Pub Date : 2025-06-01DOI: 10.1016/j.vrih.2025.01.002
Harsh SHAH , Karan SHAH , Kushagra DARJI , Adit SHAH , Manan SHAH
The advanced driver assistance system (ADAS) primarily serves to assist drivers in monitoring the speed of the car and helps them make the right decision, which leads to fewer fatal accidents and ensures higher safety. In the artificial Intelligence domain, machine learning (ML) was developed to make inferences with a degree of accuracy similar to that of humans; however, enormous amounts of data are required. Machine learning enhances the accuracy of the decisions taken by ADAS, by evaluating all the data received from various vehicle sensors. This study summarizes all the critical algorithms used in ADAS technologies and presents the evolution of ADAS technology. Initially, ADAS technology is introduced, along with its evolution, to understand the objectives of developing this technology. Subsequently, the critical algorithms used in ADAS technology, which include face detection, head-pose estimation, gaze estimation, and link detection are discussed. A further discussion follows on the impact of ML on each algorithm in different environments, leading to increased accuracy at the expense of additional computing, to increase efficiency. The aim of this study was to evaluate all the methods with or without ML for each algorithm.
{"title":"Advanced driver assistance system (ADAS) and machine learning (ML): The dynamic duo revolutionizing the automotive industry","authors":"Harsh SHAH , Karan SHAH , Kushagra DARJI , Adit SHAH , Manan SHAH","doi":"10.1016/j.vrih.2025.01.002","DOIUrl":"10.1016/j.vrih.2025.01.002","url":null,"abstract":"<div><div>The advanced driver assistance system (ADAS) primarily serves to assist drivers in monitoring the speed of the car and helps them make the right decision, which leads to fewer fatal accidents and ensures higher safety. In the artificial Intelligence domain, machine learning (ML) was developed to make inferences with a degree of accuracy similar to that of humans; however, enormous amounts of data are required. Machine learning enhances the accuracy of the decisions taken by ADAS, by evaluating all the data received from various vehicle sensors. This study summarizes all the critical algorithms used in ADAS technologies and presents the evolution of ADAS technology. Initially, ADAS technology is introduced, along with its evolution, to understand the objectives of developing this technology. Subsequently, the critical algorithms used in ADAS technology, which include face detection, head-pose estimation, gaze estimation, and link detection are discussed. A further discussion follows on the impact of ML on each algorithm in different environments, leading to increased accuracy at the expense of additional computing, to increase efficiency. The aim of this study was to evaluate all the methods with or without ML for each algorithm.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 3","pages":"Pages 203-236"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.bcra.2024.100265
Zening Zhao , Jinsong Wang , Jiajia Wei
Public blockchain has outstanding performance in transaction privacy protection because of its anonymity. The data openness brings feasibility to transaction behavior analysis. At present, the transaction data of the public chain are huge, including complex trading objects and relationships. It is difficult to extract attributes and predict transaction behavior by traditional methods. To solve these problems, we extract transaction features to construct an Ethereum transaction heterogeneous information network (HIN) and propose a graph neural network (GNN)-based transaction prediction method for public blockchains in HINs, which can divide the network into subgraphs according to connectivity and increase the accuracy of the prediction results of transaction behavior. Experiments show that the execution time consumption of the proposed transaction subgraph division method is reduced by 70.61% on average compared with that of the search method. The accuracy of the proposed behavior prediction method also improves compared with that of the traditional random walk method, with an average accuracy of 83.82%.
{"title":"Graph neural network-based transaction link prediction method for public blockchain in heterogeneous information networks","authors":"Zening Zhao , Jinsong Wang , Jiajia Wei","doi":"10.1016/j.bcra.2024.100265","DOIUrl":"10.1016/j.bcra.2024.100265","url":null,"abstract":"<div><div>Public blockchain has outstanding performance in transaction privacy protection because of its anonymity. The data openness brings feasibility to transaction behavior analysis. At present, the transaction data of the public chain are huge, including complex trading objects and relationships. It is difficult to extract attributes and predict transaction behavior by traditional methods. To solve these problems, we extract transaction features to construct an Ethereum transaction heterogeneous information network (HIN) and propose a graph neural network (GNN)-based transaction prediction method for public blockchains in HINs, which can divide the network into subgraphs according to connectivity and increase the accuracy of the prediction results of transaction behavior. Experiments show that the execution time consumption of the proposed transaction subgraph division method is reduced by 70.61% on average compared with that of the search method. The accuracy of the proposed behavior prediction method also improves compared with that of the traditional random walk method, with an average accuracy of 83.82%.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100265"},"PeriodicalIF":6.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-28DOI: 10.1007/s43684-025-00098-w
Hua Wang
The field of human motion data capture and fusion has a broad range of potential applications and market opportunities. The capture of human motion data for wearable sensors is less costly and more convenient than other methods, but it also suffers from poor data capture accuracy and high latency. Consequently, in order to overcome the limitations of existing wearable sensors in data capture and fusion, the study initially constructed a model of the human joint and bone by combining the quaternion method and root bone human forward kinematics through mathematical modeling. Subsequently, the sensor data calibration was optimized, and the Madgwick algorithm was introduced to address the resulting issues. Finally, a novel human joint motion data capture and fusion model was proposed. The experimental results indicated that the maximum mean error and root mean square error of yaw angle of this new model were 1.21° and 1.17°, respectively. The mean error and root mean square error of pitch angle were maximum 1.24° and 1.19°, respectively. The maximum knee joint and elbow joint data capture errors were 3.8 and 6.1, respectively. The suggested approach, which offers a new path for technological advancement in this area, greatly enhances the precision and dependability of human motion capture, which has a broad variety of application possibilities.
{"title":"Human joint motion data capture and fusion based on wearable sensors","authors":"Hua Wang","doi":"10.1007/s43684-025-00098-w","DOIUrl":"10.1007/s43684-025-00098-w","url":null,"abstract":"<div><p>The field of human motion data capture and fusion has a broad range of potential applications and market opportunities. The capture of human motion data for wearable sensors is less costly and more convenient than other methods, but it also suffers from poor data capture accuracy and high latency. Consequently, in order to overcome the limitations of existing wearable sensors in data capture and fusion, the study initially constructed a model of the human joint and bone by combining the quaternion method and root bone human forward kinematics through mathematical modeling. Subsequently, the sensor data calibration was optimized, and the Madgwick algorithm was introduced to address the resulting issues. Finally, a novel human joint motion data capture and fusion model was proposed. The experimental results indicated that the maximum mean error and root mean square error of yaw angle of this new model were 1.21° and 1.17°, respectively. The mean error and root mean square error of pitch angle were maximum 1.24° and 1.19°, respectively. The maximum knee joint and elbow joint data capture errors were 3.8 and 6.1, respectively. The suggested approach, which offers a new path for technological advancement in this area, greatly enhances the precision and dependability of human motion capture, which has a broad variety of application possibilities.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00098-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145171149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-21DOI: 10.1016/j.bcra.2025.100311
Tianqi Zhou , Kai Zhao , Wenying Zheng
Blockchain, as a rapidly developing technology nowadays, involves multi-party collaboration scenarios. However, as the number of users grows, security issues in blockchain systems also increase, driving the need for features such as collusion resistance and traceability. To meet the needs of multi-party collaboration on the blockchain, we propose a blockchain-based collusion-resistant and a traceable broadcast encryption scheme. On the one hand, the traitor tracing scheme is adopted to effectively enable accountability for malicious users. On the other hand, the SM2 public key encryption algorithm is deployed to satisfy high security requirements with relatively low computational costs. Security analysis demonstrates that the proposed scheme has the same level of security as the SM2 algorithm. Performance evaluation shows that the proposed scheme is superior to the relevant schemes and maintains functionalities such as collusion-resistant and traitor tracing.
{"title":"A blockchain-based collusion-resistant and traceable broadcast encryption scheme","authors":"Tianqi Zhou , Kai Zhao , Wenying Zheng","doi":"10.1016/j.bcra.2025.100311","DOIUrl":"10.1016/j.bcra.2025.100311","url":null,"abstract":"<div><div>Blockchain, as a rapidly developing technology nowadays, involves multi-party collaboration scenarios. However, as the number of users grows, security issues in blockchain systems also increase, driving the need for features such as collusion resistance and traceability. To meet the needs of multi-party collaboration on the blockchain, we propose a blockchain-based collusion-resistant and a traceable broadcast encryption scheme. On the one hand, the traitor tracing scheme is adopted to effectively enable accountability for malicious users. On the other hand, the SM2 public key encryption algorithm is deployed to satisfy high security requirements with relatively low computational costs. Security analysis demonstrates that the proposed scheme has the same level of security as the SM2 algorithm. Performance evaluation shows that the proposed scheme is superior to the relevant schemes and maintains functionalities such as collusion-resistant and traitor tracing.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"7 1","pages":"Article 100311"},"PeriodicalIF":5.6,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-19DOI: 10.1016/j.bcra.2025.100299
Samuel Akwasi Frimpong , Mu Han , Emmanuel Kwame Effah , Joseph Kwame Adjei , Isaac Hanson , Percy Brown
{"title":"Erratum to “A deep decentralized privacy-preservation framework for online social networks”","authors":"Samuel Akwasi Frimpong , Mu Han , Emmanuel Kwame Effah , Joseph Kwame Adjei , Isaac Hanson , Percy Brown","doi":"10.1016/j.bcra.2025.100299","DOIUrl":"10.1016/j.bcra.2025.100299","url":null,"abstract":"","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100299"},"PeriodicalIF":6.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-12DOI: 10.1016/j.jobb.2025.04.001
Rawaa A. Abdul-Nabi , Ehssan Al-Bermany
Hybrid nanomaterials (HNMs) have become more interesting to researchers for various optoelectronic and biological applications. In response, this investigation focuses on the impact of loading ratios of (0, 1 %, 3 %, and 5 %) of HNMs from graphene oxide (GO) and silicon nitride (Si3N4). HNMs are utilized to reinforce blended polymers, including polyethylene oxide (PEO), carboxymethyl cellulose (CMC), and nano-polyaniline (PANI) to fabricate (PEO100K–CMC–PANI/GO–Si3N4) using the developed sol–gel-ultrasonic procedure. X-ray diffraction revealed semi-crystalline behavior among all samples, while Fourier transform infrared spectroscopy showed strong physical interfacial interactions among the sample components. Meanwhile, field emission scanning electron and transmission electron microscopies showed a fine dispersion and a homogeneous matrix with significant changes. The optical absorption behavior revealed continuous high absorption peaks at 200–280-nm wavelengths, which strongly impacts (GO–Si3N4). Increases in concentration also strongly impact (GO–Si3N4), which results in an improved optical energy gap for the allowed and forbidden transitions from 3.5 eV for the blended polymer to 3 and 2.9 eV by increasing the HNM content. The contributions of HNMs notably enhance the ability to reduce the zones of the bacteria, especially Escherichia coli, from 18 to 26 mm. In effect, HNMs with a concentration higher than 5 % assist in inhibiting the growth of lung cancer (A549) cells. As such, these NCs present good optical behavior for multi-applications, such as biosensors and biological and optoelectronic devices.
{"title":"Antibacterial and anticancer potentials of graphene-silicon nitride nanomaterials-enhanced polymer nanocomposites: advanced characterization and optical behavior insights","authors":"Rawaa A. Abdul-Nabi , Ehssan Al-Bermany","doi":"10.1016/j.jobb.2025.04.001","DOIUrl":"10.1016/j.jobb.2025.04.001","url":null,"abstract":"<div><div>Hybrid nanomaterials (HNMs) have become more interesting to researchers for various optoelectronic and biological applications. In response, this investigation focuses on the impact of loading ratios of (0, 1 %, 3 %, and 5 %) of HNMs from graphene oxide (GO) and silicon nitride (Si<sub>3</sub>N<sub>4</sub>). HNMs are utilized to reinforce blended polymers, including polyethylene oxide (PEO), carboxymethyl cellulose (CMC), and nano-polyaniline (PANI) to fabricate (PEO<sub>100K</sub>–CMC–PANI/GO–Si<sub>3</sub>N<sub>4</sub>) using the developed sol–gel-ultrasonic procedure. X-ray diffraction revealed semi-crystalline behavior among all samples, while Fourier transform infrared spectroscopy showed strong physical interfacial interactions among the sample components. Meanwhile, field emission scanning electron and transmission electron microscopies showed a fine dispersion and a homogeneous matrix with significant changes. The optical absorption behavior revealed continuous high absorption peaks at 200–280-nm wavelengths, which strongly impacts (GO–Si<sub>3</sub>N<sub>4</sub>). Increases in concentration also strongly impact (GO–Si<sub>3</sub>N<sub>4</sub>), which results in an improved optical energy gap for the allowed and forbidden transitions from 3.5 eV for the blended polymer to 3 and 2.9 eV by increasing the HNM content. The contributions of HNMs notably enhance the ability to reduce the zones of the bacteria, especially <em>Escherichia coli</em>, from 18 to 26 mm. In effect, HNMs with a concentration higher than 5 % assist in inhibiting the growth of lung cancer (A549) cells. As such, these NCs present good optical behavior for multi-applications, such as biosensors and biological and optoelectronic devices.</div></div>","PeriodicalId":52875,"journal":{"name":"Journal of Biosafety and Biosecurity","volume":"7 2","pages":"Pages 55-68"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-30DOI: 10.1016/j.bcra.2025.100300
Hua Wang , Jinjing Liu , Jian Zhao
Financial derivatives are widely recognized for their effectiveness in managing interest rate risk, demonstrating the principle of comparative advantage in finance. However, traditional financial derivative transactions are often complex and can expose participants to market and credit risks. To mitigate these risks, reduce transaction costs, and enhance liquidity, this paper proposes a blockchain-based matching mechanism for financial derivatives that uses smart contracts for decentralized counterparty matching and settlement. Smart contracts facilitate secure data sharing among participants, ensuring the integrity and immutability of transaction data. We design a transaction pool mechanism-based smart contracts for counterparty matching and automatic settlement of financial derivatives involving real fiat currencies and introduce an efficient peer-to-peer counterparty matching method, where the entire trading process is conducted on a decentralized blockchain, ensuring greater security and transparency. A prototype implementation based on Ethereum smart contracts validates the effectiveness of our proposed model, demonstrating its potential to streamline and secure financial derivative transactions.
{"title":"Blockchain smart contracts for decentralized matching of counterparties and automatic settlement of financial derivatives","authors":"Hua Wang , Jinjing Liu , Jian Zhao","doi":"10.1016/j.bcra.2025.100300","DOIUrl":"10.1016/j.bcra.2025.100300","url":null,"abstract":"<div><div>Financial derivatives are widely recognized for their effectiveness in managing interest rate risk, demonstrating the principle of comparative advantage in finance. However, traditional financial derivative transactions are often complex and can expose participants to market and credit risks. To mitigate these risks, reduce transaction costs, and enhance liquidity, this paper proposes a blockchain-based matching mechanism for financial derivatives that uses smart contracts for decentralized counterparty matching and settlement. Smart contracts facilitate secure data sharing among participants, ensuring the integrity and immutability of transaction data. We design a transaction pool mechanism-based smart contracts for counterparty matching and automatic settlement of financial derivatives involving real fiat currencies and introduce an efficient peer-to-peer counterparty matching method, where the entire trading process is conducted on a decentralized blockchain, ensuring greater security and transparency. A prototype implementation based on Ethereum smart contracts validates the effectiveness of our proposed model, demonstrating its potential to streamline and secure financial derivative transactions.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100300"},"PeriodicalIF":5.6,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-28DOI: 10.1007/s43684-025-00094-0
Fengnian Liu, Ding Wang, Junya Tang, Lei Wang
Water pipeline leaks pose significant risks to urban infrastructure, leading to water wastage and potential structural damage. Existing leak detection methods often face challenges, such as heavily relying on the manual selection of frequency bands or complex feature extraction, which can be both labour-intensive and less effective. To address these limitations, this paper introduces a Frequency-Informed Transformer model, which integrates the Fast Fourier Transform and self-attention mechanisms to enhance water pipe leak detection accuracy. Experimental results show that FiT achieves 99.9% accuracy in leak detection and 98.7% in leak type classification, surpassing other models in both accuracy and processing speed, with an efficient response time of 0.25 seconds. By significantly simplifying key features and frequency band selection and improving accuracy and response time, the proposed method offers a potential solution for real-time water leak detection, enabling timely interventions and more effective pipeline safety management.
{"title":"Frequency-informed transformer for real-time water pipeline leak detection","authors":"Fengnian Liu, Ding Wang, Junya Tang, Lei Wang","doi":"10.1007/s43684-025-00094-0","DOIUrl":"10.1007/s43684-025-00094-0","url":null,"abstract":"<div><p>Water pipeline leaks pose significant risks to urban infrastructure, leading to water wastage and potential structural damage. Existing leak detection methods often face challenges, such as heavily relying on the manual selection of frequency bands or complex feature extraction, which can be both labour-intensive and less effective. To address these limitations, this paper introduces a Frequency-Informed Transformer model, which integrates the Fast Fourier Transform and self-attention mechanisms to enhance water pipe leak detection accuracy. Experimental results show that FiT achieves 99.9% accuracy in leak detection and 98.7% in leak type classification, surpassing other models in both accuracy and processing speed, with an efficient response time of 0.25 seconds. By significantly simplifying key features and frequency band selection and improving accuracy and response time, the proposed method offers a potential solution for real-time water leak detection, enabling timely interventions and more effective pipeline safety management.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00094-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-24DOI: 10.1016/j.bcra.2025.100294
Qingyuan Liu , Meng Wu , Jiachi Chen , Ting Chen , Xi Chen , Renkai Jiang , Yuqiao Yang , Zhangyan Lin , Yuanyao Cheng
With the rapid expansion of blockchain applications, smart contracts are becoming increasingly complex, making the automated detection of contract vulnerabilities more critical than ever. Large language models, due to their advanced code comprehensive ability, are considered to have the potential to undertake the task of automated software vulnerability discovery. Although there have been empirical studies on ChatGPT's automated discovery of contract vulnerabilities, the current empirical research has not addressed how well ChatGPT can detect logical vulnerabilities in smart contracts or whether ChatGPT's detection performance for logical vulnerabilities can be improved. To fill this gap, this study collected and organized seven types of logical vulnerability source codes from 6165 real smart contract audit reports and three datasets, such as Web3Bugs, and used this database to validate ChatGPT's detection capability for logical vulnerabilities. To improve ChatGPT's accuracy in detecting logical vulnerabilities, we fine-tuned ChatGPT with a dataset marked with a specific method, achieving an average accuracy rate of 95% for single vulnerability detection per training session. We improved the original marking method to increase further the number of vulnerabilities that a single model can detect. We used a specific completion marking format, ultimately enabling ChatGPT to detect various logical vulnerabilities. In terms of enhancing model scalability, we found a special training set marking method that allows for the addition of detectable vulnerability types through secondary training.
{"title":"Exploring the potential of ChatGPT in detecting logical vulnerabilities in smart contracts","authors":"Qingyuan Liu , Meng Wu , Jiachi Chen , Ting Chen , Xi Chen , Renkai Jiang , Yuqiao Yang , Zhangyan Lin , Yuanyao Cheng","doi":"10.1016/j.bcra.2025.100294","DOIUrl":"10.1016/j.bcra.2025.100294","url":null,"abstract":"<div><div>With the rapid expansion of blockchain applications, smart contracts are becoming increasingly complex, making the automated detection of contract vulnerabilities more critical than ever. Large language models, due to their advanced code comprehensive ability, are considered to have the potential to undertake the task of automated software vulnerability discovery. Although there have been empirical studies on ChatGPT's automated discovery of contract vulnerabilities, the current empirical research has not addressed how well ChatGPT can detect logical vulnerabilities in smart contracts or whether ChatGPT's detection performance for logical vulnerabilities can be improved. To fill this gap, this study collected and organized seven types of logical vulnerability source codes from 6165 real smart contract audit reports and three datasets, such as Web3Bugs, and used this database to validate ChatGPT's detection capability for logical vulnerabilities. To improve ChatGPT's accuracy in detecting logical vulnerabilities, we fine-tuned ChatGPT with a dataset marked with a specific method, achieving an average accuracy rate of 95% for single vulnerability detection per training session. We improved the original marking method to increase further the number of vulnerabilities that a single model can detect. We used a specific completion marking format, ultimately enabling ChatGPT to detect various logical vulnerabilities. In terms of enhancing model scalability, we found a special training set marking method that allows for the addition of detectable vulnerability types through secondary training.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100294"},"PeriodicalIF":5.6,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145371140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-23DOI: 10.1007/s43684-025-00097-x
G. Rigatos, M. Abbaszadeh, K. Busawon, P. Siano, M. Al Numay, G. Cuccurullo, F. Zouari
Transportation of heavy loads is often performed by multi-axle multi-steered heavy duty vehicles In this article a novel nonlinear optimal control method is applied to the kinematic model of the five-axle and three-steering coupled vehicle system. First, it is proven that the dynamic model of this articulated multi-vehicle system is differentially flat. Next. the state-space model of the five-axle and three-steering vehicle system undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization is based on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the five-axle and three-steering vehicle system a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands for the solution of the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed nonlinear optimal control approach achieves fast and accurate tracking of setpoints under moderate variations of the control inputs and minimal dispersion of energy by the propulsion and steering system of the five-axle and three-steering vehicle system.
{"title":"Nonlinear optimal control for the five-axle and three-steering coupled-vehicle system","authors":"G. Rigatos, M. Abbaszadeh, K. Busawon, P. Siano, M. Al Numay, G. Cuccurullo, F. Zouari","doi":"10.1007/s43684-025-00097-x","DOIUrl":"10.1007/s43684-025-00097-x","url":null,"abstract":"<div><p>Transportation of heavy loads is often performed by multi-axle multi-steered heavy duty vehicles In this article a novel nonlinear optimal control method is applied to the kinematic model of the five-axle and three-steering coupled vehicle system. First, it is proven that the dynamic model of this articulated multi-vehicle system is differentially flat. Next. the state-space model of the five-axle and three-steering vehicle system undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization is based on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the five-axle and three-steering vehicle system a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands for the solution of the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed nonlinear optimal control approach achieves fast and accurate tracking of setpoints under moderate variations of the control inputs and minimal dispersion of energy by the propulsion and steering system of the five-axle and three-steering vehicle system.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00097-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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