Pub Date : 2023-05-29DOI: 10.37256/rrcs.2320232638
S. Pandey, Buddha Singh
Due to the advancement of electronics engineering technology, many types of sensors have been developed. But sensors are still battery-powered devices. Once the battery is dead, the sensors are of no use. So, energy optimization in wireless sensor networks is still a hot topic among researchers. This paper proposed a novel clustering method that uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm to select the Cluster Heads (CHs). TOPSIS is a Multi-Attribute Decision Making (MADM) based model which uses several conflicting attributes to select the best alternative. We have compared our proposed model with two other comparable models to evaluate the performance of our proposed model. The result shows that our proposed model performs better than other models.
{"title":"TOPSIS-based Optimal Cluster Head Selection for Wireless Sensor Network","authors":"S. Pandey, Buddha Singh","doi":"10.37256/rrcs.2320232638","DOIUrl":"https://doi.org/10.37256/rrcs.2320232638","url":null,"abstract":"Due to the advancement of electronics engineering technology, many types of sensors have been developed. But sensors are still battery-powered devices. Once the battery is dead, the sensors are of no use. So, energy optimization in wireless sensor networks is still a hot topic among researchers. This paper proposed a novel clustering method that uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm to select the Cluster Heads (CHs). TOPSIS is a Multi-Attribute Decision Making (MADM) based model which uses several conflicting attributes to select the best alternative. We have compared our proposed model with two other comparable models to evaluate the performance of our proposed model. The result shows that our proposed model performs better than other models.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"350 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134204010","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 : 2023-05-22DOI: 10.37256/rrcs.2320232645
D. Prakash, G. Jeyakumar
The optimization of electric vehicles (EVs) utilizing meta-heuristics has arisen as the way to propel state-of-the-art advancements, making ready for boundless reception, and reforming the flow transportation framework while lessening ozone-depleting substance discharges. The two factors that keep on obstructing the improvement of EVs are reach and cost. This study digs profoundly into the five significant EV enhancement regions: plan advancement, energy the board, ideal control, upgraded charging and releasing, and steering. Methods for single-objective and multi-objective enhancement are examined and talked about. Following a broad survey of the latest works in every space, an investigation of numerical demonstrating, the development of goal capabilities, time management for charging, and limitations are introduced. What’s more, the different scientific, regular, and nature-roused advancement calculations (swarm-optimization, transformative, and recent meta-heuristics) are arranged in view of their fame. Their merits and detriments are then analyzed, similar to the different requirements for taking care of procedures. This survey of the high-level and redesigned variants of these meta-heuristics likewise gives a precise reference to EV streamlining utilizing wise calculations.
{"title":"A Review of Problem Variants and Approaches for Electric Vehicle Charging and Location Identification","authors":"D. Prakash, G. Jeyakumar","doi":"10.37256/rrcs.2320232645","DOIUrl":"https://doi.org/10.37256/rrcs.2320232645","url":null,"abstract":"The optimization of electric vehicles (EVs) utilizing meta-heuristics has arisen as the way to propel state-of-the-art advancements, making ready for boundless reception, and reforming the flow transportation framework while lessening ozone-depleting substance discharges. The two factors that keep on obstructing the improvement of EVs are reach and cost. This study digs profoundly into the five significant EV enhancement regions: plan advancement, energy the board, ideal control, upgraded charging and releasing, and steering. Methods for single-objective and multi-objective enhancement are examined and talked about. Following a broad survey of the latest works in every space, an investigation of numerical demonstrating, the development of goal capabilities, time management for charging, and limitations are introduced. What’s more, the different scientific, regular, and nature-roused advancement calculations (swarm-optimization, transformative, and recent meta-heuristics) are arranged in view of their fame. Their merits and detriments are then analyzed, similar to the different requirements for taking care of procedures. This survey of the high-level and redesigned variants of these meta-heuristics likewise gives a precise reference to EV streamlining utilizing wise calculations.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124597032","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 : 2023-05-19DOI: 10.37256/rrcs.2320232632
Satyajeet R. Shinge, Urmila Shrawankar
Companies across industries increasingly depend upon cloud computing to manage their Industrial Internet of Things (IIoT) technology. Machines are connected over a network in the IIoT. Cloud computing plays an essential role by connecting people, devices, work processes, and buildings to deliver cloud services in industries. But cloud computing faces a problem with task scheduling, high latency delay, and memory management, affecting the overall cost of industries using cloud services. A major concern in the cloud computing field is task scheduling which is essential for achieving cost-effective execution and improving resource usage. It refers to assigning available resources to user tasks. This problem can be solved effectively by improving task execution and increasing the use of resources. The waiting time between a client’s sent request and a cloud service provider to give a response, known as latency, is another issue in cloud environments. In cloud computing, this delay can be significantly higher. As a result, users of various cloud services may incur increased expenses due to this delay. Finally, among the most significant topics in cloud computing is efficient memory management, which handles integrated data and optimizes memory management algorithms. This paper proposes a cloud model for IIoT, which provides task scheduling, helps reduce latency, and optimizes memory management. This proposed model helps to reduce the cost of using cloud computing in IIoT.
{"title":"Cloud-based Cost Effective IIoT Model Towards Industry 5.0","authors":"Satyajeet R. Shinge, Urmila Shrawankar","doi":"10.37256/rrcs.2320232632","DOIUrl":"https://doi.org/10.37256/rrcs.2320232632","url":null,"abstract":"Companies across industries increasingly depend upon cloud computing to manage their Industrial Internet of Things (IIoT) technology. Machines are connected over a network in the IIoT. Cloud computing plays an essential role by connecting people, devices, work processes, and buildings to deliver cloud services in industries. But cloud computing faces a problem with task scheduling, high latency delay, and memory management, affecting the overall cost of industries using cloud services. A major concern in the cloud computing field is task scheduling which is essential for achieving cost-effective execution and improving resource usage. It refers to assigning available resources to user tasks. This problem can be solved effectively by improving task execution and increasing the use of resources. The waiting time between a client’s sent request and a cloud service provider to give a response, known as latency, is another issue in cloud environments. In cloud computing, this delay can be significantly higher. As a result, users of various cloud services may incur increased expenses due to this delay. Finally, among the most significant topics in cloud computing is efficient memory management, which handles integrated data and optimizes memory management algorithms. This paper proposes a cloud model for IIoT, which provides task scheduling, helps reduce latency, and optimizes memory management. This proposed model helps to reduce the cost of using cloud computing in IIoT.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116059260","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 : 2023-05-18DOI: 10.37256/rrcs.2320232629
Swatej Patil, Mayur S. Patil, Kotadi Chinnaiah
The term "phishing" is often used to describe an attempt to obtain confidential data such as passwords or credit card details by impersonating a trustworthy source. In most cases, the term refers to attempts to trick users into providing sensitive information in response to a fraudulent email or web page. However, the term is also used to describe a broader category of online attacks to obtain sensitive information or to disrupt services or systems. Incorporating different machine learning and deep learning algorithms, including Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and random forest, the authors of this research presented a technique for identifying phishing websites. The data sets from PhishTank and the University of New Brunswick were used to train and test the learning models. The XGboost model was able to surpass most existing techniques by achieving a maximum accuracy of 86.8%. This technique can be used in modern web browsers like Google Chrome and Mozilla Firefox to accurately detect phishing websites.
{"title":"Machine Learning and Deep Learning for Phishing Page Detection","authors":"Swatej Patil, Mayur S. Patil, Kotadi Chinnaiah","doi":"10.37256/rrcs.2320232629","DOIUrl":"https://doi.org/10.37256/rrcs.2320232629","url":null,"abstract":"The term \"phishing\" is often used to describe an attempt to obtain confidential data such as passwords or credit card details by impersonating a trustworthy source. In most cases, the term refers to attempts to trick users into providing sensitive information in response to a fraudulent email or web page. However, the term is also used to describe a broader category of online attacks to obtain sensitive information or to disrupt services or systems. Incorporating different machine learning and deep learning algorithms, including Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and random forest, the authors of this research presented a technique for identifying phishing websites. The data sets from PhishTank and the University of New Brunswick were used to train and test the learning models. The XGboost model was able to surpass most existing techniques by achieving a maximum accuracy of 86.8%. This technique can be used in modern web browsers like Google Chrome and Mozilla Firefox to accurately detect phishing websites.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128654129","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 : 2023-05-15DOI: 10.37256/rrcs.2320232628
Shatakshi Kokate, Urmila Shrawankar
The Internet of Things (IoT) network generates a lot of data and cloud servers collect that data. The server then analyzes the collected data and based on the findings, provides appropriate intelligent services to users as a result. If there is any faulty data while the server analyzes the collected data, distorted results will be created. The data captured from IoT contains lots of heterogeneous as well as suspicious data, so cleaning, filtering, and clustering of it must be done before sending it to the server, otherwise it will unnecessarily create overhead on the server. The proposed system consists of a filtering and clustering mechanism for the data collected from IoT devices so that integrated data is transferred to the cloud server which will reduce its computational load. In the proposed system, the fog computing layer is used as an interface between IoT and cloud computing layer where data filtering and clustering take place to reduce network traffic and latency. The ultimate aim is to provide security for data transmission between IoT and the cloud.
{"title":"An Efficient Approach for Secured Data Transmission Between IoT and Cloud","authors":"Shatakshi Kokate, Urmila Shrawankar","doi":"10.37256/rrcs.2320232628","DOIUrl":"https://doi.org/10.37256/rrcs.2320232628","url":null,"abstract":"The Internet of Things (IoT) network generates a lot of data and cloud servers collect that data. The server then analyzes the collected data and based on the findings, provides appropriate intelligent services to users as a result. If there is any faulty data while the server analyzes the collected data, distorted results will be created. The data captured from IoT contains lots of heterogeneous as well as suspicious data, so cleaning, filtering, and clustering of it must be done before sending it to the server, otherwise it will unnecessarily create overhead on the server. The proposed system consists of a filtering and clustering mechanism for the data collected from IoT devices so that integrated data is transferred to the cloud server which will reduce its computational load. In the proposed system, the fog computing layer is used as an interface between IoT and cloud computing layer where data filtering and clustering take place to reduce network traffic and latency. The ultimate aim is to provide security for data transmission between IoT and the cloud.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133432952","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 : 2023-05-15DOI: 10.37256/rrcs.2320232627
V. B. Semwal, Yash Gupta
One of the most popular ways of representing any robotic model mathematically is through Denavit-Hartenberg (DH) parameter table. And the most common way of finding a forward kinematics solution to any robotic model is by finding its homogenous transformation matrix, which is obtained from the DH parameter table by a certain set of steps or algorithms. In this research work, we have tried solving this problem in just a single step by deep learning method and thus finding forward kinematics of almost any kind of manipulator. This research work shows not just this problem but many more such complex problems which require a certain set of steps or algorithms that can be solved by deep learning techniques in a single step. The results obtained are very close to accurate and show the ability of deep learning techniques for solving different kinds of such problems.
{"title":"Determining Homogenous Transformation Matrix from DH Parameter Table using Deep Learning Techniques","authors":"V. B. Semwal, Yash Gupta","doi":"10.37256/rrcs.2320232627","DOIUrl":"https://doi.org/10.37256/rrcs.2320232627","url":null,"abstract":"One of the most popular ways of representing any robotic model mathematically is through Denavit-Hartenberg (DH) parameter table. And the most common way of finding a forward kinematics solution to any robotic model is by finding its homogenous transformation matrix, which is obtained from the DH parameter table by a certain set of steps or algorithms. In this research work, we have tried solving this problem in just a single step by deep learning method and thus finding forward kinematics of almost any kind of manipulator. This research work shows not just this problem but many more such complex problems which require a certain set of steps or algorithms that can be solved by deep learning techniques in a single step. The results obtained are very close to accurate and show the ability of deep learning techniques for solving different kinds of such problems.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"1467 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124786442","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 : 2023-05-10DOI: 10.37256/rrcs.2320232635
S. Chaudhari, Archana Thakur, A. Rajan
In information technology (IT) security, defence in depth is considered the best practice. Protecting data at rest or in transit is a part of the defence in depth approach. Confidentiality, data integrity, authentication, and non-repudiation are four IT security paradigms that need to be achieved to protect data and enhance IT security. Every scientific organisation requires i) to maintain the confidentiality of information like novel research ideas, results, patents, indigenous developed techniques and designs, human resource personal data and remarks, etc. ii) to manage the integrity of Internet-based web resources, users' credentials, etc. and iii) to manage non-repudiation and integrity guarantee enabled implementation of various software systems. The Rivest-Shamir-Adleman (RSA) technique is used to achieve confidentiality of secret data during its storage and transmission over insecure channels. The elliptic curve cryptography (ECC) technique is used for key exchange with extremely constrained devices like wireless and wireless sensor networks. Data hashing is used for maintaining data integrity; digital certificates are employed to achieve non-repudiation. In order to enhance IT security, the application of these cryptographic algorithms has been studied in data security like workflow-based applications, video conferencing, Domain Name System (DNS), web security, and radio frequency identification (RFID) systems and presented in the paper. A novel scheme to ensure website integrity and to detect website attacks using time-stamped hash functions with timestamping is also demonstrated in the paper. The study revealed that symmetric key and asymmetric key algorithms provide confidentiality and authentication. Data integrity and authentication are achieved using digital signatures and message authentication codes. Non-repudiation is established with asymmetric key algorithms and digital signatures.
{"title":"Securing Digital Information Using Cryptography Techniques to Enhance IT Security","authors":"S. Chaudhari, Archana Thakur, A. Rajan","doi":"10.37256/rrcs.2320232635","DOIUrl":"https://doi.org/10.37256/rrcs.2320232635","url":null,"abstract":"In information technology (IT) security, defence in depth is considered the best practice. Protecting data at rest or in transit is a part of the defence in depth approach. Confidentiality, data integrity, authentication, and non-repudiation are four IT security paradigms that need to be achieved to protect data and enhance IT security. Every scientific organisation requires i) to maintain the confidentiality of information like novel research ideas, results, patents, indigenous developed techniques and designs, human resource personal data and remarks, etc. ii) to manage the integrity of Internet-based web resources, users' credentials, etc. and iii) to manage non-repudiation and integrity guarantee enabled implementation of various software systems. The Rivest-Shamir-Adleman (RSA) technique is used to achieve confidentiality of secret data during its storage and transmission over insecure channels. The elliptic curve cryptography (ECC) technique is used for key exchange with extremely constrained devices like wireless and wireless sensor networks. Data hashing is used for maintaining data integrity; digital certificates are employed to achieve non-repudiation. In order to enhance IT security, the application of these cryptographic algorithms has been studied in data security like workflow-based applications, video conferencing, Domain Name System (DNS), web security, and radio frequency identification (RFID) systems and presented in the paper. A novel scheme to ensure website integrity and to detect website attacks using time-stamped hash functions with timestamping is also demonstrated in the paper. The study revealed that symmetric key and asymmetric key algorithms provide confidentiality and authentication. Data integrity and authentication are achieved using digital signatures and message authentication codes. Non-repudiation is established with asymmetric key algorithms and digital signatures.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126608609","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 : 2023-05-02DOI: 10.37256/rrcs.2320232642
Agash Uthayasuriyan, Hema Chandran G, Kavvin Uv, Sabbineni Hema Mahitha, J. G
Machine Learning (ML) and Evolutionary Computing (EC) are the two most popular computational methodologies in computer science to solve learning and optimization problems around us, respectively. It is of research interest in the literature, for exploring these two methodologies and to formulate algorithmic frameworks with 'EA for ML' and 'ML for EA' where EA stands for Evolutionary Algorithm. The objective of this paper is on exploring this dimension of research. The Traveling Salesman Problem (TSP) is one of the NP-hard (nondeterministic polynomial time hard) problems in combinatorial optimization problems. The solution for a TSP is the shortest path covering all the nodes in a given city. This paper compares two algorithms, "Genetic Algorithm (GA)" of the EC domain and "Epsilon-Greedy Q-Learning Algorithm (EQLA)" of the ML domain on solving TSP. The detailed design methodology involved in both these algorithms is discussed in this paper. The experiments are carried out on two different data sets (random and ATT48) to compare the speed and accuracy of the algorithms. The comparative results reveal that the GA could solve the TSP more effectively than EQLA. The obtained inferences along with the limitations are presented in this paper.
机器学习(ML)和进化计算(EC)是计算机科学中最流行的两种计算方法，分别用于解决我们周围的学习和优化问题。在文献中，探索这两种方法并制定“EA for ML”和“ML for EA”的算法框架是研究兴趣，其中EA代表进化算法。本文的目的就是探索这一研究维度。旅行商问题(TSP)是组合优化问题中np困难(不确定多项式时间困难)问题之一。TSP的解是覆盖给定城市中所有节点的最短路径。本文比较了EC领域的“遗传算法(GA)”和ML领域的“Epsilon-Greedy Q-Learning算法(EQLA)”两种求解TSP问题的算法。本文讨论了这两种算法所涉及的详细设计方法。在两个不同的数据集(随机和ATT48)上进行了实验，比较了算法的速度和准确性。对比结果表明，遗传算法比EQLA更能有效地解决TSP问题。本文给出了所得结论和局限性。
{"title":"A Comparative Study on Genetic algorithm and Reinforcement Learning to Solve the Traveling Salesman Problem","authors":"Agash Uthayasuriyan, Hema Chandran G, Kavvin Uv, Sabbineni Hema Mahitha, J. G","doi":"10.37256/rrcs.2320232642","DOIUrl":"https://doi.org/10.37256/rrcs.2320232642","url":null,"abstract":"Machine Learning (ML) and Evolutionary Computing (EC) are the two most popular computational methodologies in computer science to solve learning and optimization problems around us, respectively. It is of research interest in the literature, for exploring these two methodologies and to formulate algorithmic frameworks with 'EA for ML' and 'ML for EA' where EA stands for Evolutionary Algorithm. The objective of this paper is on exploring this dimension of research. The Traveling Salesman Problem (TSP) is one of the NP-hard (nondeterministic polynomial time hard) problems in combinatorial optimization problems. The solution for a TSP is the shortest path covering all the nodes in a given city. This paper compares two algorithms, \"Genetic Algorithm (GA)\" of the EC domain and \"Epsilon-Greedy Q-Learning Algorithm (EQLA)\" of the ML domain on solving TSP. The detailed design methodology involved in both these algorithms is discussed in this paper. The experiments are carried out on two different data sets (random and ATT48) to compare the speed and accuracy of the algorithms. The comparative results reveal that the GA could solve the TSP more effectively than EQLA. The obtained inferences along with the limitations are presented in this paper.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129065017","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 : 2023-03-16DOI: 10.37256/rrcs.2120232295
Xu Chen, Zeguan Wu, Xuan Di
Connected vehicles (CVs) are anticipated to improve road safety and travel efficiency in a transportation system. However, the deployment of CV technologies in transportation networks can lead to privacy issues, as the communication among CVs can expose vehicles' location information. To address this issue, we introduce a privacy protection method named "silent link" to transportation networks and propose a silent link user equilibrium (SLUE) framework to study the impact of privacy protection countermeasures on network flow. A theoretical analysis regarding existence and uniqueness conditions of SLUE is provided. The proposed SLUE facilitates privacy-oriented network design to achieve optimal levels of privacy for CVs. Accordingly, a bi-level network optimization problem is formulated for the design of silent links in transportation networks. Numerical examples are demonstrated using the Braess and Sioux Falls networks.
{"title":"Network Design for Silent Link User Equilibrium","authors":"Xu Chen, Zeguan Wu, Xuan Di","doi":"10.37256/rrcs.2120232295","DOIUrl":"https://doi.org/10.37256/rrcs.2120232295","url":null,"abstract":"Connected vehicles (CVs) are anticipated to improve road safety and travel efficiency in a transportation system. However, the deployment of CV technologies in transportation networks can lead to privacy issues, as the communication among CVs can expose vehicles' location information. To address this issue, we introduce a privacy protection method named \"silent link\" to transportation networks and propose a silent link user equilibrium (SLUE) framework to study the impact of privacy protection countermeasures on network flow. A theoretical analysis regarding existence and uniqueness conditions of SLUE is provided. The proposed SLUE facilitates privacy-oriented network design to achieve optimal levels of privacy for CVs. Accordingly, a bi-level network optimization problem is formulated for the design of silent links in transportation networks. Numerical examples are demonstrated using the Braess and Sioux Falls networks.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"351 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122339226","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}
Aiming at the teaching difficulties of signal and system course, adapting to the new situation of the information age and the engineering education of outcome-based education (OBE), adhering to the traditional classroom teaching and making full use of the network teaching platform and internet technology, a blended teaching mode of internet-engineering education (BTM-IEE) is proposed. In this mode, we adhered to the educational concept of OBE, formulated teaching objectives, optimized teaching content, and built matching teaching resources. In three teaching stages: before class, in class and after class, online-offline blended teaching was effectively organized and implemented by using internet technology, network teaching platform, independently developed a comprehensive experimental system, remote virtual experiment platform, QQ group, etc. In order to ensure a good cycle of teaching quality, a multi-dimensional evaluation system is constructed. A variety of application examples and questionnaire data showed that BTM-IEE can achieve a deep integration of in class-out of class and online-offline, improve students’ engineering application ability, autonomous learning ability, cooperation, communication ability, and cultivate innovative thinking. The horizontal and vertical comparison between the traditional and the improved teaching mode shows that the BTM-IEE can improve the teaching effect, the excellent rate is significantly increased, and the failure rate is significantly reduced. This mode provides a reference for the improvement of the teaching quality of professional courses and has important practical significance.
{"title":"Blended Teaching for Signal and System Course Based on Internet-Engineering Education","authors":"Z. Dou, Yajing Wang, Zhenmei Li, Xianming Sun, Qinqin Wei, Wengang Chen","doi":"10.37256/rrcs.2120232076","DOIUrl":"https://doi.org/10.37256/rrcs.2120232076","url":null,"abstract":"Aiming at the teaching difficulties of signal and system course, adapting to the new situation of the information age and the engineering education of outcome-based education (OBE), adhering to the traditional classroom teaching and making full use of the network teaching platform and internet technology, a blended teaching mode of internet-engineering education (BTM-IEE) is proposed. In this mode, we adhered to the educational concept of OBE, formulated teaching objectives, optimized teaching content, and built matching teaching resources. In three teaching stages: before class, in class and after class, online-offline blended teaching was effectively organized and implemented by using internet technology, network teaching platform, independently developed a comprehensive experimental system, remote virtual experiment platform, QQ group, etc. In order to ensure a good cycle of teaching quality, a multi-dimensional evaluation system is constructed. A variety of application examples and questionnaire data showed that BTM-IEE can achieve a deep integration of in class-out of class and online-offline, improve students’ engineering application ability, autonomous learning ability, cooperation, communication ability, and cultivate innovative thinking. The horizontal and vertical comparison between the traditional and the improved teaching mode shows that the BTM-IEE can improve the teaching effect, the excellent rate is significantly increased, and the failure rate is significantly reduced. This mode provides a reference for the improvement of the teaching quality of professional courses and has important practical significance.","PeriodicalId":377142,"journal":{"name":"Research Reports on Computer Science","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133671867","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}
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