ppxscal/embedding_network huggingface dataset:
An analysis of clustered failures on large supercomputing systems
Authors: Thomas J. Hacker, Fabian Romero, Christopher D. Carothers
Venue: Journal of Parallel and Distributed Computing (2009)

Large supercomputers are built today using thousands of commodity components, and suffer from poor reliability due to frequent component failures. The characteristics of failure observed on large-scale systems differ from smaller scale systems studied in the past. One striking difference is that system events are clustered temporally and spatially, which complicates failure analysis and application design. Developing a clear understanding of failures for large-scale systems is a critical step in building more reliable systems and applications that can better tolerate and recover from failures. In this paper, we analyze the event logs of two large IBM Blue Gene systems, statistically characterize system failures, present a model for predicting the probability of node failure, and assess the effects of differing rates of failure on job failures for large-scale systems. The work presented in this paper will be useful for developers and designers seeking to deploy efficient and reliable petascale systems.
Application of hybrid differential transformation/finite difference method to nonlinear analysis of micro fixed-fixed beam
Authors: Cha&#x2019;o-Kuang Chen, H. Y. Lai, Chin-Chia Liu
Venue: Microsystem Technologies (2009)

Analyzing the dynamic response of electrostatic devices is problematic due to the complexity of the interactions between the electrostatic coupling effect, the fringing field effect and the nonlinear electrostatic force. To resolve this problem, this study presents an efficient computational scheme in which the nonlinear governing equation of the electrostatic device is obtained in accordance with Hamilton&#x2019;s principle and is then solved using a hybrid differential transformation/finite difference method. The feasibility of the proposed approach is demonstrated by modeling the dynamic responses of two micro fixed-fixed beams with lengths of 250 and 350&#x00a0;&#x03bc;m, respectively. The numerical results show that the pull-in voltage reduces as the beam length increases due to a loss in the structural rigidity. Furthermore, it is shown that the present results for the pull-in voltage deviate by no more than 0.75% from those derived in the literature using a variety of different schemes. Overall, the results presented in this study demonstrate that the proposed hybrid method represents a computationally efficient and precise means of obtaining detailed insights into the nonlinear dynamic behavior of micro fixed-fixed beams and similar micro-electro-mechanical systems (MEMS)-based devices.
Accelerating Segment Model Decoding for LVCSR by Parallel Processing of Neighboring Segments
Authors: Shouye Peng, Wen-Ju Liu, Hua Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In human speech, most boundaries between phones/words are fuzzy. If a time slice which only includes a sole boundary is given, it is possible that the boundary may locate at any frame within the slice. Different boundary locations form several potential observation segments, which should have similar acoustic spaces because of their neighboring trait in time domain. We call them neighboring segments. In this paper, a fast algorithm of parallel processing of neighboring segments is proposed for decoding. Since the decoder can search a bigger pruning threshold in parallel processing, the proposed algorithm is faster than decoding a single segment. This algorithm is successfully integrated into a Segment Model (SM) based Mandarin Large Vocabulary Continuous Speech Recognition (LVCSR) system, and saves approximately 50% decoding time without obvious influence on the recognition accuracy.
A New Cerebellar Model Articulation Controller for Rehabilitation Robots
Authors: Shan Liu, Yongji Wang, Yongle Xie, Shuyan Jiang, Jinsong Meng
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This paper presents a new cerebellar model articulation controller (CMAC), a sliding-mode-based diagonal recurrent fuzzy CMAC (SDRFCMAC) to robot-assisted rehabilitation for stroke patients. To design the intelligent controller, the CMAC is integrated with some control methods, in which sliding mode technology is used to reduce the dimension of the control system, and fuzzy logic and diagonal recurrent structure is used to solve dynamic problems. The control architecture is represented in terms of stepping optimization system architecture comprising two learning stages to provide robotic assistance for an upper arm rehabilitation task and improve the safety of the human-robot system. Liapunov stability theorem and Barbalat's lemma are adopted to guarantee the asymptotical stability of the system. The effectiveness of the control scheme is demonstrated through a simulated case study.
Implementation of automated diagnostic systems: ophthalmic arterial disorders detection case
Authors: Elif Derya Ubeyli
Venue: International Journal of Systems Science (2009)

This article intends to give an integrated view of the automated diagnostic systems combined with spectral analysis techniques in the detection of arterial disorders. The article includes illustrative and detailed information about implementation of automated diagnostic systems and feature extraction/selection from signals recorded from ophthalmic arteries. The major objective of the article is to be a guide for readers who want to develop an automated diagnostic systems for detection of arterial disorders. Towards achieving this objective, this article presents the techniques which should be considered in developing automated diagnostic systems. The author suggests that the content of the article will assist people in gaining a better understanding of the techniques in the detection of arterial disorders.
${\cal K}$-${\cal MORPH}$: A Semantic Web Based Knowledge Representation and Context-Driven Morphing Framework
Authors: Sajjad Hussain
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

A knowledge-intensive problem is often not solved by an individual knowledge artifact; rather the solution needs to draw upon multiple, and even heterogeneous, knowledge artifacts. The synthesis of multiple knowledge artifacts to derive a `comprehensive' knowledge artifact is a non-trivial problem. We discuss the need of knowledge morphing, and propose a Semantic Web based framework ${\cal K}$-${\cal MORPH}$ for deriving a context-driven integration of multiple knowledge artifacts. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Study of the Influence of Shadowing on the Statistical Properties of the Capacity of Mobile Radio Channels
Authors: Gulzaib Rafiq, Matthias Pätzold
Venue: Wireless Personal Communications: An International Journal (2009)

This paper studies the influence of shadowing on the statistical properties of the channel capacity. The problem is addressed by using a Suzuki process as an appropriate statistical channel model for land mobile terrestrial channels. Using this model, exact solutions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the channel capacity are derived. The results are studied for different levels of shadowing, corresponding to different terrestrial environments. It is observed that the shadowing effect has a significant influence on the variance and the maximum value of the PDF and LCR of the channel capacity, but it has almost no impact on the mean capacity of the channel. The correctness of the theoretical results is confirmed by simulation using a stochastic channel simulator based on the sum-of-sinusoids principle.
Parallel I/O Support for HPF on Computational Grids
Authors: Peter Brezany, Jonghyun Lee, Marianne Winslett
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

Recently several projects have started to implement large-scale high-performance computing on "computational grids" composed of heterogeneous and geographically distributed systems of computers, networks, and storage devices that collectively act as a single "virtual supercomuter". One of the great challenges for this environment is to provide appropriate high-level programming models. High Performance Fortran (HPF) is a language of choice for development of data parallel components of Grid applications. Another challenge is to provide efficient access to data that is distributed across local and remote Grid resources. In this paper, constructs to specify parallel input and output (I/O) operations on multidimensional arrays on the Grid in the context of HPF are proposed. The paper also presents implementation concepts that are based on the HPF compiler VFC, the parallel I/O runtime system Panda, Internet, and Grid technologies. Preliminary experimental performance results are discussed in the context of a real application example.
Managerial Entrenchment with Strategic Information Technology: A Dynamic Perspective
Authors: Xiaotong Li
Venue: Journal of Management Information Systems (2009)

Some economic and informational problems associated with organizational information technology (IT) spending may be attributed to managerial rent-seeking. Because of the unavoidable incompleteness of labor contracts, managers with misaligned incentives and budgetary discretion could entrench themselves through their non-value-maximizing adoption decisions. In order to boost their bargaining power in future contract renegotiation, they invest excessively in technologies they manage more effectively than their potential rivals. In addition, they tend to adopt technologies that can create large information asymmetries giving them significant knowledge advantage over their potential rivals ex post. We study the implications and effects of their rent-seeking behavior within the context of organizational IT adoption and management. The efficacies and the limitations of formal incentive contracting are discussed to underscore the need for additional governance mechanisms. While knowledge management may mitigate some of the agency problems associated with entrenchment, managerial self-policing issue remains a challenge. We further explore the incentive provision potential of relational labor contracts in combating entrenchment.
Agent-Based Modeling of a Mobile Robot to Detect and Follow Humans
Authors: José M. Gascueña, Antonio Fernández-Caballero
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

This paper introduces a multi-agent system (MAS) approach using the detailed process provided by Prometheus methodology for the design of a moving robot application for the detection and following of humans. Our conjecture is that complex autonomous robotic systems have to be fully modeled in their initial design stages by means of agent-based technology. The application has been completely modeled with the Prometheus Design Tool (PDT), which offers full support to Prometheus methodology.
Multimedia Techniques for Device and Ambient Intelligence, 1st edition
Authors: Ernesto Damiani, Jechang Jeong
Venue:  (2009)

Ambient Intelligence is a vision of the future where the world will be surrounded by electronic environments sensitive and responsive to people, wherein devices work in concert to support people in carrying out their everyday life activities, in an easy and natural way. This edited volume is based on the workshop Multimedia Techniques for Ambient Intelligence (MTDAI08), held in Mogliano Veneto, Italy in March 2008. Contributed by world renowned leaders in the field from academia and industry, this volume is dedicated to research on technologies used to improve the intelligence capability of multimedia devices for imaging, image processing and computer vision. Focuses on recent developments in digital signal processing, including evolutions in audiovisual signal processing, analysis, coding and authentication, and retrieval techniques. Designed for researchers and professionals, this book is also suitable for advanced-level students in computer science and electrical engineering.
Base selection method for recognition of exon-intron boundaries
Authors: Susumu Katayama, Yujiro Tomoshige
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

The genes of eukaryotes like human beings are consisted of regulatory regions that controls transcription and structural regions which is consisted of exons where protains are coded and introns that are between exons. Since protains are generated from exons via transcription and splicing, recognition of exons plays an important role in revealing the functions of genes. Although the DNA sequence is known to be finite, a huge amount of array data are being produced day by day. In this situation, exons have to be extracted automatically and efficiently by computers. Lots of pieces of research work have been devoted for this purpose, and as a result systems like GENSCAN are widely used. This paper presents the base selection method that we developed for quick recognition of the exon-intron boundaries.
Mashing up life science literature resources
Authors: Richard Easty, Nikolay Nikolov
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

In the life sciences one of the pronounced problems is the deluge of new results and data that are produced on a daily basis. This data can take many different forms, e.g. microarray probes, gene sequences, protein structures and is added by hundreds of research centers world-wide in a largely uncoordinated fashion. Thus integration of life science data is growing in importance. Unfortunately, most research centers do not have particular incentive to spend efforts on integrating their data with data produced by others. This task is largely left to large publicly-sponsored institutions like the US National Library of Medicine and similar institutions in other countries. Unfortunately, despite their work in this area, the integration of web-based life science resources is still an open issue (and one ever growing in importance) as these organizations cannot cope with the information deluge that is happening on a daily basis in the life sciences. Thus it becomes essential that as many as possible third parties are engaged in the process. Here we demonstrate a simple prototype of a browser plugin that creates a platform for third parties to contribute to cross-linking related online life science data resources and thus improving the search experience and the productivity of the life science community. The plugin creates a convenient programming interface that minimizes the effort that arises for such third-party contributors. We have provided reference implementations using the plugin that cross-link life science literature resources and illustrate the potential for third parties to create mashups that could be applied also in areas other than the life sciences.
Optimal Inversion of Open Boundary Conditions Using BPNN Data-Driven Model Combined with Tidal Model
Authors: Mingchang Li, Guangyu Zhang, Bin Zhou, Shuxiu Liang, Zhaochen Sun
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

One of major difficulties with numerical tidal models is accurate inversion of open boundary conditions. A data-driven model based on artificial neural network is developed to retrieve open boundary values. All training data are calculated by numerical tidal model, so the tidal physics are not disturbed. The basic idea is to find out the relationship between open boundary values and the values of interior tidal stations. Case testes are carried out with a real ocean bay named Liaodong Bay, part of the Bohai Sea, China. Four major tidal constituents, M2, S2, O1and K1, are considered in coupled inversion method. Case studies show that the coupled inversion for open boundary conditions can make a more satisfactory inversion for a practical problem.
Scheduling policy design for autonomic systems
Authors: Robert Glaubius, Terry Tidwell, Christopher D. Gill, William D. Smart
Venue: International Journal of Autonomous and Adaptive Communications Systems (2009)

Scheduling the execution of multiple concurrent tasks on shared resources such as CPUs and network links is essential to ensuring the reliable operation of many autonomic systems. Well-known techniques such as rate-monotonic scheduling can offer rigorous timing and preemption guarantees, but only under assumptions (i.e. a fixed set of tasks with well-known execution times and invocation rates) that do not hold in many autonomic systems. New hierarchical scheduling techniques are better suited to enforce the more flexible execution constraints and enforcement mechanisms that are required for autonomic systems, but a rigorous and efficient foundation for verifying and enforcing concurrency and timing guarantees is still needed for these approaches. This paper summarises our previous work on addressing these challenges, on Markov decision process-based scheduling policy design and on wrapping repeated structure of the scheduling state spaces involved into a more efficient model, and presents a new algorithm called expanding state policy iteration (ESPI), that allows us to compute the optimal policy for a wrapped state model.
On the improvement of brain tumour data clustering using class information
Authors: Raúl Cruz, Alfredo Vellido
Venue: Proceeding of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium (2006)

Cluster analysis can benefit from the use of class labels, if these are available, in a semi-supervised approach. In this study, we propose the integration of class information in the clustering of Magnetic Resonance Spectra (MRS) corresponding to human brain tumours using an extension of Generative Topographic Mapping (GTM) that behaves robustly in the presence of outliers.
Quantitative Data Analysis with SPSS, 1st edition
Authors: Pete Greasley
Venue:  (2007)

"This is an ideal introductory book for budding researchers who are embarking on the development and then analysis of data, and in this case, more specifically questionnaires using partly or exclusively closed questions amenable to statistical analysis." Primary Health Care Research and Development "The text is a welcome addition for nursing students at both undergraduate and postgraduate level research. Having reviewed the text I can only inform you how a student described a chapter in the book recently when she borrowed it. 'The language is clear and unambiguous'. I will be strongly encouraging students to either purchase the text ... with the purpose of giving them a foundation in statistics." William Evans, Institute of Technology Tralee, Ireland This accessible book is essential reading for those looking for a short and simple guide to basic data analysis. Written for the complete beginner, the book is the ideal companion when undertaking quantitative data analysis for the first time using SPSS. The book uses a simple example of quantitative data analysis that would be typical to the health field to take you through the process of data analysis step by step. The example used is a doctor who conducts a questionnaire survey of 30 patients to assess a specific service. The data from these questionnaires is given to you for analysis, and the book leads you through the process required to analyse this data. Handy screenshots illustrate each step of the process so you can try out the analysis for yourself, and apply it to your own research with ease. Topics covered include: Questionnaires and how to analyse them Coding the data for SPSS, setting up an SPSS database and entering the data Descriptive statistics and illustrating the data using graphs Cross-tabulation and the Chi-square statistic Correlation: examining relationships between interval data Examining differences between two sets of scores Reporting the results and presenting the data Quantitative Data Analysis Using SPSS is helpful for any students in health and social sciences with little or no experience of quantitative data analysis and statistics. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
System Definition and Implementation Plan Driven by non-Linear Quality Function Deployment Model
Authors: Tomasz Nowak, Mirosław Głowacki
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

In this paper the systematic approach for optimal definition of system functionality and implementation plan has been described. Non-linear decision model, with goal function aiming to maximize the level of customer satisfaction, and considering budget constraints as well as risk parameters is given and explained. The practical application of the proposed methodology is presented and discussed. Definition of the system architecture and implementation plan for computer-based collaboration environment supporting communication within the cross-bordered manufacturing company is illustrated.
Adaptation Knowledge Discovery from a Case Base
Authors: M. d'Aquin, F. Badra, S. Lafrogne, J. Lieber, A. Napoli, L. Szathmary
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

In case-based reasoning, the adaptation step depends in general on domain-dependent knowledge, which motivates studies on adaptation knowledge acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge discovery from databases. This system explores the variations within the case base to elicit adaptation knowledge. It has been successfully tested in an application of case-based decision support to breast cancer treatment.
A gauss function based approach for unbalanced ontology matching
Authors: Qian Zhong, Hanyu Li, Juanzi Li, Guotong Xie, Jie Tang, Lizhu Zhou, Yue Pan
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Ontology matching, aiming to obtain semantic correspondences between two ontologies, has played a key role in data exchange, data integration and metadata management. Among numerous matching scenarios, especially the applications cross multiple domains, we observe an important problem, denoted as unbalanced ontology matching which requires to find the matches between an ontology describing a local domain knowledge and another ontology covering the information over multiple domains, is not well studied in the community. In this paper, we propose a novel Gauss Function based ontology matching approach to deal with this unbalanced ontology matching issue. Given a relative lightweight ontology which represents the local domain knowledge, we extract a "similar" sub-ontology from the corresponding heavyweight ontology and then carry out the matching procedure between this lightweight ontology and the newly generated sub-ontology. The sub-ontology generation is based on the influences between concepts in the heavyweight ontology. We propose a Gauss Function based method to properly calculate the influence values between concepts. In addition, we perform an extensive experiment to verify the effectiveness and efficiency of our proposed approach by using OAEI2007 tasks. Experimental results clearly demonstrate that our solution outperforms the existing methods in terms of precision, recall and elapsed time.