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Design and Implementation of NAREGI SuperScheduler Based on the OGSA Architecture

Journal of Computer Science & Technology 2006年第4期21卷 521-528页

作者： Satoshi Matsuoka Masayuki Hatanaka Yasumasa Nakano Yuji Iguchi Toshio Ohno Kazushige Saga Hidemoto Nakada Global Scientific Information and Computing Center Tokyo Institute of Technology 2-12-10okayama Meguro-ku Tokyo 152-8550 Japan Center for Grid Research and Development National Institute of Informatics 1-105 Kanda-Jinbocho Chiyoda-ku Tokyo 101-0051 Japan Linux Software Development Div. Server Systems Unit. Fujitsu Limited 130 Miyamoto Numazu-shi Shizuoka410-0396 Japan Grid Technology Research Center National Institute of Advanced Industrial Science and Technology 1-18-13 Sotokanda Chiyoda-ku Tokyo 101-0021 Japan

NAREGI is a 5-year Japanese National Grid Project during 2003--2007, whose chief aim is to develop a set of grid middleware to serve as a basis for future e-Science. NAREGI also aims to lead the way in standardization of grid middleware, based on the OGSA architecture. Its super-scheduler is based on the proposed OGSA-EMS Architecture, in that it becomes the first working implementation that implements the documented component relationships within the OGSA-EMS architecture document v.l.0. Through the efforts and experience in the design and implementation, it has been confirmed that the documented OGSA-EMS architecture is quite feasible, but will require significant amount of refinement and speed improvements to finalize its detailed specifications. The super-scheduler also supports co-allocation across multiple sites to support automated execution of grid-based MPIs that execute across machines. Such a resource allocation requires sophisticated interactions between the OGSA-EMS components not covered in the current OGSA-EMS architecture, some of which are non-trivial. Overall, job scheduling with OGSA-EMS has proven to not only work, but also that its job allocation and execution time is within reasonable bounds.

关键词： grid scheduling resource management open grid services architecture OGSA

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Parallelization of reverse time migration using MPI + OpenMP

Parallelization of reverse time migration using MPI + OpenMP

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International Conference on advanced Communication, Control and computing Technologies (ICACCCT)

作者： S. Kansara Akanksha Gardas Naresh Kumar Gujarat Technological University Gujarat India Center of Development for Advanced Computing Pune India

ISBN: (纸本)9781467395465

Increasing computational power ensures effective implementation of high-end HPC applications but does not guarantee performance. Seismic modelling is one such high computational demanding application. In oil and gas industries, reverse time migration is one of the important migration algorithms that guarantees accurate imaging results but its practical implementation gets hindered due to its high computational cost. In this paper we will discuss reverse time migration for solving 2D wave equations using finite difference method and its parallel implementation using Message Passing Interface(MPI) and OpenMP.

关键词： Computational modeling Propagation Mathematical model Multicore processing Imaging Conferences Finite difference methods

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Improving the quality of Machine Translation using rule based tense synthesizer for Hindi

Improving the quality of Machine Translation using rule base...

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IEEE International Advance computing Conference, IACC

作者： Shashi Pal Singh Ajai Kumar Hemant Darbari Anshika Gupta AAI Center for development of Advanced Computing Pune India Banasthali Vidyapith Banasthali India

Translation of English documents into Hindi language is becoming an integral part for facilitating communication. The major population of India where 366 million people uses Hindi as primary language, for them providing information in Hindi is an important task the translation of English documents may be manually or automatically. When translation done manually the chances are rare for errors, but when we use any translation machines or engine the outputs received from these machines for Hindi have lots of grammatical mistakes or errors. One of the major issues observed is of tense. Thus, we propose solution to build a rule based tense synthesizer that would recognise the subject, verb and auxiliary verb, analyse the tense, then modify the verb and auxiliary verb according to the subject and put the sentence in the correct tense. This system could be integrated with Machine Translation engines to boost up the quality of Hindi translation.

关键词： Synthesizers Engines Accuracy Hidden Markov models Tagging Morphology Syntactics

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Two-stage hybrid binarization around fringe map based text line segmentation for document images

Two-stage hybrid binarization around fringe map based text l...

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International Conference on Pattern Recognition

作者： Saumya Jetley Swapnil Belhe V. K. Koppula Atul Negi Center for Development of Advanced Computing Pune India Department of CIS University of Hyderabad India

The performance (in terms of accuracy and speed) of present day document analysis systems, both handwritten and printed, depends on the preprocessing stage. In the existing literature we observe accuracy against speed trade-off. That is, superior binarization accuracy is arrived at the cost of increased processing time. The present paper proposes an improved binarization approach, which after a Pre Segmentation Binarization uses a state-of-the-art “fringe map” based text line segmentation algorithm to define text context. This text context is exploited to provide a more refined localized binarization (Post Segmentation Binarization). This unique combination gives benefits of both speed and accuracy with a scope of leveraging through parallel processing. It may additionally be used on skewed or warped camera captured document images. Experimental tests on ICFHR-DIBCO 2009, 2010 and 2011 databases of Printed/ Handwritten Document Images have shown promising results.

关键词： Image segmentation Accuracy Text analysis Context Parallel processing Standards

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Explainable Artificial Intelligence and Causal Inference Based ATM Fraud Detection

Explainable Artificial Intelligence and Causal Inference Bas...

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Proceedings of the IEEE/IAFE Computational Intelligence for Financial Engineering (CIFEr)

作者： Yelleti Vivek Vadlamani Ravi Abhay Mane Laveti Ramesh Naidu Institute for Development and Research in Banking Hyderabad Telangana India Center for Development of Advanced Computing Bangalore Karnataka India

ISBN: (数字)9798350354836

ISBN: (纸本)9798350354843

Gaining the empathy and trust of customers is paramount in the financial domain. However, the recurring occurrence of fraudulent activities undermines both of these factors. ATM fraud is a prevalent issue faced in today's banking landscape. The critical challenges in fraud datasets are highly imbalanced datasets, evolving fraud patterns, and lack of explainability. In this study, we handled these techniques on an ATM transaction dataset collected from India. In binary classification, we investigated the effectiveness of various over-sampling techniques, such as the Synthetic Minority Oversampling Technique (SMOTE) and its variants, Generative Adversarial Networks (GAN), to achieve oversampling. Gradient Boosting Tree (GBT), outperformed the rest of the techniques by achieving an AUC of 0.963, and Decision Tree (DT) stands second with an AUC of 0.958. In terms of complexity and interpretability, DT is the winner. Among the oversampling approaches, SMOTE and its variants performed better. We incorporated explainable artificial intelligence (XAI) and Causal Inference (CI) in the fraud detection framework and studied them via various analyses. Further, we provided managerial impact.

关键词： Economics Explainable AI Banking Generative adversarial networks Boosting Fraud Complexity theory Decision trees Computational intelligence

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Noise-injected Consistency Training and Entropy-constrained Pseudo Labeling for Semi-supervised Extractive Summarization 29

Noise-injected Consistency Training and Entropy-constrained ...

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29th International Conference on Computational Linguistics, COLING 2022

作者： Wang, Yiming Mao, Qianren Liu, Junnan Jiang, Weifeng Zhu, Hongdong Li, Jianxin Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China The State Key Laboratory of Software Development Environment Beihang University China Institute of Artificial Intelligence Beihang University China

Labeling large amounts of extractive summarization data is often prohibitive expensive due to time, financial, and expertise constraints, which poses great challenges to incorporating summarization system in practical applications. This limitation can be overcome by semi-supervised approaches: consistency-training and pseudo-labeling to make full use of unlabeled data. Researches on the two, however, are conducted independently, and very few works try to connect them. In this paper, we first use the noise-injected consistency training paradigm to regularize model predictions. Subsequently, we propose a novel entropy-constrained pseudo labeling strategy to obtain high-confidence labels from unlabeled predictions, which can obtain high-confidence labels from unlabeled predictions by comparing the entropy of supervised and unsupervised predictions. By combining consistency training and pseudo-labeling, this framework enforce a low-density separation between classes, which decently improves the performance of supervised learning over an insufficient labeled extractive summarization dataset. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Entropy

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Word and phrase prediction tool for English and Hindi language

Word and phrase prediction tool for English and Hindi langua...

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Shashi Pal Singh Ajai Kumar Daya Chand Mandad Yasha Jadwani AAI Center for development of Advanced Computing Pune India Banasthali Vidyapith Banasthali India

ISBN: (纸本)9781467399401

Prediction of text while writing has been of utmost importance to people. Prediction has served as a helping hand to people who are slow in typing, or who do not have a good vocabulary. In a country of 336 million populations where people are more frequent in Hindi language, and want to get prediction in Hindi as well. Writing the entire phrases on their own, makes it more prone to errors and mistakes that are made while typing. The prediction tool reduces the chances of having errors while typing. It helps the user for typing efficiently and with a faster speed. The tool is able to predict using multiple algorithms and also we tried to build our own bilingual database which contains phrases of variable length along with their frequency of occurrence in corpus. Whenever a word or phrase is selected from the prediction list, its frequency is increased by one. Consequently, the most frequently used word will have highest frequency/probability leading to increase in efficiency of predictions. Those words and phrases that are not present in the database but have been typed by the user are fed into the database for being used in future predictions. Thus, longer the tool is used, better results it will show Thus, this paper proposes a bilingual word prediction tool that predicts words and phrases for both English and Hindi language. The tool uses different models for the prediction and hence provides a comparison as to which model is better to use and gives better results.

关键词： Predictive models Databases Prediction algorithms Speech Random access memory Optimization Probability

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Bilingual data extraction and auto summarisation

Bilingual data extraction and auto summarisation

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Shashi Pal Singh Hemant Darbari Ajai Kumar Swati Mehta Nidhi Jain Prabh Simran Kaur AAI Center for development of Advanced Computing Pune India Banasthali Vidyapith Banasthali India

ISBN: (纸本)9781467399401

Text Extraction plays an important role in finding valuable information. As a result of rapid growth of available multimedia documents on web and increasing requirement for information, identification, indexing and retrieval, several research have been done on text extraction. Here, a methodology to build a system for text extraction has been presented that is designed to provide support to the applications like Natural Language Processing that requires the data to be in specific format. The data from various formats is extracted and is easily exported to a database. So this tool will be highly useful for creation of data repository and data bank. Also, to speed up the extraction from large size files, research was done and so, large size files are split into small size chunks and efficient use of parallel processing is done to provide faster results. Along with that, Bilingual support is provided, i.e., files of both English and Hindi language can be easily extracted, building respective data banks. Keywords are the important terms, sometimes called, index terms that contain some kind of valuable information about the document. Automatic keyword extraction is the task to identify a small set of words, which can be designated as keywords for that document, and thus provide a brief idea about the document. An effective Keyword Extraction technique has been discussed that can be applied to extract keywords effectively, that uniquely identify a document. A summary is a shortened version of a text of the document that describes the main points of the original document in brief. Automatic summarisation is the task of generating a summary of any input document by the computer. This summary can be used instead for reading the whole content/text resulting in particularly interested.

关键词： Data mining Optimization Databases Libraries Metadata Multimedia communication Parallel processing

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Frequency based spell checking and rule based grammar checking

Frequency based spell checking and rule based grammar checki...

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Shashi Pal Singh Ajai Kumar Lenali Singh Mahesh Bhargava Kritika Goyal Bhanu Sharma AAI Center for development of Advanced Computing Pune India Banasthali Vidyapith Banasthali India

ISBN: (纸本)9781467399401

English is a language that is spoken by around 380-420 million people on this planet and understanding it is not at all easy. The meaning of a sentence varies according to the context and the tone of the speaker. To convey the thoughts efficiently, the knowledge of the language and its various rules is very important as thoughts take the form of words and the words take the form of action. One should aim to minimize the errors while using the language. Lesser is the number of mistakes, better will be the communication. To aid in achieving this goal, we are creating a frequency based spell checker and a rule based grammar checker for English language. The grammar checker focuses on detecting and correcting tense related mistakes.

关键词： Grammar Dictionaries Optimization Tagging Prediction algorithms Context

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Inconsistent Fail due to Limited Tester Timing Accuracy

Inconsistent Fail due to Limited Tester Timing Accuracy

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VLSI Test Symposium

作者： Intaik Park Donghwi Lee Erik Chmelar Edward J. McCluskey Center for Reliable Computing University of Stanford USA Advanced Development LSI Corporation USA

Delay testing is a technique to determine if a chip will function correctly at a specified frequency. If a chip passes delay tests, it will presumably function at the specified frequency in the field. This paper presents experimental results that show how chips can pass very thorough delay tests and still fail in the field. It is shown that some chips sometimes pass and sometimes fail when the same delay test is applied multiple times under the same test conditions. These chips are called inconsistent fails. This paper shows how tester timing edge placement accuracy can cause inconsistent fails and suggests the minimum requirements for guardbands that avoid the inconsistent test results.

关键词： Timing Accuracy Circuit testing Delay Logic testing Frequency Integrated circuit testing Flip-flops Voltage Temperature

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