Background. English is one of the courses offered in all colleges and universities. The quality of English teaching is directly related to the quality of talent training and the development of students themselves. “Teaching quality evaluation” specifically refers to the education evaluation with teaching as the evaluation object. It is the core and foundation of the whole education evaluation. Teaching quality evaluation is based on certain teaching objectives and teaching norms and standards, through the systematic detection and assessment of teaching and learning. Evaluate its teaching effect and the degree of realization of teaching objectives, and use scientific and feasible methods to make corresponding value judgments to improve the process of teaching. To improve the accuracy of English teaching ability evaluation, an English teaching ability evaluation algorithm based on frequency effect is proposed. Methods. The paper proposes an English teaching ability evaluation algorithm based on frequency effect. Firstly, it constructs the evaluation index system of English teaching ability, including expert evaluation system, student evaluation system, and teacher evaluation system. Then, the indexes affecting the evaluation of English teaching ability are quantified by fuzzy synthesis, and the evaluation indexes are refined. Finally, the basic principle of frequency effect is analyzed, combined with the convolutional neural network. Results. The convolutional neural network evaluation model is constructed, the teaching ability indicators are input into the model, the final evaluation results are output, and the design of the English teaching ability evaluation algorithm based on frequency effect is completed. Conclusions. The experimental results show that this method has high accuracy and efficiency.
{"title":"An English Teaching Ability Evaluation Algorithm Based on Frequency Effect","authors":"Lan Xu","doi":"10.1155/2021/7643215","DOIUrl":"https://doi.org/10.1155/2021/7643215","url":null,"abstract":"Background. English is one of the courses offered in all colleges and universities. The quality of English teaching is directly related to the quality of talent training and the development of students themselves. “Teaching quality evaluation” specifically refers to the education evaluation with teaching as the evaluation object. It is the core and foundation of the whole education evaluation. Teaching quality evaluation is based on certain teaching objectives and teaching norms and standards, through the systematic detection and assessment of teaching and learning. Evaluate its teaching effect and the degree of realization of teaching objectives, and use scientific and feasible methods to make corresponding value judgments to improve the process of teaching. To improve the accuracy of English teaching ability evaluation, an English teaching ability evaluation algorithm based on frequency effect is proposed. Methods. The paper proposes an English teaching ability evaluation algorithm based on frequency effect. Firstly, it constructs the evaluation index system of English teaching ability, including expert evaluation system, student evaluation system, and teacher evaluation system. Then, the indexes affecting the evaluation of English teaching ability are quantified by fuzzy synthesis, and the evaluation indexes are refined. Finally, the basic principle of frequency effect is analyzed, combined with the convolutional neural network. Results. The convolutional neural network evaluation model is constructed, the teaching ability indicators are input into the model, the final evaluation results are output, and the design of the English teaching ability evaluation algorithm based on frequency effect is completed. Conclusions. The experimental results show that this method has high accuracy and efficiency.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"75 1","pages":"7643215:1-7643215:10"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85778843","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 : 2021-12-01DOI: 10.1016/j.is.2021.101955
M. Cazzolato, A. J. Traina, Klemens Böhm
{"title":"Establishing trajectories of moving objects without identities: The intricacies of cell tracking and a solution","authors":"M. Cazzolato, A. J. Traina, Klemens Böhm","doi":"10.1016/j.is.2021.101955","DOIUrl":"https://doi.org/10.1016/j.is.2021.101955","url":null,"abstract":"","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"8 1","pages":"101955"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75076818","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}
The Baoginshan quartz vein type gold mine in the Baimashan-Longshan-Ziyunshan gold belt is the object of study, and the nature of the fracture structure and its ore-controlling effect are studied through surface and pit investigation, and the nature of the ore-controlling structure system and combination pattern of the Baoginshan gold mine is established. The F7 and F9 fractures in the near-east-west (EW) direction are the main fractures, which tend to the north and control the spreading of the ore zone; the northwest (NW) direction secondary tension fracture, with a dominant yield of 221°∠63°, is a T-type fracture in the Riedel shear mode and is the ore-holding structure of the vein-like ore body; the northeast-east (NEE) direction secondary shear fracture, with a dominant yield of 343°∠53°, is a P-type fracture and the combination of the two controls the specific positioning of the ore body. The characteristics and nature of the fracture structures in the whole ore zone, as well as their combination patterns, indicate that the overall ore-controlling fracture system of Baoginshan is a right-going tensional shear fracture zone composed of NW-oriented (T-type) and NEE-oriented (P-type) secondary fractures with F7 and F9 fractures as boundary fractures. The directions of the principal stresses are σ1≈158°∠40°, σ2≈288°∠38°, and σ3≈42°∠28°, respectively. In the next step of the prospecting process, based on increasing the spacing of prospecting pits (to 40m), in-pit drilling is deployed in the upper and lower discs of the NEE secondary fracture along with the tendency and strike for literacy, which can significantly improve the efficiency and effectiveness of prospecting and greatly reduce the cost of prospecting.
{"title":"The Establishment of Ore-Controlling Fracture System of Baoginshan Gold Mine Based on Fracture-Tectonic Analysis","authors":"Yulong Lu, Xingqiang Li, Yang Liu, Jiahao Leng","doi":"10.1155/2021/5887680","DOIUrl":"https://doi.org/10.1155/2021/5887680","url":null,"abstract":"The Baoginshan quartz vein type gold mine in the Baimashan-Longshan-Ziyunshan gold belt is the object of study, and the nature of the fracture structure and its ore-controlling effect are studied through surface and pit investigation, and the nature of the ore-controlling structure system and combination pattern of the Baoginshan gold mine is established. The F7 and F9 fractures in the near-east-west (EW) direction are the main fractures, which tend to the north and control the spreading of the ore zone; the northwest (NW) direction secondary tension fracture, with a dominant yield of 221°∠63°, is a T-type fracture in the Riedel shear mode and is the ore-holding structure of the vein-like ore body; the northeast-east (NEE) direction secondary shear fracture, with a dominant yield of 343°∠53°, is a P-type fracture and the combination of the two controls the specific positioning of the ore body. The characteristics and nature of the fracture structures in the whole ore zone, as well as their combination patterns, indicate that the overall ore-controlling fracture system of Baoginshan is a right-going tensional shear fracture zone composed of NW-oriented (T-type) and NEE-oriented (P-type) secondary fractures with F7 and F9 fractures as boundary fractures. The directions of the principal stresses are σ1≈158°∠40°, σ2≈288°∠38°, and σ3≈42°∠28°, respectively. In the next step of the prospecting process, based on increasing the spacing of prospecting pits (to 40m), in-pit drilling is deployed in the upper and lower discs of the NEE secondary fracture along with the tendency and strike for literacy, which can significantly improve the efficiency and effectiveness of prospecting and greatly reduce the cost of prospecting.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"4 1","pages":"5887680:1-5887680:9"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89030160","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}
At present, big data related technologies are developing rapidly, and major companies provide big data analysis services. However, the big data analysis system formed by the combination method cannot sense each other and lacks cooperation, resulting in a certain amount of waste of resources in the big data analysis system. In order to find the key technology of the data analysis system and conduct in-depth analysis of the media data, this paper proposes a scheduling algorithm based on artificial intelligence (AI) to implement task scheduling and logical data block migration. By analyzing the experimental results, we know that the performance of LAS (Logistic-Block Affinity Scheduler) is improved by 23.97%, 16.11%, and 10.56%, respectively, compared with the other three algorithms. Based on real new media data, this article analyzes the content of media data and user behavior in depth through big data analysis methods. Compared with other methods, the algorithm model in this paper optimizes the accuracy of hot topic extraction, which has important implications for media data mining. In addition, the analysis results of the emotional characteristics, audience characteristics, and hot topic communication characteristics obtained by the research also have practical value. This method improves the recall rate and F value by 5% and 4.7%, respectively, and the overall F value of emotional judgment is about 88.9%.
{"title":"Key Technologies of Media Data In-Depth Analysis System Based on Artificial Intelligence-Based Big Data","authors":"Y. Zheng","doi":"10.1155/2021/7191567","DOIUrl":"https://doi.org/10.1155/2021/7191567","url":null,"abstract":"At present, big data related technologies are developing rapidly, and major companies provide big data analysis services. However, the big data analysis system formed by the combination method cannot sense each other and lacks cooperation, resulting in a certain amount of waste of resources in the big data analysis system. In order to find the key technology of the data analysis system and conduct in-depth analysis of the media data, this paper proposes a scheduling algorithm based on artificial intelligence (AI) to implement task scheduling and logical data block migration. By analyzing the experimental results, we know that the performance of LAS (Logistic-Block Affinity Scheduler) is improved by 23.97%, 16.11%, and 10.56%, respectively, compared with the other three algorithms. Based on real new media data, this article analyzes the content of media data and user behavior in depth through big data analysis methods. Compared with other methods, the algorithm model in this paper optimizes the accuracy of hot topic extraction, which has important implications for media data mining. In addition, the analysis results of the emotional characteristics, audience characteristics, and hot topic communication characteristics obtained by the research also have practical value. This method improves the recall rate and F value by 5% and 4.7%, respectively, and the overall F value of emotional judgment is about 88.9%.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"79 1","pages":"7191567:1-7191567:10"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75842118","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}
Autism is a disorder caused by nerve developmental disorders in childhood. Autism is a serious and widespread developmental disorder, with social disorders, speech development disorders, and poor language communication skills as typical symptoms, accompanied by stereotyped behaviors. With the improvement of our country's material living standards, the frequency of childhood autism is increasing year by year. Therefore, IoT smart toys specially designed for children with autism can meet their needs and help them to carry out rehabilitation education, so that they can obtain more benefits in the process of treatment and nurturing. Smart IoT toys are not only a design that pays attention to details, but also integrates care for children with autism into the design. This article aims to research based on the Internet of Things, starting with the design of toys for children with autism. This article applies the design ideas of smart IoT toys to APP product design, introduces emotional factors into APP products, and stimulates the profound emotional experience of ASD children. Designing products from the emotional perspective and details of smart Internet of things toys and the perspective of ASD children, analyze the emotional design factors of APP, and propose application programs for ASD children according to the design standards and methods of smart Internet of things toys. After studying the status quo of children with autism, it can be concluded that children with autism need special toys suitable for them. IoT smart toys can expand the design ideas of existing children’s educational toys, enrich the toy market, and provide children with more toys that meet their needs. According to the latest statistics from the US Centers for Disease Control and Prevention, from 2010 to 2014, the prevalence of children with autism in the United States rose from 0.0147 to 0.0169, and the prevalence of children with autism aged 0–14 exceeded 200,000. With the improvement of our country's material living standards, the frequency of childhood autism is increasing year by year.
{"title":"ASD Children's APP Emotional Interaction Design Based on Smart Toys of Internet of Things","authors":"B. Zhang, Yanqun Wang, Yuling Yang, Lishu Song","doi":"10.1155/2021/1342538","DOIUrl":"https://doi.org/10.1155/2021/1342538","url":null,"abstract":"Autism is a disorder caused by nerve developmental disorders in childhood. Autism is a serious and widespread developmental disorder, with social disorders, speech development disorders, and poor language communication skills as typical symptoms, accompanied by stereotyped behaviors. With the improvement of our country's material living standards, the frequency of childhood autism is increasing year by year. Therefore, IoT smart toys specially designed for children with autism can meet their needs and help them to carry out rehabilitation education, so that they can obtain more benefits in the process of treatment and nurturing. Smart IoT toys are not only a design that pays attention to details, but also integrates care for children with autism into the design. This article aims to research based on the Internet of Things, starting with the design of toys for children with autism. This article applies the design ideas of smart IoT toys to APP product design, introduces emotional factors into APP products, and stimulates the profound emotional experience of ASD children. Designing products from the emotional perspective and details of smart Internet of things toys and the perspective of ASD children, analyze the emotional design factors of APP, and propose application programs for ASD children according to the design standards and methods of smart Internet of things toys. After studying the status quo of children with autism, it can be concluded that children with autism need special toys suitable for them. IoT smart toys can expand the design ideas of existing children’s educational toys, enrich the toy market, and provide children with more toys that meet their needs. According to the latest statistics from the US Centers for Disease Control and Prevention, from 2010 to 2014, the prevalence of children with autism in the United States rose from 0.0147 to 0.0169, and the prevalence of children with autism aged 0–14 exceeded 200,000. With the improvement of our country's material living standards, the frequency of childhood autism is increasing year by year.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"44 11 1","pages":"1342538:1-1342538:7"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75694321","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}
Insaf Ullah, A. Alkhalifah, Muhammad Asghar Khan, S. Mostafa
The Internet of things (IoT) has emerged into a revolutionary technology that enables a wide range of features and applications given the proliferation of sensors and actuators embedded in everyday objects, as well as the ubiquitous availability of high-speed Internet. When nearly everything is connected to the Internet, security and privacy concerns will become more significant. Furthermore, owing to the resource-constrained nature of IoT devices, they are unable to perform standard cryptographic computations. As a result, there is a critical need for efficient and secure lightweight cryptographic scheme that can meet the demands of resource-constrained IoT devices. In this study, we propose a lightweight proxy in which a person/party can delegate its signing authority to a proxy agent. Existing proxy signcryption security approaches are computationally costly and rely on RSA, bilinear pairing, and elliptic curves cryptography (ECC). The hyperelliptic curve cryptosystem (HECC), on the other hand, employs a smaller key size while maintaining the same level of security. When assessed using the random oracle model (ROM), the proposed scheme provides resilience against indistinguishable under adaptive chosen ciphertext attacks (IND-CCA) and unforgeable under adaptive chosen message attacks (UU-ACMA). To demonstrate the viability of the proposed scheme, security analyses and comparisons with existing schemes are performed. The findings show that the proposed scheme provides high security while reducing computational and communication costs.
{"title":"Cost-Effective Proxy Signcryption Scheme for Internet of Things","authors":"Insaf Ullah, A. Alkhalifah, Muhammad Asghar Khan, S. Mostafa","doi":"10.1155/2021/2427434","DOIUrl":"https://doi.org/10.1155/2021/2427434","url":null,"abstract":"The Internet of things (IoT) has emerged into a revolutionary technology that enables a wide range of features and applications given the proliferation of sensors and actuators embedded in everyday objects, as well as the ubiquitous availability of high-speed Internet. When nearly everything is connected to the Internet, security and privacy concerns will become more significant. Furthermore, owing to the resource-constrained nature of IoT devices, they are unable to perform standard cryptographic computations. As a result, there is a critical need for efficient and secure lightweight cryptographic scheme that can meet the demands of resource-constrained IoT devices. In this study, we propose a lightweight proxy in which a person/party can delegate its signing authority to a proxy agent. Existing proxy signcryption security approaches are computationally costly and rely on RSA, bilinear pairing, and elliptic curves cryptography (ECC). The hyperelliptic curve cryptosystem (HECC), on the other hand, employs a smaller key size while maintaining the same level of security. When assessed using the random oracle model (ROM), the proposed scheme provides resilience against indistinguishable under adaptive chosen ciphertext attacks (IND-CCA) and unforgeable under adaptive chosen message attacks (UU-ACMA). To demonstrate the viability of the proposed scheme, security analyses and comparisons with existing schemes are performed. The findings show that the proposed scheme provides high security while reducing computational and communication costs.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"112 1","pages":"2427434:1-2427434:10"},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85341715","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}
Educational evaluation is the main method of modern education management and guidance. Through a systematic collection of information and quantitative and qualitative analysis, value judgments can be made on the degree to which education adapts to needs, which can effectively improve the teaching development of applied undergraduate colleges. This article applies the Internet of Things technology to the information collection process of teaching evaluation in applied undergraduate colleges. This paper establishes an Internet of Things architecture to collect information on the impact indicators of the teaching evaluation process and builds a teaching evaluation index system. On this basis, this article combines fuzzy comprehensive evaluation for the quantification and evaluation process of index information. Through comparative analysis, the program can provide an effective way to construct a teaching evaluation system suitable for application-oriented undergraduate colleges. Constructing the research-based undergraduate classroom teaching evaluation index system aims at guiding the transformation of the concept of teaching and learning of teachers and students in research universities, perfecting the teaching and learning methods, improving the quality of teaching and learning, and promoting the common development of teachers and students.
{"title":"The Design of Teaching Evaluation and Organization System Based on the Internet of Things Using Fuzzy Comprehensive Evaluation Software","authors":"Han Guo","doi":"10.1155/2021/2285937","DOIUrl":"https://doi.org/10.1155/2021/2285937","url":null,"abstract":"Educational evaluation is the main method of modern education management and guidance. Through a systematic collection of information and quantitative and qualitative analysis, value judgments can be made on the degree to which education adapts to needs, which can effectively improve the teaching development of applied undergraduate colleges. This article applies the Internet of Things technology to the information collection process of teaching evaluation in applied undergraduate colleges. This paper establishes an Internet of Things architecture to collect information on the impact indicators of the teaching evaluation process and builds a teaching evaluation index system. On this basis, this article combines fuzzy comprehensive evaluation for the quantification and evaluation process of index information. Through comparative analysis, the program can provide an effective way to construct a teaching evaluation system suitable for application-oriented undergraduate colleges. Constructing the research-based undergraduate classroom teaching evaluation index system aims at guiding the transformation of the concept of teaching and learning of teachers and students in research universities, perfecting the teaching and learning methods, improving the quality of teaching and learning, and promoting the common development of teachers and students.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"16 1","pages":"2285937:1-2285937:8"},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88279359","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}
The wide-ranging implementation of Android applications used in various devices, from smartphones to intelligent television, has made it thought-provoking for developers. The permission granting mechanism is one of the defects imposed by the developers. Such assessing of defects does not allow the user to comprehend the implication of privacy for granting permission. Mobile applications are speedily easily reachable to typical users of mobile. Despite possible applications for improving the affordability, availability, and effectiveness of delivering various services, it handles sensitive data and information. Such data and information carry considerable security and privacy risks. Users are usually unaware of how the data can be managed and used. Reusable resources are available in the form of third-party libraries, which are broadly active in android apps. It provides a diversity of functions that deliver privacy and security concerns. Host applications and third-party libraries are run in the same process and share similar permissions. The current study has presented an overview of the existing approaches, methods, and tools used for influencing user behavior concerning android privacy policy. Various prominent libraries were searched, and their search results were analyzed briefly. The search results were presented in diverse perspectives for showing the details of the work done in the area. This will help researchers to offer new solutions in the area of the research.
{"title":"Influencing User's Behavior Concerning Android Privacy Policy: An Overview","authors":"Ming Di, S. Nazir, Fucheng Deng","doi":"10.1155/2021/3452700","DOIUrl":"https://doi.org/10.1155/2021/3452700","url":null,"abstract":"The wide-ranging implementation of Android applications used in various devices, from smartphones to intelligent television, has made it thought-provoking for developers. The permission granting mechanism is one of the defects imposed by the developers. Such assessing of defects does not allow the user to comprehend the implication of privacy for granting permission. Mobile applications are speedily easily reachable to typical users of mobile. Despite possible applications for improving the affordability, availability, and effectiveness of delivering various services, it handles sensitive data and information. Such data and information carry considerable security and privacy risks. Users are usually unaware of how the data can be managed and used. Reusable resources are available in the form of third-party libraries, which are broadly active in android apps. It provides a diversity of functions that deliver privacy and security concerns. Host applications and third-party libraries are run in the same process and share similar permissions. The current study has presented an overview of the existing approaches, methods, and tools used for influencing user behavior concerning android privacy policy. Various prominent libraries were searched, and their search results were analyzed briefly. The search results were presented in diverse perspectives for showing the details of the work done in the area. This will help researchers to offer new solutions in the area of the research.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"36 1","pages":"3452700:1-3452700:19"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78036723","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}
Wenbin Shi, Jingsheng Lei, X. Gan, Zhongguang Yang
Tracking multiple objects in a substation remains a challenging problem since pedestrians often overlap together and are occluded by infrastructures such as high-tension poles. In this paper, we propose an adaptive polymorphic fusion-based fast-tracking algorithm to address the problem. We first leverage the fast segmentation algorithm to obtain the fine masks of pedestrians and then combine the motion and performance information of pedestrians to realize the fast-tracking in substations. Our model is evaluated on the widely used MOT19 dataset and real-substation scenarios. Experimental results demonstrate that our model outperforms state-of-the-art models with a significant improvement in the MOT19 dataset and occlusion cases in substations.
{"title":"Adaptive Polymorphic Fusion-Based Fast-Tracking Algorithm in Substations","authors":"Wenbin Shi, Jingsheng Lei, X. Gan, Zhongguang Yang","doi":"10.1155/2021/2292128","DOIUrl":"https://doi.org/10.1155/2021/2292128","url":null,"abstract":"Tracking multiple objects in a substation remains a challenging problem since pedestrians often overlap together and are occluded by infrastructures such as high-tension poles. In this paper, we propose an adaptive polymorphic fusion-based fast-tracking algorithm to address the problem. We first leverage the fast segmentation algorithm to obtain the fine masks of pedestrians and then combine the motion and performance information of pedestrians to realize the fast-tracking in substations. Our model is evaluated on the widely used MOT19 dataset and real-substation scenarios. Experimental results demonstrate that our model outperforms state-of-the-art models with a significant improvement in the MOT19 dataset and occlusion cases in substations.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"37 1","pages":"2292128:1-2292128:18"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91326766","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}
Short-term load forecasting is an important part to support the planning and operation of power grid, but the current load forecasting methods have the problem of poor adaptive ability of model parameters, which are difficult to ensure the demand for efficient and accurate power grid load forecasting. To solve this problem, a short-term load forecasting method for smart grid is proposed based on multilayer network model. This method uses the integrated empirical mode decomposition (IEMD) method to realize the orderly and reliable load state data and provides high-quality data support for the prediction network model. The enhanced network inception module is used to adaptively adjust the parameters of the deep neural network (DNN) prediction model to improve the fitting and tracking ability of the prediction network. At the same time, the introduction of hybrid particle swarm optimization algorithm further enhances the dynamic optimization ability of deep reinforcement learning model parameters and can realize the accurate prediction of short-term load of smart grid. The simulation results show that the mean absolute percentage error e MAPE and root-mean-square error e RMSE of the performance indexes of the prediction model are 10.01% and 2.156 MW, respectively, showing excellent curve fitting ability and load forecasting ability.
{"title":"Short-Term Load Forecasting Method Based on Deep Reinforcement Learning for Smart Grid","authors":"Wei Guo, Kai-Lun Zhang, Xinjie Wei, Mei Liu","doi":"10.1155/2021/8453896","DOIUrl":"https://doi.org/10.1155/2021/8453896","url":null,"abstract":"Short-term load forecasting is an important part to support the planning and operation of power grid, but the current load forecasting methods have the problem of poor adaptive ability of model parameters, which are difficult to ensure the demand for efficient and accurate power grid load forecasting. To solve this problem, a short-term load forecasting method for smart grid is proposed based on multilayer network model. This method uses the integrated empirical mode decomposition (IEMD) method to realize the orderly and reliable load state data and provides high-quality data support for the prediction network model. The enhanced network inception module is used to adaptively adjust the parameters of the deep neural network (DNN) prediction model to improve the fitting and tracking ability of the prediction network. At the same time, the introduction of hybrid particle swarm optimization algorithm further enhances the dynamic optimization ability of deep reinforcement learning model parameters and can realize the accurate prediction of short-term load of smart grid. The simulation results show that the mean absolute percentage error \u0000 \u0000 \u0000 \u0000 e\u0000 \u0000 \u0000 MAPE\u0000 \u0000 \u0000 \u0000 and root-mean-square error \u0000 \u0000 \u0000 \u0000 e\u0000 \u0000 \u0000 RMSE\u0000 \u0000 \u0000 \u0000 of the performance indexes of the prediction model are 10.01% and 2.156 MW, respectively, showing excellent curve fitting ability and load forecasting ability.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"9 9","pages":"8453896:1-8453896:9"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72583746","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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