Intelligent Data Analysis最新文献

{"title":"A multi-domain adaptive neural machine translation method based on domain data balancer","authors":"Jinlei Xu, Yonghua Wen, Shuanghong Huang, Zhengtao Yu","doi":"10.3233/ida-230155","DOIUrl":"https://doi.org/10.3233/ida-230155","url":null,"abstract":"Most methods for multi-domain adaptive neural machine translation (NMT) currently rely on mixing data from multiple domains in a single model to achieve multi-domain translation. However, this mixing can lead to imbalanced training data, causing the model to focus on training for the large-scale general domain while ignoring the scarce resources of specific domains, resulting in a decrease in translation performance. In this paper, we propose a multi-domain adaptive NMT method based on Domain Data Balancer (DDB) to address the problems of imbalanced data caused by simple fine-tuning. By adding DDB to the Transformer model, we adaptively learn the sampling distribution of each group of training data, replace the maximum likelihood estimation criterion with empirical risk minimization training, and introduce a reward-based iterative update of the bilevel optimizer based on reinforcement learning. Experimental results show that the proposed method improves the baseline model by an average of 1.55 and 0.14 BLEU (Bilingual Evaluation Understudy) scores respectively in English-German and Chinese-English multi-domain NMT.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conversational recommender based on graph sparsification and multi-hop attention","authors":"Yihao Zhang, Yuhao Wang, Wei Zhou, Pengxiang Lan, Haoran Xiang, Junlin Zhu, Meng Yuan","doi":"10.3233/ida-230148","DOIUrl":"https://doi.org/10.3233/ida-230148","url":null,"abstract":"Conversational recommender systems provide users with item recommendations via interactive dialogues. Existing methods using graph neural networks have been proven to be an adequate representation of the learning framework for knowledge graphs. However, the knowledge graph involved in the dialogue context is vast and noisy, especially the noise graph nodes, which restrict the primary node’s aggregation to neighbor nodes. In addition, although the recurrent neural network can encode the local structure of word sequences in a dialogue context, it may still be challenging to remember long-term dependencies. To tackle these problems, we propose a sparse multi-hop conversational recommender model named SMCR, which accurately identifies important edges through matching items, thus reducing the computational complexity of sparse graphs. Specifically, we design a multi-hop attention network to encode dialogue context, which can quickly encode the long dialogue sequences to capture the long-term dependencies. Furthermore, we utilize a variational auto-encoder to learn topic information for capturing syntactic dependencies. Extensive experiments on the travel dialogue dataset show significant improvements in our proposed model over the state-of-the-art methods in evaluating recommendation and dialogue generation.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The interactive relationship between prosody and respiration of computer BIOPAC systems: Shanghai dialect and mandarin","authors":"Xiaohong Meng, Zhongxiu Yang, Zhi Li","doi":"10.3233/ida-237443","DOIUrl":"https://doi.org/10.3233/ida-237443","url":null,"abstract":"This paper uses the computer BIOPAC Systems tool to analyze Shanghai dialect and Mandarin which refers to the relationship between prosody and respiration in reading fable, the conclusion are as follows: 1) the mean of respiratory parameters and respiratory units was positively related, and respiration curve on Shanghai dialect which shows the characteristics of small ups and downs is different from the Mandarin curve; 2) the reset of respiration has relationship with mute segment, and the occurrence of reset breathing place must have a quiet period, while the opposite does not happen; 3) on the situation of fable literary style with flexible feature, the text of the proficiency can significantly increase the complexity of the respiration curve, showing a more special features such as “breathless” pronunciation.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43873877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction and analysis of chronic epilepsy using electroencephalographic signals on medical internet of things platform","authors":"Noor Hasan Hassoon, M. H. Ali, M. Jaber, Sura Khalil Abd, Ali S. Abosinnee, Z.H. Kareem","doi":"10.3233/ida-237434","DOIUrl":"https://doi.org/10.3233/ida-237434","url":null,"abstract":"Epilepsy patients who are presently refractory may be monitored using a seizure prediction Brain-Computer Interface (BCI), which uses electrodes strategically implanted in the brain to anticipate and regulate the onset and duration of a seizure. Real-time approaches to these technologies have challenges, as seen by seizures’ instantaneous electrographic activity. Electroencephalographic (EEG) signals are inherently non-stationary, which means that the regular and seizure signals differ significantly among people with epilepsy. Due to the restricted number of contacts on electrodes, dynamically processed and collected characteristics cannot be employed in a prediction function without causing significant processing delays. Big data can guarantee secure storage in these situations, and it has the maximum processing capability to identify, record, and analyze time in real-time to conduct the seizure event on the timetable. Seizure prediction and location for huge Scalp EEG recordings have been the focus of this study, which used wearable sensor data and deep learning to use cloud storage to develop the systems. A novel technique is suggested to avoid an epileptic seizure and discover the seizure origin from the utilized wearable sensors. Secondly, deep learning architectures called Clustered Autoencoder with Convolutional Neural Network (CAE-CNN), an expanded optimization methodology is presented based on the Principal Component Analysis (PCA), the Hierarchical Searching Algorithm (HSA), and the Medical Internet of Things (MIoT) has been established to define the suggested frameworks based on the collection of big data storage of the wearable sensors in real-time, automatic computation and storage. According to clinical trials, CAE-CNN outperforms the current wearable sensor-based treatment for unresolved chronic epilepsy patients.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42032748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retracing-efficient IoT model for identifying the skin-related tags using automatic lumen detection","authors":"G.N. Vivekananda, Saman M. Almufti, C. Suresh, Salomi Samsudeen, Mohanarangan Veerapperumal Devarajan, R. Srikanth, S. Jayashree","doi":"10.3233/ida-237442","DOIUrl":"https://doi.org/10.3233/ida-237442","url":null,"abstract":"The number of patients with skin diseases reported a dramatic increase which is a major concern and should be addressed. The evaluation of skin is crucial to the correct diagnosis during the follow-up. Through technological advances and partnership, skin disorders can be identified and predicted. PROBLEM: The manual detection of skin diseases may sometimes lead to misclassification due to the same intensity and color levels, which is crucial to the correct diagnosis. SOLUTION: An automated system to identify these skin diseases is applied. An IoT-based skin monitoring infrastructure is imposed that links the entire system. METHOD: In this study, a Retracing-efficient IoT model for identifying the moles, skin tags, and warts using Automatic lumen detection with the help of IoT-based Variation regularity is proposed with the technique imposed IoMT, Automatic lumen detection, Variation regularity, and trigonometric algorithm. RESULTS: The intensity and edge width based on moles, skin tags, and warts edge width heightened intensity accuracy is 56.2% on the image group with image count is 500 to 10000, and the enhanced low-level total sample accuracy is 95.9%. The pixel analysis for intensity with wavelength and intensity with time wavelength is improved from 4.2% to 54.6%, and accuracy is 70.9% formulated. Periodic classification on image count and classification accuracy image count is 87% against the 500 to 10000 image. Correlation performance analysis of lumen detection resolution image pixel and enhanced correlation performance accuracy is 23.50% on the 480 × 640 to 2336 × 3504 pixel images. CONCLUSION: The approach is tested for varying datasets, and comparative analysis is performed that reflects the effectiveness of the proposed system with high accuracy, thus contributing to the development of a perfect platform for skincare to the early detection and diagnosis of skin conditions.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42860924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E-Health technological barriers faced by Iraqi healthcare institutions","authors":"Saif Mohammed Ali, M. A. Burhanuddin, A. T. Yaseen, M. Jaber, M. Jassim, Aseel Mohammed Ali, A. Alkhayyat, M. A. Mohammed, Auday A. H. Mohamad","doi":"10.3233/ida-237438","DOIUrl":"https://doi.org/10.3233/ida-237438","url":null,"abstract":"The health records management issues have detrimentally affected the Iraqi healthcare sector resultant from the inferior information technology integrity and the complicatedness of data. In order to resolve this problem, other methods of storage, management, and retrieval of health-related data can be offered by e-Health services. These aspects are important in tracking patients’ health conditions using multiple platforms at the service provider’s own convenience. However, there are numerous issues that hinder the extensive adoption of e-Health services by the health establishments in Iraq, such as issues on security and privacy, legalities connected to policies, and its implementation. The significance of the current study is its identification of the crucial aspects that will lead to the success of impacting the technical staff towards their positive acceptance and behavior with regard to the employment of e-Health information system in Iraqi hospitals. A self-administered survey was carried out on 104 technical staff from various healthcare organizations in Iraq using a simple random sampling technique. A nonparametric second-generation multivariate analysis was conducted on the compiled ordinal data by the utilization of the PLS-SEM approach. The outcomes indicated the favorable impact of several factors on the doctor’s employment of e-Health in Iraqi hospitals, comprising Availability and Affordability of the hardware and software, ICT Support Service, Network Reliability, Privacy, and Security. The results are important in assisting the comprehension of e-Health systems in the management of health data, in addition to the provision of the pertinent recommendations for policymakers to provide guidance, issue advice, directives to the healthcare professionals toward the continuous consideration of using advance information and communications technology at work.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47268314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative observation of changes in natriuretic peptides before and after interventional therapy for congenital heart disease","authors":"Xinghui Liu, H. Tan, Xiaoqiao Liu, Qiang Wu","doi":"10.3233/ida-237440","DOIUrl":"https://doi.org/10.3233/ida-237440","url":null,"abstract":"OBJECTIVE: To explore changes in the plasma atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) in patients with left-to-right shunt congenital heart disease (CHD) before and in the early stage after interventional occlusion and to evaluate the clinical significance. METHODS: Among 97 patients with left-to-right shunt CHD undergoing interventional occlusion, 34 cases had a VSD (ventricular septal defect), 35 cases had an ASD (atrial septal defect), and 28 cases had PDA (patent ductus arteriosus). Another 20 normal adults formed the control group. An ELISA was used to determine the plasma ANP and BNP levels before and on the third day after the operation to evaluate their correlations with cardiac functions and the defect size. RESULTS: The plasma ANP and BNP levels of patients with left-to-right shunt CHD were increased compared with those of the normal control group (P< 0.01), and the plasma ANP and BNP levels were decreased on the third day after interventional occlusion compared with the preoperative levels (P< 0.05). The plasma ANP and BNP levels were correlated with the New York Heart Association (NYHA) grade, left ventricular ejection fraction and defect diameter (P< 0.05). CONCLUSION: Patients with left-to-right congenital heart disease exhibit activation of ANP and BNP, which can be alleviated in the early stage after intervention occlusion. Left-to-right shunt congenital heart disease is given priority over atrial septal defect (ASD), ventricular septal defect (VSD) and patent ductus arteriosus (PDA). Early traditional methods included repair or correction by open heart surgery under extracorporeal circulation (also known as cardiopulmonary bypass, CPB). However, interventional therapy has become a developing trend for the treatment of congenital heart disease since 1967, when Porstmann et al. [1]. reported the transcatheter closure of ASD for the first time. The application of the AMPLATZER occluder, which is a simple and feasible method, has improved the safety of the treatment and enabled the therapeutic effect to reach ideal levels. The natriuretic peptide (NP) family consists of the atrial natriuretic polypeptide (ANP), the brain natriuretic peptide, which is also known as the B type natriuretic peptide (BNP), the C type natriuretic peptide (CNP), the renal natriuretic peptide (RNP) and the D type natriuretic peptide (DNP). These family members are similar in structure, have strong natriuretic, diuretic and vasodilative effects and antagonize the activity of the renin-angiotensin-aldosterone system (RAAS) and the sympathetic nerve. Together, the natriuretic peptides sensitively and specifically reflect the ventricular function state. Although all types of congenital heart disease differ in anatomical structure, they all contain the common features of heart failure. This study detected changes in the serum ANP and BNP levels in patients with left-to-right shunt congenital heart disease before and on the third day aft","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44440320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heart sound classification using wavelet scattering transform and support vector machine","authors":"Vishwanath Madhava Shervegar","doi":"10.3233/ida-237432","DOIUrl":"https://doi.org/10.3233/ida-237432","url":null,"abstract":"OBJECTIVE: A representation of the sound recordings that are associated with the movement of the entire cardiac structure is termed the Phonocardiogram (PCG) signal. In diagnosing such diverse diseases of the heart, PCG signals are helpful. Nevertheless, as recording PCG signals are prone to several surrounding noises and other disturbing signals, it is a complex task. Thus, prior to being wielded for advanced processing, the PCG signal needs to be denoised. This work proposes an improved heart sound classification by utilizing two-stage Low pass filtering and Wavelet Threshold (WT) technique with subsequent Feature Extraction (FE) using Wavelet Scatter Transform and further classification utilizing the Cubic Polynomial Support Vector Machine (SVM) technique for CVD. METHOD: A computer-aided diagnosis system for CVD detection centered on PCG signal analysis is offered in this work. Initially, by heavily filtering the signal, the raw PCG signals obtained using the database were pre-processed. Then, to remove redundant information and noise, it is denoised via the WT technique. From the denoised PCG, wavelet time scattering features were extracted. After that, by employing SVMs, these features were classified for pathology. RESULTS: For the analysis, the PCG signal obtained from the Physionet dataset was considered. Heavy low-pass filtering utilizing a Low-Pass Butterworth Filter (LPBF) is entailed in the pre-processing step. This removed 98% of the noise inherently present in the signal. Further, the signal strength was ameliorated by denoising it utilizing the WT technique. Promising results with maximum noise removal of up to 99% are exhibited by the method. From the PCG, Wavelet Scattering (WS) features were extracted, which were later wielded to categorize the PCG utilizing SVMs with 99.72% accuracy for different sounds. DISCUSSION: The Classification accuracies are analogized with other classification techniques present in the literature. This technique exhibited propitious outcomes with a 3% improvement in the F1 score when weighed against the top-notch techniques. The improvement in the metrics is attributed to the usage of the pre-processing stage comprising of Low-pass filter and WT method, WS Transform (WST), and SVMs. CONCLUSION: The superiority of the proposed technique is advocated by the comparative investigation with prevailing methodologies. The system revealed that Coronary Artery Disease (CAD) can be implemented with superior methods to achieve high accuracy.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43497458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time MRI lungs images revealing using Hybrid feedforward Deep Neural Network and Convolutional Neural Network","authors":"M. Karthick, Dinesh Jackson Samuel, B. Prakash, P. Sathyaprakash, Nandhini Daruvuri, M. Ali, R.S. Aiswarya","doi":"10.3233/ida-237436","DOIUrl":"https://doi.org/10.3233/ida-237436","url":null,"abstract":"This research focused on Real-time MRI lung images that were revealed using three grade processes by manipulating nanophotonics components, mapping by deep learning, machine learning, and pattern recognition. This research is Solving Magnetic resonance imaging of interstitial lung diseases with Hybrid feedforward Deep Neural Network (ffDNN) and Convolutional Neural Network (CNN) architecture. The feedforward deep neural network (ffDNN) and Convolutional Neural Network (CNN) techniques are used to Solving Magnetic resonance imaging of interstitial lung diseases on the nanophotonics components, deep learning, and machine learning Platform. The Proposed semiconductor monolithic integration approach employed for bio-Magnetic resonance imaging characterization using photonic crystal “Symptomatic Image Revealing” details of the resonant monolithic. The proposed machine-learning-based approach revealed characterizing multi-parameter design space of nanophotonic components using Nano-optic imagers. The Pattern Recognition for MRI was performed for lower dimensionality. Finally, the Hybrid feedforward Deep Neural Network (ffDNN) and Convolutional Neural Network (CNN) architecture for calculating the height and size of scatterers using the inverse design of the meta-optical structure. The temporal resolution assessment of image data pixel size 280x360 hyperspectral imaging temporal resolution is 25, and magnetic resonance imaging temporal resolution is 50. The Image distribution shows that phase shift and transmission are 2.78 degrees and at 95%. The result for the inverse design using CNN returns the efficient inverse design of test data that can be designed according to the required pressure distribution. Wavelength 1000 nanometer to 1600 machine learning method absorbance 40% and ffDNN absorbance 33%.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49430389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social and economic development impact of elderly health care products based on design ethics","authors":"Na Qi, Xun Zhang","doi":"10.3233/ida-237439","DOIUrl":"https://doi.org/10.3233/ida-237439","url":null,"abstract":"BACKGROUND: The aging of the population is a historical stage that many countries must experience, and the current design and development of elderly health care products can no longer meet the increasing demands of the elderly. OBJECTIVE: The impact of ethical design of elderly health care products on socio-economic development is explored to provide a theoretical basis for the development direction of elderly health care products. METHODS: In this study, a questionnaire survey is conducted on 268 middle-aged people to record the subjects’ willingness to purchase elderly health care products and their reasons, concerns, satisfaction, and future demands. RESULTS: Among the subjects, 181 people have purchased elderly health care products, accounting for 67.36%; the subjects are more concerned about the quality and safety of elderly health care products, accounting for 92.56% and 91.85% respectively, followed by operability (68.46%); the problems encountered by the elderly using elderly health care products are mainly operational problems, accounting for 65.37%; and high safety (86.13%) and good quality (79.55%) are the subjects’ main demands for future development of elderly health care products. 73.61% of the 30–40 year old subjects said that the intelligent aged care products were very good; 65.89% of the 41–50 year old subjects said that the intelligent aged care products were very good; 52.67% of the 51–60 subjects thought that intelligent elderly care products were very good; and 47.82% of the subjects whose age were over 60 expressed their willingness to try intelligent elderly care products. CONCLUSIONS: Good quality and high safety are the main demands for the future development of elderly health care products. The elderly health care products manufactured based on the people-oriented design ethics concept can greatly meet the aspirations of the elderly to pursue a happy later life, and promote the vigorous development of the elderly industrial economy.","PeriodicalId":50355,"journal":{"name":"Intelligent Data Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43953508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}