ppxscal/embedding_network huggingface dataset:
Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying
Authors: A. Eckhardt, T. Horváth, P. Vojtáš
Venue: Proceedings of the 1st international conference on Scalable Uncertainty Management (2007)

Uncertainty querying of large data can be solved by providing top-k answers according to a user fuzzy ranking/scoring function. Usually different users have different fuzzy scoring function --- a user preference model. Main goal of this paper is to assign a user a preference model automatically. To achieve this we decompose user's fuzzy ranking function to ordering of particular attributes and to a combination function. To solve the problem of automatic assignment of user model we design two algorithms, one for learning user preference on particular attribute and second for learning the combination function. Methods were integrated into a Fagin-like top-k querying system with some new heuristics and tested.
Convergence analysis of the preconditioned Gauss-Seidel method for H-matrices
Authors: Qingbing Liu, Guoliang Chen, Jing Cai
Venue: Computers Mathematics with Applications (2008)

In 1997, Kohno et al. [Toshiyuki Kohno, Hisashi Kotakemori, Hiroshi Niki, Improving the modified Gauss-Seidel method for Z-matrices, Linear Algebra Appl. 267 (1997) 113-123] proved that the convergence rate of the preconditioned Gauss-Seidel method for irreducibly diagonally dominant Z-matrices with a preconditioner I+S"@a is superior to that of the basic iterative method. In this paper, we present a new preconditioner I+K"@b which is different from the preconditioner given by Kohno et al. [Toshiyuki Kohno, Hisashi Kotakemori, Hiroshi Niki, Improving the modified Gauss-Seidel method for Z-matrices, Linear Algebra Appl. 267 (1997) 113-123] and prove the convergence theory about two preconditioned iterative methods when the coefficient matrix is an H-matrix. Meanwhile, two novel sufficient conditions for guaranteeing the convergence of the preconditioned iterative methods are given.
Efficient management of data center resources for massively multiplayer online games
Authors: Vlad Nae, Alexandru Iosup, Stefan Podlipnig, Radu Prodan, Dick Epema, Thomas Fahringer
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Today's Massively Multiplayer Online Games (MMOGs) can include millions of concurrent players spread across the world. To keep these highly-interactive virtual environments online, a MMOG operator may need to provision tens of thousands of computing resources from various data centers. Faced with large resource demand variability, and with misfit resource renting policies, the current industry practice is to maintain for each game tens of self-owned data centers. In this work we investigate the dynamic resource provisioning from external data centers for MMOG operation. We introduce a novel MMOG workload model that represents the dynamics of both the player population and the player interactions. We evaluate several algorithms, including a novel neural network predictor, for predicting the resource demand. Using trace-based simulation, we evaluate the impact of the data center policies on the resource provisioning efficiency; we show that dynamic provisioning can be much more efficient than its static alternative.
Analysing an Approach to Information Retrieval of Visual Descriptions with IR-n, a System Based on Passages
Authors: Sergio Navarro, Fernando Llopis, Rafael Muñoz Guillena, Elisa Noguera
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 analyses an approach made to the development of a textual image retrieval system by the University of Alicante using IR-n, a text-based information retrieval (IR) system. With only a minimal amount of adaptations to the features of this task, our system has obtained precision results above the mean average of participants for ImageCLEF07 both for English (0.1604 vs 0.1388) and for Spanish (0.1482 vs 0.1450). For German, our results were below the mean (0.0991 vs 0.1331), which could be due to the fact that our system does not incorporate a splitter for the treatment of this agglutinative language. These results are obtained without the incorporation of image recovery dominion techniques. The error analysis shows us that there is still a considerable amount of work to do concerning text-based techniques in order to improve the system, but also shows that the key to successful participation in this task is to mix text and image resources.
Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design
Authors: Sidhartha Panda, Narayana Prasad Padhy
Venue: Applied Soft Computing (2008)

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for flexible ac transmission system (FACTS)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational effort, computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances over a wide range of loading conditions and parameter variations and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a FACTS-based controller, to enhance power system stability.
Medical Image Retrieval and Automatic Annotation: OHSU at ImageCLEF 2007
Authors: Jayashree Kalpathy-Cramer, William Hersh
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)

Oregon Health Science University participated in the medical retrieval and medical annotation tasks of ImageCLEF 2007. In the medical retrieval task, we created a web-based retrieval system built on a full-text index of both image and case annotations. The text-based search engine was implemented in Ruby using Ferret, a port of Lucene and a custom query parser. In addition to this textual index of annotations, supervised machine learning techniques using visual features were used to classify the images based on image acquisition modality. All images were annotated with the purported modality. Purely textual runs as well as mixed runs using the purported modality were submitted, with the latter performing among the best of all participating research groups. In the automatic annotation task, we used the 'gist' technique to create the feature vectors. Using statistics derived from a set of multi-scale oriented filters, we created a 512-dimensional vector. PCA was then used to create a 100-dimensional vector. This feature vector was fed into a two layer neural network. Our error rate on the 1000 test images was 67.8 using the hierarchical error calculations.
Research into the Generation of Sound Effects Using a Cellular Automaton
Authors: Seita Toguchi, Yuhei Akamine, Satoshi Endo
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

The purpose of this research is to generate impact sounds often used as sound effects through physical simulation using cellular automaton (CA). The authors designed a model based on the wave propagation CA model. In the model, desired sound is generated by setting several parameters. This paper shows the effects of each parameter on the sound, and shows that various impact sound can be generated by the model. Production cost of sound effects can be reduced by using this model.
Pupil diameter measurements: untapped potential to enhance computer interaction for eye tracker users?
Authors: Armando Barreto, Ying Gao, Malek Adjouadi
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

In this paper, we propose the possibility of using real-time pupil diameter measurements, which are provided by most Eye Gaze Tracking (EGT) systems utilized for computer input by many individuals with severe motor impairments, to obtain an on-line estimation of the quality of the interaction with the computer, as perceived by the user. Increased computational power available to process, in real-time, pupil diameter data could, in the future, enable an assessment of the level of frustration (stress) that an EGT user may experience when the quality of the interaction deteriorates. This would be a critical first step in the direction of enabling EGT systems to initiate a re-calibration process, under those circumstances.
Service Design Process for Reusable Services: Financial Services Case Study
Authors: Abdelkarim Erradi, Naveen Kulkarni, Piyush Maheshwari
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Service-oriented Architecture (SOA) is an approach for building distributed systems that deliver application functionality as a set of business-aligned services with well-defined and discoverable contracts. This paper presents typical a service design process along with a set of service design principles and guidelines for systematically identifying services, designing them and deciding the service granularity and layering. The advocated principles stem from our experiences in designing services for a realistic Securities Trading application. Best practices and lessons learned during this exercise are also discussed.
Smoothing curve by orthogonal polynomial(2)
Authors: Wichuta Pispeng, Sutisa Kameesak, Piyapong Sujarakittikul, Terdkwan Changpuak, Maitree Podisuk
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

M. Podisuk, P. Rattanathanawan and P. Phataranavik, in [1], introduced the sequences of orthogonal polynomials with step functions as their weight functions but they did not use them for least square approximation. M. Podisuk, P. Rattanathanawan and S. Pansomboon, in [2], did the same kind of work but they used their results for least square approximation. In this paper, we obtain six new orthogonal polynomials with the weight function are not step function and they are not differentiable functions. We do use these orthogonal polynomials for least square approximation.
On the evaluation and extraction of thread-level parallelism in ordinary programs
Authors: Alexandru Nicolau
Venue:  (2008)

The need for high performance coupled with the increasing design complexity of modern processors and power and thermal constraints has led to the development of multi-cores systems. Examples of such systems include IBM/Toshiba's Cell processor, Intel's Core 2 Duo processor. One of the ways to exploit the hardware parallelism of such systems is via thread-level program parallelization. Although there has been a large amount of work done in the context of multithreading, the lack of detailed application characterization on real machines makes it difficult to assess the relevance and importance of the problems addressed in prior work and also of the practicality of the solutions proposed. To alleviate this limitation, we did a thorough analysis of ordinary programs, as represented by industry-standard SPEC benchmarks, on both IA-32 and IA-64 architectures to identify real performance bottlenecks. Based on the above and given that loops account for a large percentage of the total execution time in ordinary programs, we propose techniques for extracting thread-level parallelism (TLP) from both&mdash;DOALL and non-DOALL &mdash;type of loops. Extraction of TLP from DOALL loops entails efficient partitioning and mapping of a DOALL loop so as to achieve load balance between the different processors. In this regard, we present a general approach for partitioning nested DOALL loops, both perfect and non-perfect, with conditionals, with rectangular and non-rectangular iteration geometries, where the expressions in a conditional are affine functions of the outer loop indices. Non-DOALL loops can be parallelized either speculatively (TLS) or via explicit synchronization. Although TLS enables parallel execution of difficult-to-analyze (at compile time) program regions, its efficacy is limited by a wide variety of factors such as high misspeculation penalty and the need for additional hardware. This necessitates an evaluation of the performance potential of TLS. Using the Intel Fortran/C++ compiler, we show that the speedup achievable via TLS, at the loop level, is minimal in ordinary programs. Therefore, we adopted explicit synchronization as the way to parallelize non- DOALL loops and proposed lightweight lock-free synchronization techniques for extracting TLP from non-DOALL loops. We show that the proposed techniques achieve better performance than the state-of-the-art on real machines.
Personal Knowledge Management in E-Learning Era
Authors: Weichao Li, Yong Liu
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

In this paper, the author first introduces some relative theories of E-Learning and personal knowledge management(PKM), including the concept, content, objectives and their common ground, then puts forwards the requirements to personal knowledge management and how to use personal knowledge management tools such as iSpace Desktop, iNota, Mybase in E-Learning environment to improve personal knowledge literacy.
Energy-Efficient Area Monitoring for Sensor Networks
Authors: Jean Carle, David Simplot-Ryl
Venue: Computer (2004)

The nodes in sensor networks must self-organize to monitor the targetarea as long as possible. Researchers at the Fundamental Computer Science Laboratory of Lille are developing strategies for selecting and updating an energy-efficient connected active sensorset that extends the network lifetime. The authors report on their work to optimize energy consumption in three separate problems: area coverage, request spreading, and data aggregation.
A Formal Model of Coordination for Supporting Community Computing in a Ubiquitous Environment
Authors: Jingyu Nam, Hyunwoo Kim, Dongmin Shin, Jaeil Park
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

Recent advances in mobile computing technologies and platform-independent information systems have enabled to realize a ubiquitous environment. Community computing is developed to as a useful tool for realizing collaborative services in a ubiquitous environment. In this paper, we present a formal model of a ubiquitous space that takes community concept into consideration and propose two management frameworks that prevent conflicts among communities. To demonstrate the validity of the proposed frameworks, a prototype system for coordinating medical emergency system is provided.
Designing an Automatic Debugging Assistant for Improving the Learning of Computer Programming
Authors: Maria S. Lam, Eric Y. Chan, Victor C. Lee, Y. T. Yu
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Finding bugs in programs (debugging) is a core skill for practical programmers. However, debugging programs can be difficult to novice programmers. Even worse, repetitive failures may defeat students' enthusiasm for learning. The presence of a mentor giving hints and help face-to-face with students will surely make such a learning process much more effective and enjoyable. However, this requires lots of manpower and resources. To address this problem, we seek to capitalize on the potential advantages offered by hybrid learning. We are working towards a system for providing a certain level of automatic debugging assistance to students. Instructors can identify common errors in students' programs using the system and incorporate useful debug-guiding information into it so that students will be prompted with pertinent hints when common errors are detected in their programs.
Improving Unsupervised WSD with a Dynamic Thesaurus
Authors: Javier Tejada-Cárcamo, Hiram Calvo, Alexander Gelbukh
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

The method proposed by Diana McCarthy et al. [1] obtains the predominant sense for an ambiguous word based on a weighted list of terms related to the ambiguous word. This list of terms is obtained using the distributional similarity method proposed by Lin [2] to obtain a thesaurus. In that method, every occurrence of the ambiguous word uses the same thesaurus, regardless of the context where it occurs. Every different word to be disambiguated uses the same thesaurus. In this paper we explore a different method that accounts for the context of a word when determining the most frequent sense of an ambiguous word. In our method the list of distributed similar words is built based on the syntactic context of the ambiguous word. We attain a precision of 69.86%, which is 7% higher than the supervised baseline of using the MFS of 90% SemCor against the remaining 10% of SemCor.
Characterization of Star-Connected Languages Using Finite Automata
Authors: Barbara Klunder
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

In this paper we characterize star-connected languages using finite automata: any language is star-connected if and only if it is accepted by a finite automaton with cycles which are proper compositions of connected cycles. Star-connected (flat) languages play an important role in the theory of recognizable languages of monoids with partial commutations. In addition we introduce a flat counterpart of concurrent star operation used in the theory of recognizable languages.
Shell scripting with a distributed twist: using the sleep scripting language
Authors: Raphael Mudge
Venue: Linux Journal (2008)

A language for practical extraction and reporting with mobile agents?
Addressing the Issue of Service Volatility in Scientific Workflows
Authors: Khalid Belhajjame
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Workflows are increasingly used in scientific disciplines for modelling, enacting and sharing in silico experiments. However, the reuse of an existing workflow is frequently hampered by the volatility of its constituent service operations. To deal with this issue, we propose in this paper a set of criteria for characterising service replaceability using which substitute operations can be automatically located for replacing unavailable ones in workflows.
Psychology in the ICT Era: Electronic Psychology
Authors: Athanasios Drigas, Leyteris Koukianakis, Yannis Papagerasimou
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

Cognitive science is the scientific domain which studies, analyses, simulates and infers for various aspects, functions and procedures of human mentality such as, thinking, logic, language, knowledge, memory, learning, perception and the ability to solve problems. E-psychology is in a close relation with the cognitive science domain, but expands beyond it, as e-psychology is the efficient convergence of Psychology and Information and Communication Technologies (ICTs). E-psychology offers a number of services such as supporting, diagnosis, assessment, therapy, counseling, intervention and tests through an effective exploitation of ICTs. This article presents a user-friendly, flexible and adaptive electronic platform, which supports both synchronous and asynchronous e-psychology activities through the use of informative and communicative tools and services, which can be adapted to support various methods of e-psychology activities. It is important to underline that e-psychology is not an alternative psychology field, but a resource to enhance the conventional psychology process.
Performance modeling and analysis of heterogeneous meta-computing systems interconnection networks
Authors: Bahman Javadi, Jemal H. Abawajy, Mohammad K. Akbari
Venue: Computers and Electrical Engineering (2008)

The overall performance of a distributed system often depends on the effectiveness of its interconnection network. Thus, the study of the communication networks for distributed systems is very important, which is the focus of this paper. In particular, we address the problem of interconnection networks performance modeling for heterogeneous meta-computing systems. We consider the meta-computing system as a typical multi-cluster system. Since the heterogeneity is becoming common in such systems, we take into account network as well as cluster size heterogeneity to propose the model. To this end, we present an analytical network model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.
IBM smart surveillance system (S3): event based video surveillance system with an open and extensible framework
Authors: Ying-li Tian, Lisa Brown, Arun Hampapur, Max Lu, Andrew Senior, Chiao-fe Shu
Venue: Machine Vision and Applications (2008)

The increasing need for sophisticated surveillance systems and the move to a digital infrastructure has transformed surveillance into a large scale data analysis and management challenge. Smart surveillance systems use automatic image understanding techniques to extract information from the surveillance data. While the majority of the research and commercial systems have focused on the information extraction aspect of the challenge, very few systems have explored the use of extracted information in the search, retrieval, data management and investigation context. The IBM smart surveillance system (S3) is one of the few advanced surveillance systems which provides not only the capability to automatically monitor a scene but also the capability to manage the surveillance data, perform event based retrieval, receive real time event alerts thru standard web infrastructure and extract long term statistical patterns of activity. The IBM S3 is easily customized to fit the requirements of different applications by using an open-standards based architecture for surveillance.