ppxscal/embedding_network huggingface dataset:
Synchronization through Communication in a Massively Parallel Processor Array
Authors: Mike Butts
Venue: IEEE Micro (2007)

Programming MPPAs for complex real-time embedded applications is difficult with conventional multiprogramming models, which usually treat communication and synchronization separately. To ease this burden, this MPPA's architecture is based on the Structural Object Programming Model, which composes strictly encapsulated processing and memory objects in a structure of self-synchronizing channels. Small RISC CPUs and memories execute the objects.
Tapered Floating Point: A New Floating-Point Representation
Authors: R. Morris
Venue: IEEE Transactions on Computers (1971)

It is well known that there is a possible tradeoff in the binary representation of floating-point numbers in which one bit of accuracy can be gained at the cost of halving the exponent range, and vice versa. A way in which the exponent range can be greatly increased while preserving full accuracy for most computations is suggested.
Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
Authors: Pushmeet Kohli, Philip H. S. Torr
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

Abstract—In this paper we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. We show how this algorithm can be used to efficiently compute MAP solutions for certain dynamically changing MRF models in computer vision such as image segmentation. Specifically, given the solution of the max-flow problem on a graph, the dynamic algorithm efficiently computes the maximum flow in a modified version of the graph. The time taken by it is roughly proportional to the total amount of change in the edge weights of the graph. Our experiments show that, when the number of changes in the graph is small, the dynamic algorithm is significantly faster than the best known static graph cut algorithm. We test the performance of our algorithm on one particular problem: the object-background segmentation problem for video. It should be noted that the application of our algorithm is not limited to the above problem, the algorithm is generic and can be used to yield similar improvements in many other cases that involve dynamic change.
Safety Evaluation of NanoFabrics
Authors: Michelangelo Grosso, Maurizio Rebaudengo, Matteo Sonza Reorda
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

Chemically Assembled Electronic Nanotechnology is a promising alternative to CMOS fabrication. In particular, the nanoFabric has proven to be a viable solution for implementing digital circuits. The paper proposes some preliminary considerations about safety of application-oriented nanoFabrics based on some results obtained through an automated platform for fault simulation. In particular, a single-fault detecting methodology is proposed and evaluated. Different fault models have been taken into account in order to evaluate alternative scenarios.
XML Query Optimisation: Specify your Selectivity
Authors: Sven Hartmann, Sebastian Link
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

The problem of efficiently evaluating XPath and XQuery queries has become increasingly significant since more and more XML data is stored in its native form. We propose a novel optimisation technique for XML queries that is based on the semantic properties exhibited by XML data. In sharp contrast to previous studies on selectivity estimation we propose to specify bounds on the number of element nodes in an XML tree that form the root of isomorphic subtrees. It turns out that efficient reasoning about these constraints provides effective means to predict the number of XPath and XQuery query answers, to predict the number of updates using the XQuery update facility, to predict the number of en(de)cryptions using XML encryption, and to optimise XML queries.
Boosted Bayesian Kernel Classifier Method for Face Detection
Authors: Ali Reza Bayesteh Tashk, Karim Faez
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In this paper, we present a novel face detection approach based on Adaboosted Relevance Vector Machine (RVM). The novelty of this paper comes from the construction of the kernel classifier with different kernel parameters. We use Fisher's criterion to choose a subset of Haar-like features. The proposed combination outperforms in generalization in comparison with Support Vector Machine (SVM) on imbalanced classification problem. The combination of boosting algorithm and RVM classifier will yield accurate and sparse model which will perform well in real-time application. This method is compared, in terms of classification accuracy, to other commonly used methods, such as SVM and RVM without boosting, on CBCL face database. Results indicate that the performance of the proposed method is overall superior to previous approaches with very good sparsity.
A Fast Learning Algorithm for One-Class Support Vector Machine
Authors: Jia Jiong, Zhang Hao-ran
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Support vector machine (SVM) is a powerful tool to solve classification problems, this paper proposes a fast Sequential Minimal Optimization (SMO) algorithm for training one-class support vector regression (OCSVM), firstly gives a analytical solution to the size two quadratic programming (QP) problem, then proposes a new heuristic method to select the working set which leads to algorithm's faster convergence. The simulation results indicate that the proposed SMO algorithm can reduce the training time of OCSVM, and the performance of proposed SMO algorithm is better than that of original SMO algorithm.
Security and Privacy in Pervasive Computing
Authors: Charalampos Patrikakis, Pantelis Karamolegkos, Athanasios Voulodimos, Mohd Helmy Abd Wahab, Nik Shahidah Afifi Mohd Taujuddin, Christina Hanif, Linda Pareschi, Daniele Riboni, Stefan G. Weber, Andreas Heinemann, Sen-ching Samson Cheung, Jayahsri Chaudhari, Jithendra K. Paruchuri
Venue: IEEE Pervasive Computing (2007)

This Works in Progress department features six projects relating to security and privacy. The first two entries address an individual's privacy concerns and preferences. The next discusses a project on data protection for electronic passports. The remaining three entries investigate various types of privacy protection mechanisms for data collected in pervasive computing environments, by attestation services, and by voice recording systems. This department is part of a special issue on security and privacy.
A Coupled Mean Shift-Anisotropic Diffusion Approach for Document Image Segmentation and Restoration
Authors: Fadoua Drira, Frank LeBourgeois, Hubert Emptoz
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Mean Shift, a powerful color clustering approach successfully applied to image segmentation, has two main properties that are relevant for use in document image segmentation. These properties include: the autonomous definition of both color clusters. centers and numbers and the good tolerance to noisy data sets. Hence, Mean Shift could robustly process degraded background document images and improve their legibility. Nevertheless, this paper proves that coupling this approach and anisotropic diffusion within a joint iterative framework has more interesting results. For instance, this framework generates segmented images with more reduced artefacts on edges and background than those obtained after applying each method alone. This improvement is explained by the mutual interaction of global and local information, respectively introduced by the Mean Shift and anisotropic diffusion, and by the nature of this latter, smoothing while preserving continuities across edges. Some experiments, done on real ancient document images, illustrate these ideas and indicate that our proposed framework provides an efficient tool for document image segmentation and restoration.
Unsupervised acquisition of predominant word senses
Authors: Diana McCarthy, Rob Koeling, Julie Weeds, John Carroll
Venue: Computational Linguistics (2007)

There has been a great deal of recent research into word sense disambiguation, particularly since the inception of the Senseval evaluation exercises. Because a word often has more than one meaning, resolving word sense ambiguity could benefit applications that need some level of semantic interpretation of language input. A major problem is that the accuracy of word sense disambiguation systems is strongly dependent on the quantity of manually sense-tagged data available, and even the best systems, when tagging every word token in a document, perform little better than a simple heuristic that guesses the first, or predominant, sense of a word in all contexts. The success of this heuristic is due to the skewed nature of word sense distributions. Data for the heuristic can come from either dictionaries or a sample of sense-tagged data. However, there is a limited supply of the latter, and the sense distributions and predominant sense of a word can depend on the domain or source of a document. (The first sense of “star” for example would be different in the popular press and scientific journals). In this article, we expand on a previously proposed method for determining the predominant sense of a word automatically from raw text. We look at a number of different data sources and parameterizations of the method, using evaluation results and error analyses to identify where the method performs well and also where it does not. In particular, we find that the method does not work as well for verbs and adverbs as nouns and adjectives, but produces more accurate predominant sense information than the widely used SemCor corpus for nouns with low coverage in that corpus. We further show that the method is able to adapt successfully to domains when using domain specific corpora as input and where the input can either be hand-labeled for domain or automatically classified.
An EffectiveMulti-Layer Model for Controlling the Quality of Data
Authors: Carson Kai-Sang Leung, Mark Anthony F. Mateo, Andrew J. Nadler
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

Data mining aims to search for implicit, previously unknown, and potentially useful information that might be embedded in the data. It is well known that "garbage in, garbage out". Hence, to get meaningful mining results, a clean set of data is essential. In this paper, we propose an effective model for controlling the quality of data. Specifically, this three-layer model focuses on data validity and data consistency. To elaborate, the internal layer ensures that the observed data are valid and their values fall within reasonable ranges. The temporal layer ensures that data are consistent with their temporal behaviour. The spatial layer ensures that data are consistent with their spatial neighbours. A case study on applying our proposed model to real-life weather data for an agricultural application shows that our model is effective in controlling and improving data quality, and thus leading to better mining results. It is important to note the application of our proposed model is not confined to the weather data for agricultural applications. We also discuss, in this paper, how the proposed three-layer model can be effectively applicable to control the quality of data in some other real-life situations.
Building Single Fault Survivable Parallel Algorithms for Matrix Operations Using Redundant Parallel Computation
Authors: Yunfei Du, Panfeng Wang, Hongyi Fu, Jia Jia, Haifang Zhou, Xuejun Yang
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

As the size of today's high performance computers con- tinue to grow, node failures in these computers are becom- ing frequent events. Although checkpoint is the typical tech- nique to tolerate such failures, it often introduces a consid- erable overhead and has shown poor scalability on today's large scale systems. In this paper we defined a new term called fault toler- ant parallel algorithm which means that the algorithm gets the correct answer despite the failure of nodes. The fault tolerance approach in which the data of failed processes is recovered by modifying applications to recompute on all surviving processes is checkpoint-free. In particular, if no failure occurs, the fault tolerant parallel algorithms are the same as the original algorithms. We show the practicality of this technique by applying it to parallel dense matrix-matrix multiplication and Gaussian elimination to tolerate single process failure. Experimental results demonstrate that a process failure can be tolerated with a good scalability for the two fault tolerant parallel algorithms and the proposed fault tolerant parallel dense matrix-matrix multiplication is able to survive process failure with a very low perfor- mance overhead. The main drawback of this approach is non-transparent and algorithm-dependent.
Approach toward flexible semantic E-business in Web Service Community
Authors: Xuejuan Huang, Xinmeng Chen, Jiazhen Xu, Hua Li, Jinshuo Liu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The automated integration of semantic web service is one of the most promising approaches to building semantic e-business application on condition that business process's strategies or structure is dynamically changed. In this paper we discuss how to describe the semantic of web service using OWL-S and make a capability matching based on semantic knowledge of both service's advertisements and business definition. We improve the capability matching algorithm by adding some constraints. Specifically we carry out the dynamic integration of web service for e-business implementation in the circumstance of Web Service Community (WSC) we proposed.
Information technology education in india
Authors: P. Mani Joseph, Jibulal Nair, Smiju I. S., Barry Lunt
Venue: Proceedings of the 8th ACM SIGITE conference on Information technology education (2007)

The success of Indian firms and professionals in the Information technology (IT) arena during the last decade has been spectacular. India has built up valuable brand equity in the global IT markets. In IT-enabled services (ITES), India has emerged as the most preferred destination for business process outsourcing (BPO), a key driver of growth for the software industry and the services sector. This paper will provide an overview of IT Education in India focusing mainly on the curriculum and accreditation. Here a comparative study of Association for Computing Machinery (ACM) undergraduate model IT curriculum with Indian undergraduate IT curriculum is presented. The accreditation criteria used in this country for quality assurance is also discussed. regulating and maintaining standards in higher education. Education policy is formulated by a number of bodies under the Central Advisory Board of Education (CABE). In technical disciplines including IT education, the central policymaking and regulatory body is the All India Council for Technical Education (AICTE). The AICTE determines the requirements for new universities and programs of study, and outlines curriculum standards and norms [1].
A Decade of Increased Oil Recovery in Virtual Reality
Authors: Endre M. Lidal, Tor Langeland, Christopher Giertsen, Jens Grimsgaard, Rolf Helland
Venue: IEEE Computer Graphics and Applications (2007)

In the early '90s, VR was still in its infancy, but the Norwegian oil company Norsk Hydro saw the technology's potential. Still, there was no framework for developing VR for exploration and production. Working with the Norwegian research institute Christian Michelsen Research (CMR), Hydro began work on a proof-of-concept demonstration. The goal was to show that, by using VR technology, a company could perform critical E&P operations "more efficiently, with better quality, and at lower costs." In 1997, Hydro invested in a CAVE laboratory and CMR began developing the HydroVR application. The HydroVR project both changed work processes and increased revenue for petroleum E&P in general. Here, we describe the project's major application milestones and summarize how and why the project has sustained its extensive activity over the past 10 years.
Retiming for Synchronous Data Flow Graphs
Authors: N. Liveris, C. Lin, J. Wang, H. Zhou, P. Banerjee
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

In this paper we present a new algorithm for retiming synchronous dataflow (SDF) graphs. The retiming aims at minimizing the cycle length of an SDF. The algorithm is provably optimal and its execution time is improved compared to previous approaches.
Nonlinear Optical Data Processing and Filtering: A Feasibility Study
Authors: N. H. Farhat
Venue: IEEE Transactions on Computers (1975)

The feasibility of nonlinear optical data processing with photochromic materials is analyzed. It is shown that a host of useful computations may be achieved by incorporating nonlinear optical elements (transparencies) into conventional optical data processing channels.
Remembrance of streams past: overload-sensitive management of archived streams
Authors: Sirish Chandrasekaran, Michael Franklin
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

This paper studies Data Stream Management Systems that combine real-time data streams with historical data, and hence access incoming streams and archived data simultaneously. A significant problem for these systems is the I/O cost of fetching historical data which inhibits processing of the live data streams. Our solution is to reduce the I/O cost for accessing the archive by retrieving only a reduced (summarized or sampled) version of the historical data. This paper does not propose new summarization or sampling techniques, but rather a framework in which multiple resolutions of summarization/sampling can be generated efficiently. The query engine can select the appropriate level of summarization to use depending on the resources currently available. The central research problem studied is whether to generate the multiple representations of archived data eagerly upon data-arrival, lazily at query-time, or in a hybrid fashion. Concrete techniques for each approach are presented, which are tied to a specific data reduction technique (random sampling). The tradeoffs among the three approaches are studied both analytically and experimentally.
A new laser scalpel - a brief report
Authors: Pascal Rol, Franz Fankhauser, Pierre-David Henchoz, Sylwia Kwasniewska, Ulrich Dürr, Ceri England, Eugen Van der Zypen, Peter Niederer
Venue: Technology and Health Care (1996)

One may consider the clad silica fibre cutting probe as a cheap alternative of the popular sapphire probe, sharing some of its properties. Made of silica, the scalpels have a fair heat tolerance and may be used without cooling by liquids or gas as is necessary with sapphire blades. The laser scalpel described here is driven (powered) with a 10 W cw Nd:YAG laser energy source (1064 nm) and possesses good cutting and haemostatic properties. It may also be used with lasers emitting other wavelengths. One may assume that a diode laser emitting in the near infrared (800-810 nm) may have very similar, although not analogous cutting properties when used with the described scalpel.
A Performance Study of Java Communication Stacks over InfiniBand and Giga-bit Ethernet
Authors: Hongwei Zhang, Wan Huang, Jizhong Han, Jin He, Lisheng Zhang
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

With the popularity of Java programming language and the progress on Java compiler techniques, people have been trying to use Java to develop applications where C/C++ ruled before. However, to deliver comparable overall run-time performance with C/C++, Java I/O must also keep up with that of C/C++. In this paper, we studied comprehensively the performances of Java communication stacks over InfiniBand and Giga-bit Ethernet, and compared them with those of benchmarks written in C. We found the network performance of current version of Sun Java run-time could be parallel with C over Giga-bit Ethernet. But for higher performance InfiniBand network, the current communication stacks, mainly the TCP/IP emulation layers, showed rather poor performances. It can be concluded it's necessary to invent new approach to support InfiniBand in Java applications.
Information-theoretical comparison of likelihood ratio methods of forensic evidence evaluation
Authors: Daniel Ramos, Joaquin Gonzalez-Rodriguez, Grzegorz Zadora, Janina Zieba-Palus, Colin Aitken
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Forensic evidence in the form of two-level hierarchical multivariate continuous data is modelled using a likelihood ratio approach. Data are available from fragments of glass and of paint. Cross-entropy is used to compare the results with a neutral method and a method using the correct answers.
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Venue: Computer graphics and interactive techniques in Australasia and South East Asia (2007)

Here you will find the proceedings of the 5th International Conference on Computer Graphics and Interactive Techniques in Australasia and South-East Asia. This successful conference series has grown from the first event in Melbourne in 2003 to Singapore 2004, Dunedin 2005, Kuala Lumpur 2006 and finally back to Australia to Perth in 2007. This event provides a key forum in South East Asia and Oceania to bring together leading graphics researchers and practitioners from all over the world to discuss their latest results and meet others from their community. This year we received 55 submissions from which the program committee selected 35 high quality papers for presentation as full papers at the conference as well as numerous short papers. Given the quality of all the submissions, it was a difficult decision to choose the final selection. 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
Child development consulting blog: a childcare supporting system for child nurses
Authors: Aki Kono, Kimio Shintani, Yukiko Shirai, Yoshinori Sano, Hirohide Haga, Shigeo Kaneda
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

Recently, kindergartens and nursery schools in Japan are facing a big problem: an increase in the number of children who require special care and attention. Caring for these children causes many problems for child nurses, especially if they are young and inexperienced. To resolve the above problem, first the present "no record" situation is analyzed through field research. We clarify that a paper format record cannot be utilized effectively in daily nurturing environments. Second, this paper proposes a new blog system called "Child Development Consulting Blog." CDC-Blog is a communication platform for childcare professionals through which child nurses and visiting counselors mutually exchange messages.