Pub Date : 2023-09-10DOI: 10.12694/scpe.v24i3.2339
Lan Cui, Yuefen Zhi
Hybrid education is the most effective process of education, which is the mixture of two education processes that help increase the student’s understanding level. In the study, it has been discussed that the intelligent learning environment influences the education style, which allows the students and the educator to understand the topic correctly. Also, from the study, a good bond between the teacher and the students increases the achievement rate in an education system. Therefore, the professional life of the students is also more developed. The study aims to consider the disadvantages of the modern or hybrid education system, and the communication gap is one of the significant disadvantages of education.
{"title":"A Hybrid Education Quality Assessment Method based on Heuristic Optimization Algorithm","authors":"Lan Cui, Yuefen Zhi","doi":"10.12694/scpe.v24i3.2339","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2339","url":null,"abstract":"Hybrid education is the most effective process of education, which is the mixture of two education processes that help increase the student’s understanding level. In the study, it has been discussed that the intelligent learning environment influences the education style, which allows the students and the educator to understand the topic correctly. Also, from the study, a good bond between the teacher and the students increases the achievement rate in an education system. Therefore, the professional life of the students is also more developed. The study aims to consider the disadvantages of the modern or hybrid education system, and the communication gap is one of the significant disadvantages of education.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071661","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2284
Xinqing Li, Juan Li, Qin He
Conventional intelligent layout algorithm of ceramic design drawing elements mainly uses density distribution method to obtain ceramic design drawing element units, which is vulnerable to the influence of pattern density, resulting in a low distribution balance of design drawing elements. Therefore, a new intelligent layout algorithm for ceramic design drawing elements needs to be designed based on a genetic algorithm. That is, combining the characteristics of ceramic design drawing elements, the intelligent parting structure of ceramic design drawing elements is constructed, and then the brilliant layout model of ceramic design drawing elements is designed using genetic algorithm. The experimental results show that the developed intelligent layout algorithm of ceramic design elements has a high distribution balance, which proves that the designed intelligent layout algorithm of ceramic design elements has good performance, reliability, and certain application value, and has made specific contributions to improving the aesthetic quality of ceramic design drawings.
{"title":"Intelligent Element Layout Algorithm of Ceramic Design Drawing Based on Genetic Algorithm","authors":"Xinqing Li, Juan Li, Qin He","doi":"10.12694/scpe.v24i3.2284","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2284","url":null,"abstract":"Conventional intelligent layout algorithm of ceramic design drawing elements mainly uses density distribution method to obtain ceramic design drawing element units, which is vulnerable to the influence of pattern density, resulting in a low distribution balance of design drawing elements. Therefore, a new intelligent layout algorithm for ceramic design drawing elements needs to be designed based on a genetic algorithm. That is, combining the characteristics of ceramic design drawing elements, the intelligent parting structure of ceramic design drawing elements is constructed, and then the brilliant layout model of ceramic design drawing elements is designed using genetic algorithm. The experimental results show that the developed intelligent layout algorithm of ceramic design elements has a high distribution balance, which proves that the designed intelligent layout algorithm of ceramic design elements has good performance, reliability, and certain application value, and has made specific contributions to improving the aesthetic quality of ceramic design drawings.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072815","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2224
Sian Chen, Linqiang Tang
In the modern age, developing practical online learning tools for English language learners is challenging due to existing systems’ shortcomings. These systems often need proper instructional design, are well-connected to motivational theories, and have limited infrastructure for data sharing, leading to poor learning outcomes and low motivation. To tackle these issues, a new approach called OAELT has been proposed in this paper. OAELT is an Online Assisted English Learning Tool that uses the Fuzzy Analytical Hierarchy Process (FAHP) and collaborative cloud-fog-edge networking to create a flexible learning design that adapts to the needs and preferences of individual learners. Using the FAHP approach, OAELT provides an improved learning experience by tailoring its design to each learner’s unique needs. The collaborative cloud-fog-edge networking approach uses each computing layer’s strengths to deliver a personalized and seamless learning experience. OAELT employs adaptive and dynamic approaches within a flexible instructional paradigm to ensure effective instructional design. This paradigm facilitates collective learning data exchange across cloud, fog, and edge computing layers. The effectiveness of OAELT was evaluated using a descriptive statistics approach, which included a five-dimension questionnaire for students covering cognition, emotion, action, cooperation, and literacy. The results demonstrated that OAELT could enhance learning effectiveness and motivation while providing a flexible and seamless learning experience. According to the experimental data of the proposed model, 46.8% of learners often read English magazines and newspapers to improve their flexibility in English learning. Additionally, 50.4% classified and memorized English according to their categories, while 59% of learners often used context to memorize. These findings suggest that the traditional methods for flexible English learning are not adequate, and the average score of the student’s methods and strategies is mediocre. However, after using OAELT, some students have been able to use different learning curricular reading. Overall, OAELT’s integration of cloud-fog-edge computing with a flexible English learning design can create a more effective and personalized learning system that addresses the challenges of modern learning.
{"title":"Flexible English Learning Platform using Collaborative Cloud-Fog-Edge Networking","authors":"Sian Chen, Linqiang Tang","doi":"10.12694/scpe.v24i3.2224","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2224","url":null,"abstract":"In the modern age, developing practical online learning tools for English language learners is challenging due to existing systems’ shortcomings. These systems often need proper instructional design, are well-connected to motivational theories, and have limited infrastructure for data sharing, leading to poor learning outcomes and low motivation. To tackle these issues, a new approach called OAELT has been proposed in this paper. OAELT is an Online Assisted English Learning Tool that uses the Fuzzy Analytical Hierarchy Process (FAHP) and collaborative cloud-fog-edge networking to create a flexible learning design that adapts to the needs and preferences of individual learners. Using the FAHP approach, OAELT provides an improved learning experience by tailoring its design to each learner’s unique needs. The collaborative cloud-fog-edge networking approach uses each computing layer’s strengths to deliver a personalized and seamless learning experience. OAELT employs adaptive and dynamic approaches within a flexible instructional paradigm to ensure effective instructional design. This paradigm facilitates collective learning data exchange across cloud, fog, and edge computing layers. The effectiveness of OAELT was evaluated using a descriptive statistics approach, which included a five-dimension questionnaire for students covering cognition, emotion, action, cooperation, and literacy. The results demonstrated that OAELT could enhance learning effectiveness and motivation while providing a flexible and seamless learning experience. According to the experimental data of the proposed model, 46.8% of learners often read English magazines and newspapers to improve their flexibility in English learning. Additionally, 50.4% classified and memorized English according to their categories, while 59% of learners often used context to memorize. These findings suggest that the traditional methods for flexible English learning are not adequate, and the average score of the student’s methods and strategies is mediocre. However, after using OAELT, some students have been able to use different learning curricular reading. Overall, OAELT’s integration of cloud-fog-edge computing with a flexible English learning design can create a more effective and personalized learning system that addresses the challenges of modern learning.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071354","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2245
Shuang Wu, Jinlong Wu, Yifeng Sun, Tong Yao
At present, the traditional urban public transportation system cannot meet people’s daily travel needs. Urban Rail Transit (URT) has been rapidly promoted in major cities due to its advantages such as low energy consumption, high frequency, and large traffic volume. To achieve a more excellent and energy-saving operation scheduling strategy, the research first combines the train dynamics model and the energy consumption model. Since the optimization problem of URT is a linear problem, the attraction model of the Firefly algorithm can determine the calculation time consumed by the algorithm, which is very suitable for the complex optimization problem of URT. Therefore, the FA based optimization algorithm for urban rail transit operation scheduling (FURTOSO) based on the Firefly algorithm is studied and designed. Therefore, based on the study of the four working conditions of traction, cruise, coasting, and braking, a Firefly Algorithm for Urban Rail Transit Operation Scheduling (FURTOSO) was designed. Finally, the study optimizes the operation scheduling of Chengdu Metro Line 8 from two aspects: driving strategy and train schedule. The research demonstrates that the FURTOSO algorithm only needs 76 iterations to reach a stable state, with a fitness value of 0.6827. In practical applications, the utilization rate of train RBE is 30.1%, the total energy consumption (TEC) is 2.661 * 1011J, and the energy saving rate is 13.03%. In summary, the FURTOSO algorithm proposed in the study has excellent performance and has better energy-saving effects in Chengdu Metro Line 8.
{"title":"Optimization Algorithm for Urban Rail Transit Operation Scheduling based on Linear Programming","authors":"Shuang Wu, Jinlong Wu, Yifeng Sun, Tong Yao","doi":"10.12694/scpe.v24i3.2245","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2245","url":null,"abstract":"At present, the traditional urban public transportation system cannot meet people’s daily travel needs. Urban Rail Transit (URT) has been rapidly promoted in major cities due to its advantages such as low energy consumption, high frequency, and large traffic volume. To achieve a more excellent and energy-saving operation scheduling strategy, the research first combines the train dynamics model and the energy consumption model. Since the optimization problem of URT is a linear problem, the attraction model of the Firefly algorithm can determine the calculation time consumed by the algorithm, which is very suitable for the complex optimization problem of URT. Therefore, the FA based optimization algorithm for urban rail transit operation scheduling (FURTOSO) based on the Firefly algorithm is studied and designed. Therefore, based on the study of the four working conditions of traction, cruise, coasting, and braking, a Firefly Algorithm for Urban Rail Transit Operation Scheduling (FURTOSO) was designed. Finally, the study optimizes the operation scheduling of Chengdu Metro Line 8 from two aspects: driving strategy and train schedule. The research demonstrates that the FURTOSO algorithm only needs 76 iterations to reach a stable state, with a fitness value of 0.6827. In practical applications, the utilization rate of train RBE is 30.1%, the total energy consumption (TEC) is 2.661 * 1011J, and the energy saving rate is 13.03%. In summary, the FURTOSO algorithm proposed in the study has excellent performance and has better energy-saving effects in Chengdu Metro Line 8.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071670","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2335
Zhengjun Hao
The use of traditional manual supervision means to deal with motor vehicle traffic safety violations can result in a large amount of wasted manpower and oversight problems. To assist road managers in better directing traffic order and managing traffic situations, the study proposes an improved target tracking network model. Simple online real-time tracking, deep correlation metrics, and cascading open-source computer vision libraries are combined to create a tracking model for motor vehicle traffic infraction recognition. Pursuant to the experimental findings, the Institute’s upgraded target recognition network model had accuracy and recall rates of 95.7% and 99.7%, respectively, with an accuracy rate of 16.6% higher than the model’s historical counterpart. The recognition accuracy of the constructed motor vehicle traffic violation recognition and tracking model regarding the three basic traffic violations was 98.2%, 98.7%, and 97.9%, respectively; the missed detection rate was 2.0%, 0.31%, and 2.1%, respectively; and the false detection rate was 0.17%, 0.31%, and 0%, respectively. It shows that the improved network model of the study is advanced and the motor vehicle traffic offence model has a good recognition rate and stable performance, which can assist traffic managers in their operations to a certain extent.
{"title":"Method for Identifying Motor Vehicle Traffic Violations Based on Improved YOLOv Network","authors":"Zhengjun Hao","doi":"10.12694/scpe.v24i3.2335","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2335","url":null,"abstract":"The use of traditional manual supervision means to deal with motor vehicle traffic safety violations can result in a large amount of wasted manpower and oversight problems. To assist road managers in better directing traffic order and managing traffic situations, the study proposes an improved target tracking network model. Simple online real-time tracking, deep correlation metrics, and cascading open-source computer vision libraries are combined to create a tracking model for motor vehicle traffic infraction recognition. Pursuant to the experimental findings, the Institute’s upgraded target recognition network model had accuracy and recall rates of 95.7% and 99.7%, respectively, with an accuracy rate of 16.6% higher than the model’s historical counterpart. The recognition accuracy of the constructed motor vehicle traffic violation recognition and tracking model regarding the three basic traffic violations was 98.2%, 98.7%, and 97.9%, respectively; the missed detection rate was 2.0%, 0.31%, and 2.1%, respectively; and the false detection rate was 0.17%, 0.31%, and 0%, respectively. It shows that the improved network model of the study is advanced and the motor vehicle traffic offence model has a good recognition rate and stable performance, which can assist traffic managers in their operations to a certain extent.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071799","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2371
Shuqin Lin
Along the continuous advancement of the network and the rise of digital media, the amount of data produced by the exponential explosion. And how to use these data to provide personalized services for users is one of the current research focuses. To address the issue of insufficient coverage in the current sentiment lexicon and the difficulty of constructing sentiment lexicon in specific fields, this study proposes a multi-modal emotional thesaurus. Semi-supervised learning is used to solve the problem of insufficient coverage of emotional thesaurus, and a semi-supervised classification algorithm is realized by using a large number of unlabeled sample data combined with a small number of labeled sample data. Optimized learning is used to solve the problem of difficult construction of emotional thesaurus in specific fields, the corresponding specific emotional thesaurus is constructed by adaptive adjustment of emotional word score, and finally the improved emotional thesaurus is used to build a digital media short text sentiment analysis framework. For testing, the NLPCC dataset was used in this study, Experiments show that the framework constructed in this study requires 87 iterations, a Recall value of 0.912, a F1 value of 0.753, and an average accuracy of 83.39%, all of which are better than the sentiment analysis framework without the use of multi-pattern sentiment lexicon. In the simulation experiment, the recognition accuracy reached 85.88%, which was 16.85%, 11.57% and 6.72% higher than the test scenarios using a single emotion thesaurus selected in this study. The above results show that the digital media short-text sentiment analysis framework built in this research based on multi-pattern sentiment lexicon can carry out short-text sentiment analysis more accurately and efficiently, so as to accurately analyze users’ needs and provide customized services precisely.
{"title":"Design of Sentiment Analysis Framework of Digital Media Short Text Based on Multi-pattern Sentiment Lexicon","authors":"Shuqin Lin","doi":"10.12694/scpe.v24i3.2371","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2371","url":null,"abstract":"Along the continuous advancement of the network and the rise of digital media, the amount of data produced by the exponential explosion. And how to use these data to provide personalized services for users is one of the current research focuses. To address the issue of insufficient coverage in the current sentiment lexicon and the difficulty of constructing sentiment lexicon in specific fields, this study proposes a multi-modal emotional thesaurus. Semi-supervised learning is used to solve the problem of insufficient coverage of emotional thesaurus, and a semi-supervised classification algorithm is realized by using a large number of unlabeled sample data combined with a small number of labeled sample data. Optimized learning is used to solve the problem of difficult construction of emotional thesaurus in specific fields, the corresponding specific emotional thesaurus is constructed by adaptive adjustment of emotional word score, and finally the improved emotional thesaurus is used to build a digital media short text sentiment analysis framework. For testing, the NLPCC dataset was used in this study, Experiments show that the framework constructed in this study requires 87 iterations, a Recall value of 0.912, a F1 value of 0.753, and an average accuracy of 83.39%, all of which are better than the sentiment analysis framework without the use of multi-pattern sentiment lexicon. In the simulation experiment, the recognition accuracy reached 85.88%, which was 16.85%, 11.57% and 6.72% higher than the test scenarios using a single emotion thesaurus selected in this study. The above results show that the digital media short-text sentiment analysis framework built in this research based on multi-pattern sentiment lexicon can carry out short-text sentiment analysis more accurately and efficiently, so as to accurately analyze users’ needs and provide customized services precisely.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071899","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2288
Zhuoran Song, Jianfeng Li, Tao Jiang, Sichen Lu
This paper introduces a novel distribution network planning method that addresses the limitations of conventional approaches. The existing methods primarily focus on optimizing component objectives using reliability analysis, which results in inadequate operational power control performance due to neglecting the coupling degree analysis of distribution network subprojects. To overcome this limitation, the proposed method incorporates the coupling of the traffic and distribution networks into the planning process. The method involves modeling the transportation network and analyzing the coupling characteristics of the planning items. Specifically, the energy efficiency coupling degree is calculated to assess the degree of coupling. Based on this analysis, the planning nodes are strategically deployed, and a comprehensive planning model is constructed. The model is then subjected to constraints and solved to obtain an optimal distribution network planning scheme. To evaluate the effectiveness of the proposed method, experiments are conducted to assess its operational power control capability. The experimental results demonstrate that when the proposed method is employed for distribution network planning, it reduces operating power and achieves a more desirable planning outcome. The novelty of this work lies in integrating the coupling analysis of the traffic network and the distribution network into the planning process. Considering the interdependencies between these networks, the proposed method enables a more comprehensive and efficient distribution network planning scheme. This approach enhances operational power control performance and improves the overall effectiveness of distribution network planning.
{"title":"Distribution Network Planning Method considering the Coupling of Transportation Network and Distribution Network","authors":"Zhuoran Song, Jianfeng Li, Tao Jiang, Sichen Lu","doi":"10.12694/scpe.v24i3.2288","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2288","url":null,"abstract":"This paper introduces a novel distribution network planning method that addresses the limitations of conventional approaches. The existing methods primarily focus on optimizing component objectives using reliability analysis, which results in inadequate operational power control performance due to neglecting the coupling degree analysis of distribution network subprojects. To overcome this limitation, the proposed method incorporates the coupling of the traffic and distribution networks into the planning process. The method involves modeling the transportation network and analyzing the coupling characteristics of the planning items. Specifically, the energy efficiency coupling degree is calculated to assess the degree of coupling. Based on this analysis, the planning nodes are strategically deployed, and a comprehensive planning model is constructed. The model is then subjected to constraints and solved to obtain an optimal distribution network planning scheme. To evaluate the effectiveness of the proposed method, experiments are conducted to assess its operational power control capability. The experimental results demonstrate that when the proposed method is employed for distribution network planning, it reduces operating power and achieves a more desirable planning outcome. The novelty of this work lies in integrating the coupling analysis of the traffic network and the distribution network into the planning process. Considering the interdependencies between these networks, the proposed method enables a more comprehensive and efficient distribution network planning scheme. This approach enhances operational power control performance and improves the overall effectiveness of distribution network planning.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071916","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2274
Hao Wang, Huiyan Li
The conventional evaluation method for the effectiveness of curriculum implementation mainly focuses on the complete orientation analysis of students’ curriculum content, which does not reflect the value of the educational curriculum and affects the effectiveness of evaluation. Therefore, an evaluation method of curriculum implementation effectiveness of higher vocational education based on a collaborative filtering algorithm is designed. Identify the practical focus of evaluating the implementation of the higher vocational education curriculum and discover the educational curriculum’s significance. Qualitative evaluation of curriculum implementation degree based on collaborative filtering algorithm, find out the hidden characteristics of curriculum implementation evaluation to effectively evaluate higher vocational education curriculum implementation. Using case analysis, it is verified that the method is more effective and can be applied in real life.
{"title":"Evaluation of Curriculum Implementation Effectiveness of Higher Vocational Education Based on Collaborative Filtering Algorithm","authors":"Hao Wang, Huiyan Li","doi":"10.12694/scpe.v24i3.2274","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2274","url":null,"abstract":"The conventional evaluation method for the effectiveness of curriculum implementation mainly focuses on the complete orientation analysis of students’ curriculum content, which does not reflect the value of the educational curriculum and affects the effectiveness of evaluation. Therefore, an evaluation method of curriculum implementation effectiveness of higher vocational education based on a collaborative filtering algorithm is designed. Identify the practical focus of evaluating the implementation of the higher vocational education curriculum and discover the educational curriculum’s significance. Qualitative evaluation of curriculum implementation degree based on collaborative filtering algorithm, find out the hidden characteristics of curriculum implementation evaluation to effectively evaluate higher vocational education curriculum implementation. Using case analysis, it is verified that the method is more effective and can be applied in real life.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072022","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2162
Songlin Liu
This paper challenges the time-related challenges inherent in conventional network security detection methodologies. It is achieved by incorporating virtual reality technology into the domain of computer network security detection. The research methodology employs optimization calculations to extract attributes that characterize network security vulnerabilities. Concurrently, the weighting of diverse vulnerability attributes is adjusted using a web crawler, a comprehensive list of injection points, and meticulous analyses of the attacks’ genetic characteristics. This collective approach facilitates the exploration of automated network security vulnerability detection within a virtual reality framework. The study’s empirical results demonstrate that the detection method proposed within this investigation exhibits a notably reduced delay of 75.33 milliseconds. The respective delays observed in the two conventional methods stand at 290.11 milliseconds and 337.30 milliseconds. The substantial decrease in detection delay validates the effectiveness and efficiency of the devised automated network vulnerability detection approach grounded in virtual reality technology.
{"title":"Vulnerability Detection in Computer Networks using Virtual Reality Technology","authors":"Songlin Liu","doi":"10.12694/scpe.v24i3.2162","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2162","url":null,"abstract":"This paper challenges the time-related challenges inherent in conventional network security detection methodologies. It is achieved by incorporating virtual reality technology into the domain of computer network security detection. The research methodology employs optimization calculations to extract attributes that characterize network security vulnerabilities. Concurrently, the weighting of diverse vulnerability attributes is adjusted using a web crawler, a comprehensive list of injection points, and meticulous analyses of the attacks’ genetic characteristics. This collective approach facilitates the exploration of automated network security vulnerability detection within a virtual reality framework. The study’s empirical results demonstrate that the detection method proposed within this investigation exhibits a notably reduced delay of 75.33 milliseconds. The respective delays observed in the two conventional methods stand at 290.11 milliseconds and 337.30 milliseconds. The substantial decrease in detection delay validates the effectiveness and efficiency of the devised automated network vulnerability detection approach grounded in virtual reality technology.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072025","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 : 2023-09-10DOI: 10.12694/scpe.v24i3.2283
Xuecai Yin
The current optimal selection matrix for ideological and political issues of business courses is mostly set as a single objective form, and the topic selection is limited in scope, increasing the mutation rate of the optimal selection of topics. Therefore, the design and analysis of the optimal selection method for ideological and political issues of business courses based on the swarm intelligence algorithm is proposed. According to the actual measurement needs and standards, extract the optimal characteristic of ideological and political issues selection of the curriculum, use a multi-level approach to break the limits of issues selection, establish a multi-level swarm intelligence selection matrix, build an optimal selection model for ideological and political issues of business and trade courses based on swarm intelligence accounting, and achieve the optimal selection of issues through group fixed-point optimization. The novelty of this work lies in the design and analysis of the optimal selection method for ideological and political issues in business courses using a swarm intelligence algorithm. This approach introduces a new way of selecting topics by harnessing the power of collective intelligence inspired by the behavior of insects or animals. The final test results show that the mutation rate of the optimal selection of the three topics finally screened using the swarm intelligence algorithm is better controlled below 0.2 through the measurement of five classes, indicating that the topic is more practical, more targeted, and has better discussion value.
{"title":"The Optimal Selection of Ideological and Political Issues in Business Courses Based on Swarm Intelligence Algorithm","authors":"Xuecai Yin","doi":"10.12694/scpe.v24i3.2283","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2283","url":null,"abstract":"The current optimal selection matrix for ideological and political issues of business courses is mostly set as a single objective form, and the topic selection is limited in scope, increasing the mutation rate of the optimal selection of topics. Therefore, the design and analysis of the optimal selection method for ideological and political issues of business courses based on the swarm intelligence algorithm is proposed. According to the actual measurement needs and standards, extract the optimal characteristic of ideological and political issues selection of the curriculum, use a multi-level approach to break the limits of issues selection, establish a multi-level swarm intelligence selection matrix, build an optimal selection model for ideological and political issues of business and trade courses based on swarm intelligence accounting, and achieve the optimal selection of issues through group fixed-point optimization. The novelty of this work lies in the design and analysis of the optimal selection method for ideological and political issues in business courses using a swarm intelligence algorithm. This approach introduces a new way of selecting topics by harnessing the power of collective intelligence inspired by the behavior of insects or animals. The final test results show that the mutation rate of the optimal selection of the three topics finally screened using the swarm intelligence algorithm is better controlled below 0.2 through the measurement of five classes, indicating that the topic is more practical, more targeted, and has better discussion value.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072027","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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