ppxscal/embedding_network huggingface dataset:
NP-Completeness of (k-SAT,r-UNk-SAT) and (LSAT ≥ k,r-UNLSAT ≥ k)
Authors: Tianyan Deng, Daoyun Xu
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

k-CNF is the class of CNF formulas in which the length of each clause of every formula is k. The decision problem asks for an assignment of truth values to the variables that satisfies all the clauses of a given CNF formula. k-SAT problem is k-CNF decision problem. Cook [9] has shown that k-SAT is NP-complete for k &iquest; 3. LCNF is the class of linear formulas and LSAT is its decision problem. In [3] we present a general method to construct linear minimal unsatisfiable (MU) formulas. NP = PCP(log,1) is called PCP theorem, and it is equivalent to that there exists some r > 1 such that (3SAT, r-UN3SAT)(or denoted by $(1-\frac{1}{r})-GAP3SAT)$ is NP-complete [1,2]. In this paper,we show that for k &iquest; 3, (kSAT, r-UNkSAT) is NP-completre and (LSAT, r-UNLSAT) is NP-completre for some r > 1. Based on the application of linear MU formulas, [3] we construct a reduction from (4SAT, r-UN4SAT) to (LSAT &ge; 4,r'-UNLSAT &ge; 4), and proved that (LSAT &ge; 4,r - UNLSAT &ge; 4) is NP-complete for some r > 1, so the approximation problem s-Approx-LSAT &ge; 4 is NP-hard for some s > 1.
Overview of QAST 2007
Authors: Jordi Turmo, Pere R. Comas, Christelle Ayache, Djamel Mostefa, Sophie Rosset, Lori Lamel
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes QAST, a pilot track of CLEF 2007 aimed at evaluating the task of Question Answering in Speech Transcripts. The paper summarizes the evaluation framework, the systems that participated and the results achieved. These results have shown that question answering technology can be useful to deal with spontaneous speech transcripts, so for manually transcribed speech as for automatically recognized speech. The loss in accuracy from dealing with manual transcripts to dealing with automatic ones implies that there is room for future reseach in this area.
Plenary lecture I: trends and challenges in RF-analog and mixed-mode signal designs for wireless applications
Authors: Ahmed El Oualkadi
Venue: Proceedings of the 7th WSEAS International Conference on Microelectronics, Nanoelectronics, Optoelectronics (2008)

The expansion of wireless services and other telecom applications increases the need for low-cost highly integrated solutions with very demanding performances and specifications. This requires the development of intelligent front-end architectures that circumvent the physical limitations posed by the semiconductor technology. In addition, with the evolution towards nanometer CMOS technologies, the design of complex systems-on-chip (SoC) is emerging in consumermarket applications such as telecom and multimedia. These integrated systems are increasingly mixed-mode signal designs, embedding high-performance analog blocks and possibly sensitive RF front-ends together with complex digital circuitry on the same chip. These complex RF and mixed-signal SOC designs require accurate prediction early in the design schedule, and time-tomarket pressures dictate that design iterations be kept to a minimum. As an example, emerging wireless applications for logistics (e.g., RFID, intelligent home networks, smart dusts, & wireless body area networks) will need integration and fusion of a diverse set of technologies. These technologies include digital CMOS circuits, analog/RF circuits, sensors, MEMS components, embedded software, memories, antennas, displays, polymers, packaging and interconnections, new materials, and new integration process. True system-level integration requires a new multidisciplinary design methodology that defines the optimal miniaturization path of a wireless device when product design begins. It spans the development cycle, from device- to system-level design, through electrical, thermal and mechanical analysis including characterization, and on to component selection, product assembly and test. However, the main challenge remains cost and power consumption. For RF IC design, optimizing the architecture for a given application is a key requirement when considering ultralow- power consumption. The RF-analog-digital mixed signal cosimulation environment is one of the major challenges since many functional blocks depend on both analog and digital designs, to fully exercise and verify the proper functionality of those tunable and programmable loops. To have short and reliable design cycles, efficient verification methods and tools are necessary. Modeling and simulation need to accompany the design steps from the specification to the overall system verification in order to bridge the gaps between system specification, system simulation, and circuit level simulation. Very high carrier frequencies together with long observation periods result in extremely large computation times and requires, therefore, specialized modeling methods and simulation tools on all design levels.
Avatar Puppetry Using Real-Time Audio and Video Analysis
Authors: Sylvain Gallou, Gaspard Breton, Renaud Séguier, Christophe Garcia
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

We present a system which consists of a lifelike agent animated in real-time using video and audio analysis from the user. This kind of system could be used for Instant Messaging where an avatar controlled like a puppet is displayed instead of the webcam flow. The overall system is made of video analysis based on Active Appearance Models and audio analysis based on Hidden Markov Model. The parameters from these two modules are sent to a control system driving the animation engine. The video analysis extracts the head orientation and the audio analysis provides the phonetic string used to move the lips.
EmoVoice -- A Framework for Online Recognition of Emotions from Voice
Authors: Thurid Vogt, Elisabeth André, Nikolaus Bee
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

We present EmoVoice, a framework for emotional speech corpus and classifier creation and for offline as well as real-time online speech emotion recognition. The framework is intended to be used by non-experts and therefore comes with an interface to create an own personal or application specific emotion recogniser. Furthermore, we describe some applications and prototypes that already use our framework to track online emotional user states from voice information.
A Model for Securing E-Banking Authentication Process: Antiphishing Approach
Authors: Antonio San Martino, Xavier Perramon
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

This paper presents the authentication environment defined for securing E-Banking applications. The proposed method is part of a Phd Doctoral thesis aimed at defining a model for secure operation of an Internet Banking environment, even in the presence of malware on the client side. The authentication model has been designed to be easily applicable with minimum impact to the current Internet banking systems. Its goal is to be resistant to the nowadays too frequent phishing and pharming attacks, and also to more classical ones like social engineering or man-in-the-middle attacks. The key point of this model is the need for multifactor mutual authentication, instead of simply basing the security on the digital certificate of the financial entity, since in many cases users are not able to discern the validity of a certificate, and may not even pay attention to it. By following the rules defined in this proposal, the security level of the Web Banking environment will increase and customers’ trust will be enhanced, thus allowing a more beneficial use of this service.
Enthusiasm and Its Contagion: Nature and Function
Authors: Isabella Poggi
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

The paper presents a conceptual analysis of enthusiasm in terms of a goal and belief model of emotions. Enthusiasm is an emotion of the same family of joy, felt when an Agent believes she will very likely achieve a goal she is pursuing, because she has the necessary internal resources to achieve it. The function of enthusiasm is to enhance energy and persistence in goal pursuit. Some positive and negative aspects of the contagion of enthusiasm are presented and some empirical studies about enthusiasm and its contagion briefly overviewed.
A Biological Intelligent Access Control System Based on DSP and NIR Technology
Authors: Xingming Zhang, Yingshan Li, Zihao Pan, Wenjin Gu, Jianfu Chen
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Face recognition, fingerprint recognition and other biometric technology are used widely now, and requirement of safety and reliability of Access Control in the market is getting higher and higher. The paper designs and implements Intelligent Biometric Access Control System based on DSP and NIR technology. It mostly describes the overall design, embedded system design, near infrared camera design, face recognition and verification algorithm design in server. By using NIR technology the system fundamentally change the impact of illumination on face recognition and resolve the limitations of face recognition in applications.
Collective Reuse of Software Components Speeds-Up Reliability
Authors: Iaakov Exman, Guy Zohar, Yehuda Hassin
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

Reliable behavior of systems of autonomous agents --- such as collections of deployed robots --- is difficult to attain. Agents could provide mutual support, but lack of coordination may weaken, rather than increase reliability. We propose collective reuse of replaceable software components among autonomous agents, based upon a shared factory architecture. Coordinated replacement is achievable on-the-fly, whatever the component status: idle, runnable or actually running. Replacement propagation among agents grows faster with increasing numbers of agents for practical collection sizes, as measured by a reliability speedup. The architecture was demonstrated by simulations combining real and virtual robots.
New Algorithms to Map Asymmetries of 3D Surfaces
Authors: Benoît Combès, Sylvain Prima
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper, we propose a set of new generic automated processing tools to characterise the local asymmetries of anatomical structures (represented by surfaces) at an individual level, and within/between populations. The building bricks of this toolbox are: 1) a new algorithm for robust, accurate, and fast estimation of the symmetry plane of grossly symmetrical surfaces, and 2) a new algorithm for the fast, dense, non-linear matching of surfaces. This last algorithm is used both to compute dense individual asymmetry maps on surfaces, and to register these maps to a common template for population studies. We show these two algorithms to be mathematically well-grounded, and provide some validation experiments. Then we propose a pipeline for the statistical evaluation of local asymmetries within and between populations. Finally we present some results on real data.
Engineering Service Oriented Systems: A Model Driven Approach
Authors: Bill Karakostas, Yannis Zorgios
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

In this presentation we argue that a business value chain model drives the identification and modeling of business services, and the business oriented/technology neutral modeling language IDEF0, is used for modeling web services. We expect the next generation of advanced (i.e. intelligent/semantics-based) Web services to be generated and driven directly by business models, rather than laboriously hand-crafted. In our approach, a systemic view of services offers a declarative specification of what are the capabilities that the service delivers. More about the methodological aspects of our approach can be found in: “Engineering Service Oriented Systems: A Model Driven Approach” Bill Karakostas & Yannis Zorgios, IGI-Global, 2008, ISBN: 978-1-59904-968-7
Predicting Time Series Using Incremental Langrangian Support Vector Regression
Authors: Hua Duan, Weizhen Hou, Guoping He, Qingtian Zeng
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A novel Support Vector Regression(SVR) algorithm has been proposed recently by us. This approach, called Lagrangian Support Vector Regression(LSVR), is an reformulation on the standard linear support vector regression, which leads to the minimization problem of an unconstrained differentiable convex function. During the process of computing, the inversion of matrix after incremented is solved based on the previous results, therefore it is not necessary to relearn the whole training set to reduce the computation process. In this paper, we implemented the LSVR and tested it on Mackey-Glass time series to compare the performances of different algorithms. According to the experiment results, we achieve a high-quality prediction about time series.
Spatio-chromatic decorrelation for color image compression
Authors: Mark S. Drew, Steven Bergner
Venue: Image Communication (2008)

We investigate the implications of a unified spatio-chromatic basis for image compression and reconstruction. Different adaptive and general methods (principal component analysis, PCA, independent component analysis, ICA, and discrete cosine transform, DCT) are applied to generate bases. While typically such bases with spatial extent are investigated in terms of their correspondence to human visual perception, we are interested in their applicability to multimedia encoding. The performance of the extracted spatio-chromatic spatial patch bases is evaluated in terms of quality of reconstruction with respect to their potential for data compression. Since ICA is not as widely used as it should be, compared to the other decorrelation methods applied here in a new domain, we also provide a review of ICA. The results discussed here are intended to provide another path towards perceptually based encoding of visual data. This leads to a deeper understanding of the role played by chromatic features in data reduction.
A Classification Method of Children with Developmental Dysphasia Based on Disorder Speech Analysis
Authors: Marek Bártů, Jana Tučková
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

This paper focuses on method developed for classifications of the speech with disorders. We are interested in children's neurological disorder called developmental dysphasia and its influence on the speech. Described classification method is based on children's speech signal analysis and allows observing the trend of the speech disorder during therapy. The classification is based on the fact that the disorder has an direct impact on speech production (i.e. movement of vocal tract). Thus, we can measure the trend of the disorders comparing patterns obtained from speech of healthy children to the patterns obtained from children with disorder. Described method is based on cluster analysis of Kohonen Self-Organizing Maps (KSOMs) trained on speech signals. The main advantage of using artificial neural network is adaptability to specific attributes of the signal and tolerance for the noise contained in recordings.
A Feature Selection Algorithm Based on Discernibility Matrix
Authors: Fuyan Liu, Shaoyi Lu
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

A heuristic algorithm of reduct computation for feature selection is proposed in the paper, which is a discernibility matrix based method and aims at reducing the number of irrelevant and redundant features in data mining. The method used both significance information of attributes and information of discernibility matrix to define the necessity of heuristic feature selection. The advantage of the algorithm is that it can find an optimal reduct for feature selection in most cases. Experimental results confirmed the above assertion. It also shown that the proposed algorithm is more efficient in time performance comparing with other similar computation methods.
A Sequential Learning Algorithm for RBF Networks with Application to Ship Inverse Control
Authors: Gexin Bi, Fang Dong
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

A sequential learning algorithm for constructing radial basis function (RBF) network is introduced referred to as dynamic orthogonal structure adaptation (DOSA) algorithm. The algorithm learns samples sequentially, with both structure and connecting parameters of network are adjusted on-line. The algorithm is further improved by setting initial hidden units and incorporating weight factors. Based on the improved DOSA algorithm, a direct inverse control strategy is introduced and applied to ship control. Simulation results of ship course control simulation demonstrate the applicability and effectiveness of the improved DOSA algorithm and the RBF network-based inverse control strategy.
Predicting Binding Sites of Hepatitis C Virus Complexes Using Residue Binding Propensity and Sequence Entropy
Authors: Guang-Zheng Zhang, Chirag Nepal, Kyungsook Han
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Hepatitis C virus (HCV) remains a dangerous health problem for the reason that the mechanism of hepatocyte infection is still unknown. Hence, much attention has been put on the problem of interaction between HCV and human proteins. However, the research is still standing at the beginning point due to the lack of structure information of HCV and human proteins. We extracted the most representative set of 18 complexes all known HCV protein complexes involving human proteins, and computed the binding propensity of each residue and sequence entropy of each HCV protein. analyzed the most representative set of 18 complexes. Using a radial basis function neural network (RBFNN), we predicted binding sites with an overall sensitivity of 77%. The approach will help understand the interaction between HCV and human proteins.
Dynamical Nonstationarity Analysis of Resting EEGs in Alzheimer's Disease
Authors: Charles-Francois Vincent Latchoumane, Emmanuel Ifeachor, Nigel Hudson, Sunil Wimalaratna, Jaeseung Jeong
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

The understanding of nonstationarity, from both a dynamical and a statistical point of view, has turned from a constraint on application of a specific type of analysis (e.g. spectral analysis), into a new insight into complex system behavior. The application of nonstationarity detection in an EEG time series plays an important role in the characterization of brain processes and the prediction of brain state and behavior such as seizure prediction. In this study, we report a very significant difference in the mean stationarity duration of an EEG over the frontal and temporal regions of the brain, comparing 22 healthy subjects and 16 patients with mild Alzheimer's disease (AD). The findings help illuminate the interpretation of the EEG's duration of dynamical stationarity and proposes to be useful for distinguishing AD patients from control patients. This study supports the idea of a compensatory activation of the fronto-temporal region of the brain in the early stages of Alzheimer's disease.
Efficient Processing of Nearest Neighbor Queries in Parallel Multimedia Databases
Authors: Jorge Manjarrez-Sanchez, José Martinez, Patrick Valduriez
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

This paper deals with the performance problem of nearest neighbor queries in voluminous multimedia databases. We propose a data allocation method which allows achieving a $0(\sqrt{n})$ query processing time in parallel settings. Our proposal is based on the complexity analysis of content based retrieval when it is used a clustering method. We derive a valid range of values for the number of clusters that should be obtained from the database. Then, to efficiently process nearest neighbor queries, we derive the optimal number of nodes to maximize parallel resources. We validated our method through experiments with different high dimensional databases and implemented a query processing algorithm for full k nearest neighbors in a shared nothing cluster.
The Application of Real Time Tracking Technologies in Freight Transport
Authors: Yingli Wang, Andrew Potter
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

With the recent rapid development of information and wireless communication technologies, there is an increasing use of real time tracking in the freight transport practices. However our understanding of the impact of such technologies on the supply chain structure and logistics performance has been very limited. Through an in-depth examination of a case example in UK’s FMCG industry, this research explores how the tracking system has been implemented, and examines the impact it brings to both the shippers and the carriers. Both technical and, managerial issues are discussed along the analysis of costs and benefits. The research reveals that the use of real time tracking technology in logistics is still at its infancy stage in the UK, but with great potential to grow in the future. Alternative technologies for example RFID are compared against vehicle telematics systems used in the case, along with a brief summary of advantages and disadvantages of each.
How to Protect Yourself without Perfect Shredding
Authors: Ran Canetti, Dror Eiger, Shafi Goldwasser, Dah-Yoh Lim
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

Erasing old data and keys is an important tool in cryptographic protocol design. It is useful in many settings, including proactive security, adaptive security, forward security, and intrusion resilience. Protocols for all these settings typically assume the ability to perfectly erase information. Unfortunately, as amply demonstrated in the systems literature, perfect erasures are hard to implement in practice.We propose a model of partial erasures where erasure instructions leave almost all the data erased intact, thus giving the honest players only a limited capability for disposing of old data. Nonetheless, we provide a general compiler that transforms any secure protocol using perfect erasures into one that maintains the same security properties when only partial erasures are available. The key idea is a new redundant representation of secret data which can still be computed on, and yet is rendered useless when partially erased. We prove that any such a compiler must incur a cost in additional storage, and that our compiler is near optimal in terms of its storage overhead.