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Outstanding People and Works in the Area of Computer science Enhancing Quality of Life. the Evidence from Prestigious American, European and asian Computer science Awards 40th

Outstanding People and Works in the Area of Computer Science...

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40th Anniversary International conference on Information Systems Architecture and Technology (ISAT)

作者： Wiechetek, Lukasz Marie Curie Sklodowska Univ Fac Econ Lublin Poland

ISBN: (纸本)9783030304430;9783030304423

Information technology is one of the fastest developing business sector and research area. People use IT solutions based on computer science both for entertainment, education and work. Modern organizations cannot operate effectively without application of IT tools for data acquisition, storage, communication, visualization, but also for linking digital world with the real life or the real business processes. Works in the field of computer science are the foundation of fast and balanced development of IT sector. they are the accelerators of transformation from traditional, real economy into digital business and digital society. the main aim of the article is to explore what nations, people and works played the most significant role in development of information technology during the previous decades. Also what works are crucial today to ensure stability of present digital natives. the author analyzes the five prestigious awards in computer science to find out what works were honored for the past hundred years. In the first part of the article the characteristics of the explored awards is presented. the second part of the paper contains quantitative analysis of award recipients (n = 224) and prizes comparison. the performed literature review and the analysis of the awarded works allow to conclude that during the last decades the main drivers for IT development, noticed by awards committees were related both to the theory, hardware, software development and application areas. the vast majority of laureates came from (was born in) United States (62%), United Kingdom (8,5%) and Japan (4,9%). At the beginning of twenty first century huge amounts of data are generated not only by people but also autonomous objects, so the most crucial in computer science was to prepare systems and networks for secure processing (transferring) huge amounts of data in real time and find methods to assess the accuracy and quality of the information. therefore, new awards like IEEE Internet Aw

关键词： Computer science IT Award Turing Award Millennium Prize Kyoto Prize IEEE Medal of Honor IEEE Internet Award IT evolution Computer science evolution Important works in IT

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Word Sense Disambiguation Corpora Acquisition via Confirmation Code 5

Word Sense Disambiguation Corpora Acquisition via Confirmati...

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5th International Joint conference on Natural Language Processing, IJCNLP 2011

作者： Che, Wanxiang Liu, Ting Research Center for Social Computing and Information Retrieval MOE-Microsoft Key Laboratory of Natural Language Processing and Speech School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9789744665645

Word Sense Disambiguation (WSD) is one of the fundamental natural language processing tasks. However, lack of training corpora is a bottleneck to construct a high accurate all-words WSD system. Annotating a large-scale corpus by experts costs enormous time and financial resources. Human Computation is a novel idea for integrating human resources behind the Web, which has been wasted, to solve practical problems that are difficult for computers. Based on human computation, we design a confirmation code system, which can not only distinguish between human beings and computers (the function of normal confirmation code system), but also annotate WSD corpora. the preliminary experimental result shows that the proposed method can annotate large-scale and high-quality WSD corpora within a short time. To the best of our knowledge, this is the first attempt to use confirmation code in natural language processing for corpora acquisition. © 2011 AFNLP

关键词： Natural language processing systems

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Generalised fuzzy hidden markov models for speech recognition 5th

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5th International conference on asian Fuzzy Systems Society, AFSS 2002

作者： Tran, Dat Wagner, Michael University of Canberra School of Computing ACT2601 Australia

ISBN: (纸本)9783540431503

A generalised fuzzy approach to statistical modelling techniques for speech recognition is proposed in this paper. Fuzzy C-means (FCM) and fuzzy entropy (FE) techniques are combined into a generalised fuzzy technique and applied to hidden Markov models (HMMs). A more robust version of the above fuzzy technique based on the noise clustering (NC) method is also proposed. Experimental results were performed on the TI46 speech data corpus. A significant result for isolatedword recognition performed on a highly confusable vocabulary consisting of the nine English E-set words is that, a 33.8% recognition error rate for the HMM-based system was reduced to 30.5%, 29.9%, 29.8% and 27.8%, respectively, by using the FCM-HMM, the FE-HMM, the NC-FE-HMM, and the NC-FCM-HMM-based systems. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Hidden Markov models

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Extracting Hierarchical Rules from a Weighted Alignment Matrix 5

Extracting Hierarchical Rules from a Weighted Alignment Matr...

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5th International Joint conference on Natural Language Processing, IJCNLP 2011

作者： Tu, Zhaopeng Liu, Yang Liu, Qun Lin, Shouxun Key Lab. of Intelligent Info. Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing100190 China

ISBN: (纸本)9789744665645

Word alignment is a fundamental step in machine translation. Current statistical machine translation systems suffer from a major drawback: they only extract rules from 1-best alignments, which adversely affects the rule sets quality due to alignment mistakes. To alleviate this problem, we extract hierarchical rules from weighted alignment matrix (Liu et al., 2009). Since the sub-phrase pairs would change the inside and outside areas in the weighted alignment matrix of the hierarchical rules, we propose a new algorithm to calculate the relative frequencies and lexical weights of hierarchical rules. To achieve a balance between rule table size and performance, we construct a scoring measure that incorporates both frequency and lexical weight to select the best target phrase for each source phrase. Experiments show that our approach improves BLEU score by ranging from 1.4 to 1.9 points over baseline for hierarchical phrase-based, and 1.4 to 1.5 points for tree-to-string model. © 2011 AFNLP

关键词： Alignment

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Analysis on the Current Situation and Advantages of Sino-Vietnamese Cooperation

Analysis on the Current Situation and Advantages of Sino-Vie...

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2018 5th International conference on Education,Management and computing Technology(ICEMCT 2018)

作者： Di Wu Kunming University of Science and Technology Oxbridge College

the cooperation within the greater Mekong Sub-region has opened a chapter for the development of China and Southeast asian countries, and promoted the cooperation between these countries. In recent ye

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Association-based dissimilarity measures for categorical data: Limitation and improvement

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10th Pacific-Asia conference on advances in Knowledge Discovery and Data Mining, PAKDD 2006

作者： Le, Si Quang Ho, Tu Bao Vinh, Le Sy Japan Advanced Institute of Science and Technology Tatsunokuchi Ishikawa 923-1292 Japan LIRMM Montpellier Cedex 5 France John von Neumann Institute for Computing Juelich Germany American Museum of Natural History New York United States

ISBN: (纸本)3540332065

Measuring the similarity for categorical data is a challenging task in data mining due to the poor structure of categorical data. this paper presents a dissimilarity measure for categorical data based on the relations among attributes. this measure not only has the advantage of value variance but also overcomes the limitations of condition the probability-based measure when applied to databases whose attributes are independent. Experiments with 30 databases also showed that the proposed measure boosted the accuracy of Nearest Neighbor classification in comparison with other tested measures. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Data mining

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A Human-Robot Interactive Mahjong Playing System Based on Visual Recognition Using a Convolutional Neural Network 21

A Human-Robot Interactive Mahjong Playing System Based on Vi...

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5th International conference on Computer science and Application Engineering, CSAE 2021

作者： Wu, Zhifang Han, Jiuqiang Liu, Erhu Lyu, Hongqiang Faculty of Electronic and Information Engineering School of Automation Science and Engineering Xi'an Jiaotong University Shaanxi Xi'an710049 China Guangdong Artificial Intelligence and Digital Economy Laboratory Guangdong Guangzhou510335 China

ISBN: (纸本)9781450389853

Mahjong is a popular tabletop game in China, Japan, and other asian countries. As an incomplete information game, it is more complicated than other complete information games, such as Go, chess, and shogi. With the rapid development of service robot, there have been several human-robot interactive playing systems for complete information games so far, but mahjong is not the case. In this paper, a human-robot interactive mahjong playing system (HRMPS) was developed. HRMPS consists of five modules, including central host, robot players, visual kit, mahjong conveyor, and interactive software. the central host serves the communication between four robot players, which grab a tile on mahjong conveyor and recognize its face via visual kit, and make an action decision by themselves or by human opponents with the help of the interactive software. In HRMPS, to visually recognize a total of 27 different mahjong faces in uncontrolled conditions, a deep convolutional neural network was adopted to achieve an accuracy of 99.71% with a running time of 29ms. the experimental results tell that HRMPS is applicable in human-robot interactive mahjong game.. © 2021 Association for computing Machinery. All rights reserved.

关键词： Human robot interaction

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Anthropometric Considerations for Occupational Well-Being of Women Weavers Engaged in Commercial Handloom Weaving

Anthropometric Considerations for Occupational Well-Being of...

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Joint conference of the asian Council on Ergonomics and Design and Southeast asian Network of Ergonomics Societies, ACED SEANES 2020

作者： Bori, Geetashree Bhattacharyya, Nandita Kalita, Mira Department of Family Resource Management and Consumer Science College of Community Science Assam Agricultural University Jorhat Assam India

ISBN: (纸本)9783030633349

Handloom sector of India has served the economy in terms of employment where 31.45 Lakhs household are engaged in handloom weaving and women weavers comprises of 71.8% of the total workforce (Handloom census 2019–20). the occupational risk of women weavers is a key factor in handloom weaving. It is possible to reduce by developing a well-equipped ergonomically designed workplace considering the anthropometric measurements. the present study was undertaken to assess the anthropometric considerations for the occupational wellbeing of women weavers engaged in commercial handloom weaving. Various parameters were used i.e., weight, height, grip strength which were recorded by weighting balance, anthropometric rods, grip dynamometer. A multistage sampling design was used. A total of 90 weavers, thirty weavers engaged in each category of looms was selected purposively. the anthropometric dimension of weavers working in Frame-loom using jacquard, Frame-loom using dobby, and throw-shuttle loom using dobby was taken and compared with different female and male anthropometric data. the mean stature of the women weavers was found to be 153 cm ± 3.39 and high variation between the ranges of 5th and 95th percentile values. the result shows that the anthropometric dimension of women weaver varies with the male population. the proportion of stature indicated for dimension as sitting height, buttock popliteal length, and sitting popliteal height was found to be 0.501, 0.280, and 0.268. therefore, an implementation of these data will help to create comfortability, safety, the well-being of the user and enhance the productivity of commercial handloom weavers. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anthropometry

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Learning a metric space for neighbourhood topology estimation: Application to manifold learning 5

Learning a metric space for neighbourhood topology estimatio...

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5th asian conference on Machine Learning, ACML 2013

作者： Abou-Moustafa, Karim T. Schuurmans, Dale Ferrie, Frank Dept. of Computing Science University of Alberta EdmontonAB T6G 2E8 Canada Centre for Intelligent Machines McGill University MontréalQC H3A 0E9 Canada

Manifold learning algorithms rely on a neighbourhood graph to provide an estimate of the data's local topology. Unfortunately, current methods for estimating local topology assume local Euclidean geometry and locally uniform data density, which often leads to poor data embeddings. We address these shortcomings by proposing a framework that combines local learning with parametric density estimation for local topology estimation. Given a data set D⊂X, we first estimate a new metric space (X;dX) that characterizes the varying sample density of X in X, then use (X;dX) as a new (pilot) input space for the graph construction step of the manifold learning process. the proposed framework results in significantly improved embeddings, which we demonstrated objectively by assessing clustering accuracy. Keywords: Manifold learning, neighbourhood graphs, neighbourhood topology, divergence based graphs, low rank covariance matrix estimation. © 2013 K.T. Abou-Moustafa, D. Schuurmans & F. Ferrie.

关键词： Topology

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Clustering Semantically Equivalent Words into Cognate Sets in Multilingual Lists 5

Clustering Semantically Equivalent Words into Cognate Sets i...

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5th International Joint conference on Natural Language Processing, IJCNLP 2011

作者： Hauer, Bradley Kondrak, Grzegorz Department of Computing Science University of Alberta EdmontonABT6G 2E8 Canada

ISBN: (纸本)9789744665645

Word lists have become available for most of the world's languages, but only a small fraction of such lists contain cognate information. We present a machine-learning approach that automatically clusters words in multilingual word lists into cognate sets. Our method incorporates a number of diverse word similarity measures and features that encode the degree of affinity between pairs of languages. the output of the classification algorithm is then used to generate cognate groups. the results of the experiments on word lists representing several language families demonstrate the utility of the proposed approach. © 2011 AFNLP

关键词： Natural language processing systems

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