scholarly journals Theory and practice in artificial intelligence

2019 ◽  
Vol 89 (4) ◽  
pp. 365-370
Author(s):  
I. A. Sokolov
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Intelligent Systems ◽  
Description Logic ◽  
New Technologies ◽  
Machine Intelligence ◽  
Theory And Practice ◽  
Experimental Science ◽  
Mathematical Methods ◽  
Interdisciplinary Field

Artificial Intelligence is an interdisciplinary field, and formed about 60 years ago as an interaction between mathematical methods, computer science, psychology, and linguistics. Artificial Intelligence is an experimental science and today features a number of internally designed theoretical methods: knowledge representation, modeling of reasoning and behavior, textual analysis, and data mining. Within the framework of Artificial Intelligence, novel scientific domains have arisen: non-monotonic logic, description logic, heuristic programming, expert systems, and knowledge-based software engineering. Increasing interest in Artificial Intelligence in recent years is related to the development of promising new technologies based on specific methods like knowledge discovery (or machine learning), natural language processing, autonomous unmanned intelligent systems, and hybrid human-machine intelligence.

The Future of Human Workers

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Mental Capacity ◽  
Machine Intelligence ◽  
The Internet ◽  
Traditional Model ◽  
Global Workforce ◽  
Repetitive Tasks ◽  
The Internet Of Things

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.

Selected Papers from TAAI 2006

2008 ◽  
Vol 12 (3) ◽  
pp. 217-217
Author(s):  
Hsin-Chang Yang ◽  
Wen-Yang Lin ◽  
Chun-Yang Chang ◽  
Cheng-Hong Yang ◽  
Shyi-Ming Chen
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Theory And Practice ◽  
Annual Conference ◽  
Valuable Resource ◽  
Special Issue ◽  
High Quality ◽  
Swarm Optimization ◽  
Music Retrieval

The 11th Conference on Artificial Intelligence and Applications (TAAI 2006), which was held during Dec. 15-16, 2006 at Kaohsiung, Taiwan, is the annual conference of Taiwanese Association for Artificial Intelligence. The conference is intended to provide a forum for researchers and scholars in the related fields of artificial intelligence. Past conferences have proven them successful attempts to become the most important meeting of artificial intelligence researchers in Taiwan. This is also true for TAAI 2006, which focuses on various aspects on theory and practice of artificial intelligence. In this special issue, 11 papers presented in the conference are selected and extended for their outstanding performance on the conference. These papers cover wide spreading aspects, which include versatile motion planning, particle swarm optimization, data mining, image retrieval, music retrieval, natural language processing, navigation, fuzzy logic, gaming, and bioinformatics. This issue thus concisely summarizes recent advances in artificial intelligence and its applications. The readers should find them valuable and inspiring. We hope that this issue should provide a valuable resource for their researches. As guest editors of this special issue, we like to express our greatest gratitude to those that help this issue come true. Thanks to all contributors and referees for their elaborate works and careful reviews that assure the high quality of this issue. Special thanks should go to Mr. Makoto Shimada of Fuji Technology Press for his efforts and kind assistance in publishing this issue. Finally, we also like to thank the Editors in Chief of JACIII, Prof. Toshio Fukuda and Prof. Kaoru Hirota, for their generous hospitality in supporting this special issue.

scholarly journals Sign Translation Via Natural Language Processing

2021 ◽  
pp. 1-7
Author(s):  
Shadman A. Khan ◽  
Zulfikar Ali Ansari ◽  
Riya Singh ◽  
Mohit Singh Rawat ◽  
Fiza Zafar Khan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Sign Language ◽  
Language Processing ◽  
New Technologies ◽  
End User ◽  
User Input ◽  
Sign Recognition ◽  
Voice User ◽  
The Voice

Artificial Intelligence (AI) technologies are new technologies with new complicated features emerging quickly. Technology adoption has been beneficial for many general models. The models help in train the voice user-interface assistance (Alexa, Cortona, Siri). Voice assistants are easy to use, and thus millions of devices incorporate them in households nowadays. The primary purpose of the sign language translator prototype is to reduce interaction barriers between deaf and mute. To overcome this problem, we have proposed a prototype. It is named sign language translator with Sign Recognition Intelligence which takes the user input in sign language and processes it, and returns the output in voice out load to the end-user.

scholarly journals Accounting Practice and Intelligent Technologies

2012 ◽  
Author(s):  
Daniela Postolache (Males)
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Technology Management ◽  
Intelligent Systems ◽  
New Technologies ◽  
Accounting Information ◽  
Qualitative Approach ◽  
Information Technology Management ◽  
Accounting Practice ◽  
Area Of Interest

was to determine how intelligent technologies can support accounting practice. Our research allowed for establishment of accounting information intelligent systems typology and for placement of these solutions in the sphere of artificial intelligence applications. It is underlined the intelligent technologies contribution to improve accounting processes and activities, in a qualitative approach, from the hermeneutic perspective. The results of our research are useful for researchers in the fields of applied accounting, intelligent systems for accounting, information technology management. Also, our study is useful in the activity of accounting experts, given the presentation of new technologies used in their area of interest.

scholarly journals Artificial Intelligence in Politics, Media and Public Administration: Reflections on the Thematic Portfolio

2020 ◽  
Vol 4 (2) ◽  
pp. 3-9
Author(s):  
Sergey Fedorchenko
Keyword(s):  
Artificial Intelligence ◽  
Political Science ◽  
Public Administration ◽  
Soft Power ◽  
Intelligent Systems ◽  
New Technologies ◽  
Scientific Discourse ◽  
Political Regime ◽  
Political Agenda ◽  
The Political

The issue «Artificial Intelligence in the Sphere of Politics, Media Space and Public Administration» was conceived after updating the topic of artificial intelligence in the socio-political and value sphere at several scientific events organized by the Department of History, Political Science and Law of Moscow Region State University: Scientific and Public Forum «Values and artificial intelligence» (10.11.2019) and the round table «Ethics and artificial intelligence» (04.16.2019). This issue includes works devoted to the issues of the practice of artificial intelligence in public administration, public policy and other fields. The authors also touched on the nuances of scientific discourse and futorology. The compiler of the issue is Candidate of Political Sciences, associate professor Fedorchenko Sergey Nikolaevich. Artificial intelligence technologies are a pretty debatable topic. Artificial intelligence technologies are a pretty debatable topic. Currently, political leaders, scientists and members of the public are actively discussing the problems of artificial intelligence related to the following aspects: new opportunities for political communication; media policy, mediation of the political sphere; axiological policy; social networks, bots; government departments; opportunities and limitations of new technologies in political analysis; the importance of intelligent systems for democracy and democratic procedures; threats of cyber autocracy; legitimacy of the political regime and national security; political values, political propaganda, frames, political myths, stereotypes, «soft power», «smart power»; digital diplomacy; the risks of media manipulation, information wars, the formation of a political agenda; experience of using intelligent systems in the organization of high-quality communication between society and the state. The theme of the issue is extremely relevant for modern academic political science. artificial intelligence, digitalization, political science, scientific discourse, futorology, state, democracy, manipulation, political communications. The issue is aimed at specialists, political scientists, graduate students and all those who are interested in this difficult issue in an interdisciplinary manner.

scholarly journals ENTERPRISE ENGINEERING AND INTELLECTUAL TECHNOLOGIES FOR LIFECYCLE MANAGEMENT OF INDUSTRIAL PRODUCTION

2021 ◽  
Vol 2021 (3) ◽  
pp. 50-53
Author(s):  
Nadirbek Yusupbekov ◽  
◽  
Valery Tarasov ◽  
Shukhrat Gulyamov ◽  
Fahritdin Abdurasulov ◽  
...  
Keyword(s):  
Intelligent Systems ◽  
Production Management ◽  
Life Cycles ◽  
Mathematical Methods ◽  
Enterprise Engineering ◽  
Industrial Enterprises ◽  
Modeling Methods ◽  
Interdisciplinary Field ◽  
Mathematical Foundations ◽  
Lifecycle Management

The fundamental scientific problem of the development of the mathematical foundations of engineering for industrial enterprises and the development of mathematical methods of production management, as well as the creation of intelligent systems for coordinated management of the life cycles of products and production in the network of enterprises are discussed. The issues in demand in the development of a vast interdisciplinary field of enterprise engineering and the development of modern network enterprises and intelligent production using mathematical modeling methods are discussed.

SCRS CONFERENCE PROCEEDINGS ON INTELLIGENT SYSTEMS

2021 ◽  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Data Analysis ◽  
Conference Proceedings ◽  
Language Processing ◽  
Business Intelligence ◽  
Intelligent Systems ◽  
Cognitive Computing ◽  
Fake News ◽  
Research Papers

This book presents the collection of the accepted research papers presented in the Conference on Intelligent Vision and Computing, 2021 and Conference on Intelligent Systems, 2021. In addition, this edited book contains articles related to the themes of business intelligence, artificial intelligence, data analysis, fake news detection, natural language processing, neural network, and cognitive computing.

scholarly journals Prediction of a Ship’s Operational Parameters Using Artificial Intelligence Techniques

2021 ◽  
Vol 9 (6) ◽  
pp. 681
Author(s):  
Kiriakos Alexiou ◽  
Efthimios G. Pariotis ◽  
Theodoros C. Zannis ◽  
Helen C. Leligou
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
New Technologies ◽  
Operating Costs ◽  
Maritime Industry ◽  
Data Logging ◽  
K Nearest Neighbor ◽  
Operational Parameters ◽  
Maximum Absolute Error ◽  
Regression Algorithms

The maritime industry is one of the most competitive industries today. However, there is a tendency for the profit margins of shipping companies to reduce due to an increase in operational costs, and it does not seem that this trend will change in the near future. The most important reason for the increase in operating costs relates to the increase in fuel prices. To compensate for the increase in operating costs, shipping companies can either renew their fleet or try to make use of new technologies to optimize the performance of their existing one. The software structure in the maritime industry has changed and is now leaning towards the use of Artificial Intelligence (AI) and, more specifically, Machine Learning (ML) for calculating its operational scenarios as a way to compensate the reduction of profit. While AI is a technology for creating intelligent systems that can simulate human intelligence, ML is a subfield of AI, which enables machines to learn from past data without being explicitly programmed. ML has been used in other industries for increasing both availability and profitability, and it seems that there is also great potential for the maritime industry. In this paper the authors compares the performance of multiple regression algorithms like Artificial Neural Network (ANN), Tree Regressor (TRs), Random Forest Regressor (RFR), K-Nearest Neighbor (kNN), Linear Regression, and AdaBoost, in predicting the output power of the Main Engines (M/E) of an ocean going vessel. These regression algorithms are selected because they are commonly used and are well supported by the main software developers in the area of ML. For this scope, measured values that are collected from the onboard Automated Data Logging & Monitoring (ADLM) system of the vessel for a period of six months have been used. The study shows that ML, with the proper processing of the measured parameters based on fundamental knowledge of naval architecture, can achieve remarkable prediction results. With the use of the proposed method there was a vast reduction in both the computational power needed for calculations, and the maximum absolute error value of prediction.

scholarly journals Essential Features in a Theory of Context for Enabling Artificial General Intelligence

2021 ◽  
Vol 11 (24) ◽  
pp. 11991
Author(s):  
Mayank Kejriwal
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Face Recognition ◽  
Natural Language ◽  
Language Processing ◽  
Representation Learning ◽  
Machine Intelligence ◽  
General Intelligence ◽  
Commonsense Reasoning ◽  
Core Concept

Despite recent Artificial Intelligence (AI) advances in narrow task areas such as face recognition and natural language processing, the emergence of general machine intelligence continues to be elusive. Such an AI must overcome several challenges, one of which is the ability to be aware of, and appropriately handle, context. In this article, we argue that context needs to be rigorously treated as a first-class citizen in AI research and discourse for achieving true general machine intelligence. Unfortunately, context is only loosely defined, if at all, within AI research. This article aims to synthesize the myriad pragmatic ways in which context has been used, or implicitly assumed, as a core concept in multiple AI sub-areas, such as representation learning and commonsense reasoning. While not all definitions are equivalent, we systematically identify a set of seven features associated with context in these sub-areas. We argue that such features are necessary for a sufficiently rich theory of context, as applicable to practical domains and applications in AI.

scholarly journals DIGITAL TRANSFORMATION OF THE MANAGEMENT ORGANIZATIONAL STRUCTURE OF A PRODUCTION ENTERPRISE

2021 ◽  
Vol 23 (2) ◽  
pp. 46-50
Author(s):  
A.V. Ivaschenko ◽  
◽  
T.V. Nikiforova ◽  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
New Technologies ◽  
Cyber Physical Systems ◽  
Information Environment ◽  
Organizational System ◽  
Physical Systems ◽  
Optimal Replacement ◽  
Proposed Model ◽  
Digital Enterprise

The article discusses the problem of finding a rational share of artificial intelligence in the organizational system of a manufacturing enterprise. An original formal-logical model of a mixed integrated information environment of a digital enterprise is proposed, which differs from analogues in the possibility of an ontological description of the processes of interaction between personnel and artificial intelligence systems. On the basis of the proposed model, a technique has been developed for the optimal replacement of staffing for cyber-physical systems with artificial intelligence components, which allows balancing the load of human resources and intelligent systems. The proposed developments can be applied in the organization of the production process of enterprises for planning and management, as well as the introduction of new technologies and artificial intelligence. Research results are recommended under the framework of implementation of the concept of Industry 4.0 for modern enterprises of industrial engineering.

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