In order to get sparsity clustering ability of unbalanced cloud data set, combined with adaptive environment density screening, data clustering was carried out, and an improved adaptive environment density peak clustering algorithm under cloud computing technology was proposed. The storage structure model of grid sparse unbalanced cloud data set is constructed, and structure of grid sparse unbalanced cloud data set is reconstructed by combining feature space reconstruction technology. Rough feature quantity of grid sparse unbalanced cloud data set is extracted, and feature extraction and registration are carried out through strict feature registration method. Cloud fusion and peak feature clustering were carried out according to the grid block distribution of the data set. Peak feature quantities of the grid sparse unbalanced cloud data set were extracted, and binary semantic feature distributed detection of the data was carried out.
{"title":"Adaptive Peak Environmental Density Clustering Algorithm in Cloud Computing Technology","authors":"Qiangshan Zhang","doi":"10.4018/jitr.298614","DOIUrl":"https://doi.org/10.4018/jitr.298614","url":null,"abstract":"In order to get sparsity clustering ability of unbalanced cloud data set, combined with adaptive environment density screening, data clustering was carried out, and an improved adaptive environment density peak clustering algorithm under cloud computing technology was proposed. The storage structure model of grid sparse unbalanced cloud data set is constructed, and structure of grid sparse unbalanced cloud data set is reconstructed by combining feature space reconstruction technology. Rough feature quantity of grid sparse unbalanced cloud data set is extracted, and feature extraction and registration are carried out through strict feature registration method. Cloud fusion and peak feature clustering were carried out according to the grid block distribution of the data set. Peak feature quantities of the grid sparse unbalanced cloud data set were extracted, and binary semantic feature distributed detection of the data was carried out.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123435449","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}
Extracting an effective facial feature representation is the critical task for an automatic expression recognition system. Local Binary Pattern (LBP) is known to be a popular texture feature for facial expression recognition. However, only a few approaches utilize the relationship between local neighborhood pixels itself. This paper presents a Hybrid Local Texture Descriptor (HLTD) which is derived from the logical fusion of Local Neighborhood XNOR Patterns (LNXP) and LBP to investigate the potential of positional pixel relationship in automatic emotion recognition. The LNXP encodes texture information based on two nearest vertical and/or horizontal neighboring pixel of the current pixel whereas LBP encodes the center pixel relationship of the neighboring pixel. After logical feature fusion, the Deep Stacked Autoencoder (DSA) is established on the CK+, MMI and KDEF-dyn dataset and the results show that the proposed HLTD based approach outperforms many of the state of art methods with an average recognition rate of 97.5% for CK+, 94.1% for MMI and 88.5% for KDEF.
{"title":"Deep Stacked Autoencoder-Based Automatic Emotion Recognition Using an Efficient Hybrid Local Texture Descriptor","authors":"Shanthi Pitchaiyan, N. Savarimuthu","doi":"10.4018/jitr.2022010103","DOIUrl":"https://doi.org/10.4018/jitr.2022010103","url":null,"abstract":"Extracting an effective facial feature representation is the critical task for an automatic expression recognition system. Local Binary Pattern (LBP) is known to be a popular texture feature for facial expression recognition. However, only a few approaches utilize the relationship between local neighborhood pixels itself. This paper presents a Hybrid Local Texture Descriptor (HLTD) which is derived from the logical fusion of Local Neighborhood XNOR Patterns (LNXP) and LBP to investigate the potential of positional pixel relationship in automatic emotion recognition. The LNXP encodes texture information based on two nearest vertical and/or horizontal neighboring pixel of the current pixel whereas LBP encodes the center pixel relationship of the neighboring pixel. After logical feature fusion, the Deep Stacked Autoencoder (DSA) is established on the CK+, MMI and KDEF-dyn dataset and the results show that the proposed HLTD based approach outperforms many of the state of art methods with an average recognition rate of 97.5% for CK+, 94.1% for MMI and 88.5% for KDEF.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129184112","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}
Xiangzhen He, Shengyin Zhu, Yihao Zhang, Yerong Hu, Dengyun Zhu, Xiaoyu Liu, F. Wan
Most of the traditional face modeling methods adopt the parameter-based method to construct, but the face model constructed by this method is too smooth and ignores the detailed features of the face. To solve this problem, a virtual face modeling method based on 3D motion capture data is proposed in this paper. In order to improve the deformation method for the realistic modeling purpose, this paper divides the modeling process of personalized face into two parts: overall modification and local deformation. The overall deformation modifies the facial shape and the position of the facial features of Maya universal model; Based on the principle of radial basis function interpolation algorithm, a smooth interpolation function is constructed, and the new position coordinates of non-characteristic points are obtained by solving the linear equations, so that they are more in line with the physiological characteristics of human faces. The end result is a more realistic virtual face that you model.
{"title":"Research on Photorealistic Virtual Face Modeling","authors":"Xiangzhen He, Shengyin Zhu, Yihao Zhang, Yerong Hu, Dengyun Zhu, Xiaoyu Liu, F. Wan","doi":"10.4018/jitr.299949","DOIUrl":"https://doi.org/10.4018/jitr.299949","url":null,"abstract":"Most of the traditional face modeling methods adopt the parameter-based method to construct, but the face model constructed by this method is too smooth and ignores the detailed features of the face. To solve this problem, a virtual face modeling method based on 3D motion capture data is proposed in this paper. In order to improve the deformation method for the realistic modeling purpose, this paper divides the modeling process of personalized face into two parts: overall modification and local deformation. The overall deformation modifies the facial shape and the position of the facial features of Maya universal model; Based on the principle of radial basis function interpolation algorithm, a smooth interpolation function is constructed, and the new position coordinates of non-characteristic points are obtained by solving the linear equations, so that they are more in line with the physiological characteristics of human faces. The end result is a more realistic virtual face that you model.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127736750","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}
With the increasing adoption of serverless computing, there is a need for a benchmark. The aim of this paper is to present such a benchmark based on performance and usability testing to better understand serverless services as well as help practitioners to select between two major clouds, namely, Amazon and Azure. Jmeter tool and system usability scale are used to conduct performance and usability testing, respectively. In addition, a replication package is provided to increase the validity and reliability of the results. The main findings revealed that the serverless platforms are different in their architecture. Even though both of them support the same serverless concept, they differ considerably in structure, development, and creations of services. Overall, both the cloud vendors under study provide the same core capabilities one would expect but, there are some differences too. In particular, usability could be improved to extend the market and capture more customers.
{"title":"Benchmarking Serverless Computing: Performance and Usability","authors":"Mubashra Sadaqat, Mary-Luz Sánchez-Gordón, Ricardo Colomo Palacios","doi":"10.4018/jitr.299374","DOIUrl":"https://doi.org/10.4018/jitr.299374","url":null,"abstract":"With the increasing adoption of serverless computing, there is a need for a benchmark. The aim of this paper is to present such a benchmark based on performance and usability testing to better understand serverless services as well as help practitioners to select between two major clouds, namely, Amazon and Azure. Jmeter tool and system usability scale are used to conduct performance and usability testing, respectively. In addition, a replication package is provided to increase the validity and reliability of the results. The main findings revealed that the serverless platforms are different in their architecture. Even though both of them support the same serverless concept, they differ considerably in structure, development, and creations of services. Overall, both the cloud vendors under study provide the same core capabilities one would expect but, there are some differences too. In particular, usability could be improved to extend the market and capture more customers.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114442191","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}
F. Oladeji, J. A. Balogun, T. Aderounmu, T. Omodunbi, P. Idowu
This study formulated a model for assessing the risk of coronavirus disease (COVID-19) based on variables associated with the spread of COVID-19 infections. The study used the Mamdani fuzzy logic model based on a multiple input and single output (MISO) scheme which required 12 inputs and 1 output variable. Each of the input variables was identified using binary values, namely: No and Yes while the spread of COVID-19 was assessed using four nominal linguistic values. Two triangular membership functions were used to formulate each associated variable and four triangular membership functions to formulate the spread of COVID-19 using specific crisp intervals. The results of the study showed that 4096 rules were inferred from the possible combination of the binary linguistic values of the associated variables for the assessment of the spread of COVID-19. The study concluded that knowledge about variables associated with the spread of COVID-19 infection can be adopted for supporting decision-making which affects the assessment of the spread of COVID-19 by stakeholders.
{"title":"Prognostic Model for the Risk of Coronavirus Disease (COVID-19) Using Fuzzy Logic Modeling","authors":"F. Oladeji, J. A. Balogun, T. Aderounmu, T. Omodunbi, P. Idowu","doi":"10.4018/jitr.299378","DOIUrl":"https://doi.org/10.4018/jitr.299378","url":null,"abstract":"This study formulated a model for assessing the risk of coronavirus disease (COVID-19) based on variables associated with the spread of COVID-19 infections. The study used the Mamdani fuzzy logic model based on a multiple input and single output (MISO) scheme which required 12 inputs and 1 output variable. Each of the input variables was identified using binary values, namely: No and Yes while the spread of COVID-19 was assessed using four nominal linguistic values. Two triangular membership functions were used to formulate each associated variable and four triangular membership functions to formulate the spread of COVID-19 using specific crisp intervals. The results of the study showed that 4096 rules were inferred from the possible combination of the binary linguistic values of the associated variables for the assessment of the spread of COVID-19. The study concluded that knowledge about variables associated with the spread of COVID-19 infection can be adopted for supporting decision-making which affects the assessment of the spread of COVID-19 by stakeholders.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114794908","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}
Asymptomatic patients (AP) travel through neighborhoods in communities. The mobility dynamics of the AP makes it hard to tag them with specific interests. The lack of efficient monitoring systems can enable the AP to infect several vulnerable people in the communities. This article studied the monitoring of AP through their mobility and trajectory towards reducing the stress of socio-economic complications in the case of pandemics. Mobility and Trajectory based Technique for Monitoring Asymptomatic Patients (MTT-MAP) was established. The time-ordered spatial and temporal trajectory records of the AP were captured through their activities. A grid-based index data structure was designed based on network topology, graph theory and trajectory analysis to cater for the continuous monitoring of the AP over time. Also, concurrent object localisation and recognition, branch and bound, and multi-object instance strategies were adopted. The MTT-MAP has shown efficient when experimented with GeoLife dataset and can be integrated with state-of-the-art patients monitoring systems.
{"title":"Mobility and Trajectory-Based Technique for Monitoring Asymptomatic Patients","authors":"D. Adu-Gyamfi, Fengli Zhang","doi":"10.4018/jitr.2022010109","DOIUrl":"https://doi.org/10.4018/jitr.2022010109","url":null,"abstract":"Asymptomatic patients (AP) travel through neighborhoods in communities. The mobility dynamics of the AP makes it hard to tag them with specific interests. The lack of efficient monitoring systems can enable the AP to infect several vulnerable people in the communities. This article studied the monitoring of AP through their mobility and trajectory towards reducing the stress of socio-economic complications in the case of pandemics. Mobility and Trajectory based Technique for Monitoring Asymptomatic Patients (MTT-MAP) was established. The time-ordered spatial and temporal trajectory records of the AP were captured through their activities. A grid-based index data structure was designed based on network topology, graph theory and trajectory analysis to cater for the continuous monitoring of the AP over time. Also, concurrent object localisation and recognition, branch and bound, and multi-object instance strategies were adopted. The MTT-MAP has shown efficient when experimented with GeoLife dataset and can be integrated with state-of-the-art patients monitoring systems.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124815686","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}
Instructors often experience difficulties in selecting and sequencing relevant content for deployment into learning management systems. Human error and subjectivity is apparent. This study focuses on integrating learning management systems and massive open online courses with the goal of eliminating the human element in uploading content. As far as data sharing is concerned, learning management systems and massive open online courses have known weaknesses. The proposed integration aims to reach a tradeoff between the two systems. A requirements elicitation exercise was conducted towards identification of the component units of a hybrid system. The study utilized a mixed method approach to realize the foundation of the integrated design model. The findings, based on evaluation, showed that experts established completeness of the software design model. They, however, expressed the need for the designs to be extended towards accommodating artificial intelligence features. The proposed designs, thus, present a baseline framework upon which implementation considerations may be built on.
{"title":"A Software Design Model for Integrating LMS and MOOCs","authors":"Talent T. Rugube, C. Chibaya, D. Govender","doi":"10.4018/jitr.299375","DOIUrl":"https://doi.org/10.4018/jitr.299375","url":null,"abstract":"Instructors often experience difficulties in selecting and sequencing relevant content for deployment into learning management systems. Human error and subjectivity is apparent. This study focuses on integrating learning management systems and massive open online courses with the goal of eliminating the human element in uploading content. As far as data sharing is concerned, learning management systems and massive open online courses have known weaknesses. The proposed integration aims to reach a tradeoff between the two systems. A requirements elicitation exercise was conducted towards identification of the component units of a hybrid system. The study utilized a mixed method approach to realize the foundation of the integrated design model. The findings, based on evaluation, showed that experts established completeness of the software design model. They, however, expressed the need for the designs to be extended towards accommodating artificial intelligence features. The proposed designs, thus, present a baseline framework upon which implementation considerations may be built on.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131357564","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 structure and composition of the worldwide mobility infrastructure is growing exponentially and urgently needs to reduce the emission of carbon dioxide gas, to decrease the growing of traffic jam, to limit the over-abundancy traffic signs, and to improve the interoperability of traffic sign between different countries. First, this paper proposes a new mobility paradigm to organize in a global way the mobility based on three arising technology characteristics: high-performance computing efficiency, geo-positioning accuracy and 5G technology. Second, the paper proposes a cluster based approach for managing the mobility of (autonomous-)vehicles in the frame of that new paradigm and propose a set of usage scenarios. Finally, some basic tool are presented in order to implement machine learning based clustering step of the approach.
{"title":"Cluster-Based Vehicle Routing on Road Segments in Dematerialised Traffic Infrastructures","authors":"C. Feltus","doi":"10.4018/jitr.299373","DOIUrl":"https://doi.org/10.4018/jitr.299373","url":null,"abstract":"The structure and composition of the worldwide mobility infrastructure is growing exponentially and urgently needs to reduce the emission of carbon dioxide gas, to decrease the growing of traffic jam, to limit the over-abundancy traffic signs, and to improve the interoperability of traffic sign between different countries. First, this paper proposes a new mobility paradigm to organize in a global way the mobility based on three arising technology characteristics: high-performance computing efficiency, geo-positioning accuracy and 5G technology. Second, the paper proposes a cluster based approach for managing the mobility of (autonomous-)vehicles in the frame of that new paradigm and propose a set of usage scenarios. Finally, some basic tool are presented in order to implement machine learning based clustering step of the approach.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115089150","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}
Asim Iftikhar, Shahrulniza Musa, M. Alam, Rizwan Ahmed, M. M. Su’ud, L. Khan, Syed Mubashir Ali
Software development through teams at different geographical locations is a trend of modern era, which is not only producing good results without costing lot of money but also productive in relation to its cost, low risk and high return. This shift of perception of working in a group rather than alone is getting stronger day by day and has become an important planning tool and part of their business strategy. In this research classification approaches like SVM and K-NN have been implemented to classify the true positive events of global software development project risk according to Time, Cost and Resource. Comparative analysis has also been performed between these two algorithms to determine the highest accuracy algorithms. Results proved that Support Vector Machine (SVM) performed very well in case of Cost Related Risk and Resource Related Risk. Whereas, KNN is found superior to SVM for Time Related Risk.
{"title":"Risk Classification in Global Software Development Using a Machine Learning Approach: A Result Comparison of Support Vector Machine and K-Nearest Neighbor Algorithms","authors":"Asim Iftikhar, Shahrulniza Musa, M. Alam, Rizwan Ahmed, M. M. Su’ud, L. Khan, Syed Mubashir Ali","doi":"10.4018/jitr.299385","DOIUrl":"https://doi.org/10.4018/jitr.299385","url":null,"abstract":"Software development through teams at different geographical locations is a trend of modern era, which is not only producing good results without costing lot of money but also productive in relation to its cost, low risk and high return. This shift of perception of working in a group rather than alone is getting stronger day by day and has become an important planning tool and part of their business strategy. In this research classification approaches like SVM and K-NN have been implemented to classify the true positive events of global software development project risk according to Time, Cost and Resource. Comparative analysis has also been performed between these two algorithms to determine the highest accuracy algorithms. Results proved that Support Vector Machine (SVM) performed very well in case of Cost Related Risk and Resource Related Risk. Whereas, KNN is found superior to SVM for Time Related Risk.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"602 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134462244","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}
Prior studies have found that mobile cloud computing could bring substantial cost savings to firms, ultimately resulting in reduced transaction cost to customers. Despite this, financial firms in Fiji are slow adopters of mobile cloud computing. The study identifies the challenges faced by financial firms in the adoption of mobile cloud computing to advance the literature on innovation adoption with evidence from a unique context – a Pacific island country. The context is important as the issues are likely to be similar in other developing and remote island countries but the extant research is largely confined to developed countries. Our findings suggest that the lack of mobile cloud computing policy, infrastructure constraints, and security constraints, among others are the main barriers to the adoption thereof. The study contributes by presenting a revised model based on factors that emerged from the study.
{"title":"Determinants of Mobile Cloud Computing Adoption by Financial Services Firms","authors":"M. Sathye, Sam Goundar, Akashdeep Bhardwaj","doi":"10.4018/jitr.299921","DOIUrl":"https://doi.org/10.4018/jitr.299921","url":null,"abstract":"Prior studies have found that mobile cloud computing could bring substantial cost savings to firms, ultimately resulting in reduced transaction cost to customers. Despite this, financial firms in Fiji are slow adopters of mobile cloud computing. The study identifies the challenges faced by financial firms in the adoption of mobile cloud computing to advance the literature on innovation adoption with evidence from a unique context – a Pacific island country. The context is important as the issues are likely to be similar in other developing and remote island countries but the extant research is largely confined to developed countries. Our findings suggest that the lack of mobile cloud computing policy, infrastructure constraints, and security constraints, among others are the main barriers to the adoption thereof. The study contributes by presenting a revised model based on factors that emerged from the study.","PeriodicalId":296080,"journal":{"name":"J. Inf. Technol. Res.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133003503","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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