Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429458
M. El-Fandi, Kholoud El-Henqari, Abulgasim Shallof
In this paper, a brand new technique for detection of ventricular suction in a Rotary Left Ventricular Assist Device (LVAD) helping a failing cardiovascular gadget the usage of recursive DFT algorithm is presented. The algorithm is developed by the author and used in different frequency data measurement. The suction detection is primarily based on-line frequency data measurement of a periodic signals. The algorithm is computationally easy with a small variety of mathematical parameters and comparatively easy to implement. Simulation were carried out on a fifth-order lumped parametric circuit which can produce the cardiovascular system combined with a rotary pump to illustrate responsiveness and robustness of the algorithm.
{"title":"New Method for Detection of Ventricular Suction in an Implantable Pump Using Recursive DFT Algorithm","authors":"M. El-Fandi, Kholoud El-Henqari, Abulgasim Shallof","doi":"10.1109/SSD52085.2021.9429458","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429458","url":null,"abstract":"In this paper, a brand new technique for detection of ventricular suction in a Rotary Left Ventricular Assist Device (LVAD) helping a failing cardiovascular gadget the usage of recursive DFT algorithm is presented. The algorithm is developed by the author and used in different frequency data measurement. The suction detection is primarily based on-line frequency data measurement of a periodic signals. The algorithm is computationally easy with a small variety of mathematical parameters and comparatively easy to implement. Simulation were carried out on a fifth-order lumped parametric circuit which can produce the cardiovascular system combined with a rotary pump to illustrate responsiveness and robustness of the algorithm.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"31 1","pages":"346-352"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79655239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429404
Hmidi Alaeddine, J. Malek
In early work, the automatic recognition problem of plant diseases relied on traditional machine learning techniques such as Multilayer Perceptrons (MLP) and Support Vector Machines (SVM). However, in recent years new approaches have moved towards the application of Deep Learning (DL) and convolutional neural network which is described as a dominant tool in this field. In this work, we introduce a model with an architecture based on the AlexNet model for the plant diseases classification from leaf images. We present a deeper version of AlexNet with size (3x3) convolution, normalization, regularization, and linear exponential unit (eLU) layers. The training and testing of the proposed model was performed on a PlantVillage dataset. This proposed model obtained precision and a high gain in convergence learning speed. It achieved 99.48% classification accuracy with 17.54x fewer parameters compared to AlexNet.
{"title":"Deep Batch-normalized eLU AlexNet For Plant Diseases Classification","authors":"Hmidi Alaeddine, J. Malek","doi":"10.1109/SSD52085.2021.9429404","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429404","url":null,"abstract":"In early work, the automatic recognition problem of plant diseases relied on traditional machine learning techniques such as Multilayer Perceptrons (MLP) and Support Vector Machines (SVM). However, in recent years new approaches have moved towards the application of Deep Learning (DL) and convolutional neural network which is described as a dominant tool in this field. In this work, we introduce a model with an architecture based on the AlexNet model for the plant diseases classification from leaf images. We present a deeper version of AlexNet with size (3x3) convolution, normalization, regularization, and linear exponential unit (eLU) layers. The training and testing of the proposed model was performed on a PlantVillage dataset. This proposed model obtained precision and a high gain in convergence learning speed. It achieved 99.48% classification accuracy with 17.54x fewer parameters compared to AlexNet.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"264 1","pages":"17-22"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79719774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429468
Roman Ceresnák, K. Matiaško, A. Dudáš
In the 1950s, the demand for useful data storage gained importance and with it relational databases started to play an essential role in many sectors. Nowadays, relational databases cannot effectively fulfill the demands for interactive web and mobile applications, which demand flexibility and scalability for a data model. With the term NoSQL, we cover all the non-relational databases which provide no scheme and scaling model. NoSQL Databases, also called internet databases, are nowadays used by such significant organizations as Google, Amazon, Facebook and many others. Different classes of databases NoSQL, specifically couples of key-value pairs, documentary, column-oriented databases and graph databases, allow programmers to model the data near the format used in their application. One of the disadvantages, resulting from a free structure, is the security of effective searching in the non-relational databases. Several studies dealt with the effective way of searching in the non-relational databases. These studies examined the model data in the non-relational database MongoDB with the help of a relational model. In this paper, we introduce a method which searches for the data stored in the non-relational database MongoDB using the model with the permanent structure in relational database Oracle. Even though efficiency of our solution could be debated while using smaller datasets, with growing size of data the efficiency of presented solution increases.
{"title":"Improvement of Data Searching in MongoDB with the Use of Oracle Database","authors":"Roman Ceresnák, K. Matiaško, A. Dudáš","doi":"10.1109/SSD52085.2021.9429468","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429468","url":null,"abstract":"In the 1950s, the demand for useful data storage gained importance and with it relational databases started to play an essential role in many sectors. Nowadays, relational databases cannot effectively fulfill the demands for interactive web and mobile applications, which demand flexibility and scalability for a data model. With the term NoSQL, we cover all the non-relational databases which provide no scheme and scaling model. NoSQL Databases, also called internet databases, are nowadays used by such significant organizations as Google, Amazon, Facebook and many others. Different classes of databases NoSQL, specifically couples of key-value pairs, documentary, column-oriented databases and graph databases, allow programmers to model the data near the format used in their application. One of the disadvantages, resulting from a free structure, is the security of effective searching in the non-relational databases. Several studies dealt with the effective way of searching in the non-relational databases. These studies examined the model data in the non-relational database MongoDB with the help of a relational model. In this paper, we introduce a method which searches for the data stored in the non-relational database MongoDB using the model with the permanent structure in relational database Oracle. Even though efficiency of our solution could be debated while using smaller datasets, with growing size of data the efficiency of presented solution increases.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"8 3 1","pages":"1388-1393"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83708470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429451
Ines Slimene, Imen Messaoudi, A. Oueslati, Z. Lachiri
Recent research has shown that microRNA plays an important role in human disease specification. Study of miRNA expression helps to accelerate the diagnosis of diseases and to anticipate treatment. However experimental identification of diseases from microRNA expression such as RPM poses difficulties. Nowadays, we haven't enough bioinformatics algorithm to predict the association between miRNA and diseases. Herein, we present a machine learning based approach for distinguishing patient from normal person based on miRNA expression. In this paper, we compare different machine learning algorithms such as SVM, KNN and logistic regression to predict infected gene from miRNAs RPM values.
{"title":"MicroRNA expression classification for human disease prediction","authors":"Ines Slimene, Imen Messaoudi, A. Oueslati, Z. Lachiri","doi":"10.1109/SSD52085.2021.9429451","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429451","url":null,"abstract":"Recent research has shown that microRNA plays an important role in human disease specification. Study of miRNA expression helps to accelerate the diagnosis of diseases and to anticipate treatment. However experimental identification of diseases from microRNA expression such as RPM poses difficulties. Nowadays, we haven't enough bioinformatics algorithm to predict the association between miRNA and diseases. Herein, we present a machine learning based approach for distinguishing patient from normal person based on miRNA expression. In this paper, we compare different machine learning algorithms such as SVM, KNN and logistic regression to predict infected gene from miRNAs RPM values.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"29 1","pages":"1209-1214"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80507912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429368
Atheer J. Mansoor, Hikmat N. Abdullah, M. F. Al-Gailani, H. Ziboon
In this paper, a full image encryption system is proposed. The proposed system depends on changing the value and coordinates of the pixels at the same time. The system has the ability to be applied on all types of images with any dimensions. The results of the system were tasted and compared with the traditional algorithms. The results that have been obtained from the simulation show that the proposed system has higher degree of security and faster encryption time.
{"title":"Chaotic encryption system based on pixel value and position transformation for color images","authors":"Atheer J. Mansoor, Hikmat N. Abdullah, M. F. Al-Gailani, H. Ziboon","doi":"10.1109/SSD52085.2021.9429368","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429368","url":null,"abstract":"In this paper, a full image encryption system is proposed. The proposed system depends on changing the value and coordinates of the pixels at the same time. The system has the ability to be applied on all types of images with any dimensions. The results of the system were tasted and compared with the traditional algorithms. The results that have been obtained from the simulation show that the proposed system has higher degree of security and faster encryption time.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"91 1","pages":"433-439"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80372414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429443
Gaith Baccouche, A. S. Saidi, C. B. Salah, S. Makhloufi, A. H. Hamida
This article provides a comparative study of the technical requirements applied by the two Tunisian and Algerian countries. This comparison including Low Voltage Ride-Through (LVRT) and High Voltage Ride-Through (HVRT) is provided and discussed. As well, each country establishes its own network code to meet the minimum technical criteria required and revises it frequently to cope with new modifications of the public service, to keep the protection, the quality of the power supply, the reliability and the stability. This comparison showed that the two countries have a great similarity in their grid codes almost 90% and almost 100% in certain intervals. All results have been checked and carried out using real electrical parameters data.
{"title":"A Comparative Analysis Study of Tunisian and Algerian Grid Codes Relevant to PV Solar Energy Installations","authors":"Gaith Baccouche, A. S. Saidi, C. B. Salah, S. Makhloufi, A. H. Hamida","doi":"10.1109/SSD52085.2021.9429443","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429443","url":null,"abstract":"This article provides a comparative study of the technical requirements applied by the two Tunisian and Algerian countries. This comparison including Low Voltage Ride-Through (LVRT) and High Voltage Ride-Through (HVRT) is provided and discussed. As well, each country establishes its own network code to meet the minimum technical criteria required and revises it frequently to cope with new modifications of the public service, to keep the protection, the quality of the power supply, the reliability and the stability. This comparison showed that the two countries have a great similarity in their grid codes almost 90% and almost 100% in certain intervals. All results have been checked and carried out using real electrical parameters data.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"22 1","pages":"719-724"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83304635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429351
R. Fezai, Kais Bouzrara, M. Mansouri, H. Nounou, M. Nounou, M. Trabelsi
In this paper, Interval Gaussian Process Regression (IGPR)-based Random Forest (RF) proposed for fault detection and diagnosis (FDD) due to its effectiveness in handling uncertain industrial process data, which are often with high nonlinearities and strong correlations. This technique aims to extract the features from raw data using IGPR technique. Then, the interval mean vector and the interval variance matrix obtained from IGPR technique are used as inputs to the Random Forest (RF) classifier. The results show the effectiveness of the features and the classifiers in detection of faults of Wind Energy Conversion (WEC) Systems.
{"title":"Random forest-based nonlinear improved feature extraction and selection for fault classification","authors":"R. Fezai, Kais Bouzrara, M. Mansouri, H. Nounou, M. Nounou, M. Trabelsi","doi":"10.1109/SSD52085.2021.9429351","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429351","url":null,"abstract":"In this paper, Interval Gaussian Process Regression (IGPR)-based Random Forest (RF) proposed for fault detection and diagnosis (FDD) due to its effectiveness in handling uncertain industrial process data, which are often with high nonlinearities and strong correlations. This technique aims to extract the features from raw data using IGPR technique. Then, the interval mean vector and the interval variance matrix obtained from IGPR technique are used as inputs to the Random Forest (RF) classifier. The results show the effectiveness of the features and the classifiers in detection of faults of Wind Energy Conversion (WEC) Systems.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"68 1","pages":"601-606"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90469054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429302
B. Brahmi, Ibrahim El Bojairami, T. Ahmed, M. Rahman, Asif Al Zubayer Swapnil, Javier Dario Sanjuan De Caro
The paper put forth presents the design and validation of a novel adaptive, variable gain, sliding mode control (SMC) reaching law, for the purpose of controlling unperturbed nonlinear systems. The novelty of this law stems from its capability to overcome the main limitations involved with conventional SMCs. In contrast to existing reaching laws, the presented law is potentially able to achieve high system performance, reduce the chattering problem significantly, and ensure fast convergence of system trajectories to equilibrium. The designed law integrates the features of both, the exponential reaching law (ERL) and the power rate reaching law (PRL), meanwhile, it overcomes their limitations. Simulation and comparison case studies against ERL and PRL are also carried out with Forearm and Wrist Rehabilitation Robot to validate the effectiveness and advantages of the proposed reaching law scheme (Proposed RL).
{"title":"New Adaptive Sliding Mode for Unperturbed Forearm and Wrist Rehabilitation Robot","authors":"B. Brahmi, Ibrahim El Bojairami, T. Ahmed, M. Rahman, Asif Al Zubayer Swapnil, Javier Dario Sanjuan De Caro","doi":"10.1109/SSD52085.2021.9429302","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429302","url":null,"abstract":"The paper put forth presents the design and validation of a novel adaptive, variable gain, sliding mode control (SMC) reaching law, for the purpose of controlling unperturbed nonlinear systems. The novelty of this law stems from its capability to overcome the main limitations involved with conventional SMCs. In contrast to existing reaching laws, the presented law is potentially able to achieve high system performance, reduce the chattering problem significantly, and ensure fast convergence of system trajectories to equilibrium. The designed law integrates the features of both, the exponential reaching law (ERL) and the power rate reaching law (PRL), meanwhile, it overcomes their limitations. Simulation and comparison case studies against ERL and PRL are also carried out with Forearm and Wrist Rehabilitation Robot to validate the effectiveness and advantages of the proposed reaching law scheme (Proposed RL).","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"15 1","pages":"1160-1165"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89868472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429327
F. Bouazza, A. Kouzou, Kaabeche Hamid
In this paper, a simple and low cost method based on a mathematical equation is used to calculate the solar irradiance (G). It is based on the short circuit currents output and the currents at the maximum power point (MPP) of the PV module at both Standard test conditions (STC) and Actual conditions of irradiation & temperature (G,T). The values of currents at $(STC){I_{sc}(STC); I_{mp}(STC)}$ are read directly on the PV module datasheet, while the other value of currents at ($G, T$) conditions ${I_{sc}(G, T); I_{mp}(G, T)}$ are measured via a data acquisition card equipped with a PIC microcontroller and voltage and current sensors. The used equation with the four currents is programmed using LabView interface. Several irradiances deduced from these four data are displayed on the graphical interface. Three different PV modules have been tested and the obtained solar irradiances have been compared to those displayed by a first class pyranometer. The error calculation confirms the accuracy of the proposed method.
{"title":"Solar Irradiance measuring using PV module and PIC microcontroller based Electronic assembly","authors":"F. Bouazza, A. Kouzou, Kaabeche Hamid","doi":"10.1109/SSD52085.2021.9429327","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429327","url":null,"abstract":"In this paper, a simple and low cost method based on a mathematical equation is used to calculate the solar irradiance (G). It is based on the short circuit currents output and the currents at the maximum power point (MPP) of the PV module at both Standard test conditions (STC) and Actual conditions of irradiation & temperature (G,T). The values of currents at $(STC){I_{sc}(STC); I_{mp}(STC)}$ are read directly on the PV module datasheet, while the other value of currents at ($G, T$) conditions ${I_{sc}(G, T); I_{mp}(G, T)}$ are measured via a data acquisition card equipped with a PIC microcontroller and voltage and current sensors. The used equation with the four currents is programmed using LabView interface. Several irradiances deduced from these four data are displayed on the graphical interface. Three different PV modules have been tested and the obtained solar irradiances have been compared to those displayed by a first class pyranometer. The error calculation confirms the accuracy of the proposed method.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"10 1","pages":"1053-1058"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86553545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1109/SSD52085.2021.9429495
Mouna Afif, R. Ayachi, Yahia Said, M. Atri
Indoor signage plays an important role in finding specific destinations and way-finding especially for blind and visually impaired people (VIP). In this paper, we developed a new indoor signage classifier using deep convolutional neural Network (DCNN). Computer vision-based systems using cameras-based present a potential intermediate to assist blind and VIP persons on accessing unfamiliar buildings. Experiments were performed on a new dataset taken in an indoor building in France. The proposed dataset present 800 natural images divided into 4 indoor signs. Results achieved show that our proposed approach presents very encouraging results coming to 99.8% as recognition precision rate.
{"title":"Indoor sign Detection System for Indoor Assistance Navigation","authors":"Mouna Afif, R. Ayachi, Yahia Said, M. Atri","doi":"10.1109/SSD52085.2021.9429495","DOIUrl":"https://doi.org/10.1109/SSD52085.2021.9429495","url":null,"abstract":"Indoor signage plays an important role in finding specific destinations and way-finding especially for blind and visually impaired people (VIP). In this paper, we developed a new indoor signage classifier using deep convolutional neural Network (DCNN). Computer vision-based systems using cameras-based present a potential intermediate to assist blind and VIP persons on accessing unfamiliar buildings. Experiments were performed on a new dataset taken in an indoor building in France. The proposed dataset present 800 natural images divided into 4 indoor signs. Results achieved show that our proposed approach presents very encouraging results coming to 99.8% as recognition precision rate.","PeriodicalId":6799,"journal":{"name":"2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)","volume":"11 1","pages":"1383-1387"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88828002","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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