Dynamic Information Systems Research Articles

Distributed optimal consensus control for discrete-time multi-agent systems with composite switching topologies via an iterative Q-learning method

This paper aims to achieve distributed optimal consensus control for discrete-time multi-agent systems (MASs) under composite switching topologies through utilising the iterative Q-learning approach. First, the optimal consensus control strategy, independent of system dynamics information, is developed by using the designed iterative Q-learning approach to guarantee that all follower states can synchronise to the desired trajectory formulated by the leader. Compared with the invariable algebraic or edge-fixed topology structures, the designed Q-learning control algorithm in this paper is implemented based on the composite switching topologies consisting of periodic and stochastic mechanisms. Then, an error dynamic system is established, which transforms the optimal consensus control issue into an optimal regulation issue and removes the influence of the two types of switching topologies. To conquer the problems of lack of model information and the inaccessible analytical solution of Hamilton-Jacobi-Isaacs (HJI) equation, an iterative Q-learning approach is designed according to the reconstructed Q-function Bellman equation. Through further iterative learning, the optimal control strategy can be acquired so as to realise consensus control and ensure the stability of the closed-loop systems. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed distributed optimal control scheme.

Perencanaan Enterprise Arsitektur Menggunakan Framework Togaf pada Aplikasi Srikandi

Information technology (IT) has developed rapidly and is known to be the most important part of all aspects of life, such as education, business, and also government. Information technology allows organizations to increase efficiency and create innovative solutions and has an important role in improving the accountability of public services, especially in the aspect of government. The development of technology in the government aspect has an important role. One of the innovations in Indonesia is the SRIKANDI (Integrated Dynamic Archives Information System) application. SRIKANDI is an application developed to digitize archive and document management in government. The development of enterprise architecture in government institutions is crucial in ensuring that information systems can support processes effectively and efficiently. This research aims to develop enterprise architecture using the TOGAF (The Open Group Architecture Framework) method on the SRIKANDI application at the Baturraden District Office. The SRIKANDI application, which is an Integrated Dynamic Archive Information System, plays an important role in digitizing government archive management. The TOGAF method was chosen for its comprehensive approach in designing, implementing, and managing information system architecture.

Digital Transformation of Archives through the SRIKANDI Application

The digitalization of archive management represents a strategic step toward modernizing government administration. This study examines the implementation of the Integrated Dynamic Archival Information System (APLIKASI SRIKANDI) at the Regional Archives and Library Office of Sikka Regency. Key aspects explored include challenges in digital archive transformation, objectives of system integration, methodologies employed, and the outcomes achieved, alongside future prospects for improvement. The study highlights the role of Universitas Nusa Nipa students’ internship programs in supporting digital archive initiatives. The findings reveal that APLIKASI SRIKANDI has significantly improved the efficiency of archival management processes. However, technical limitations, inadequate technological infrastructure, and human resource constraints remain challenges. To address these issues, the study recommends enhancing infrastructure, offering comprehensive training programs, and developing inclusive digital communication strategies. These efforts aim to optimize system implementation and ensure sustainability in achieving a fully integrated archival management framework. This research underscores the importance of strategic planning and collaboration in driving successful digital transformation within the public sector.

On the Question of the Concept of “Historical Time” in the Psychology

The article examines the theoretical and methodological problems of historical psychology. The problem of forming one’s own conceptual and categorical apparatus of historical psychology is substantiated, and a scheme for highlighting the essential characteristics of the concept of “historical time” is proposed on the basis of V.I. Razumov’s categorical-system methodology and theory of dynamic information systems. The primary categorical triad allowed us to identify three main characteristics that are essential, necessary and sufficient to describe the content of a particular historical time. It is shown that “historical time” in psychological research can be considered taking into account the entire time context: historical events, historical personalities, worldview, lifestyle. The article identifies another significant aspect of the manifestation and reflection of “historical time” — material material history. The task of considering material history in a specific historical time is set.

Категориальная методология в формировании аппарата концептуализации

There is reason to believe that the growth of international tension, various crises and conflicts are generated by numerous and continuing to increase imbalances in the distribution of various resources. The worldview that is familiar to most on the vanguard role of science and education in permanent social progress is being replaced by the dominance of technology and technology in modern civilization and culture. The concept of cognition as reflection is criticized. It wasproposed to apply the concept of K.Popper's three worlds more widely. It is concluded that cognition and knowledge complement the physical and mental in an object, mak-ing it accessible to a person. Concepts are units of knowledge that convey meanings and contents, and catego-ries are formations responsible for routing thinking. The difference between concepts and categories is func-tional. Modern constructions of knowledge must not be inferior in levels of organization and internal diversi-ty to natural and technical systems. In this vein, categorical methodology, combining categorical-system methodology (CSM) and the theory of dynamic information systems (TDIS, DIS), makes it possible to devel-op cognitive tools that use the apparatus of digitalization in the interests of experiments that automate the procedures for constructing concepts.

Incremental attribute reduction for dynamic fuzzy decision information systems based on fuzzy knowledge granularity

Rough set-based attribute reduction is a powerful technique for data preprocessing in data mining. Knowledge granularity, as a reliable measure for assessing uncertainty in decision information systems (DIS), finds applicability in attribute reduction within such systems. Nevertheless, the limitation arises from the fact that static attribute reduction methods fail to effectively utilize the information contained in acquired data and promptly update knowledge due to the continuous evolution of data. In addition, existing incremental methods based on knowledge granularity are designed exclusively for symbolic data and lack the capability to handle real-valued data. Inspired by this, our study focuses on the attribute reduction approach for fuzzy decision information systems (FDIS) that encompass object variations by utilizing fuzzy knowledge granularity. Firstly, fuzzy knowledge granulation is defined to quantify uncertainty within FDIS, and utilized to determine the importance of attributes for attribute reduction. Additionally, the incremental mechanisms and attribute reduction algorithms are investigated for adding an object and an object set to FDIS, respectively. Moreover, an explication of how the incremental mechanism for increasing an object set can be viewed as a generalization of the mechanism used for a single object is provided. Finally, comparative experiments on various datasets are conducted to validate the effectiveness and efficiency of the proposed incremental algorithms. The results demonstrate that our algorithms achieve superior classification accuracy and while requiring minimal computing time when compared to the comparative algorithms.

Enhancing e-government in digital transformation: integrating archive management and digital solutions in Pekanbaru, Indonesia

Efficient and modern archive management is very important in this digital era, especially at the local government level. In this context, this study explores the urgency of archive management using the Integrated Dynamic Archival Information System (SRIKANDI) approach in the Pekanbaru City Government. The research method used is qualitative, with data sources from interviews, documentation, and observation and analysis using the NVivo 12 Plus software. The study's results identified challenges to SRIKANDI implementation, including inadequate technological infrastructure, the need for skilled human resources in information technology, attention to data security, changes in organizational culture, and ongoing technical support. Based on these findings, policy recommendations have been made, including investments in technology infrastructure, human resource training and development, strict data protection, and changes in organizational culture. This research has positive implications for archive management, increasing efficiency and accountability in Pekanbaru. This research provides insights for other city governments wishing to undertake similar digital transformations in electronic-based archives management

Micro-Randomized Trials in Information Systems Research: An Experimental Method for Advancing Knowledge About Our Dynamic and Digitalized World

The increasing ubiquity of individualized digital devices expands the scope of Information Systems (IS) research and offers novel opportunities for investigating and influencing individuals’ intentions, cognitions, and behavior. Based on these technological advancements behavioral science researchers have started to develop experimental methods that allow for rigorously investigating dynamic phenomena in our digitalized world. We introduce an experimental design, called a Micro-Randomized-Trial (MRT), and propose that it is widely applicable in IS research for examining complex and dynamic IS research phenomena. MRTs allow for analyzing causalities and testing theories with dynamic components by considering how time-varying personal and contextual factors influence an experimental treatment’s efficacy over time. The resulting insights can be leveraged to refine theories, improve IS design, influence users’ cognitions and intentions, and steer user behavior. This paper motivates the relevance of the MRT experimental design for IS research, equips interested IS researchers with the required knowledge to conduct MRTs, and demonstrates how MRTs can be deployed to advance IS knowledge by achieving research goals that until now, given the standard IS method assortment, could not be properly addressed.

Data mining based on dynamic waste information system in Surakarta City

Data mining based on dynamic waste information system in Surakarta City

Optimizing Urban Layout: A System Dynamics, Artificial Intelligence, and 3D Urban Information Model Approach for Active Management of City Complexity

Optimizing Urban Layout: A System Dynamics, Artificial Intelligence, and 3D Urban Information Model Approach for Active Management of City Complexity

Innovative risk management in the hotel and restaurant business: Scientific and practical aspect

Effective risk management is essential for success in the dynamic development of the hotel and restaurant business. Amid increasing competition and market instability, there is a need to develop innovative risk management strategies. The purpose of the study is to develop and test methods for assessing and minimising risks aimed at strengthening and sustainable development of enterprises in the hotel and restaurant business. Using abstract-logical analysis and a systematic approach, the study classifies enterprises depending on the level of risk. The results of this study demonstrate a comprehensive understanding of innovative management methods in the hotel and restaurant industry. The findings indicate that enterprises from the initial cluster are less vulnerable to risks, confirming the effectiveness of cluster analysis in assessing risks in the hotel and restaurant sector. In conditions of economic and political instability, systematic analysis and risk management became important. Internal risk management strategies, including innovative methods, were successfully used to reduce potential threats to the hotel and restaurant business, considering the specifics of this industry. The development and support of a dynamic information system became a key element, facilitating effective risk management and enhancing the competitiveness of enterprises. The mentioned enterprises, remaining within the lowest level of risk, confirmed the importance of using cluster analysis for identifying and managing risks in the hotel and restaurant sector. This study introduces innovative approaches to risk management in the hotel and restaurant sphere, providing specific strategies that can be used by companies to increase resilience and adapt to market competition challenges

Two-dimensional identification of time-varying batch nonlinear processes with input dead-zone nonlinearity

ABSTRACT In the time dimension, the batch process with input dead-zone nonlinearity often has the characteristics of short operation time and time-varying process parameters. A two-dimensional recursive least squares (2D-RLS) identification method for time-varying nonlinear systems with input dead zone is proposed. By mining system dynamic information from the time direction of the same batch and different batch directions, the identification parameters are updated. The proposed two-dimensional identification strategy converts the time-varying parameter estimation problem of time dimension into the equivalent time-invariant parameter estimation problem of batch dimension. Sufficient production data in batch dimension ensure that the proposed identification algorithm can eliminate the influence of random measurement noise. The identification strategy with unequal length of batch data is also given. The convergence of the proposed algorithm is analysed. Finally, numerical simulation and experimental tests are used to verify the effectiveness and superiority of the proposed algorithm.

Reinforcement learning based sliding mode control for two-time-scale multi-agent systems with malicious attacks

The optimal consensus problem for linear two-time-scale multi-agent systems under malicious attacks is studied in this paper. Firstly, an integral sliding mode function is devised to guide the system trajectory towards the sliding mode surface and the impact of attacks can be eliminated. Then, the optional consensus problem is reformulated as a zero-sum game problem between each agent and its neighbouring agents. Thus, the game algebraic Riccati equation with singularly perturbed parameter is formulated. Furthermore, to avoid the requirement of the system dynamics information, an integral reinforcement learning algorithm is presented to obtain the optimal control policy for multi-agent systems. Compared with existing learning methods, the obtained reinforcement learning algorithm is devoid of potential calculation error issues from singularly perturbed parameter. Meanwhile, the convergence of the proposed algorithm is verified. Finally, a simulation example is provided to demonstrate the efficacy of the proposed control method.

Development of Efficient Models of Artificial Intelligence for Autonomous Decision Making in Dynamic Information Systems

This research paper focuses on the development of efficient artificial intelligence models for autonomous decision-making in dynamic information systems. Using innovative approaches in data analysis and algorithm optimization, we explore ways to improve model performance in dynamic environments. The results of this research can provide a deeper understanding of how artificial intelligence can operate effectively in real time, thus opening up new perspectives for application in different industries. The research includes the implementation of advanced machine learning techniques, as well as the analysis of adaptive models that can adapt to changes in the environment. Key attention is devoted to the optimization of resources in order to ensure quick and precise decision-making in dynamic situations. In addition, the work addresses the integration of the model with high-performance sensors to improve the system's ability to gather relevant information for decision-making. Through this interdisciplinary analysis, we aim to contribute to the development of intelligent systems that can autonomously react to changes and unforeseen situations in real time.

Managing big data and blockchain for enterprise internationalization process: Mediating role of dynamic accounting system capability

Abstract This study develops and confirms a model that examines the relationship between Big Data Analytics Capabilities (BDAC), Blockchain Technology (BT), and Internationalization Process (IP). It also requires various efforts to explore how Dynamic Accounting Information System Capability (DAISC) mediates the interconnections between BDAC, BT, and IP. This study focuses on small and medium enterprises (SMEs) in Vietnam, which are widely recognized as crucial to the Vietnamese economy. The current research utilized the hypothetico-deductive method. The proposed model's hypothesized linkages were based on a comprehensive evaluation of relevant literature and investigations. The statistics database was created using a paper-and-pencil survey distributed to 612 accountants in SMEs in southern Vietnam utilizing the convenient and snowball sampling technique. A covariance-based structural equation modelling approach was used to assess the measurement and structural models in this research due to its ability to offer a strong foundation for analyzing intricate linkages within a research framework. The outcome confirmed the significant and positive relationships between BDAC, BT, and IP. Concurrently, these relationships were partially influenced by DAISC. The practitioners would greatly benefit from detailed insights on the findings, as they would provide guidance on how to identify and take advantage of the growth opportunities afforded by digital technology. Moreover, the observations could provide policymakers with new insights on necessary policy measures to support the application of digital technologies and encourage the implementation of a dynamic accounting information system, which could result in significant benefits in the future.

Learning-based DoS attack game strategy over multi-process systems

<p>In cyber-physical systems, the state information from multiple processes is sent simultaneously to remote estimators through wireless channels. However, with the introduction of open media such as wireless networks, cyber-physical systems may become vulnerable to denial-of-service attacks, which can pose significant security risks and challenges to the systems. To better understand the impact of denial-of-service attacks on cyber-physical systems and develop corresponding defense strategies, several research papers have explored this issue from various perspectives. However, most current works still face three limitations. First, they only study the optimal strategy from the perspective of one side (either the attacker or defender). Second, these works assume that the attacker possesses complete knowledge of the system's dynamic information. Finally, the power exerted by both the attacker and defender is assumed to be small and discrete. All these limitations are relatively strict and not suitable for practical applications. In this paper, we addressed these limitations by establishing a continuous power game problem of a denial-of-service attack in a multi-process cyber-physical system with asymmetric information. We also introduced the concept of the age of information to comprehensively characterize data freshness. To solve this problem, we employed the multi-agent deep deterministic policy gradient algorithm. Numerical experiments demonstrate that the algorithm is effective for solving the game problem and exhibits convergence in multi-agent environments, outperforming other algorithms.</p>

Examining the mediating role of organizational trust in the relationship between organizational learning and innovation performance: A study of information systems and computer science service firms

Innovation is a crucial driver of competitive advantage and long-term success, particularly in the dynamic Information Systems and Computer Science Service industry. This study investigates the relationships between organizational learning constructs (organizational memory, knowledge acquisition, knowledge interpretation, and knowledge distribution), organizational trust, and innovation performance within Information Systems and Computer Science Service Firms in Jordan. Recognizing the potential mediating role of organizational trust, the study aims to provide insights into the mechanisms that enable effective translation of organizational learning into innovation outcomes. The study employs a quantitative research design using a cross-sectional survey approach. In this study, the data was gathered from 468 participants from Information Systems and Computer Science Service companies in Jordan, consisting of both senior managers and department heads, and the people involved in organizational learning and innovation processes. The analysis shows that organizational memory, knowledge collection and knowledge interpretation have direct impacts on innovations’ performance, but knowledge distribution does not contribute to this performance. Primarily, organizational trust works as the mediating factor that allows the innovation constructs of organizational learning to improve throughput sizes. The evidence also shows that competent learning is a prerequisite for organizational trust.

Development of Efficient Models of Artificial Intelligence for Autonomous Decision Making in Dynamic Information Systems

Development of Efficient Models of Artificial Intelligence for Autonomous Decision Making in Dynamic Information Systems

Новые технологии естественного интеллекта в задачах автоматизации рассуждений

One of the most important challenges that humanity will have to answer in the 21st century is its ability to master intelligence. This provides for the elaboration of a series of questions, including the following: Are there other, non-humanoid intellectual beings? In which variants, in relation to possible extra-human forms of intelligence, is human intelligence positioned (surpasses, lags behind, competes)? Using the topic of new technologies of natural intelligence in the automation of reasoning, the authors propose to shift the emphasis from the focus on the development of artificial intelligence as a competitor and even a threat to man in its strong version, to the task of a complex development of intelligence as a cosmic phenomenon. This focus provides for such a work plan, where the audit of natural intelligence should be the beginning. An assumption is made that the untapped potential of natural intelligence is very large, and its insufficient development was due to significant advances in computer automation. The authors propose to consider the prospects that open up from the use of categorical methodology in reasoning, and especially in their automation. Categories are defined by cognitive units that organize reasoning, and concepts are forms of thought that convey the meaning and content of reasoning. The experiments of implementing categorical methodology in dual and triadic constructions are discussed. It is stated that the potential of categorical schemes in the forms of triads is not sufficiently realized. The authors proceed from the assumption of a significant methodological potential contained in the theory of dynamic information systems (TDIS, DIS). TDIS can play the role of a base for the deployment of a categorical methodology. An example is given demonstrating the operation of a TDIS device. In conclusion, a summary is made about the expediency of the complex human development of intelligence, implemented in various ways and on a variety of natural and artificial media. A more important task, in comparison with the isolated improvement of artificial intelligence to the level of its strong version, is the work on the integration of individual intelligences. In principle, we can talk about a tremendous success in combining the computing power of computers in cloud technologies, but this is not the integration of intelligence.

A dynamic three-way conflict analysis model with adaptive thresholds

Three-way conflict analysis model, based on information systems, is about trisecting, getting coalitions and decision-making. Since the model is proposed by Yao, many models have been proposed to enrich the field of three-way conflict analysis. In this paper, we propose a new three-way conflict analysis model. Our work can be divided into four parts. First, we define new fuzzy granules and an new approximation operator to obtain better trisections. Second, we introduce dynamic information systems which are generalizations of classical information systems. The new information systems enable us to induce trisections dynamically. Third, a new Bayesian algorithm is proposed for thresholds-computing which plays an important role in inducing trisections. In the classical Bayesian approach, there are six original parameters given subjectively. And in our algorithm, the parameters are replaced by three centers and a distance measure. Finally, our new model is applied to tourism planning in two cases, one can be presented by a dynamic information system and the other one can be presented by a dispersed information system generalized from dynamic information system.