2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)最新文献

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Identifying the Level of Diabetic Retinopathy Using Deep Convolution Neural Network 利用深度卷积神经网络识别糖尿病视网膜病变的水平
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350905
Rahat Hassan, M. A. Rahman, I. Ullah, Ali Hamdan Alenezi, Taha H. Rassem
{"title":"Identifying the Level of Diabetic Retinopathy Using Deep Convolution Neural Network","authors":"Rahat Hassan, M. A. Rahman, I. Ullah, Ali Hamdan Alenezi, Taha H. Rassem","doi":"10.1109/ETCCE51779.2020.9350905","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350905","url":null,"abstract":"Diabetic Retinopathy is the leading cause of blindness in the last 100 years. The traditional screening process for DR and its stages takes a lot of time, and it is not practical. Using machine learning techniques and image processing, we can automate detecting diabetic retinal disease and disease stage with acceptable performance. In this work, we have used multiple deep convolution neural networks (CNN) with the same architecture of InceptionV3. Each of the pre-trained Inception V3 architecture is retrained with 2200 preprocessed and leveled images. The dataset is preprocessed using multiple high performing and effective image processing techniques. Then the newly trained models are used for identifying the level of DR. In the final stage, we use a voting scheme for classifying the level of DR from the output of each model. We have achieved 90.5% accuracy in binary classification (Normal/DR) and 81.1% accuracy in 5-class classification.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131271777","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}
引用次数: 1
Event Detection and Knowledge Mining from Unlabelled Bengali News Articles 无标签孟加拉语新闻文章的事件检测与知识挖掘
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350891
Iftakhar Ali Khandokar, I. Mamun, Tasmia Ishrat Alam Chadni, Z. Anas, Swakkhar Shatabda
{"title":"Event Detection and Knowledge Mining from Unlabelled Bengali News Articles","authors":"Iftakhar Ali Khandokar, I. Mamun, Tasmia Ishrat Alam Chadni, Z. Anas, Swakkhar Shatabda","doi":"10.1109/ETCCE51779.2020.9350891","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350891","url":null,"abstract":"Text mining is one of the most important tasks in Natural Language Processing (NLP). It is often very difficult to detect events of interest from vast unstructured or data that is not properly labeled. In this paper, we present a machine learning-based approach to discriminate particular event-related news from its text content. We focus here particularly on violence and related events. We have created a dataset from popular Bengali newspapers and used a keyword-based search method to select violence-related news articles. Based on the dataset, we first trained a supervised learning model. We have experimented with six classification algorithms where Logistic Regression outperformed each of the contemporary algorithms in both full and reduced feature set acquiring 75.7 % and 83.4 % accuracy respectively. Using the models, we then further analyzed violence- related news data to find out important insights from unlabeled data.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125386351","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}
引用次数: 0
Multi-Access Edge Computing-Aware Internet of Things: MEC-IoT 多接入边缘计算感知物联网:MEC-IoT
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350909
Mobasshir Mahbub, Md. Shamrat Apu Gazi, Sayed Al Arabi Provar, Md. Saiful Islam
{"title":"Multi-Access Edge Computing-Aware Internet of Things: MEC-IoT","authors":"Mobasshir Mahbub, Md. Shamrat Apu Gazi, Sayed Al Arabi Provar, Md. Saiful Islam","doi":"10.1109/ETCCE51779.2020.9350909","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350909","url":null,"abstract":"Recently, the IoT, which is the basis of future consumer values for both product and service companies, has emerged from experimental technology. The development of Multi-Access Edge Computing (MEC) technologies intended for growing the ability of cloud services to the network edge, offering links to radio network services in real-time, low latent, and high-bandwidth conditions. MEC is thus an important enabler for IoT services that need to be operated in real-time. This review gives a comprehensive description of the utilization of MEC technologies for IoT implementations and their cooperative interactions. The work moreover discusses the technical characteristics of employing MEC-aware IoT applications and provides insights into various sorts of integration technologies. This article extended the literature regarding MEC focusing on evolving technologies and trends.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114859220","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}
引用次数: 3
Simulation on Robot Arm Manipulator Modeling using Dynamic Kinematic 机械臂机械臂动力学建模仿真
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350907
R. M. Ramli, N. A. Herman, Mohd Azrul Hisham Mohd Adib
{"title":"Simulation on Robot Arm Manipulator Modeling using Dynamic Kinematic","authors":"R. M. Ramli, N. A. Herman, Mohd Azrul Hisham Mohd Adib","doi":"10.1109/ETCCE51779.2020.9350907","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350907","url":null,"abstract":"This simulation shows about analysis of 6 Degrees of Freedom (DOF) Of robotic arm kit generated by Robo Analyzer software. Moreover, this visual simulation consisted of mathematical elements that can animate the mechanical of motion for a robot manipulator. Nowadays, there was a lot of Unmanned Ground Vehicle (UGV) had been equipped with manipulator but the lack of stability in pick and place object was the main problem in safety issues especially in a safety application. For example, safety authorities need to lift picric acid by using less vibration and correct trajectory to avoid an explosion. Therefore, the main objective of this research is to identify the value of the position and orientation of each joint correctly because all these values were needed to be used by the controller to tackle stability issues. Besides, parameters to conduct the simulation can solve forward kinematic of the robot in the form of a 3D model which can determine the suitable motor with enough power and torque that can be used by each of the joints. This Robo Analyzer used a geometrical approach which is first, it used Denavit Hartenberg parameters to determine end effectors. Next, Robo Analyzer used forward and inverse dynamic analysis to get torque values. The simulation results clearly show the effectiveness of Robo Analyzer software to generate a simulation of the coordinate for each joint, joint parameter, and joint torque that is needed to select a suitable motor with enough torque. In other words, the significance of this research is, by using Robo Analyzer, the user can forecast the hardware simulation result before applying it in the real situation because the visual stimulation can animate the motion of the robot from the beginning until its last position.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"580 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115896864","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}
引用次数: 1
Performance of Machine Learning and Deep Learning on Arabic Handwritten Text Recognition 机器学习和深度学习在阿拉伯语手写文本识别中的表现
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350863
J. AlKhateeb, A. Turani, Abdulrahman A. Alsewari
{"title":"Performance of Machine Learning and Deep Learning on Arabic Handwritten Text Recognition","authors":"J. AlKhateeb, A. Turani, Abdulrahman A. Alsewari","doi":"10.1109/ETCCE51779.2020.9350863","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350863","url":null,"abstract":"This paper proposes machine learning and deep learning techniques for recognizing Arabic handwritten text. Finally, this paper introduces a comparative study between them in term of their performance. Actually, the classification of Arabic handwritten text plays a vital role in the computer vision domain, where traditional machine learning techniques and deep learning techniques are commonly used by researchers. In this paper, both machine learning and deep learning techniques are proposed and evaluated for recognizing Arabic handwritten text. Several experiments were carried out using both machine learning and deep learning on two different databases the AHCR and ADBase. The AHCR contains 28000 images of handwritten Arabic alphabet letters written by 100 writers. While the ADBase contains 70,000 images of handwritten Arabic digits written by 700 writers. The experimental results on both databases have demonstrated that the performance of the deep learning outperforms machine learning.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127879938","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}
引用次数: 2
Drugs Rating Generation and Recommendation from Sentiment Analysis of Drug Reviews using Machine Learning 使用机器学习从药物评论的情感分析中生成药物评级和推荐
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350868
Md.Deloar Hossain, M. S. Azam, Md Jahan Ali, Hakilo Sabit
{"title":"Drugs Rating Generation and Recommendation from Sentiment Analysis of Drug Reviews using Machine Learning","authors":"Md.Deloar Hossain, M. S. Azam, Md Jahan Ali, Hakilo Sabit","doi":"10.1109/ETCCE51779.2020.9350868","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350868","url":null,"abstract":"A recommendation system can assist the user to compose an understanding of requirements and propose informed decisions from a lot of complicated knowledge. Recommendation from an analysis of sentiments seems to be a great challenge as user-generated content is represented using human language in several complicated ways. Many studies have focused on common fields such as reviews of electrical items, films, and restaurants, but not enough on health and medical issues. Sentiment analysis of healthcare in general and that of the drug experiences of individuals, in particular, may shed considerable light on how to focus on improving public health and reach the correct decision. In this paper, we design and implement a drug recommender system framework that applies sentiment analysis technologies on drug reviews. The objective of this research is to build a decision-making support platform to help patients to achieve more significant choices in drug selection. Firstly, we propose a sentimental measurement approach to drug reviews and generate ratings on drugs. Secondly, we take how much the drug reviews are useful to users, patient's conditions, and dictionary sentiment polarity of drug reviews into consideration. Then, we fuse those factors into the recommendation system to list appropriate medications. Experiments have been carried out using Decision Tree, K-Nearest Neighbors, and Linear Support Vector Classifier algorithm in rating generation and Hybrid model in recommendation based on the given open dataset. The analysis is carried out to tune the parameters for each algorithm in order to achieve greater performance. Finally, Linear Support Vector Classifier is selected for rating generation to obtain a good trade-off among model accuracy, model efficiency, and model scalability.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128129080","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}
引用次数: 17
An approach of cost-effective automatic irrigation and soil testing system 一种经济高效的自动灌溉测土系统
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350896
Istiak Mahmud, Nafis Almas Nafi
{"title":"An approach of cost-effective automatic irrigation and soil testing system","authors":"Istiak Mahmud, Nafis Almas Nafi","doi":"10.1109/ETCCE51779.2020.9350896","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350896","url":null,"abstract":"The population of Bangladesh reached beyond 16 Crores, and the rate of population is increasing every day. There will be a severe food issue after 25–30 years, so it is important to improve the agriculture. The farmers today suffer from a shortage of rainfall and water shortages. The key objective of this paper is to include an integrated irrigation network, and also to measure the quantity of the three major macronutrients, nitrogen (N), phosphorus (P), and potassium (K), in the soil, thereby saving the farmer's time, money, and strength. Comparing the solution to a color diagram determines the amount of N, P and K in the soil sample. It will describe the high, medium and low levels of N, P and K. Manual control is necessary for the conventional farmland techniques. Human interference can be minimized with automatic irrigation systems. This paper presents a smart system that will sense and analyze the NPK rate of soil and will detect the moisture rate of that land, then based on these values, automatic irrigation will happen. As a master of system ATtiny Microcontroller used here to make the device cost-effective and instead of pH meter here used TCS230 color sensor to detect the soil pH or NPK rate. To make the system more cost-effective, there used a Mobile app as the monitoring device instead of any external hardware display.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132499307","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}
引用次数: 4
Exploring Design Issues in Developing Usable Mobile Application for Dyscalculia People 探索为计算障碍人群开发可用移动应用程序的设计问题
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350910
Jubaida Quader Jerin, Tarannum Zaki, Mursalin Mahmood, S. Rochée, M. Islam
{"title":"Exploring Design Issues in Developing Usable Mobile Application for Dyscalculia People","authors":"Jubaida Quader Jerin, Tarannum Zaki, Mursalin Mahmood, S. Rochée, M. Islam","doi":"10.1109/ETCCE51779.2020.9350910","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350910","url":null,"abstract":"Dyscalculia is a disorder that causes difficulties in learning mathematical concepts, performing arithmetic operations, memorizing mathematical terms, and understanding how mathematical formulas and arguments are formulated. A number of studies have been conducted focusing on the development of IT-based screening system and learning applications for people with dyscalculia and development towards learning and training applications for dyscalculic children. However, the system developed for dyscalculic people should be usable considering its performance and user satisfaction. Therefore, the objective of this paper is to design and develop a mobile application that would provide assistance to dyscalculic people explore the design issues for developing such applications with enhanced usability. To attain this objective, four applications with alternative design of UIs have been developed, that includes, text and icon-based in English; text and icon-based in Bengali; text, icon, and voice-based in English; and text, icon and voice-based in Bengali. The outcomes of the user evaluation revealed that the interface design with Bengali text, icon, and (Bengali) voice-based applications shows better usability in terms of efficiency, effectiveness, and satisfaction.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131816460","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}
引用次数: 1
A Comprehensive Comparison Between Boost and Buck-Boost Converters in Solar MPPT With ANN 基于人工神经网络的太阳能MPPT中升压与降压变换器的综合比较
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350867
Omar Kamrul Islam, Md. Sabbir Ahmed, Khalilur Rahman, Tasnia Tahsin
{"title":"A Comprehensive Comparison Between Boost and Buck-Boost Converters in Solar MPPT With ANN","authors":"Omar Kamrul Islam, Md. Sabbir Ahmed, Khalilur Rahman, Tasnia Tahsin","doi":"10.1109/ETCCE51779.2020.9350867","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350867","url":null,"abstract":"Solar energy is one of the most promising energy sources that can meet the ever-increasing demand for electricity in the world. But due to the lower efficiency of solar photovoltaic (PV) cells and dependency on environmental conditions, it is necessary to track the Maximum Power Point (MPP) of the solar PV system. Hence, different Maximum Power Point Tracking (MPPT) methods are implemented with solar PV systems but one of the main problems associated with maximum power point tracking methods is the designing of a DC-DC converter. This paper depicts a detailed comparison between the performance of a Boost Converter and Buck-Boost converter for the maximum power point tracking of a solar PV system with Artificial Neural Network (ANN) because ANN based MPPT model provides remarkably fast tracking speed and higher efficiency. To understand the designing of a suitable DC-DC converter for MPPT with ANN, for different values of the passive elements in the converter, the response of the DC-DC converters are represented through comparison. All the test results and graphs of this paper were conducted in MATLAB/Simulink environment. The outcome of the simulations will provide a clear conception to the future researchers to predict the behaviours of the mentioned converters and design the most efficient converter accordingly for solar MPPT.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131211179","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}
引用次数: 3
Performance Comparison of Non-Invasive Blood Glucose Level using Artificial Neural Network and Ultra-Wide Band Antenna 基于人工神经网络和超宽带天线的无创血糖监测性能比较
2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) Pub Date : 2020-12-21 DOI: 10.1109/ETCCE51779.2020.9350885
Minarul Islam, S. Khatun, K. Ghazali, M. M. Saari, M. Shakib, M. S. A. Karim
{"title":"Performance Comparison of Non-Invasive Blood Glucose Level using Artificial Neural Network and Ultra-Wide Band Antenna","authors":"Minarul Islam, S. Khatun, K. Ghazali, M. M. Saari, M. Shakib, M. S. A. Karim","doi":"10.1109/ETCCE51779.2020.9350885","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350885","url":null,"abstract":"Diabetes is a serious health concern, and it became more and more common to the people due to its rapidly increasing cases. People with diabetes are required to monitor their blood glucose level regularly in order to control their blood glucose concentration level (BGCL). Common monitoring methods which taken recently are either laboratory chemical analysis or using invasive device such as glucometer to do self-checking. The process is painful and intimidating as it requires to collect blood sample from fingertips or arms. To minimize the pain and suffer, a non-invasive system for BGCL measurement is highly demanded. In this research, A small pair of ultra-wide band (UWB) antenna was utilized for BGCL measurement through human earlobe. Due to its high data rate lower transmission capacity and the power is below the noise floor level, which does not affect the human body, the UWB based system is commonly used in biomedical applications. A pair of UWB antennas attached to the P400 RCM transceivers are used in the integrated device to produce a 4.7 GHz frequency and pass through the earlobe. The scattered signal pulse obtained was translated from analogue to digital discrete values and afterwards decreased discrete values were used as artificial neural network data (ANN). In this work, feed-forward backpropagation neural network (FFBPNN) has been used as an ANN module. Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. During the investigations, LM, RP, SCG shows the performance with 89.47%, 85.96% and 82.85% respectively.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121704361","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}
引用次数: 2
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