ppxscal/embedding_network huggingface dataset:
A note on reducing parallel model simulations to integer sorting
Authors: Yossi Matias, Uzi Vishkin
Venue: Proceedings of the 9th International Symposium on Parallel Processing (1995)

We show that simulating a step of a FETCH&ADD PRAM model on an EREW PRAM model can be made as efficient as integer sorting. In particular, we present several efficient reductions of the simulation problem to various integer sorting problems. By using some recent algorithms for integer sorting, we get simulation algorithms on CREW and EREW that take o(n lg n) operations where n is the number of processors in the simulated CROW machine. Previous simulations were using /spl Theta/(n lg n) operations. Some of the more interesting simulation results are obtained by using a bootstrapping technique with a CRCW PRAM algorithm for hashing.
Gracefully Degradable Pipeline Networks
Authors: Robert Cypher, Ambrose Kofi Laing
Venue: Proceedings of the 11th International Symposium on Parallel Processing (1997)

A pipeline is a linear array of processors with an input node at one end and an output node at the other end. This paper presents k-gracefully-degradable graphs which, given any set of up to k faults, contain a pipeline that uses all the healthy processor nodes. Our constructions are designed to tolerate faulty input and output nodes, but they can be adapted to provide solutions when the input and output nodes are guaranteed to be healthy. All of our constructions are optimal in terms of the number of nodes and the maximum degree of the processor nodes.
Recognition of Chinese business card
Authors: Yaw-Huei Chiou, Hsi-Jian Lee
Venue: Proceedings of the 4th International Conference on Document Analysis and Recognition (1997)

Business cards include many kinds of information, such as names, addresses and telephone numbers. In order to use the information effectively, it is necessary to extract the information from the cards automatically in order to build a database. The goal of this paper is to extract and recognize characters from color business cards. To separate the foreground from the background in a card, we assign all pixels to eight color types. Then we calculate a dynamic threshold using the color information to extract the foreground. Next, we extract the characters by four steps: (i) connected component extraction, (ii) local thresholding, (iii) mark, line and noise deletion, and (iv) character grouping. Finally, we recognize the characters by a statistical Chinese and English character recognition system. We test 30 business cards which have Chinese characters, English characters, numerals and punctuation marks. The extraction rate and accuracy for our system are 96.97% and 95.43% respectively. The recognition rate is 88.78% for Chinese characters and 97.58% for English characters, numerals and punctuation marks.
Service quality in TINA-quality of service trading in open network architecture
Authors: Takeo Hamada, Stephanie Hogg, Jarno Rajahalme, Carlo Licciardi, Lill Kristiansen, Per Fly Hansen
Venue: Proceedings of the 1st International Conference on Enterprise Distributed Object Computing (1997)

Enterprise level QoS issues are discussed, from which QoS evolution paths are derived. Service level QoS issues are identified and they have been studied as apart of service quality issues in TINA service architecture. TINA stream binding and its role in the TINA QoS framework are presented. A soft guarantee of stream quality is proposed, which does not require strict resource reservation. Soft guarantee concept combined with TINA stream binding architecture supports progressive evolution of service quality.
Robust Character Recognition of Gray-Scaled Images with Graphical Designs and Noise
Authors: Minako Sawaki, Norihiro Hagita, Kenichiro Ishii
Venue: Proceedings of the 4th International Conference on Document Analysis and Recognition (1997)

This paper proposes a method for recognizing characters in gray-scale images with graphical designs and noise. Our previous method for binary images is robust against graphical designs, however, it is easily affected by binarization conditions or scanning conditions. Therefore, we improve the method to be tolerant for such conditions by handling gray-scaled images directly. First, a projection profile for text-line extraction and a similarity value for character recognition are expanded for gray-scaled images. Next, learning method of adaptive threshold values against the degree of degradation and variations of intensity levels are introduced to suppress spurious candidates during recognition process. Experimental results for fifty Japanese newspaper headlines show that the proposed method achieves higher recognition rates than our previous method in the wide range of scanning brightness conditions.
Automatic Gray Level Thresholding Based on Relevant Features for Subjective Decisions
Authors: Fabrício Martin Lopes, Luís Augusto Consularo
Venue: Proceedings of the 15th Brazilian Symposium on Computer Graphics and Image Processing (2002)

This work searches the relationship between global criteria for automatic image gray levelthresholding, and the subjective decision concerned to best image gray level threshold. An approach based on fuzzy membership functions is proposed to confirm this relationship. As aside, an efficient uncertainty measure arose. A set of 100 images was trained and tested, and their results will be discussed.
Generalized Partial Indexes
Authors: Praveen Seshadri, Arun N. Swami
Venue: Proceedings of the Eleventh International Conference on Data Engineering (1995)

This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this information to significantly improve average query performance. Results from simulation experiments demonstrate that the proposed generalized partial indexing strategies perform well compared to the traditional approach to indexing.
An Immune Neural Network Used for Classification
Authors: Lei Wang, Licheng Jiao
Venue: Proceedings of the 2001 IEEE International Conference on Data Mining (2001)

Based on analyzing the immune phenomena in nature and utilizing performances of ANN, a novel network model, i.e., an immune neural network (INN), is proposed which integrates the immune mechanism and the function of neural information processing. The learning algorithm of INN is mainly about the selection of an excitation function and an adaptive algorithm of the network.
Towards the Reverse Engineering of Denormalized Relational Databases
Authors: Jean-Marc Petit, Farouk Toumani, Jean-Francois Boulicaut, Jacques Kouloumdjian
Venue: Proceedings of the Twelfth International Conference on Data Engineering (1996)

This paper describes a method to cope with denormalized relational schemas in a database reverse engineering process. We propose two main steps to improve the understanding of data semantics. Firstly we extract inclusion dependencies by analyzing the equi-join queries embedded in application programs and by querying the database extension. Secondly we show how to discover only functional dependencies which influence the way attributes should be restructured. The method is interactive since an expert user has to validate the presumptions on the elicited dependencies. Moreover, a restructuring phase leads to a relational schema in third normal form provided with key dependencies and referential integrity constraints. Finally, we sketch how an Entity-Relationship schema can be derived from such information.
Performance of Asynchronous Linear Iterations with Random Delays
Authors: Adrian Moga, Michel Dubois
Venue: Proceedings of the 10th International Parallel Processing Symposium (1996)

In this paper we investigate the speedup potential of asynchronous iterative algorithms over their synchronous counterparts for the special case of linear iterations. The space of linear iterations of size two is explored by simulation and analytical methods. We find cases and conditions for high asynchronous speedups. However, averaging asynchronous speedups over the whole set of iteration matrices reveals that the domain of matrices with high speedups is not sizable and that asynchronous iterations perform no better than synchronous ones over the entire convergence space.
Early field experience with the Software Reconnaissance technique for program comprehension
Authors: Norman Wilde, Christopher Casey
Venue: Proceedings of the 1996 International Conference on Software Maintenance (1996)

Software Reconnaissance is a dynamic analysis technique to help programmers locate code that they need to understand, fix, or enhance in an unfamiliar system. The technique was originally motivated by comments by industrial maintainers about the need for better ways of locating software features in large systems. It was then prototyped in a university setting and an initial tool called RECON was developed. The paper describes four case studies applying Reconnaissance to three different industrial programs of moderate size. Reconnaissance seems to be effective in finding "places to start looking" for maintainers of unfamiliar code. It can also be used to recover a traceability relation between program features and program code that may help identify design patterns. The case studies are the initial phase of an ongoing technology transfer project of the Software Engineering Research Center, to make Software Reconnaissance into a usable industrial technique.
A study of the effects of software development practices on software maintenance effort
Authors: Sandra Slaughter, Rajiv D. Banker
Venue: Proceedings of the 1996 International Conference on Software Maintenance (1996)

Many maintenance problems derive from inadequate software development practices. Poor design choices result in complex software that may be costly to support and difficult to change. A general framework based upon software complexity is proposed that could be used to assess the potential maintenance impact of development tools and techniques. To test the framework, a study was conducted in two commercial organizations. The results indicate that reduced maintenance effort is associated with development practices, including structured programming, report generators and packaged software. A surprising finding is that use of a software code generator is associated with increased maintenance effort.
Wavelet-Based Compared to Function-Based On-Line Signature Verification
Authors: Andréa Vergara da Silva, Daniel Santana de Freitas
Venue: Proceedings of the 15th Brazilian Symposium on Computer Graphics and Image Processing (2002)

Abstract. We implemented two direct methods for on-line signature verification. First, data produced by a graphics tablet describing a signature to be tested are treated with wavelet transforms to generate features to be nonlinearly confronted with a reference signature chosen among 10 previously stored tryings from the same writer. In order to recover the time dependence lost in the wavelet treatment, we included the level of departure from the diagonal line in the warping function as a complementary measure of distance. In a second approach, the functions x(t) and y(t) describing position in time of each pixel of the same test signature were directly (though nonlinearly) compared to their counterparts from the reference. We concluded that both approaches showed good fidelity to all details in the signatures, with acceptable false rejection rates (we obtained around 30% FRR) to this kind of biometry. On the other hand, the inclusion of the wavelet transform turned out to be an essential step for the achievement of low false acceptation rates. It was only with the inclusion of the wavelet transform, at the right level of resolution, that we managed to completely prevent trained forgeries to be accepted (0% FAR) in the cases studied.
Deadlock- and Livelock-Free Routing Protocols for Wave Switching
Authors: José Duato, Pedro López, Sudhakar Yalamanchili
Venue: Proceedings of the 11th International Symposium on Parallel Processing (1997)

Wave switching is a hybrid switching technique for high performance routers. It combines wormhole switching and circuit switching in the same router architecture. Wave switching achieves very high performance by exploiting communication locality. When two nodes are going to communicate frequently, a physical circuit is established between them. By combining circuit switching, pre-established physical circuits and wave pipelining across channels and switches, it is possible to increase network bandwidth considerably, also reducing latency for communications that use pre-established physical circuits.In this paper, we propose two protocols for routers implementing wave switching. The first protocol handles the network as a cache of circuits, automatically establishing a circuit when two nodes are going to communicate. Subsequent communications use the previously established circuit. When a new circuit requests channels belonging to another circuit, a replacement algorithm selects the circuit to be torn down. The second protocol relies on the programmer and/or the compiler to decide when a circuit should be established or torn down for a set of messages. Also, we show that the proposed protocols are always able to deliver messages, and are deadlock- and livelock-free.
Evaluating OCR and Non-OCR Text Representations for Learning Document Classifiers
Authors: Markus Junker, Rainer Hoch
Venue: Proceedings of the 4th International Conference on Document Analysis and Recognition (1997)

In literature, many feature types and learning algorithms are proposed for document classification. However, an extensive and systematic evaluation of the various approaches has not been done yet. In order to investigate different text representations for document classification, we have developed a tool which transforms documents into feature-value representations suitable for standard learning algorithms. In this paper we investigate seven document representations for German texts based on n-grams and single words. We compare their effectiveness in classifying OCR texts and the corresponding correct ASCII texts in two domains: business letters and abstracts of technical reports. Our results indicate that the use of n-grams is an attractive technique which can even compare to techniques relying on a morphological analysis. This holds for OCR texts as well as for correct ASCII texts.
Monte Carlo and molecular dynamics simulations using p4
Authors: K. J. Runge, L. P. Lee, J. Correa, R. T. Scalettar, Vojin G. Oklobdzija
Venue: Proceedings of the 9th International Symposium on Parallel Processing (1995)

Monte Carlo (MC) and molecular dynamics (MD) simulations are powerful tools for understanding the properties of systems of interacting electrons and phonons in a solid. When mobile electrons are studied, these simulations are limited to a few hundred particles. More powerful machines and algorithms must be used to address many of the most important issues in the field. We present results from using the p4 parallel programming system on a variety of parallel architectures to conduct MC and MD simulations.
An Efficient Clustering Algorithm for Market Basket Data Based on Small Large Ratios
Authors: Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
Venue: Proceedings of the 25th International Computer Software and Applications Conference on Invigorating Software Development (2001)

In this paper, we devise an efficient algorithm for clustering market-basket data items. In view of the nature of clustering market basket data, we devise in this paper a novel measurement, called the small-large (abbreviated as SL) ratio, and utilize this ratio to perform the clustering. With this SL ratio measurement, we develop an efficient clustering algorithm for data items to minimize the SL ratio in each group. The proposed algorithm not only incurs an execution time that is significantly smaller than that by prior work but also leads to the clustering results of very good quality.
Establishing Enterprise Communities
Authors: Constantin Serban, Xuhui Ao, Naftaly Minsky
Venue: Proceedings of the 5th IEEE International Conference on Enterprise Distributed Object Computing (2001)

Abstract: One of the most important challenges facing the builders of enterprise software is the reliable implementation of the policies that are supposed to govern the various communities operating within an enterprise. Such policies are widely considered fundamental to enterprise modeling, and their specification were the subject of several recent investigations. But specification of the policy that is to govern a given community is only the first step towards its implementation-the second, and more critical step is to ensure that all members of the community actually conform to the specified policy. The conventional approach to the implementation of a policy is to build it into all members of the community subject to it. But if the community in question is large and heterogeneous, and if its members are dispersed throughout a distributed enterprise, then such "manual" implementation of its policy would be too laborious and error-prone to be practical. Moreover, a policy implemented in this manual manner would be very unstable with respect to the evolution of the system, because it can be violated by a change in the code of any member of community subject to it. It is our thesis that the only reliable way for ensuring that an heterogeneous distributed community of software modules and people conforms to a given policy is for this policy to be strictly enforced. A mechanism for establishing enterprise communities by formally specifying their policies, and by having these policies enforced is the subject of this paper.
Detection of Fault-Prone Software Modules During a Spiral Life Cycle
Authors: Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, Gary P. Trio
Venue: Proceedings of the 1996 International Conference on Software Maintenance (1996)

This is an experience report on identifying fault-prone modules in a subsystem of the Joint Surveillance Target Attack Radar System, jstars, a large tactical military system. The project followed the spiral life cycle model. The iterations of the system were developed in fortran about one year apart. We developed a discriminant analysis model using software metrics from one iteration to predict whether or not each module in the next would be considered fault-prone. Tactical military software is required to have high reliability. Each software function is often considered mission-critical, and the lives of military personnel often depend on mission success. In our project, each iteration of a spiral life cycle development produced a system that was suitable for operational testing. A risk analysis based on operational testing guided development of the next iteration. Identifying fault-prone modules early in the development of an iteration can lead to better reliability. The results confirm previously published studies that discriminant analysis can be a useful tool in identification of fault-prone software modules. This study used consecutive iterations, first, to build, and then, to evaluate the model. This model validation approach is more realistic than earlier studies which split data from one project to simulate two iterations. Model results could be used to identify those modules that would probably benefit from extra reviews and testing, and thus, reduce the risk of unexpected problems with those modules.
Reducing Risks of Widespread Faults and Attacks for Commercial Software Applications: Towards Diversity of Software Components
Authors: Marco Casassa Mont, A. Baldwin, Y. Beres, Keith Harrison, M. Sadler, S. Shiu
Venue: Proceedings of the 26th International Computer Software and Applications Conference on Prolonging Software Life: Development and Redevelopment (2002)

Recent IT attacks demonstrated how vulnerable consumers and enterprises are when adopting commercial and widely deployed operating systems, software applications and solutions.Diversity in software applications is fundamental to increase chances of survivability to faults and attacks. Current approaches to diversity are mainly based on the development of multiple versions of the same software, their parallel execution and the usage of votingmechanisms. Because of the high cost, they are used mainly for very critical and special cases.We introduce and discuss an alternative method to ensure diversity for common, widespread software applications without requiring additional resources. We describe a few encouraging results obtained from simulations.
Formal Specification in Collaborative Design of Critical Software Tools
Authors: David Coppit, Kevin J. Sullivan
Venue: The 3rd IEEE International Symposium on High-Assurance Systems Engineering (1998)

Engineers use software tools to analyze designs for critical systems. Because important decisions are based on tool results, tools must provide valid modeling constructs; engineers must understand them to validate their models; and tools must be implemented without major error. Such tools thus demand careful conceptual and software design. One aspect of such design is the use of rigorous specifica-tion and design techniques. This paper contributes a case study on the use of such techniques in the collaborative development of a dynamic fault tree analysis tool. The collaboration involved software engineering researchers knowledgeable in software specification and design and reliability engineering researchers expert in fault tree analysis. Our work revealed conceptual and implementa-tion errors in an earlier version of the tool. Our study supports the position that there is a need for rigorous software specification and design in developing novel analysis tools, and that collaboration between software engineers and domain experts is feasible and profitable
Performance evaluation of a new parallel preconditioner
Authors: Keith D. Gremban, Gary L. Miller, Marco Zagha
Venue: Proceedings of the 9th International Symposium on Parallel Processing (1995)

The linear systems associated with large, sparse, symmetric, positive definite matrices are often solved iteratively using the preconditioned conjugate gradient method. We have developed a new class of preconditioners, support tree preconditioners, that are based on the connectivity of the graphs corresponding to the matrices and are well-structured for parallel implementation. We evaluate the performance of support tree preconditioners by comparing them against two common types of preconditioners: diagonal scaling and incomplete Cholesky. Support tree preconditioners require less overall storage and less work per iteration than incomplete Cholesky preconditioners. In terms of total execution time, support tree preconditioners outperform both diagonal scaling and incomplete Cholesky preconditioners.