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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1353 条记录，以下是131-140 订阅

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Problems and Issues of Emotional computing and Artificial Emotional intelligence: A Review of Rosalind W. Picard's thesis 'Affective computing: Challenges' 7

Problems and Issues of Emotional Computing and Artificial Em...

引用

7th IEEE/ACIS international conference on big data, Cloud computing, and data Science, BCD 2022

作者： Lee, Jina Lee, Saeyeon Kim, Dongcheol Soongfill Univ Dept of Business Administration Seoul Korea Republic of SoongSill Univ Dept of IT Policy and Management Seoul Korea Republic of

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

Affective computing not only includes interactions with machines such as artificial intelligence, robots, and computers that recognize, respond to, and influence human emotions, but also spans a wide range of research fields such as psychology, engineering, sociology, mathematics, computer science, education, and linguistics. Artificial Emotional intelligence is developing beyond the stage of recognizing and interpreting human emotions to simulating emotions, stimulating human emotions, and interacting emotionally. As the market for emotions related technology grows larger, it is very important to look at the problems, issues, and current status of this field. This paper will look into the limitations, problems, and issues of emotional computing and artificial emotional intelligence raised in a paper 'Affective computing: Challenges' by Rosalind W. Picard (Published in 2003) and discuss how many of these problems have been solved and what new current issues have been raised. © 2022 IEEE.

关键词： Emotion Recognition

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The Secure computing Architecture for Dual Hard Disk and Dual System Switching 5

The Secure Computing Architecture for Dual Hard Disk and Dua...

引用

5th IEEE international conference on big data and Artificial intelligence (BDAI)

作者： Zhao, Yue Lin, Leyu Niu, Yiru Wu, Kaijun Hao, Yao Su, Hong Yang, Yarang Sci & Technol Commun Secur Lab Chengdu 610041 Peoples R China Kashi Univ Coll Phys & Elect Engn Kashi 84006 Peoples R China

ISBN: (数字)9781665470810

ISBN: (纸本)9781665470810

This paper proposes a secure computing architecture based on the dual hard disk and dual system switching ((DS)-S-3), and provide the mechanism of sensitive data copy and transmission processing for the two operating environments of the computer. It can not only provide a secure computing environment for all processing links involving sensitive files, but also resist various possible malicious attacks. The experimental simulation results show that the D3S architecture has obvious performance advantages in both the data delivery ratio and the memory computing overhead. When the size of the copied sensitive file is 50MB, the copy time overhead of (DS)-S-3 is 1.12s. The secure transmission rate of sensitive data of (DS)-S-3 architecture is significantly better than that of other existing architectures, which has been maintained at about 8.5 Mbps.

关键词： secure computing architecture the dual hard disk and dual system switching sensitive data secure transmission sensitive file copy and output

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A Toolkit for Text Extraction and Analysis for Natural Language Processing Tasks 5

A Toolkit for Text Extraction and Analysis for Natural Langu...

引用

5th international conference on Artificial intelligence, big data, computing and data Communication Systems (ICABCD)

作者： Sefara, Tshephisho Joseph Mbooi, Mahlatse Mashile, Katlego Rambuda, Thompho Rangata, Mapitsi CSIR Data Sci Dept Pretoria South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

Text extraction is an important part of natural language processing (NLP) tasks. Most NLP tasks like text classification, machine translation, text-to-speech, text-based language identification, text summarization, and named-entity recognition involve the use of textual data. Such data is limited for low-resourced languages making it difficult to experiment advanced NLP techniques on these languages. This paper presents a Python-based toolkit for text analysis and text extraction from different types of images, documents, and audio files. The toolkit is built as a library that has functions that can be imported and utilized for text extraction.

关键词： natural language processing text extraction text analysis

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Towards Sharper Risk Bounds for Minimax Problems 33

Towards Sharper Risk Bounds for Minimax Problems

引用

33rd international Joint conference on Artificial intelligence (IJCAI)

作者： Zhu, Bowei Li, Shaojie Liu, Yong Renmin Univ China Gaoling Sch Artificial Intelligence Beijing Peoples R China Beijing Key Lab Big Data Management & Anal Method Beijing Peoples R China

ISBN: (纸本)9781956792041

Minimax problems have achieved success in machine learning such as adversarial training, robust optimization, reinforcement learning. For theoretical analysis, current optimal excess risk bounds, which are composed by generalization error and optimization error, present 1/n-rates in stronglyconvex-strongly-concave (SC-SC) settings. Existing studies mainly focus on minimax problems with specific algorithms for optimization error, with only a few studies on generalization performance, which limit better excess risk bounds. In this paper, we study the generalization bounds measured by the gradients of primal functions using uniform localized convergence. We obtain a sharper high probability generalization error bound for nonconvex-strongly-concave (NC-SC) stochastic minimax problems. Furthermore, we provide dimension-independent results under PolyakLojasiewicz condition for the outer layer. Based on our generalization error bound, we analyze some popular algorithms such as empirical saddle point (ESP), gradient descent ascent (GDA) and stochastic gradient descent ascent (SGDA). We derive better excess primal risk bounds with further reasonable assumptions, which, to the best of our knowledge, are n times faster than exist results in minimax problems.

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Design and Research of Smart Agriculture Fine Planting System Based on YOLOv3 Algorithm 4

Design and Research of Smart Agriculture Fine Planting Syste...

引用

4th international conference on Industrial IoT, big data and Supply Chain, IIoTBDSC 2023

作者： Zhu, Shaoping Zhu, Leping Zeng, Yan Yang, Yu Liu, Yujie Guan, Jingxin Yan, Yupei Xiao, Yongliang Department of Artificial Intelligence Zhuhai City Polytechnic 519090 China Department of Sports and Health Guangdong Polytechnic of Science and Technology Zhuhai519090 China Department of Information Management Hunan University of Finance and Economics 410205 China

ISBN: (纸本)9798350341690

With the application of artificial intelligence and big data technology in the field of agricultural production, modern information technology means such as the Internet of Things, big data and cloud computing are used to deeply integrate with agriculture. An intelligent agricultural fine planting system based onYOLOv3 algorithmis researched and designed, in order to realize theinformation perception and intelligent control in the agricultural production. In order to improve the intelligent management level of agricultural fine planting, it has good feasibility, and has important significance in promoting and serving Chinese agricultural modernization and national economic development. © 2023 IEEE.

关键词： big data

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Drug Repositioning with Disease-Drug Clusters from Word Representations

Drug Repositioning with Disease-Drug Clusters from Word Repr...

引用

IEEE international conference on big data and Smart computing (bigComp)

作者： Lee, Dong-gi Kim, Myungjun Shin, Hyunjung Ajou Univ Sch Med Dept Psychiat Suwon South Korea Ajou Univ Dept Artificial Intelligence Suwon South Korea Ajou Univ Dept Ind Engn Dept Artificial Intelligence Suwon South Korea

ISBN: (纸本)9781665421973

With the advent of easy access to a tremendous amount of text data, various studies utilizing text mining have been conducted in the biomedical field. However, most are only concerned with retrieving information solely from the perspective of either diseases or drugs. Extending from such boundary, we propose an approach of embedding disease and drugs from biomedical literature, determining direct relationships between them, and identifying possibilities of drug repositioning. To embed both disease and drugs, we utilize the word2vec algorithm and generate embedded word vectors for each disease and drug. Then hierarchical clustering with Ward's method is applied for categorization. Moreover, we suggest an evaluation measure that compares clusters from the text data with results from the molecular biology level. The proposed method was applied to 17,606,652 MEDLINE abstracts and extracted 4,163 diseases and 3,930 drugs. By examining heterogeneous clusters in which both disease and drug exist, nine candidate drugs were deduced for each disease in combination with 79 diseases and 84 drugs. The results are expected to serve as a baseline for the preliminary selection of candidate drugs for drug repositioning.

关键词： Drug repositioning Text mining Word embedding Word2vec Disease-drug clustering

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English-Chinese Corpus Collection and Machine Intelligent Translation Methods based on big data and Pattern Analysis Model

English-Chinese Corpus Collection and Machine Intelligent Tr...

引用

6th international conference on computing Methodologies and Communication, ICCMC 2022

作者： Luo, Fei Xi'an Fanyi University Xi'an 710065 China

ISBN: (纸本)9781665410281

First, it analyzes the development trend of artificial intelligence in the machine translation industry, and explains the specific application methods; second, based on the national conditions, explore the development advantages of China in the artificial intelligence and machine translation industry, and automatically align the results with the artificial Comparison of manual alignment results, thinking about the problems encountered in the process of building the database, including the selection of sentence identification, the alignment and matching of many-to-many types of sentences, and on this basis, this paper proposes a design framework for machine translation systems. Including the design method of the electronic dictionary, the storage structure of the electronic dictionary. © 2022 IEEE.

关键词： big data

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Application and Trend Analysis of Artificial intelligence in Weighing Apparatus

Application and Trend Analysis of Artificial Intelligence in...

引用

2022 international conference on Cloud computing, big data and Internet of Things, 3CBIT 2022

作者： Zhang, Lili Xu, Kai Li, Yuan Jiang, Kun Shanghai Institute of Measurement and Testing Technology Shanghai China

ISBN: (纸本)9781665492256

This paper introduces the new discipline of artificial intelligence technology in *** with the development history of weighing instruments, it expounds that the intelligent development of the industrial chain of weighing instruments industry is inseparable from artificial intelligence. By introducing the penetration of artificial intelligence in the weighing instrument field, this paper describes the speech recognition technology and machine vision system technology, and gives a detailed example of the application of the two technologies in the weighing instrument intelligence, which leads to the problems and analysis of artificial intelligence in the weighing instrument industry. Finally, a predictive analysis of the future integration and development trend of artificial intelligence and weighing instruments is made. © 2022 IEEE.

关键词： Weighing

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Research of Hybrid Collaborative Filtering Algorithm in Course Recommendation 5

Research of Hybrid Collaborative Filtering Algorithm in Cour...

引用

5th international conference on Robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Wang, MeiRong Mariano, Vladimir Y. College of Computing and Information Technologies National University Manila Philippines College of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China

ISBN: (纸本)9798350357950

At present, as people's awareness of learning increases, more and more learning resources appear on the Internet, and online courses are becoming more and more popular. Recommendation research for online courses can help users get the quality courses they need faster. This article integrates the optimized Apriori algorithm and the user-based collaborative filtering algorithm and recommends more appropriate courses to users based on this hybrid model. The results are more reasonable than those obtained by relying on any of the above algorithms alone. © 2023 IEEE.

关键词： optimized Apriori recommendation user-based collaborative filtering algorithm

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Research on Pedestrian Recognition Based on Deep Learning 5

Research on Pedestrian Recognition Based on Deep Learning

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5th international conference on Machine Learning, big data and Business intelligence, MLBDBI 2023

作者： Liqin, Liu Blancaflor, Eric Abisado, Mideth National University College of Computing and Information Technologies Manila Philippines Anhui Xinhua University School of Big Data and Artificial Intelligence Hefei China Mapua University School of Information Technology Manila Philippines

ISBN: (纸本)9798350359930

In the realm of computer vision, pedestrian recognition has gained popularity as a study topic in recent years, and has received widespread attention and research from scholars. How to extract more discriminative pedestrian information for pedestrian re recognition has always been a noteworthy issue. While deep learning models can extract features independently, they may face gradient vanishing as the number of network layers increases. Traditional pedestrian recognition techniques rely on the human construction of visual features, which have low recognition accuracy and are easily influenced by other external circumstances. An additional aspect influencing pedestrian recognition accuracy is partial occlusion of pedestrian images. This article proposes an enhanced neural network that combines random erasure and residual attention networks for pedestrian recognition to improve the accuracy of recognition. © 2023 IEEE.

关键词： Network layers

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