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Artificial Intelligence (AI) and Machine Learning (ML) transforming the Insurance industry by improving efficiency, reducing costs, and providing a better customer experience. As these technologies continue to evolve, more innovation can be expected in the Insurance industry. A Bibliographic analysis is conducted for scientific mapping based on 1,084 SCOPUS-indexed publications between the year 2000-2022 using VOSviewer Application. The Analysis was conducted based on Publications by year, Source, Author, Affiliation, Country, Type, Subject Area and Funding Sponsors. The research found the result, the year 2022 had the highest publication of 203, through documents per year by the source of Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics at 43 publications, Bauder, R.A. author is the maximum contributor, Harvard Medical School has been the major affiliate, United States of America, has the maximum 341 publications, Conference paper has the majority participation at 412 documents at 38 percent and Keywords "Artificial intelligence", Machine Learning" and "Insurance" has the highest occurrence. The maximum number of publications inthe field of computer science at 28 percent. Overall, this bibliographic analysis provides a comprehensive overview of the current state of research in AI and Machine Learning in the Insurance industry and highlights the potential for further innovation and development in this field. [ABSTRACT FROM AUTHOR]

Bitcoin in the last decade, has become increasingly popular as a form of electronic currency. This paper aims to review the status and visual map position of research in the internationally Bitcoin studies indexed Scopus that used a bibliometric positioning overview. The research was carried out using bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 3,281 documents issued from 2011 through 2019. The study reveals that Bouri, E. and Chinese Academy of Sciences, Studies were the most active individual scientists and affiliated institutions in Bitcoin studies. In bitcoin studies, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were one worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from eight years of publication, this study constructed a convergence axis grouping comprising of bitcoin studies: Bitcoin, E-Finance, Blockchain, Privacy, Cybercrime, Computation, and Systems, abbreviated as the theme BFBPCCS. [ABSTRACT FROM AUTHOR]

Bitcoin in the last decade, has become increasingly popular as a form of electronic currency. This paper aims to review the status and visual map position of research in the internationally Bitcoin studies indexed Scopus that used a bibliometric positioning overview. The research was carried out using bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 3,281 documents issued from 2011 through 2019. The study reveals that Bouri, E. and Chinese Academy of Sciences, Studies were the most active individual scientists and affiliated institutions in Bitcoin studies. In bitcoin studies, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were one worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from eight years of publication, this study constructed a convergence axis grouping comprising of bitcoin studies: Bitcoin, E-Finance, Blockchain, Privacy, Cybercrime, Computation, and Systems, abbreviated as the theme BFBPCCS. [ABSTRACT FROM AUTHOR]

WeChat is the most popular social media in the world, especially in China. There is no overview of publications in the area of WeChat Research which shows the big picture using data from all countries. This paper aims to review the status and visual map position of WeChat publication indexed by Scopus used a Bibliometric. The research was carried out using Bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 1.264 documents issued from 2012 through 2019. The study reveals that He, L. and Sun Yat-Sen University were the most active individual scientists and affiliated institutions in WeChat Research. In WeChat Research, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were three worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from seven years of publication, this study constructed a convergence axis grouping comprising of WeChat Research: Social Networking, Education, Human, Article, WeChat. abbreviated as the SEHAW theme. [ABSTRACT FROM AUTHOR]

WeChat is the most popular social media in the world, especially in China. There is no overview of publications in the area of WeChat Research which shows the big picture using data from all countries. This paper aims to review the status and visual map position of WeChat publication indexed by Scopus used a Bibliometric. The research was carried out using Bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 1.264 documents issued from 2012 through 2019. The study reveals that He, L. and Sun Yat-Sen University were the most active individual scientists and affiliated institutions in WeChat Research. In WeChat Research, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were three worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from seven years of publication, this study constructed a convergence axis grouping comprising of WeChat Research: Social Networking, Education, Human, Article, WeChat. abbreviated as the SEHAW theme. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Machine Learning (ML) is a branches of computer science applications that develop system-related tasks performed by programs and mathematical algorithms providing computers able to learn with or without human intervention. The perspective of AI and ML includes looking at exceptionally expansive space if conceivable speculations to decide one that best fits with the watched information and any earlier information held by the learner for this purpose so many algorithms are used in different types. Artificial intelligence is something that will produce our lives easier by performing different high-level computations and understanding complex issues. This can be a straightforward definition of what precisely artificial intelligence has done. The paper presents the supporting ability of artificial intelligence and machine learning in different applications, such as education, smartphones, medical care, and space technologies. However, this review studies the present status of machine learning, deep learning, and artificial intelligence technologies applied to the above technologies. [ABSTRACT FROM AUTHOR]

The concept of this paper focuses on the area of testing university students while using tools of artificial intelligence. The sample set of students were students of the third year of bachelor studies of Applied Informatics and the test was focused on testing English: grammar, vocabulary, IT English. The introductory part describes current possible ways of testing students, mainly in paper- or computer-based tests. The paper-based method is the traditional one while the computer-based one can take advantage of modern tools of artificial intelligence, such as expert systems and neural networks. The core of this paper lies in the comparison of the results that are acquired from paper-based and computer-based testing which uses artificial intelligence tools. The final part envisages the most optimal ways of testing university students. [ABSTRACT FROM AUTHOR]

‘Machine Consciousness’, which some years ago might have been suppressed as an inappropriate pursuit, has come out of the closet and is now a legitimate area of research concern. This paper briefly surveys the last few years of worldwide research in this area which divides into rule-based and neural approaches and then reviews the work of the author’s laboratory during the last ten years. The paper develops a fresh perspective on this work: it is argued that neural approaches, in this case, digital neural systems, can address phenomenological consciousness. Important clarifications of phenomenology and virtuality which enter this modelling are explained in the early parts of the paper. In neural models, phenomenology is a form of depictive inner representation that has five specific axiomatic features: a sense of self-presence in an external world; a sense of imagination of past experience and fiction; a sense of attention; a capacity for planning; a sense of emotion-based volition that influences planning. It is shown that these five features have separate but integrated support in dynamic neural systems. [ABSTRACT FROM AUTHOR]

Geometrical inaccuracy of sheet metal parts due to the springback phenomenon is the reason for considerable efforts in tools and process development. Prediction of springback is a key issue to design the tools and control the process parameters in order to obtain close tolerances in the formed parts. The objective of this paper is to use simulation procedure coupled with neural networks method to get the best relation between process parameters and tools geometry in order to minimize the shape deviations of the formed parts related to the target geometry. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

Path-finding problems are generally famous in computer sciences, specifically those which are associated with uncertain environments are very common in artificial intelligence. Although in such problems greedy approaches are computationally light-weighted, they may not guarantee a good solution or even a solution. Our objective is to analyze the suitability of greedy solutions in a typical instance of uncertain path-finding problems. [ABSTRACT FROM AUTHOR]