scholarly journals DEFINITION OF THE CATEGORY OF ROOMS FOR EXPLOSION AND FIRE HAZARDS USING ONTOLOGICAL SIMULATION

2021 ◽  
Vol 56 ◽  
pp. 112-118
Author(s):  
Tatiana E. Shulga ◽  
◽  
Yuliya V. Nikulina ◽  
Keyword(s):  
Decision Support ◽  
Support System ◽  
Fire Hazard ◽  
Subject Area ◽  
Systematic Analysis ◽  
Fire Hazards ◽  
Regulatory Documents ◽  
The Subject ◽  
Ontological Model ◽  
Definition Of

The article formalizes the task of determining the category of premises for explosion and fire hazard in accordance with regulatory documents. A systematic analysis of the process of its solution is carried out and a model of the subject area in the form of an ontology is proposed. Based on the analysis of the regulatory documentation, the scheme for determining the category of the premises was formalized in the form of an algorithm. The authors have identified the main criteria for determining the belonging of a room to a certain category. Examples of using the algorithm for determining the category of a room on real practical problems are considered. The ontological model obtained as a result of the analysis is used as the basis for the decision support system.

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.

Ontological Knowledge Representation and Inference Rules for MTM Decision Support System

2014 ◽  
Author(s):  
Rahul Renu ◽  
Gregory Mocko
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Representation ◽  
Support System ◽  
Time Estimation ◽  
Time Measurement ◽  
Inference Rules ◽  
Assembly Time ◽  
Time Estimates ◽  
Definition Of

The objective of the research presented is to develop and implement an ontological knowledge representation for Methods-Time Measurement assembly time estimation process. The knowledge representation is used to drive a decision support system that provides the user with intelligent MTM table suggestions based on assembly work instructions. Inference rules are used to map work instructions to MTM tables. An explicit definition of the assembly time estimation domain is required. The contribution of this research, in addition to the decision support system, is an extensible knowledge representation that models work instructions, MTM tables and mapping rules between the two which will enable the establishment of assembly time estimates. Further, the ontology provides an extensible knowledge representation framework for linking time studies and assembly processes.

FORMALIZATION OF THE PROBLEM OF MATHEMATICAL INTERPRETATION RECOGNITION OF MEDICAL IMAGES FOR EXAMPLE ALOPECIA

2021 ◽  
pp. 126-129
Author(s):  
Ахмед Магомедович Денгаев
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Image Recognition ◽  
Support System ◽  
Medical Knowledge ◽  
Recognition System ◽  
Subject Area ◽  
Main Task ◽  
Medical Image Recognition ◽  
Mathematical Interpretation

Одним из перспективных и эффективных направлений автоматизированной диагностики заболевания является использование системы распознавания медицинских образов. Главная задача - это максимально точная интерпретация изображения. Прежде всего, необходимо правильно формализовать задачу, провести структуризацию основных условий функционирования системы. В статье составлено содержательное описание предметной области, разработано формализованная схема исследуемой системы. Обозначено, что решение задачи структуризации сводится к разработке отдельных классов, сгруппированных по общим признакам и характеристикам болезни. В этом случае точность и информативность диагноза будет зависеть от полноты базы данных конкретного класса. Приведена математическая интерпретация отношений и связей элементов системы. Применение математических моделей и алгоритмов в медицине является важной задачей. Выбор того или иного алгоритма определяется решаемой задачей. Необходимо понимать, что получаемый результат особо ценен, если он подтверждается математическими расчетами. Предложена многоуровневая архитектура системы поддержки принятия решений, где ключевое место отведено модулю автоматизированной диагностики и распознавания изображения. Отмечено, что при создании системы поддержки принятия решения в медицине специалисты сталкиваются с двумя концептуальными барьерами: первый - связан с колоссальным объемом медицинских знаний, а второй - с постоянным обновлением этих знаний и технологий их обработки. Поэтому главной задачей является правильная структуризация и формализация системы поддержки принятия решений для его эффективного применения One of the most promising and effective areas of automated diagnosis of the disease is the use of a medical image recognition system. The main task is to interpret the image as accurately as possible. First of all, it is necessary to properly formalize the task, to structure the basic conditions for the functioning of the system. The article contains a meaningful description of the subject area, and a formalized scheme of the system under study is developed. It is indicated that the solution to the problem of structuring is reduced to the development of separate classes grouped by common signs and characteristics of the disease. In this case, the accuracy and informativeness of the diagnosis will depend on the completeness of the database of a particular class. The mathematical interpretation of the relations and connections of the system elements is given. The application of mathematical models and algorithms in medicine is an important task. The choice of an algorithm is determined by the problem being solved. It is necessary to understand that the result obtained is particularly valuable if it is confirmed by mathematical calculations. A multi-level architecture of the decision support system is proposed, where the key place is given to the module of automated diagnostics and image recognition. It is noted that when creating a decision support system in medicine, specialists face two conceptual barriers: the first one is associated with a huge amount of medical knowledge, and the second one is associated with the constant updating of this knowledge and technologies for their processing. Therefore, the main task is to properly structure and formalize the decision support system for its effective application

A Decision Support System for Containership Stowage Planning

1989 ◽  
Vol 26 (01) ◽  
pp. 47-61
Author(s):  
D. J. Saginaw ◽  
A. N. Perakis
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Interactive Graphics ◽  
Maritime Industry ◽  
Automate Data ◽  
Plan Generation ◽  
Stowage Planning ◽  
Definition Of ◽  
Stowage Plan

The results of a project intending to design and develop a microcomputer-based, interactive graphics decision support system for containership stowage planning are presented. The objective was to create a working prototype that would automate data management tasks and provide computational capabilities to allow the stowage planner to continuously assess vessel trim, stability, and strength characteristics. The paper provides a complete description of the decision support system developed to meet this objective, including a definition of the containership stowage problem, and details on the design and development of the Automated Stowage Plan Generation Routine (ASPGR). The paper concludes with a discussion of issues relevant to the implementation of the system in the maritime industry.

scholarly journals CERTAIN ASPECTS OF AUTOMATIZATION OF FORMING THE FORENSIC EXAMINATION CONCLUSION PROCESS

2021 ◽  
Vol 74 (1) ◽  
pp. 114-121
Author(s):  
Vasyl Kovalov ◽  
Keyword(s):  
Information System ◽  
Expert Opinion ◽  
Information Technologies ◽  
Digital Technologies ◽  
Research Process ◽  
Subject Area ◽  
Technical Errors ◽  
Forensic Examination ◽  
The Subject ◽  
Definition Of

Active introduction of digital technologies in all spheres of life is one of the main directions of state development as a whole and separate sphere of activity. The issue of using information technologies and systems during forensic examination is the subject of scientific research of many domestic and foreign scientists, but this sphere remains relevant. The introduction of digital technologies in forensic activities is one of the priority areas for the forensic science development at the present stage and has significant development potential. One of the areas of optimization and improvement of forensic activity is the development of methods to automate the formation of forensic experts and unify the description of the research process, identified features, justification and formulation of forensic conclusions, which requires legislative consolidation and regulation, analysis and definition of the subject area and development requirements and algorithms for the operation of the system interface. Unification and standardization of the content of forensic experts' opinions requires the development of common standards and an information system adopted by all subjects of forensic expertise, and meets the needs of practice. The development of an information system for forming an expert opinion and automatically forming an expert opinion will allow formalizing and unifying the description of research and results of forensic examinations, optimizing the time of forensic experts and potentially reducing the number of logical, typographical and technical errors, and simplifying quality control of forensic examinations. The proposed system will not only automate the technical work of registration of research results carried out during forensic examinations, but will also contain research algorithms, which will be stored in the form of data on already conducted research of similar objects (list and sequence of operations, identified features and their parameters).

scholarly journals Intelligent decision support method in a typical situation

2021 ◽  
Vol 11 (1) ◽  
pp. 126-136
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Business Process ◽  
Support System ◽  
System Integration ◽  
General Structure ◽  
Typical Situation ◽  
Ontological Model ◽  
Decision Support Method

The article discusses a decision support method using a knowledge base. The relevance of the study of issues related to decision-making in typical situations is shown. In order to increase the effectiveness of management activities, the is-sues of system integration of the regulatory framework, ontological model and knowledge base of the intelligent sub-system of decision support within the framework of the business process are considered. In support of the proposed method, a model has been formed for replenishing the knowledge base both at the structural and analytical levels, which demonstrates the connection between the most important elements of the system: the ontological model, the knowledge base and the normative subsystem. An example of using the proposed scheme is shown. To demonstrate the model of functioning of the decision support system, an algorithm for replenishing the knowledge base is proposed and described. As a conceptual basis for the formal description of the model, operations for working with knowledge are described in the set-theoretic aspect. The principles of adaptation of the ontological model as an information object for linking with the knowledge base are considered. The conceptual diagram of the general structure of the ontological model for making decisions within the framework of the business process as a set of interrelated concepts is proposed and demonstrated. An information model of a specialized database has been developed and presented, serving as a technical basis for building a knowledge base of a decision support system in a typical situation, its main structural el-ements, the principles of their interrelation and an approach to ensuring the consistency of its internal structure are de-scribed.

scholarly journals Ontologization of tools for modeling and synthesis technological process trajectories

2020 ◽  
Vol 157 ◽  
pp. 04032
Author(s):  
Vasily Mokhov ◽  
Danil Shaykhutdinov ◽  
Evgeniy Kirievskiy ◽  
Alexander Vlasov ◽  
Nikolay Gorbatenko
Keyword(s):  
Subject Area ◽  
Power Networks ◽  
Intelligent Modeling ◽  
Technological Chain ◽  
Transformer Substation ◽  
Digital Substation ◽  
Electric Power Networks ◽  
The Subject ◽  
Ontological Model ◽  
Upper Level

The publication is devoted to the development of an ontological model of tools for intelligent modeling and synthesis of the trajectories of technological processes in electric power networks. Development includes two levels of modeling: the level of metaontology and the level of applied ontologies. At the upper level, the structure of the upper level is proposed and described. At the level of applied ontologies, the ontology of the “digital substation - distribution network” system and the structure for the ontology of tasks are detailed. The first is implemented and presented in the Protégé framework environment. The second is presented descriptively by the example of the task of minimizing energy losses at the level of a transformer substation with an illustration of a functional diagram of the technological chain of its solution. The findings of the work reflect the potential of using the proposed solution to prepare an integrated knowledge management system in the subject area.

Subject Expertise and Teachers’ Knowledge

1998 ◽  
Vol 17 (3) ◽  
pp. 342-356 ◽  
Author(s):  
Paul G. Schempp ◽  
Dean Manross ◽  
Steven K.S. Tan ◽  
Matthew D. Fincher
Keyword(s):  
Pedagogical Content Knowledge ◽  
Content Knowledge ◽  
Student Motivation ◽  
Evaluation Criteria ◽  
Subject Area ◽  
Pedagogical Content ◽  
Perceptions Of Students ◽  
Subject Matter Expertise ◽  
The Subject ◽  
Definition Of

The purpose of the study was to ascertain the influence of subject matter expertise on teachers’ pedagogical content knowledge. Data were collected through multiple, extended interviews with 10 teachers with expertise in at least 1 subject area in physical education. Each teacher was interviewed 4 times for approximately 1 hour, focusing on the teacher’s familiarity with 2 content areas (1 expert and 1 nonexpert) and their experiences teaching the subjects. Data were analyzed using the constant comparative technique. The findings were presented with reference to Grossman’s (1990) definition of pedagogical content knowledge. Subject experts identified their largest pedagogical problem as student motivation, while nonexperts believed finding appropriate activities was their greatest challenge. Subject experts were more comfortable and enthusiastic about pedagogical duties and could accommodate a greater range of abilities. The experts and nonexperts revealed no differences in curricular selection, perceptions of students’ understanding of the subject, or evaluation criteria.

Application of Psychological Principles to Decision Support System Design: An Overview

1983 ◽  
Vol 27 (6) ◽  
pp. 479-481 ◽  
Author(s):  
Ruth H. Phelps
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
System Design ◽  
Support System ◽  
Support Systems ◽  
Psychological Perspective ◽  
Behavioral Decision ◽  
Definition Of

The Behavioral Decision Making session will focus on the application of psychological principles to the design of decision support systems. In this overview the definition of a decision support system and a psychological perspective are described.

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