Pub Date : 2020-04-30DOI: 10.17993/3ctecno.2020.specialissue5.63-73
Muhammad Talha, Atif Saeed, M. Jaffer, Hayyan Yousuf Khan, A. Haider, Wajahat Ali
In this current smart era, electricity is considered a necessity for development as almost all of machinery and circuitry runs on electrical power. Therefore, the production of electricity is a must for attaining progress. But nowadays, there is a constant struggle for access to large fossil reservoirs and the development for renewable resources is slow. There have been innovative inventions such as the wind turbines, water turbines, solar cells and many other renewable sources. These resources have slowed down the depletion of fossil fuels to a certain extent, but these inventions do have their shortcomings and most areas where energy harnessing is possible, are left unanswered. One such area where energy conversion is possible is in the water transportation system. To harness electrical energy from this system, a small turbine generator can be installed onto the pipelines to harness the kinetic energy of the flowing water in them. Hence forth by applying this research, another renewable energy resource is developed.
{"title":"Design and analysis of inline pipe turbine","authors":"Muhammad Talha, Atif Saeed, M. Jaffer, Hayyan Yousuf Khan, A. Haider, Wajahat Ali","doi":"10.17993/3ctecno.2020.specialissue5.63-73","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue5.63-73","url":null,"abstract":"In this current smart era, electricity is considered a necessity for development as almost all of machinery and circuitry runs on electrical power. Therefore, the production of electricity is a must for attaining progress. But nowadays, there is a constant struggle for access to large fossil reservoirs and the development for renewable resources is slow. There have been innovative inventions such as the wind turbines, water turbines, solar cells and many other renewable sources. These resources have slowed down the depletion of fossil fuels to a certain extent, but these inventions do have their shortcomings and most areas where energy harnessing is possible, are left unanswered. One such area where energy conversion is possible is in the water transportation system. To harness electrical energy from this system, a small turbine generator can be installed onto the pipelines to harness the kinetic energy of the flowing water in them. Hence forth by applying this research, another renewable energy resource is developed.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45449803","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 : 2020-04-30DOI: 10.17993/3ctecno.2020.specialissue5.159-179
Syed Abbas Ali, N. Tariq, Sallar Khan, Asif Raza, Syed Muhammad Faza-ul-Karim, Muhammad Usman
This paper facilitates radiologists in diagnosis of lung tumor and provides with a probability to differentiate between the types of tumor through automated analysis and increase in accuracy. The system is aggregated model for tumor identification and 3D reconstruction of lung using (computed Tomography) CT-scan images in Digital Imaging and Communications in Medicine (DICOM) format to identify the lung tumor (Benign or Malignant) using learning algorithm. The proposed system is capable to reconstruct the 3D model of lung tumor using CT-scan medical images and identify tumor (Benign or Malignant) including location of tumor (Attached to wall or parenchyma) with significant accuracy. The proposed diagnostic software provides significant results with bright CT scans to identify lungs tissue with different orientations by rotating it and reduces the enormous false positive rate by increasing the efficiency and accuracy of the diagnostic procedure. Whereas, CT-scan image is below required brightness or if CT-scan is done in a dark room than the module does not shows considerable results of segmentation. The proposed computer aided diagnosis can help the radiologists to detect tumor at early stage, decrease the enormous false positive rate, and the overall cost of the diagnostic procedure; thus, bringing windfall benefits in the field of medical imaging.
{"title":"Aggregated model for tumor identification and 3D reconstruction of lung using CT-Scan","authors":"Syed Abbas Ali, N. Tariq, Sallar Khan, Asif Raza, Syed Muhammad Faza-ul-Karim, Muhammad Usman","doi":"10.17993/3ctecno.2020.specialissue5.159-179","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue5.159-179","url":null,"abstract":"This paper facilitates radiologists in diagnosis of lung tumor and provides with a probability to differentiate between the types of tumor through automated analysis and increase in accuracy. The system is aggregated model for tumor identification and 3D reconstruction of lung using (computed Tomography) CT-scan images in Digital Imaging and Communications in Medicine (DICOM) format to identify the lung tumor (Benign or Malignant) using learning algorithm. The proposed system is capable to reconstruct the 3D model of lung tumor using CT-scan medical images and identify tumor (Benign or Malignant) including location of tumor (Attached to wall or parenchyma) with significant accuracy. The proposed diagnostic software provides significant results with bright CT scans to identify lungs tissue with different orientations by rotating it and reduces the enormous false positive rate by increasing the efficiency and accuracy of the diagnostic procedure. Whereas, CT-scan image is below required brightness or if CT-scan is done in a dark room than the module does not shows considerable results of segmentation. The proposed computer aided diagnosis can help the radiologists to detect tumor at early stage, decrease the enormous false positive rate, and the overall cost of the diagnostic procedure; thus, bringing windfall benefits in the field of medical imaging.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46238634","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 : 2020-04-30DOI: 10.17993/3ctecno.2020.specialissue5.233-247
Hector Daniel Huapaya, Ciro Rodriguez, D. Esenarro
This paper describes the most prominent algorithms of Supervised Machine Learning (SML), their characteristics, and comparatives in the way of treating data. The Heart Disease dataset obtained from Kaggle was used to determine and test its highest percentage of accuracy. To achieve the objective, Python sklearn libraries were used to implement the selected algorithms, evaluate and determine which algorithm is the one that obtains the best results, applying decision tree algorithms achieved the best prediction results.
{"title":"Comparative analysis of supervised machine learning algorithms for heart disease detection","authors":"Hector Daniel Huapaya, Ciro Rodriguez, D. Esenarro","doi":"10.17993/3ctecno.2020.specialissue5.233-247","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue5.233-247","url":null,"abstract":"This paper describes the most prominent algorithms of Supervised Machine Learning (SML), their characteristics, and comparatives in the way of treating data. The Heart Disease dataset obtained from Kaggle was used to determine and test its highest percentage of accuracy. To achieve the objective, Python sklearn libraries were used to implement the selected algorithms, evaluate and determine which algorithm is the one that obtains the best results, applying decision tree algorithms achieved the best prediction results.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46617502","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 : 2020-04-30DOI: 10.17993/3ctecno.2020.specialissue5.265-277
A. Dahri, Shafiq-ur-Rehman Massan, Ayaz Ali Maitlo
eGovernance is a vital component of any nations’ modern governmental structure and suitable for mass-scale adaptation. Pakistan has also established an eGovernance council for mitigation of the problems of the common man. One big step in this direction is the establishment of Pakistan Citizens’ Portal (PCP) that facilitates eGovernance. Through the PCP app, citizens can directly lodge complaints and report their issues for immediate resolution. This study looks at the important aspect of mobile usability through field tests to determine the viability of the PCP app in Pakistan. This study is vital towards determining the main factors for large scale adaptation of the PCP app and underlines the weaknesses of the present system. Hence, the PCP app was evaluated in terms of efficiency and effectiveness according to ISO 92421-11. And the user satisfaction was measured through system usability satisfaction (SUS) on five-point Likert scale. The evaluation method included more than a dozen citizens of Sindh and findings showed that overall application enriched the user experience. However, the few areas of PCP were identified as needing improvements. The main areas that the PCP application needs to improve are the areas of registration and ‘findability’ which would further improve user satisfaction and experience.
{"title":"Usability of eGovernance application for citizens of Pakistan","authors":"A. Dahri, Shafiq-ur-Rehman Massan, Ayaz Ali Maitlo","doi":"10.17993/3ctecno.2020.specialissue5.265-277","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue5.265-277","url":null,"abstract":"eGovernance is a vital component of any nations’ modern governmental structure and suitable for mass-scale adaptation. Pakistan has also established an eGovernance council for mitigation of the problems of the common man. One big step in this direction is the establishment of Pakistan Citizens’ Portal (PCP) that facilitates eGovernance. Through the PCP app, citizens can directly lodge complaints and report their issues for immediate resolution. This study looks at the important aspect of mobile usability through field tests to determine the viability of the PCP app in Pakistan. This study is vital towards determining the main factors for large scale adaptation of the PCP app and underlines the weaknesses of the present system. Hence, the PCP app was evaluated in terms of efficiency and effectiveness according to ISO 92421-11. And the user satisfaction was measured through system usability satisfaction (SUS) on five-point Likert scale. The evaluation method included more than a dozen citizens of Sindh and findings showed that overall application enriched the user experience. However, the few areas of PCP were identified as needing improvements. The main areas that the PCP application needs to improve are the areas of registration and ‘findability’ which would further improve user satisfaction and experience.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41638561","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 : 2020-04-30DOI: 10.17993/3ctecno.2020.specialissue5.217-231
Sanaullah Mehran Ujjan, I. H. Kalwar, B. S. Chowdhry, T. Memon, Dileep Kumar Soother
Robust and accurate adhesion level identification is crucial for proper operation of railway vehicle. It is necessary for braking and traction forces characterization, development of maintenance strategies, wheel-rail wear predictions and development of robust onboard health monitoring systems. Adhesion being the function of many uncertain parameters is difficult to model, whereas data driven algorithms such as Deep Neural networks (DNNs) are very good at mapping a nonlinear function from cause to effect. In this research a solid axle Wheel-set was modeled along with different adhesion conditions and a dataset was prepared for the training of DNNs in Python. Furthermore, it explored the potential of DNNs and various data driven algorithms on our noisy sequential dataset for classification task and achieved 91% accuracy in identification of adhesion condition with our final model.
{"title":"Adhesion level identification in wheel-rail contact using deep neural networks","authors":"Sanaullah Mehran Ujjan, I. H. Kalwar, B. S. Chowdhry, T. Memon, Dileep Kumar Soother","doi":"10.17993/3ctecno.2020.specialissue5.217-231","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue5.217-231","url":null,"abstract":"Robust and accurate adhesion level identification is crucial for proper operation of railway vehicle. It is necessary for braking and traction forces characterization, development of maintenance strategies, wheel-rail wear predictions and development of robust onboard health monitoring systems. Adhesion being the function of many uncertain parameters is difficult to model, whereas data driven algorithms such as Deep Neural networks (DNNs) are very good at mapping a nonlinear function from cause to effect. In this research a solid axle Wheel-set was modeled along with different adhesion conditions and a dataset was prepared for the training of DNNs in Python. Furthermore, it explored the potential of DNNs and various data driven algorithms on our noisy sequential dataset for classification task and achieved 91% accuracy in identification of adhesion condition with our final model.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45417457","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 : 2020-03-23DOI: 10.17993/3ctecno.2020.specialissue4.287-299
P. Dhanusha, A. Lakshmi, K. Saravanan
Driving is one of the most important job for almost all people. Person use their vehicle to travel from one place to other. The count of automobiles is increasing every day. It increases the risk to accident. Currently, percentage numbers of accident are increasing drastically. One of the main reason for accident is the failure in concentration of the driver due to which he/she may fall asleep or sometimes due to the delay for applying the brake. A new system is developed that can solve these problems where an alert is given to the people present inside the vehicle to indicate that the driver is falling asleep and a cosystem which can automatically stop the vehicle even if the driver may not brake manually due to obstacles. Our aim is to make a smart driving system with automatic waking alert and automatic braking system to ensure the safety of driving.
{"title":"Smart driving system with automatic driver alert and braking mechanism","authors":"P. Dhanusha, A. Lakshmi, K. Saravanan","doi":"10.17993/3ctecno.2020.specialissue4.287-299","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue4.287-299","url":null,"abstract":"Driving is one of the most important job for almost all people. Person use their vehicle to travel from one place to other. The count of automobiles is increasing every day. It increases the risk to accident. Currently, percentage numbers of accident are increasing drastically. One of the main reason for accident is the failure in concentration of the driver due to which he/she may fall asleep or sometimes due to the delay for applying the brake. A new system is developed that can solve these problems where an alert is given to the people present inside the vehicle to indicate that the driver is falling asleep and a cosystem which can automatically stop the vehicle even if the driver may not brake manually due to obstacles. Our aim is to make a smart driving system with automatic waking alert and automatic braking system to ensure the safety of driving.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45856188","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 : 2020-03-23DOI: 10.17993/3ctecno.2020.specialissue4.313-327
B. Aruna Devi, M. Pallikonda Rajasekaran
Magnetic Resonance Imaging (MRI) is a modern, robust method that uses in the detection of various medical problems. In this research work, a trial is used to attempt for the detection of tumour in pancreas MR images. An automated classifier is used for detection of tumour in MR images and avoids the drawbacks of MRI. This automated classifiers can detect automatically, either the MR image is affected or not affected. Features are extracted from MR images using second order statistics approach and are classified by two techniques Support Vector Machine (SVM) and Extreme Learning Machine (ELM). SVM approach has high classification accuracy (96%) which is higher than ELM, while ELM performs faster compared to SVM.
{"title":"Optimal choice of supervised techniques for MR image classification","authors":"B. Aruna Devi, M. Pallikonda Rajasekaran","doi":"10.17993/3ctecno.2020.specialissue4.313-327","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue4.313-327","url":null,"abstract":"Magnetic Resonance Imaging (MRI) is a modern, robust method that uses in the detection of various medical problems. In this research work, a trial is used to attempt for the detection of tumour in pancreas MR images. An automated classifier is used for detection of tumour in MR images and avoids the drawbacks of MRI. This automated classifiers can detect automatically, either the MR image is affected or not affected. Features are extracted from MR images using second order statistics approach and are classified by two techniques Support Vector Machine (SVM) and Extreme Learning Machine (ELM). SVM approach has high classification accuracy (96%) which is higher than ELM, while ELM performs faster compared to SVM.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46291258","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 : 2020-03-23DOI: 10.17993/3ctecno.2020.specialissue4.159-179
A. Kavipriya, M. Arunachalam
At present, Frequent Biometrics Scientific Research deals with other biometric application like Face, Iris, Voice, Hand-Based Biometrics traits for classification and spotting out the persons. These Specific Biometric traits have their own improvement and weakness for opting the terms like Accuracy & cost of all applications. However, in addition to other Face-based Biometric techniques, Ear Recognition has been appealed to Boom the attention among other Biometric researchers. This Image Template Pattern Formation of Ear cuddles the report which is relevant for maculating the Uniqueness of their individuality. This Ear Biometric trait observes the person’s identity based on its stable Anatomical behavior. This biometric trait does not involve any emotional feelings with facial expressions in the same way as a unique pair of Fingerprint. In this work, a Contemporary approach for Personal identification is imported with Ear along with the data stores in a secured way has been proposed. This authentication Process includes the revolution of features with Gabor Filter and Dimension Reduction based on Multi-Manifold Discriminant Analysis (MMDA). This work is adequately analyzed in Matlab with the Evaluation metrics such as FMR, GAR, FNMR, by modifying the key value each time. The results of this suggested work promote better values in recognition of individuals as for Ear modalities. Conclusively the Features are grouped using K-Means for both identification and Verification Process. This Proposed system is initialized with Ear Recognition Template based on Fuzzy Vault. The Key stored in the Fuzzy Vault is utilized in safeguarding the existence of Chaff Points.
{"title":"New Intuition on Ear Authentication with Gabor Filter Using Fuzzy Vault","authors":"A. Kavipriya, M. Arunachalam","doi":"10.17993/3ctecno.2020.specialissue4.159-179","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue4.159-179","url":null,"abstract":"At present, Frequent Biometrics Scientific Research deals with other biometric application like Face, Iris, Voice, Hand-Based Biometrics traits for classification and spotting out the persons. These Specific Biometric traits have their own improvement and weakness for opting the terms like Accuracy & cost of all applications. However, in addition to other Face-based Biometric techniques, Ear Recognition has been appealed to Boom the attention among other Biometric researchers. This Image Template Pattern Formation of Ear cuddles the report which is relevant for maculating the Uniqueness of their individuality. This Ear Biometric trait observes the person’s identity based on its stable Anatomical behavior. This biometric trait does not involve any emotional feelings with facial expressions in the same way as a unique pair of Fingerprint. In this work, a Contemporary approach for Personal identification is imported with Ear along with the data stores in a secured way has been proposed. This authentication Process includes the revolution of features with Gabor Filter and Dimension Reduction based on Multi-Manifold Discriminant Analysis (MMDA). This work is adequately analyzed in Matlab with the Evaluation metrics such as FMR, GAR, FNMR, by modifying the key value each time. The results of this suggested work promote better values in recognition of individuals as for Ear modalities. Conclusively the Features are grouped using K-Means for both identification and Verification Process. This Proposed system is initialized with Ear Recognition Template based on Fuzzy Vault. The Key stored in the Fuzzy Vault is utilized in safeguarding the existence of Chaff Points.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43834666","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 : 2020-03-23DOI: 10.17993/3ctecno.2020.specialissue4.301-311
P. Sivakumar, S. Velmurugan, Jenyfal Sampson
Automated mechanization for curing a disease is a reliable and protuberant method. A disease in brain can be detected by Magnetic Resonance Imaging (MRI). In this context, image fusion is a method for creating an image by merging pertinent data from 2 or more images. The resultant image will be highly useful than the individual input images to retentive the vital characteristics of every image. Multiple image fusion is a significant method employed in image processing techniques. In this study, differential evolution (DE) algorithm-based image fusion has been performed with MRI and computed tomography (CT) images. The simulation works have been carried out to evaluate the different quality measurements of DE on image fusion.
{"title":"Implementation of differential evolution algorithm to perform image fusion for identifying brain tumor","authors":"P. Sivakumar, S. Velmurugan, Jenyfal Sampson","doi":"10.17993/3ctecno.2020.specialissue4.301-311","DOIUrl":"https://doi.org/10.17993/3ctecno.2020.specialissue4.301-311","url":null,"abstract":"Automated mechanization for curing a disease is a reliable and protuberant method. A disease in brain can be detected by Magnetic Resonance Imaging (MRI). In this context, image fusion is a method for creating an image by merging pertinent data from 2 or more images. The resultant image will be highly useful than the individual input images to retentive the vital characteristics of every image. Multiple image fusion is a significant method employed in image processing techniques. In this study, differential evolution (DE) algorithm-based image fusion has been performed with MRI and computed tomography (CT) images. The simulation works have been carried out to evaluate the different quality measurements of DE on image fusion.","PeriodicalId":41375,"journal":{"name":"3c Tecnologia","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42038500","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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