Int. J. Inf. Technol. Decis. Mak.最新文献_第5页

Assessing the Barriers Towards the Glocalization of India's Mobile Industry: An IVIFs-DEMATEL with Choquet Integral Method 印度移动产业全球本土化的障碍评估:基于Choquet积分法的IVIFs-DEMATEL

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-07-15 DOI: 10.1142/s0219622022500353

Shubham Sachan, A. Barve, Aditya Kamat, S. Shanker

引用次数: 0

A New Method for Analysis of Customers' Online Review in Medical Tourism Using Fuzzy Logic and Text Mining Approaches 基于模糊逻辑和文本挖掘的医疗旅游客户在线评论分析新方法

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-07-15 DOI: 10.1142/s0219622022500341

M. Nilashi, Sarminah Samad, Abdullah M. Alghamdi, Muhammed Yousoof Ismail, O. Alghamdi, Syed Salman Mehmood, Saidatulakmal Mohd, W. Zogaan, Ashwaq Alhargan

引用次数: 0

Toward a Maturity Model for Big Data Analytics: A Roadmap for Complex Data Processing 迈向大数据分析的成熟度模型:复杂数据处理的路线图

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-07-15 DOI: 10.1142/s0219622022500390

Mona Jami Pour, Fatemeh Abbasi, B. Sohrabi

引用次数: 1

Editor's Introduction 编辑器的介绍

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-06-20 DOI: 10.1111/dome.12271

C. Warrick

引用次数: 0

Exploring the Ranking, Classifications and Evolution Mechanisms of Research Fronts: A Method Based on Multiattribute Decision Making and Clustering 基于多属性决策和聚类的研究前沿排序、分类和进化机制研究

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-06-17 DOI: 10.1142/s0219622022300038

Kai Xiong, Yucheng Dong, Zhaoxia Guo, F. Chiclana, E. Herrera-Viedma

{"title":"Exploring the Ranking, Classifications and Evolution Mechanisms of Research Fronts: A Method Based on Multiattribute Decision Making and Clustering","authors":"Kai Xiong, Yucheng Dong, Zhaoxia Guo, F. Chiclana, E. Herrera-Viedma","doi":"10.1142/s0219622022300038","DOIUrl":"https://doi.org/10.1142/s0219622022300038","url":null,"abstract":": This study aims to present a multiattribute decision making and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs). Second, the 8 representative indicators are discovered to get answers to the following two questions: (i) who publishes ESI-HCPs to form a research front? and (ii) where citations to these ESI-HCPs come from in a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts and uncover the evolution process of the research fronts in different clusters based on these representative indicators. We also compare the performances of different countries in these research fronts, and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently at different levels with regard to the rankings, the classifications and the evolution.","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":"31 1","pages":"157-185"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76471289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Approach to Correspondence Analysis Based on Interval-Valued Hesitant Fuzzy Sets 基于区间值犹豫模糊集的对应分析新方法

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-06-17 DOI: 10.1142/s0219622022500328

O. Yanmaz, Cigdem Kadaifci, E. Bozdag

引用次数: 0

A Group Decision-Making Approach for Global Consistency of Heterogeneous Models 异构模型全局一致性的群体决策方法

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-06-17 DOI: 10.1142/s0219622022500316

S. Bennani, S. Ebersold, M. Hamlaoui, B. Coulette, M. Nassar

引用次数: 0

Automatic Discrimination of Task Difficulty Predicted by Frontal EEG Activity During Working Memory Tasks in Young and Elderly Drivers 中老年司机工作记忆任务中额叶脑电活动预测任务难度的自动判别

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-05-31 DOI: 10.1142/s0219622022500201

Koji Kashihara

{"title":"Automatic Discrimination of Task Difficulty Predicted by Frontal EEG Activity During Working Memory Tasks in Young and Elderly Drivers","authors":"Koji Kashihara","doi":"10.1142/s0219622022500201","DOIUrl":"https://doi.org/10.1142/s0219622022500201","url":null,"abstract":"It is desirable to prevent traffic accidents by focusing on elderly people’s brain characteristics. The attention level during driving depends on the amount of information-processing resources. This study first aimed at investigating the effects of the change in attention levels on the electroencephalogram (EEG) waves during the graded working memory tasks for a traffic situation. With the increase in memory loads, reaction times were delayed in the elderly than the young group. The difficult tasks activated the induced [Formula: see text] and [Formula: see text] powers in the frontal midline area primarily in the elderly, during the selective task for a target. The elderly could retain the attention level because of the activated slow EEG responses, regardless of the task performance, although the increased [Formula: see text] wave may reflect drowsiness. Because the assistance system based on drivers’ brain signals can prevent car accidents, this study also aimed at evaluating the analytical method to automatically discriminate the different attentional tasks from the EEG signals. Compared with [Formula: see text]-nearest neighbors and artificial neural networks, support vector machines more accurately classified attention levels (i.e., task difficulty) during working memory tasks reflecting a change in the induced [Formula: see text] and [Formula: see text] waves. This result can be related to a brain-computer interface system to judge the task difficulty during driving and alert a driver to danger. The experimental tasks for this study were limited because they involved simulations only in which participants recognized guided boards and removed irrelevant information. Real-time judgments should be investigated using EEG data to improve systems that can alert drivers to oncoming dangers.","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":"109 1","pages":"1189-1231"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85240778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Look at the Focus on Big Data for Information Technology and Decision Making During 1994 to 2020 1994 - 2020年信息技术与决策重点大数据研究

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-05-26 DOI: 10.1142/s0219622022500298

Zeshui Xu, Zijing Ge, Xinxin Wang, Gang Kou

引用次数: 1

A Review on Vision-based Hand Gesture Recognition Targeting RGB-Depth Sensors 基于视觉的rgb深度传感器手势识别研究进展

Int. J. Inf. Technol. Decis. Mak. Pub Date : 2022-05-26 DOI: 10.1142/s0219622022300026

P. Rawat, Lalit Kane, Mrinal Goswami, Avani Jindal, Shriya Sehgal

引用次数: 2