712ea3803485467a46b46b71242477560c18f0 | A Novel Differential-Fed Patch Antenna on Stepped-Impedance Resonator With Enhanced Bandwidth Under Dual-Resonance | A novel design concept to enhance the bandwidth of a differential-fed patch antenna using the dual-resonant radiation of a stepped-impedance resonator (SIR) is proposed. The SIR is composed of two distinctive portions: the radiating patch and a pair of open stubs. Initially, based on the transmission line model, the first and second odd-order radiative resonant modes, i.e., TM10 and TM30, of this SIR-typed patch antenna are extensively investigated. It is demonstrated that the frequency ratio between the dual-resonant modes can be fully controlled by the electrical length and the impedance ratios between the open stub and radiating patch. After that, the SIR-typed patch antenna is reshaped with stepped ground plane in order to increase the impedance ratio as highly required for wideband radiation. With this arrangement, these two radiative modes are merged with each other, resulting in a wide impedance bandwidth with a stable radiation pattern under dual-resonant radiation. Finally, the proposed antenna is designed, fabricated, and measured. It is verified in experiment that the impedance bandwidth (|Sdd11| <; -10 dB) of the proposed antenna has gained tremendous increment up to 10% (0.85-0.94 GHz) with two attenuation poles. Most importantly, the antenna has achieved a stable gain varying from 7.4 to 8.5 dB within the whole operating band, while keeping low-cross polarization. |
9f7b1b9d4f7dc2dcf850dcb311ecd309be380226 | Design and Analysis of a Low-Profile and Broadband Microstrip Monopolar Patch Antenna | A new microstrip monopolar patch antenna is proposed and analyzed. The antenna has a wide bandwidth and a monopole like radiation pattern. Such antenna is constructed on a circular patch antenna that is shorted concentrically with a set of conductive vias. The antenna is analyzed using a cavity model. The cavity model analysis not only distinguishes each resonating mode and gives a physical insight into each mode of the antenna, but also provides a guideline to design a broadband monopolar patch antenna that utilizes two modes (TM01 and TM02 modes). Both modes provide a monopole like radiation pattern. The proposed antenna has a simple structure with a low profile of 0.024 wavelengths, and yields a wide impedance bandwidth of 18% and a maximum gain of 6 dBi. |
1965a7d9a3eb0727c054fb235b1758c8ffbb8e22 | Circularly Polarized U-Slot Antenna | Circularly polarized single-layer U-slot microstrip patch antenna has been proposed. The suggested asymmetrical U-slot can generate the two orthogonal modes for circular polarization without chamfering any corner of the probe-fed square patch microstrip antenna. A parametric study has been carried out to investigate the effects caused by different arm lengths of the U-slot. The thickness of the foam substrate is about 8.5% of the wavelength at the operating frequency. The 3 dB axial ratio bandwidth of the antenna is 4%. Both experimental and theoretical results of the antenna have been presented and discussed. Circular polarization, printed antennas, U-slot. |
4f86fdb8312794929b9a11770fba271c5bf886fa | A Broadband Center-Fed Circular Patch-Ring Antenna With a Monopole Like Radiation Pattern | A center-fed circular microstrip patch antenna with a coupled annular ring is presented. This antenna has a low profile configuration with a monopole like radiation pattern. Compared to the center-fed circular patch antenna (CPA), the proposed antenna has a large bandwidth and similar radiation pattern. The proposed antenna is fabricated and tested. It resonates at 5.8 GHz, the corresponding impedance bandwidth and gain are 12.8% and 5.7 dBi, respectively. Very good agreement between the measurement and simulation for the return loss and radiation patterns is achieved. |
9462cd1ec2e404b22f76c88b6149d1e84683acb7 | Printed Meandering Probe-Fed Circularly Polarized Patch Antenna With Wide Bandwidth | In this letter, a wideband compact circularly polarized (CP) patch antenna is proposed. This patch antenna consists of a printed meandering probe (M-probe) and truncated patches that excite orthogonal resonant modes to generate a wideband CP operation. The stacked patch is employed to further improve the axial-ratio (AR) bandwidth to fit the 5G Wi-Fi application. The proposed antenna achieves 42.3% impedance bandwidth and 16.8% AR bandwidth, respectively. The average gain within the AR bandwidth is 6.6 dBic with less than 0.5 dB variation. This work demonstrates a bandwidth broadening technique of an M-probe fed CP patch antenna. It is the first study to investigate and exhibit the M-probe could also provide the wideband characteristics in the dielectric loaded patch antenna. The potential applications of the antenna are 5G Wi-Fi and satellite communication systems. |
c9ed18a4a52503ede1f50691ff77efdf26acedd5 | A PFC based BLDC motor drive using a Bridgeless Zeta converter | This paper deals with a PFC (Power Factor Corrected) Bridgeless Zeta converter based VSI (Voltage Source Inverter) fed BLDC (Brushless DC) motor drive. The speed control is achieved by controlling the voltage at the DC bus of VSI using a single voltage sensor. This facilitates the operation of VSI in fundamental frequency switching mode (Electronic Commutation of BLDC motor) in place of high frequency PWM (Pulse Width Modulation) switching for speed control. This leads to low switching losses in VSI and thus improves the efficiency of the drive. Moreover, a bridgeless configuration is used to reduce the conduction losses of DBR (Diode Bridge Rectifier). The bridgeless Zeta converter working in DCM (Discontinuous Conduction Mode) is used which utilizes a voltage follower approach thus requiring a single voltage sensor for speed control and PFC operation. The proposed drive is designed to operate over a wide range of speed control and under wide variation in supply voltages with high power factor and low harmonic distortion in the supply current at AC mains. An improved power quality is achieved with performance indices satisfying the international PQ (Power Quality) standards such as IEC-61000-3-2. |
d6002a6cc8b5fc2218754aed970aac91c8d8e7e9 | Discriminatively Trained Templates for 3D Object Detection: A Real Time Scalable Approach | In this paper we propose a new method for detecting multiple specific 3D objects in real time. We start from the template-based approach based on the LINE2D/LINEMOD representation introduced recently by Hinterstoisser et al., yet extend it in two ways. First, we propose to learn the templates in a discriminative fashion. We show that this can be done online during the collection of the example images, in just a few milliseconds, and has a big impact on the accuracy of the detector. Second, we propose a scheme based on cascades that speeds up detection. Since detection of an object is fast, new objects can be added with very low cost, making our approach scale well. In our experiments, we easily handle 10-30 3D objects at frame rates above 10fps using a single CPU core. We outperform the state-of-the-art both in terms of speed as well as in terms of accuracy, as validated on 3 different datasets. This holds both when using monocular color images (with LINE2D) and when using RGBD images (with LINEMOD). Moreover, we propose a challenging new dataset made of 12 objects, for future competing methods on monocular color images. |
aaf0a8925f8564e904abc46b3ad1f9aa2b120cf6 | Vector filtering for color imaging | Vector processing operations use essential spectral and spatial information to remove noise and localize microarray spots. The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool. |
89c59ac45c267a1c12b9d0ed4af88f6d6c619683 | Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach | Many applications that process social data, such as tweets, must extract entities from tweets (e.g., “Obama” and “Hawaii” in “Obama went to Hawaii”), link them to entities in a knowledge base (e.g., Wikipedia), classify tweets into a set of predefined topics, and assign descriptive tags to tweets. Few solutions exist today to solve these problems for social data, and they are limited in important ways. Further, even though several industrial systems such as OpenCalais have been deployed to solve these problems for text data, little if any has been published about them, and it is unclear if any of the systems has been tailored for social media. In this paper we describe in depth an end-to-end industrial system that solves these problems for social data. The system has been developed and used heavily in the past three years, first at Kosmix, a startup, and later at WalmartLabs. We show how our system uses a Wikipedia-based global “real-time” knowledge base that is well suited for social data, how we interleave the tasks in a synergistic fashion, how we generate and use contexts and social signals to improve task accuracy, and how we scale the system to the entire Twitter firehose. We describe experiments that show that our system outperforms current approaches. Finally we describe applications of the system at Kosmix and WalmartLabs, and lessons learned. |
0b632048208c9c6b48b636f9f7ef8a5466325488 | A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving | Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles’ driving behaviors plays a crucial role in autonomous vehicles. Most traditional driving behavior prediction models work only for a specific traffic scenario and cannot be adapted to different scenarios. In addition, priori driving knowledge was never considered sufficiently. This study proposes a novel scenario-adaptive approach to solve these problems. A novel ontology model was developed to model traffic scenarios. Continuous features of driving behavior were learned by Hidden Markov Models (HMMs). Then, a knowledge base was constructed to specify the model adaptation strategies and store priori probabilities based on the scenario’s characteristics. Finally, the target vehicle’s future behavior was predicted considering both a posteriori probabilities and a priori probabilities. The proposed approach was sufficiently evaluated with a real autonomous vehicle. The application scope of traditional models can be extended to a variety of scenarios, while the prediction performance can be improved by the consideration of priori knowledge. For lane-changing behaviors, the prediction time horizon can be extended by up to 56% (0.76 s) on average. Meanwhile, long-term prediction precision can be enhanced by over 26%. |
41d103f751d47f0c140d21c5baa4981b3d4c9a76 | Commonsense Causal Reasoning Using Millions of Personal Stories | The personal stories that people write in their Internet weblogs include a substantial amount of information about the causal relationships between everyday events. In this paper we describe our efforts to use millions of these stories for automated commonsense causal reasoning. Casting the commonsense causal reasoning problem as a Choice of Plausible Alternatives, we describe four experiments that compare various statistical and information retrieval approaches to exploit causal information in story corpora. The top performing system in these experiments uses a simple co-occurrence statistic between words in the causal antecedent and consequent, calculated as the Pointwise Mutual Information between words in a corpus of millions of personal stories. |
c9d1bcdb95aa748940b85508fd7277622f74c0a4 | Rigor in Information Systems Positivist Case Research: Current Practices | Case research has commanded respect in the information systems (IS) discipline for at least a decade. Notwithstanding the relevance and potential value of case studies, this methodological approach was once considered to be one of the least systematic. Toward the end of the 1980s, the issue of whether IS case research was rigorously conducted was first raised. Researchers from our field (e.g., Benbasat et al. 1987; Lee 1989) and from other disciplines (e.g., Eisenhardt 1989; Yin 1994) called for more rigor in case research and, through theirrecommendations, contributed to the advancement of the case study methodology. Considering these contributions, the present study seeks to determine the extent to which the field of IS has advanced in its operational use of case study method. Precisely, it investigates the level of methodological rigor in positivist IS case research conducted over the past decade. To fulfill this objective, we identified and coded 183 case articles from seven major IS journals. Evaluation attributes or criteria considered in the present review focus on three main areas, namely, design issues, data collection, and data analysis. While the level of methodological rigor has experienced modest progress with respect to some specific attributes, the overall assessed rigor is somewhat equivocal and there are still significant areas for improvement. One of the keys is to include better documentation particularly regarding issues related to the data collection and |
30584b8d5bf99e51139e7ca9a8c04637480b73ca | Design of Compact Wide Stopband Microstrip Low-pass Filter using T-shaped Resonator | In this letter, a compact microstrip low-pass filter (LPF) using T-shaped resonator with wide stopband is presented. The proposed LPF has capability to remove the eighth harmonic and a low insertion loss of 0.12 dB. The bandstop structure using stepped impendence resonator and two open-circuit stubs are used to design a wide stopband with attenuation level better than −20 dB from 3.08 up to 22 GHz. The proposed filter with −3-dB cutoff frequency of 2.68 GHz has been designed, fabricated, and measured. The operating of the LPF is investigated based on equivalent circuit model. Simulation results are verified by measurement results and excellent agreement between them is observed. |
bb9936dc85acfc794636140f02644f4f29a754c9 | On-Line Analytical Processing | On-line analytical processing (OLAP) describes an approach to decision support, which aims to extract knowledge from a data warehouse, or more specifically, from data marts. Its main idea is providing navigation through data to non-expert users, so that they are able to interactively generate ad hoc queries without the intervention of IT professionals. This name was introduced in contrast to on-line transactional processing (OLTP), so that it reflected the different requirements and characteristics between these classes of uses. The concept falls in the area of business intelligence. |
566199b865312f259d0cf694d71d6a51462e0fb8 | Mining Roles with Multiple Objectives | With the growing adoption of Role-Based Access Control (RBAC) in commercial security and identity management products, how to facilitate the process of migrating a non-RBAC system to an RBAC system has become a problem with significant business impact. Researchers have proposed to use data mining techniques to discover roles to complement the costly top-down approaches for RBAC system construction. An important problem is how to construct RBAC systems with low complexity. In this article, we define the notion of weighted structural complexity measure and propose a role mining algorithm that mines RBAC systems with low structural complexity. Another key problem that has not been adequately addressed by existing role mining approaches is how to discover roles with semantic meanings. In this article, we study the problem in two primary settings with different information availability. When the only information is user-permission relation, we propose to discover roles whose semantic meaning is based on formal concept lattices. We argue that the theory of formal concept analysis provides a solid theoretical foundation for mining roles from a user-permission relation. When user-attribute information is also available, we propose to create roles that can be explained by expressions of user-attributes. Since an expression of attributes describes a real-world concept, the corresponding role represents a real-world concept as well. Furthermore, the algorithms we propose balance the semantic guarantee of roles with system complexity. Finally, we indicate how to create a hybrid approach combining top-down candidate roles. Our experimental results demonstrate the effectiveness of our approaches. |
0f0133873e0ddf9db8e190ccf44a07249c16ba10 | Data Fusion by Matrix Factorization | For most problems in science and engineering we can obtain data sets that describe the observed system from various perspectives and record the behavior of its individual components. Heterogeneous data sets can be collectively mined by data fusion. Fusion can focus on a specific target relation and exploit directly associated data together with contextual data and data about system's constraints. In the paper we describe a data fusion approach with penalized matrix tri-factorization (DFMF) that simultaneously factorizes data matrices to reveal hidden associations. The approach can directly consider any data that can be expressed in a matrix, including those from feature-based representations, ontologies, associations and networks. We demonstrate the utility of DFMF for gene function prediction task with eleven different data sources and for prediction of pharmacologic actions by fusing six data sources. Our data fusion algorithm compares favorably to alternative data integration approaches and achieves higher accuracy than can be obtained from any single data source alone. |
34c15e94066894d92b5b0ec6817b8a246c009aaa | Cloud Service Negotiation: A Research Roadmap | Cloud services are Internet-based XaaS (X as a Service) services, where X can be hardware, software or applications. As Cloud consumers value QoS (Quality of Service), Cloud providers should make certain service level commitments in order to achieve business success. This paper argues for Cloud service negotiation. It outlines a research roadmap, reviews the state of the art, and reports our work on Cloud service negotiation. Three research problems that we formulate are QoS measurement, QoS negotiation, and QoS enforcement. To address QoS measurement, we pioneer a quality model named CLOUDQUAL for Cloud services. To address QoS negotiation, we propose a tradeoff negotiation approach for Cloud services, which can achieve a higher utility. We also give some ideas to solve QoS enforcement, and balance utility and success rate for QoS negotiation. |
08d6c0f860378a8c56b4ba7f347429970f70e3bd | Classification of brain disease in magnetic resonance images using two-stage local feature fusion | BACKGROUND
Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale.
METHODS
Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to.
RESULTS
We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block.
DISCUSSION
This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls. |
e3bb879045c5807a950047d91e65c15e7f087313 | Community Detection in Social Networks Based on Influential Nodes | Large-scale social networks emerged rapidly in recent years. Social networks have become complex networks. The structure of social networks is an important research area and has attracted much scientific interest. Community is an important structure in social networks. In this paper, we propose a community detection algorithm based on influential nodes. First, we introduce how to find influential nodes based on random walk. Then we combine the algorithm with order statistics theory to find community structure. We apply our algorithm in three classical data sets and compare to other algorithms. Our community detection algorithm is proved to be effective in the experiments. Our algorithm also has applications in data mining and recommendations. |
0414c4cc1974e6d3e69d9f2986e5bb9fb1af4701 | Natural Language Processing using NLTK and WordNet | Natural Language Processing is a theoretically motivated range of computational techniques for analysing and representing naturally occurring texts at one or more levels of linguistic analysis for the purpose of achieving human-like language processing for a range of tasks or applications [1]. To perform natural language processing a variety of tools and platform have been developed, in our case we will discuss about NLTK for Python.The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for the Python programming language[2]. It provides easy-to-use interfaces to many corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning. In this paper we discuss different approaches for natural language processing using NLTK. |
7beabda9986a546cbf4f6c66de9c9aa7ea92a7ac | Arabic Automatic Speech Recognition Enhancement | In this paper, we propose three approaches for Arabic automatic speech recognition. For pronunciation modeling, we propose a pronunciation variant generation with decision tree. For acoustic modeling, we propose the Hybrid approach to adapt the native acoustic model using another native acoustic model. Regarding the language model, we improve the language model using processed text. The experimental results show that the proposed pronunciation model approach has reduction in WER around 1%. The acoustic modeling reduce the WER by 1.2% and the adapted language modeling show reduction in WER by 1.9%. |
2a1c06ea40469064f2419df481a6e6aab7b09cdf | Driving Hotzenplotz: A Hybrid Interface for Vehicle Control Aiming to Maximize Pleasure in Highway Driving | A prerequisite to foster proliferation of automated driving is common system acceptance. However, different users groups (novice, enthusiasts) decline automation, which could be, in turn, problematic for a successful market launch. We see a feasible solution in the combination of the advantages of manual (autonomy) and automated (increased safety) driving. Hence, we've developed the Hotzenplotz interface, combining possibility-driven design with psychological user needs. A simulator study (N=30) was carried-out to assess user experience with subjective criteria (Need Scale, PANAS/-X, HEMA, AttrakDiff) and quantitative measures (driving behavior, HR/HRV) in different conditions. Our results confirm that pure AD is significantly less able to satisfy user needs compared to manual driving and make people feeling bored/out of control. In contrast, the Hotzenplotz interface has proven to reduce the negative effects of AD. Our implication is that drivers should be provided with different control options to secure acceptance and avoid deskilling. |
715250b1a76178cbc057de701524db7b2695234c | The Design and Implementation of CoGaDB: A Column-oriented GPU-accelerated DBMS | Nowadays, the performance of processors is primarily bound by a fixed energy budget, the power wall. This forces hardware vendors to optimize processors for specific tasks, which leads to an increasingly heterogeneous hardware landscape. Although efficient algorithms for modern processors such as GPUs are heavily investigated, we also need to prepare the database optimizer to handle computations on heterogeneous processors. GPUs are an interesting base for case studies, because they already offer many difficulties we will face tomorrow. In this paper, we present CoGaDB, a main-memory DBMS with built-in GPU acceleration, which is optimized for OLAP workloads. CoGaDB uses the self-tuning optimizer framework HyPE to build a hardware-oblivious optimizer, which learns cost models for database operators and efficiently distributes a workload on available processors. Furthermore, CoGaDB implements efficient algorithms on CPU and GPU and efficiently supports star joins. We show in this paper, how these novel techniques interact with each other in a single system. Our evaluation shows that CoGaDB quickly adapts to the underlying hardware by increasing the accuracy of its cost models at runtime. |
e4c98cd116c0b86387354208bc97c1dc3c79d16d | Understanding Stories with Large-Scale Common Sense | Story understanding systems need to be able to perform commonsense reasoning, specifically regarding characters’ goals and their associated actions. Some efforts have been made to form large-scale commonsense knowledge bases, but integrating that knowledge into story understanding systems remains a challenge. We have implemented the Aspire system, an application of large-scale commonsense knowledge to story understanding. Aspire extends Genesis, a rule-based story understanding system, with tens of thousands of goalrelated assertions from the commonsense semantic network ConceptNet. Aspire uses ConceptNet’s knowledge to infer plausible implicit character goals and story causal connections at a scale unprecedented in the space of story understanding. Genesis’s rule-based inference enables precise story analysis, while ConceptNet’s relatively inexact but widely applicable knowledge provides a significant breadth of coverage difficult to achieve solely using rules. Genesis uses Aspire’s inferences to answer questions about stories, and these answers were found to be plausible in a small study. Though we focus on Genesis and ConceptNet, demonstrating the value of supplementing precise reasoning systems with large-scale, scruffy commonsense knowledge is our primary contribution. |
79b4723a010c66c2f3fdcd3bd79dba1c3a3e2d28 | A comprehensive model of PMOS NBTI degradation | Negative bias temperature instability has become an important reliability concern for ultra-scaled Silicon IC technology with significant implications for both analog and digital circuit design. In this paper, we construct a comprehensive model for NBTI phenomena within the framework of the standard reaction–diffusion model. We demonstrate how to solve the reaction–diffusion equations in a way that emphasizes the physical aspects of the degradation process and allows easy generalization of the existing work. We also augment this basic reaction–diffusion model by including the temperature and field-dependence of the NBTI phenomena so that reliability projections can be made under arbitrary circuit operating conditions. 2004 Published by Elsevier Ltd. |
8e5ba7d60a4d9f425deeb3a05f3124fe6686b29a | Neural correlates of experimentally induced flow experiences | Flow refers to a positive, activity-associated, subjective experience under conditions of a perceived fit between skills and task demands. Using functional magnetic resonance perfusion imaging, we investigated the neural correlates of flow in a sample of 27 human subjects. Experimentally, in the flow condition participants worked on mental arithmetic tasks at challenging task difficulty which was automatically and continuously adjusted to individuals' skill level. Experimental settings of "boredom" and "overload" served as comparison conditions. The experience of flow was associated with relative increases in neural activity in the left anterior inferior frontal gyrus (IFG) and the left putamen. Relative decreases in neural activity were observed in the medial prefrontal cortex (MPFC) and the amygdala (AMY). Subjective ratings of the flow experience were significantly associated with changes in neural activity in the IFG, AMY, and, with trend towards significance, in the MPFC. We conclude that neural activity changes in these brain regions reflect psychological processes that map on the characteristic features of flow: coding of increased outcome probability (putamen), deeper sense of cognitive control (IFG), decreased self-referential processing (MPFC), and decreased negative arousal (AMY). |
23e4844f33adaf2e26195ffc2a7514a2e45fd33d | Discovering Structure in the Universe of Attribute Names | Recently, search engines have invested significant effort to answering entity–attribute queries from structured data, but have focused mostly on queries for frequent attributes. In parallel, several research efforts have demonstrated that there is a long tail of attributes, often thousands per class of entities, that are of interest to users. Researchers are beginning to leverage these new collections of attributes to expand the ontologies that power search engines and to recognize entity– attribute queries. Because of the sheer number of potential attributes, such tasks require us to impose some structure on this long and heavy tail of attributes. This paper introduces the problem of organizing the attributes by expressing the compositional structure of their names as a rule-based grammar. These rules offer a compact and rich semantic interpretation of multi-word attributes, while generalizing from the observed attributes to new unseen ones. The paper describes an unsupervised learning method to generate such a grammar automatically from a large set of attribute names. Experiments show that our method can discover a precise grammar over 100,000 attributes of Countries while providing a 40-fold compaction over the attribute names. Furthermore, our grammar enables us to increase the precision of attributes from 47% to more than 90% with only a minimal curation effort. Thus, our approach provides an efficient and scalable way to expand ontologies with attributes of user interest. |
025cdba37d191dc73859c51503e91b0dcf466741 | Fingerprint image enhancement using GWT and DMF | Fingerprint image enhancement is an essential preprocessing step in fingerprint recognition applications. In this paper we introduce an approach that extracts simultaneously orientation and frequency of local ridge in the fingerprint image by Gabor wavelet filter bank and use them in Gabor Filtering of image. Furthermore, we describes a robust approach to fingerprint image enhancement, which is based on integration of Gabor Filters and Directional Median Filter(DMF). In fact, Gaussian-distributed noises are reduced effectively by Gabor Filters and impulse noises by DMF. the proposed DMF not only can finish its original tasks, it can also join broken fingerprint ridges, fill out the holes of fingerprint images, smooth irregular ridges as well as remove some annoying small artifacts between ridges. Experimental results show our method to be superior to those described in the literature. |
cccb533cd14259b92ec7cd71b1d3f679ef251394 | Combining haptic human-machine interaction with predictive path planning for lane-keeping and collision avoidance systems | This paper presents a first approach for a haptic human-machine interface combined with a novel lane-keeping and collision-avoidance assistance system approach, as well as the results of a first exploration study with human test drivers. The assistance system approach is based on a potential field predictive path planning algorithm that incorporates the drivers wishes commanded by the steering wheel angle, the brake pedal or throttle, and the intended maneuver. For the design of the haptic human-machine interface the assistance torque characteristic at the handwheel is shaped and the path planning parameters are held constant. In the exploration, both driving data as well as questionnaires are evaluated. The results show good acceptance for the lane-keeping assistance while the collision avoidance assistance needs to be improved. |
fbbe5bf055f997cbd1ed1f3b72b1d630771e358e | Learning patterns of university student retention | Learning predictors for student retention is very difficult. After reviewing the literature, it is evident that there is considerable room for improvement in the current state of the art. As shown in this paper, improvements are possible if we (a) explore a wide range of learning methods; (b) take care when selecting attributes; (c) assess the efficacy of the learned theory not just by its median performance, but also by the variance in that performance; (d) study the delta of student factors between those who stay and those who are retained. Using these techniques, for the goal of predicting if students will remain for the first three years of an undergraduate degree, the following factors were found to be informative: family background and family’s social-economic status, high school GPA |
03dbbd987ea1fd5307ba5ae2f56d88e4f465b88c | Anonymizing sequential releases | An organization makes a new release as new information become available, releases a tailored view for each data request, releases sensitive information and identifying information separately. The availability of related releases sharpens the identification of individuals by a global quasi-identifier consisting of attributes from related releases. Since it is not an option to anonymize previously released data, the current release must be anonymized to ensure that a global quasi-identifier is not effective for identification. In this paper, we study the sequential anonymization problem under this assumption. A key question is how to anonymize the current release so that it cannot be linked to previous releases yet remains useful for its own release purpose. We introduce the lossy join, a negative property in relational database design, as a way to hide the join relationship among releases, and propose a scalable and practical solution. |
3dfce4601c3f413605399267b3314b90dc4b3362 | Protecting Respondents' Identities in Microdata Release | ÐToday's globally networked society places great demand on the dissemination and sharing of information. While in the past released information was mostly in tabular and statistical form, many situations call today for the release of specific data (microdata). In order to protect the anonymity of the entities (called respondents) to which information refers, data holders often remove or encrypt explicit identifiers such as names, addresses, and phone numbers. Deidentifying data, however, provides no guarantee of anonymity. Released information often contains other data, such as race, birth date, sex, and ZIP code, that can be linked to publicly available information to reidentify respondents and inferring information that was not intended for disclosure. In this paper we address the problem of releasing microdata while safeguarding the anonymity of the respondents to which the data refer. The approach is based on the definition of k-anonymity. A table provides k-anonymity if attempts to link explicitly identifying information to its content map the information to at least k entities. We illustrate how k-anonymity can be provided without compromising the integrity (or truthfulness) of the information released by using generalization and suppression techniques. We introduce the concept of minimal generalization that captures the property of the release process not to distort the data more than needed to achieve k-anonymity, and present an algorithm for the computation of such a generalization. We also discuss possible preference policies to choose among different minimal |
5c15b11610d7c3ee8d6d99846c276795c072eec3 | Generalizing Data to Provide Anonymity when Disclosing Information (Abstract) | The proliferation of information on the Internet and access to fast computers with large storage capacities has increased the volume of information collected and disseminated about individuals. The existence os these other data sources makes it much easier to re-identify individuals whose private information is released in data believed to be anonymous. At the same time, increasing demands are made on organizations to release individualized data rather than aggregate statistical information. Even when explicit identi ers, such as name and phone number, are removed or encrypted when releasing individualized data, other characteristic data, which we term quasi-identi ers, can exist which allow the data recipient to re-identify individuals to whom the data refer. In this paper, we provide a computational disclosure technique for releasing information from a private table such that the identity of any individual to whom the released data refer cannot be de nitively recognized. Our approach protects against linking to other data. It is based on the concepts of generalization, by which stored values can be replaced with semantically consistent and truthful but less precise alternatives, and of k-anonymity . A table is said to provide k-anonymity when the contained data do not allow the recipient to associate the released information to a set of individuals smaller than k. We introduce the notions of generalized table and of minimal generalization of a table with respect to a k-anonymity requirement. As an optimization problem, the objective is to minimally distort the data while providing adequate protection. We describe an algorithm that, given a table, e ciently computes a preferred minimal generalization to provide anonymity. |
9492fb8d3b3ce09451fc1df46d5e3c200095f5eb | Bottom-Up Generalization : A Data Mining Solution to Privacy Protection | In recent years, privacy-preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. This paper investigates data mining as a technique for masking data; therefore, termed data mining based privacy protection. This approach incorporates partially the requirement of a targeted data mining task into the process of masking data so that essential structure is preserved in the masked data. The following privacy problem is considered in this paper: a data holder wants to release a version of data for building classification models, but wants to protect against linking the released data to an external source for inferring sensitive information. An iterative bottom-up generalization is adapted from data mining to generalize the data. The generalized data remains useful to classification but becomes difficult to link to other sources. The generalization space is specified by a hierarchical structure of generalizations. A key is identifying the best generalization to climb up the hierarchy at each iteration. |
b30706600c01e23e11b303842fe548d62bf3ecf8 | M-invariance: towards privacy preserving re-publication of dynamic datasets | The previous literature of privacy preserving data publication has focused on performing "one-time" releases. Specifically, none of the existing solutions supports re-publication of the microdata, after it has been updated with insertions <u>and</u> deletions. This is a serious drawback, because currently a publisher cannot provide researchers with the most recent dataset continuously.
This paper remedies the drawback. First, we reveal the characteristics of the re-publication problem that invalidate the conventional approaches leveraging k-anonymity and l-diversity. Based on rigorous theoretical analysis, we develop a new generalization principle m-invariance that effectively limits the risk of privacy disclosure in re-publication. We accompany the principle with an algorithm, which computes privacy-guarded relations that permit retrieval of accurate aggregate information about the original microdata. Our theoretical results are confirmed by extensive experiments with real data. |
43d7f7a090630db3ed0d7fca9d649c8562aeaaa9 | Evaluating Sketchiness as a Visual Variable for the Depiction of Qualitative Uncertainty | We report on results of a series of user studies on the perception of four visual variables that are commonly used in the literature to depict uncertainty. To the best of our knowledge, we provide the first formal evaluation of the use of these variables to facilitate an easier reading of uncertainty in visualizations that rely on line graphical primitives. In addition to blur, dashing and grayscale, we investigate the use of `sketchiness' as a visual variable because it conveys visual impreciseness that may be associated with data quality. Inspired by work in non-photorealistic rendering and by the features of hand-drawn lines, we generate line trajectories that resemble hand-drawn strokes of various levels of proficiency-ranging from child to adult strokes-where the amount of perturbations in the line corresponds to the level of uncertainty in the data. Our results show that sketchiness is a viable alternative for the visualization of uncertainty in lines and is as intuitive as blur; although people subjectively prefer dashing style over blur, grayscale and sketchiness. We discuss advantages and limitations of each technique and conclude with design considerations on how to deploy these visual variables to effectively depict various levels of uncertainty for line marks. |
99aba9948302a8bd2cdf46a809a59e34d1b57d86 | An Architecture for Local Energy Generation, Distribution, and Sharing | The United States electricity grid faces significant problems resulting from fundamental design principles that limit its ability to handle the key energy challenges of the 21st century. We propose an innovative electric power architecture, rooted in lessons learned from the Internet and microgrids, which addresses these problems while interfacing gracefully into the current grid to allow for non-disruptive incremental adoption. Such a system, which we term a "Local" grid, is controlled by intelligent power switches (IPS), and can consist of loads, energy sources, and energy storage. The desired result of the proposed architecture is to produce a grid network designed for distributed renewable energy, prevalent energy storage, and stable autonomous systems. We will describe organizing principles of such a system that ensure well-behaved operation, such as requirements for communication and energy transfer protocols, regulation and control schemes, and market-based rules of operation. |
30b32f4a6341b5809428df1271bdb707f2418362 | A Sequential Neural Encoder With Latent Structured Description for Modeling Sentences | In this paper, we propose a sequential neural encoder with latent structured description SNELSD for modeling sentences. This model introduces latent chunk-level representations into conventional sequential neural encoders, i.e., recurrent neural networks with long short-term memory LSTM units, to consider the compositionality of languages in semantic modeling. An SNELSD model has a hierarchical structure that includes a detection layer and a description layer. The detection layer predicts the boundaries of latent word chunks in an input sentence and derives a chunk-level vector for each word. The description layer utilizes modified LSTM units to process these chunk-level vectors in a recurrent manner and produces sequential encoding outputs. These output vectors are further concatenated with word vectors or the outputs of a chain LSTM encoder to obtain the final sentence representation. All the model parameters are learned in an end-to-end manner without a dependency on additional text chunking or syntax parsing. A natural language inference task and a sentiment analysis task are adopted to evaluate the performance of our proposed model. The experimental results demonstrate the effectiveness of the proposed SNELSD model on exploring task-dependent chunking patterns during the semantic modeling of sentences. Furthermore, the proposed method achieves better performance than conventional chain LSTMs and tree-structured LSTMs on both tasks. |
36cd10d9afacdc26a019d44ff3d39a8cf3fd4a9a | Advanced Gate Drive Unit With Closed-Loop $di_{{C}}/dt$ Control | This paper describes the design and the experimental investigation of a gate drive unit with closed-loop control of the collector current slope diC/dt for multichip insulated-gate bipolar transistors (IGBTs). Compared to a pure resistive gate drive, the proposed diC/dt control offers the ability to adjust the collector current slope freely which helps to find an optimized relation between switching losses and secure operation of the freewheeling diode for every type of IGBT. Based on the description of IGBT's switching behavior, the design and the realization of the gate drive are presented. The test setup and the comparison of switching tests with and without the proposed diC/dt control are discussed. |
efa2be90d7f48e11da39c3ed3fa14579fd367f9c | 3-Dimensional Localization via RFID Tag Array | In this paper, we propose 3DLoc, which performs 3-dimensional localization on the tagged objects by using the RFID tag arrays. 3DLoc deploys three arrays of RFID tags on three mutually orthogonal surfaces of each object. When performing 3D localization, 3DLoc continuously moves the RFID antenna and scans the tagged objects in a 2-dimensional space right in front of the tagged objects. It then estimates the object's 3D position according to the phases from the tag arrays. By referring to the fixed layout of the tag array, we use Angle of Arrival-based schemes to accurately estimate the tagged objects' orientation and 3D coordinates in the 3D space. To suppress the localization errors caused by the multipath effect, we use the linear relationship of the AoA parameters to remove the unexpected outliers from the estimated results. We have implemented a prototype system and evaluated the actual performance in the real complex environment. The experimental results show that 3DLoc achieves the mean accuracy of 10cm in free space and 15.3cm in the multipath environment for the tagged object. |
3d676791081e7b16a4ead9924fc03bac587d181d | Inductive Learning of Answer Set Programs from Noisy Examples | In recent years, non-monotonic Inductive Logic Programming has received growing interest. Specifically, several new learning frameworks and algorithms have been introduced for learning under the answer set semantics, allowing the learning of common-sense knowledge involving defaults and exceptions, which are essential aspects of human reasoning. In this paper, we present a noise-tolerant generalisation of the learning from answer sets framework. We evaluate our ILASP3 system, both on synthetic and on real datasets, represented in the new framework. In particular, we show that on many of the datasets ILASP3 achieves a higher accuracy than other ILP systems that have previously been applied to the datasets, including a recently proposed differentiable learning framework. |
7d46c3648f76b5542d8ecd582f01f155e6b248d5 | On Formal and Cognitive Semantics for Semantic Computing | Semantics is the meaning of symbols, notations, concepts, functions, and behaviors, as well as their relations that can be deduced onto a set of predefined entities and/or known concepts. Semantic computing is an emerging computational methodology that models and implements computational structures and behaviors at semantic or knowledge level beyond that of symbolic data. In semantic computing, formal semantics can be classified into the categories of to be, to have, and to do semantics. This paper presents a comprehensive survey of formal and cognitive semantics for semantic computing in the fields of computational linguistics, software science, computational intelligence, cognitive computing, and denotational mathematics. A set of novel formal semantics, such as deductive semantics, concept-algebra-based semantics, and visual semantics, is introduced that forms a theoretical and cognitive foundation for semantic computing. Applications of formal semantics in semantic computing are presented in case studies on semantic cognition of natural languages, semantic analyses of computing behaviors, behavioral semantics of human cognitive processes, and visual semantic algebra for image and visual object manipulations. |
927aa1bd7c0e122ae77224e92821f2eaafc96cf9 | GENDER RECOGNITION FROM FACES USING BANDLET TRANSFORMATION | Gender Recognition is important in different commercial and law enforcement applications. In this paper we have proposed a gender recognition system through facial images. We have used a different technique that involves Bandlet Transform instead of previously used Wavelet Transform, which is a multi-resolution technique and more efficiently provides the edges of images, and then mean is combined to create the feature vectors of the images. To classify the images for gender, we have used fuzzy c mean clustering. Experimental results have shown that average 97.1% accuracy have been achieved using this technique when SUMS database was used and 93.3% was achieved when FERET database was used. Keywords----Bandlet, Gender Recognition, Fuzzy C-mean, Multi Resolution. |
86cd8da6c6b35d99b75aaaaf7be55c78a31948eb | Evolution of the internal fixation of long bone fractures. The scientific basis of biological internal fixation: choosing a new balance between stability and biology. | The advent of 'biological internal fixation' is an important development in the surgical management of fractures. Locked nailing has demonstrated that flexible fixation without precise reduction results in reliable healing. While external fixators are mainly used today to provide temporary fixation in fractures after severe injury, the internal fixator offers flexible fixation, maintaining the advantages of the external fixator but allowing long-term treatment. The internal fixator resembles a plate but functions differently. It is based on pure splinting rather than compression. The resulting flexible stabilisation induces the formation of callus. With the use of locked threaded bolts, the application of the internal fixator foregoes the need of adaptation of the shape of the splint to that of the bone during surgery. Thus, it is possible to apply the internal fixator as a minimally invasive percutaneous osteosynthesis (MIPO). Minimal surgical trauma and flexible fixation allow prompt healing when the blood supply to bone is maintained or can be restored early. The scientific basis of the fixation and function of these new implants has been reviewed. The biomechanical aspects principally address the degree of instability which may be tolerated by fracture healing under different biological conditions. Fractures may heal spontaneously in spite of gross instability while minimal, even non-visible, instability may be deleterious for rigidly fixed small fracture gaps. The theory of strain offers an explanation for the maximum instability which will be tolerated and the minimal degree required for induction of callus formation. The biological aspects of damage to the blood supply, necrosis and temporary porosity explain the importance of avoiding extensive contact of the implant with bone. The phenomenon of bone loss and stress protection has a biological rather than a mechanical explanation. The same mechanism of necrosis-induced internal remodelling may explain the basic process of direct healing. |
59ae5541e1dc71ff33b4b6e14cbbc5c3d46fc506 | A Survey on Clustering Algorithms for Wireless Sensor Networks | A wireless sensor network (WSN)consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms news's and highlights the challenges in clustering. |
ce7f81e898f1c78468df2480294806864899549e | 80ºC, 50-Gb/s Directly Modulated InGaAlAs BH-DFB Lasers | Direct modulation at 50 Gb/s of 1.3-μm InGaAlAs DFB lasers operating at up to 80°C was experimentally demonstrated by using a ridge-shaped buried heterostructure. |
c955e319595b8ae051fe18f193490ba56c4f0254 | Platform-as-a-Service (PaaS): The Next Hype of Cloud Computing | Cloud Computing is expected to become the driving force of information technology to revolutionize the future. Presently number of companies is trying to adopt this new technology either as service providers, enablers or vendors. In this way the cloud market is estimated be likely to emerge at a remarkable rate. Under the whole cloud umbrella, PaaS seems to have a relatively small market share. However, it is expected to offer much more as it is compared with its counterparts SaaS and IaaS. This paper is aimed to assess and analyze the future of PaaS technology. Year 2015 named as “the year of PaaS”. It means that PaaS technology has established strong roots and ready to hit the market with better technology services. This research will discuss future PaaS market trends, growth and business competitors. In the current dynamic era, several companies in the market are offering PaaS services. This research will also outline some of the top service providers (proprietary & open source) to discuss their current technology status and present a futuristic look into their services and business strategies. Analysis of the present and future PaaS technology infrastructure will also be a major discussion in this paper. |
e1a7cf4e4760bb580dd67255fbe872bac33ae28b | Hybrid CMOS/memristor circuits | This is a brief review of recent work on the prospective hybrid CMOS/memristor circuits. Such hybrids combine the flexibility, reliability and high functionality of the CMOS subsystem with very high density of nanoscale thin film resistance switching devices operating on different physical principles. Simulation and initial experimental results demonstrate that performance of CMOS/memristor circuits for several important applications is well beyond scaling limits of conventional VLSI paradigm. |
91d513af1f667f64c9afc55ea1f45b0be7ba08d4 | Automatic Face Image Quality Prediction | Face image quality can be defined as a measure of the utility of a face image to automatic face recognition. In this work, we propose (and compare) two methods for automatic face image quality based on target face quality values from (i) human assessments of face image quality (matcherindependent), and (ii) quality values computed from similarity scores (matcher-dependent). A support vector regression model trained on face features extracted using a deep convolutional neural network (ConvNet) is used to predict the quality of a face image. The proposed methods are evaluated on two unconstrained face image databases, LFW and IJB-A, which both contain facial variations with multiple quality factors. Evaluation of the proposed automatic face image quality measures shows we are able to reduce the FNMR at 1% FMR by at least 13% for two face matchers (a COTS matcher and a ConvNet matcher) by using the proposed face quality to select subsets of face images and video frames for matching templates (i.e., multiple faces per subject) in the IJB-A protocol. To our knowledge, this is the first work to utilize human assessments of face image quality in designing a predictor of unconstrained face quality that is shown to be effective in cross-database evaluation. |
2e3522d8d9c30f34e18161246c2f6dac7a9ae04d | The Neural Architecture of the Language Comprehension Network: Converging Evidence from Lesion and Connectivity Analyses | While traditional models of language comprehension have focused on the left posterior temporal cortex as the neurological basis for language comprehension, lesion and functional imaging studies indicate the involvement of an extensive network of cortical regions. However, the full extent of this network and the white matter pathways that contribute to it remain to be characterized. In an earlier voxel-based lesion-symptom mapping analysis of data from aphasic patients (Dronkers et al., 2004), several brain regions in the left hemisphere were found to be critical for language comprehension: the left posterior middle temporal gyrus, the anterior part of Brodmann's area 22 in the superior temporal gyrus (anterior STG/BA22), the posterior superior temporal sulcus (STS) extending into Brodmann's area 39 (STS/BA39), the orbital part of the inferior frontal gyrus (BA47), and the middle frontal gyrus (BA46). Here, we investigated the white matter pathways associated with these regions using diffusion tensor imaging from healthy subjects. We also used resting-state functional magnetic resonance imaging data to assess the functional connectivity profiles of these regions. Fiber tractography and functional connectivity analyses indicated that the left MTG, anterior STG/BA22, STS/BA39, and BA47 are part of a richly interconnected network that extends to additional frontal, parietal, and temporal regions in the two hemispheres. The inferior occipito-frontal fasciculus, the arcuate fasciculus, and the middle and inferior longitudinal fasciculi, as well as transcallosal projections via the tapetum were found to be the most prominent white matter pathways bridging the regions important for language comprehension. The left MTG showed a particularly extensive structural and functional connectivity pattern which is consistent with the severity of the impairments associated with MTG lesions and which suggests a central role for this region in language comprehension. |
a58fe54d2677fb01533c4dc2d8ef958a2cb921cb | Distribution of Eigenvalues for 2x2 MIMO Channel Capacity Based on Indoor Measurements | Based on the non line-of-sight (NLOS) indoor measurements performed in the corridors on the third floor of the Electronics and Telecommunications Research Institute (ETRI) building in Daejeon city, Republic of Korea, we investigated the distribution of the eigenvalues of HH*, where H denotes a 2×2 multiple-input multiple-output (MIMO) channel matrix. Using the observation that the distribution of the measured eigenvalues matches well with the Gamma distribution, we propose a model of eigenvalues as Gamma distributed random variables that prominently feature both transmitting and receiving correlations. Using the model with positive integer k_i, i=1, 2, which is the shape parameter of a Gamma distribution, we derive the closed-form ergodic capacity of the 2×2 MIMO channel. Validation results show that the proposed model enables the evaluation of the outage and ergodic capacities of the correlated 2×2 MIMO channel in the NLOS indoor corridor environment. |
d4b29432c3e7bd4e2d06935169c91f781f441160 | Speech recognition of Malayalam numbers | Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task. |
517a461a8839733e34c9025154de3d6275543642 | Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval | We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics of a query topic. In such a problem, the utility of a document in a ranking is dependent on other documents in the ranking, violating the assumption of independent relevance which is assumed in most traditional retrieval methods. Subtopic retrieval poses challenges for evaluating performance, as well as for developing effective algorithms. We propose a framework for evaluating subtopic retrieval which generalizes the traditional precision and recall metrics by accounting for intrinsic topic difficulty as well as redundancy in documents. We propose and systematically evaluate several methods for performing subtopic retrieval using statistical language models and a maximal marginal relevance (MMR) ranking strategy. A mixture model combined with query likelihood relevance ranking is shown to modestly outperform a baseline relevance ranking on a data set used in the TREC interactive track. |
6b3abd1a6bf9c9564147cfda946c447955d01804 | Kaleido: You Can Watch It But Cannot Record It | Recently a number of systems have been developed to implement and improve the visual communication over screen-camera links. In this paper we study an opposite problem: how to prevent unauthorized users from videotaping a video played on a screen, such as in a theater, while do not affect the viewing experience of legitimate audiences. We propose and develop a light-weight hardware-free system, called Kaleido, that ensures these properties by taking advantage of the limited disparities between the screen-eye channel and the screen-camera channel. Kaleido does not require any extra hardware and is purely based on re-encoding the original video frame into multiple frames used for displaying. We extensively test our system Kaleido using a variety of smartphone cameras. Our experiments confirm that Kaleido preserves the high-quality screen-eye channel while reducing the secondary screen-camera channel quality significantly. |
528407a9c5b41f81366bbe5cf8058dadcb139fea | A new design of XOR-XNOR gates for low power application | XOR and XNOR gate plays an important role in digital systems including arithmetic and encryption circuits. This paper proposes a combination of XOR-XNOR gate using 6-transistors for low power applications. Comparison between a best existing XOR-XNOR have been done by simulating the proposed and other design using 65nm CMOS technology in Cadence environment. The simulation results demonstrate the delay, power consumption and power-delay product (PDP) at different supply voltages ranging from 0.6V to 1.2V. The results show that the proposed design has lower power dissipation and has a full voltage swing. |
17580101d22476be5ad1655abb48d967c78a3875 | Twenty-Five Years of Research on Women Farmers in Africa : Lessons and Implications for Agricultural Research Institutions with an Annotated Bibliography | .................................................................................................................... iv Acknowledgments ...................................................................................................... iv Introduction ............................................................................................................... 1 Labor ..........................................................................................................................2 Gender Division of Labor .................................................................................... 2 Household Labor Availability ............................................................................... 6 Agricultural Labor Markets .................................................................................. 8 Conclusions: Labor and Gender .......................................................................... 9 Land ........................................................................................................................ 10 Access to Land ................................................................................................... 10 Security of Land ................................................................................................ 11 Changing Access to Land ................................................................................... 11 Access to Other Inputs .............................................................................................. 12 Access to Credit ................................................................................................. 13 Access to Fertilizer ............................................................................................. 14 Access to Extension and Information ................................................................. 15 Access to Mechanization .................................................................................... 16 Gender Issues in Access to Inputs: Summary...................................................... 16 Outputs .................................................................................................................... 17 Household Decision-Making .................................................................................... 18 Cooperative Bargaining and Collective Models .................................................. 19 Noncooperative Bargaining Models ................................................................... 19 Conclusions .............................................................................................................. 21 References ................................................................................................................. 23 Annotated Bibliography ............................................................................................ 27 |
205917e8e885b3c2c6c31c90f9de7f411a24ec22 | Sensor Based PUF IoT Authentication Model for a Smart Home with Private Blockchain | With ubiquitous adoption of connected sensors, actuators and smart devices are finding inroads into daily life. Internet of Things (IoT) authentication is rapidly transforming from classical cryptographic user-centric knowledge based approaches to device signature based automated methodologies to corroborate identity between claimant and a verifier. Physical Unclonable Function (PUF) based IoT authentication mechanisms are gaining widespread interest as users are required to access IoT devices in real time while also expecting execution of sensitive (even physical) IoT actions immediately. This paper, delineates combination of BlockChain and Sensor based PUF authentication mechanism for solving real-time but non-repudiable access to IoT devices in a Smart Home by utilizing a mining less consensus mechanism for the provision of immutable assurance to users' and IoT devices' transactions i.e. commands, status alerts, actions etc. |
112f07f90d4395623a51725e90bf9d91b89e559a | Defending the morality of violent video games | The effect of violent video games is among the most widely discussed topics in media studies, and for good reason. These games are immensely popular, but many seem morally objectionable. Critics attack them for a number of reasons ranging from their capacity to teach players weapons skills to their ability to directly cause violent actions. This essay shows that many of these criticisms are misguided. Theoretical and empirical arguments against violent video games often suffer from a number of significant shortcomings that make them ineffective. This essay argues that video games are defensible from the perspective of Kantian, Aristotelian, and utilitarian moral theories. |
cdbb15ee448ee4dc6db16a540a40fbb035d1f4ca | Education-specific Tag Recommendation in CQA Systems | Systems for Community Question Answering (CQA) are well-known on the open web (e.g. Stack Overflow or Quora). They have been recently adopted also for use in educational domain (mostly in MOOCs) to mediate communication between students and teachers. As students are only novices in topics they learn about, they may need various scaffoldings to achieve effective question answering. In this work, we focus specifically on automatic recommendation of tags classifying students' questions. We propose a novel method that can automatically analyze a text of a question and suggest appropriate tags to an asker. The method takes specifics of educational domain into consideration by a two-step recommendation process in which tags reflecting course structure are recommended at first and consequently supplemented with additional related tags.
Evaluation of the method on data from CS50 MOOC at Stack Exchange platform showed that the proposed method achieved higher performance in comparison with a baseline method (tag recommendation without taking educational specifics into account). |
598caa7f431930892a78f1083453b1c0ba29e725 | Teaching a Machine to Read Maps With Deep Reinforcement Learning | The ability to use a 2D map to navigate a complex 3D environment is quite remarkable, and even difficult for many humans. Localization and navigation is also an important problem in domains such as robotics, and has recently become a focus of the deep reinforcement learning community. In this paper we teach a reinforcement learning agent to read a map in order to find the shortest way out of a random maze it has never seen before. Our system combines several state-of-theart methods such as A3C and incorporates novel elements such as a recurrent localization cell. Our agent learns to localize itself based on 3D first person images and an approximate orientation angle. The agent generalizes well to bigger mazes, showing that it learned useful localization and naviga- |
13082af1fd6bb9bfe63e73cf007de1655b7f9ae0 | Machine learning in automated text categorization | The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert labor power, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely, document representation, classifier construction, and classifier evaluation. |
6eb69624732a589e91816cc7722be0b0cdd28767 | Discovering actionable patterns in event data | Applications such as those for systems management and intrusion detection employ an automated real-time operation system in which sensor data are collected and processed in real time. Although such a system effectively reduces the need for operation staff, it requires constructing and maintaining correlation rules. Currently, rule construction requires experts to identify problem patterns, a process that is timeconsuming and error-prone. In this paper, we propose reducing this burden by mining historical data that are readily available. Specifically, we first present efficient algorithms to mine three types of important patterns from historical event data: event bursts, periodic patterns, and mutually dependent patterns. We then discuss a framework for efficiently mining events that have multiple attributes. Last, we present Event Correlation Constructor—a tool that validates and extends correlation knowledge. |
cd866d4510e397dbc18156f8d840d7745943cc1a | A tutorial on hidden Markov models and selected applications in speech recognition |