The masterly lesson, tedious and lacking in motivation for today's university students, provokes a passive attitude from them in the classroom. If they also use their mobile phones to escape from the classroom, the situation seems to get worse. Low attendance rates and poor academic results are some of the consequences of a serious problem: the lack of commitment of students to their learning process. Incorporating elements of games, together with new technologies, may be a possible solution. Thus, in the academic year 2018/2019 the classes of the subject Operations Management II taught throughout the fourth year of Business Administration and Management Degree offered by the University of Cadiz were gamified with Kahoot! The students felt more motivated and their grades improved in comparison to the previous year. In addition, a comparison was made with the results shown in the exams of the academic year after the gamified activity.
{"title":"Gamification of University Subjects: A Case Study for Operations Management","authors":"M. Río, Vanessa Rodríguez Cornejo, Margarita Ruiz Rodríguez, Jaime Sánchez Ortiz","doi":"10.4018/JITR.2021040101","DOIUrl":"https://doi.org/10.4018/JITR.2021040101","url":null,"abstract":"The masterly lesson, tedious and lacking in motivation for today's university students, provokes a passive attitude from them in the classroom. If they also use their mobile phones to escape from the classroom, the situation seems to get worse. Low attendance rates and poor academic results are some of the consequences of a serious problem: the lack of commitment of students to their learning process. Incorporating elements of games, together with new technologies, may be a possible solution. Thus, in the academic year 2018/2019 the classes of the subject Operations Management II taught throughout the fourth year of Business Administration and Management Degree offered by the University of Cadiz were gamified with Kahoot! The students felt more motivated and their grades improved in comparison to the previous year. In addition, a comparison was made with the results shown in the exams of the academic year after the gamified activity.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130354212","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}
Testing of software requires a great amount of time and effort. The tester's main aim is to design optimized test sequences with a minimum amount of time, effort, and with less redundancy. Testers have used artificial intelligence meta-heuristic algorithms for optimization of test sequences. The model-driven approach is helpful in the generation of test sequences at early designing phase only. The model-driven approach uses UML diagram to represent the system's behavior and design test cases for the system at design stage of software development life cycle. The proposed approach uses natural river system for optimizing favourable non-redundant test path sequences using UML activity diagrams and sequence diagrams. The implementation of proposed approach has been done using python and results show that the proposed approach provides full coverage of test paths with less redundant test nodes compared to other meta heuristic algorithms.
{"title":"Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm","authors":"Nisha Rathee, R. S. Chhillar","doi":"10.4018/JITR.2021040105","DOIUrl":"https://doi.org/10.4018/JITR.2021040105","url":null,"abstract":"Testing of software requires a great amount of time and effort. The tester's main aim is to design optimized test sequences with a minimum amount of time, effort, and with less redundancy. Testers have used artificial intelligence meta-heuristic algorithms for optimization of test sequences. The model-driven approach is helpful in the generation of test sequences at early designing phase only. The model-driven approach uses UML diagram to represent the system's behavior and design test cases for the system at design stage of software development life cycle. The proposed approach uses natural river system for optimizing favourable non-redundant test path sequences using UML activity diagrams and sequence diagrams. The implementation of proposed approach has been done using python and results show that the proposed approach provides full coverage of test paths with less redundant test nodes compared to other meta heuristic algorithms.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124060555","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}
In a rapidly growing industry like telecommunications, customer churn prediction is a crucial challenge affecting the sustainability of the business as a whole. The fact that retaining a customer is more profitable than acquiring new customers is important to predict potential churners and present them with offers to prevent them from churning. This work presents a stacked CLV-based heuristic incorporated ensemble (SCHIE) to enable identification of potential churners so as to provide them with offers that can eventually aid in retaining them. The proposed model is composed of two levels of prediction followed by a recommendation to reduce customer churn. The first level involves identifying effective models to predict potential churners. This is followed by result segregation, CLV-based prediction, and user shortlisting for offers. Experimental results indicate high efficiencies in predicting potential churners and non-churners. The proposed model is found to reduce the overall loss by up to 50% in comparison to state-of-the-art models.
{"title":"Enhanced Churn Prediction Using Stacked Heuristic Incorporated Ensemble Model","authors":"Sivasankar Karuppaiah, N. Gopalan","doi":"10.4018/JITR.2021040109","DOIUrl":"https://doi.org/10.4018/JITR.2021040109","url":null,"abstract":"In a rapidly growing industry like telecommunications, customer churn prediction is a crucial challenge affecting the sustainability of the business as a whole. The fact that retaining a customer is more profitable than acquiring new customers is important to predict potential churners and present them with offers to prevent them from churning. This work presents a stacked CLV-based heuristic incorporated ensemble (SCHIE) to enable identification of potential churners so as to provide them with offers that can eventually aid in retaining them. The proposed model is composed of two levels of prediction followed by a recommendation to reduce customer churn. The first level involves identifying effective models to predict potential churners. This is followed by result segregation, CLV-based prediction, and user shortlisting for offers. Experimental results indicate high efficiencies in predicting potential churners and non-churners. The proposed model is found to reduce the overall loss by up to 50% in comparison to state-of-the-art models.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128776376","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}
By understanding the function of each protein encoded in genome, the molecular mechanism of the cell can be recognized. In genome annotation field, several methods or techniques have been developed to locate or predict the patterns of genes in genome sequence. However, recognizing corresponding gene of a given protein sequence using conventional tools is inherently complicated and error prone. This paper first focuses on the issue of gene prediction and its challenges. The authors then present a novel method for identifying genes that involves a two-step process. First the research presents new features extracted from protein sequences using a position specific scoring matrix (PSSM). The PSSM profiles are converted into uniform numeric representation. Then, a new structured approach has been applied on PSSM vector which uses a decision tree-based technique for obtaining rules. Finally, the rules of single class are joined together to form a matrix which is then given as an input to SVM for classification purpose. The rules derived from algorithm correspond to genes. The authors also introduce another approach for predicting genes based on PSSM using SVM. Both the methods have been implemented on genome DNAset dataset. Empirical evaluation shows that PSSM based SAFARI approach produces better results.
{"title":"Novel PSSM-Based Approaches for Gene Identification Using Support Vector Machine","authors":"Heena Farooq Bhat, M. Wani","doi":"10.4018/JITR.2021040108","DOIUrl":"https://doi.org/10.4018/JITR.2021040108","url":null,"abstract":"By understanding the function of each protein encoded in genome, the molecular mechanism of the cell can be recognized. In genome annotation field, several methods or techniques have been developed to locate or predict the patterns of genes in genome sequence. However, recognizing corresponding gene of a given protein sequence using conventional tools is inherently complicated and error prone. This paper first focuses on the issue of gene prediction and its challenges. The authors then present a novel method for identifying genes that involves a two-step process. First the research presents new features extracted from protein sequences using a position specific scoring matrix (PSSM). The PSSM profiles are converted into uniform numeric representation. Then, a new structured approach has been applied on PSSM vector which uses a decision tree-based technique for obtaining rules. Finally, the rules of single class are joined together to form a matrix which is then given as an input to SVM for classification purpose. The rules derived from algorithm correspond to genes. The authors also introduce another approach for predicting genes based on PSSM using SVM. Both the methods have been implemented on genome DNAset dataset. Empirical evaluation shows that PSSM based SAFARI approach produces better results.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"526 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127631440","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}
A. Saif, Md. Akib Shahriar Khan, Abir Mohammad Hadi, Rahul Proshad Karmoker, Joy Julian Gomes
Recent years have seen a rise in the use of various machine learning techniques in computer vision, particularly in posing feature-based human action recognition which includes convolutional neural networks (CNN) and recurrent neural network (RNN). CNN-based methods are useful in recognizing human actions for combined motions (i.e., standing up, hand shaking, walking). However, in case of uncertainty of camera motion, occlusion, and multiple people, CNN suppresses important feature information and is not efficient enough to recognize variations for human action. Besides, RNN with long short-term memory (LSTM) requires more computational power to retain memories to classify human actions. This research proposes an extended framework based on capsule network using silhouette pose features to recognize human actions. Proposed extended framework achieved high accuracy of 95.64% which is higher than previous research methodology. Extensive experimental validation of the proposed extended framework reveals efficiency which is expected to contribute significantly in action recognition research.
{"title":"Silhouette Pose Feature-Based Human Action Classification Using Capsule Network","authors":"A. Saif, Md. Akib Shahriar Khan, Abir Mohammad Hadi, Rahul Proshad Karmoker, Joy Julian Gomes","doi":"10.4018/JITR.2021040106","DOIUrl":"https://doi.org/10.4018/JITR.2021040106","url":null,"abstract":"Recent years have seen a rise in the use of various machine learning techniques in computer vision, particularly in posing feature-based human action recognition which includes convolutional neural networks (CNN) and recurrent neural network (RNN). CNN-based methods are useful in recognizing human actions for combined motions (i.e., standing up, hand shaking, walking). However, in case of uncertainty of camera motion, occlusion, and multiple people, CNN suppresses important feature information and is not efficient enough to recognize variations for human action. Besides, RNN with long short-term memory (LSTM) requires more computational power to retain memories to classify human actions. This research proposes an extended framework based on capsule network using silhouette pose features to recognize human actions. Proposed extended framework achieved high accuracy of 95.64% which is higher than previous research methodology. Extensive experimental validation of the proposed extended framework reveals efficiency which is expected to contribute significantly in action recognition research.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133849051","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}
This paper proposes to create an augmented reality interface for the visually impaired, enabling a way of haptically interacting with the computer system by creating a virtual workstation, facilitating a natural and intuitive way to accomplish a multitude of computer-based tasks (such as emailing, word processing, storing and retrieving files from the computer, making a phone call, searching the web, etc.). The proposed system utilizes a combination of a haptic glove device, a gesture-based control system, and an augmented reality computer interface which creates an immersive interaction between the blind user and the computer. The gestures are recognized, and the user is provided with audio and vibratory haptic feedbacks. This user interface allows the user to actually “touch, feel, and physically interact” with digital controls and virtual real estate of a computer system. A test of applicability was conducted which showcased promising positive results.
{"title":"Gesture Controlled Tactile Augmented Reality Interface for the Visually Impaired","authors":"Siddharth Kalra, Sarika Jain, Amit Agarwal","doi":"10.4018/JITR.2021040107","DOIUrl":"https://doi.org/10.4018/JITR.2021040107","url":null,"abstract":"This paper proposes to create an augmented reality interface for the visually impaired, enabling a way of haptically interacting with the computer system by creating a virtual workstation, facilitating a natural and intuitive way to accomplish a multitude of computer-based tasks (such as emailing, word processing, storing and retrieving files from the computer, making a phone call, searching the web, etc.). The proposed system utilizes a combination of a haptic glove device, a gesture-based control system, and an augmented reality computer interface which creates an immersive interaction between the blind user and the computer. The gestures are recognized, and the user is provided with audio and vibratory haptic feedbacks. This user interface allows the user to actually “touch, feel, and physically interact” with digital controls and virtual real estate of a computer system. A test of applicability was conducted which showcased promising positive results.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134185313","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}
Modern businesses and jobs in demand have witnessed the requirement of programming skills in candidates, for example, business analyst, database administrator, software engineer, software developer, and many more. Programming courses are a very influential and important part of forming the future of the IT industry. Throughout the recent years, a substantial amount of research has been conducted to improve the programming novices, but the problems are returning in every new generation and reporting high failure rates. The dataset used in this study is the ‘CodeChef competition' dataset and the ‘Coursera' dataset. Firstly, this research work conducts the preview analysis to understand the performance of learners in programming languages. Secondly, this work proposes a clear rationale between the popularity of MOOC courses and low completion rates. There is increasingly high enrolment in MOOC courses but with non-ideal completion rates. Finally, it builds the machine learning model and validates the accuracy of the trained model.
{"title":"Predicting the Efficiency and Success Rate of Programming Courses in MOOC Using Machine Learning Approach for Future Employment in the IT Industry","authors":"Shivangi Gupta, A. Sabitha, S. Chowdhary","doi":"10.4018/JITR.2021040102","DOIUrl":"https://doi.org/10.4018/JITR.2021040102","url":null,"abstract":"Modern businesses and jobs in demand have witnessed the requirement of programming skills in candidates, for example, business analyst, database administrator, software engineer, software developer, and many more. Programming courses are a very influential and important part of forming the future of the IT industry. Throughout the recent years, a substantial amount of research has been conducted to improve the programming novices, but the problems are returning in every new generation and reporting high failure rates. The dataset used in this study is the ‘CodeChef competition' dataset and the ‘Coursera' dataset. Firstly, this research work conducts the preview analysis to understand the performance of learners in programming languages. Secondly, this work proposes a clear rationale between the popularity of MOOC courses and low completion rates. There is increasingly high enrolment in MOOC courses but with non-ideal completion rates. Finally, it builds the machine learning model and validates the accuracy of the trained model.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123654261","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 deployment of acoustic sensor nodes in 3-D underwater acoustic wireless sensor networks (UAWSN) is a difficult task due to various aquatic conditions and physical obstacles. This work proposes multi-agent-based acoustic sensor node deployment (MASD) to deploy the acoustic nodes at ideal positions to enhance coverage and seamless connectivity. The proposed scheme works is threefold: 1) AUV initiates random walk in the network to gather the information and prospective common reference points; 2) the base station gets this information through surface buoys and computes the routing path, feasible locations for deploying new nodes; and 3) AUV collects this information and follows the path to deploy nodes with the help of agents. The multi-agent-enabled deployment framework (MADF) is proposed to support the deployment process at each level of the proposed MASD scheme. The performance of propagation loss, coverage, and overhead tradeoffs are analyzed to validate the proposed scheme. Mobility issues can be further re-investigated in shallow water as a future direction to the MASD scheme.
{"title":"Multi-Agent-Based Acoustic Sensor Node Deployment in Underwater Acoustic Wireless Sensor Networks","authors":"B. S. Halakarnimath, A. Sutagundar","doi":"10.4018/jitr.2020100109","DOIUrl":"https://doi.org/10.4018/jitr.2020100109","url":null,"abstract":"The deployment of acoustic sensor nodes in 3-D underwater acoustic wireless sensor networks (UAWSN) is a difficult task due to various aquatic conditions and physical obstacles. This work proposes multi-agent-based acoustic sensor node deployment (MASD) to deploy the acoustic nodes at ideal positions to enhance coverage and seamless connectivity. The proposed scheme works is threefold: 1) AUV initiates random walk in the network to gather the information and prospective common reference points; 2) the base station gets this information through surface buoys and computes the routing path, feasible locations for deploying new nodes; and 3) AUV collects this information and follows the path to deploy nodes with the help of agents. The multi-agent-enabled deployment framework (MADF) is proposed to support the deployment process at each level of the proposed MASD scheme. The performance of propagation loss, coverage, and overhead tradeoffs are analyzed to validate the proposed scheme. Mobility issues can be further re-investigated in shallow water as a future direction to the MASD scheme.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128314417","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}
This paper proposed a reversible medical image watermarking scheme using multiple histogram modification (MHM) and redundant discrete wavelet transform (RDWT). The MHM was introduced to the proposed scheme to enhance the embedding capacity. By embedding the watermark in the RDWT coefficients, the proposed scheme exploited the visual masking property of RDWT to guarantee the visual quality. Also, the proposed scheme has better performance on embedding capacity because the RDWT has several sub-band coefficients for embedding. The experimental results on medical images suggests that the proposed scheme could meet the demand of perceptional quality with better embedding capacity than former schemes.
{"title":"Reversible Watermarking in Medical Images Using Sub-Sample and Multiple Histogram Modification","authors":"Lin Gao, Yun-jin Zhang, Guoyan Li","doi":"10.4018/jitr.2020100106","DOIUrl":"https://doi.org/10.4018/jitr.2020100106","url":null,"abstract":"This paper proposed a reversible medical image watermarking scheme using multiple histogram modification (MHM) and redundant discrete wavelet transform (RDWT). The MHM was introduced to the proposed scheme to enhance the embedding capacity. By embedding the watermark in the RDWT coefficients, the proposed scheme exploited the visual masking property of RDWT to guarantee the visual quality. Also, the proposed scheme has better performance on embedding capacity because the RDWT has several sub-band coefficients for embedding. The experimental results on medical images suggests that the proposed scheme could meet the demand of perceptional quality with better embedding capacity than former schemes.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127265573","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}
M. Winterhagen, Munir M. Salman, M. Then, B. Wallenborn, Tobias Neuber, D. Heutelbeck, Michael Fuchs, M. Hemmje
E-learning standards like learning tools interoperability can support at realizing innovative learning scenarios in distributed architectures. A learning tools interoperability connection between a learning management system and a gaming platform offers possibilities like embedding a game into an online course and sending player-specific data back to the learning management system. This allows for a new and data-driven evaluation of students' individual learning performances, especially for alternative methods like qualifications-based learning. The learning tools interoperability-specified mechanisms can also be applied for implementing functionality to exchange students' competence profiles and traces within a knowledge-management eco-system portal that provides a toolkit for creating competence-based games that meet the requirements of qualifications-based learning as well as tools for creating game-specific analytics. As a first result, the authors made a prototypical implementation with a serious game prototype based on the unity game engine and unity analytics as analysis platform.
{"title":"LTI-Connections Between Learning Management Systems and Gaming Platforms: Integrating a Serious-Game Prototype Into Moodle Courses","authors":"M. Winterhagen, Munir M. Salman, M. Then, B. Wallenborn, Tobias Neuber, D. Heutelbeck, Michael Fuchs, M. Hemmje","doi":"10.4018/jitr.2020100104","DOIUrl":"https://doi.org/10.4018/jitr.2020100104","url":null,"abstract":"E-learning standards like learning tools interoperability can support at realizing innovative learning scenarios in distributed architectures. A learning tools interoperability connection between a learning management system and a gaming platform offers possibilities like embedding a game into an online course and sending player-specific data back to the learning management system. This allows for a new and data-driven evaluation of students' individual learning performances, especially for alternative methods like qualifications-based learning. The learning tools interoperability-specified mechanisms can also be applied for implementing functionality to exchange students' competence profiles and traces within a knowledge-management eco-system portal that provides a toolkit for creating competence-based games that meet the requirements of qualifications-based learning as well as tools for creating game-specific analytics. As a first result, the authors made a prototypical implementation with a serious game prototype based on the unity game engine and unity analytics as analysis platform.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129121267","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：