УЗГОДЖЕННЯ ПОЯСНЕННЯ В ІНТЕЛЕКТУАЛЬНІЙ ІНФОРМАЦІЙНІЙ СИСТЕМІ З БАЗОВИМИ ЗНАННЯМИ ЩОДО ПРЕДМЕТНОЇ ОБЛАСТІ

The aim of the study is to develop a model of consistent knowledge about the decision-making process in intelligent systems, which would consider their logical consistency and provide an opportunity to explain the process and outcome of such systems. The object of study is the process of constructing explanations in intelligent systems. Research objectives: development of a generalized approach to the harmonization of knowledge to build explanations in intelligent information systems; development of a model for the presentation of consistent knowledge, considering their logical consistency. The following results were obtained. A generalized approach to the harmonization of knowledge to build explanations in intelligent information systems has been developed. The approach provides the possibility of forming a set of agreed explanations that reflect different aspects of the decision-making process and the result obtained by the intelligent system, which simplifies the application of these results in the subject area of the user. The model of representation of the coordinated knowledge considering their logical consistency is offered. The model makes it possible to check the consistency of knowledge directly in the formation of explanations, which creates conditions for the formation of explanations on the principle of the black box and allows to supplement functioning systems with explanations, as well as to adapt explanations when changing their functionality.

In this chapter of the research, a method of processing various types of data in intelligent management systems of the network and server architecture of the internet of military equipment is proposed. The basis of this research is the theory of artificial intelligence, namely evolving artificial neural networks, basic genetic algorithm procedures, neuro-fuzzy expert systems, as well as bio-inspired algorithms. In the course of the research, the authors proposed:– a complex model of processing various types of data in intelligent decision-making support systems;– a method of processing various types of data in intelligent management systems of network and server architecture;– a method of increasing the efficiency of processing various types of data in intelligent management systems of network and server architecture. The use of methods of processing various types of data in intelligent management systems of the network and server architecture of the internet of military equipment:– to reduce the probability of premature convergence of the metaheuristic algorithm while processing various types of data in intelligent management systems of the network and server architecture of the internet of military equipment;– to maintain a balance between the speed of convergence of the metaheuristic algorithm and diversification while processing various types of data in the intelligent control systems of the network and server architecture of the internet of military equipment;– to take into account the type of uncertainty and noise of the data of the metaheuristic algorithm while processing various types of data in the intelligent control systems of the network and server architecture of the internet of military equipment;– to take into account the available computing resources of the system while processing various types of data in the intelligent management systems of the network and server architecture of the internet of military equipment;– to take into account the priority of search by swarm agents of the meta-heuristic algorithm while processing various types of data in intelligent management systems of the network and server architecture of the internet of military equipment;– to conduct an initial display of flock individuals taking into account the type of uncertainty;– to conduct accurate training of metaheuristic algorithms;– to conduct a local and global search taking into account the degree of data noise while processing various types of data in intelligent management systems of the network and server architecture of the internet of military equipment.

The subject of research in the article is the processes of constructing explanations in intelligent systems based on the use of causal dependencies. The aim is to develop a hierarchical representation of causal relationships between the actions of an intelligent system to form an explanation of the process of the system's operation with a given degree of generalization or detailing. Representation of the hierarchy of cause-and-effect relationships allows you to form an explanation at a given level of detail using the input data in the form of a temporally ordered sequence of events reflecting the known actions of an intelligent system. Tasks: structuring the hierarchy of cause-and-effect relationships for known variants of the decision-making process in an intelligent information system, considering the temporal ordering of the corresponding actions; development of a model of a multi-level representation of causal dependencies for description for explanations in an intelligent system. The approaches used are: counterfactual analysis of causality, used to describe alternative dependencies for possible decision-making options; linear temporal logic to reflect the temporal aspect of causation. The following results were obtained. A generalized hierarchy of cause-and-effect relationships is highlighted for the known variants of the process of obtaining recommendations in an intelligent information system based on the temporal ordering of the corresponding decision-making actions. A model of hierarchical representation of causal dependencies has been developed to describe explanations in an intellectual system with a given degree of detail. Conclusions. The scientific novelty of the results obtained is as follows. A model of hierarchical representation of time-ordered causal relationships is proposed to describe the explanations of the operation of an intelligent system with a given degree of detail. At the top level of the hierarchy, the model defines a generalized causal relationship between the event of using the input data and the event of the result of the system's operation. This connection describes the current task that the intelligent information system solves. At the lower level, cause-and-effect relationships are set between events sequential in time, between which there are no other events. At intermediate levels of the hierarchical representation, the causal dependencies of pairs of events are determined, between which there are other events. The developed model creates conditions for constructing explanations with a given degree of detailing of the actions of the decision-making process in an intelligent system. The model also provides the ability to describe early and late anticipation of alternative sequences of the decision-making process by describing causal dependencies for events between which there are other events.

Objective To improve the handover quality of instruments between operating room and central sterile supply department (CSSD) in special period. Methods The instrument recovery records between operating room and CSSD during special period, including weekends, holidays and night shifts from September to December 2016 and from September to December 2017 in Union Hospital of Tongji Medical College, Huazhong University of Science and Technology were collected. The records from September to December 2016 were assigned as control group, using artificial transition method. The records from September to December 2017 were assigned as intervention group, using using new intelligent information system. The quality of instrument handover and the incidence of adverse events were compared between the two groups. Results After using intelligent information system, the accuracy rate of records and the content of instrument package of the intervention group were both higher than those of the control group, and the differences were statistically significant (P<0.01) . The incidences of instrument loss, instrument defect, occupational exposure and problem traceability in the intervention group were lower than those in the control group, and the differences were statistically significant (P<0.01) . Conclusions The intelligent information system has good application effect on instrument handover between operating room and CSSD in special period. It can solve handover problem in time and can be popularized. Key words: Central supply, hospital; Intelligent information system; Surgical instrument recovery; Special time

The relevance of the program is to implement the client part with a chatbot, which makes the interface simple for the client and helps the administrator to obtain detailed statistics of client actions for further analysis. The intelligent e-commerce information system of the clothing brand uses a database and filters information that meets the user's request. The task of the project is to develop a software product that implements an algorithm that will allow you to select products and add them to the shopping cart. The software product consists of a chatbot and a web application. The chatbot is designed for customers and helps to view available products, select the required number of products and add these products to the cart, also provides an opportunity to view a list of all products in the cart. The web application is designed for the administrator, and allows you to edit content, track customer activity and view the shopping cart. During the completion of this thesis, development and research were conducted, as well as the implementation of a chatbot and a web application that provides information support in e-commerce of the clothing brand. The theoretical concepts of intelligent information system and e-commerce in general are studied and certain aspects that are essential for the topic of qualification work are described in more detail. Information on the basic parameters of the intelligent information system of e-commerce of the clothing brand is given, the analysis of classification and features of analogues is carried out. A comparative analysis of all existing software options to solve the problem and selected the most effective. The implementation of the information system used a functional approach in combination with object-oriented. JavaScript programming language and a number of closely related frameworks have been chosen for development. As a result of the last section, an intelligent information system for e-commerce of the clothing brand was created. The designed structure of the program, database was analyzed and the server part of the system was created. The main functions of the future system, the sequence of processes and the relationships between them are identified. Also analyzed and selected system and software tools needed to implement the tasks. A ready-to-use software product was developed.

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications and multimedia systems methods and applications. The book will be interesting forpractitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced academics and specialists interested in developing and verification of intelligent information, database and multimedia systems models, methods and applications. The readers of this volume are enabled to find many inspiring ideas and motivating practical examples that will help them in the current and future work.

Purpose of research. The aim of this work is to develop an approach to constructing intelligent systems based on a replenished semantic network and a multi-agent environment with agents of various types: cognitive and deductive reactive. The architecture of a multi-level intelligent system is proposed and substantiated, which uses cognitive and reactive intelligent agents that differ in composition and number of implemented cognitive and deductive presumptions. Methods. Knowledge about the subject area is formalized both using the modal version of the first-order predicate calculus for describing cognitive agents and in terms of classical non-modal versions of predicate calculus and deductive inference mechanisms for reactive agents. The operation of an intelligent system is described by an incompletely defined semantic network represented by a conceptual graph and a system of production rules. Results. A functional architecture of an intelligent agent-based system is proposed. At the conceptual level, the architecture of an intelligent agent-based system is proposed to be represented by three sublevels. Cognitive agentsuse knowledge and beliefs that follow from epistemic logic systems. Cognitive presumptions of these agents include beliefs, goals, intentions, and desires of agents and are modeled within the framework of BDI logic. Conclusion. The conducted study shows the importance of BDI logic for cognitive agents, although it was used insignificantly in solving the task at hand, at the level of the content-conceptual description of the intelligent system. The extended functions of cognitive agents include the execution of input, registration, transmission and comparison of lists of objects and relations between them. The goals for the subsequent interpretation of cognitive agents are defined.

The rapid digitalization of European economies has fundamentally transformed traditional approaches to national economic security, creating a strategic need to integrate intelligent information systems (IIS) into state-level governance and financial architectures. Within the framework of European digital transformation and integration, the modernization of economic security mechanisms requires interoperability between national systems and European digital infrastructures. The study addresses the relevance of developing an architectural model for embedding IIS into the system of national economic security to enhance resilience, transparency, and evidence-based policymaking. The aim of the research is to determine how intelligent information systems can optimize decision-making and risk prevention within the economic security framework of states pursuing European digital integration. The object of study is the national economic security architecture influenced by artificial intelligence, big data, and automated monitoring technologies. The research applies a mixed-method approach combining system analysis, economic modeling, and comparative evaluation across EU and candidate states. The theoretical basis rests on the principles of digital governance, cyber resilience, and systems theory of economic security. Methodologically, the study employs multicriteria decision modeling (MCDM) and regression-based simulation using Eurostat and Digital Economy and Society Index (DESI) indicators to assess the effectiveness of IIS modules. Structural-functional and expert analysis methods are applied to identify causal links between intelligent monitoring systems and economic stability indicators, including fiscal transparency, financial control, and cyber resilience. Model simulations demonstrate that the implementation of IIS-driven monitoring mechanisms can reduce financial fraud, accelerate cyber incident response, and increase the efficiency of budget resource allocation. Consequently, the integration of intelligent systems enhances early threat detection, data interoperability, and coordination between national and European institutions responsible for economic stability. The results confirm that IIS integration contributes to a measurable rise in the national resilience index and strengthens compatibility with the European Economic Security Framework and Digital Europe Programme priorities. The practical value of the study lies in the proposed architectural model that unites analytical, infrastructural, and institutional layers of economic security governance. It provides a roadmap for harmonizing national security systems with the European Union’s standards of digital sovereignty and sustainable growth. Thus, the integration of intelligent information systems emerges as a crucial instrument for achieving long-term economic stability, innovation capacity, and digital independence within the evolving landscape of European digital transformation.

Purpose—The purpose of this research is to explore the direct relationship between the emotional intelligence of top management and the quality of strategic decisions they take for their companies. This relationship is further examined by the mediating role of open innovation in the context of intelligent information systems that can impact the way top managers take decisions. This research adopted a survey design as cross-sectional data were taken through questionnaires from top management of the UAE national banks. A final sample size of 213 questionnaires completed by managers was obtained and analyzed. As predicted, there was a strong, positive relationship between managers’ emotional intelligence and the quality of their strategic decisions. Open innovation has revolutionized the way top managers of banks take decisions that are later transformed into policies. Decision-makers are required to possess the skill of decision-making by being vigilant of their surroundings. Hence, they have emotional intelligence and intelligent information systems (IIS) only enhances the trait. IIS is the glorified version of open innovation that further contributes to the decision-making process and the quality of decisions. This research is one of a kind as no one has explored these dimensions of emotional intelligence in the UAE.

Exploring and analyzing the effectiveness of an intelligent pacifying strategy information system based on assisted decision-making in reducing the sedation rate of children in short-duration magnetic resonance scans. A total of 125 children aged 3–5 years who underwent MRI scans at a children's hospital from July to December 2021 participated in this study, during which 62 children were assigned to a control group from July to September, and 63 children were assigned to an intervention group from October to December. In the intervention group, the pacifier used the intelligent pacifying strategy information system based on assisted decision-making to assess children's temperament, and utilization of a system-generated pacification plan according to assessment results. In the control group, the pacification plan was formulated by the pacifier based on their own experience and discussion with families of the participating children. The success rate of pacification, duration of pacification, and image quality of the two groups were compare. Compared with the control group, the intervention group had a higher success rate of pacification and lower duration of pacification, with statistically significant differences (P < 0.05). There was no difference in image quality between the two groups (P > 0.05). The intelligent pacifying strategy information system can help reduce the use of the sedative drugs in children aged 3–5 years who underwent a short-duration MRI scan.

The 2022 International Conference on Image Processing and Intelligent Information Systems (IPIIS 2022) was successfully held online during October 22-23, 2022 in Zhengzhou, China. In the context of the conference, scholars and experts in the fields of image processing and intelligent information systems, involved both in experimental and theoretical research, were invited from various universities and institutions. The conference focused on the most recent advancements in topics such as 'Wireless Sensor Networks', 'Digital Signal Processing', 'Embedded Systems' and others.&#x0D; The main goal of IPIIS 2022 was to present the related research work, to promote the cooperation of experts and scholars in these fields, to share the research achievements both on a national and international level. This collection of proceedings compiles oral and paper presentations submitted by the authors and scrutinized by the editorial committee.&#x0D; Because of restrictions on travel and indoor activities related to COVID-19, we were forced to hold the conference online only. Attendees were notified well in advance that the on-site conference was changed to an online conference, where the timeline and order of the talks were defined. The video conference was held on the original set dates. Due to the large variety of topics and the relatively large number of attendees, the conference was separated into main and parallel sessions. Each plenary speaker gave an oral presentation of 30-40 minutes accompanied by his slides' material, allocated for questions and discussion.&#x0D; The organizing and editorial committees of IPIIS 2022 hope you can enjoy the reading of this volume. Additionally, we want to thank all authors and participants for providing their valuable contributions for these proceedings, as well as the reviewers for their constructive recommendations and feedback aiding to improve the presented articles.&#x0D; IPIIS Organizing Committee&#x0D; Zhengzhou, China

The intelligent management of infrastructure is crucial to maintain structural stability. Although much more attention has been paid to the development of intelligent systems, the cooperation and efficiency of different components in the system is still a remaining problem. Along this line, an optimized intelligent information system (IIS) driven by big-data technology is proposed for the smart management of infrastructure. First, the integration framework of IIS is proposed, including data collection and storage, data analysis, and data expression modules. According to this framework, the remaining problems existing in each component are pointed out and the corresponding optimization measures are given. Especially for the processing technology of massive monitoring data, some trained machine learning algorithms are introduced for data analysis. As a case study, the devised system was adopted in an underwater shield tunnel for real-time monitoring, big data analysis, and information visualization. The intelligent system and advanced data-driven models presented in this study are suitable for most infrastructures, affording useful smart management experience and data processing technology for other underground projects and promoting the intelligent development of civil engineering.

Introduction. The article describes the approach to solving the problem of complex technical system troubleshooting based on expert knowledge modeling. Intelligent information systems are widely used to solve the problems of diagnostics of multilevel systems including combine harvesters. The formal description of the subject domain knowledge is the framework for building the knowledge base of these systems. The sequence of creating an expert system knowledge base in accordance with production rules is considered. Materials and Methods. The approach is founded on the fault function table. As the object of diagnostics, one of the subsystems of the combine harvester electric equipment “opening the hopper roof flaps” is considered. The basis for constructing a sequence of elementary checks is a system of logical equations describing both the serviceable and possible faulty states of the subsystem. Results. A structural logic model is developed. As a result of analyzing the fault function table, the sets of elementary checks are determined. Four criteria have been used to analyze the weight of these checks. The authors have determined optimal sequence of checks and have developed a decision tree, which allows finding the cause of the malfunction and is the basis for creating the knowledge base of an intelligent information system. A fragment of the knowledge base is given. Discussion and Conclusion. The proposed approach of expert knowledge modelling increases the efficiency of the unit for troubleshooting of the intelligent decision support system. It makes possible to structure the base of expertise and establishing the optimal sequence of elementary checks. This allows determining the optimal sequence of application of the knowledge base production rule that makes it possible to reduce the time of restoring the serviceability of combines.

Oil and gas will continue to play an increasingly important role in global economy development and prosperity for the upcoming years. However, a fact which sometimes is ignored is that the oil and gas industry is an intensive energy-consumption industry and a major contributor to greenhouse gas emissions as well. Recently, with the arrival of the “double carbon” era, the energy-intensive production of oil and gas has caused people to pay more attention. Currently, big data technologies as well as the Internet of things (IoT) are developing at a rapid pace, and the metering infrastructure technology also shows huge advancement; oil and gas companies have built many information systems and developed many functions to acquire the energy consumption and oil production data for the aim of reducing the oil production cost via the emerging information technologies, and it turned out that these investments do improve the energy efficiency and lower oil production cost. Unfortunately, due to the different development standards, some systems store the same data with different values; so, therefore, there is a “data barrier” among these systems and somehow discount the share and analysis of these data resources. To this end, in our work, based on these rich data resources from the other information systems, we discussed an intelligent energy management information system with four machine learning algorithms to enhance the analysis of data resources over energy consumption and oil production. First, we presented the innovation of energy consumption data fusion with the method “Data Lake”; then, four different machine learning algorithms: Support Vector Machine (SVM), Linear Regression (LR), Extreme Learning Machine (ELM), and Artificial Neural Networks (ANN) are installed in the proposed system for predicting the oil and gas production and total energy consumption. In order to aggregate these data into dashboard views that help managers make decisions about operations, we also demonstrated the process of energy consumption data visualization with emerging open-source software tool ECharts. Finally, a real life application of the proposed system was summarized in case of total energy consumption prediction and the system output shows good prediction accuracy which proves the feasibility and benefits of the intelligent energy management information system.

With the gradual maturity of geographical multimedia information system, applying geographical multimedia information system to urban intelligent traffic management information system and urban traffic sharing information platform can realize unified management and real-time update of traffic information. Through the urban traffic sharing information platform, it can increase the value of information. The multimedia information of the entire intelligent traffic management system can be stored, organized and processed by the shared multimedia information platform. It can more effectively ensure the correctness, comprehensibility and avoid redundancy of data relationships. Then it improves the utilization and transmission speed of multimedia information in the system. The urban traffic multimedia information management system has improved the use efficiency of urban road construction in China. And it also made the traffic multimedia information system more scientific and intelligent. It can also improve its management level and play an important role in urban traffic management. This paper first briefly analyzes the current traffic situation and the development of intelligent traffic multimedia information system in China. The basic concepts of GIS and urban intelligent transportation system based on GIS are introduced secondly. At last, the possibility about GIS as urban intelligent traffic management system sharing multimedia information platform is analyzed. The system framework and the basic function of GIS platform are put forward, and the application of GIS in urban traffic common information platform using the key technical support was discussed. It expounds the application of GIS in urban traffic common multimedia information platform.