Systems

17 pages, 5879 KiB

Open AccessArticle

Formalizing Attack Tree on Security Object for MySANi in Legal Metrology

by Muhammad Azwan Ibrahim, Faizan Qamar, Zarina Shukur, Nasharuddin Zainal, Nazri Marzuki and Maria Ulfah Siregar

Systems 2023, 11(1), 49; https://doi.org/10.3390/systems11010049 - 16 Jan 2023

Viewed by 1564

Abstract

Illegal software manipulation is one of the biggest issues in software security. This includes the legally relevant software which are now crucial modules in weight and measuring instruments such as weighbridges. Despite the advancement and complexity of weight and measuring instruments, the inspection [...] Read more.

Illegal software manipulation is one of the biggest issues in software security. This includes the legally relevant software which are now crucial modules in weight and measuring instruments such as weighbridges. Despite the advancement and complexity of weight and measuring instruments, the inspection methodology is weak and lacks of innovation. The conventional inspection method is merely based on the observation printed certificate of the software. This paper introduces Malaysia Software-Assisted Non-Automatic Weighing Instrument (NAWI) Inspection (MySANI), a method used to enhance the software inspection scheme in legal metrology. MySANI introduces security objects in order to assist and enhance the inspection process. The security evaluation is based on the best practices in IT in metrology, where the attack model on relevant assets of the security objects is simulated for the Attack Probability Tree. The attack tree is verified by integrating formal notation and comparison with finite state transition system domain to verify the correctness properties of the tree design before the model can be further used in a risk analysis procedure within the Attack Probability Tree framework. Results show that the designed attack tree is consistent with the designed simulation. Full article

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13 pages, 826 KiB

Open AccessArticle

Optimization Model for the Energy Supply Chain Management Problem of Supplier Selection in Emergency Procurement

by Jiseong Noh and Seung-June Hwang

Systems 2023, 11(1), 48; https://doi.org/10.3390/systems11010048 - 16 Jan 2023

Cited by 2 | Viewed by 2662

Abstract

In energy supply chain management (ESCM), the supply chain members try to make long-term contracts for supplying energy stably and reducing the cost. Currently, optimizing ESCM is a complex problem with two social issues: environmental regulations and uncertainties. First, environmental regulations have been [...] Read more.

In energy supply chain management (ESCM), the supply chain members try to make long-term contracts for supplying energy stably and reducing the cost. Currently, optimizing ESCM is a complex problem with two social issues: environmental regulations and uncertainties. First, environmental regulations have been tightened in countries around the world, leading to eco-friendly management. As a result, it has become imperative for the energy buyer to consider not only the total operating cost but also carbon emissions. Second, the uncertainties, such as pandemics and wars, have had a serious impact on handling ESCM. Since the COVID-19 pandemic disrupted the supply chain, the supply chain members adopted emergency procurement for sustainable operations. In this study, we developed an optimization model using mixed-integer linear programming to solve ESCM with supplier selection problems in emergency procurement. The model considers a single thermal power plant and multiple fossil fuel suppliers. Because of uncertainties, energy demand may suddenly change or may not be supplied on time. To better manage these uncertainties, we developed a rolling horizon method (RHM), which is a well-known method for solving deterministic problems in mathematical programming models. To test the model and the RHM, we conducted three types of numerical experiments. First, we examined replenishment strategies and schedules under uncertain demands. Second, we conducted a supplier selection experiment within a limited budget and carbon emission regulations. Finally, we conducted a sensitivity analysis of carbon emission limits. The results show that our RHM can handle ESCM under uncertain situations effectively. Full article

(This article belongs to the Topic Energy Systems Planning, Operation and Optimization in Net-Zero Emissions)

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19 pages, 1107 KiB

Open AccessArticle

The Impact of Internet Use on Citizens’ Trust in Government: The Mediating Role of Sense of Security

by Zicheng Wang, Huiting Liu, Tianfeng Li, Lijuan Zhou and Mingxing Zhou

Systems 2023, 11(1), 47; https://doi.org/10.3390/systems11010047 - 15 Jan 2023

Cited by 3 | Viewed by 4687

Abstract

With the rapid development of communication technologies, the Internet use has become the main channel for citizens to obtain information and knowledge. It has been widely established that Internet use can have a significant impact on citizens’ expectations, perceptions, and behaviors. Government trust [...] Read more.

With the rapid development of communication technologies, the Internet use has become the main channel for citizens to obtain information and knowledge. It has been widely established that Internet use can have a significant impact on citizens’ expectations, perceptions, and behaviors. Government trust is the reasonable expectation of citizens on in the administrative activities of the government and its administrators, which should rightly be influenced by the behavior of citizens’ Internet use. However, limited studies have investigated the relationship between Internet use and citizens’ trust in the government. Therefore, in this study, the effect of Internet use on trust in the government was investigated using data from the 2017 Chinese Social Survey. The baseline regression results revealed that Internet use reduces trust in the government. This phenomenon was persistently observed after several robustness tests. A heterogeneity analysis revealed that Internet use negatively influenced citizens from Eastern and Western China, lower age groups, and agricultural households. Social amplification of the risk and the theory of rational choice revealed that a sense of security partially mediates the relationship between Internet use and citizens’ trust in the government. Internet use reduces citizens’ sense of security and subsequently decreases trust in the government. Our findings revealed establishing a network information supervision and public opinion guidance mechanism. At the same time, consider the role of social security services in resolving social risks. These initiatives are essential to ensure citizens’ trust in their government. Full article

(This article belongs to the Special Issue Communication for the Digital Media Age)

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19 pages, 2780 KiB

Open AccessArticle

Environmental Supply Chain Risk Management for Industry 4.0: A Data Mining Framework and Research Agenda

by Jamal El Baz, Anass Cherrafi, Abla Chaouni Benabdellah, Kamar Zekhnini, Jean Noel Beka Be Nguema and Ridha Derrouiche

Systems 2023, 11(1), 46; https://doi.org/10.3390/systems11010046 - 13 Jan 2023

Cited by 7 | Viewed by 3670

Abstract

Smart technologies have dramatically improved environmental risk perception and altered the way organizations share knowledge and communicate. As a result of the increasing amount of data, there is a need for using business intelligence and data mining (DM) approaches to supply chain risk [...] Read more.

Smart technologies have dramatically improved environmental risk perception and altered the way organizations share knowledge and communicate. As a result of the increasing amount of data, there is a need for using business intelligence and data mining (DM) approaches to supply chain risk management. This paper proposes a novel environmental supply chain risk management (ESCRM) framework for Industry 4.0, supported by data mining (DM), to identify, assess, and mitigate environmental risks. Through a systematic literature review, this paper conceptualizes Industry 4.0 ESCRM using a DM framework by providing taxonomies for environmental risks, levels, consequences, and strategies to address them. This study proposes a comprehensive guide to systematically identify, gather, monitor, and assess environmental risk data from various sources. The DM framework helps identify environmental risk indicators, develop risk data warehouses, and elaborate a specific module for assessing environmental risks, all of which can generate useful insights for academics and practitioners. Full article

(This article belongs to the Special Issue Enablers and Capabilities for the Digital Supply Chain)

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17 pages, 2537 KiB

Open AccessArticle

Exploring the Dynamic Characteristics of Public Risk Perception and Emotional Expression during the COVID-19 Pandemic on Sina Weibo

by Tong Li, Xin Wang, Yongtian Yu, Guang Yu and Xue Tong

Systems 2023, 11(1), 45; https://doi.org/10.3390/systems11010045 - 13 Jan 2023

Cited by 6 | Viewed by 1830

Abstract

(1) Background: Risk perception is a key factor in motivating people to comply with preventive behaviors during the COVID-19 pandemic. Appropriate risk perception is important to enhance beliefs and promote emergency management response to public health events. (2) Objective: This study developed a [...] Read more.

(1) Background: Risk perception is a key factor in motivating people to comply with preventive behaviors during the COVID-19 pandemic. Appropriate risk perception is important to enhance beliefs and promote emergency management response to public health events. (2) Objective: This study developed a public risk perception measurement method for social media data to understand the dynamic characteristics of risk perception and emotional expression during public health emergencies. (3) Methods: Utilizing text-mining techniques and deep-learning algorithms, risk perception was calculated from two dimensions (dread and unknown) as well as the emotional expression characteristics of 185,025 posts from 10 January 2020 to 20 March 2020 on Sina Weibo. We also analyzed the characteristics of risk perception at different stages of the crisis life cycle. Furthermore, drawing on arousal theory, we constructed dynamic response relationships between emotion type (angry, fearful, sad, positive, and neutral) and risk perceptions by a vector autoregressive (VAR) model. (4) Results: The results revealed that the public expresses significantly more dread words than unknown words in shaping the risk perception process. As for the characteristics of evolution, public risk perception had been at a high level since the outbreak stage, and there was a sudden increase and a gradual decrease in the level of public risk perception. We also found that there is a significant response relationship between positive emotion, angry emotion, and risk perception. (5) Conclusion: This study provides a theoretical basis for more targeted epidemic crisis interventions. It points out the need for health communication strategy makers to consider the public’s risk perception and emotional expression characteristics during public health emergencies. Full article

(This article belongs to the Special Issue Systemic and Quantitative Methods for the Analysis of Societal Threats)

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26 pages, 15132 KiB

Open AccessArticle

Tree-Based Mix-Order Polynomial Fusion Network for Multimodal Sentiment Analysis

by Jiajia Tang, Ming Hou, Xuanyu Jin, Jianhai Zhang, Qibin Zhao and Wanzeng Kong

Systems 2023, 11(1), 44; https://doi.org/10.3390/systems11010044 - 12 Jan 2023

Viewed by 1914

Abstract

Multimodal sentiment analysis is an actively growing field of research, where tensor-based techniques have demonstrated great expressive efficiency in previous research. However, existing sequential sentiment analysis methods only focus on a single fixed-order representation space with a specific order, which results in the [...] Read more.

Multimodal sentiment analysis is an actively growing field of research, where tensor-based techniques have demonstrated great expressive efficiency in previous research. However, existing sequential sentiment analysis methods only focus on a single fixed-order representation space with a specific order, which results in the local optimal performance of the sentiment analysis model. Furthermore, existing methods could only employ a single sentiment analysis strategy at each layer, which indeed limits the capability of exploring comprehensive sentiment properties. In this work, the mixed-order polynomial tensor pooling (MOPTP) block is first proposed to adaptively activate the much more discriminative sentiment properties among mixed-order representation subspaces with varying orders, leading to relatively global optimal performance. Using MOPTP as a basic component, we further establish a tree-based mixed-order polynomial fusion network (TMOPFN) to explore multi-level sentiment properties via the parallel procedure. Indeed, TMOPFN allows using multiple sentiment analysis strategies at the same network layer simultaneously, resulting in the improvement of expressive power and the great flexibility of the model. We verified TMOPFN on three multimodal datasets with various experiments, and find it can obtain state-of-the-art or competitive performance. Full article

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8 pages, 932 KiB

Open AccessPerspective

Biochip Systems for Intelligence and Integration

by Junhao Wang, Bihao Sun and Zhiyuan Zhu

Systems 2023, 11(1), 43; https://doi.org/10.3390/systems11010043 - 11 Jan 2023

Cited by 3 | Viewed by 2745

Abstract

Disease is one of the major threats to human life and health, and historically there have been many cases which threatened human life due to infectious diseases. In almost all cases, specific triggers for the emergence of disease can be identified, so there [...] Read more.

Disease is one of the major threats to human life and health, and historically there have been many cases which threatened human life due to infectious diseases. In almost all cases, specific triggers for the emergence of disease can be identified, so there is an urgent need for effective detection and identification of most diseases, including infectious diseases. Therefore, this article proposes biochip systems as a tool for disease detection and risk assessment, and explains why they are effective in detecting disease, in terms of their working mechanisms, advantages and disadvantages, specific application scenarios and future trends. Full article

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15 pages, 345 KiB

Open AccessSystematic Review

A Systematic Review on the Use of Emerging Technologies in Teaching English as an Applied Language at the University Level

by Blanka Klimova, Marcel Pikhart, Petra Polakova, Miloslava Cerna, Sule Yildirim Yayilgan and Sarang Shaikh

Systems 2023, 11(1), 42; https://doi.org/10.3390/systems11010042 - 11 Jan 2023

Cited by 13 | Viewed by 5617

Abstract

At present, emerging technologies, such as machine learning, deep learning, or various forms of artificial intelligence are penetrating different fields of education, including foreign language education (FLE). Moreover, the current young generation was born into the technological environment, and they perceive technologies as [...] Read more.

At present, emerging technologies, such as machine learning, deep learning, or various forms of artificial intelligence are penetrating different fields of education, including foreign language education (FLE). Moreover, the current young generation was born into the technological environment, and they perceive technologies as being an indispensable part of their everyday life. However, they mainly use technologies in their informal learning, but there is not much research into emerging technologies in FLE, namely in teaching and learning English as an applied language. Therefore, the purpose of this systematic review is to identify, bring together, compare and analyze all of the technologies that are currently efficiently employed in foreign language teaching and learning, and based on the findings of the detected experimental studies, we provide specific pedagogical implications on how to use these technologies in the acquisition of English as an applied language at the university level. The methodology followed the PRISMA guidelines for systematic reviews and meta-analyses. The results of the detected experimental studies revealed that there was a serious lack of the latest technologies, such as chatbots or virtual reality (VR) devices, that are being empirically employed in a foreign language (FL) education. Moreover, mobile apps are merely focused on the development of FL vocabulary. The findings also indicate that although the FL teachers might theoretically know about these latest technological devices, such as neural machine translation, they do not know how to practically implement them in their teaching process. Therefore, this research suggests that teachers must be trained and pedagogically guided on how to purposefully implement them in their FL classes to support traditional instruction in order to identify what skills or language structures could be developed through their use. In addition, it is also claimed that more experimental studies are needed to clearly the evidence and its usefulness in teaching a foreign language as an applied language. Full article

(This article belongs to the Special Issue Innovations in Educational Systems and Digital Transformations in Education)

24 pages, 5337 KiB

Open AccessArticle

Proposing a Small-Scale Digital Twin Implementation Framework for Manufacturing from a Systems Perspective

by Jonatan H. Loaiza, Robert J. Cloutier and Kari Lippert

Systems 2023, 11(1), 41; https://doi.org/10.3390/systems11010041 - 11 Jan 2023

Cited by 4 | Viewed by 3419

Abstract

Due to the fourth industrial revolution, manufacturing companies are looking to implement digital twins in their factories to be more competitive. However, the implementation of digital twins in manufacturing systems is a complex task. Factories need a framework that can guide them in [...] Read more.

Due to the fourth industrial revolution, manufacturing companies are looking to implement digital twins in their factories to be more competitive. However, the implementation of digital twins in manufacturing systems is a complex task. Factories need a framework that can guide them in the development of digital twins. Hence, this article proposes a small-scale digital twin implementation framework for manufacturing systems. To build this framework, the authors gathered several concepts from the literature and designed a digital twin subsystem model using a model-based systems engineering (MBSE) approach and the systems engineering “Vee” model. The systems modelling defines the digital twin components, functionalities, and structure. The authors distribute most of these concepts throughout the framework configuration and some concepts next to this general configuration. This configuration presents three spaces: physical, virtual, and information. The physical space presents a physical layer and a perception layer. The information space has a single layer called middleware. Finally, the virtual space presents two layers: application and model. In addition to these layers, this framework includes other concepts such as digital thread, data, ontology, and enabling technologies. This framework could help researchers and practitioners to learn more about digital twins and apply it to different domains. Full article

(This article belongs to the Special Issue Model-Based Systems Engineering: From Design to Practical Systems Engineering)

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24 pages, 4204 KiB

Open AccessArticle

Optimal Production and Pricing Strategies of Automobile Manufacturers in Big Cities under Subsidy Policy and Dual-Credit Policy

by Li Tang and Xiaobei Liang

Systems 2023, 11(1), 40; https://doi.org/10.3390/systems11010040 - 11 Jan 2023

Cited by 1 | Viewed by 1855

Abstract

Encouraging the usage of new energy vehicles (NEVs) in big cities is not only a key area of priority for the government to encourage the transformation of the automobile industry, but it is also a crucial step in reducing environmental pollution. Big cities [...] Read more.

Encouraging the usage of new energy vehicles (NEVs) in big cities is not only a key area of priority for the government to encourage the transformation of the automobile industry, but it is also a crucial step in reducing environmental pollution. Big cities commonly limit the number of cars because they lack the resources and space to accommodate new vehicles. A crucial policy to reduce the number of cars in metropolitan areas is the license plate auction policy. Therefore, considering the fuel vehicle (FV)’s license plate auction policy, this study investigated the effects of the subsidy policy and the dual-credit policy on the production decisions of NEVs and FVs manufacturers. A competitive game model was constructed that considered NEV and FV manufacturers and accounted for consumer environmental awareness. The manufacturer’s optimal production decision was analyzed in four different scenarios—no government intervention, a license plate auction policy, a subsidy policy based on license plate auction policy, and a dual-credit policy based on the license plate auction policy. The results suggested that the manufacturer’s profit will be significantly higher in the absence of a license plate auction policy than in the presence of one. In other words, both NEV and FV manufacturers will suffer as a result of license plate restriction. Additionally, improvements in consumer environmental awareness, government subsidies, and credit cost/benefit ratios will improve the weak position of NEV manufacturers following the introduction of a license plate auction. Full article

(This article belongs to the Topic Climate Change and Environmental Sustainability, 2nd Volume)

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18 pages, 3433 KiB

Open AccessArticle

Simulation of Manufacturing Scenarios’ Ambidexterity Green Technological Innovation Driven by Inter-Firm Social Networks: Based on a Multi-Objective Model

by Xuan Wei, Hongyu Wu, Zaoli Yang, Chunjia Han and Bing Xu

Systems 2023, 11(1), 39; https://doi.org/10.3390/systems11010039 - 10 Jan 2023

Cited by 5 | Viewed by 1939

Abstract

The mechanism of the impact of inter-firm social networks on innovation capabilities has attracted much research from both theoretical and empirical perspectives. However, as a special emerged and developing complex production system, how the scenario factors affect the relationship between these variables has [...] Read more.

The mechanism of the impact of inter-firm social networks on innovation capabilities has attracted much research from both theoretical and empirical perspectives. However, as a special emerged and developing complex production system, how the scenario factors affect the relationship between these variables has not yet been analyzed. This study identified several scenario factors which can affect the firm’s technological innovation capabilities. Take the manufacturing scenario in China as an example, combined with the need for firms’ ambidexterity innovation and green innovation capability, a multi-objective simulation model is constructed. Past empirical analysis results on the relationship between inter-firm social network factors and innovation capabilities are used in the model. In addition, a numerical analysis was conducted using data from the Chinese auto manufacturing industry. The results of the simulation model led to several optimization strategies for firms that are in a dilemma of development in the manufacturing scenario. Full article

(This article belongs to the Special Issue Data Driven Decision-Making for Complex Production Systems)

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44 pages, 8615 KiB

Open AccessReview

Blockchain Application in Healthcare Systems: A Review

by Pranto Kumar Ghosh, Arindom Chakraborty, Mehedi Hasan, Khalid Rashid and Abdul Hasib Siddique

Systems 2023, 11(1), 38; https://doi.org/10.3390/systems11010038 - 08 Jan 2023

Cited by 38 | Viewed by 19634

Abstract

In the recent years, blockchain technology has gained significant attention in the healthcare sector. It has the potential to alleviate a wide variety of major difficulties in electronic health record systems. This study presents an elaborate overview of the existing research works on [...] Read more.

In the recent years, blockchain technology has gained significant attention in the healthcare sector. It has the potential to alleviate a wide variety of major difficulties in electronic health record systems. This study presents an elaborate overview of the existing research works on blockchain applications in the healthcare industry. This paper evaluates 144 articles that discuss the importance and limits of using blockchain technologies to improve healthcare operations. The objective is to demonstrate the technology’s potential uses and highlight the difficulties and possible sectors for future blockchain research in the healthcare domain. The paper starts with an extensive background study of blockchain and its features. Then, the paper focuses on providing an extensive literature review of the selected articles to highlight the current research themes in blockchain-based healthcare systems. After that, major application areas along with the solutions provided by blockchain in healthcare systems are pointed out. Finally, a discussion section provides insight into the limitations, challenges and future research directions. Full article

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19 pages, 1910 KiB

Open AccessArticle

Developing an Evaluation Index System for Enterprise Niche

by Renjie Hu, Steve Conway, Guangyu Zhang, Xueying Liu and Chen Chen

Systems 2023, 11(1), 37; https://doi.org/10.3390/systems11010037 - 08 Jan 2023

Viewed by 1408

Abstract

With the progress of globalization, the environment for enterprises’ survival and development has become increasingly complex. More and more enterprises realize that their sustainable competitive advantage is closely related to the development of enterprise niche. Based on the ecostate-ecorole theory, an evaluation index [...] Read more.

With the progress of globalization, the environment for enterprises’ survival and development has become increasingly complex. More and more enterprises realize that their sustainable competitive advantage is closely related to the development of enterprise niche. Based on the ecostate-ecorole theory, an evaluation index system for enterprise niche is developed in this paper. The study selects indicators based on literature research and frequency analysis, adopts factors including market environment, industrial environment, human resources, and technical resources to evaluate ecostate of enterprise niche, and establishes an evaluation model for ecostate; the research uses factors including policy environment, innovation decision-making ability, resource accessibility, and technical management capability to evaluate ecorole of enterprise niche, and sets up an evaluation model for ecorole by catastrophe progression method. The results of the reliability and validity test showed that the evaluation index system is both reliable and effective. The paper provides implications for the evaluation of enterprise niche. Full article

(This article belongs to the Section Systems Practice in Social Science)

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15 pages, 2465 KiB

Open AccessArticle

Encipher GAN: An End-to-End Color Image Encryption System Using a Deep Generative Model

by Kirtee Panwar, Akansha Singh, Sonal Kukreja, Krishna Kant Singh, Nataliya Shakhovska and Andrii Boichuk

Systems 2023, 11(1), 36; https://doi.org/10.3390/systems11010036 - 07 Jan 2023

Cited by 6 | Viewed by 2859

Abstract

Chaos-based image encryption schemes are applied widely for their cryptographic properties. However, chaos and cryptographic relations remain a challenge. The chaotic systems are defined on the set of real numbers and then normalized to a small group of integers in the range 0–255, [...] Read more.

Chaos-based image encryption schemes are applied widely for their cryptographic properties. However, chaos and cryptographic relations remain a challenge. The chaotic systems are defined on the set of real numbers and then normalized to a small group of integers in the range 0–255, which affects the security of such cryptosystems. This paper proposes an image encryption system developed using deep learning to realize the secure and efficient transmission of medical images over an insecure network. The non-linearity introduced with deep learning makes the encryption system secure against plaintext attacks. Another limiting factor for applying deep learning in this area is the quality of the recovered image. The application of an appropriate loss function further improves the quality of the recovered image. The loss function employs the structure similarity index metric (SSIM) to train the encryption/decryption network to achieve the desired output. This loss function helped to generate cipher images similar to the target cipher images and recovered images similar to the originals concerning structure, luminance and contrast. The images recovered through the proposed decryption scheme were high-quality, which was further justified by their PSNR values. Security analysis and its results explain that the proposed model provides security against statistical and differential attacks. Comparative analysis justified the robustness of the proposed encryption system. Full article

(This article belongs to the Special Issue Intelligent Information Technologies for Quality and Security Assurance)

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25 pages, 1329 KiB

Open AccessReview

Human-in-Loop: A Review of Smart Manufacturing Deployments

by Mangolika Bhattacharya, Mihai Penica, Eoin O’Connell, Mark Southern and Martin Hayes

Systems 2023, 11(1), 35; https://doi.org/10.3390/systems11010035 - 06 Jan 2023

Cited by 10 | Viewed by 3605

Abstract

The recent increase in computational capability has led to an unprecedented increase in the range of new applications where machine learning can be used in real time. Notwithstanding the range of use cases where automation is now feasible, humans are likely to retain [...] Read more.

The recent increase in computational capability has led to an unprecedented increase in the range of new applications where machine learning can be used in real time. Notwithstanding the range of use cases where automation is now feasible, humans are likely to retain a critical role in the operation and certification of manufacturing systems for the foreseeable future. This paper presents a use case review of how human operators affect the performance of cyber–physical systems within a ’smart’ or ’cognitive’ setting. Such applications are classified using Industry 4.0 (I4.0) or 5.0 (I5.0) terminology. The authors argue that, as there is often no general agreement as to when a specific use case moves from being an I4.0 to an I5.0 example, the use of a hybrid Industry X.0 notation at the intersection between I4.0 and I5.0 is warranted. Through a structured review of the literature, the focus is on how secure human-mediated autonomous production can be performed most effectively to augment and optimise machine operation. Full article

(This article belongs to the Special Issue Smart Manufacturing Systems for Industry 5.0)

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13 pages, 2349 KiB

Open AccessArticle

Adaptive Curriculum Sequencing and Education Management System via Group-Theoretic Particle Swarm Optimization

by Xiaojing Sheng, Kun Lan, Xiaoliang Jiang and Jie Yang

Systems 2023, 11(1), 34; https://doi.org/10.3390/systems11010034 - 06 Jan 2023

Cited by 6 | Viewed by 2490

Abstract

The Curriculum Sequencing (CS) problem is a challenging task to tackle in the field of online teaching and learning system development. The current methods of education management might still possess certain drawbacks that would cause ineffectiveness and incompatibility of the whole system. A [...] Read more.

The Curriculum Sequencing (CS) problem is a challenging task to tackle in the field of online teaching and learning system development. The current methods of education management might still possess certain drawbacks that would cause ineffectiveness and incompatibility of the whole system. A solution for achieving better user satisfaction would be to treat users individually and to offer educational materials in a customized way. Adaptive Curriculum Sequencing (ACS) plays an important role in education management system, for it helps finding the optimal sequence of a curriculum among various possible solutions, which is a typical NP-hard combinatorial optimization problem. Therefore, this paper proposes a novel metaheuristic algorithm named Group-Theoretic Particle Swarm Optimization (GT-PSO) to tackle the ACS problem. GT-PSO would rebuild the search paradigm adaptively based on the solid mathematical foundation of symmetric group through encoding the solution candidates, decomposing the search space, guiding neighborhood movements, and updating the swarm topology. The objective function is the learning goal, with additional intrinsic and extrinsic information from those users. Experimental results show that GT-PSO has outperformed most other methods in real-life scenarios, and the insights provided by our proposed method further indicate the theoretical and practical value of an effective and robust education management system. Full article

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19 pages, 4513 KiB

Open AccessArticle

Spatiotemporal Evolution and Determinants of the Geography of Chinese Patents Abroad: A Case Study of Strategic Emerging Industries

by Chenyang Zhai, Debin Du and Wentian Shi

Systems 2023, 11(1), 33; https://doi.org/10.3390/systems11010033 - 06 Jan 2023

Cited by 4 | Viewed by 2125

Abstract

China’s rapid technological growth and aggressive globalization policies have led to an increasing interest in Chinese patents abroad. This study uses strategic emerging industries (SEIs) that are important for the future development of the world as examples and constructs a novel dataset of [...] Read more.

China’s rapid technological growth and aggressive globalization policies have led to an increasing interest in Chinese patents abroad. This study uses strategic emerging industries (SEIs) that are important for the future development of the world as examples and constructs a novel dataset of Chinese SEI patents abroad (1993–2017) to explore the spatiotemporal evolution and determinants of the geography of these patents. Our results show that the number of Chinese SEI patents abroad is growing rapidly, and the new-generation information technology industry is increasingly dominating, accounting for approximately 50% of all SEI patents abroad. Chinese SEI patents abroad are highly concentrated in the United States, Western Europe, and East Asia, and their influence is gradually spreading from African countries to developed countries. The host country’s intellectual property rights (IPR) protection level, technology market size and imitation risk have significant positive effects on Chinese SEI patents abroad, while the host country’s high-tech product market size and competition risk have negative effects on Chinese patents abroad. The conclusions provide new information for understanding Chinese patents abroad activities and the motivation of China’s technology globalization and provide evidence from an emerging country for research of the international diffusion of technology innovation. Full article

(This article belongs to the Section Systems Practice in Social Science)

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16 pages, 3763 KiB

Open AccessArticle

Maintenance Service Configuration Optimization for Complex Equipment

by Chunliu Zhou, Shan Ye, Hongjun Wang, Jianhua Cao and Zhenhua Gao

Systems 2023, 11(1), 32; https://doi.org/10.3390/systems11010032 - 05 Jan 2023

Cited by 1 | Viewed by 1315

Abstract

Maintenance activities mostly depend on the specific conditions of individual equipment, being defined as personalized businesses. In order to improve the efficiency of maintenance activities for complex equipment in lots, the thinking of mass customization is used. After the modular technology used for [...] Read more.

Maintenance activities mostly depend on the specific conditions of individual equipment, being defined as personalized businesses. In order to improve the efficiency of maintenance activities for complex equipment in lots, the thinking of mass customization is used. After the modular technology used for generic maintenance model, the product/service was divided into mandatory and optional modules, which can form multiple optional maintenance service solutions. Considering the characteristics of maintenance activities and customers’ personalized maintenance requirements, configuration optimization is used to find the most satisfied maintenance solution under different objectives. This paper aims to provide the configuration optimization ideas and solutions for complex equipment maintenance services. A multi-objective optimization model was established, and an algorithm based on Non-Dominated Sorting Genetic Algorithms (NSGA-II) was proposed to solve this configuration optimization model. Finally, the maintenance service of the Electric Multiple Units (EMU) bogie was taken as an example to verify the feasibility of the model and the algorithm. Full article

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11 pages, 1059 KiB

Open AccessArticle

Efficacy of an Adaptive Learning System on Course Scores

by Lyndon Lim, Seo Hong Lim and Wei Ying Rebekah Lim

Systems 2023, 11(1), 31; https://doi.org/10.3390/systems11010031 - 05 Jan 2023

Viewed by 3110

Abstract

Adaptive learning systems have gained popularity within higher education, given the affordances that claim to enhance student learning outcomes by providing personalised learning trajectories that allow students to interact with course content at their own pace. Nonetheless, studies investigating the impact of such [...] Read more.

Adaptive learning systems have gained popularity within higher education, given the affordances that claim to enhance student learning outcomes by providing personalised learning trajectories that allow students to interact with course content at their own pace. Nonetheless, studies investigating the impact of such systems on learning outcomes such as course scores have been mixed, in part due to the research approaches applied, as found by the review undertaken in this study. Yet, for purposes of accountability, it remains critical to investigate the efficacy of adaptive learning systems, at least for its relation to course scores when assessment stakes are involved. This study reports the efficacy of an in-house adaptive learning system used within an institution in terms of its impact on course scores, based upon propensity score analysis, a quasi-experimental approach considered as a feasible alternative to randomised controlled trials. Results of this study reported a difference in course scores, suggesting merit in using the in-house adaptive learning system, though the difference did not present statistically significant differences at the 95% confidence level. Directions for future research are also discussed. Full article

(This article belongs to the Special Issue Innovations in Educational Systems and Digital Transformations in Education)

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10 pages, 746 KiB

Open AccessArticle

Foreign Language Vocabulary Acquisition and Retention in Print Text vs. Digital Media Environments

by Marcel Pikhart, Blanka Klimova and Fanny Bohnenberger Ruschel

Systems 2023, 11(1), 30; https://doi.org/10.3390/systems11010030 - 05 Jan 2023

Cited by 2 | Viewed by 2883

Abstract

In the context of very current trends in digital language education generally supported by governments and educational institutions, it seems necessary to evaluate the efficiency of these tools from various points of psycholinguistics and applied linguistics, mostly when it comes to learning a [...] Read more.

In the context of very current trends in digital language education generally supported by governments and educational institutions, it seems necessary to evaluate the efficiency of these tools from various points of psycholinguistics and applied linguistics, mostly when it comes to learning a foreign/second language (L2). Therefore, this paper aims to evaluate vocabulary retention in L2 when using print text in contrast with digital media. The research was conducted among 122 participants who were university students and were divided into two groups to learn 60 new phrasal verbs; one group of them using a standard print text, the other using the same text displayed and annotated on their digital devices. There were two memory tests after four weeks of studying the four sets of phrasal verbs, i.e., 15 verbs a week, and another test after another month to evaluate students’ memory retention of the given vocabulary in time. The results clearly show a slight but clear discrepancy in these two groups in favor of the group using the print text in both tests performed. The findings of this study suggest that students can retain L2 vocabulary better in conditions where they have access to printed vocabulary and if they can make notes, highlight or write their translation in their native language. However, these findings should be verified from other perspectives as well to obtain more reliable data. Full article

(This article belongs to the Special Issue Innovations in Educational Systems and Digital Transformations in Education)

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19 pages, 7607 KiB

Open AccessArticle

Fresh Product Supply Chain Analysis in Cauca, Colombia — A Hass Avocado System Dynamics Approach

by Yesid Ediver Anacona Mopan, Oscar Rubiano-Ovalle, Helmer Paz, Andrés Felipe Solis Pino, Mario Chong and Ana Luna

Systems 2023, 11(1), 29; https://doi.org/10.3390/systems11010029 - 05 Jan 2023

Viewed by 2531

Abstract

In recent years, agriculture has become an essential activity in Colombia, despite the challenges faced by farmers due to low yields and insufficient resources to improve their main activities, such as irrigation systems, agricultural practices, and industrial machinery. This Hass avocado approach has [...] Read more.

In recent years, agriculture has become an essential activity in Colombia, despite the challenges faced by farmers due to low yields and insufficient resources to improve their main activities, such as irrigation systems, agricultural practices, and industrial machinery. This Hass avocado approach has been addressed in previous research considering system dynamics simulation to evaluate farmers’ behavior strategies and improve their competitiveness. However, these studies typically examine a single strategy effect and avoid multiple integrated strategies. Other studies focused on the complex interactions between different factors in the production chain and their feedback effects on farmers’ productivity and cash flow. For these reasons, this research provides a comprehensively dynamic model and evaluates long-term strategies and their effects on supporting and improving small farmers’ productivity and profitability. A system dynamics methodology was used to model complex systems processing Hass avocado farmer association data and explore their effects on competitiveness for long-term sustainable and profitable agriculture. This research proposes optimal scenarios for small farmers, including strategies such as low-interest credit access, logistics practices, and government technical support. The scenarios provide a proactive tool for decision makers and promote rural farmers’ development, aligning high-quality fresh product supply and demand. Full article

(This article belongs to the Special Issue Business Model–the Perspective of Systems Thinking and Innovation)

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20 pages, 5722 KiB

Open AccessArticle

A Hybrid AES with a Chaotic Map-Based Biometric Authentication Framework for IoT and Industry 4.0

by Ayman Altameem, Prabu P, Senthilnathan T, Ramesh Chandra Poonia and Abdul Khader Jilani Saudagar

Systems 2023, 11(1), 28; https://doi.org/10.3390/systems11010028 - 05 Jan 2023

Cited by 2 | Viewed by 2011

Abstract

The Internet of Things (IoT) is being applied in multiple domains, including smart homes and energy management. This work aims to tighten security in IoTs using fingerprint authentications and avoid unauthorized access to systems for safeguarding user privacy. Captured fingerprints can jeopardize the [...] Read more.

The Internet of Things (IoT) is being applied in multiple domains, including smart homes and energy management. This work aims to tighten security in IoTs using fingerprint authentications and avoid unauthorized access to systems for safeguarding user privacy. Captured fingerprints can jeopardize the security and privacy of personal information. To solve privacy- and security-related problems in IoT-based environments, Biometric Authentication Frameworks (BAFs) are proposed to enable authentications in IoTs coupled with fingerprint authentications on edge consumer devices and to ensure biometric security in transmissions and databases. The Honeywell Advanced Encryption Security-Cryptography Measure (HAES-CM) scheme combined with Hybrid Advanced Encryption Standards with Chaotic Map Encryptions is proposed. BAFs enable private and secure communications between Industry 4.0’s edge devices and IoT. This work’s suggested scheme’s evaluations with other encryption methods reveal that the suggested HAES-CM encryption strategy outperforms others in terms of processing speeds. Full article

(This article belongs to the Section Systems Engineering)

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19 pages, 1791 KiB

Open AccessArticle

Adaptive Artificial Bee Colony Algorithm for Nature-Inspired Cyber Defense

by Chirag Ganguli, Shishir Kumar Shandilya, Maryna Nehrey and Myroslav Havryliuk

Systems 2023, 11(1), 27; https://doi.org/10.3390/systems11010027 - 05 Jan 2023

Cited by 5 | Viewed by 2310

Abstract

With the significant growth of the cyber environment over recent years, defensive mechanisms against adversaries have become an important step in maintaining online safety. The adaptive defense mechanism is an evolving approach that, when combined with nature-inspired algorithms, allows users to effectively run [...] Read more.

With the significant growth of the cyber environment over recent years, defensive mechanisms against adversaries have become an important step in maintaining online safety. The adaptive defense mechanism is an evolving approach that, when combined with nature-inspired algorithms, allows users to effectively run a series of artificial intelligence-driven tests on their customized networks to detect normal and under attack behavior of the nodes or machines attached to the network. This includes a detailed analysis of the difference in the throughput, end-to-end delay, and packet delivery ratio of the nodes before and after an attack. In this paper, we compare the behavior and fitness of the nodes when nodes under a simulated attack are altered, aiding several nature-inspired cyber security-based adaptive defense mechanism approaches and achieving clear experimental results. The simulation results show the effectiveness of the fitness of the nodes and their differences through a specially crafted metric value defined using the network performance statistics and the actual throughput difference of the attacked node before and after the attack. Full article

(This article belongs to the Special Issue Intelligent Information Technologies for Quality and Security Assurance)

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21 pages, 1554 KiB

Open AccessArticle

Motor Vehicle Insurance Anti-Fraud Modeling Based on a Stochastic Differential Game System

by Meixuan Li, Wei Liu, Chun Yan and Mengchao Zhang

Systems 2023, 11(1), 26; https://doi.org/10.3390/systems11010026 - 04 Jan 2023

Viewed by 1311

Abstract

In this paper, we regard policyholders, insurance companies, and government departments to be an anti-fraud supervision system, and we explore the supervision of motor vehicle insurance fraud from the perspective of a tripartite game. Taking into consideration the bad reputation records of policyholders [...] Read more.

In this paper, we regard policyholders, insurance companies, and government departments to be an anti-fraud supervision system, and we explore the supervision of motor vehicle insurance fraud from the perspective of a tripartite game. Taking into consideration the bad reputation records of policyholders as a state variable, through continuous accumulation in effective time, it creates a continuous growth-type warning effect on policyholders, and thus, effectively curbs policyholder fraud and false supervision by insurance companies. At the same time, by considering the influence of random factors on the anti-fraud game of motor vehicle insurance, in this paper, we establish a stochastic differential game model to explore the optimal strategy, the optimal income level, and the expectation and variance of the insured’s bad reputation record stock under the conditions of with and without government supervision. Finally, through a simulation analysis, it is found that the game with government supervision is more conducive to reduce the insured’s fraud intensity, and the simulation proves the impact of different parameters on system stability. Full article

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31 pages, 15874 KiB

Open AccessArticle

Effectiveness of AR Board Game on Computational Thinking and Programming Skills for Elementary School Students

by Shih-Yun Huang, Wernhuar Tarng and Kuo-Liang Ou

Systems 2023, 11(1), 25; https://doi.org/10.3390/systems11010025 - 04 Jan 2023

Cited by 8 | Viewed by 3776

Abstract

This study integrated the augmented reality (AR) technology into the “Coding Ocean” board game to provide players with real-time simulation of ship paths and learning scaffolds. Combined with Scratch block-based programming, an interactive learning environment is developed to assist elementary school students in [...] Read more.

This study integrated the augmented reality (AR) technology into the “Coding Ocean” board game to provide players with real-time simulation of ship paths and learning scaffolds. Combined with Scratch block-based programming, an interactive learning environment is developed to assist elementary school students in learning coding skills from the unplugged board game to enhance their computational thinking concepts. The AR board game is focused on the programming concepts of sequential, and/or and loop. Through the process of treasure hunting, the basic concepts of computational thinking can be developed, i.e., abstraction, problem decomposition, pattern recognition and algorithmic thinking. In order to investigate the learning effectiveness of the AR board game on computational thinking and programming skills, a number of 51 third graders from an elementary school were recruited as research samples. The experimental group (n = 26) used the AR board game and the control group (n = 25) used the traditional board game for game-based learning. The experimental results indicate: (1) the learning effectiveness of computational thinking for the experimental group was significantly higher than that of the control group; (2) the learning achievement of the block-based programming skills for the experimental group was significantly higher than that of the control group; (3) the cognitive load of the experimental group was significantly lower than that of the control group. The AR technology can combine the unplugged board games with plugged learning modules to assist students in game-based learning, which is useful for enhancing computational thinking abilities while reducing the cognitive load. Full article

(This article belongs to the Special Issue Innovations in Educational Systems and Digital Transformations in Education)

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19 pages, 1978 KiB

Open AccessArticle

High-Speed Rails and City Innovation System: Empirical Evidence from China

by Jiafeng Gu

Systems 2023, 11(1), 24; https://doi.org/10.3390/systems11010024 - 04 Jan 2023

Cited by 4 | Viewed by 1742

Abstract

The rapid development of high-speed rail has markedly shortened the travel time from one city to another. However, the impact of space–time compression brought about by high-speed rail on city innovation has not received sufficient attention. This paper examines the space–time compression phenomenon [...] Read more.

The rapid development of high-speed rail has markedly shortened the travel time from one city to another. However, the impact of space–time compression brought about by high-speed rail on city innovation has not received sufficient attention. This paper examines the space–time compression phenomenon produced by high-speed railway networks and its impact on city innovation from 2000 to 2019 using a sample of 279 Chinese prefecture-level cities. The empirical results show that there was a strong space–time compression during this period. The development of high-speed rail can promote city innovation. However, the construction of high-speed rail also produces a siphon effect, which accelerates the convergence of innovative elements in cities with stronger innovation capabilities. Nevertheless, it has a negative spillover effect on cities with weaker innovation capabilities. Finally, policy recommendations for promoting the balanced development of city innovation and recommendations for future research are presented. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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42 pages, 8606 KiB

Open AccessArticle

A New Decision-Making Strategy for Techno-Economic Assessment of Generation and Transmission Expansion Planning for Modern Power Systems

by Mohamed M. Refaat, Shady H. E. Abdel Aleem, Yousry Atia, Essam El Din Aboul Zahab and Mahmoud M. Sayed

Systems 2023, 11(1), 23; https://doi.org/10.3390/systems11010023 - 04 Jan 2023

Cited by 4 | Viewed by 1992

Abstract

Planning for the intensive use of renewable energy sources (RESs) has attracted wide attention to limit global warming and meet future load growth. Existing studies have shown that installing projects such as transmission lines, energy storage systems (ESSs), fault current limiters, and FACTs [...] Read more.

Planning for the intensive use of renewable energy sources (RESs) has attracted wide attention to limit global warming and meet future load growth. Existing studies have shown that installing projects such as transmission lines, energy storage systems (ESSs), fault current limiters, and FACTs facilitate the integration of RESs into power systems. Different generation and transmission network expansion planning models have been developed in the literature; however, a planning model that manages multiple types of projects while maximizing the hosting capacity (HC) is not widely presented. In this paper, a novel planning framework is proposed to enhance and control the HC level of RESs by comparing various kinds of renewables, ESSs, fault current limiters, and FACTs to choose the right one, economically and technically. The proposed problem is formulated as a challenging mixed-integer non-linear optimization problem. To solve it, a solution methodology based on a developed decision-making approach and an improved meta-heuristic algorithm is developed. The decision-making approach aims to keep the number of decision variables as fixed as possible, regardless of the number of projects planned. While an improved war strategy optimizer that relies on the Runge-Kutta learning strategy is applied to strengthen the global search ability. The proposed decision-making approach depends primarily on grouping candidate projects that directly impact the same system state into four separate planning schemes. The first scheme relies on the impedance of devices installed in any path to optimally identify the location and size of the new circuits and the series-type FACTs. The second scheme is based on optimally determining the suitable types of ESSs. On the other hand, the third scheme optimizes the reactive power dispatched from the ESSs and shunt-type FACTs simultaneously. The fourth scheme is concerned with regulating the power dispatched from different types of RESs. All of the simulations, which were carried out on the Garver network and the 118-bus system, demonstrated the ability of the investigated model to select the appropriate projects precisely. Further, the results proved the robustness and effectiveness of the proposed method in obtaining high-quality solutions in fewer runs compared to the conventional method. Full article

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27 pages, 5924 KiB

Open AccessArticle

Enabling Mobility: A Simulation Model of the Health Care System for Major Lower-Limb Amputees to Assess the Impact of Digital Prosthetics Services

by Jefferson K. Rajah, William Chernicoff, Christopher J. Hutchison, Paulo Gonçalves and Birgit Kopainsky

Systems 2023, 11(1), 22; https://doi.org/10.3390/systems11010022 - 03 Jan 2023

Cited by 2 | Viewed by 7050

Abstract

The World Health Organization estimates that 5 to 15% of amputees in any given population have access to a prosthesis. This figure is likely to worsen as the amputee population is expected to double by 2050, straining the limited capacity of prosthetics services. [...] Read more.

The World Health Organization estimates that 5 to 15% of amputees in any given population have access to a prosthesis. This figure is likely to worsen as the amputee population is expected to double by 2050, straining the limited capacity of prosthetics services. Without proper and timely prosthetic interventions, amputees with major lower-limb loss experience adverse mobility outcomes, including the loss of independence, lowered quality of life, and decreased life expectancy. Presently, the use of digital technology in prosthetics (e.g., 3D imaging, digital processing, and 3D printed sockets) is contended as a viable solution to this problem. This paper uses system dynamics modeling to assess the impact of digital prosthetics service provision. Our simulation model represents the patient-care continuum and digital prosthetics market system, providing a feedback-rich causal theory of how digital prosthetics impacts amputee mobility and the corollary socio-health-economic outcomes over time. With sufficient resources for market formation and capacity expansion for digital prosthetics services, our work suggests an increased proportion of prosthesis usage and improved associated health-economic outcomes. Accordingly, our findings could provide decision support for health policy to better mitigate the accessibility problem and bolster the social impact of prosthesis usage. Full article

(This article belongs to the Special Issue System Dynamics Models for Public Health and Health Care Policy)

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14 pages, 2657 KiB

Open AccessArticle

MLA-LSTM: A Local and Global Location Attention LSTM Learning Model for Scoring Figure Skating

by Chaoyu Han, Fangyao Shen, Lina Chen, Xiaoyi Lian, Hongjie Gou and Hong Gao

Systems 2023, 11(1), 21; https://doi.org/10.3390/systems11010021 - 02 Jan 2023

Cited by 1 | Viewed by 2026

Abstract

Video-based scoring using neural networks is a very important means for evaluating many sports, especially figure skating. Although many methods for evaluating action quality have been proposed, there is no uniform conclusion on the best feature extractor and clip length for the existing [...] Read more.

Video-based scoring using neural networks is a very important means for evaluating many sports, especially figure skating. Although many methods for evaluating action quality have been proposed, there is no uniform conclusion on the best feature extractor and clip length for the existing methods. Furthermore, during the feature aggregation stage, these methods cannot accurately locate the target information. To address these tasks, firstly, we systematically compare the effects of the figure skating model with three different feature extractors (C3D, I3D, R3D) and four different segment lengths (5, 8, 16, 32). Secondly, we propose a Multi-Scale Location Attention Module (MS-LAM) to capture the location information of athletes in different video frames. Finally, we present a novel Multi-scale Location Attentive Long Short-Term Memory (MLA-LSTM), which can efficiently learn local and global sequence information in each video. In addition, our proposed model has been validated on the Fis-V and MIT-Skate datasets. The experimental results show that I3D and 32 frames per second are the best feature extractor and clip length for video scoring tasks. In addition, our model outperforms the current state-of-the-art method hybrid dynAmic-statiC conText-aware attentION NETwork (ACTION-NET), especially on MIT-Skate (by 0.069 on Spearman’s rank correlation). In addition, it achieves average improvements of 0.059 on Fis-V compared with Multi-scale convolutional skip Self-attentive LSTM Module (MS-LSTM). It demonstrates the effectiveness of our models in learning to score figure skating videos. Full article

(This article belongs to the Special Issue Human–AI Teaming: Synergy, Decision-Making and Interdependency)

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23 pages, 9530 KiB

Open AccessArticle

Unraveling the Most Influential Determinants of Residential Segregation in Jakarta: A Spatial Agent-Based Modeling and Simulation Approach

by Hendra Kusumah and Meditya Wasesa

Systems 2023, 11(1), 20; https://doi.org/10.3390/systems11010020 - 02 Jan 2023

Cited by 2 | Viewed by 2344

Abstract

This study involves the analysis of the residential segregation patterns in Jakarta, Indonesia, one of the largest global metropolitan cities. Our objective is to determine whether similarities in religion or socioeconomic status are more dominant in shaping residential segregation patterns in Jakarta. To [...] Read more.

This study involves the analysis of the residential segregation patterns in Jakarta, Indonesia, one of the largest global metropolitan cities. Our objective is to determine whether similarities in religion or socioeconomic status are more dominant in shaping residential segregation patterns in Jakarta. To do so, we extended Schelling’s segregation agent-based model incorporating the random discrete utility choice approach to simulate the relocation decisions of the inhabitants. Utilizing actual census data from the 2010–2013 time period and the Jakarta GIS map, we simulated the relocation movements of the inhabitants at the subdistrict level. We set the inhabitants’ socioeconomic and religious similarities as the independent variables and the housing constraints as the moderating variable. The segregation parameters of the inhabitants (i.e., dissimilarity and Simpson indexes) and the spatial patterns of residential segregation (i.e., Moran index and segregation maps) were set as the dependent variables. Additionally, we further validated the simulation outcomes for various scenarios and contrasted them with their actual empirical values. This study concludes that religious similarity is more dominant than socioeconomic status similarity in shaping residential segregation patterns in Jakarta. Full article

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Systems, Volume 11, Issue 1 (January 2023) – 49 articles

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