ppxscal/embedding_network huggingface dataset:
Enhanced current gain in SiC power BJTs using a novel surface accumulation layer transistor concept
Authors: M. Jagadesh Kumar, Vinod Parihar
Venue: Microelectronic Engineering (2005)

In this paper, we demonstrate that the current gain of SiC power bipolar transistors can be improved by as large as 100% by using a novel surface accumulation layer transistor concept in which a reflecting boundary in the emitter reduces the base current. The reasons for the improved current gain are explained based on simulation results.
Design of a Chinese Name Card Understanding System
Authors: Hsi-Jian Lee, Shan-Hung Lee
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

In this paper, we present an automatic understanding system for Chinese name cards. After preprocessing of an input card image, we grouped characters into item blocks and segmented characters according to their aspect ratios and gap widths. After character extraction, we sent characters to a statistical multi-font character recognizer. We identified items according to their geometric characteristics and embedded key-characters. A user can edit segmentation results interactively and then save the results in the database for further applications. The high performance in the experimenats show the effectiveness of the proposed system.
Recognition for Large Sets of Handwritten Mathematical Symbols
Authors: Stephen M. Watt, Xiaofang Xie
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Natural and convenient mathematical handwriting recognition requires recognizers for large sets of handwritten symbols. This paper presents a recognition system for such handwritten mathematical symbols. We use a pre-classification strategy, in combination with elastic matching, to improve recognition speed. Elastic matching is a model-based method that involves computation proportional to the set of candidate models. To solve this problem, we prune prototypes by examining character features. To this end, we have defined and analyzed different features. By applying these features into an elastic recognition system, the recognition speed is improved while maintain high recognition accuracy.
A comparative study on text representation schemes in text categorization
Authors: Fengxi Song, Shuhai Liu, Jingyu Yang
Venue: Pattern Analysis Applications (2005)

It is well known that the classification effectiveness of the text categorization system is not simply a matter of learning algorithms. Text representation factors are also at work. This paper will consider the ways in which the effectiveness of text classifiers is linked to the five text representation factors: &#x201c;stop words removal&#x201d;, &#x201c;word stemming&#x201d;, &#x201c;indexing&#x201d;, &#x201c;weighting&#x201d;, and &#x201c;normalization&#x201d;. Statistical analyses of experimental results show that performing &#x201c;normalization&#x201d; can always promote effectiveness of text classifiers significantly. The effects of the other factors are not as great as expected. Contradictory to common sense, a simple binary indexing method can sometimes be helpful for text categorization.
A New Association Rule-Based Text Classifier Algorithm
Authors: Supaporn Buddeewong, Worapoj Kreesuradej
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

This paper proposes a new association rule-based text classifier algorithm to improve the prediction accuracy of Association Rule-based Classifier By Categories (ARC-BC) algorithm. Unlike the previous algorithms, the proposed association rule generation algorithm constructs two types of frequent itemsets. The first frequent itemsets, i.e. Lk, contain all term that have no an overlap with other categories. The second frequent itemsets, i.e. OLk, contain all features that have an overlap with other categories. In addition, this paper also proposes a new join operation for the second frequent itemsets. The experimental results are shown a good performance of the proposed classifier.
Improving memory system performance with energy-efficient value speculation
Authors: Nana B. Sam, Martin Burtscher
Venue: ACM SIGARCH Computer Architecture News (2005)

Microprocessor speeds have been improving much faster than memory speeds, resulting in the CPU spending a larger and larger amount of time waiting for data. Processor designers have employed several ways to improve memory performance, including hierarchical caching, prefetching, and faster memory chips. Yet, memory accesses still represent a major performance bottleneck and much remains to be done to tolerate the increasing memory latencies. Load-value prediction has been shown to effectively hide some of this latency. However, the hardware required to achieve good performance is substantial, making load-value prediction unappealing in light of increasing power constraints. In this paper, we present a novel predictor that significantly increases CPU performance while at the same time decreasing the energy consumption of the entire processor relative to a baseline with a well-performing hybrid load-value predictor.
Stereo Matching with Linear Superposition of Layers
Authors: Yanghai Tsin, Sing Bing Kang, Richard Szeliski
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

In this paper, we address stereo matching in the presence of a class of non-Lambertian effects, where image formation can be modeled as the additive superposition of layers at different depths. The presence of such effects makes it impossible for traditional stereo vision algorithms to recover depths using direct color matching-based methods. We develop several techniques to estimate both depths and colors of the component layers. Depth hypotheses are enumerated in pairs, one from each layer, in a nested plane sweep. For each pair of depth hypotheses, matching is accomplished using spatial-temporal differencing. We then use graph cut optimization to solve for the depths of both layers. This is followed by an iterative color update algorithm which we proved to be convergent. Our algorithm recovers depth and color estimates for both synthetic and real image sequences.
SIMBAS: a process-oriented simulation language
Authors: James Daley
Venue: ACM SIGSIM Simulation Digest (1978)

A process-oriented simulation language is described, which is an extension of BASIC, is implementable using an existing BASIC interpreter, and uses the general semaphore as a modeling primitive. Examples and a discussion of the implementation are included.
Dynamic pricing based on asymmetric multiagent reinforcement learning: Research Articles
Authors: Ville Könönen
Venue: International Journal of Intelligent Systems (2006)

A dynamic pricing problem is solved by using asymmetric multiagent reinforcement learning in this article. In the problem, there are two competing brokers that sell identical products to customers and compete on the basis of price. We model this dynamic pricing problem as a Markov game and solve it by using two different learning methods. The first method utilizes modified gradient descent in the parameter space of the value function approximator and the second method uses a direct gradient of the parameterized policy function. We present a brief literature survey of pricing models based on multiagent reinforcement learning, introduce the basic concepts of Markov games, and solve the problem by using proposed methods. &copy; 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 73&ndash;98, 2006.
Information systems outsourcing relationship factors: detailed conceptualization and initial evidence
Authors: Tim Goles, Wynne W. Chin
Venue: ACM SIGMIS Database (2005)

Outsourcing is now a commonly accepted means of meeting organizational IS needs. One facet of recent outsourcing research has begun to concentrate on the relationship between customers and their service providers. However, this line of research is hampered by a lack of consistent conceptual focus, and a corresponding inconsistent treatment of constructs associated with the relationship. This paper uses Relational Exchange Theory as a conceptual basis for identifying the individual constructs that comprise a relationship. It then develops and tests a set of items to measure those constructs, using structural equation modeling and survey data collected from U.S. outsourcing customers.
A Layered View Model for XML Repositories and XML Data Warehouses
Authors: R. Rajugan, Tharam S. Dillon, Elizabeth Chang, Ling Feng
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

The Object-Oriented (OO) conceptual models have the power in describing and modeling real-world data semantics and their inter-relationships in a form that is precise and comprehensible to users. Conversely, XML is fast emerging as the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS) and databases. With software engineering placing added emphasis on MDA solutions and modeling approaches, it is important to investigate data models for EIS that are abstract enough to be utilized under the MDA paradigm, yet is adoptable in the current data engineering practice. In this paper, we demonstrate a set of language independent conceptual operators for constructing abstract views for XML. The proposed view model has conceptual and logical extensions for supporting abstract views definitions at the conceptual level.
Approximate Information Retrieval for Heterogeneity Ontologies
Authors: Dazhou Kang, Hanwu Chen, Baowen Xu, Jianjiang Lu, Keyue Li, William C. Chu
Venue: Proceedings of the 2005 International Conference on Cyberworlds (2005)

Ontology-based information retrieval is precise and effective but suffers from the problem of ontology heterogeneity. This paper focuses on the approximate information retrieval approach to solve the heterogeneity problem of both common ontologies as well as fuzzy ontologies on the semantic web. Approximate information retrieval needs to find approximations of concepts. However, current methods cannot find the best approximations of concepts for common ontologies, and there is still no published work for fuzzy ontologies. This paper firstly proposes a method of approximate information retrieval between common ontologies. It defines multielement least upper bounds and multielement greatest lower bounds, and then simplifies the multielement bounds to remove redundancy. It provides effective algorithms to find the simplified multielement bounds, and get the best approximations of concepts from the bounds. Then for the fuzzy ontologies, the paper defines cut concepts to transform fuzzy concepts into common concepts, and then applies the proposed method for approximate information retrieval between fuzzy ontologies. The improved algorithms for fuzzy ontologies are given to make the method more feasible and effective.
e-Science and its application: Life Sciences and Finance
Authors: R H. Perrott
Venue: Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing (2005)

In 2001 the UK government announced new funding for an initiative known as e-Science. This Initiative was challenged with developing a new way of collaborative research using grid as the information utility. The Initiative was structured to provide funding to support a national grid infrastructure, tackle large scale scientific research problems and to engage in projects with industry. This paper considers the impact of e-Science in the UK and, in particular, in the finance and life sciences sectors.
Flexible Template and Model Matching Using Intensity
Authors: Bernard F. Buxton, Vasileios Zografos
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

Intensity-based image and template matching is briefly reviewed with particular emphasis on the problems that arise when flexible templates or models are used. Use of such models and templates may often lead to a very small basin of attraction in the error landscape surrounding the desired solution and also to spurious, trivial solutions. Simple examples are studied in order to illustrate these problems which may arise from photometric transformations of the template, from geometric transforms of it or from internal parameters of the template that allow similar types of variation. It is pointed out that these problems are, from a probabilistic point of view, exacerbated by a failure to model the whole image, i.e. both the foreground object or template and the image background, which a Bayesian approach strictly requires. Some general remarks are made about the form of the error landscape to be expected in object recognition applications and suggestions made as to optimisation techniques that may prove effective in locating a correct match. These suggestions are illustrated by a preliminary example.
Higher Weights for Ternary and Quaternary Self-Dual Codes*
Authors: Steven T. Dougherty, T. Aaron. Gulliver, Manabu Oura
Venue: Designs, Codes and Cryptography (2006)

We study higher weights applied to ternary and quaternary self-dual codes. We give lower bounds on the second higher weight and compute the second higher weights for optimal codes of length less than 24. We relate the joint weight enumerator with the higher weight enumerator and use this relationship to produce Gleason theorems. Graded rings of the higher weight enumerators are also determined.
IUI mining: human expert guidance of information theoretic network approach
Authors: S. Kooptiwoot, M. A. Salam
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

The intra uterine insemination (IUI) is an assisted reproductive technique, enabling infertile couples to achieve pregnancy. We propose the variation of information theoretic network approach which uses human expert guidance to knowledge mining and suggest some possible modifications to IUI treatment plan in order to improve overall success rates. The information theoretic network algorithm employs the statistic significance to construct the network. We propose a new algorithm by adding up the medical significant criteria from human expert to construct the information theoretic network. We found that this new algorithm give us more reasonable result to human expert than the original information theoretic approach. The reliability of the knowledge got from this new algorithm is more acceptable than the original algorithm. And also human experts accept and satisfy the knowledge got from this new algorithm than the original algorithm. This shows that using human expert guidance with the original information theoretic approach to be the new algorithm can give us better result.
Ultra Folded High-Speed Architectures for Reed-Solomon Decoders
Authors: Kavish Seth, K. N. Viswajith, S. Srinivasan, V. Kamakoti
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

In this paper, a new high-speed VLSI architecture for decoding Reed-Solomon codes with the Berlekamp-Masseyalgorithm is presented. The proposed scheme uses the fully folded systolic architecture in which a single array of processors, computes both the error-locator and the error-evaluator polynomials. The proposed scheme utilizes the folding property of systolic array architectures and reduces the number of multipliers and adders drastically at the expense of some compromise in the speed. More interestingly, the proposed architecture requires approximately 60% fewer multipliers and a simpler control structure than the popular RiBM architecture. The reduction in the number of multipliers and adders in the proposed architecture leads to smaller silicon area and lower power consumption.
Framework and Network Based Multimedia Object Management Environment
Authors: Chris Germano, Taehyung George Wang, Akira K. Onoma
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

Because multimedia objects are becoming more prevalent, on ever-increasing volume, inventing an efficient multimedia object management environment is a matter of increasing urgency. In recognition of this crisis, we developed the Multimedia Object Management Environment (MOME) that includes a suite of tools such as the Vortex Framework, and Network File Indexer (NFI). MOME also includes a fully featured graphical user interface for maximum user control and flexibility. With meta-data, it automatically generates indexes and paths for different types of multimedia objects and allows users to quickly find what they are looking for. In this paper, we address the background, architecture, and performance of MOME in detail.
On the cost-ineffectiveness of redundancy in commercial P2P computing
Authors: Matthew Yurkewych, Brian N. Levine, Arnold L. Rosenberg
Venue: Proceedings of the 12th ACM conference on Computer and communications security (2005)

We present a game-theoretic model of the interactions between server and clients in a constrained family of commercial P2P computations (where clients are financially compensated for work). We study the cost of implementing redundant task allocation (redundancy, for short) as a means of preventing cheating. Under the assumption that clients are motivated solely by the desire to maximize expected profit, we prove that, within this framework, redundancy is cost effective only when collusion among clients, including the Sybil attack, can be prevented. We show that in situations where this condition cannot be met, non-redundant task allocation is much less costly than redundancy.
Text Degradations and OCR Training
Authors: Elisa H. Barney Smith, Tim Andersen
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Printing and scanning of text documents introduces degradations to the characters which can be modeled. Interestingly, certain combinations of the parameters that govern the degradations introduced by the printing and scanning process affect characters in such a way that the degraded characters have a similar appearance, while other degradations leave the characters with an appearance that is very different. It is well known that (generally speaking) a test set that more closely matches a training set will be recognized with higher accuracy than one that matches the training set less well. Likewise, classifiers tend to perform better on data sets that have lower variance. This paper explores an analytical method that uses a formal printer/scanner degradation model to identify the similarity between groups of degraded characters. This similarity is shown to improve the recognition accuracy of a classifier through model directed choice of training set data.
Dynamic Selection of Composite Web Services Based on a Genetic Algorithm Optimized New Structured Neural Network
Authors: Lei YANG, Yu DAI, Bin ZHANG, Yan GAO
Venue: Proceedings of the 2005 International Conference on Cyberworlds (2005)

In order to realize a high-quality and goodperformance service composition, based on current approach, we propose a new QoS-driven dynamic selection of composite Web Services, which takes account of both the QoS properties and interface parameters matching degree. When doing the selection, we aware that the task is more or less a multistage decision-making process. Motivated by neural networks' high parallel performance and genetic algorithm's powerful computation ability, a genetic algorithm optimized neural network algorithm is proposed in this paper for such task. In order to make this algorithm more adaptable for multistage decision-making problem, we propose a new structured neural network to express the composed service instead of using the traditional neural networks, which minimizes the neurons involved and shows high performance than the earlier ones. Finally, through experimentation one can find that method proposed in this paper is more practical and effective than others.
Research note: Anatomy of UDP and M-VIA for cluster communication
Authors: Xiao Zhang, Laxmi N. Bhuyan, Wu-Chun Feng
Venue: Journal of Parallel and Distributed Computing (2005)

High interprocess communication latency is detrimental to parallel and grid computing. Over the years, the network bandwidth has increased rapidly while the end-to-end latency has not decreased much. This is because the latency is dominated by the protocol software execution time in the kernel instead of the raw transmission time over the link. In this paper, we perform an anatomical analysis of the complete communication path between a sender and a receiver through measurements. We present an in-depth evaluation of various components of the UDP protocol over Fast Ethernet. Virtual Interface Architecture (VIA) protocol has been recently proposed to overcome the software overhead of the TCP/UDP/IP protocol. We analyze M-VIA, a modular VIA implementation for Linux over Ethernet, and compare its performance with UDP. The aim of our experiments is to present the protocol overheads in details rather than to suggest new techniques to reduce overheads.
Digital divide and learning disabilities: counteracting educational exclusion in information society
Authors: M. Pieper
Venue: Issue 83 (September 2005) (2005)

A 1998 inquiry by the U.S. government showed that 42% of all U.S. households had a computer and 26% regularly used e-mail or more far-reaching Internet-based services. More recent but not fully comparable studies have revealed, that gradually, the originally extremely remarkable differences in Internet use between men and women and young and elderly have decreased, which is probably due primarily to the increasing user-friendliness and controllability of graphical user interfaces. But at present, income-caused, educationally conditioned differences in Internet use are increasing dramatically.
A self-learning worm using importance scanning
Authors: Zesheng Chen, Chuanyi Ji
Venue: Proceedings of the 2005 ACM workshop on Rapid malcode (2005)

The use of side information by an attacker can help a worm speed up the propagation. This philosophy has been the basis for advanced worm scanning mechanisms such as hitlist scanning, routable scanning, and importance scanning. Some of these scanning methods use information on vulnerable hosts. Such information, however, may not be easy to collect before a worm is released. Questions then arise whether and how a worm can self-learn and use such information while propagating, and how virulent the resulting worm may be. In this paper, we design a self-learning worm using importance scanning. An optimal yet practical importance-scanning strategy is derived based on a new metric. A self-learning worm is demonstrated to have the ability to accurately estimate the underlying vulnerable-host distribution if a sufficient number of infected hosts are observed. Experimental results based on parameters chosen from Code Red show that after accurately estimating the distribution of vulnerable hosts, a self-learning worm can spread much faster than a random-scanning worm, a permutation-scanning worm, and a Class A routing worm. Some guidelines for detecting and defending against such self learning worms are also discussed.