Miracle-dz/UniFAR-FTUs huggingface dataset:
Error Detection for Floating-Point Program via Branch and Bound Method

It is well-known that writing an error-free floating-point program is very difficult. Thus, detecting unacceptable errors of a floating-point program is important. In this paper, we develop a system named SpaceAED. The main function of this system is to automatically detect unacceptable errors of a floating-point program written in C programming language. The key insight of this work is to use interval arithmetic in conjunction with branch and bound technique. The implementation of SpaceAED is to rewrite a floating-point program to one that can run on interval arithmetic, and then use branch and bound technique to find all inputs that can trigger unacceptable errors. We choose a great many of functions in GNU Scientific Library (GSL) to test SpaceAED, including matrix computations and evaluation of special functions etc. Numerical results show that SpaceAED is available for accurately detecting unacceptable error-triggering inputs of numerical functions.
A Review on Speech Synthesis an ArtificialVoice Production

Speech is used to convey emotions, feelings and information. It has began from day one when human beings start to communicate. Speech synthesis, also called text-to-speech, is the generation of synthetic speech. An application or other process sends text to a speech synthesizer, which creates a spoken version that can be output through the audio hardware or saved to a file. This paper deals with some methods of speech synthesis. Speech synthesis has very wide range of applications, which are reviewed in later part of the paper.
Comparison of CBIR Techniques using DCT and FFT for Feature Vector Generation

In recent years, the accelerated growth of digital media collections has established the need for the development of tools for the efficient access and retrieval of visual information . The paper presents innovative content based image retrieval (CBIR) techniques based on feature vectors as DC coefficients of transformed images using DCT and FFT. Here the feature vector size per image is greatly reduced by taking only DC coefficients of each R, G, and B component of transformed image. The proposed CBIR techniques are implemented on a database having 1000 images spread across 10 categories. For each proposed CBIR technique 50 queries (5 per category) are fired on the database and net average precision and recall are computed for all feature sets per transform. Finally FFT surpasses DCT transforms in performance with highest precision and recall values.
EM radiation behavior upon biological tissues in a radio-frequency power transfer link for a cortical visual implant

This paper presents a method to evaluate the interactions between a radio-frequency power transfer link and biological tissues. First the authors analyze the propagation of a plane wave model at the skin interface to evaluate the frequency that optimize the transfer ratio. They then use the Finite-Difference Time-Domain method to calculate the exact electromagnetic fields propagation in a discrete 3D space and time for a box brain model with an inductive emitting antenna. The results exhibit the electric field pattern in the antenna axis plane and in the back of the head. They show for an optimized frequency carrier (20 MHz) that the attenuation of electric field strength is 15 dB and that most of the energy is reflected at the air-tissue interface.
Speech Signal processing 2010

Master General Linguistics Module Speech Signal Processing Code TW85231 Points 5 ECTS Precondition Master, reasonable mathematical background or affinity Period Semester 2, block 1 (February–March 2010) Information Onderwijssecretariaat Taalen Letterkunde also IFA teaching also The page in the studiegids Teacher David Weenink Time & Place Wednesday 9:00–12:00, Bungehuis K302 Language English Book SSPBook:D.J.M. Weenink, Speech signal processing by Praat, To be published in 2009/10 (book will change during the course, don’t print it)
EFFICIENT PROCESSING OF JOB BY ENHANCING HADOOP MAPREDUCE FRAMEWORK

Cloud Computing uses Hadoop framework for processing BigData in parallel. The Hadoop Map Reduce programming paradigm used in the context of Big Data, is one of the popular approaches that abstract the characterstics of parallel and distributed computing which comes off as a solution to Big Data. Improving performance of Map Reduce is a major concern as it affects the energy efficiency. Improving the energy efficiency of Map Reduce will have significant impact on energy savings for data centers. There are many parameters that influence the performance of Map Reduce . Various parameters like scheduling, resource allocation and data flow have a significant impact on Map Reduce performance. Cloud Computing leverages Hadoop framework for processing BigData in parallel. Hadoop has certain limitations that could be exploited to execute the job efficiently. Efficient resource allocation remains a challenge in Cloud Computing MapReduce platforms. We propose a methodology which is an enhanced Hadoop architecture that reduces the computation cost associated with BigData analysis.
Information processing system, information processing apparatus and method

In Failure to operate as expected by the user, to determine if there were a expected from any point of view, provides a technique for responding closer to expectations. The information processing system according to the present invention comprises a reaction unit for executing first processing based on the request of the user, and an output unit for outputting the result of the processing, a signal detection unit for measuring a signal related to an event-related potential of the user electroencephalogram, identifying vertices positive event-related potential from the signal, the result is the amount of time elapsed since the output until a vertex, and determining the analysis unit to close or to any of the first reference time and a second reference time, determining and a reaction correction unit for determining a second processing in accordance with the result. This judgment result indicates the degree of disappointing the user, the second process is determined depending on the degree. By reaction unit to execute a second processing, operating along the user's expectations even if you did not able to operate as expected of a user can be realized.
On the true multilook intensity distribution in SAR imagery

The speckle intensity after the multilooking process is generally modelled as a gamma distributed random variable. This is definitely true only if the averaging is performed with uncorrelated samples of equal mean radiometry, each one distributed by a negative exponential function. If the samples still follow this negative exponential distribution, but are correlated or have different mean radiometry, the gamma distribution function is only an approximation of the true probability density function (pdf). J.W. Goodman derived the exact distribution resulting from an incoherent summation of correlated samples with unequal mean power. This exact probability density function was not used to describe the multilook speckle intensity up to now. In this communication, the authors show how to fit the true distribution, mainly when the gamma pdf is still used.
Combining augmented statistical noise suppression and framewise speech/non-speech classification for robust voice activity detection

This paper proposes a new voice activity detection (VAD) algorithm based on statistical noise suppression and framewise speech/non-speech classification. Although many VAD algorithms have been developed that are robust in noisy environments, the most successful ones are related to statistical noise suppression in some way. Accordingly, we formulate our VAD algorithm as a combination of noise suppression and subsequent framewise classification. The noise suppression part is improved by introducing the idea that any unreliable frequency component should be removed, and the decision can be made by the remaining signal. This augmentation can be realized using a few additional parameters embedded in the gain-estimation process. The framewise classification part can be either model-less or model-based. A model-less classifier has the advantage that it can be applied to any situation, even if no training data are available. In contrast, a model-based classifier (e.g., neural network-based classifier) requires training data but tends to be more accurate. The accuracy of the proposed algorithm is evaluated using the CENSREC-1-C public framework and confirmed to be superior to many existing algorithms.
Large scale simulations of a spin glass image associative memory

Large scale parallel simulations of a spin glass associative memory are described. As a massively parallel neural network architecture, it is similar to the Boltzmann Machine, but is based on the material and physical characteristics of spin glasses and the use of opto-magnetic control. The system is designed to learn, store, and recall very high dimensional binary patterns vectors. Performance results of the system's autoassociative learning and recall capabilities on a 4996 bit Coca-Cola trademark image are discussed. <<ETX>>
ITS and incident management: a problem in fragmented governance

Intelligent transportation systems (ITS) programs have introduced new strategies for minimizing the social impacts of traffic incidents. ITS has funded programs for sensing the flow of traffic, detecting incidents through changes in flow characteristics and diagnosing incident severity through closed circuit television. To date, ITS programs have supported incident management strategies that focus on pretrip and en-route information for the driving public. Of limited consideration has been the application of ITS technologies to activities taking place at the incident site. First responders depend upon mobile cellular calls sent free of charge over emergency number systems for incident detection. First responders' communications centers receive the cells and often process them by hand. The message is sent from the intake officer to the dispatcher by foot. At this point the message is sent over low band two way radio into the distortion and shadow areas created in hilly metropolitan areas. Each of these functions can be improved through the use of ITS. Each function can be integrated into state Departments' of Transportation procurement and personnel management practices such that both regional and an site incident management work together to reduce congestion.
Characterization and Modeling of M2M Video Surveillance Traffic

—The relevance of machine-to-machine (M2M) communications is growing signiﬁcantly, largely driven by wireless networks. Internet of Things (IoT) applications will create new demands and challenges that will require high bandwidth, real-time communications or reliability in remote locations. Since M2M applications will generate trafﬁc and transactions that compete for bandwidth and priority, network operators must be concerned of how to handle the enormous increases in their signaling trafﬁc and, in particular, in ﬁnding new ways to meet each M2M application’s requirements and service level agreements, while protecting the network and making a more efﬁcient use of the available resources. An efﬁcient design and control of the future Internet needs to take into account the main characteristics of the supported trafﬁc and, therefore, accurate and detailed measurements of M2M trafﬁc have to be carried out in order to perform a complete characterization and develop stochastic models that are able to capture the most important statistical properties of the network trafﬁc. This paper considers a particular case of a M2M service, a video surveillance application, and proposes a general methodology that performs a detailed statistical characterization of its trafﬁc, while addressing the main challenges that are involved in the development of an appropriate stochastic modeling approach. The M2M trafﬁc analysis relies on the use of wavelet scalograms, which describe the signal energy on a timescale/time domain and are constructed based on the wavelet coefﬁcients obtained from the multi-scale decomposition of the trafﬁc process, to identify all the different trafﬁc features. An innovative M2M modeling framework based on a multiple state machine is also proposed: its parameters should be inferred from the salient features of the trafﬁc and it should be able to characterize both the download and upload trafﬁc and quantify the overhead that is necessary to guarantee a secure communication.
Evolutionary artificial neural networks

We present experiments which show that a genetic algorithm (GA) can effectively search for a set of local feature detectors, which can be used by higher neural network layers to perform an image classification task. Three different methods of encoding hidden unit weights into the GA are presented, including one which coevolves all the feature detectors in a single chromosome, and two which promote the cooperation of feature detectors by encoding them in their own chromosome. The fitness function measures the classification percentage and confidence of the networks on validation data in order to encourage generalization.
Dynamic brain networks measured by using phase synchronization across different seizure patterns

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Tactile Sensors and Displays for Non-conscious Tactile Sensation

1. はじめに 触覚 . の覚は自覚 . の覚だろうか? そもそも「覚」とは「意識 的に感じる」という意味である. したがって,語源通りに受 け入れるならば,触覚の覚は自覚の覚であるといえよう. し かし,ヒトの触覚はそんなに単純ではない. 図 1 に示したよ うに,触覚の伝達先は少なくとも 3 つある. ひとつめは,私 たちが「つるつる」や「すべすべ」,「こり」や「しこり」の クオリアを知覚する,意識下の触覚である. このような,い わゆる触感は,触覚受容器で発射された神経インパルスが, 脊髄に入り,上昇し,大脳新皮質の感覚野に到達し,そこで 情報処理された結果として知覚される. ふたつめは,筆者が これまで関わってきた把持力制御のようなケースである. ヒ トは,重さと摩擦係数が不明の物体を,滑り落とさず,かつ, 握りつぶさないようなちょうど良い把持力(最小限必要な把 持力の 1.3 倍から 1.5 倍の力)で把持し持ち上げることがで きる. これは,指と物体の接触面の状態がフィードバック 情報として利用され,無意識下で把持力がフィードバック制 御されているためである. このとき,“どのくらい滑り落と しそうか”というような触感が自覚されるわけではないにも かかわらず,無意識下でフィードバック制御が行われている 点が興味深い. この制御は下位中枢で行なわれていると考え られる. 3 つめは,「熱い」「痛い」といった触覚情報が下位 中枢にフィードバックされた結果,反射的に手を離すといっ た制御(脊髄反射)である. 脊髄反射は無意識下で行われ, 大脳皮質に熱い・痛いといった情報が伝達され意識されるの はその後である. 以上のように,触覚は下位中枢における無 自覚 . なフィードバック制御に使わる場面が少なくないにも 関わらず,触覚の研究者の多くは意識下の触覚を研究対象に している. 本稿では,あまのじゃくな筆者は,無自覚 . な方の 触覚 . のひとつ,把持力の制御問題について述べる.
Evaluation of Data Currency Relative to Users for Incomplete or Partly Erroneous Data

The incomplete or partly erroneous data can usually cause the poor currency and badly influence on the peoples daily lives. The evaluation of data currency for incomplete or partly erroneous data is closely related to users. However, the data coming from different data sources do not carry reliable timestamps. So this paper focus on evaluation of data currency to users for incomplete or partly erroneous data with the redundant records and currency orders of data. Firstly, in order to better illustrate, we introduce the basic definitions and knowledge associated with the data currency relative to users. Secondly, we study the data currency relative to users and the algorithm to evaluate the data currency by using the method of Data Recovery. Finally, experimental results on real are shown to compare the data currency of three types of users to query and to analyze the effect of parameters.
Efficient M2M Gateway Planning for Next-Generation Cellular Networks

ABSTRACT Machine-to-machine (M2M) communications and applications are expected to play a significant role in the next-generation wireless networks. M2M communication features a myriad of devices (machines), generating a massive number of intermittent, small-sized data transmissions. Traditionally, gateways are used to provide wireless connectivity to such a large number of devices. However, with the emerging concept of Internet of Things (IoT) and 5G wireless technology, the number of devices is expected to increase exponentially. This exponential increase in the number of devices raises a significant question in the ability of traditional gateways to provide connectivity and schedule uplink transmissions. In this paper, we propose a novel Grouping and Adaptive Compression (GAC) strategy in the M2M gateways to reduce the number of uplink requests. The gateways first group the machines into different clusters and subsequently explore adaptive compression to reduce the uplink traffic to the base stations (BS). Simulation results on typical M2M communications demonstrate that our proposed GAC algorithm reduces the number of uplink requests and corresponding radio resource requirement by around 60% and 50%, respectively. Moreover, it also increases the existing BS capacity by almost 10 times in terms of M2M devices, thus addressing the key challenge of the exponential increase in M2M deployment.
Event driven timeline displays: beyond message lists in human-intelligent system interaction

One aspect of human-intelligent system cooperation is the set of mechanisms that help the human track the intelligent system's assessment, recommendations, or actions with regard to the monitored process. The deficiencies of message lists for this purpose are outlined, and alternatives are discussed. The first step is to recognize that message lists are just one instance of temporally organized displays of information. A generic timeline display for event-driven applications such as human-intelligent system interaction in fault management is presented. In this domain, the cognitive task is to track and understand the sequence of events following a fault. This includes automatic and manual activities to ensure safety and intelligent system situation assessments, diagnoses, and recommended corrective actions in relation to the events in the monitored process. <<ETX>>
A Low Energy Time Based Clustering Technique for Routing in Wireless Sensor Networks

A Wireless sensor network (WSN) is a collection of tiny sensor nodes that are deployed to monitor the environment. These sensor nodes have limited capabilities, especially the energy reserve and processing ability. So, the routing protocols design for this kind of networks is a crucial challenge. Because these routing protocols should be simple, energy-efficient, and robust to deal with a very large number of nodes, they should also be self-configurable to node failures and changes of the network topology dynamically. The most proposed routing techniques organize the network in clusters where the sensing area is divided into many sub-areas. This paper presents a new algorithm for clustering in WSN based on the node residual energy compared to the network one and allowing a better partitioning of the network area which enhance the data distortion at the sink by using the best data coding rate at the cluster head. The simulation results show that this algorithm allows network stability extension compared to the most known clustering algorithm.
DIGITAL AUDIO WATERMARKING APPLICATIONS AND TECHNIQUES

Digital audio watermarking is nowadays gaining popularity among the original audio content producers. It provides a way to the owner to prove ownership by using watermark which forms integral part of audio. An approach is made in this paper to collectively introduce applications and techniques up till developed for audio watermarking.The proposedalgorithm is based on wavelet transform which has efficient computational load and also on cosine transform for increasing the watermark embedding capacity.
Data fragmentation and allocation algorithms for distributed database design

In a distributed database system data fragmentation and allocation are the major design issues. This dissertation presents a set of algorithms for fragmentation (or partitioning) and allocation. The relational model of data is assumed for convenience. The algorithms can be applied to other data models with minor variations. The partitioning of a global schema into fragments can be performed in two different ways: vertical partitioning and horizontal partitioning. Vertical partitioning is the process of subdividing the attributes of a relation or a record type into multiple records, thereby creating fragments. Horizontal partitioning is the process that divides a global relation into subsets of tuples, called horizontal fragments. In this dissertation a new vertical partitioning algorithm is presented. This algorithm starts from the attribute affinity matrix by considering it as a complete graph. Then, forming a linearly connected spanning tree, it generates all meaningful fragments simultaneously. A new horizontal partitioning algorithm is also presented, which is developed by applying the same graphical technique as in vertical partitioning. The need for mixed partitioning arises because database users usually access data subsets which are simultaneously vertical and horizontal fragments of global relations. However, this problem has not been addressed well in the current literature. A mixed partitioning methodology, which first forms a grid by partitioning a global relation vertically and horizontally in an independent fashion and then produces the final fragments (called mixed fragments) by merging the grid cells, is addressed. In most of the previous allocation work, the unit of allocation is the fragment that results from horizontal partitioning or vertical partitioning. Little work has been done for the allocation of the result of mixed partitioning. This dissertation presents an allocation algorithm for fragments that are generated from our mixed partitioning procedure. In this algorithm a mixed fragment is the unit of allocation. This algorithm is developed based on a heuristic called the pseudoallocation technique. The contribution of this dissertation consists of providing efficient graph oriented algorithms for partitioning, developing a mixed partitioning approach to distribution and a new approach to fragment allocation in distributed databases.
Preface to Learning Design: A Handbook on Modelling and Delivering Networked Education and Training

Abstract: In March 2002, thirty-three experts in e-learning from four continents met each other for the first time in Valkenburg aan de Geul, a small village in the south of The Netherlands. Since then, the group, referred to as the Valkenburg Group, has met several times at different locations to explore how to improve the pedagogical quality of e-learning courses, in an interoperable way, with user-friendly tools. The general feeling of the experts was that most of the current e-learning offerings lack one or more of these aspects: they are of poor pedagogical quality, they lack portability, or they lack adequate tooling. Pedagogical quality is considered to be the key issue. To be successful, e-learning must offer effective and attractive courses and programmes to learners, while at the same time providing a pleasant and effective work environment for staff members who have the task of developing course materials, planning the learning processes, providing tutoring, and assessing performance. Editors: Colin Tattersall and Rob Koper. N.B. This article is reproduced with permission from Koper, R. and Tattersall, C. (2005) (Eds.) Learning Design: A handbook on modelling and delivering networked education and training. Berlin: Springer. More information about the book is available from http://www.springeronline. com/sgw/cda/frontpage/0,0,5-0-22-36633821-0,0.html [link checked 24 August 2005] or from http://www.springer. com/computer/general+issues/book/978-3-540-22814-1 [link checked 26 August 2010]