scholarly journals Character model identification and interactive AI simulation application

Impact ◽  
2020 ◽  
Vol 2020 (4) ◽  
pp. 70-72
Author(s):  
Pei-Chun Lin
Keyword(s):  
Fuzzy Logic ◽  
Data Analysis ◽  
Speech Recognition ◽  
Visual Perception ◽  
Computer Science ◽  
Computer Systems ◽  
Model Identification ◽  
Analysis Tools ◽  
The World ◽  
Information Engineering

AI is the theory and development of computer systems that can operate and perform functions which would normally require human input, such as visual perception, speech recognition, and translating one language into another. Dr Pei-Chun Lin is a researcher based in the Department of Information Engineering and Computer Science at Feng Chia University in Taiwan. She is collaborating with other academics around the world to develop a robot that incorporates AI and will act in a way that suggests it is a thinking and feeling robot which humans can relate to. The character model identification is especially important for creating an AI robot. The team applied data analysis tools to confirm the model and incorporate fuzzy logic, which holds significant promise for the field of AI application. Lin believes that there is a great deal of potential for AI robots to improve the lives of people around the world.

Character model identification and interactive AI simulation application

Impact ◽  
2021 ◽  
Vol 2021 (1) ◽  
pp. 18-20
Author(s):  
Pei-Chun Lin
Keyword(s):  
Fuzzy Logic ◽  
Data Analysis ◽  
Speech Recognition ◽  
Visual Perception ◽  
Computer Science ◽  
Computer Systems ◽  
Model Identification ◽  
Analysis Tools ◽  
The World ◽  
Information Engineering

AI is the theory and development of computer systems that can operate and perform functions which would normally require human input, such as visual perception, speech recognition, and translating one language into another. Dr Pei-Chun Lin is a researcher based in the Department of Information Engineering and Computer Science at Feng Chia University in Taiwan. She is collaborating with other academics around the world to develop a robot that incorporates AI and will act in a way that suggests it is a thinking and feeling robot which humans can relate to. The character model identification is especially important for creating an AI robot. The team applied data analysis tools to confirm the model and incorporate fuzzy logic, which holds significant promise for the field of AI application. Lin believes that there is a great deal of potential for AI robots to improve the lives of people around the world.

Medical Diagnosis from a Clinician’s Point of View

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Computer Science ◽  
Medical Diagnosis ◽  
Information Science ◽  
Point Of View ◽  
Joint Research ◽  
The World

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.

Medical Diagnosis from a Clinician’s Point of View

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35 ◽  
Author(s):  
F. T. De Dombal
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Computer Science ◽  
Medical Diagnosis ◽  
Information Science ◽  
Point Of View ◽  
Joint Research ◽  
The World

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.

Algorithm for the formation of a scene for visualizing data for HT-devices

2021 ◽  
Author(s):  
A.V. Voronin
Keyword(s):  
Visual Perception ◽  
Computer Science ◽  
Data Visualization ◽  
Golden Section ◽  
Mathematical Definition ◽  
Optimal Value ◽  
The World ◽  
Definition Of ◽  
Mathematical Interpretation

Data visualization through the formation of a scene on the screen of a Hi-Tech- (HT)-device is increasingly attracting the attention of specialists in the field of computer science and software. This is due to the fact that the visibility of the visualized information is important not only for users of HT-devices (a person perceives 80% of information visually (with the eyes)), but also for analytics of decisions made based on the analysis of the visualized data. At the same time, there is a steady tendency in the world to increase the volume of visualized data, and the resource of its perception by a human is limited. The use of the patterns of visual perception of objects associated with the properties of the «golden» section allows one to formulate a visualization criterion for visualized data, and, consequently, an algorithm for the formation of a scene for visualizing data for HT-devices. The purpose of the study is to determine the visualization criterion for visualized data and, based on it, the algorithm for the formation of the data visualization scene, as well as the features of the algorithm functioning. The visualization criterion for visualized data is determined through the coefficient of coverage of the screen area. The optimal value of the coefficient corresponds to the mathematical definition of the «golden» section. As a result of the study, it is necessary to highlight the definition, based on the analysis of the properties of the «golden» section, of the visualization criterion for data visualization, the algorithm for the formation of the data visualization scene and the features of its functioning. The practical value of the results lies in the fact that the proposed criterion represents a mathematical interpretation of the «golden» section property for visualizing data on modern HT-devices of various sizes.

International School in Informatics “Junior” for IOI Training

2018 ◽  
Vol 12 ◽  
pp. 187-193
Author(s):  
Marina S. TSVETKOVA ◽  
Vladimir M. KIRYUKHIN
Keyword(s):  
Science Education ◽  
Secondary School ◽  
Computer Science ◽  
International School ◽  
International Training ◽  
Internet Resources ◽  
Thirtieth Anniversary ◽  
The World ◽  
Training Event ◽  
School Computer

In 2018 the IOI will celebrate its thirtieth anniversary. Over these three decades, not only the world secondary school Olympiads in informatics community have been formed, which covers more than 80 countries from all continents, but a formation of an united methodological space of the school Informatics started also. This space allows many countries today to develop school computer science education, using the experience of other countries, materials from the IOI conference journal, sites of computer science contests, and other Internet resources. This article describes a model for organizing an international training event for juniors – International School in Informatics “Junior” – ISIJ.

Withdrawn: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC)

2019 ◽  
Vol 13 ◽  
Author(s):  
Abeer A. Amer ◽  
Soha M. Ismail
Keyword(s):  
Diabetes Mellitus ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Computer Science ◽  
Recent Advances ◽  
Vascular Center ◽  
Copyright Permission ◽  
Legal Right

The following article has been withdrawn on the request of the author of the journal Recent Advances in Computer Science and Communications (Recent Patents on Computer Science): Title: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC) Authors: Abeer A. Amer and Soha M. Ismail* Bentham Science apologizes to the readers of the journal for any inconvenience this may cause BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

scholarly journals The weirdest people in the world?

2010 ◽  
Vol 33 (2-3) ◽  
pp. 61-83 ◽  
Author(s):  
Joseph Henrich ◽  
Steven J. Heine ◽  
Ara Norenzayan
Keyword(s):  
Visual Perception ◽  
Young Children ◽  
Moral Reasoning ◽  
Spatial Reasoning ◽  
A Priori ◽  
Human Populations ◽  
Behavioral Sciences ◽  
The World ◽  
And Behavior ◽  
Behavioral Phenomenon

AbstractBehavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Researchers – often implicitly – assume that either there is little variation across human populations, or that these “standard subjects” are as representative of the species as any other population. Are these assumptions justified? Here, our review of the comparative database from across the behavioral sciences suggests both that there is substantial variability in experimental results across populations and that WEIRD subjects are particularly unusual compared with the rest of the species – frequent outliers. The domains reviewed include visual perception, fairness, cooperation, spatial reasoning, categorization and inferential induction, moral reasoning, reasoning styles, self-concepts and related motivations, and the heritability of IQ. The findings suggest that members of WEIRD societies, including young children, are among the least representative populations one could find for generalizing about humans. Many of these findings involve domains that are associated with fundamental aspects of psychology, motivation, and behavior – hence, there are no obviousa priorigrounds for claiming that a particular behavioral phenomenon is universal based on sampling from a single subpopulation. Overall, these empirical patterns suggests that we need to be less cavalier in addressing questions ofhumannature on the basis of data drawn from this particularly thin, and rather unusual, slice of humanity. We close by proposing ways to structurally re-organize the behavioral sciences to best tackle these challenges.

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