Pub Date : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664758
Mokhtar A. Al-Awadhi, R. Deshmukh
Honey botanical origin classification is essential to honey authentication and honey botanical origin mislabeling prevention. Recently, several researchers have used advanced analytical techniques for classifying honey floral sources. These methods have incorporated different acquisition technologies and machine learning (ML) models. In this paper, we review state-of-the-art approaches for classifying honey botanical sources. We discuss the various technologies used for measuring honey constituents, honey physical and chemical properties, and technologies for capturing honey spatial and spectral data. Also, we discuss the ML techniques and their classification performances. We give recommendations for future work at the end of this paper.
{"title":"A Review on Automatic Classification of Honey Botanical Origins using Machine Learning","authors":"Mokhtar A. Al-Awadhi, R. Deshmukh","doi":"10.1109/MTICTI53925.2021.9664758","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664758","url":null,"abstract":"Honey botanical origin classification is essential to honey authentication and honey botanical origin mislabeling prevention. Recently, several researchers have used advanced analytical techniques for classifying honey floral sources. These methods have incorporated different acquisition technologies and machine learning (ML) models. In this paper, we review state-of-the-art approaches for classifying honey botanical sources. We discuss the various technologies used for measuring honey constituents, honey physical and chemical properties, and technologies for capturing honey spatial and spectral data. Also, we discuss the ML techniques and their classification performances. We give recommendations for future work at the end of this paper.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"25 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125675484","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664756
Khadeeja Sabah Jasim, Khattab M. Ali Alheeti, Abdul Kareem A. Najem Alaloosy
Unmanned aerial vehicles, also called drones, are small vehicles that fly in the sky and do multiple functions in many areas of life such as industry, agriculture, order delivery, media, and military applications. This paper aims to survey the earlier studies of UAVs’ security communications and a quick overview of Flying Ad Hoc Network (FANET) Routing Protocols and Attacks. Finally, the results of previous studies are summarized, compared and discussed.
{"title":"A Review Paper on Secure Communications in FANET","authors":"Khadeeja Sabah Jasim, Khattab M. Ali Alheeti, Abdul Kareem A. Najem Alaloosy","doi":"10.1109/MTICTI53925.2021.9664756","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664756","url":null,"abstract":"Unmanned aerial vehicles, also called drones, are small vehicles that fly in the sky and do multiple functions in many areas of life such as industry, agriculture, order delivery, media, and military applications. This paper aims to survey the earlier studies of UAVs’ security communications and a quick overview of Flying Ad Hoc Network (FANET) Routing Protocols and Attacks. Finally, the results of previous studies are summarized, compared and discussed.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124536869","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664779
Basel A. Dabwan, M. Jadhav
There are more than 466 million people with hearing disabilities in the world. Those people need to communicate with others, get learning and interact with activities around them. Sign language is the bridge to eliminate the gap between them and other people. Developing an automatic system to recognize sign language has a lot of challenges, especially for Yemeni sign language, as there are very few researches touching on this language. In this paper, we propose a new Convolution Neural Network based model for classifying the sign language of Yemen. The System was trained and tested using a dataset that includes 16,192 images gathered from 40 people with different distances and variations. The proposed model uses pre-processing methods to remove noises and reposition the images, etc. The results display that the proposed model achieved 94% accuracy.
{"title":"A Deep Learning based Recognition System for Yemeni Sign Language","authors":"Basel A. Dabwan, M. Jadhav","doi":"10.1109/MTICTI53925.2021.9664779","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664779","url":null,"abstract":"There are more than 466 million people with hearing disabilities in the world. Those people need to communicate with others, get learning and interact with activities around them. Sign language is the bridge to eliminate the gap between them and other people. Developing an automatic system to recognize sign language has a lot of challenges, especially for Yemeni sign language, as there are very few researches touching on this language. In this paper, we propose a new Convolution Neural Network based model for classifying the sign language of Yemen. The System was trained and tested using a dataset that includes 16,192 images gathered from 40 people with different distances and variations. The proposed model uses pre-processing methods to remove noises and reposition the images, etc. The results display that the proposed model achieved 94% accuracy.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114722151","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664766
Ehsan Salajegheh, H. Daealhaq, Shahaboddin Seddighi, Ali Mojarrad Ghahfarokhi, Fatemehalsadat Beheshtinejad, Hossein Mirzanejad
In this paper, we have studied actuator hysteresis compensation using dither input for robotics and automation systems. To mathematically model hysteresis, we have used the Bouc-Wen model, which is common in engineering fields, to represent the nonlinear behavior of hysteresis. We have used square dither to reduce nonlinear distortion caused by system actuator hysteresis. Under the control system is an integrator and the controller is a proportional type. We have reached an optimum hysteresis control by minimizing a cost function, including all required parameters. According to simulation results, we have shown that tracking will be performed well with appropriate amplitude and frequency of square dither.
{"title":"Optimal Compensation of Bouc-Wen model hysteresis using square dither","authors":"Ehsan Salajegheh, H. Daealhaq, Shahaboddin Seddighi, Ali Mojarrad Ghahfarokhi, Fatemehalsadat Beheshtinejad, Hossein Mirzanejad","doi":"10.1109/MTICTI53925.2021.9664766","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664766","url":null,"abstract":"In this paper, we have studied actuator hysteresis compensation using dither input for robotics and automation systems. To mathematically model hysteresis, we have used the Bouc-Wen model, which is common in engineering fields, to represent the nonlinear behavior of hysteresis. We have used square dither to reduce nonlinear distortion caused by system actuator hysteresis. Under the control system is an integrator and the controller is a proportional type. We have reached an optimum hysteresis control by minimizing a cost function, including all required parameters. According to simulation results, we have shown that tracking will be performed well with appropriate amplitude and frequency of square dither.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130355815","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664790
H. M. Yasin, S. Y. Ameen
Recent years have shown exponential growth in video processing and transfer through the Internet and other applications. With the restriction on bandwidth, processing, and storage, there is an extensive demand for end-to-end video compression. Many conventional methods have been developed to compress video. However, with the extensive use of Artificial Intelligence, AI, such as Deep Learning (DL) have emerged as a best-of-breed alternative for performing different tasks have also been used in the option of improving video compression in the last years, with the primary objective of reducing compression ratio while preserving the same video quality. Evolving video compression research based on Neural Networks (NNs) focuses on two distinct directions: First, enhancing current video codecs by better predictions integrated even in the same codec framework, and second, holistic end-to-end VC systems approach. Although some of the outcomes are optimistic and the results are well, no breakthrough has been reported previously. This paper reviews new research work, including samples of a few influential articles that demonstrate. Further, describe the various highlighted issues in the area of using DL for end-to-end video compression.
{"title":"Review and Evaluation of End-to-End Video Compression with Deep-Learning","authors":"H. M. Yasin, S. Y. Ameen","doi":"10.1109/MTICTI53925.2021.9664790","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664790","url":null,"abstract":"Recent years have shown exponential growth in video processing and transfer through the Internet and other applications. With the restriction on bandwidth, processing, and storage, there is an extensive demand for end-to-end video compression. Many conventional methods have been developed to compress video. However, with the extensive use of Artificial Intelligence, AI, such as Deep Learning (DL) have emerged as a best-of-breed alternative for performing different tasks have also been used in the option of improving video compression in the last years, with the primary objective of reducing compression ratio while preserving the same video quality. Evolving video compression research based on Neural Networks (NNs) focuses on two distinct directions: First, enhancing current video codecs by better predictions integrated even in the same codec framework, and second, holistic end-to-end VC systems approach. Although some of the outcomes are optimistic and the results are well, no breakthrough has been reported previously. This paper reviews new research work, including samples of a few influential articles that demonstrate. Further, describe the various highlighted issues in the area of using DL for end-to-end video compression.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131719665","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664760
Deepti Kulkarni, Rashmi Soni
Crimes against women and children are increasing day by day in the present scenario. It is highly needed to provide a safe environment for them. The objective of this paper is to save the woman from unforeseen circumstances. For that, we propose a “Smart AIOT based Woman security system”. The proposed system consists of a Raspberry Pi processor, RPi camera, GPS module, GSM, Mic, pulse rate sensor, LCD screen. The system monitors the activities of the pulse rate sensor and mic input. If any abnormality occurs then the system will make the decision. This paper reviews different women’s security systems by their technology, platform, functionality, & compares different systems on different criteria. AI is involved in the proposed system to sense the danger prior and decide accordingly.
{"title":"Smart AIOT based Woman Security system","authors":"Deepti Kulkarni, Rashmi Soni","doi":"10.1109/MTICTI53925.2021.9664760","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664760","url":null,"abstract":"Crimes against women and children are increasing day by day in the present scenario. It is highly needed to provide a safe environment for them. The objective of this paper is to save the woman from unforeseen circumstances. For that, we propose a “Smart AIOT based Woman security system”. The proposed system consists of a Raspberry Pi processor, RPi camera, GPS module, GSM, Mic, pulse rate sensor, LCD screen. The system monitors the activities of the pulse rate sensor and mic input. If any abnormality occurs then the system will make the decision. This paper reviews different women’s security systems by their technology, platform, functionality, & compares different systems on different criteria. AI is involved in the proposed system to sense the danger prior and decide accordingly.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125319413","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664773
Ghadir Alselwi, Tugrul Tasci
Optimization is an effort to find the best option in the settings of the objective function. The goal of this study is to optimize multivariable functions using Artificial Bee Colony (ABC) which is one of the most current swarm intelligence-based algorithms, simulating the foraging activity of honeybees. The performance of the ABC algorithm has been measured on the minimization process of 22 benchmark functions including the popular Griewank, Rastrigin, Sphere, and Rosenbrock. The experimental results demonstrate that the ABC algorithm has approximated the actual value with an accuracy percentage of 98.85.
{"title":"Error Optimization in Random Number Generation Using ABC Algorithm","authors":"Ghadir Alselwi, Tugrul Tasci","doi":"10.1109/MTICTI53925.2021.9664773","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664773","url":null,"abstract":"Optimization is an effort to find the best option in the settings of the objective function. The goal of this study is to optimize multivariable functions using Artificial Bee Colony (ABC) which is one of the most current swarm intelligence-based algorithms, simulating the foraging activity of honeybees. The performance of the ABC algorithm has been measured on the minimization process of 22 benchmark functions including the popular Griewank, Rastrigin, Sphere, and Rosenbrock. The experimental results demonstrate that the ABC algorithm has approximated the actual value with an accuracy percentage of 98.85.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"3 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116823774","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664789
Ahmed Qasim Abdulghani, O. Ucan, Khattab M. Ali Alheeti
Fraudulent transactions have skyrocketed in tandem with the rise in Credit Card users. Since legitimate and fraudulent transactions look similar, it is nearly impossible to tell one from the other. This paper proposes a fraud detection system that uses Machine Learning (ML) and a fuzzy membership function to identify fraudulent transactions. The ML techniques used were Logistic regression (LR), Linear Discriminant Analysis (LDA), and the boosting algorithm XGBoost to create models for the proposed system. The dataset from Kaggle was used for training and testing these models. Many performance metrics were used to evaluate the proposed system models’ efficiency: confusion matrix, accuracy, precision, f1, recall, and AUC. The results showed the superiority of the XGBoost model over the other models.
{"title":"Credit Card Fraud Detection System using Machine Learning Algorithms and Fuzzy Membership","authors":"Ahmed Qasim Abdulghani, O. Ucan, Khattab M. Ali Alheeti","doi":"10.1109/MTICTI53925.2021.9664789","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664789","url":null,"abstract":"Fraudulent transactions have skyrocketed in tandem with the rise in Credit Card users. Since legitimate and fraudulent transactions look similar, it is nearly impossible to tell one from the other. This paper proposes a fraud detection system that uses Machine Learning (ML) and a fuzzy membership function to identify fraudulent transactions. The ML techniques used were Logistic regression (LR), Linear Discriminant Analysis (LDA), and the boosting algorithm XGBoost to create models for the proposed system. The dataset from Kaggle was used for training and testing these models. Many performance metrics were used to evaluate the proposed system models’ efficiency: confusion matrix, accuracy, precision, f1, recall, and AUC. The results showed the superiority of the XGBoost model over the other models.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132110710","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 : 2021-12-04DOI: 10.1109/MTICTI53925.2021.9664765
Salar Ismael Ahmed, S. Ameen, Subhi R. M. Zeebaree
Mobile core networks are facing exponential growth in traffic and computing demand as smart devices, and mobile applications become more popular. Caching is one of the most promising approaches to challenges and problems. Caching reduces the backhauling load in wireless networks by caching frequently used information at the destination node. Furthermore, proactive caching is an important technique to minimize the delay of storing planned content needs, relieving backhaul traffic and alleviating the delay caused by handovers. The paper investigates the caching types and compared caching techniques improvement with other methods used to improve 5G performance. The problems and solutions of caching in 5G networks are explored in this research. Caching research showed that the improvement with caching will depend on load, cache size, and the number of requested users who can get the required results by a proactive caching scheme. A significant decrease in traffic and total network latency can be achieved with caching.
{"title":"5G Mobile Communication System Performance Improvement with Caching: A Review","authors":"Salar Ismael Ahmed, S. Ameen, Subhi R. M. Zeebaree","doi":"10.1109/MTICTI53925.2021.9664765","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664765","url":null,"abstract":"Mobile core networks are facing exponential growth in traffic and computing demand as smart devices, and mobile applications become more popular. Caching is one of the most promising approaches to challenges and problems. Caching reduces the backhauling load in wireless networks by caching frequently used information at the destination node. Furthermore, proactive caching is an important technique to minimize the delay of storing planned content needs, relieving backhaul traffic and alleviating the delay caused by handovers. The paper investigates the caching types and compared caching techniques improvement with other methods used to improve 5G performance. The problems and solutions of caching in 5G networks are explored in this research. Caching research showed that the improvement with caching will depend on load, cache size, and the number of requested users who can get the required results by a proactive caching scheme. A significant decrease in traffic and total network latency can be achieved with caching.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134083368","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}
Learning analytics is the process of measuring, collecting, analyzing, and reporting data on learners and their environments in order to better understand and optimize learning and the environments in which it occurs. Assessment of students’ performance is a difficult and time-consuming undertaking for teachers and researchers in e-learning environments. The majority of LMS frameworks, whether commercial or open-source, access tracking and log analysis capabilities are insufficient. They also lack support for a variety of features such as evaluating participation levels, analyzing interactions, visually portraying current interactions, and semantic analysis of message content. Estimating the number of participants, non-participants, and lurkers in a continuing discourse is challenging and time-consuming for instructors and educationalists. Text mining, web page retrieval, and dialogue systems are all examples of text-related research and applications, semantic similarity measurements of text are becoming increasingly relevant. This study will present a unique learning analytics system for learning management systems (LMS) that will aid teachers and researchers in identifying and analyzing interaction patterns and participant knowledge acquisition in continuous online interactions.
{"title":"Learning analytics toolset for evaluating students’ performance in an E-learning Platform","authors":"Yahya Al-Ashmoery, Hisham Haider, Adnan Haider, Najran Nasser","doi":"10.1109/MTICTI53925.2021.9664761","DOIUrl":"https://doi.org/10.1109/MTICTI53925.2021.9664761","url":null,"abstract":"Learning analytics is the process of measuring, collecting, analyzing, and reporting data on learners and their environments in order to better understand and optimize learning and the environments in which it occurs. Assessment of students’ performance is a difficult and time-consuming undertaking for teachers and researchers in e-learning environments. The majority of LMS frameworks, whether commercial or open-source, access tracking and log analysis capabilities are insufficient. They also lack support for a variety of features such as evaluating participation levels, analyzing interactions, visually portraying current interactions, and semantic analysis of message content. Estimating the number of participants, non-participants, and lurkers in a continuing discourse is challenging and time-consuming for instructors and educationalists. Text mining, web page retrieval, and dialogue systems are all examples of text-related research and applications, semantic similarity measurements of text are becoming increasingly relevant. This study will present a unique learning analytics system for learning management systems (LMS) that will aid teachers and researchers in identifying and analyzing interaction patterns and participant knowledge acquisition in continuous online interactions.","PeriodicalId":218225,"journal":{"name":"2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133601506","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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