Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226926
Yun-Chiao Cheng, Yan-Hung Chou, Chia-Yu Lin
The blooming season is a crucial aspect of tourism in Taiwan, but it is subject to annual variations caused by weather factors such as rainfall and temperature. While many AI models are on the market for predicting flowering, they often need more applicability to specific regions due to climate variations. Moreover, Taiwan’s climate is known for being changeable, which can further complicate flower prediction. Using Taiwan’s climate and flowering date as training parameters, our model can achieve significantly higher accuracy than models that do not incorporate Taiwan’s climate information. This paper presents an App called "Booming Blooming," which integrates a flower prediction model with real-time weather information. The App utilizes weather data from Taiwan’s Central Weather Bureau to predict the optimal time for flower viewing and provides users with up-to-date weather forecasts. With this App, users can plan their flower-viewing trips more effectively. Moreover, the App includes a built-in Google map to assist users in locating nearby stores, traffic conditions, and other people at popular flower-viewing locations. Additionally, Booming Blooming offers a flower-sharing platform where users can share the latest information on flower blooming conditions. Overall, the proposed flower blooming prediction model and App provide a convenient and efficient way for Taiwanese to enjoy flower-viewing activities.
{"title":"Booming Blooming: When Can You Enjoy Flowering Season?","authors":"Yun-Chiao Cheng, Yan-Hung Chou, Chia-Yu Lin","doi":"10.1109/ICCE-Taiwan58799.2023.10226926","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226926","url":null,"abstract":"The blooming season is a crucial aspect of tourism in Taiwan, but it is subject to annual variations caused by weather factors such as rainfall and temperature. While many AI models are on the market for predicting flowering, they often need more applicability to specific regions due to climate variations. Moreover, Taiwan’s climate is known for being changeable, which can further complicate flower prediction. Using Taiwan’s climate and flowering date as training parameters, our model can achieve significantly higher accuracy than models that do not incorporate Taiwan’s climate information. This paper presents an App called \"Booming Blooming,\" which integrates a flower prediction model with real-time weather information. The App utilizes weather data from Taiwan’s Central Weather Bureau to predict the optimal time for flower viewing and provides users with up-to-date weather forecasts. With this App, users can plan their flower-viewing trips more effectively. Moreover, the App includes a built-in Google map to assist users in locating nearby stores, traffic conditions, and other people at popular flower-viewing locations. Additionally, Booming Blooming offers a flower-sharing platform where users can share the latest information on flower blooming conditions. Overall, the proposed flower blooming prediction model and App provide a convenient and efficient way for Taiwanese to enjoy flower-viewing activities.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129732645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226813
Yu-Ting Yang, Chih-Yung Chang, Shih-Jung Wu, Chia-Ling Ho
In the current era, there has been a rapid advancement in the field of information technology. When scholars compose their research papers, it can be challenging for them to conduct an exhaustive examination of the existing literature. Therefore, it is essential to create a system that can suggest suitable citations to researchers during the writing process. This study aims to recommend relevant citations to researchers by utilizing weighted bag of words and BERT models. The proposed mechanism provides the following benefits: (1) Clear and transparent representation of document vectors; (2) A range of diverse natural language processing techniques, and (3) Avoidance of redundant citation suggestions.
{"title":"Enhancing Academic Writing: A Smart Citation Recommendation System Leveraging BERT and Weighted Bag-of-Words Models","authors":"Yu-Ting Yang, Chih-Yung Chang, Shih-Jung Wu, Chia-Ling Ho","doi":"10.1109/ICCE-Taiwan58799.2023.10226813","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226813","url":null,"abstract":"In the current era, there has been a rapid advancement in the field of information technology. When scholars compose their research papers, it can be challenging for them to conduct an exhaustive examination of the existing literature. Therefore, it is essential to create a system that can suggest suitable citations to researchers during the writing process. This study aims to recommend relevant citations to researchers by utilizing weighted bag of words and BERT models. The proposed mechanism provides the following benefits: (1) Clear and transparent representation of document vectors; (2) A range of diverse natural language processing techniques, and (3) Avoidance of redundant citation suggestions.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127418424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226955
Keizo Sato, Yusuke Chibe, Makoto Nakashima
A Tablet PC is now used not only for reading books and watching videos, but also for various work tasks such as creating business documents and analyzing data. However, while graphics performance and other specifications of the tablet PC have improved over the years, the basic application usage is similar on all devices, that is, a user maximizes any application window and uses it in full-screen mode. The question remains as to whether the maximized single window is truly appropriate for performing various tasks on a tablet PC. In fact, multi-window environments facilitate multitasking on desktop or laptop PCs. We analyzed the usability of the multi-window environment on a tablet PC through experiments in which subjects performed simple tasks while switching between two or more windows. The results revealed that while the multi-window environment has great potential to perform multitasking on a tablet PC, the ability to automatically adjust the positions/sizes of multiple application windows is needed.
{"title":"A Usability Analysis of the Multi-window Working Environment Modified for a Tablet PC","authors":"Keizo Sato, Yusuke Chibe, Makoto Nakashima","doi":"10.1109/ICCE-Taiwan58799.2023.10226955","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226955","url":null,"abstract":"A Tablet PC is now used not only for reading books and watching videos, but also for various work tasks such as creating business documents and analyzing data. However, while graphics performance and other specifications of the tablet PC have improved over the years, the basic application usage is similar on all devices, that is, a user maximizes any application window and uses it in full-screen mode. The question remains as to whether the maximized single window is truly appropriate for performing various tasks on a tablet PC. In fact, multi-window environments facilitate multitasking on desktop or laptop PCs. We analyzed the usability of the multi-window environment on a tablet PC through experiments in which subjects performed simple tasks while switching between two or more windows. The results revealed that while the multi-window environment has great potential to perform multitasking on a tablet PC, the ability to automatically adjust the positions/sizes of multiple application windows is needed.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129041329","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 presents the synthesis result of extreme learning machine (ELM), a machine learning technique, to detect age-related macular degeneration (AMD), an eye disease prevalent in elderly people. The model is trained with optical coherence tomography (OCT) images and a desirable clock period, area, and power is obtained. This is the first of its kind synthesis result of ELM implementation for AMD detection on OCT images.
{"title":"Implementation of Extreme Learning Machine Algorithm for Age-related Macular Degeneration Detection on OCT volumes","authors":"Himajah Natarajan, Jie-Yi Ji, Aadhitiyan Sridharan, Cheng-Hung Lin, Cheng-Kai Lu, Jia-Kang Wang, Tzu-Lun Huang","doi":"10.1109/ICCE-Taiwan58799.2023.10226920","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226920","url":null,"abstract":"This paper presents the synthesis result of extreme learning machine (ELM), a machine learning technique, to detect age-related macular degeneration (AMD), an eye disease prevalent in elderly people. The model is trained with optical coherence tomography (OCT) images and a desirable clock period, area, and power is obtained. This is the first of its kind synthesis result of ELM implementation for AMD detection on OCT images.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226696
Yu-An Chen
Fifth generation (5G) New Radio (NR), was developed to offer more flexibility to meet new service requirements. Meanwhile, machine learning (ML) has proven successful in a variety of tasks, such as natural language processing, computer vision, and pattern recognition, in particular, which is proven to have a performance that is proportional to the total amount of available data. In NR, the capability to locate users is still one of the critical obstacles when mobile operator is planning and optimizing the cellular networks. Developing the technique to distinguish indoor from outdoor users' traffic pattern can achieve higher efficiency in terms of resource management and which results in larger economic benefit. In this paper, we present a pattern classifier based on decision tree to solve the indoor/outdoor classification problem. More specifically, rules for classification of indoor/outdoor users are generated by repeatedly splitting the features from cellular network key performance indicators (KPIs) which utilize the measurement criteria of entropy from the information theory community.
{"title":"A Machine Learning Based Scheme for Indoor/Outdoor Classification in Wireless Communication Networks","authors":"Yu-An Chen","doi":"10.1109/ICCE-Taiwan58799.2023.10226696","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226696","url":null,"abstract":"Fifth generation (5G) New Radio (NR), was developed to offer more flexibility to meet new service requirements. Meanwhile, machine learning (ML) has proven successful in a variety of tasks, such as natural language processing, computer vision, and pattern recognition, in particular, which is proven to have a performance that is proportional to the total amount of available data. In NR, the capability to locate users is still one of the critical obstacles when mobile operator is planning and optimizing the cellular networks. Developing the technique to distinguish indoor from outdoor users' traffic pattern can achieve higher efficiency in terms of resource management and which results in larger economic benefit. In this paper, we present a pattern classifier based on decision tree to solve the indoor/outdoor classification problem. More specifically, rules for classification of indoor/outdoor users are generated by repeatedly splitting the features from cellular network key performance indicators (KPIs) which utilize the measurement criteria of entropy from the information theory community.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129165034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226881
Yunyou Fan, Chih-Yu Wen
Due to the limited physical space and training facilities, we propose one efficient immersive training method to integrate a virtual reality (VR) simulation system with a body area network (BAN). With the Customized deep neural network algorithm, the body-worn inertial sensors are capable to recognize the activities of participants and avoid mismatched actions. Moreover, the neural networks have been utilized to provide greater access to physical actions of the VR real-time training environment. In this paper, a quaternion based deep neural network algorithm is developed and implemented for human activity recognition (HAR). We share the experience on the VR application that has the potential to fulfil multi-user immersive VR system on HAR.
{"title":"Real-Time Human Activity Recognition for VR Simulators with Body Area Networks","authors":"Yunyou Fan, Chih-Yu Wen","doi":"10.1109/ICCE-Taiwan58799.2023.10226881","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226881","url":null,"abstract":"Due to the limited physical space and training facilities, we propose one efficient immersive training method to integrate a virtual reality (VR) simulation system with a body area network (BAN). With the Customized deep neural network algorithm, the body-worn inertial sensors are capable to recognize the activities of participants and avoid mismatched actions. Moreover, the neural networks have been utilized to provide greater access to physical actions of the VR real-time training environment. In this paper, a quaternion based deep neural network algorithm is developed and implemented for human activity recognition (HAR). We share the experience on the VR application that has the potential to fulfil multi-user immersive VR system on HAR.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128885501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10227023
S. Javaid, M. Kaneko, Yasuo Tan
The integration of RESs such as wind generation system and photovoltaic generation system increases the risks of power fluctuations from the supply side. The uncertainty due to seasonal data, temperature variations, and consumer activity increases the risks of power fluctuations on the demand side. To accommodate the uncertainty of both generator side and consumer side, the power grid has to increase its ability to accommodate fluctuating power. Based on this, the robust energy balancing between power generators, consumers, and storage devices in a periodic operation is introduced. This paper proposes the minimum requirements on controllable generators, loads and storage devices for supply-dominated energy balancing of a system which includes fluctuating generator and load. The discussions on the periodic operation of the system enable us to apply the result to a long-term system operation.
{"title":"Supply-Dominated Energy Balancing for Periodic Operation of Power System","authors":"S. Javaid, M. Kaneko, Yasuo Tan","doi":"10.1109/ICCE-Taiwan58799.2023.10227023","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10227023","url":null,"abstract":"The integration of RESs such as wind generation system and photovoltaic generation system increases the risks of power fluctuations from the supply side. The uncertainty due to seasonal data, temperature variations, and consumer activity increases the risks of power fluctuations on the demand side. To accommodate the uncertainty of both generator side and consumer side, the power grid has to increase its ability to accommodate fluctuating power. Based on this, the robust energy balancing between power generators, consumers, and storage devices in a periodic operation is introduced. This paper proposes the minimum requirements on controllable generators, loads and storage devices for supply-dominated energy balancing of a system which includes fluctuating generator and load. The discussions on the periodic operation of the system enable us to apply the result to a long-term system operation.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130562651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226947
Takeru Miyazaki, Shunsuke Araki, S. Uehara
In this paper, we propose a new pseudorandom bit sequence generator, which is based on a method digging out walls. Although each of these sequences lacks enough randomness, synthesized sequences of them can pass all of the NIST statistical test suite. We also describe a conjectural relation between the number of types on the square mazes and their sizes.
{"title":"How to Construct Pseudorandom Bit Sequences from Mazes by a Method Digging Out Walls","authors":"Takeru Miyazaki, Shunsuke Araki, S. Uehara","doi":"10.1109/ICCE-Taiwan58799.2023.10226947","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226947","url":null,"abstract":"In this paper, we propose a new pseudorandom bit sequence generator, which is based on a method digging out walls. Although each of these sequences lacks enough randomness, synthesized sequences of them can pass all of the NIST statistical test suite. We also describe a conjectural relation between the number of types on the square mazes and their sizes.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10227043
Chao-Chung Peng
Depth camera is a field-of-view (FoV) based distance sensor and has been widely used in commercial entertainments such as augmented reality, industrial field for object 3D modeling, as well as intelligence vehicle obstacle avoidance. No doubt, the depth camera measurement accuracy definitely affects the associated application performance and therefore the noise behavior should be properly modeled. The measurement noise of the depth cameras depends on various factors, which can be difficult to model in practice. In this short note, three different depth noise models are presented based on the pin-hole model of the camera. The goal is to match the practical depth camera noise distributions as close as possible and to provide a simulation sketch for further noise analysis and possible improvement of the depth measurements.
{"title":"Depth Camera Noise Modeling","authors":"Chao-Chung Peng","doi":"10.1109/ICCE-Taiwan58799.2023.10227043","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10227043","url":null,"abstract":"Depth camera is a field-of-view (FoV) based distance sensor and has been widely used in commercial entertainments such as augmented reality, industrial field for object 3D modeling, as well as intelligence vehicle obstacle avoidance. No doubt, the depth camera measurement accuracy definitely affects the associated application performance and therefore the noise behavior should be properly modeled. The measurement noise of the depth cameras depends on various factors, which can be difficult to model in practice. In this short note, three different depth noise models are presented based on the pin-hole model of the camera. The goal is to match the practical depth camera noise distributions as close as possible and to provide a simulation sketch for further noise analysis and possible improvement of the depth measurements.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132406260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.1109/ICCE-Taiwan58799.2023.10226919
Risa Takeuchi, T. Murase
We propose a novel travel route control for autonomous mobile robots (AMRs) ad hoc networks. In this method, relaying AMRs (referred to as "nodes") can provide high throughput for a longer time by relaying other nodes data and taking a route that mitigates interference from external networks. Relay nodes form the ad hoc network as they move. At this time, it takes a longcut route on its own path for the best performance, so that it can take the best position for relaying. In ad hoc networks formed with moving nodes, it is difficult to comprehensively consider effects of influence from external network and effects of communication distance with adjacent communication node. Thus, it is also difficult to set up an optimal route in which relay nodes can take a longcut route and take the best position for relaying. The evaluation results showed that the proposed method can maintain high throughput in 72% of the routes.
{"title":"Longcut route of multiple autonomous mobile robots forming ad hoc networks to avoid interference from other networks","authors":"Risa Takeuchi, T. Murase","doi":"10.1109/ICCE-Taiwan58799.2023.10226919","DOIUrl":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226919","url":null,"abstract":"We propose a novel travel route control for autonomous mobile robots (AMRs) ad hoc networks. In this method, relaying AMRs (referred to as \"nodes\") can provide high throughput for a longer time by relaying other nodes data and taking a route that mitigates interference from external networks. Relay nodes form the ad hoc network as they move. At this time, it takes a longcut route on its own path for the best performance, so that it can take the best position for relaying. In ad hoc networks formed with moving nodes, it is difficult to comprehensively consider effects of influence from external network and effects of communication distance with adjacent communication node. Thus, it is also difficult to set up an optimal route in which relay nodes can take a longcut route and take the best position for relaying. The evaluation results showed that the proposed method can maintain high throughput in 72% of the routes.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130443566","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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