The Guidelines for Use of Climate Scenarios Developed from Statistical Downscaling Methods constitutes " Supporting material " of the Intergovernmental Panel on Climate Change (as defined in the Procedures for the Preparation, Review, Acceptance, Adoption, Approval, and Publication of IPCC Reports). The Guidelines were prepared for consideration by the IPCC at the request of its Task Group on Data and Scenario Support for Impacts and Climate Analysis (TGICA). This supporting material has not been subject to the formal intergovernmental IPCC review processes. Eduardo Zorito provided additional materials and feedback that were incorporated by June 2003. Revisions were made in the light of comments received from Elaine Barrow and John Mitchell in November 2003 – most notably the inclusion of a worked case study. Further comments were received from Penny Whetton and Steven Charles in February 2004.


title: Extracting Data from NoSQL Databases

text: Businesses and organizations today generate increasing volumes of data. Being able to analyze and visualize this data to find trends that can be used as input when making business decisions is an important factor for competitive advantage. Spotfire is a software platform for doing this. Spotfire uses a tabular data model similar to the relational model used in relational database management systems (RDBMSs), which are commonly used by companies for storing data. Extraction and import of data from RDBMSs to Spotfire is generally a simple task. In recent years, because of changing application requirements, new types of databases under the general term NoSQL have become popular. NoSQL databases differ from RDBMSs mainly in that they use non-relational data models, lack explicit schemas and scale horizontally. Some of these features cause problems for applications like Spotfire when extracting and importing data. This thesis investigates how these problems can be solved, thus enabling support for NoSQL databases in Spotfire. The approach and conclusions are valid for any application that interacts with databases in a similar way as Spotfire. General solutions for supporting NoSQL databases are suggested. Also, two concrete tools for importing data from Cassandra and Neo4j that have been implemented in the Spotfire platform are described. The presented solutions comprise a data model mapping from the NoSQL system to Spotfire tables, sampling and possibly clustering for finding schemas, and an extraction mechanism tailored to the particular system’s query interface. The suggested solutions are not claimed to be complete. Rather, the work in this thesis can serve as a starting point for more thorough investigations or as a basis for something that can be extended.


title: Ontologies in biology: design, applications and future challenges

text: Biological knowledge is inherently complex and so cannot readily be integrated into existing databases of molecular (for example, sequence) data. An ontology is a formal way of representing knowledge in which concepts are described both by their meaning and their relationship to each other. Unique identifiers that are associated with each concept in biological ontologies (bio-ontologies) can be used for linking to and querying molecular databases. This article reviews the principal bio-ontologies and the current issues in their design and development: these include the ability to query across databases and the problems of constructing ontologies that describe complex knowledge, such as phenotypes.


title: A SIFT-Based Forensic Method for Copy–Move Attack Detection and Transformation Recovery

text: One of the principal problems in image forensics is determining if a particular image is authentic or not. This can be a crucial task when images are used as basic evidence to influence judgment like, for example, in a court of law. To carry out such forensic analysis, various technological instruments have been developed in the literature. In this paper, the problem of detecting if an image has been forged is investigated; in particular, attention has been paid to the case in which an area of an image is copied and then pasted onto another zone to create a duplication or to cancel something that was awkward. Generally, to adapt the image patch to the new context a geometric transformation is needed. To detect such modifications, a novel methodology based on scale invariant features transform (SIFT) is proposed. Such a method allows us to both understand if a copy-move attack has occurred and, furthermore, to recover the geometric transformation used to perform cloning. Extensive experimental results are presented to confirm that the technique is able to precisely individuate the altered area and, in addition, to estimate the geometric transformation parameters with high reliability. The method also deals with multiple cloning.


title: Internet self-efficacy and electronic service acceptance

text: Internet self-efficacy (ISE), or the beliefs in one’s capabilities to organize and execute courses of Internet actions required to produce given attainments, is a potentially important factor to explain the consumers’ decisions in e-commerce use, such as eservice. In this study, we introduce two types of ISE (i.e., general Internet self-efficacy and Web-specific self-efficacy) as new factors that reflect the user’s behavioral control beliefs in e-service acceptance. Using these two constructs as behavioral control factors, we extend and empirically validate the Theory of Planned Behavior (TPB) for the World Wide Web (WWW) context. D 2003 Elsevier B.V. All rights reserved.


title: Corrosion Study and Intermetallics Formation in Gold and Copper Wire Bonding in Microelectronics Packaging

text: A comparison study on the reliability of gold (Au) and copper (Cu) wire bonding is conducted to determine their corrosion and oxidation behavior in different environmental conditions. The corrosion and oxidation behaviors of Au and Cu wire bonding are determined through soaking in sodium chloride (NaCl) solution and high temperature storage (HTS) at 175 °C, 200 °C and 225 °C. Galvanic corrosion is more intense in Cu wire bonding as compared to Au wire bonding in NaCl solution due to the minimal formation of intermetallics in the former. At all three HTS annealing temperatures, the rate of Cu-Al intermetallic formation is found to be three to five times slower than Au-Al intermetallics. The faster intermetallic growth rate and lower activation energy found in this work for both Au/Al and Cu/Al as compared to literature could be due to the thicker Al pad metallization which removed the rate-determining step in previous studies due to deficit in Al material.


title: Introducing teachers to computational thinking using unplugged storytelling

text: Many countries are introducing new school computing syllabuses that make programming and computational thinking core components. However, many of the teachers involved have major knowledge, skill and pedagogy gaps. We have explored the effectiveness of using 'unplugged' methods (constructivist, often kinaesthetic, activities away from computers) with contextually rich storytelling to introduce teachers to these topics in a non-threatening way. We describe the approach we have used in workshops for teachers and its survey based evaluation. Teachers were highly positive that the approach was inspiring, confidence building and gave them a greater understanding of the concepts involved, as well as giving practical teaching techniques that they would use.


title: Sustainable Power Supply Solutions for Off-Grid Base Stations

text: The telecommunication sector plays a significant role in shaping the global economy and the way people share information and knowledge. At present, the telecommunication sector is liable for its energy consumption and the amount of emissions it emits in the environment. In the context of off-grid telecommunication applications, offgrid base stations (BSs) are commonly used due to their ability to provide radio coverage over a wide geographic area. However, in the past, the off-grid BSs usually relied on emission-intensive power supply solutions such as diesel generators. In this review paper, various types of solutions (including, in particular, the sustainable solutions) for powering BSs are discussed. The key aspects in designing an ideal power supply solution are reviewed, and these mainly include the pre-feasibility study and the thermal management of BSs, which comprise heating and cooling of the BS shelter/cabinets and BS electronic equipment and power supply components. The sizing and optimization approaches used to design the BSs’ power supply systems as well as the operational and control strategies adopted to manage the power supply systems are also reviewed in this paper.


title: On Exploiting Dynamic Execution Patterns for Workload Offloading in Mobile Cloud Applications

text: Mobile Cloud Computing (MCC) bridges the gap between limited capabilities of mobile devices and the increasing users' demand of mobile multimedia applications, by offloading the computational workloads from local devices to the remote cloud. Current MCC research focuses on making offloading decisions over different methods of a MCC application, but may inappropriately increase the energy consumption if having transmitted a large amount of program states over expensive wireless channels. Limited research has been done on avoiding such energy waste by exploiting the dynamic patterns of applications' run-time execution for workload offloading. In this paper, we adaptively offload the local computational workload with respect to the run-time application dynamics. Our basic idea is to formulate the dynamic executions of user applications using a semi-Markov model, and to further make offloading decisions based on probabilistic estimations of the offloading operation's energy saving. Such estimation is motivated by experimental investigations over practical smart phone applications, and then builds on analytical modeling of methods' execution times and offloading expenses. Systematic evaluations show that our scheme significantly improves the efficiency of workload offloading compared to existing schemes over various smart phone applications.


title: : Past , Present , Future

text: We thank Steve Burks, Dick Thaler, and especially Matthew Rabin (who collaborated during part of the process) for helpful comments.


title: InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

text: This paper describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information between a small subset of the latent variables and the observation. We derive a lower bound of the mutual information objective that can be optimized efficiently. Specifically, InfoGAN successfully disentangles writing styles from digit shapes on the MNIST dataset, pose from lighting of 3D rendered images, and background digits from the central digit on the SVHN dataset. It also discovers visual concepts that include hair styles, presence/absence of eyeglasses, and emotions on the CelebA face dataset. Experiments show that InfoGAN learns interpretable representations that are competitive with representations learned by existing supervised methods. For an up-to-date version of this paper, please see https://arxiv.org/abs/1606.03657.


title: Real-time Simulation of Large Bodies of Water with Small Scale Details

text: We present a hybrid water simulation method that combines grid based and particles based approaches. Our specialized shallow water solver can handle arbitrary underlying terrain slopes, arbitrary water depth and supports wet-dry regions tracking. To treat open water scenes we introduce a method for handling non-reflecting boundary conditions. Regions of liquid that cannot be represented by the height field including breaking waves, water falls and splashing due to rigid and soft bodies interaction are automatically turned into spray, splash and foam particles. The particles are treated as simple non-interacting point masses and they exchange mass and momentum with the height field fluid. We also present a method for procedurally adding small scale waves that are advected with the water flow. We demonstrate the effectiveness of our method in various test scene including a large flowing river along a valley with beaches, big rocks, steep cliffs and waterfalls. Both the grid and the particles simulations are implemented in CUDA. We achieve real-time performance on modern GPUs in all the examples.


title: From Hashing to CNNs: Training Binary Weight Networks via Hashing

text: Deep convolutional neural networks (CNNs) have shown appealing performance on various computer vision tasks in recent years. This motivates people to deploy CNNs to realworld applications. However, most of state-of-art CNNs require large memory and computational resources, which hinders the deployment on mobile devices. Recent studies show that low-bit weight representation can reduce much storage and memory demand, and also can achieve efficient network inference. To achieve this goal, we propose a novel approach named BWNH to train Binary Weight Networks via Hashing. In this paper, we first reveal the strong connection between inner-product preserving hashing and binary weight networks, and show that training binary weight networks can be intrinsically regarded as a hashing problem. Based on this perspective, we propose an alternating optimization method to learn the hash codes instead of directly learning binary weights. Extensive experiments on CIFAR10, CIFAR100 and ImageNet demonstrate that our proposed BWNH outperforms current state-of-art by a large margin.


title: iMapper: Interaction-guided Joint Scene and Human Motion Mapping from Monocular Videos

text: Fig. 1. We present iMapper, a method that reasons about the interactions of humans with objects, to recover both a plausible scene arrangement and human motions, that best explain an input monocular video (see inset). We fit characteristic interactions called scenelets (e.g., A, B, C) to the video and use them to reconstruct a plausible object arrangement and human motion path (left). The key challenge is that reliable fitting requires information about occlusions, which are unknown (i.e., latent). (Right) We show an overlay (from top-view) of our result over manually annotated groundtruth object placements. Note that object meshes are placed based on estimated object category, location, and size information.


title: Algorithm for 3D Point Cloud Denoising

text: The raw data of point cloud produced by 3D scanning tools contains additive noise from various sources. This paper proposes a method for 3D unorganized point cloud denoising by making full use of the depth information of unorganized points and space analytic geometry theory, applying over-domain average method for 2D image of image denoising theory to 3D point data. The point cloud noises are filtered by using irregular polyhedron based on the limited local neighborhoods. The experiment shows that the proposed method successfully removes noise from point cloud with the features of the scattered point model reserved. Furthermore, the presented algorithm excels in its simplicity both in implementation and operation.


title: Central Bank Communication and the Yield Curve: A Semi-Automatic Approach using Non-Negative Matrix Factorization

text: Communication is now a standard tool in the central bank’s monetary policy toolkit. Theoretically, communication provides the central bank an opportunity to guide public expectations, and it has been shown empirically that central bank communication can lead to financial market fluctuations. However, there has been little research into which dimensions or topics of information are most important in causing these fluctuations. We develop a semi-automatic methodology that summarizes the FOMC statements into its main themes, automatically selects the best model based on coherency, and assesses whether there is a significant impact of these themes on the shape of the U.S Treasury yield curve using topic modeling methods from the machine learning literature. Our findings suggest that the FOMC statements can be decomposed into three topics: (i) information related to the economic conditions and the mandates, (ii) information related to monetary policy tools and intermediate targets, and (iii) information related to financial markets and the financial crisis. We find that statements are most influential during the financial crisis and the effects are mostly present in the curvature of the yield curve through information related to the financial theme.


title: Substrate Integrated Waveguide Cross-Coupled Filter With Negative Coupling Structure

text: Substrate integrated waveguide (SIW) technology provides an attractive solution to the integration of planar and nonplanar circuits by using a planar circuit fabrication process. However, it is usually difficult to implement the negative coupling structure required for the design of compact canonical folded elliptic or quasi-elliptic cross-coupled bandpass filter on the basis of a single-layer SIW. In this paper, a special planar negative coupling scheme including a magnetic coupling post-wall iris and a balanced microstrip line with a pair of metallic via-holes is studied in detail. Two -band fourth-degree cross-coupled bandpass filters without and with source-load coupling using the negative coupling structures are then proposed and designed. The two novel SIW filters having the same center frequency of 20.5 GHz and respective passband width of 700 and 800 MHz are implemented on a single-layer Rogers RT/Duroid 5880 substrate with thickness of 0.508 mm. Measured results of those filters, which exhibit a high selectivity, and a minimum in-band insertion loss of approximately 0.9 and 1.0 dB, respectively, agree well with simulated results.


title: Dispersion characteristics of substrate integrated rectangular waveguide

text: Dispersion properties of the substrate integrated rectangular waveguide (SIRW) are rigorously obtained using the BI-RME method combined with the Floquet's theorem. Our analysis shows that the SIRW basically has the same guided-wave characteristics as the conventional rectangular waveguide. Empirical equations are derived from the calculated dispersion curves in order to estimate the cutoff frequency of the first two dominant modes of the SIRW To validate the analysis results, an SIRW guide was designed and measured. Very good agreements between the experimental and theoretical results were obtained.


title: Characteristics of cross (bypass) coupling through higher/lower order modes and their applications in elliptic filter design

text: This paper presents a new set of results concerning the use of higher/lower order modes as a means to implement bypass or cross coupling for applications in elliptic filter design. It is shown that the signs of the coupling coefficients to produce a transmission zero (TZ) either below or above the passband are, in certain situations, reversed from the predictions of simpler existing models. In particular, the bypass coupling to higher/lower order modes must be significantly stronger than the coupling to the main resonance in order to generate TZs in the immediate vicinity of the passband. Planar (H-plane) singlets are used to illustrate the derived results. This study should provide very important guidelines in selecting the proper main and bypass couplings for sophisticated filtering structures. Example filters are designed, built, and measured to demonstrate the validity of the introduced theory.


title: Multilayered substrate integrated waveguide (MSIW) elliptic filter

text: This letter presents the design and experiment of a novel elliptic filter based on the multilayered substrate integrated waveguide (MSIW) technique. A C-band elliptic filter with four folded MSIW cavities is simulated by using high frequency structure simulator software and fabricated with a two-layer printed circuit board process, the measured results show good performance and in agreement with the simulated results.


title: Novel compact net-type resonators and their applications to microstrip bandpass filters

text: Novel compact net-type resonators and their practical applications to microstrip bandpass filters have been presented in this paper. Three kinds of filters are designed and fabricated to demonstrate the practicality of the proposed compact net-type resonators. In addition, by adjusting the structural parameters of the net-type resonators, the spurious frequencies can be properly shifted to higher frequencies. As a result, a three-pole Chebyshev net-type resonator filter with a fractional bandwidth (FBW) of 6.8% has a spurious resonance of up to 4.1f/sub 0/, and it has more than 80% size reduction in comparison with the conventional U-shaped resonator filter. A four-pole quasi-elliptic net-type resonator filter with a FBW of 3.5% has a spurious resonance of up to 5f/sub 0/, and it has approximately 67% size reduction in comparison with the cross-coupled open-loop resonator filter. A three-pole trisection net-type resonator filter with a FBW of 4.7% has a spurious resonance of up to 6.5f/sub 0/, and its size is reduced by 68% in comparison with the trisection open-loop resonator filter. Consequently, each of the designed filters occupies a very small circuit size and has a good stopband response. The measured results are in good agreement with the full-wave simulation results by IE3D.


title: Today ’ s State-Owned Enterprises of China : Are They Dying Dinosaurs or Dynamic Dynamos ?

text: NOTE: The authors thank Bianca Bain for her assistance on an earlier draft of the paper and the University of Macao for providing financial support. Summary This paper raises the question and provides empirical evidence regarding the status of the evolution of the state-owned enterprises (SOEs) in China today. In this study, we compare the SOEs to domestic private-owned enterprises (POEs) and foreign-controlled businesses (FCBs) in the context of their organizational cultures. While a new ownership form, many of the POEs, evolved from former collectives that reflect the traditional values of Chinese business. Conversely, the FCBs are much more indicative of the large global MNCs. Therefore, we look at the SOEs in the context of these two reference points. We conclude that the SOEs of today have substantially transformed to approximate a configuration desired by the Chinese government when it began the SOE transformation a couple of decades ago to make them globally competitive. The SOEs of today appear to be appropriately described as China's economic dynamic dynamo for the future.


title: Simplified high-accuracy calculation of eddy-current loss in round-wire windings

text: It has recently been shown that the most commonly used methods for calculating high-frequency eddy-current loss in round-wire windings can have substantial error, exceeding 60%. Previous work includes a formula based on a parametric set of finite-element analysis (FEA) simulations that gives proximity-effect loss for a large range of frequencies, using the parameters from a lookup table based on winding geometry. We improve the formula by decreasing the number of parameters in the formula and also, more importantly, by using simple functions to get the parameters from winding geometry such that a large lookup table is not needed. The function we present is exact in the low frequency limit (diameter much smaller than skin depth) and has error less than 4% at higher frequencies. We make our new model complete by examining the field expression needed to get the total proximity-effect loss and by including the skin-effect loss. We also present experimental results confirming the validity of the model and its superiority to standard methods.


title: Adapting attributes by selecting features similar across domains

text: Attributes are semantic visual properties shared by objects. They have been shown to improve object recognition and to enhance content-based image search. While attributes are expected to cover multiple categories, e.g. a dalmatian and a whale can both have "smooth skin", we find that the appearance of a single attribute varies quite a bit across categories. Thus, an attribute model learned on one category may not be usable on another category. We show how to adapt attribute models towards new categories. We ensure that positive transfer can occur between a source domain of categories and a novel target domain, by learning in a feature subspace found by feature selection where the data distributions of the domains are similar. We demonstrate that when data from the novel domain is limited, regularizing attribute models for that novel domain with models trained on an auxiliary domain (via Adaptive SVM) improves the accuracy of attribute prediction.


title: Area-efficient parallel-prefix Ling adders

text: Efficient addition of binary numbers plays a very important role in the design of dedicated as well as general purpose processors for the implementation of arithmetic and logic units, branch decision, and floating-point operations, address generations, etc. Several methods have been reported in the literature for the fast and hardware-efficient realization of binary additions. Among these methods, parallel-prefix addition schemes have received much of attentions, since they provide many design choices for delay/area-efficient implementations and optimization of tradeoffs. In this paper, we have proposed area-efficient approach for the design of parallel-prefix Ling adders. We have achieved the area efficiency by computing the real carries, based on the Ling carries produced by the lower bit positions. Using the proposed method, the number of logic levels can be reduced by one, which leads to reduction of delay as well as significant saving of area complexity of the adder. We have implemented the proposed adders using 0.18µm CMOS technology; and from the synthesis results, we find that our proposed adders could achieve up to 35% saving of area over the previously reported parallel-prefix Ling adders under the same delay constraints.


title: 3D shape regression for real-time facial animation

text: We present a real-time performance-driven facial animation system based on 3D shape regression. In this system, the 3D positions of facial landmark points are inferred by a regressor from 2D video frames of an ordinary web camera. From these 3D points, the pose and expressions of the face are recovered by fitting a user-specific blendshape model to them. The main technical contribution of this work is the 3D regression algorithm that learns an accurate, user-specific face alignment model from an easily acquired set of training data, generated from images of the user performing a sequence of predefined facial poses and expressions. Experiments show that our system can accurately recover 3D face shapes even for fast motions, non-frontal faces, and exaggerated expressions. In addition, some capacity to handle partial occlusions and changing lighting conditions is demonstrated.


title: Explaining International Migration in the Skype Network: The Role of Social Network Features

text: In recent years, several new ways have appeared for quantifying human migration such as location based smartphone applications and tracking user activity from websites. To show usefulness of these new approaches, we present the results of a study of cross-country migration as observed via login events in the Skype network. We explore possibility to extract human migration and correlate it with institutional statistics. The study demonstrates that a number of social network features are strongly related to net migration from and to a given country, as well as net migration between pairs of countries. Specifically, we find that percentage of international calls, percentage of international links and foreign logins in a country, complemented by gross domestic product, can be used as relatively accurate proxies for estimating migration.


title: Compact Proofs of Retrievability

text: In a proof-of-retrievability system, a data storage center must prove to a verifier that he is actually storing all of a client’s data. The central challenge is to build systems that are both efficient and provably secure—that is, it should be possible to extract the client’s data from any prover that passes a verification check. In this paper, we give the first proof-of-retrievability schemes with full proofs of security against arbitrary adversaries in the strongest model, that of Juels and Kaliski. Our first scheme, built from BLS signatures and secure in the random oracle model, features a proof-of-retrievability protocol in which the client’s query and server’s response are both extremely short. This scheme allows public verifiability: anyone can act as a verifier, not just the file owner. Our second scheme, which builds on pseudorandom functions (PRFs) and is secure in the standard model, allows only private verification. It features a proof-of-retrievability protocol with an even shorter server’s response than our first scheme, but the client’s query is long. Both schemes rely on homomorphic properties to aggregate a proof into one small authenticator value.


title: Verilog HDL model based thermometer-to-binary encoder with bubble error correction

text: This paper compares several approaches to come up with the Verilog HDL model of the thermometer-to-binary encoder with bubble error correction. It has been demonstrated that implementations of different ideas to correct bubble errors yield circuits whose parameters tremendously vary in delay, area and power consumption. The shortest delay is achieved for the design synthesized from the model which mimics a human reading temperature on classic liquid-in-glass thermometer.


title: Robust detection of non-motorized road users using deep learning on optical and LIDAR data

text: Detection of non-motorized road users, such as cyclists and pedestrians, is a challenging problem in collision warning/collision avoidance (CW/CA) systems as direct information (e.g. location, speed, and class) cannot be obtained from such users. In this paper, we propose a fusion of LIDAR data and a deep learning-based computer vision algorithm, to substantially improve the detection of regions of interest (ROIs) and subsequent identification of road users. Experimental results on the KITTI object detection benchmark quantify the effectiveness of incorporating LIDAR data with region-based deep convolutional networks. Thus our work provides another step towards the goal of designing safe and smart transportation systems of the future.


title: Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks

text: Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate quantification of post-operative thrombus volume is required. However, a proper evaluation is hindered by the lack of automatic, robust and reproducible thrombus segmentation algorithms. We propose a new fully automatic approach based on Deep Convolutional Neural Networks (DCNN) for robust and reproducible thrombus region of interest detection and subsequent fine thrombus segmentation. The DetecNet detection network is adapted to perform region of interest extraction from a complete CTA and a new segmentation network architecture, based on Fully Convolutional Networks and a Holistically-Nested Edge Detection Network, is presented. These networks are trained, validated and tested in 13 post-operative CTA volumes of different patients using a 4-fold cross-validation approach to provide more robustness to the results. Our pipeline achieves a Dice score of more than 82% for post-operative thrombus segmentation and provides a mean relative volume difference between ground truth and automatic segmentation that lays within the experienced human observer variance without the need of human intervention in most common cases.


title: The infrastructure problem in HCI

text: HCI endeavors to create human-centered computer systems, but underlying technological infrastructures often stymie these efforts. We outline three specific classes of user experience difficulties caused by underlying technical infrastructures, which we term constrained possibilities, unmediated interaction, and interjected abstractions. We explore how prior approaches in HCI have addressed these issues, and discuss new approaches that will be required for future progress. We argue that the HCI community must become more deeply involved with the creation of technical infrastructures. Doing so, however, requires a substantial expansion to the methodological toolbox of HCI.


title: An examination of the celebrity endorsements and online customer reviews influence female consumers' shopping behavior

text: 0747-5632/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.chb.2012.08.005 ⇑ Corresponding author. Tel.: +886 2 2737 6764; fa E-mail address: melodyps@gmail.com (P.-S. Wei). The goal of this study is to compare the influence of celebrity endorsements to online customer reviews on female shopping behavior. Based on AIDMA and AISAS models, we design an experiment to investigate consumer responses to search good and experience good respectively. The results revealed that search good (shoes) endorsed by a celebrity in an advertisement evoked significantly more attention, desire, and action from the consumer than did an online customer review. We also found that online customer reviews emerged higher than the celebrity endorsement on the scale of participants’ memory, search and share attitudes toward the experience good (toner). Implications for marketers as well as suggestions for future research are discussed. 2012 Elsevier Ltd. All rights reserved.


title: Hat-Delta --- One Right Does Make a Wrong

text: We outline two methods for locating bugs in a program. This is done by comparing computations of the same program with different input. At least one of these computations must produce a correct result, while exactly one must exhibit some erroneous behaviour. Firstly reductions that are thought highly likely to be correct are eliminated from the search for the bug. Secondly, a program slicing technique is used to identify areas of code that are likely to be correct. Both methods have been implemented. In combination with algorithmic debugging they provide a system that quickly and accurately identifies bugs.


title: Terabit/sec-class board-level optical interconnects through polymer waveguides using 24-channel bidirectional transceiver modules

text: We report here on the design, fabrication and characterization of an integrated optical data bus designed for terabit/sec-class module-to-module on-board data transfer using integrated optical transceivers. The parallel optical transceiver is based on a through-silicon-via (TSV) silicon carrier as the platform for integration of 24-channel VCSEL and photodiode arrays with CMOS ICs. The Si carrier also includes optical vias (holes) for optical access to conventional surface-emitting 850-nm optoelectronic (OE) devices. The 48-channel transceiver is flip-chip soldered to an organic carrier forming the transceiver Optomodule. The optical printed circuit board (o-PCB) is a typical FR4 board with a polymer waveguide layer added on top. A 48-channel flex-waveguide is fabricated separately and attached to the FR4 board. Turning mirrors are fabricated into the waveguides and a lens array is attached to facilitate optical coupling. An assembly procedure has been developed to surface mount the Optomodule to the o-PCB using a ball grid array (BGA) process which provides both electrical and optical interconnections. Efficient optical coupling is achieved using a dual-lens optical system, with one lens array incorporated into the Optomodule and a second on the o-PCB. Fully functional Optomodules with 24 transmitter + 24 receiver channels were characterized with transmitters operating up to 20 Gb/s and receivers up to 15 Gb/s. Finally, two Optomodules were assembled onto an o-PCB and a full optical link demonstrated, achieving > 20 bidirectional links at 10 Gb/s. At 15 Gb/s, error-free operation was demonstrated for 15 channels in each direction, realizing a record o-PCB link with a 225 Gb/s bidirectional aggregate data rate.


title: PLUG: flexible lookup modules for rapid deployment of new protocols in high-speed routers

text: New protocols for the data link and network layer are being proposed to address limitations of current protocols in terms of scalability, security, and manageability. High-speed routers and switches that implement these protocols traditionally perform packet processing using ASICs which offer high speed, low chip area, and low power. But with inflexible custom hardware, the deployment of new protocols could happen only through equipment upgrades. While newer routers use more flexible network processors for data plane processing, due to power and area constraints lookups in forwarding tables are done with custom lookup modules. Thus most of the proposed protocols can only be deployed with equipment upgrades. To speed up the deployment of new protocols, we propose a flexible lookup module, PLUG (Pipelined Lookup Grid). We can achieve generality without loosing efficiency because various custom lookup modules have the same fundamental features we retain: area dominated by memories, simple processing, and strict access patterns defined by the data structure. We implemented IPv4, Ethernet, Ethane, and SEATTLE in our dataflow-based programming model for the PLUG and mapped them to the PLUG hardware which consists of a grid of tiles. Throughput, area, power, and latency of PLUGs are close to those of specialized lookup modules.


title: Algorithmic improvements for fast concurrent Cuckoo hashing

text:
Fast concurrent hash tables are an increasingly important building block as we scale systems to greater numbers of cores and threads. This paper presents the design, implementation, and evaluation of a high-throughput and memory-efficient concurrent hash table that supports multiple readers and writers. The design arises from careful attention to systems-level optimizations such as minimizing critical section length and reducing interprocessor coherence traffic through algorithm re-engineering. As part of the architectural basis for this engineering, we include a discussion of our experience and results adopting Intel's recent hardware transactional memory (HTM) support to this critical building block. We find that naively allowing concurrent access using a coarse-grained lock on existing data structures reduces overall performance with more threads. While HTM mitigates this slowdown somewhat, it does not eliminate it. Algorithmic optimizations that benefit both HTM and designs for fine-grained locking are needed to achieve high performance.
 Our performance results demonstrate that our new hash table design---based around optimistic cuckoo hashing---outperforms other optimized concurrent hash tables by up to 2.5x for write-heavy workloads, even while using substantially less memory for small key-value items. On a 16-core machine, our hash table executes almost 40 million insert and more than 70 million lookup operations per second.


title: Information-Driven Dynamic Sensor Collaboration for Tracking Applications

text: This article overviews the information-driven approach to sensor collaboration in ad hoc sensor networks. The main idea is for a network to determine participants in a " sensor collaboration " by dynamically optimizing the information utility of data for a given cost of communication and computation. A definition of information utility is introduced, and several approximate measures of the information utility are developed for reasons of computational tractability. We illustrate the use of this approach using examples drawn from tracking applications. I. INTRODUCTION The technology of wirelessly networked micro-sensors promises to revolutionize the way we live, work, and interact with the physical environment. For example, tiny, inexpensive sensors can be " sprayed " onto roads, walls, or machines to monitor and detect a variety of interesting events such as highway traffic, wildlife habitat condition, forest fire, manufacturing job flow, and military battlefield situation.


title: Estimating 3D Hand Pose from a Cluttered Image

text: A method is proposed that can generate a ranked list of plausible three-dimensional hand configurations that best match an input image. Hand pose estimation is formulated as an image database indexing problem, where the closest matches for an input hand image are retrieved from a large database of synthetic hand images. In contrast to previous approaches, the system can function in the presence of clutter, thanks to two novel clutter-tolerant indexing methods. First, a computationally efficient approximation of the image-to-model chamfer distance is obtained by embedding binary edge images into a high-dimensional Euclidean space. Second, a general-purpose, probabilistic line matching method identifies those line segment correspondences between model and input images that are the least likely to have occurred by chance. The performance of this cluttertolerant approach is demonstrated in quantitative experiments with hundreds of real hand images.


title: Thermal degradation of DRAM retention time: Characterization and improving techniques

text: Variation of DRAM retention time and reliability problem induced by thermal stress was investigated. Most of the DRAM cells revealed 2-state retention time with thermal stress. The effects of hydrogen annealing condition and fluorine implantation on the variation of retention time and reliability are discussed.


title: Data Science , Predictive Analytics , and Big Data : A Revolution That Will Transform Supply Chain Design and Management

text: W e illuminate the myriad of opportunities for research where supply chain management (SCM) intersects with data science, predictive analytics, and big data, collectively referred to as DPB. We show that these terms are not only becoming popular but are also relevant to supply chain research and education. Data science requires both domain knowledge and a broad set of quantitative skills, but there is a dearth of literature on the topic and many questions. We call for research on skills that are needed by SCM data scientists and discuss how such skills and domain knowledge affect the effectiveness of an SCM data scientist. Such knowledge is crucial to develop future supply chain leaders. We propose definitions of data science and predictive analytics as applied to SCM. We examine possible applications of DPB in practice and provide examples of research questions from these applications, as well as examples of research questions employing DPB that stem from management theories. Finally, we propose specific steps interested researchers can take to respond to our call for research on the intersection of SCM and DPB.


title: An integrated charger using segmented windings of interior permanent magnet motor based on 3 phase with 9 windings

text: Connecting the plug of electric vehicles (EVs) into the grid source directly means to charge the battery. The electric power generated from the grid goes through the electric motor, crosses the bidirectional inverter used as three-boost rectifier and is received by the load (battery). An innovative fast-integrated charger based on segmented windings of permanent magnet synchronous motor (PMSM) is introduced for plug-in electric vehicles (PEV). The three-phase with nine windings of PMSM is used during the traction and charging modes. Three (or single) phases of grid source are directly connected to the neutral points of segmented PMSM windings to provide high power density to the battery. The system configuration and operation of charging mode are explained in detail for proposed integrated on-board charger. The simulation models are designed by using Ansoft Maxwell, Ansys Maxwell circuit editor, and Matlab/Simulink softwares, and simulation results are presented to verify the performance of the proposed system. In addition, the experimental setup of the integrated system is under progress.


title: From the Internet of Computers to the Internet of Things

text: This paper1 discusses the vision, the challenges, possible usage scenarios and technological building blocks of the “Internet of Things”. In particular, we consider RFID and other important technological developments such as IP stacks and web servers for smart everyday objects. The paper concludes with a discussion of social and governance issues that are likely to arise as the vision of the Internet of Things becomes a reality.


title: of the Thesis Classification of Imbalanced Data Using Synthetic OverSampling Techniques by

text: of the Thesis Classification of Imbalanced Data Using Synthetic Over-Sampling Techniques


title: Query Optimization Techniques In Graph Databases

text: Graph databases (GDB) have recently been arisen to overcome the limits of traditional databases for storing and managing data with graph-like structure. Today, they represent a requirementfor many applications that manage graph-like data,like social networks.Most of the techniques, applied to optimize queries in graph databases, have been used in traditional databases, distribution systems,... or they are inspired from graph theory. However, their reuse in graph databases should take care of the main characteristics of graph databases, such as dynamic structure, highly interconnected data, and ability to efficiently access data relationships. In this paper, we survey the query optimization techniques in graph databases. In particular,we focus on the features they have introduced to improve querying graph-like data.


title: Wait-Free Synchronization

text: A wait-free implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a wait-free implementation of one data object from another lies at the heart of much recent work in concurrent algorithms, concurrent data structures, and multiprocessor architectures. First, we introduce a simple and general technique, based on reduction to a concensus protocol, for proving statements of the form, “there is no wait-free implementation of X by Y.” We derive a hierarchy of objects such that no object at one level has a wait-free implementation in terms of objects at lower levels. In particular, we show that atomic read/write registers, which have been the focus of much recent attention, are at the bottom of the hierarchy: thay cannot be used to construct wait-free implementations of many simple and familiar data types. Moreover, classical synchronization primitives such astest&set and fetch&add, while more powerful than read and write, are also computationally weak, as are the standard message-passing primitives. Second, nevertheless, we show that there do exist simple universal objects from which one can construct a wait-free implementation of any sequential object.


title: MapReduce: Simplified Data Processing on Large Clusters

text: MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users specify the computation in terms of a map and a reduce function, and the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks. Programmers find the system easy to use: more than ten thousand distinct MapReduce programs have been implemented internally at Google over the past four years, and an average of one hundred thousand MapReduce jobs are executed on Google's clusters every day, processing a total of more than twenty petabytes of data per day.


title: Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

text: This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.


title: Adaptive median filters: new algorithms and results

text: Based on two types of image models corrupted by impulse noise, we propose two new algorithms for adaptive median filters. They have variable window size for removal of impulses while preserving sharpness. The first one, called the ranked-order based adaptive median filter (RAMF), is based on a test for the presence of impulses in the center pixel itself followed by a test for the presence of residual impulses in the median filter output. The second one, called the impulse size based adaptive median filter (SAMF), is based on the detection of the size of the impulse noise. It is shown that the RAMF is superior to the nonlinear mean L(p) filter in removing positive and negative impulses while simultaneously preserving sharpness; the SAMF is superior to Lin's (1988) adaptive scheme because it is simpler with better performance in removing the high density impulsive noise as well as nonimpulsive noise and in preserving the fine details. Simulations on standard images confirm that these algorithms are superior to standard median filters.


title: AP3: cooperative, decentralized anonymous communication

text: This paper describes a cooperative overlay network that provides anonymous communication services for participating users. The Anonymizing Peer-to-Peer Proxy (AP3) system provides clients with three primitives: (i) anonymous message delivery, (ii) anonymous channels, and (iii) secure pseudonyms. AP3 is designed to be lightweight, low-cost and provides "probable innocence" anonymity to participating users, even under a large-scale coordinated attack by a limited fraction of malicious overlay nodes. Additionally, we use AP3's primitives to build novel anonymous group communication facilities (multicast and anycast), which shield the identity of both publishers and subscribers.


Probabilistic Encryption


title: THE ROLE OF MUSIC COMMUNICATION IN CINEMA

text: [Authors’ note: This paper is an abbreviated version of a chapter included in a forthcoming book entitled Music Communication (D. Miell, R. MacDonald, & D. Hargreaves, Eds.), to be published by Oxford University Press.] Past research leaves no doubt about the efficacy of music as a means of communication. In the following pages, after presenting a general model of music communication, the authors will introduce models – both empirical and theoretical – of film music perception and the role of music in film, referencing some of the most significant research investigating the relationship between sound and image in the cinematic context. We shall then enumerate the many ways in which the motion picture soundtrack can supplement, enhance, and expand upon the meaning of a film’s narrative. The relationship between the auditory and visual components in cinema is both active and dynamic, affording a multiplicity of possible relations than can evolve – sometimes dramatically – as the narrative unfolds. This paper will take a cognitive approach to the study of musical communication in cinema. As a result, much credence will be given to the results of empirical research investigating human cognitive processing in response to the motion picture experience. In conclusion, the present authors will argue for a more inclusive definition of the term “film music” than that utilized or implied in previous publications. In our view, film music is one component of a sonic fabric that includes the musical score, ambient sound, dialogue, sound effects, and silence. The functions of these constituent elements often overlap or interact with one another, creating a harmonious counterpoint to the visual image. 1. A MODEL OF MUSIC COMMUNICATION Many studies have investigated various aspects of musical communication as a form of expression (Bengtsson & Gabrielsson, 1983; Clarke, 1988; Clynes, 1983, Gabrielsson, 1988, Seashore, 1967/1938; Senju & Ohgushi, 1987; Sundberg, 1988; Sundberg et al., 1983). A tripartite communication model was proposed by Campbell and Heller (1980), consisting simply of a composer, performer, and listener. Using this previous model as a foundation, Kendall and Carterette (1990) elegantly expanded upon this model of music communication, detailing a process involving multiple states of coding, decoding, and recoding. Kendall and Carterette suggest that this process involves the “grouping and parsing of elementary thought units” (p. 132), these “thought units” (metasymbols) are mental representations involved in the process of creating, performing, and listening to musical sound. 2. MODELS OF FILM MUSIC COMMUNICATION 2.1 Empirical Evidence Several researchers have proposed models specific to the perception and cognition of music within the cinematic context. Initiating this systematic effort, Marshall and Cohen’s (1988) bipartite “congruence-associationist” model suggests that the meaning of a film is altered by the music as the result of two complex cognitive processes. Based upon subject responses, the researchers determined that musical sound directly effects subject ratings on the Potency (strong-weak) and Activity (active-passive) dimensions, while the Evaluative dimension (good-bad) relies on the degree of congruence between the audio and visual components on all three dimensions, as determined by a “comparator” component. The second part of the model describes how musical meaning is ascribed to the film. Marshall and Cohen claim that attention is directed to the overlapping congruent meaning of the music and the film. Referential meanings associated with the music are ascribed to the overlapped (congruent) audio-visual components upon which attention is focused. As a result, “the music alters meaning of a particular aspect of the film” (1988, p. 109). Marshall and Cohen also acknowledge the important role played by temporal characteristics of the sound and image, stating that “the assignment of accent to events will affect retention, processing, and interpretation” (1988, p. 108). Incorporation of this important component of the developing model was provided by Lipscomb and Kendall’s (1994) Film Music Paradigm, in which two implicit processes are considered as the basis for whether attentional focus is shifted to the musical component or whether it is likely to remain at the subconscious – cognitively “inaudible” – level. The authors suggested that these two implicit processes include an association judgment (similar to Marshall and Cohen’s assessment of “congruence”) and an evaluation of the accent structure relationship between the auditory and visual components. Based on the results of a series of three experiments utilizing stimuli ranging from extremely simple, single-object animations to actual movie excerpts, Lipscomb (1995) determined that the role of the two implicit judgments appears to be dynamic such that, with simple stimuli (such as that used in Lipscomb, 1995, Experiment 1 and Marshall & Cohen, 1988), accent structure alignment plays a dominant role. As the stimuli become more complex (e.g., multi-object animations and actual movie excerpts) the primary determinant of meaning in the auditory domain appears to shift to the associational judgment, with the accent structure alignment aspect receding to a supporting role, i.e., focusing audience attention on certain aspects of the visual image (Boltz, 2001). The most complex and fully developed model of film music perception proposed to date is Cohen’s (2001) “congruence-associationist framework for understanding film-music communication” (p. 259; see Figure 1). This multi-stage model attempts to account for meaning derived from the spoken narrative, visual images, and musical sound. Level A represents bottom-up processing based on physical features derived from input to each perceptual modality. Level B represents the determination of cross-modal congruence, based on both semantic (associational) and syntactic (temporal) grouping features. Level D represents top-down processing, determined by an individual’s past experience and the retention of that experience in long term memory. According to this model, the input from levels B (bottom-up) and D (top-down) meet in the observer’s conscious mind (level C), where information is prepared for transfer to short term memory. In its details, clearly documented in Cohen (2001), this model is based on an assumption of visual primacy, citing several studies that have suggested a subservient role for the auditory component (Bolivar et al., 1994; Driver, 1997; Thompson et al., 1994). Though a common assumption throughout the literature, the present authors would like to express reservation about this assumption and suggest that additional research is required before such a claim can be supported definitively. Figure 1. Cohen’s “congruence-associationist framework. 2.2 Theoretical Evidence Richard Wagner, creator of the idealized Gesamtkunstwerk in the form of the 19 century music drama, claimed that “as pure organ of the feeling, [music] speaks out the very thing which word speech in itself can not speak out ... that which, looked at from the standpoint of our human intellect, is the unspeakable” (Wagner 1849/1964, p. 217). According to Suzanne K. Langer, “music has all the earmarks of a true symbolism, except one: the existence of an assigned connotation” and, though music is clearly a symbolic form, it remains an “unconsummated symbol” (1942, p. 240). In order for a film to make the greatest possible impact, there must be an interaction between the verbal dialogue (consummated symbol), the cinematic images (also, typically, a consummated symbol), and the musical score (unconsummated symbol). To answer the question “How does music in film narration create a point of experience for the spectator?,” Gorbman (1987) suggests three methods by which music can “signify” in the context of a narrative film. Purely musical signification results from the highly coded syntactical relationships inherent in the association of one musical tone with another. Patterns of tension and release provide a sense of organization and meaning to the musical sound, apart from any extramusical association that might exist. Cultural musical codes are exemplified by music that has come to be associated with a certain mood or state of mind. These associations have been further canonized by the Hollywood film industry into certain conventional expectations – implicitly anticipated by enculturated audience members – determined by the narrative content of a given scene. Finally, cinematic codes influence musical meaning merely due to the placement of musical sound within the filmic context. Opening credit and end title music illustrate this type of signification, as well as recurring musical themes that come to represent characters or situations within the film. There is a commonly held belief that film music is not to be heard (Burt, 1994; Gorbman, 1987). Instead, it is believed to fulfill its role in communicating the underlying psychological drama of the narrative at a subconscious level (Lipscomb, 1989). There is, however, certain music that is intended to be heard by the audience as part of the cinematic diegesis, i.e., “the narratively implied spatiotemporal world of the actions and characters” (Gorbman 1987, p. 21). This “world” includes, naturally, a sonic component. Therefore, all sounds that are understood to be heard by characters in the narrative – including music – are referred to as diegetic, while those that are not part of the diegesis (e.g., the orchestral score) are referred to as nondiegetic. This would suggest that diegetic music is more likely to be processed at the conscious level while nondiegetic music might remain at the subconscious level, though research is needed to determine whether this is true, in fact. It is worth noting also, that the source of diegetic sound can be either seen or unseen. Michel Chion (199


title: Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey

text: Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been proposed. Most of them exploit mobility to address the problem of data collection in WSNs. In this article we first define WSNs with MEs and provide a comprehensive taxonomy of their architectures, based on the role of the MEs. Then we present an overview of the data collection process in such a scenario, and identify the corresponding issues and challenges. On the basis of these issues, we provide an extensive survey of the related literature. Finally, we compare the underlying approaches and solutions, with hints to open problems and future research directions.


title: A Successive Approximation Recursive Digital Low-Dropout Voltage Regulator With PD Compensation and Sub-LSB Duty Control

text: This paper presents a recursive digital low-dropout (RLDO) regulator that improves response time, quiescent power, and load regulation dynamic range over prior digital LDO designs by 1–2 orders of magnitude. The proposed RLDO enables a practical digital replacement to analog LDOs by using an SAR-like binary search algorithm in a coarse loop and a sub-LSB pulse width modulation duty control scheme in a fine loop. A proportional-derivative compensation scheme is employed to ensure stable operation independent of load current, the size of the output decoupling capacitor, and clock frequency. Implemented in 0.0023 mm2 in 65 nm CMOS, the 7-bit RLDO achieves, at a 0.5-V input, a response time of 15.1 ns with a figure of merit of 199.4 ps, along with stable operation across a 20 000 $\times $  dynamic load range.


title: Imaging Cognition II: An Empirical Review of 275 PET and fMRI Studies

text: Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have been extensively used to explore the functional neuroanatomy of cognitive functions. Here we review 275 PET and fMRI studies of attention (sustained, selective, Stroop, orientation, divided), perception (object, face, space/motion, smell), imagery (object, space/ motion), language (written/spoken word recognition, spoken/ no spoken response), working memory (verbal/numeric, object, spatial, problem solving), semantic memory retrieval (categorization, generation), episodic memory encoding (verbal, object, spatial), episodic memory retrieval (verbal, nonverbal, success, effort, mode, context), priming (perceptual, conceptual), and procedural memory (conditioning, motor, and nonmotor skill learning). To identify consistent activation patterns associated with these cognitive operations, data from 412 contrasts were summarized at the level of cortical Brodmann's areas, insula, thalamus, medial-temporal lobe (including hippocampus), basal ganglia, and cerebellum. For perception and imagery, activation patterns included primary and secondary regions in the dorsal and ventral pathways. For attention and working memory, activations were usually found in prefrontal and parietal regions. For language and semantic memory retrieval, typical regions included left prefrontal and temporal regions. For episodic memory encoding, consistently activated regions included left prefrontal and medial-temporal regions. For episodic memory retrieval, activation patterns included prefrontal, medial-temporal, and posterior midline regions. For priming, deactivations in prefrontal (conceptual) or extrastriate (perceptual) regions were consistently seen. For procedural memory, activations were found in motor as well as in non-motor brain areas. Analysis of regional activations across cognitive domains suggested that several brain regions, including the cerebellum, are engaged by a variety of cognitive challenges. These observations are discussed in relation to functional specialization as well as functional integration.


title: Exploring Synergies between Machine Learning and Knowledge Representation to Capture Scientific Knowledge

text: In this paper we explore synergies between the machine learning and knowledge representation fields by considering how scientific knowledge is represented in these areas. We illustrate some of the knowledge obtained through machine learning methods, providing two contrasting examples of such models: probabilistic graphical models (aka Bayesian networks) and artificial neural networks (including deep learning networks). From knowledge representation, we give an overview of ontological representations, qualitative reasoning, and planning. Then we discuss potential synergies that would benefit both areas.


title: Coupling Matrix Synthesis for a New Class of Microwave Filter Configuration

text: In this paper a new approach to the synthesis of coupling matrices for microwave filters is presente d. The new approach represents an advance on existing direct a nd optimization methods for coupling matrix synthesis in that it will exhaustively discover all possible coupling matrix solutions for a network if more than one exists. This enables a se lection to be made of the set of coupling values, resonator frequ ency offsets, parasitic coupling tolerance etc that will be best suited to the technology it is intended to realize the microwave filter with. To demonstrate the use of the method, the case of the r cently – introduced ‘extended box’ (EB) coupling matrix configuration is taken. The EB represents a new class of filter con figuration featuring a number of important advantages, one of which is the existence of multiple coupling matrix solutions for each prototype filtering function, eg 16 for 8 degree cases. This case is taken as an example to demonstrate the use of the synthesis method – yielding one solution suitable for dual-mode realiz ation and one where some couplings are small enough to neglect. Index Terms — Coupling matrix, filter synthesis, Groebner basis, inverted characteristic, multiple solutions.


title: An Artificial Bee Colony-Based COPE Framework for Wireless Sensor Network

text: In wireless communication, network coding is one of the intelligent approaches to process the packets before transmitting for efficient information exchange. The goal of this work is to enhance throughput by using the intelligent technique, which may give comparatively better optimization. This paper introduces a biologically-inspired coding approach called Artificial Bee Colony Network Coding (ABC-NC), a modification in the COPE framework. The existing COPE and its variant are probabilistic approaches, which may not give good results in all of the real-time scenarios. Therefore, it needs some intelligent technique to find better packet combinations at intermediate nodes before forwarding to optimize the energy and maximize the throughput in wireless networks. This paper proposes ABC-NC over the existing COPE framework for the wireless environment.


title: Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition

text: Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of these bases. The applicability of these methods to visual object recognition tasks has been limited because of the prohibitive cost of the optimization algorithms required to compute the sparse representation. In this work we propose a simple and efficient algorithm to learn basis functions. After training, this model also provides a fast and smooth approximator to the optimal representation, achieving even better accuracy than exact sparse coding algorithms on visual object recognition tasks.


title: What are mobile developers asking about? A large scale study using stack overflow

text: The popularity of mobile devices has been steadily growing in recent years. These devices heavily depend on software from the underlying operating systems to the applications they run. Prior research showed that mobile software is different than traditional, large software systems. However, to date most of our research has been conducted on traditional software systems. Very little work has focused on the issues that mobile developers face. Therefore, in this paper, we use data from the popular online Q&A site, Stack Overflow, and analyze 13,232,821 posts to examine what mobile developers ask about. We employ Latent Dirichlet allocation-based topic models to help us summarize the mobile-related questions. Our findings show that developers are asking about app distribution, mobile APIs, data management, sensors and context, mobile tools, and user interface development. We also determine what popular mobile-related issues are the most difficult, explore platform specific issues, and investigate the types (e.g., what, how, or why) of questions mobile developers ask. Our findings help highlight the challenges facing mobile developers that require more attention from the software engineering research and development communities in the future and establish a novel approach for analyzing questions asked on Q&A forums.


title: Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval

text: Thanks to the success of deep learning, cross-modal retrieval has made significant progress recently. However, there still remains a crucial bottleneck: how to bridge the modality gap to further enhance the retrieval accuracy. In this paper, we propose a self-supervised adversarial hashing (SSAH) approach, which lies among the early attempts to incorporate adversarial learning into cross-modal hashing in a self-supervised fashion. The primary contribution of this work is that two adversarial networks are leveraged to maximize the semantic correlation and consistency of the representations between different modalities. In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations. Such information guides the feature learning process and preserves the modality relationships in both the common semantic space and the Hamming space. Extensive experiments carried out on three benchmark datasets validate that the proposed SSAH surpasses the state-of-the-art methods.


title: Arthrodesis with Intramedular Fixation in Posttraumatic Arthrosis of the Midfoot: A Case Report

text: We present two middle-aged men with posttraumatic arthrosis of the midfoot. Both patients suffered from severe pain and their foot was unable to bear weight. Both were operated using new fusion bolt 6.5 mm and additional screws. In their case, arthrodesis was mandatory and effective intervention. After surgical treatment both patients were pain free and able to walk without crutches and return to daily work.


title: Wavelet analysis of EEG for seizure detection: Coherence and phasesynchrony estimation.

text: This paper deals with the wavelet analysis method f or seizure detection in EEG time series and coherence estimation. The main part of the paper pr esents the basic principles of signal decomposition in connection with the EEG frequency ba nds. Wavelet analysis method has been used for detection of seizure onset. The wavelet fi ltered signal is used for the computation of spectral power ratio. The results show that our met hod can identify pre seizure, seizure, post seizure and non seizure phases. When dealing with s eizure detection and prediction problems it is important to identify seizure precursor dynamics and necessary to identify information about onset and spread of seizures. Therefore in th e second part the coherence and phase synchrony during pre seizure, seizure, post seizure an d non seizure are computed. We expect this method to provide more insight into dynamic aspects of the seizure generating process.


title: Evaluating Digital Forensic Options for the Apple iPad

text: The iPod Touch, iPhone and iPad from Apple are among the most popular mobile computing platforms in use today. These devices are of forensic interest because of their high adoption rate and potential for containing digital evidence. The uniformity in their design and underlying operating system (iOS) also allows forensic tools and methods to be shared across product types. This paper analyzes the tools and methods available for conducting forensic examinations of the Apple iPad. These include commercial software products, updated methodologies based on existing jailbreaking processes and the analysis of the device backup contents provided by iTunes. While many of the available commercial tools offer promise, the results of our analysis indicate that most comprehensive examination of the iPad requires jailbreaking to perform forensic duplication and manual analysis of its media content.


title: Enhancing scholarly use of digital libraries: A comparative survey and review of bibliographic metadata ontologies

text: The HathiTrust Research Center (HTRC) is engaged in the development of tools that will give scholars the ability to analyze the HathiTrust digital library's 14 million volume corpus. A cornerstone of the HTRC's digital infrastructure is the workset -- a kind of scholar-built research collection intended for use with the HTRC's analytics platform. Because more than 66% of the digital corpus is subject to copyright restrictions, scholarly users remain dependent upon the descriptive accounts provided by traditional metadata records in order to identify and gather together bibliographic resources for analysis. This paper compares the MADSRDF/MODSRDF, Bibframe, schema.org, BIBO, and FaBiO ontologies by assessing their suitability for employment by the HTRC to meet scholars' needs. These include distinguishing among multiple versions of the same work; representing the complex historical and physical relationships among those versions; and identifying and providing access to finer grained bibliographic entities, e.g., poems, chapters, sections, and even smaller segments of content.


title: Decreased gut microbiota diversity, delayed Bacteroidetes colonisation and reduced Th1 responses in infants delivered by caesarean section.

text:
OBJECTIVE
The early intestinal microbiota exerts important stimuli for immune development, and a reduced microbial exposure as well as caesarean section (CS) has been associated with the development of allergic disease. Here we address how microbiota development in infants is affected by mode of delivery, and relate differences in colonisation patterns to the maturation of a balanced Th1/Th2 immune response.

DESIGN
The postnatal intestinal colonisation pattern was investigated in 24 infants, born vaginally (15) or by CS (nine). The intestinal microbiota were characterised using pyrosequencing of 16S rRNA genes at 1 week and 1, 3, 6, 12 and 24 months after birth. Venous blood levels of Th1- and Th2-associated chemokines were measured at 6, 12 and 24 months.

RESULTS
Infants born through CS had lower total microbiota diversity during the first 2 years of life. CS delivered infants also had a lower abundance and diversity of the Bacteroidetes phylum and were less often colonised with the Bacteroidetes phylum. Infants born through CS had significantly lower levels of the Th1-associated chemokines CXCL10 and CXCL11 in blood.

CONCLUSIONS
CS was associated with a lower total microbial diversity, delayed colonisation of the Bacteroidetes phylum and reduced Th1 responses during the first 2 years of life.


title: Whole-function vectorization

text: Data-parallel programming languages are an important component in today's parallel computing landscape. Among those are domain-specific languages like shading languages in graphics (HLSL, GLSL, RenderMan, etc.) and "general-purpose" languages like CUDA or OpenCL. Current implementations of those languages on CPUs solely rely on multi-threading to implement parallelism and ignore the additional intra-core parallelism provided by the SIMD instruction set of those processors (like Intel's SSE and the upcoming AVX or Larrabee instruction sets). In this paper, we discuss several aspects of implementing dataparallel languages on machines with SIMD instruction sets. Our main contribution is a language- and platform-independent code transformation that performs whole-function vectorization on low-level intermediate code given by a control flow graph in SSA form. We evaluate our technique in two scenarios: First, incorporated in a compiler for a domain-specific language used in realtime ray tracing. Second, in a stand-alone OpenCL driver. We observe average speedup factors of 3.9 for the ray tracer and factors between 0.6 and 5.2 for different OpenCL kernels.


title: Argumentation Theory: A Very Short Introduction

text: Since the time of the ancient Greek philosophers and rhetoricians, argumentation theorists have searched for the requirements that make an argument correct, by some appropriate standard of proof, by examining the errors of reasoning we make when we try to use arguments. These errors have long been called fallacies, and the logic textbooks have for over 2000 years tried to help students to identify these fallacies, and to deal with them when they are encountered. The problem was that deductive logic did not seem to be much use for this purpose, and there seemed to be no other obvious formal structure that could usefully be applied to them. The radical approach taken by Hamblin (1970) was to refashion the concept of an argument to think of it not just as an arbitrarily designated set of propositions, but as a move one party makes in a dialog to offer premises that may be acceptable to another party who doubts the conclusion of the argument. Just after Hamblin's time a school of thought called informal logic grew up that wanted to take a new practical approach to teaching students skills of critical thinking by going beyond deductive logic to seek other methods for analyzing and evaluating arguments. Around the same time, an interdisciplinary group of scholars associated with the term 'argumentation', coming from fields like speech communication, joined with the informal logic group to help build up such practical methods and apply them to real examples of argumentation (Johnson and Blair, 1987). The methods that have been developed so far are still in a process of rapid evolution. More recently, improvements in them have been due to some computer scientists joining the group, and to collaborative research efforts between argumentation theorists and computer scientists. Another recent development has been the adaption of argumentation models and techniques to fields in artificial intelligence, like multi-agent systems and artificial intelligence for legal reasoning. In a short paper, it is not possible to survey all these developments. The best that can be done is to offer an introduction to some of the basic concepts and methods of argumentation theory as they have evolved to the present point, and to briefly indicate some problems and limitations in them. 1. Arguments and Argumentation There are four tasks undertaken by argumentation, or informal logic, as it is also often called: identification, analysis, evaluation and invention. The task of identification …


title: Super Normal Vector for Activity Recognition Using Depth Sequences

text: This paper presents a new framework for human activity recognition from video sequences captured by a depth camera. We cluster hypersurface normals in a depth sequence to form the polynormal which is used to jointly characterize the local motion and shape information. In order to globally capture the spatial and temporal orders, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time grids. We then propose a novel scheme of aggregating the low-level polynormals into the super normal vector (SNV) which can be seen as a simplified version of the Fisher kernel representation. In the extensive experiments, we achieve classification results superior to all previous published results on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.


title: A Seed-Based Method for Generating Chinese Confusion Sets

text:
In natural language, people often misuse a word (called a “confused word”) in place of other words (called “confusing words”). In misspelling corrections, many approaches to finding and correcting misspelling errors are based on a simple notion called a “confusion set.” The confusion set of a confused word consists of confusing words. In this article, we propose a new method of building Chinese character confusion sets.
 Our method is composed of two major phases. In the first phase, we build a list of seed confusion sets for each Chinese character, which is based on measuring similarity in character pinyin or similarity in character shape. In this phase, all confusion sets are constructed manually, and the confusion sets are organized into a graph, called a “seed confusion graph” (SCG), in which vertices denote characters and edges are pairs of characters in the form (confused character, confusing character).
 In the second phase, we extend the SCG by acquiring more pairs of (confused character, confusing character) from a large Chinese corpus. For this, we use several word patterns (or patterns) to generate new confusion pairs and then verify the pairs before adding them into a SCG. Comprehensive experiments show that our method of extending confusion sets is effective. Also, we shall use the confusion sets in Chinese misspelling corrections to show the utility of our method.


title: Learning Over Long Time Lags

text: The advantage of recurrent neural networks (RNNs) in learni ng dependencies between time-series data has distinguished RNNs from other deep learning models. Recent ly, many advances are proposed in this emerging field. However, there is a lack of comprehensive review on mem ory models in RNNs in the literature. This paper provides a fundamental review on RNNs and long short te rm memory (LSTM) model. Then, provides a surveys of recent advances in different memory enhancement s and learning techniques for capturing long term dependencies in RNNs.


title: Ethical Artificial Intelligence

text: First Edition Please send typo and error reports, and any other comments, to hibbard@wisc.edu.


title: Twitter Part-of-Speech Tagging for All: Overcoming Sparse and Noisy Data

text: Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We present a detailed error analysis of existing taggers, motivating a series of tagger augmentations which are demonstrated to improve performance. We identify and evaluate techniques for improving English part-of-speech tagging performance in this genre. Further, we present a novel approach to system combination for the case where available taggers use different tagsets, based on voteconstrained bootstrapping with unlabeled data. Coupled with assigning prior probabilities to some tokens and handling of unknown words and slang, we reach 88.7% tagging accuracy (90.5% on development data). This is a new high in PTB-compatible tweet part-of-speech tagging, reducing token error by 26.8% and sentence error by 12.2%. The model, training data and tools are made available.


title: Photobook: Content-based manipulation of image databases

text: We describe the Photobook system, which is a set of interactive tools for browsing and searching images and image sequences. These query tools differ from those used in standard image databases in that they make direct use of the image content rather than relying on text annotations. Direct search on image content is made possible by use of semantics-preserving image compression, which reduces images to a small set of perceptually-significant coefficients. We discuss three types of Photobook descriptions in detail: one that allows search based on appearance, one that uses 2-D shape, and a third that allows search based on textural properties. These image content descriptions can be combined with each other and with text-based descriptions to provide a sophisticated browsing and search capability. In this paper we demonstrate Photobook on databases containing images of people, video keyframes, hand tools, fish, texture swatches, and 3-D medical data.


title: Face recognition/detection by probabilistic decision-based neural network

text: This paper proposes a face recognition system, based on probabilistic decision-based neural networks (PDBNN). With technological advance on microelectronic and vision system, high performance automatic techniques on biometric recognition are now becoming economically feasible. Among all the biometric identification methods, face recognition has attracted much attention in recent years because it has potential to be most nonintrusive and user-friendly. The PDBNN face recognition system consists of three modules: First, a face detector finds the location of a human face in an image. Then an eye localizer determines the positions of both eyes in order to generate meaningful feature vectors. The facial region proposed contains eyebrows, eyes, and nose, but excluding mouth (eye-glasses will be allowed). Lastly, the third module is a face recognizer. The PDBNN can be effectively applied to all the three modules. It adopts a hierarchical network structures with nonlinear basis functions and a competitive credit-assignment scheme. The paper demonstrates a successful application of PDBNN to face recognition applications on two public (FERET and ORL) and one in-house (SCR) databases. Regarding the performance, experimental results on three different databases such as recognition accuracies as well as false rejection and false acceptance rates are elaborated. As to the processing speed, the whole recognition process (including PDBNN processing for eye localization, feature extraction, and classification) consumes approximately one second on Sparc10, without using hardware accelerator or co-processor.


title: Eigenfaces for Recognition

text: We have developed a near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. The computational approach taken in this system is motivated by both physiology and information theory, as well as by the practical requirements of near-real-time performance and accuracy. Our approach treats the face recognition problem as an intrinsically two-dimensional (2-D) recognition problem rather than requiring recovery of three-dimensional geometry, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features are known as "eigenfaces," because they are the eigenvectors (principal components) of the set of faces; they do not necessarily correspond to features such as eyes, ears, and noses. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and so to recognize a particular face it is necessary only to compare these weights to those of known individuals. Some particular advantages of our approach are that it provides for the ability to learn and later recognize new faces in an unsupervised manner, and that it is easy to implement using a neural network architecture.


title: The multilayer perceptron as an approximation to a Bayes optimal discriminant function

text: The multilayer perceptron, when trained as a classifier using backpropagation, is shown to approximate the Bayes optimal discriminant function. The result is demonstrated for both the two-class problem and multiple classes. It is shown that the outputs of the multilayer perceptron approximate the a posteriori probability functions of the classes being trained. The proof applies to any number of layers and any type of unit activation function, linear or nonlinear.


title: An Efficient Active Learning Framework for New Relation Types

text: Supervised training of models for semantic relation extraction has yielded good performance, but at substantial cost for the annotation of large training corpora. Active learning strategies can greatly reduce this annotation cost. We present an efficient active learning framework that starts from a better balance between positive and negative samples, and boosts training efficiency by interleaving self-training and co-testing. We also studied the reduction of annotation cost by enforcing argument type constraints. Experiments show a substantial speed-up by comparison to the previous state-of-the-art pure co-testing active learning framework. We obtain reasonable performance with only 150 labels for individual ACE 2004 relation


title: Complications during root canal irrigation--literature review and case reports.

text: LITERATURE REVIEW AND CASE REPORTS: The literature concerning the aetiology, symptomatology and therapy of complications during root canal irrigation is reviewed. Three cases of inadvertent injection of sodium hypochlorite and hydrogen peroxide beyond the root apex are presented. Clinical symptoms are discussed, as well as preventive and therapeutic considerations.


title: Neural Machine Translation Advised by Statistical Machine Translation

text: Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years. However, recent studies show that NMT generally produces fluent but inadequate translations (Tu et al. 2016; He et al. 2016). This is in contrast to conventional Statistical Machine Translation (SMT), which usually yields adequate but non-fluent translations. It is natural, therefore, to leverage the advantages of both models for better translations, and in this work we propose to incorporate SMT model into NMT framework. More specifically, at each decoding step, SMT offers additional recommendations of generated words based on the decoding information from NMT (e.g., the generated partial translation and attention history). Then we employ an auxiliary classifier to score the SMT recommendations and a gating function to combine the SMT recommendations with NMT generations, both of which are jointly trained within the NMT architecture in an end-to-end manner. Experimental results on Chinese-English translation show that the proposed approach achieves significant and consistent improvements over state-of-the-art NMT and SMT systems on multiple NIST test sets.


title: Leveraging Wikipedia Table Schemas for Knowledge Graph Augmentation

text: General solutions to augment Knowledge Graphs (KGs) with facts extracted from Web tables aim to associate pairs of columns from the table with a KG relation based on the matches between pairs of entities in the table and facts in the KG. These approaches suffer from intrinsic limitations due to the incompleteness of the KGs. In this paper we investigate an alternative solution, which leverages the patterns that occur on the schemas of a large corpus of Wikipedia tables. Our experimental evaluation, which used DBpedia as reference KG, demonstrates the advantages of our approach over state-of-the-art solutions and reveals that we can extract more than 1.7M of facts with an estimated accuracy of 0.81 even from tables that do not expose any fact on the KG.


title: Breaking out of the box of recommendations: from items to packages

text:
Classical recommender systems provide users with a list of recommendations where each recommendation consists of a single item, e.g., a book or DVD. However, several applications can benefit from a system capable of recommending packages of items, in the form of sets. Sample applications include travel planning with a limited budget (price or time) and twitter users wanting to select worthwhile tweeters to follow given that they can deal with only a bounded number of tweets. In these contexts, there is a need for a system that can recommend top-k packages for the user to choose from.
 Motivated by these applications, we consider composite recommendations, where each recommendation comprises a set of items. Each item has both a value (rating) and a cost associated with it, and the user specifies a maximum total cost (budget) for any recommended set of items. Our composite recommender system has access to one or more component recommender system, focusing on different domains, as well as to information sources which can provide the cost associated with each item. Because the problem of generating the top recommendation (package) is NP-complete, we devise several approximation algorithms for generating top-k packages as recommendations. We analyze their efficiency as well as approximation quality. Finally, using two real and two synthetic data sets, we subject our algorithms to thorough experimentation and empirical analysis. Our findings attest to the efficiency and quality of our approximation algorithms for top-k packages compared to exact algorithms.


title: Guided filtering for PRNU-based localization of small-size image forgeries

text: PRNU-based techniques guarantee a good forgery detection performance irrespective of the specific type of forgery. The presence or absence of the camera PRNU pattern is detected by a correlation test. Given the very low power of the PRNU signal, however, the correlation must be averaged over a pretty large window, reducing the algorithm's ability to reveal small forgeries. To improve resolution, we estimate correlation with a spatially adaptive filtering technique, with weights computed over a suitable pilot image. Implementation efficiency is achieved by resorting to the recently proposed guided filters. Experiments prove that the proposed filtering strategy allows for a much better detection performance in the case of small forgeries.


title: Intel MPX Explained: An Empirical Study of Intel MPX and Software-based Bounds Checking Approaches

text: Memory-safety violations are a prevalent cause of both reliability and security vulnerabilities in systems software written in unsafe languages like C/C++. Unfortunately, all the existing software-based solutions to this problem exhibit high performance overheads preventing them from wide adoption in production runs. To address this issue, Intel recently released a new ISA extension—Memory Protection Extensions (Intel MPX), a hardware-assisted full-stack solution to protect against memory safety violations. In this work, we perform an exhaustive study of the Intel MPX architecture to understand its advantages and caveats. We base our study along three dimensions: (a) performance overheads, (b) security guarantees, and (c) usability issues. To put our results in perspective, we compare Intel MPX with three prominent software-based approaches: (1) trip-wire—AddressSanitizer, (2) objectbased—SAFECode, and (3) pointer-based—SoftBound. Our main conclusion is that Intel MPX is a promising technique that is not yet practical for widespread adoption. Intel MPX’s performance overheads are still high (~50% on average), and the supporting infrastructure has bugs which may cause compilation or runtime errors. Moreover, we showcase the design limitations of Intel MPX: it cannot detect temporal errors, may have false positives and false negatives in multithreaded code, and its restrictions on memory layout require substantial code changes for some programs. This paper presents only the general discussion and aggregated data; for the complete evaluation, please see the supporting website: https://Intel-MPX.github.io/. Evaluation plots and section headings have hyperlinks to the complete experimental description and results.


title: Childhood predictors differentiate life-course persistent and adolescence-limited antisocial pathways among males and females.

text: This article reports a comparison on childhood risk factors of males and females exhibiting childhood-onset and adolescent-onset antisocial behavior, using data from the Dunedin longitudinal study. Childhood-onset delinquents had childhoods of inadequate parenting, neurocognitive problems, and temperament and behavior problems, whereas adolescent-onset delinquents did not have these pathological backgrounds. Sex comparisons showed a male-to-female ratio of 10:1 for childhood-onset delinquency but a sex ratio of only 1.5:1 for adolescence-onset delinquency. Showing the same pattern as males, childhood-onset females had high-risk backgrounds but adolescent-onset females did not. These findings are consistent with core predictions from the taxonomic theory of life-course persistent and adolescence-limited antisocial behavior.