: With the rapid development of science and technology and the increasing popularity of the Internet, the number of network users is gradually expanding, and the behavior of network users is becoming more and more complex. Users’ actual demand for resources on the network application platform is closely related to their historical behavior records. Therefore, it is very important to analyze the user behavior path conversion rate. Therefore, this paper analyses and studies user behavior path based on sales data. Through analyzing the user quality of the website as well as the user’s repurchase rate, repurchase rate and retention rate in the website, we can get some user habits and use the data to guide the website optimization.
{"title":"User Behavior Path Analysis Based on Sales Data","authors":"Wangdong Jiang, Dongling Zhang, Yapeng Peng, Guang Sun, Ying Cao, Jing Li","doi":"10.32604/jnm.2020.010088","DOIUrl":"https://doi.org/10.32604/jnm.2020.010088","url":null,"abstract":": With the rapid development of science and technology and the increasing popularity of the Internet, the number of network users is gradually expanding, and the behavior of network users is becoming more and more complex. Users’ actual demand for resources on the network application platform is closely related to their historical behavior records. Therefore, it is very important to analyze the user behavior path conversion rate. Therefore, this paper analyses and studies user behavior path based on sales data. Through analyzing the user quality of the website as well as the user’s repurchase rate, repurchase rate and retention rate in the website, we can get some user habits and use the data to guide the website optimization.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795259","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 : 2020-01-01DOI: 10.32604/jnm.2020.012815
Y. Mao, Kaiyong Li, Duolu Mao
: Based on the analysis of the advantages and disadvantages of GPS positioning system in practical application, this paper proposes the combination of wireless network positioning technology and GPS positioning system to overcome the low accuracy of GPS positioning system in the case of occlusion. This paper introduces in detail the principle of the application of wireless network positioning technology based on GPS positioning system in geographic information measurement, and illustrates its practical application in production by taking coal mine positioning as an example.
{"title":"Application of Wireless Network Positioning Technology Based on GPS in Geographic Information Measurement","authors":"Y. Mao, Kaiyong Li, Duolu Mao","doi":"10.32604/jnm.2020.012815","DOIUrl":"https://doi.org/10.32604/jnm.2020.012815","url":null,"abstract":": Based on the analysis of the advantages and disadvantages of GPS positioning system in practical application, this paper proposes the combination of wireless network positioning technology and GPS positioning system to overcome the low accuracy of GPS positioning system in the case of occlusion. This paper introduces in detail the principle of the application of wireless network positioning technology based on GPS positioning system in geographic information measurement, and illustrates its practical application in production by taking coal mine positioning as an example.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795754","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 : 2020-01-01DOI: 10.32604/jnm.2020.014115
A. Wulamu, Jingyue Sang, D. Zhang, Zuxian Shi
: Cultivated land extraction is essential for sustainable development and agriculture. In this paper, the network we propose is based on the encoder-decoder structure, which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation solutions. The encoder consists of two part: the first is the modified Xception, it can used as the feature extraction network, and the second is the atrous convolution, it can used to expand the receptive field and the context information to extract richer feature information. The decoder part uses the conventional upsampling operation to restore the original resolution. In addition, we use the combination of BCE and Loves-hinge as a loss function to optimize the Intersection over Union (IoU). Experimental results show that the proposed network structure can solve the problem of cultivated land extraction in Yinchuan City.
:开垦耕地对可持续发展和农业至关重要。本文提出的网络基于编码器-解码器结构，从卫星图像中提取耕地语义分割神经网络，并将其用于农业自动化解决方案。该编码器由两部分组成:第一部分是改进的异常，它可以作为特征提取网络;第二部分是亚历克斯卷积，它可以用来扩展接受域和上下文信息，以提取更丰富的特征信息。解码器部分使用传统的上采样操作来恢复原始分辨率。此外，我们使用BCE和love -hinge的组合作为损失函数来优化Intersection over Union (IoU)。实验结果表明，所提出的网络结构能够很好地解决银川市耕地抽取问题。
{"title":"Robust Cultivated Land Extraction Using Encoder-Decoder","authors":"A. Wulamu, Jingyue Sang, D. Zhang, Zuxian Shi","doi":"10.32604/jnm.2020.014115","DOIUrl":"https://doi.org/10.32604/jnm.2020.014115","url":null,"abstract":": Cultivated land extraction is essential for sustainable development and agriculture. In this paper, the network we propose is based on the encoder-decoder structure, which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation solutions. The encoder consists of two part: the first is the modified Xception, it can used as the feature extraction network, and the second is the atrous convolution, it can used to expand the receptive field and the context information to extract richer feature information. The decoder part uses the conventional upsampling operation to restore the original resolution. In addition, we use the combination of BCE and Loves-hinge as a loss function to optimize the Intersection over Union (IoU). Experimental results show that the proposed network structure can solve the problem of cultivated land extraction in Yinchuan City.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795875","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 : 2020-01-01DOI: 10.32604/jnm.2020.014278
Junchuan Yang
{"title":"Review of Image-Based Person Re-Identification in Deep Learning","authors":"Junchuan Yang","doi":"10.32604/jnm.2020.014278","DOIUrl":"https://doi.org/10.32604/jnm.2020.014278","url":null,"abstract":"","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69796013","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 : 2020-01-01DOI: 10.32604/jnm.2020.014309
Y. Jihai, Zongtao Duan, Muyao Wang, Jabar Mahmood, Xiao Yuanyuan, Yun Yang
: Modern autonomous vehicles are getting progressively popular and increasingly getting closer to the core of future development in transportation field. However, there is no reliable authentication mechanism for the unmanned vehicle communication system, this phenomenon draws attention about the security of autonomous vehicles of people in all aspects. Physical Unclonable Function (PUF) circuits is light-weight, and it can product unique and unpredictable digital signature utilizing the manufacturing variations occur in each die and these exact silicon features cannot be recreated theoretically. Considering security issues of communication between Electronic Control Units (ECUs) in vehicles, we propose a novel delay-based PUF circuit using all the available logical components in every two-slice within Configurable Logic Blocks (CLBs) in Field Programmable Gate Array (FPGA) chips, which is significantly suitable for circuit authentication in ECUs of autonomous vehicles and is a significant improvement over the usual arbiter PUF in resource occupation in FPGA chips, that is to say it can get stronger resistance to security risks with less logic resource overhead. Our PUF design is resource efficient so that it can exactly be applied to the source-constrained devices such as in-vehicle ECUs. It effectively reduce the risk of the messages delivered between ECUs being tampered and then vehicle be illegally controlled by adversary. We simulated the proposed PUF circuit in simulator and implemented it on Xilinx boards under different conditions to obtain experimental results, the analyzed result proves that the proposed PUF satisfies the properties of Uniqueness and Stability. Finally, the ECUs authentication mechanism utilizing our PUF circuit is introduced.
{"title":"An Authentication Mechanism for Autonomous Vehicle ECU Utilizing a Novel Slice-Based PUF Design","authors":"Y. Jihai, Zongtao Duan, Muyao Wang, Jabar Mahmood, Xiao Yuanyuan, Yun Yang","doi":"10.32604/jnm.2020.014309","DOIUrl":"https://doi.org/10.32604/jnm.2020.014309","url":null,"abstract":": Modern autonomous vehicles are getting progressively popular and increasingly getting closer to the core of future development in transportation field. However, there is no reliable authentication mechanism for the unmanned vehicle communication system, this phenomenon draws attention about the security of autonomous vehicles of people in all aspects. Physical Unclonable Function (PUF) circuits is light-weight, and it can product unique and unpredictable digital signature utilizing the manufacturing variations occur in each die and these exact silicon features cannot be recreated theoretically. Considering security issues of communication between Electronic Control Units (ECUs) in vehicles, we propose a novel delay-based PUF circuit using all the available logical components in every two-slice within Configurable Logic Blocks (CLBs) in Field Programmable Gate Array (FPGA) chips, which is significantly suitable for circuit authentication in ECUs of autonomous vehicles and is a significant improvement over the usual arbiter PUF in resource occupation in FPGA chips, that is to say it can get stronger resistance to security risks with less logic resource overhead. Our PUF design is resource efficient so that it can exactly be applied to the source-constrained devices such as in-vehicle ECUs. It effectively reduce the risk of the messages delivered between ECUs being tampered and then vehicle be illegally controlled by adversary. We simulated the proposed PUF circuit in simulator and implemented it on Xilinx boards under different conditions to obtain experimental results, the analyzed result proves that the proposed PUF satisfies the properties of Uniqueness and Stability. Finally, the ECUs authentication mechanism utilizing our PUF circuit is introduced.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69796132","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 : 2020-01-01DOI: 10.32604/jnm.2020.010674
Zequn Wang, Rui Jiao, Huiping Jiang
: With the continuous development of the computer, people's requirements for computers are also getting more and more, so the brain-computer interface system (BCI) has become an essential part of computer research. Emotion recognition is an important task for the computer to understand social status in BCI. Affective computing (AC) aims to develop the model of emotions and advance the affective intelligence of computers. There are various emotion recognition approaches. The method based on electroencephalogram (EEG) is more reliable because it is higher in accuracy and more objective in evaluation than other external appearance clues such as emotion expression and gesture. In this paper, we use the wavelet transform (WT) to extract three kinds of EEG features in time, and frequency domain, which are sub-band energy, energy ratio and root mean square of wavelet coefficients. They reflect the emotion related to EEG activities well. The average classification accuracy of support vector machine (SVM) can reach 82.87%, which indicates that these three features are very effective in emotion recognition. On the other hand, compared with international affective picture system (IAPs), EEG data collected by Chinese affective picture system (CAPs) stimulation has a higher emotion recognition rate, indicating that there are cultural background differences in emotions.
{"title":"Emotion Recognition Using WT-SVM in Human-Computer Interaction","authors":"Zequn Wang, Rui Jiao, Huiping Jiang","doi":"10.32604/jnm.2020.010674","DOIUrl":"https://doi.org/10.32604/jnm.2020.010674","url":null,"abstract":": With the continuous development of the computer, people's requirements for computers are also getting more and more, so the brain-computer interface system (BCI) has become an essential part of computer research. Emotion recognition is an important task for the computer to understand social status in BCI. Affective computing (AC) aims to develop the model of emotions and advance the affective intelligence of computers. There are various emotion recognition approaches. The method based on electroencephalogram (EEG) is more reliable because it is higher in accuracy and more objective in evaluation than other external appearance clues such as emotion expression and gesture. In this paper, we use the wavelet transform (WT) to extract three kinds of EEG features in time, and frequency domain, which are sub-band energy, energy ratio and root mean square of wavelet coefficients. They reflect the emotion related to EEG activities well. The average classification accuracy of support vector machine (SVM) can reach 82.87%, which indicates that these three features are very effective in emotion recognition. On the other hand, compared with international affective picture system (IAPs), EEG data collected by Chinese affective picture system (CAPs) stimulation has a higher emotion recognition rate, indicating that there are cultural background differences in emotions.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69796111","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 : 2020-01-01DOI: 10.32604/jnm.2020.012816
Duolu Mao, Kaiyong Li, Y. Mao
: In order to improve the accuracy of wireless network positioning, the triangulation method of wireless network positioning technology is proposed, which is based on the linear least square fitting method. It makes the observed value and the fitting value very close, effectively solves the problem of significant contradiction between the fitting result and the observed value in the principle of least square method, and can realize the accurate measurement of geographic information by wireless network positioning technology.
{"title":"Improvement of Location Algorithm in Wireless Networks","authors":"Duolu Mao, Kaiyong Li, Y. Mao","doi":"10.32604/jnm.2020.012816","DOIUrl":"https://doi.org/10.32604/jnm.2020.012816","url":null,"abstract":": In order to improve the accuracy of wireless network positioning, the triangulation method of wireless network positioning technology is proposed, which is based on the linear least square fitting method. It makes the observed value and the fitting value very close, effectively solves the problem of significant contradiction between the fitting result and the observed value in the principle of least square method, and can realize the accurate measurement of geographic information by wireless network positioning technology.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795821","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}
: Due to the huge difference of noise distribution, the result of a mixture of multiple noises becomes very complicated. Under normal circumstances, the most common type of mixed noise is to add impulse noise (IN) and then white Gaussian noise (AWGN). From the reduction of cascaded IN and AWGN to the latest sparse representation, a great deal of methods has been proposed to reduce this form of mixed noise. However, when the mixed noise is very strong, most methods often produce a lot of artifacts. In order to solve the above problems, we propose a method based on residual learning for the removal of AWGN-IN noise in this paper. By training, our model can obtain stable nonlinear mapping from the images with mixed noise to the clean images. After a series of experiments under different noise settings, the results show that our method is obviously better than the traditional sparse representation and patch based method. Meanwhile, the time of model training and image denoising is greatly reduced.
{"title":"Mixed Noise Removal by Residual Learning of Deep CNN","authors":"Kang Yang, Jielin Jiang, Zhaoqing Pan","doi":"10.32604/jnm.2020.09356","DOIUrl":"https://doi.org/10.32604/jnm.2020.09356","url":null,"abstract":": Due to the huge difference of noise distribution, the result of a mixture of multiple noises becomes very complicated. Under normal circumstances, the most common type of mixed noise is to add impulse noise (IN) and then white Gaussian noise (AWGN). From the reduction of cascaded IN and AWGN to the latest sparse representation, a great deal of methods has been proposed to reduce this form of mixed noise. However, when the mixed noise is very strong, most methods often produce a lot of artifacts. In order to solve the above problems, we propose a method based on residual learning for the removal of AWGN-IN noise in this paper. By training, our model can obtain stable nonlinear mapping from the images with mixed noise to the clean images. After a series of experiments under different noise settings, the results show that our method is obviously better than the traditional sparse representation and patch based method. Meanwhile, the time of model training and image denoising is greatly reduced.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795883","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}
Tao Li, Hao Li, Sheng Zhong, Yan Kang, Yachuan Zhang, Rongjing Bu, Yang Hu
: In view of the low interpretability of existing collaborative filtering recommendation algorithms and the difficulty of extracting information from content-based recommendation algorithms, we propose an efficient KGRS model. KGRS first obtains reasoning paths of knowledge graph and embeds the entities of paths into vectors based on knowledge representation learning TransD algorithm, then uses LSTM and soft attention mechanism to capture the semantic of each path reasoning, then uses convolution operation and pooling operation to distinguish the importance of different paths reasoning. Finally, through the full connection layer and sigmoid function to get the prediction ratings, and the items are sorted according to the prediction ratings to get the user’s recommendation list. KGRS is tested on the movielens-100k dataset. Compared with the related representative algorithm, including the state-of-the-art interpretable recommendation models RKGE and RippleNet, the experimental results show that KGRS has good recommendation interpretation and higher recommendation accuracy.
{"title":"Knowledge Graph Representation Reasoning for Recommendation System","authors":"Tao Li, Hao Li, Sheng Zhong, Yan Kang, Yachuan Zhang, Rongjing Bu, Yang Hu","doi":"10.32604/jnm.2020.09767","DOIUrl":"https://doi.org/10.32604/jnm.2020.09767","url":null,"abstract":": In view of the low interpretability of existing collaborative filtering recommendation algorithms and the difficulty of extracting information from content-based recommendation algorithms, we propose an efficient KGRS model. KGRS first obtains reasoning paths of knowledge graph and embeds the entities of paths into vectors based on knowledge representation learning TransD algorithm, then uses LSTM and soft attention mechanism to capture the semantic of each path reasoning, then uses convolution operation and pooling operation to distinguish the importance of different paths reasoning. Finally, through the full connection layer and sigmoid function to get the prediction ratings, and the items are sorted according to the prediction ratings to get the user’s recommendation list. KGRS is tested on the movielens-100k dataset. Compared with the related representative algorithm, including the state-of-the-art interpretable recommendation models RKGE and RippleNet, the experimental results show that KGRS has good recommendation interpretation and higher recommendation accuracy.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69796426","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}
: Attribute-based encryption is cryptographic techniques that provide flexible data access control to encrypted data content in cloud storage. Each trusted authority needs proper management and distribution of secret keys to the user’s to only authorized user’s attributes. However existing schemes cannot be applied multiple authority that supports only a single keywords search compare to multi keywords search high computational burden or inefficient attribute’s revocation. In this paper, a ciphertext policy attribute-based encryption (CP-ABE) scheme has been proposed which focuses on multi-keyword search and attribute revocation by new policy updating feathers under multiple authorities and central authority. The data owner encrypts the keywords index under the initial access policy. Moreover, this paper addresses further issues such as data access, search policy, and confidentiality against unauthorized users. Finally, we provide the correctness analysis, performance analysis and security proof for chosen keywords attack and search trapdoor in general group model using DBDH and DLIN assumption.
{"title":"Authorized Attribute-Based Encryption Multi-Keywords Search with\u0000Policy Updating","authors":"M. Ali, Chungen Xu, Abid Hussain","doi":"10.32604/jnm.2020.09946","DOIUrl":"https://doi.org/10.32604/jnm.2020.09946","url":null,"abstract":": Attribute-based encryption is cryptographic techniques that provide flexible data access control to encrypted data content in cloud storage. Each trusted authority needs proper management and distribution of secret keys to the user’s to only authorized user’s attributes. However existing schemes cannot be applied multiple authority that supports only a single keywords search compare to multi keywords search high computational burden or inefficient attribute’s revocation. In this paper, a ciphertext policy attribute-based encryption (CP-ABE) scheme has been proposed which focuses on multi-keyword search and attribute revocation by new policy updating feathers under multiple authorities and central authority. The data owner encrypts the keywords index under the initial access policy. Moreover, this paper addresses further issues such as data access, search policy, and confidentiality against unauthorized users. Finally, we provide the correctness analysis, performance analysis and security proof for chosen keywords attack and search trapdoor in general group model using DBDH and DLIN assumption.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69796224","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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