ppxscal/embedding_network huggingface dataset:
Parallel and Distributed Visualization: The State of the Art
Authors: Ali Meligy
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

Visualization is one of the most important applications of computer graphics. To have a parallel infrastructure for visualization, some technologies would be needed. We identify the state-of-the-art technologies that have prepared for building such an infrastructure and examine a collection of applications that would benefit from it. We consider a broad range of scientific and technological advances in visualization, which are relevant to visual supercomputing. Mainly, we present the original abstracts from the cited papers.
Stability Analysis of AQM Algorithm Based on Generalized Predictive Control
Authors: Xing-Hui Zhang, Kuan-Sheng Zou, Zeng-Qiang Chen, Zhi-Dong Deng
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The network congestion has become increasingly serious. So many active queue management (AQM) algorithms used in routers have been proposed to alleviate network congestion.Generalized predictive control (GPC) is an effective control strategy, which has been widely applied in nonlinear and time-delay systems. This paper mainly analyses the stability of GPC as an AQM algorithm. It educes the discrete model of the network based on the fluid-flow model of TCP congestion window, then elicits the closed loop transfer function of router's output queue length with reference queue length. When the length of predictive region isn't smaller than system total time delay, it gives the characteristic equation of the closed loop system in one-step control. Then conditions of system stabilization are proved with jury criterion, and it gives three theorems about system stability. The validity of theorems is verified by simulation results.
SEM: A Security Evaluation Model for Inter-domain Routing System in the Internet
Authors: Xin Liu, Peidong Zhu, Yuxing Peng
Venue: Proceedings of the 8th IEEE international workshop on IP Operations and Management (2008)

Since the lack of necessary security mechanisms, the Internet's inter-domain routing system, mainly based on the Border Gateway Protocol (BGP), inevitably faces with serious security threats. Although there are many researches focus on the security of inter-domain routing and BGP, few people have quantified the routing security of the current BGP system effectively. Moreover, Internet operators do need useful information to judge security threats of their autonomous systems (ASes) and BGP routers. In this paper, we propose a security evaluation model, SEM, to assess security threats of the routing system. The basic idea of SEM is simple, namely, the security status of the whole system rests with its parts'. In addition, we quantify security threats status of the routing information from RouteViews using our model. The experimental results show that the model can provide intuitive security threat indices for BGP routers, various ASes and the BGP system respectively, and further more, it can provide valuable, intuitional curve for Internet operators.
Parameterized Gait Synthesis
Authors: Michiel van de Panne
Venue: IEEE Computer Graphics and Applications (1996)

A method of producing gaits is presented that uses control mechanisms analogous to windup toys. The synthesis technique is based on optimization. One primary characteristics of the "virtual windup toys" is that they are oblivious to their environment. This means that the simulated creatures have no active control over balance. Nevertheless, "blind" control mechanisms work well for many common periodic gaits as well as aperiodic motions such as turns and leaps. The possibilities and limitations of the technique are presented in the context of example creatures having one, two, four, and six legs. An important attribute of the proposed synthesis method is that the motions produced can be parameterized. Instead of producing a fixed instance of a motion, a family of motions can be synthesized. Examples presented are a hopping gait parameterized with respect to speed, a turning walk parameterized with respect to the turning rate, and a leaping gait parameterized with respect to the size of the leap. The animator can thus interactively specify the hopping speed, turning rate, and leap size, respectively, for these physics-based motions.
"I Would Like to Trust It but" Perceived Credibility of Embodied Social Agents: A Proposal for a Research Framework
Authors: Federico Tajariol, Valérie Maffiolo, Gaspard Breton
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

We suggest a research framework to evaluate users' perceived credibility when they interact with an ESA. Our research framework only addresses ESA's nonverbal features, thus we do not take the content and the rhetorical arguments of the message delivered by ESAs into account.
Can Tsunami Waves in the South China Sea Be Modeled with Linear Theory?
Authors: Yingchun Liu, Yaolin Shi, Hailing Liu, Shuo M. Wang, David A. Yuen, Hui Lin Xing
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

We have compared the results from linear and nonlinear theories of the shallow-water equations applied to the South China Sea. Our results indicate that tsunami waves in the South China Sea can be modeled with linear theory. There is little difference in the probability predicted by nonlinear theory and that forecasted by linear treatment on tall waves, more than two meters high, which may impinge on Hong Kong, Macau and Taiwan. This probability is estimated to be 10% in the next century.
Eliciting Motivation Knowledge from Log Files Towards Motivation Diagnosis for Adaptive Systems
Authors: Mihaela Cocea, Stephan Weibelzahl
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Motivation is well-known for its importance in learning and its influence on cognitive processes. Adaptive systems would greatly benefit from having a user model of the learner's motivation, especially if integrated with information about knowledge. In this paper a log file analysis for eliciting motivation knowledge is presented, as a first step towards a user model for motivation. Several data mining techniques are used in order to find the best method and the best indicators for disengagement prediction. Results show a very good level of prediction: around 87% correctly predicted instances of all three levels of engagement and 93% correctly predicted instances of disengagement. Data sets with reduced attribute sets show similar results, indicating that engagement level can be predicted from information like reading pages and taking tests, which are common to most e-Learning systems.
Reduce Feature Based NN for Transient Stability Analysis of Large-Scale Power Systems
Authors: Youping Fan, Min Xiong, Lu Liu, Jiguan Men, Cheng Tan, Yunping Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Aiming at the existence of relativity between repeat or similar samples and character parameters during diagnosis of character data, this paper presents an effective data analysis approach for character data compression from bi-direction, which can reduce the burden of learning machine without losing the connotative character knowledge of character data. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity measurement of principle component core for vertical reduction by using related mechanism of clone selection as well as immune network self-stabilization in organism natural immune system for reference. Finally, to analyze machine behavior quantitatively, a pattern discrimination model based on a cerebellar model articulation controller neural network (NN) was developed. Simulation experiments proved the effectiveness of this algorithm.
Wire sweep issue in a newly developed quad flat no-lead (QFN) semiconductor package
Authors: S. Abdullah, Z. A. Aziz, I. Ahmad, A. Jalar, M. F. Abdullah
Venue: Proceedings of the 7th WSEAS International Conference on Microelectronics, Nanoelectronics, Optoelectronics (2008)

The deflection of gold wire bonds during the encapsulation of IC packaging can seriously cause wire crossover and shorting. To date, there is no standard procedure has been proposed to decide a better bond looping system for optimal adjusting parameter of wire bonder to obtain lower deflection of wire bond. Thus, the objectives of this paper is to investigate the effect of looping parameter and mold compound flow related to wire sweep issue, so that, the correlation between these two was observed. A wire sweep condition in a semiconductor package is defined as the distance of deflection per bond span. Lower wire sweep possesses higher sweep stiffness and thereby higher rate of semiconductor package. In this paper, three looping parameters have been analyzed, i.e. kink height, reverse motion and loop factor, for which they have considered to perform nine combinations of looping formations. The results pointed out that the looping formation with higher loop height and wire payout gave the higher readings of wire sweep.
Comparisons of attitudes toward computer use and computer technology based on gender and race/ethnicity among eighth graders
Authors: James H. Mcmillan
Venue:  (2007)

The purpose of this study is to determine whether or not having a laptop computer for individual use 24-hours-a-day, seven-days-a-week lessens differences between how eighth grade girls and eighth grade boys in 10 middle schools in Henrico County, Virginia perceive computer use and computer technology. Having a laptop computer to use at any time of the day or night eliminates the issue of competition between boys and girls for computer use. It also eliminates the need for either girls or boys to perform in front of other students while learning, thus lessening to some degree, feelings of computer anxiety. Competition for computer access and computer anxiety are two theories that have been offered to explain why many young women in previous studies have chosen not to use computers to the same extent that young men do, as well as why many young women generally do not consider computer-related careers as career options in their futures. A modified Computer Attitude Questionnaire, based upon the CAQ, Version 5.14 was used to survey eighth grade girls and boys in 10 Henrico County middle schools. Data collected from the surveys were analyzed using the statistical package, SPSS 14 for Windows. Comparisons were based on gender and on the self-reported race/ethnicity of the participants. A comparison of attitudes related to the number of computers already in the home in addition to the school-issued laptop was also conducted. A variety of statistical analyses were used in order to determine differences in attitudes between the boys and girls surveyed and the interactions between the attitudes of the respondents and their race/ethnicity. This was a non-experimental, quantitative, comparative research study.
Analyzing an Electronic Cash Protocol Using Applied Pi Calculus
Authors: Zhengqin Luo, Xiaojuan Cai, Jun Pang, Yuxin Deng
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

Untraceability and unreuseability are essential security properties for electronic cash protocols. Many protocols have been proposed to meet these two properties. However, most of them have not been formally proved to be untraceable and unreuseable. In this paper we propose to use the applied pi calculus as a framework for describing and analyzing electronic cash protocols, and we analyze Ferguson's electronic cash protocol as a case study. We believe that this approach is suitable for many different electronic cash protocols.
Towards Affective-Psychophysiological Foundations for Music Production
Authors: António Pedro Oliveira, Amílcar Cardoso
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

This paper describes affective and psychophysiological foundations used to help to control affective content in music production. Our work includes the proposal of a knowledge base grounded on the state of the art done in areas of Music Psychology. This knowledge base has relations between affective states (happiness, sadness, etc.) and high level music features (rhythm, melody, etc.) to assist in the production of affective music. A computer system uses this knowledge base to select and transform chunks of music. The methodology underlying this system is essentially founded on Affective Computing topics. Psychophysiology measures will be used to detect listener's affective state.
Evolutionary Design of Fault Tolerant Collective Communications
Authors: Jiri Jaros
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

Scheduling of collective communications (CC) in interconnection networks possibly containing faulty links has been done with the use of the evolutionary techniques. Inter-node communication patterns scheduled in the minimum number of time slots have been obtained. The results show that evolutionary techniques often lead to ultimate scheduling of CC that reaches theoretical bounds on the number of steps. Analysis of fault tolerance by the same techniques revealed graceful CC performance degradation for a single link or node fault. Once the faulty region is located, CC can be re-scheduled during a recovery period.
A Graph Partitioning Approach to Entity Disambiguation Using Uncertain Information
Authors: Emili Sapena, Lluís Padró, Jordi Turmo
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

This paper presents a method for Entity Disambiguation in Information Extraction from different sources in the web. Once entities and relations between them are extracted, it is needed to determine which ones are referring to the same real-world entity. We model the problem as a graph partitioning problem in order to combine the available information more accurately than a pairwise classifier. Moreover, our method handle uncertain information which turns out to be quite helpful. Two algorithms are trained and compared, one probabilistic and the other deterministic. Both are tuned using genetic algorithms to find the best weights for the set of constraints. Experiments show that graph-based modeling yields better results using uncertain information.
Power control of wireless network interfaces
Authors: Marius-Cristian Niculescu, Ionut Resceanu
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

This paper presents a new power management technique aimed at increasing the energy efficiency of client-server multimedia applications running on wireless portable devices. We focus on reducing the energy consumption of the wireless network interface of the client by allowing the remote server to control the power configuration of the network card depending on the workload. In particular, we exploit server knowledge of the workload to perform an energy-efficient traffic reshaping, without compromising on the quality of service. We tested our methodology on the SmartBadge IV wearable device running an MPEG4 streaming video application. Using our technique we measured energy savings of more than 67% compared to no power management being used on the WLAN interface. In addition, we save as much as 50% of energy with respect to the standard 802.l1b power management. All of the energy savings are obtained with no performance loss on the video playback.
An Empirical Investigation of the Use of a Neural Network Committee for Identifying the Streptococcus Pneumoniae Growth Phases in Batch Cultivations
Authors: Antonio C. Horta, Teresa C. Zangirolami, Maria Carmo Nicoletti, Luciana Montera, Talita S. Carmo, Viviane M. Gonçalves
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

Streptococcus pneumoniae is a bacterial pathogen that causes many life-threatening diseases and an effective vaccine against this pa-thogen is still subject of research. These bacteria grow with low carbon dioxide production, which hinders the application of exhaust gas composition for on-line process monitoring. This work investigates the proposal of a committee of neural networks for identifying Streptococcus pneumoniae growth phases, to be used for on-line state inference. The committee results as well as the accuracy for predicting the culture phases are compared to the results of a unique neural network, for different input variables. The best configuration for the software was: a committee of three NN trained with two input attributes (optical density and mass of alkali solution), 200 epochs of training and log sigmoid as the activation function in the hidden layer as well as in the output layer.
Neural Network Method for Protein Structure Search Using Cell-Cell Adhesion
Authors: Cheng-Yuan Liou, Cheng-Jung Ho
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We propose a neural network method for three dimensional protein structure search that utilizes the link relationships among features. This method is an offline index-based method which builds indices for protein structures in the database and the search is performed on the indices. We can easily extend this method to incoporate more physical properties of the protein structures since the structural information is preserved in the extracted features.
A Computing Resource Management Framework for Software-Defined Radios
Authors: Vuk Marojevic, Xavier Revés Ballesté, Antoni Gelonch
Venue: IEEE Transactions on Computers (2008)

Software-defined radio (SDR) is an emerging concept that leverages the design of software-defined and hardware-independent signal processing chains for radio communication. It introduces flexibility to wireless systems, facilitating the dynamic switch from one radio access technology to another or, in other words, the de- and reallocation of computing resources from one SDR application to another. This paper introduces an SDR computing resource management framework. It accounts for several SDR system characteristics, including real-time computing requirements, limited computing resources, and the use of heterogeneous multiprocessor plat-forms, including multiprocessor systems-on-chip. The framework features the tw-mapping, a dy-namic mapping algorithm that is apt for many cost functions and, thus, adaptable to any radio scenario. The cost function proposal dynamically manages the available computing resources to satisfy the given SDR computing constraints. Two relevant SDR scenarios and the corresponding simulations, based on representative SDR platforms and processing chains, demonstrate the framework's importance and suitability for software-defined radios.
The design of a generic framework for integrating ECA components
Authors: Hung-Hsuan Huang, Toyoaki Nishida, Aleksandra Cerekovic, Igor S. Pandzic, Yukiko Nakano
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

Embodied Conversational Agents (ECAs) are life-like computer generated characters that interact with human users in face-to-face multi-modal conversations. ECA systems are generally complex and difficult for individual research groups to develop. Therefore, if there was a common frame-work for connecting ECA functioning blocks seamlessly to an integrated system, redundant effort can be saved. This paper discusses the issues emerged in developing such a framework and introduces the design and preliminary results of our ongoing project, Generic ECA Framework.
Developing and Evaluating a Meeting Assistant Test Bed
Authors: Wilfried Post, Mike Lincoln
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

A test bed has been developed in which participants are tasked to work in simulated, scenario based, projects in which face-to-face and remote meetings of about 45 minutes have to be held. Measures on performance, team factors and remote aspects are automatically collected with electronic questionnaires. The sensitivity and reliability of these questionnaires are positively evaluated. The test bed is now ready to be used for evaluating how well meeting assistants support collocated meetings and videoconferencing.
Knowledge-Based Approaches to Quantitative Medical Image Analysis and Image-Based Decision Making
Authors: Milan Sonka
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

Widespread use of three-dimensional tomographic imaging scanners and other imaging modalities has revolutionized medical care as we know it today. The ever-increasing sizes of acquired data volumes are making conventional visual analysis of image data and consequent image-based decision making time consuming, tedious, and difficult to perform at the time available in busy clinical practice. The field of quantitative medical imaging, which has considerably matured in the past decade, is increasingly promising to solve many current problems that radiologists, cardiologists, orthopedists, and many other physicians are facing on a daily basis.
Virtual Reality as a Valuable Research Tool for Investigating Different Aspects of Spatial Cognition
Authors: Heinrich H. Bülthoff, Jennifer L. Campos, Tobias Meilinger
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

The interdisciplinary research field of spatial cognition has benefited greatly from the use of advanced Virtual Reality (VR) technologies. Such tools have provided the ability to explicitly control specific experimental conditions, manipulate variables not possible in the real world, and provide a convincing, multimodal experience. Here we will first describe several of the VR facilities at the Max Planck Institute (MPI) for Biological Cybernetics that have been developed to optimize scientific investigations related to multi-modal self-motion perception and spatial cognition. Subsequently, we will present some recent empirical work contributing to these research areas.
Properties of state spaces and their applications
Authors: Radek Pel&#x00e1;nek
Venue: International Journal on Software Tools for Technology Transfer (STTT) (2008)

Explicit model checking algorithms explore the full state space of a system. State spaces are usually treated as directed graphs without any specific features. We gather a large collection of state spaces and extensively study their structural properties. Our results show that state spaces have several typical properties, i.e., they are not arbitrary graphs. We also demonstrate that state spaces differ significantly from random graphs and that different classes of models (application domains, academic vs. industrial) have different properties. We discuss consequences of these results for model checking experiments and we point out how to exploit typical properties of state spaces in practical model checking algorithms.