Pub Date : 2025-01-01DOI: 10.1016/j.jestch.2024.101914
Van-Truong Nguyen , Quoc-Cuong Nguyen , Mien Van , Shun-Feng Su , Harish Garg , Dai-Nhan Duong , Phan Xuan Tan
This paper presents a new adaptive nonlinear proportional integral derivative radial basis function neural network (NPID-RBFNN) for ballbots with external force. The proposed controller is designed based on a hybrid of a nonlinear proportional integral derivative (NPID) control, radial basis function neural networks (RBFNN), and balancing composite motion optimization (BCMO). The hybrid NPID-RBFNN controller offers a light-weight computation, chattering-reduction, while providing high robustness against model uncertainties and external disturbance. Therefore, it provides excellent features to control ballbots against the counterpart approaches such as the conventional PID, conventional NPID, which preserves low robustness against disturbances, or sliding mode control (SMC), which provides higher chattering. The BCMO is used to determine the gain values that best fit the system, and RBFNN is learned continuously during the ballbot movement to balance the system in the most stable and smooth way. The NPID-RBFNN controller is proven to be stable through the Lyapunov approach. The simulation and experiment results show that the NPID-RBFNN controller is a robust method for controlling the ballbot system’s motion in applications with external force.
{"title":"Robust adaptive nonlinear PID controller using radial basis function neural network for ballbots with external force","authors":"Van-Truong Nguyen , Quoc-Cuong Nguyen , Mien Van , Shun-Feng Su , Harish Garg , Dai-Nhan Duong , Phan Xuan Tan","doi":"10.1016/j.jestch.2024.101914","DOIUrl":"10.1016/j.jestch.2024.101914","url":null,"abstract":"<div><div>This paper presents a new adaptive nonlinear proportional integral derivative radial basis function neural network (NPID-RBFNN) for ballbots with external force. The proposed controller is designed based on a hybrid of a nonlinear proportional integral derivative (NPID) control, radial basis function neural networks (RBFNN), and balancing composite motion optimization (BCMO). The hybrid NPID-RBFNN controller offers a light-weight computation, chattering-reduction, while providing high robustness against model uncertainties and external disturbance. Therefore, it provides excellent features to control ballbots against the counterpart approaches such as the conventional PID, conventional NPID, which preserves low robustness against disturbances, or sliding mode control (SMC), which provides higher chattering. The BCMO is used to determine the gain values that best fit the system, and RBFNN is learned continuously during the ballbot movement to balance the system in the most stable and smooth way. The NPID-RBFNN controller is proven to be stable through the Lyapunov approach. The simulation and experiment results show that the NPID-RBFNN controller is a robust method for controlling the ballbot system’s motion in applications with external force.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101914"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jestch.2024.101936
Mesut Samasti , Emre Cakmak , Alper Ozpinar
Smart cities represent the forefront of combining technological innovation with urban management to enhance the quality of life and sustainability of urban environments. While existing studies have focused on individual smart city evaluations, there is a notable gap in systematic classification approaches that can handle uncertain and incomplete data in developing countries. As urban populations continue to grow, the strategic integration of smart technologies in city planning and management becomes crucial, necessitating more sophisticated evaluation methodologies. These technologies offer promising solutions to urban challenges by improving efficiency, economic growth, and citizen engagement. This research addresses this gap by proposing a novel framework that combines Interval Valued Neutrosophic Sets (IVNS) with the EDAS Method, specifically designed to handle the complexities and uncertainties inherent in developing country contexts.
The study extensively reviews existing literature and methodologies applied in similar contexts, identifying key limitations in current approaches and building a robust framework that incorporates both new and established criteria. Through the systematic application of IVNS-EDAS methodology across multiple urban environments, this study develops a comprehensive classification system that accounts for both quantitative metrics and qualitative assessments of smart city capabilities. The results showcase a dynamic classification framework that effectively handles data uncertainty while providing clear, actionable insights for urban planners and policymakers. The paper concludes by validating the effectiveness of the proposed approach through a detailed computational study involving diverse stakeholders, confirming its applicability and utility in refining smart city strategies globally, particularly in developing country contexts where data reliability and completeness may be challenging.
The study provides specific policy guidelines for each city classification, offering policymakers a structured framework for resource allocation and strategic planning, ranging from foundational infrastructure development in emerging cities to advanced technology integration in metropolitan areas.
{"title":"Strategic classification of smart city strategies in developing countries","authors":"Mesut Samasti , Emre Cakmak , Alper Ozpinar","doi":"10.1016/j.jestch.2024.101936","DOIUrl":"10.1016/j.jestch.2024.101936","url":null,"abstract":"<div><div>Smart cities represent the forefront of combining technological innovation with urban management to enhance the quality of life and sustainability of urban environments. While existing studies have focused on individual smart city evaluations, there is a notable gap in systematic classification approaches that can handle uncertain and incomplete data in developing countries. As urban populations continue to grow, the strategic integration of smart technologies in city planning and management becomes crucial, necessitating more sophisticated evaluation methodologies. These technologies offer promising solutions to urban challenges by improving efficiency, economic growth, and citizen engagement. This research addresses this gap by proposing a novel framework that combines Interval Valued Neutrosophic Sets (IVNS) with the EDAS Method, specifically designed to handle the complexities and uncertainties inherent in developing country contexts.</div><div>The study extensively reviews existing literature and methodologies applied in similar contexts, identifying key limitations in current approaches and building a robust framework that incorporates both new and established criteria. Through the systematic application of IVNS-EDAS methodology across multiple urban environments, this study develops a comprehensive classification system that accounts for both quantitative metrics and qualitative assessments of smart city capabilities. The results showcase a dynamic classification framework that effectively handles data uncertainty while providing clear, actionable insights for urban planners and policymakers. The paper concludes by validating the effectiveness of the proposed approach through a detailed computational study involving diverse stakeholders, confirming its applicability and utility in refining smart city strategies globally, particularly in developing country contexts where data reliability and completeness may be challenging.</div><div>The study provides specific policy guidelines for each city classification, offering policymakers a structured framework for resource allocation and strategic planning, ranging from foundational infrastructure development in emerging cities to advanced technology integration in metropolitan areas.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101936"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jestch.2024.101933
Ahmed Fouly, Hassan Alshehri, Ibrahim A. Alnaser, El-Sayed M. Sherif
Titanium alloys are poised to become increasingly prevalent as implant materials in medical applications. When compared to other implant materials, Ti alloys are considered superior in terms of corrosion resistance, specific strength and biocompatibility. As such, there is a growing interest in further exploring the properties of titanium alloys in the field of implants, orthopedic, and dental prostheses. This paper presents a comprehensive investigation into the development and characterization of Ti alloys for biomedical applications. The study focuses on the incorporation of various alloying elements, including Zr, Sn, Mo, and Ta, to enhance the tribo-mechanical performance of the alloys. The impact of varying Ta and Mo content on the performance of Ti alloys was investigated, while maintaining constant levels of Zr and Sn. The fabrication process involves advanced sintering techniques, and the resulting alloys are evaluated for their density, mechanical characteristics, and wear behavior. The load-carrying capacity of the alloys in a realistic scenario, a hip joint, was assessed by employing a finite element analysis. The results demonstrate that the addition of Ta improves the mechanical properties and wear resistance of the alloys, while reducing friction coefficients. Although Ta markedly improves mechanical strength and wear resistance, Mo exhibited a contrary impact. The SEM analysis of the tested surfaces demonstrated that the addition of Ta had a good impact on the wear mechanism.
{"title":"Exploring the tribo-mechanical performance of Ti-Mo-Zr-Ta-Sn alloys with a focus on their suitability for biomedical use","authors":"Ahmed Fouly, Hassan Alshehri, Ibrahim A. Alnaser, El-Sayed M. Sherif","doi":"10.1016/j.jestch.2024.101933","DOIUrl":"10.1016/j.jestch.2024.101933","url":null,"abstract":"<div><div>Titanium alloys are poised to become increasingly prevalent as implant materials in medical applications. When compared to other implant materials, Ti alloys are considered superior in terms of corrosion resistance, specific strength and biocompatibility. As such, there is a growing interest in further exploring the properties of titanium alloys in the field of implants, orthopedic, and dental prostheses. This paper presents a comprehensive investigation into the development and characterization of Ti alloys for biomedical applications. The study focuses on the incorporation of various alloying elements, including Zr, Sn, Mo, and Ta, to enhance the tribo-mechanical performance of the alloys. The impact of varying Ta and Mo content on the performance of Ti alloys was investigated, while maintaining constant levels of Zr and Sn. The fabrication process involves advanced sintering techniques, and the resulting alloys are evaluated for their density, mechanical characteristics, and wear behavior. The load-carrying capacity of the alloys in a realistic scenario, a hip joint, was assessed by employing a finite element analysis. The results demonstrate that the addition of Ta improves the mechanical properties and wear resistance of the alloys, while reducing friction coefficients. Although Ta markedly improves mechanical strength and wear resistance, Mo exhibited a contrary impact. The SEM analysis of the tested surfaces demonstrated that the addition of Ta had a good impact on the wear mechanism.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101933"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image watermarking is one of techniques that can be used to protect and recover from the altered images. Tamper detection in semi-fragile still does not achieve high accuracy for tamper localization, especially in malicious attacks. This study proposes two-phase tamper detection in semi-fragile image watermarking using two-level Integer Wavelet Transform (IWT). The study proposes two-phases of tamper detection to achieve a high level of accuracy in the tamper localization. The initial phase will check four segments to determine the tampered bit or not. A tampered segment is identified if it contains at least one tampered bit. The second phase will be performed if the first phase has no tampered bit. The second phase checked each segment to determine whether it was tampered with or not. This study also used Normalized Hamming Similarity (NHS) to classify malicious and incidental attacks. The proposed scheme performed two-level integer wavelets transform to obtain the LL, LH, HL, and HH sub-bands. The authentication bits of LL are embedded into the LH and HL sub-bands to generate a watermarked image. The LH and HL are compared using XOR bitwise with authentication bit to localize the tamper detection. The experimental results show that the proposed scheme achieved high quality of the recovered images with an average PSNR score of 44.1864 dB, wPSNR score of 46.2218 dB and SSIM score of 0.9945. The proposed method produced high accuracy of tamper detection of about 98.33 % under object manipulation with the tampering rate of about 12.1643 %.
{"title":"TDSF: Two-phase tamper detection in semi-fragile watermarking using two-level integer wavelet transform","authors":"Agit Amrullah , Ferda Ernawan , Anis Farihan Mat Raffei , Liew Siau Chuin","doi":"10.1016/j.jestch.2024.101909","DOIUrl":"10.1016/j.jestch.2024.101909","url":null,"abstract":"<div><div>Image watermarking is one of techniques that can be used to protect and recover from the altered images. Tamper detection in semi-fragile still does not achieve high accuracy for tamper localization, especially in malicious attacks. This study proposes two-phase tamper detection in semi-fragile image watermarking using two-level Integer Wavelet Transform (IWT). The study proposes two-phases of tamper detection to achieve a high level of accuracy in the tamper localization. The initial phase will check four segments to determine the tampered bit or not. A tampered segment is identified if it contains at least one tampered bit. The second phase will be performed if the first phase has no tampered bit. The second phase checked each segment to determine whether it was tampered with or not. This study also used Normalized Hamming Similarity (NHS) to classify malicious and incidental attacks. The proposed scheme performed two-level integer wavelets transform to obtain the LL, LH, HL, and HH sub-bands. The authentication bits of LL are embedded into the LH and HL sub-bands to generate a watermarked image. The LH and HL are compared using XOR bitwise with authentication bit<!--> <!-->to localize the tamper detection. The experimental results show that the proposed scheme achieved high quality of the recovered images with an average PSNR score of 44.1864 dB, wPSNR score of 46.2218 dB and SSIM score of 0.9945. The proposed method produced high accuracy of tamper detection of about 98.33 % under object manipulation with the tampering rate of about 12.1643 %.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101909"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jestch.2024.101944
Xuehua Zhu , Juntao Ye , Ziruo Ren , Xinyu Liu
Uniform magnetic fields are commonly utilized in scientific and engineering domains for a variety of purposes, such as atomic magnetometers, nuclear magnetic resonance, and other magnetic tools. However, the conventional Helmholtz coils have limitations in generating the highly uniform magnetic fields required for larger devices. To tackle this challenge, a new four-coil Helmholtz configuration has been devised in this paper to produce extremely uniform magnetic fields. Through the utilization of an enhanced Wolf Pack Algorithm (WPA) for optimizing spatial parameters, the four-coil system notably enhances the effective coverage ratio (ECR) of the uniform magnetic field. Finite element simulations confirm that this configuration delivers superior magnetic field uniformity, the ratio of the uniform magnetic field space, known as the ECR, experienced an increase from 18.5495% to 34.3046% when the magnetic field change rate remained below 0.1%. The research underscores the enhanced adaptability and effectiveness of the improved WPA in addressing multi-dimensional optimization challenges, providing a swift and efficient method for attaining uniform magnetic fields. This progress supports applications reliant on uniform magnetic fields, such as geomagnetic navigation, sensor calibration, and magnetic guidance systems, opening up possibilities for future applications of intelligent optimization algorithms in intricate physical and engineering tasks.
{"title":"Design of high uniform magnetic field with four coils based on improved wolf pack algorithm","authors":"Xuehua Zhu , Juntao Ye , Ziruo Ren , Xinyu Liu","doi":"10.1016/j.jestch.2024.101944","DOIUrl":"10.1016/j.jestch.2024.101944","url":null,"abstract":"<div><div>Uniform magnetic fields are commonly utilized in scientific and engineering domains for a variety of purposes, such as atomic magnetometers, nuclear magnetic resonance, and other magnetic tools. However, the conventional Helmholtz coils have limitations in generating the highly uniform magnetic fields required for larger devices. To tackle this challenge, a new four-coil Helmholtz configuration has been devised in this paper to produce extremely uniform magnetic fields. Through the utilization of an enhanced Wolf Pack Algorithm (WPA) for optimizing spatial parameters, the four-coil system notably enhances the effective coverage ratio (ECR) of the uniform magnetic field. Finite element simulations confirm that this configuration delivers superior magnetic field uniformity, the ratio of the uniform magnetic field space, known as the ECR, experienced an increase from 18.5495% to 34.3046% when the magnetic field change rate remained below 0.1%. The research underscores the enhanced adaptability and effectiveness of the improved WPA in addressing multi-dimensional optimization challenges, providing a swift and efficient method for attaining uniform magnetic fields. This progress supports applications reliant on uniform magnetic fields, such as geomagnetic navigation, sensor calibration, and magnetic guidance systems, opening up possibilities for future applications of intelligent optimization algorithms in intricate physical and engineering tasks.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101944"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jestch.2024.101939
Geunseo Park , Min Seok Hur , Tong Seop Kim
A stepped honeycomb labyrinth seal was optimized, and its leakage performance was predicted across various operating conditions using computational fluid dynamics (CFD) and artificial neural networks (ANNs). The process involved two stages: geometry optimization and performance prediction. In the first stage, incremental Latin hypercube sampling (i-LHS) was used to select geometric design points for training the ANN with CFD providing the leakage performance data. An ANN-based performance prediction metamodel was developed, and a genetic algorithm was applied to the metamodel to optimize seal geometry, achieving a 12.34% improvement in leakage performance over the reference seal. The second stage involved performance prediction across a wide range of operating conditions, including pressure ratios, rotational speeds, and clearances. Similar to geometry optimization, i-LHS was used to select the operating design points for training the ANN. A metamodel reflecting operating conditions was developed by evaluating the generalization and practicality of the ANN. The impact of pressure ratio, rotational speed, and clearance on the leakage performance was predicted. The leakage performance of the optimized seal was compared with the reference seal, showing improvements from 1.44% to 16.74%. This study revealed the effectiveness of ANN-based performance predictions for optimizing complex geometries, such as honeycomb seals, and developing models that account for various operating conditions.
{"title":"Optimal design and performance prediction of stepped honeycomb labyrinth seal using CFD and ANN","authors":"Geunseo Park , Min Seok Hur , Tong Seop Kim","doi":"10.1016/j.jestch.2024.101939","DOIUrl":"10.1016/j.jestch.2024.101939","url":null,"abstract":"<div><div>A stepped honeycomb labyrinth seal was optimized, and its leakage performance was predicted across various operating conditions using computational fluid dynamics (CFD) and artificial neural networks (ANNs). The process involved two stages: geometry optimization and performance prediction. In the first stage, incremental Latin hypercube sampling (i-LHS) was used to select geometric design points for training the ANN with CFD providing the leakage performance data. An ANN-based performance prediction metamodel was developed, and a genetic algorithm was applied to the metamodel to optimize seal geometry, achieving a 12.34% improvement in leakage performance over the reference seal. The second stage involved performance prediction across a wide range of operating conditions, including pressure ratios, rotational speeds, and clearances. Similar to geometry optimization, i-LHS was used to select the operating design points for training the ANN. A metamodel reflecting operating conditions was developed by evaluating the generalization and practicality of the ANN. The impact of pressure ratio, rotational speed, and clearance on the leakage performance was predicted. The leakage performance of the optimized seal was compared with the reference seal, showing improvements from 1.44% to 16.74%. This study revealed the effectiveness of ANN-based performance predictions for optimizing complex geometries, such as honeycomb seals, and developing models that account for various operating conditions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101939"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/S2215-0986(24)00313-6
{"title":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S2215-0986(24)00313-6","DOIUrl":"10.1016/S2215-0986(24)00313-6","url":null,"abstract":"","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"60 ","pages":"Article 101927"},"PeriodicalIF":5.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jestch.2024.101913
Xu Liu, Junwu Zhu
Smart contracts, being security-critical code, facilitate consensus among players and ensure secure and accurate value transfer, and formal verification is necessary to guarantee functional correctness of contracts. Game theory serves as one of the tools in formal verification by assessing whether the outcomes of contract executions meet the expected goals. While most studies employing game theory to verify smart contract functionality assume rational players, in practice, players may invoke and deploy smart contracts involving irrational behavior, casting doubt on the correctness of verification results. The aim of this study is to propose an alternative game model to verify smart contract functionality in dynamic player interactions where irrational behavior is involved. Specifically, a belief-based smart contract execution game (BSC-game) model was introduced, utilizing belief – the probability that a player believes in the irrationality of others – to capture how the irrational behavior of others affects a player’s contract execution decisions. Reasonable economic incentives were introduced to encourage honest behavior of players. Moreover, a computationally feasible method was designed to update players’ beliefs in large-scale dynamic smart contract executions. Theoretical analysis discloses the existence of equilibrium in the BSC-game, as well as the conditions for the number of faulty players within the system’s fault tolerance. We conducted the simulation experiments, and verified the business-oriented smart contract written in G language by the BSC-game model. The results further indicate that although players’ beliefs impact their decisions to execute contracts, reasonable economic incentives can motivate players to execute contracts honestly. This ensures that smart contract functionality aligns with expected goals, showing that the BSC-game model can verify and guarantee the correctness of contract functions. This new approach significantly contributes to bolstering smart contract security and credibility, positively influencing blockchain stability.
{"title":"Belief game: Verifying smart contract functionality in player dynamic interactions","authors":"Xu Liu, Junwu Zhu","doi":"10.1016/j.jestch.2024.101913","DOIUrl":"10.1016/j.jestch.2024.101913","url":null,"abstract":"<div><div>Smart contracts, being security-critical code, facilitate consensus among players and ensure secure and accurate value transfer, and formal verification is necessary to guarantee functional correctness of contracts. Game theory serves as one of the tools in formal verification by assessing whether the outcomes of contract executions meet the expected goals. While most studies employing game theory to verify smart contract functionality assume rational players, in practice, players may invoke and deploy smart contracts involving irrational behavior, casting doubt on the correctness of verification results. The aim of this study is to propose an alternative game model to verify smart contract functionality in dynamic player interactions where irrational behavior is involved. Specifically, a belief-based smart contract execution game (BSC-game) model was introduced, utilizing belief – the probability that a player believes in the irrationality of others – to capture how the irrational behavior of others affects a player’s contract execution decisions. Reasonable economic incentives were introduced to encourage honest behavior of players. Moreover, a computationally feasible method was designed to update players’ beliefs in large-scale dynamic smart contract executions. Theoretical analysis discloses the existence of equilibrium in the BSC-game, as well as the conditions for the number of faulty players within the system’s fault tolerance. We conducted the simulation experiments, and verified the business-oriented smart contract written in G language by the BSC-game model. The results further indicate that although players’ beliefs impact their decisions to execute contracts, reasonable economic incentives can motivate players to execute contracts honestly. This ensures that smart contract functionality aligns with expected goals, showing that the BSC-game model can verify and guarantee the correctness of contract functions. This new approach significantly contributes to bolstering smart contract security and credibility, positively influencing blockchain stability.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"60 ","pages":"Article 101913"},"PeriodicalIF":5.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-01DOI: 10.1016/j.jestch.2024.101860
Hisham Alghamdi , Chika Maduabuchi , Abdullah Albaker , Ibrahim Alatawi , Theyab R. Alsenani , Ahmed S. Alsafran , Abdulaziz Almalaq , Mohammed AlAqil , Mostafa A.H. Abdelmohimen , Mohammad Alkhedher
{"title":"Retraction notice to “A prediction model for the performance of solar photovoltaic-thermoelectric systems utilizing various semiconductors via optimal surrogate machine learning methods” [Eng. Sci. Technol. Int. J. 40 (2023) 101363]","authors":"Hisham Alghamdi , Chika Maduabuchi , Abdullah Albaker , Ibrahim Alatawi , Theyab R. Alsenani , Ahmed S. Alsafran , Abdulaziz Almalaq , Mohammed AlAqil , Mostafa A.H. Abdelmohimen , Mohammad Alkhedher","doi":"10.1016/j.jestch.2024.101860","DOIUrl":"10.1016/j.jestch.2024.101860","url":null,"abstract":"","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"60 ","pages":"Article 101860"},"PeriodicalIF":5.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-30DOI: 10.1016/j.jestch.2024.101889
Ruxue Bai , Jinsong Li , Jinsong Liu , Yuetao Shi , Suoying He , Wei Wei
Precisely forecasting output of solar photovoltaics is crucial for (i) effective solar power management, (ii) integration into the electrical grid, (iii) flexible allocation of power resources. While deep learning algorithms have shown promise in energy applications, single algorithms often struggle with unstable predictions and limited generalizability for predicting photovoltaic (PV) output. This study introduces an innovative hybrid model (HWGC-WPD-LSTM) that integrates an improved similar day algorithm (WGC: weighted grey correlation analysis and cosine similarity), Wavelet Packet Decomposition (WPD), and Long Short-Term Memory neural network (LSTM) for predicting day-ahead power output. The model suggests an approach to identifying similar days by integrating weighted GRA with cosine similarity. It then decomposes power sequences employing WPD to capture various frequency characteristics. Four independent LSTM networks are then applied to these sub-sequences to forecast output, which are then reconstructed to derive the ultimate forecast outcome for solar photovoltaics. The evaluation of the hybrid model is conducted based on data gathered from actual generating station in Shandong Province, China. Then it is compared against other models utilizing similar day selection methods and other hybrid HWGC-BP, HWGC-Elman, HWGC-SVM, HWGC-RF, and HWGC-LSTM models. This comparison is based on four performance metrics: Mean Absolute Error (MAE), Root Mean Square Error (RMSE), normalized Root Mean Square Error (NRMSE), and Mean Absolute Deviation (MAD). Results demonstrate that the HWGC-WPD-LSTM model offers enhanced precision and stability (MAE = 0.2168 MW, RMSE = 0.2996 MW, NRMSE = 6.78 %, MAD = 2.18 %) in day-ahead power generation predictions. This highlights the potency of the hybrid model in enhancing the forecasting capabilities for solar photovoltaics, which is crucial for the strategic enhancement of renewable energy resource exploitation in the context of modern power systems.
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