scholarly journals Аlgorithmization of the knowledge base in service of passenger cars

2022 ◽  
Vol 14 (2) ◽  
pp. 80-88
Author(s):  
Viacheslav Pavlenko ◽  
◽  
Volodymyr Manuylov ◽  
Volodymyr Kuzhel ◽  
Vladislav Listgarten ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Intelligent Systems ◽  
Driving Forces ◽  
Conceptual Modeling ◽  
Subject Area ◽  
Detailed Knowledge ◽  
Passenger Cars ◽  
Subject Areas ◽  
The Subject

The article considers the architecture of conceptual modeling of the knowledge base, which creates a model of the subject area in the form of many concepts and relationships between them. This approach is based on the concept of a mobile software agent, which is implemented and functions as an independent specialized computer program or an element of artificial intelligence. Ensuring the use of subject area knowledge has become one of the driving forces of the recent surge in the study of artificial intelligence. For example, for models of many different subject areas it is necessary to formulate the concept of time. This representation includes the concepts of time intervals, time points, relative measures of time, etc. If one group of scientists develops a detailed knowledge base, others can simply reuse it in their subject areas using their own database. Creating explicit assumptions in the subject area, which underlie the implementation, makes it easy to change the assumptions when changing our knowledge of the subject area. The process of conceptualization of TO and P, first of all, involves the development of databases in research areas for the formalization and systematization of knowledge about the characteristics of this area of entities and phenomena. That is, the use of concepts in the field of maintenance in a consistent manner in relation to theories of knowledge. Ultimately, the paper updated mathematical modeling, algorithmization and implementation of intelligent systems in the field of maintenance, which will help automate the process of diagnosis and inspection of all car systems, facilitate fault prevention and improve the maintenance process and modernize the maintenance system itself. The approach of algorithmization of the base of knowledge of a condition of the car in each moment of time considered in work gives the chance to reduce time of stay of the car in the service center and to reduce considerably expenses for passing of MOT at service of cars.

scholarly journals Weaknesses of artificial intelligence in medicine

2021 ◽  
Vol 7 (2) ◽  
pp. 50-52
Author(s):  
I.A. Shaderkin ◽  
◽  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Medical Knowledge ◽  
Professional Community ◽  
Subject Area ◽  
Medical Decision ◽  
Successful Operation ◽  
Medical Decisions ◽  
The Subject ◽  
Sensitivity Specificity

Introduction. Recently, a large number of intelligent systems have begun to appear that are used to support medical decision- making – «artificial intelligence in medicine». Material and methods. The author of the publication also works on the issues of making medical decisions, and, being a doctor himself, in the course of his work and existing practice, discovered a number of important issues that he considered necessary to share with the professional community. Results. In some cases, the demonstration of the successful operation of the software in the declared characteristics (sensitivity, specificity) occurs only in the «reliable hands» of the developers and on the data that underlie the software. When attempting to demonstrate performance in clinical situations, the claimed characteristics are often not achieved, so the clinical community that must use this AI-based solution does not always form a favorable opinion. The author considers various types of errors that can be fatal in making medical clinical decisions – distortion of primary medical knowledge, lack of knowledge or inaccurate knowledge about the subject area, social distortions. Conclusions. When developing solutions based on AI, it seems important to keep the above points in mind for both developers and users.

Intelligent information systems and artificial intelligence methods

2021 ◽  
Author(s):  
Aleksandr Andreychikov ◽  
Ol'ga Andreychikova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Information Science ◽  
Federal State ◽  
Construction Technology ◽  
Intelligent Information Systems ◽  
Engineering And Technology ◽  
Subject Areas ◽  
Intelligent Information ◽  
State Educational

The textbook discusses the methods of artificial intelligence and their application to solve problems from various subject areas. Methods of acquisition, representation and processing of knowledge in intelligent systems, as well as technologies for designing and implementing intelligent systems, are described. Special attention is paid to the application of intelligent systems for the selection of collective solutions, the design of complex systems( objects), the analysis and forecasting of the enterprise. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students enrolled in groups of training master's degree program "Management in technical systems", "Computer and information science", "computer science", "engineering and technology land transport", "engineering and construction technology", "Photonics, instrumentation, optical and biotechnical systems and technology", "aerospace engineering", "engineering and technologies of shipbuilding and water transport", and also in the areas of "automation of technological processes and productions", "mechatronics and robotics".

Fraud at the Central Bank of Tanzania (A)

2011 ◽  
Vol 1 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Mussa J. Assad
Keyword(s):  
Central Bank ◽  
Undergraduate Students ◽  
Financial Reporting ◽  
Subject Area ◽  
Internal Controls ◽  
Institutional Governance ◽  
Content Type ◽  
Forensic Accounting ◽  
Subject Areas ◽  
The Subject

Subject area The subject areas for this case are auditing, fraud and investigations. It is also relevant for teaching aspects of corporate governance. Student level/applicability This case consolidates techniques and methodologies of special investigations and demonstrates weaknesses in governance and internal controls. It is appropriate for final year undergraduate students and graduate students who have attended classes on basics of accounting and financial reporting. Case overview The case is about institutional governance and the effects of ineptness at different levels of an organization that resulted in TAS. 133 billion being “improperly” paid out to 22 firms in the financial year 2005/2006.The case is structured to focus at the dilemma of the Director of Finance as an individual who featured in the latter stages of an extensive fraud where old unclaimable debts were revived and were being claimed and paid to fictitious assignees involving a number of Central Bank officials. However, the case seeks to interrogate issues related to financial records and controls in which the position of Director of Finance had more relevance. Expected learning outcomes Working on this case should result in enabling students to acquire expertise necessary for forensic accounting. It should also enable students to learn to gain an understanding of the practice of investigative and forensic accounting as well as an understanding of the interrelationships of the parties involved in forensic investigations. Supplementary materials Teaching note.

scholarly journals USING THE ONTOLOGY FOR CREATING KNOWLEDGE BASE OF THE EXPERT SYSTEM OF THE SUBJECT AREA OF THE STORING OF VEGETABLES AND FRUITS BY THE TECHNOLOGY «ULO»

2020 ◽  
Author(s):  
Ye. Proskurka ◽  
S. Kyrychuk
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Subject Area ◽  
Automation System ◽  
The Subject ◽  
Vegetables And Fruits

Using the ontology for creating the knowledge base of the expert system of the subject area of the storing of vegetables and fruits by the technology «ULO» is reviewed in this article. The expert system, which will be created with CLIPS language, will be used for manage of the automation system of the warehouses for the storing of vegetables and fruits by the technology «ULO».

scholarly journals A new method for creating Mivar knowledge bases in tabular-matrix form for ground intelligent vehicle control systems

2021 ◽  
Vol 2061 (1) ◽  
pp. 012123
Author(s):  
D A Chuvikov ◽  
D V Aladin ◽  
L E Adamova ◽  
O O Varlamov ◽  
V G Osipov
Keyword(s):  
Knowledge Base ◽  
Control Systems ◽  
Knowledge Bases ◽  
Subject Area ◽  
Vehicle Control ◽  
Matrix Form ◽  
Intelligent Vehicle ◽  
Knowledge Map ◽  
Knowledge Model ◽  
The Subject

Abstract This research presents a methodology for creating mivar knowledge bases in tabular-matrix form for ground intelligent vehicle control systems. At its core, this methodology is kind of instruction for analysts facing the task of formalizing knowledge in a given subject area. The result of this formalization is a “knowledge map” created according to a special proposed template. In the future, this template allows forming a knowledge base for a given subject area in the formalism of bipartite oriented mivar networks. As an example, the subject area of ground-based intelligent vehicle control systems is used as a template. The proposed methodology of knowledge formalization makes it possible to simplify the process of creating models in Wi!Mi “Razumator-Consultant” 2.1 and also to level the probability of logical collisions when designing a knowledge model in the formalism of bipartite oriented mivar networks.

scholarly journals Modeling the subject areas of psychological research on pain

2020 ◽  
pp. 579-595
Author(s):  
Alexey I. Chuloshnikov ◽  
Keyword(s):  
Subjective Experience ◽  
Graphical Model ◽  
Selection Process ◽  
Psychological Research ◽  
Subject Area ◽  
Subject Areas ◽  
The Subject ◽  
Objective Basis ◽  
The Individual

The article is devoted to the description and justification of the author’s model representing possible demarcation of subject areas in psychological and non-psychological studies of the phenomenon of pain. In the first part of the paper, the deficiencies of existing approaches to the study and explanation of pain are analyzed, and the need for rethinking the existing biopsychosocial approach is indicated, which can be done based on the understanding of pain as a phenomenon of mental reflection. As prerequisites for solving and concretizing these problems, we briefly analyze the historically established non-psychological areas of the pain study (physiological, algometric, and humanities-based), within which we identify the main issues and statements about the nature of pain (particularly as a phenomenon of the subjective world). These issues are considered in a more specific form on the basis of methodological difficulties in psychological research on pain. The main questions are formulated, including the following: the relation of the objective basis of pain to the subjective experience; determination of the subject area of psychological research into pain; determination of the categorical status of pain and its relation to other phenomena of the psyche, to the categories of «subject», «personality». In the second part of the article, based on the indicated theoretical and empirical assumptions, a graphical model illustrating potential subject areas of psychological and non-psychological research is derived. The model reflects the place of various pain phenomena within a single selection process, and the exclusion of the information necessary to reflect and regulate the interaction of an organism and a destructive agent at the physiological, mental (direct behavioral regulation), and sociopsychological levels (socially-mediated regulation). In accordance with the levels of ‘pain’ regulation and reflection, we formulate the following: hypothetical scope of the pain concept (the narrow and broad definition); subject areas and their specifics; possible determinants that represent their phenomenology; possible hierarchical relationships of pain reflection levels. The paper also provides an outline of a hypothetical mechanism that connects the process of selecting pain experiences (the content of the subjective picture of pain) to the individual personality characteristics of the subject experiencing pain.

scholarly journals Method for resolving the lexical polysemous search query based on ontology

2020 ◽  
Vol 15 (89) ◽  
pp. 103-110
Author(s):  
Iuliia I. Butenko ◽  
Keyword(s):  
Natural Language ◽  
Search Engine ◽  
Subject Area ◽  
Search Query ◽  
Lexical Unit ◽  
Area Of Interest ◽  
Factors Influencing ◽  
Semantic Component ◽  
Subject Areas ◽  
The Subject

One of the factors influencing the relevance of search output is the multivalued search query, expressed by lexical means of a natural language. The multivalued lexical unit manifests itself at the stage of a search query. The method of removing the multivalence of lexical units in a search query based on ontologies is proposed. It is grounded that ontologies allow transferring semantic component of data related to a subject area accurately enough. The proposed method for lexical multivariance resolution can be described as follows. A user search query is received at the search engine input. The search engine contacts the ontology library to find the query. If the lexical unit from the search query is multivalued, the search engine will offer the user a list of subject areas in which the lexical unit from the search query was found. Oft the user searches in advance for the result from a particular subject area. When the subject area is defined, the search engine determines the nearest elements in the structure of ontology, and when ranking the search output will be guided by their presence or absence. The use of ontologies also allows adding synonyms and acronyms meaning the same to the search query. The proposed approach will allow solving lexical multiplicity and significantly relieving the search output, leaving only the subject area of interest to the user.

scholarly journals AN ONTOLOGICAL APPROACH TO THE DEVELOPMENT OF A KNOWLEDGE BASE OF A DECISION SUPPORT SYSTEM FOR CHOOSING AN INDIVIDUAL EDUCATIONAL TRAJECTORY

2021 ◽  
pp. 29-34
Author(s):  
О.В. Баюк ◽  
И.О. Лозикова
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Support System ◽  
Subject Area ◽  
Educational Trajectories ◽  
Ontological Approach ◽  
The Subject ◽  
Ontological Modeling ◽  
Ontological Model

В статье рассмотрены актуальные вопросы онтологического моделирования базы знаний интеллектуальной системы поддержки принятия решения (СППР) по выбору индивидуальной образовательной траектории. Цель работы – разработка онтологической модели базы знаний системы поддержки принятия решения для построения индивидуальной образовательной траектории обучающегося. Предметом исследования является онтологическое моделирование процесса построения индивидуальной образовательной траектории. Актуальность работы обусловлена индивидуализацией образовательного процесса, который предлагается осуществлять по индивидуальным образовательным траекториям (ИОТ). При построении ИОТ большая роль отводится самостоятельному выбору и принятию решения обучающимся, где необходимо ясно видеть возможный результат своего выбора. Система построения сценариев выбора ИОТ или Система поддержки принятия решения (СППР, Decision Support System, DSS) является интеллектуальной системой, ядром которой будет база знаний на основе онтологической модели. Представлены методологические и технологические аспекты моделирования онтологии базы знаний предметной области индивидуальных образовательных траекторий, применение современных программных средств и стандартов разработки онтологических моделей. Описан метод и технология онтологического моделирования, представлены основные технологические стандарты и их теоретические основания, а также основные процессы методики проектирования. Дано описание предметной области онтологической модели, подход к построению модели базы знаний индивидуальной образовательной траектории, где сформулированы целевые вопросы данной онтологии для определения её масштаба и компетентности. Представлен последовательный процесс онтологического моделирования знаний описанной предметной области. Разработаны правила логического вывода для проверки компетентности онтологической модели и представлены результаты логических вычислений. Представлен выбор семантических технологий для разработки СППР. В заключение сделаны выводы о преимуществах онтологического подхода к разработке базы знаний системы поддержки принятия решения по выбору индивидуальной образовательной траектории и о программной архитектуре реализации данной системы. The article deals with topical issues of ontological modeling of the knowledge base of the intelligent decision support system (DSS) for the choice of an individual educational trajectory. The purpose of the work is to develop an ontological model of the knowledge base of the decision support system for building an individual educational trajectory of a student. The subject of the research is the ontological modeling of the process of building an individual educational trajectory. The relevance of the work is due to the individualization of the educational process, which is proposed to be carried out according to individual educational trajectories (IOT). When building an IOT, a large role is assigned to the independent choice and decision-making of students, where it is necessary to clearly see the possible result of their choice. The system for constructing IOT selection scenarios or the Decision Support System (DSS, Decision Support System, DSS) is an intelligent system, the core of which will be a knowledge base based on an ontological model. Methodological and technological aspects of modeling the ontology of the knowledge base of the subject area of individual educational trajectories, the use of modern software tools and standards for the development of ontological models are presented. The method and technology of ontological modeling are described, the main technical standards and their theoretical foundations are presented, as well as the main processes of the design methodology. The article describes the subject area of the ontological model, an approach to building a knowledge base model of an individual educational trajectory, where the target questions of this ontology are formulated to determine its scale and competence. A sequential process of ontological modeling of knowledge of the described subject area is presented. The rules of logical inference for checking the competence of the ontological model are developed and the results of logical calculations are presented. The choice of semantic technologies for the development of DSS is presented. In conclusion, conclusions are made about the advantages of the ontological approach to the development of the knowledge base of the decision support system for choosing an individual educational trajectory and about the software architecture of the implementation of this system.

scholarly journals literature Review: Artificial Intelligence Impact on the Recruitment ProcessA LITERATURE REVIEW: ARTIFICIAL INTELLIGENCE IMPACT ON THE RECRUITMENT PROCESS

2021 ◽  
Vol 6 (1) ◽  
pp. 108-119
Author(s):  
JihaD FraiJ ◽  
Várallyai László
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Human Resources Management ◽  
Subject Area ◽  
Recruitment Process ◽  
Core Subject ◽  
The Subject ◽  
The Impact ◽  
Magazine Articles ◽  
Good Number

This paper aim is to review the implementation of artificial intelligence (AI) in the Human Resources Management (HRM) recruitment processes. A systematic review was adopted in which academic papers, magazine articles as well as high rated websites with related fields were checked. The findings of this study should contribute to the general understanding of the impact of AI on the HRM recruitment process. It was impossible to track and cover all topics related to the subject. However, the research methodology used seems to be reasonable and acceptable as it covers a good number of articles which are related to the core subject area. The results and findings were almost clear that using AI is advantages in the area of recruitment as technology can serve best in this area. Moreover, time, efforts, and boring daily tasks are transformed to be computerized which makes a good space for humans to focus on more important subjects related to boosting performance and development. Acquiring automation and cognitive insights as well as cognitive engagement in the recruitment process would make it possible for systems to work similarly to the human brain in terms of data analysis and the ability to build an effective systematic engagement to process the data in an unbiased, efficient and fast way.

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