2020 2nd International Conference on Advancements in Computing (ICAC)最新文献_第2页

Melanoma Skin Cancer Detection Using Image Processing and Machine Learning Techniques 使用图像处理和机器学习技术检测黑色素瘤皮肤癌

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357309

MA. Ahmed Thaajwer, U. P. Ishanka

{"title":"Melanoma Skin Cancer Detection Using Image Processing and Machine Learning Techniques","authors":"MA. Ahmed Thaajwer, U. P. Ishanka","doi":"10.1109/ICAC51239.2020.9357309","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357309","url":null,"abstract":"In humans, skin cancer is the most common and severe type of cancer. Melanoma is a deadly type of skin cancer. If it identifies early stages, it can be easily cured. The formal method for diagnosing melanoma detection is the biopsy method. This method can be a very painful one and a time-consuming process. This study gives a computer-aided detection system for the early identification of melanoma. In this study, image processing techniques and the Support vector machine (SVM) algorithms are used to introduce an efficient diagnosing system. The affected skin image is taken, and it sent under several pre-processing techniques for getting the enhanced image and smoothed image. Then the image is sent through the segmentation process using morphological and thresholding methods. Some essential texture, color and shape features of the skin images are extracted. Gray Level Co-occurrence Matrix (GLCM) methodology is used for extracting texture features. These extracted GLCM, color and shape features are given as input to the SVM classifier. It classifies the given image into malignant melanoma or benign melanoma. High accuracy of 83% is achieved when we combine and apply the shape, color and GLCM features to the classifier.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134601180","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: 18

Ontology based Optimized Algorithms to Communicate with a Service Robot using a User Command with Unknown Terms 基于本体的未知项用户指令与服务机器人通信优化算法

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357254

U. Rajapaksha, C. Jayawardena

{"title":"Ontology based Optimized Algorithms to Communicate with a Service Robot using a User Command with Unknown Terms","authors":"U. Rajapaksha, C. Jayawardena","doi":"10.1109/ICAC51239.2020.9357254","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357254","url":null,"abstract":"In real world applications, seamless integration of heterogeneous robots is very important to complete a task given by high level user instruction with unknown terms to all robotic devices simultaneously. In this research, we have used the technologies in Semantic Web mainly with the use of the ontology to represent the meaning of the unknown terms in the given high level instruction. If a user has given an instruction in domestic environment as “clean My Room 01 while finding my key for the car” to clean different locations with different capabilities and there can be robot who does not the meaning of the “key”. The robot can get the meaning of the unknown term by communicating with the semantic analyzer which is working with the ontology. According to our analysis we have proved that the object represented by the unknown term can be detected more accurately with compared to existing object detection algorithms since our ontology can represents more concepts related to the given object. The results indicate that if number of unknown terms in the command are increased then the time taken to process the command also be increased.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132636285","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: 11

AI - Driven Smart Bin for Waste Management 用于废物管理的人工智能驱动的智能垃圾箱

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357151

A. G. D. T. Abeygunawardhana, R. M. M. M. Shalinda, W. Bandara, W. D. S. Anesta, D. Kasthurirathna, L. Abeysiri

{"title":"AI - Driven Smart Bin for Waste Management","authors":"A. G. D. T. Abeygunawardhana, R. M. M. M. Shalinda, W. Bandara, W. D. S. Anesta, D. Kasthurirathna, L. Abeysiri","doi":"10.1109/ICAC51239.2020.9357151","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357151","url":null,"abstract":"With increasing urbanization, waste has become a major problem in the present world. Therefore, proper waste management is a must for a healthy and clean environment. Though government authorities in most countries provide various solutions for waste management, solid waste tends to make a significant impact on the environment as they do not decompose easily. This research focuses on AI (Artificial Intelligence)-driven smart waste bin that can classify the most widely available solid waste materials namely Metal, Glass, and Plastic. The smart waste bin performs the separation of waste using image processing and machine learning algorithms. The system also performs the continuous monitoring of the collected waste level by using ultrasonic sensors. A dedicated mobile application will generate the optimal routes for the available waste collectors to collect the filled bins. Moreover, with this smart bin, the challenge of recognizing each waste item is overcome by using visual data as the source. Therefore, the usage of expensive sensor devices and filtration techniques to determine the category is disregarded. The smart bin can recognize the category of solid waste, collect it to the specified container, and notify the garbage level in each container. So, it is a portable waste management system.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128898714","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

Secured, Intelligent Blood and Organ Donation Management System - “LifeShare” 安全、智能的血液及器官捐献管理系统-“LifeShare”

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357211

P.L. Wijayathilaka, P. H. P. Gamage, K.H.B. De Silva, A.P.P.S. Athukorala, K. Kahandawaarachchi, K. Pulasinghe

{"title":"Secured, Intelligent Blood and Organ Donation Management System - “LifeShare”","authors":"P.L. Wijayathilaka, P. H. P. Gamage, K.H.B. De Silva, A.P.P.S. Athukorala, K. Kahandawaarachchi, K. Pulasinghe","doi":"10.1109/ICAC51239.2020.9357211","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357211","url":null,"abstract":"The scarcity and exigency for blood and organs has created many discrepancies in current approaches. These have created the criteria for malpractices such as organ trafficking and black market selling. This research presents a solution with a secured-smart blood and organ donation web developed system, allowing both patients and healthcare providers to access information about the blood and organ processing records. The database would be managed using the Blockchain technology which could be only accessed by authorized users. Finally, tracking all registered donors, the proposed system generates a smart identity developed by Ethereum Smart Contract (ESC). System predicts blood demand for the future ten years using Linear Regression Model with 0.998 of high R-squared accuracy value. This reduces shortages and wastage of blood. Also, using global positioning system and K-Nearest Neighbors Machine Learning algorithm, the system finds the best matches among donors and seekers according to the nearest location. Further, the system will automatically send questionnaires for registered users to identify and evaluate their awareness and issues about organ donation. Overall, this study aims for a secured and transparent web application. Thus, it facilitates an innovative and a productive blood donation and organ transplantation process in Sri Lankan healthcare sector.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121952456","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: 13

Smart Personal Intelligent Assistant for Candidates of IELTS Exams 面向雅思考生的Smart个人智能助手

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357150

S.S. Senevirathne, G.U.D. Fernando, J.B. White, S.T.H. Divyanjala, Udara Srimath S. Samaratunge Arachchillage, D. Dias

{"title":"Smart Personal Intelligent Assistant for Candidates of IELTS Exams","authors":"S.S. Senevirathne, G.U.D. Fernando, J.B. White, S.T.H. Divyanjala, Udara Srimath S. Samaratunge Arachchillage, D. Dias","doi":"10.1109/ICAC51239.2020.9357150","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357150","url":null,"abstract":"Many IELTS candidates encounter problems at the examinations and majority of them are unable to achieve their goals even though they strive hard to accomplish their targets. Candidates strive to achieve higher band score in exams, but fail to achieve them due to the ignorance of prevailing weaknesses which have to be identified if they were to succeed. At present, IELTS seems to be the most demanding exam among applicants who are planning to embark their higher studies or migration purposes. Currently, there is no proper mechanism to assist candidates and generate an improvement plan by identifying the weaknesses of them. As a solution, Smart Personal Intelligent Assistant for Candidates Exams (SPIACIE) has been proposed to detect IELTS candidates' weaknesses through an analysis of their answers. The SPIACIE assesses four components (Reading, Writing, Listening, and Speaking) in IELTS exams. This paper is specifically based on the Long Short-Term Memory (LSTM) network model used to analyze the score of grammar and cohesion. To analyze the similarity of the sentences, the cosine proximity technique is proposed to evaluate the paraphrasing of the graph explanations. The final outcome of this application is to generate an improvement plan, developed using Machine Learning (ML) algorithms. The proposed algorithms are; Gaussian naïve base for reading exam, support vector machines for listening exam, decision tree classifier for speaking exam, and k-neighbors classifier for writing exam. An improvement plan on the prediction model is provided to increase the band score of the IELTS exams, based on applicants' weakness.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122034845","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

Analyzing the Influence of Current Situation in the Country for Vegetable Prices using LDA Topic Modeling 利用LDA主题模型分析国家现状对蔬菜价格的影响

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357264

I.M.G.L. Illankoon, B. Kumara

{"title":"Analyzing the Influence of Current Situation in the Country for Vegetable Prices using LDA Topic Modeling","authors":"I.M.G.L. Illankoon, B. Kumara","doi":"10.1109/ICAC51239.2020.9357264","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357264","url":null,"abstract":"The price fluctuation of vegetables is one of the economic problems faced by every country, including Sri Lanka. Many factors such as environmental conditions as well as supply, demand, social, cultural, and political situations of the country cause the price of vegetables to fluctuate. Nowadays, social media represents public opinion about current events. Twitter has become one of the fastest social media platforms for getting the latest and historical news and it can be used to track historical trends in different fields. In this paper, we applied the Latent Dirichlet Allocation (LDA) topic modeling algorithm to determine the topics of the tweets about Sri Lanka when the prices of vegetables were very high and low. Through a manual analysis of extracted topics, we identified the situation in the country during a selected period and how it has impacted the vegetable prices. According to the results, vegetable prices are on the rise during the festive season in Sri Lanka. It also appears that political factors, such as elections, do not have a major impact on vegetable prices. It seems that vegetable prices have gone up during the unstable or chaotic periods in Sri Lanka.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127135140","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

Ontological Knowledge Inferring Approach based on Term-Clustering and Intra-Cluster Permutations 基于术语聚类和聚类内排列的本体知识推断方法

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357243

Muditha Tissera, R. Weerasinghe

{"title":"Ontological Knowledge Inferring Approach based on Term-Clustering and Intra-Cluster Permutations","authors":"Muditha Tissera, R. Weerasinghe","doi":"10.1109/ICAC51239.2020.9357243","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357243","url":null,"abstract":"Ontological representation of knowledge has the advantage of being easy to reason with, but ontology construction with knowledge facts, automatically acquiring them from open domain text is often challenging. This research introduces a novel approach to infer new ontological knowledge in a fully automated manner. Such ontological knowledge can be utilized in both constructing new ontologies and extending existing ontologies. Basic level triples that can be extracted from open domain text are used as the data source for this study. A simple mechanism has been introduced to convert the triple into an ontological knowledge fact and such ontological knowledge facts are further processed to infer new ontological knowledge. The main focus of this research is to infer new ontological knowledge using an advanced term-clustering mechanism followed by an intra-cluster permutation generation task. Generated permutations are potential to be selected as good ontological knowledge facts. Inferred ontological knowledge was tested with inter-rater agreement method with high reliability and variability. Results demonstrated that, out of 43,103 triples, this method inferred 127,874 ontological knowledge (approximately 3 times) of which 66% were estimated to be effective. Finally, this research contributes a reliable approach which requires a single pass over the corpus of triples to infer a large number of ontological knowledge facts that can be used to construct/extend ontologies.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131954220","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

Towards the Development of a User-Centred Health Management Application for Elderly 面向以用户为中心的老年人健康管理应用的开发

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/icac51239.2020.9357142

Fathima Naja Musthafa, Mumtaz Begum Mustafa, Farzana Parveen Tajudeen, T. S. Ramasamy, A. Sinniah

{"title":"Towards the Development of a User-Centred Health Management Application for Elderly","authors":"Fathima Naja Musthafa, Mumtaz Begum Mustafa, Farzana Parveen Tajudeen, T. S. Ramasamy, A. Sinniah","doi":"10.1109/icac51239.2020.9357142","DOIUrl":"https://doi.org/10.1109/icac51239.2020.9357142","url":null,"abstract":"As the world is gearing towards an increased older adult population, the need to focus on wellness and healthy lifestyle become essential. Studies reveal evident of delaying the chronic diseases that cause serious health issues among the elderly, which is made possible by educating the elderly on healthy ageing. Mobile applications can be used as a tool to educate the elderly on health management. Hence, the focus on developing health management mobile applications has arisen among the software engineering community as well as the medical experts. Though a considerable amount of health management applications are available online, which some of it are already in use, many still find these application to be less effective and the elderly community is left behind in using them as they don't provide sufficient features preferred by the elderly. Hence, this research focuses on developing a user centered health management application exclusively for the elderly. User requirement related information was collected, and a thorough literature review was conducted with the aim of finding the preferred features needed in the application and the proof of concept prototype was developed. The developed application underwent a functional testing process, where the system performed as expected.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114194254","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

Gamified Smart Mirror to Leverage Autistic Education - Aliza 利用自闭症教育的游戏化智能镜子- Aliza

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357065

R. Najeeb, J. Uthayan, R.P. Lojini, G. Vishaliney, Jesuthasan Alosius, A. Gamage

{"title":"Gamified Smart Mirror to Leverage Autistic Education - Aliza","authors":"R. Najeeb, J. Uthayan, R.P. Lojini, G. Vishaliney, Jesuthasan Alosius, A. Gamage","doi":"10.1109/ICAC51239.2020.9357065","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357065","url":null,"abstract":"Autism is a neurodevelopmental disorder that causes difficulties in communication, emotional responsiveness and social skills. There has been a global increase rate in autism and lack of resources locally to educate ASD children. As this condition affects children at an early stage, it remains a challenge in learning. Even though today's world there are ample of teaching methods and technologies, people are unaware of the use and impact of them. This paper presents “Aliza” Gamified smart mirror to teach basic education for autism children. “Aliza” consists of four core components such as writing mentor for pre-writing, math tutor for mathematics, verbal trainer for speech and attentiveness tracker for emotion detection. These components assist and enhance their competency in education. The users of the “Aliza” will be constantly monitored and evaluated during their training using Convolutional Neural Network (CNN). The interactive games are given to impact their learning process while the generated report from the Deep Learning evaluation system can acquaint parents and the tutors with the progress of the children. Through this research, it is expected to improve autistic children's basic education with assistance of “Aliza”.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121750204","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

Exploiting Multivariate LSTM Models with Multistep Price Forecasting for Agricultural Produce in Sri Lankan Context 斯里兰卡农产品多步价格预测的多元LSTM模型研究

2020 2nd International Conference on Advancements in Computing (ICAC) Pub Date : 2020-12-10 DOI: 10.1109/ICAC51239.2020.9357144

Shriram Navaratnalingam, N. Kodagoda, Kushnara Suriyawansa

{"title":"Exploiting Multivariate LSTM Models with Multistep Price Forecasting for Agricultural Produce in Sri Lankan Context","authors":"Shriram Navaratnalingam, N. Kodagoda, Kushnara Suriyawansa","doi":"10.1109/ICAC51239.2020.9357144","DOIUrl":"https://doi.org/10.1109/ICAC51239.2020.9357144","url":null,"abstract":"In Sri Lanka agricultural produces possess a large supply which involves various stakeholders and thus, fluctuation of the agricultural produce prices has a direct impact on the purchasing decisions of the consumer. So, the main purpose of this study is to address the problem faced by the consumer due to poor awareness of price fluctuation which consequently astonish the consumers and hinder them from making better purchasing decisions. The research study is being specially developed in a way to adapt the Sri Lankan agricultural consumer market that is mainly based on Pettah and Dambulla trade centers. As the study we exploited different types of LSTM model with multivariate inputs along with the different combination of multistep models. The result of the study reveals that better performance was obtained for the multivariate CNN LSTM model with encoder decoder multistep model which provided an average RMSE of 19.46 Sri Lankan rupees per kilogram with an average RMSPE of 14.9%. Also, study reveals a correlation between price fluctuation and standard days of the week, where a better prediction was obtained for Monday and Tuesday with an average RMSE of 17.2 and 17.7 Sri Lankan rupees per kilogram respectively with an average RMSPE of 12.2%. Based on the input timestep considered for model, though 14 days and 21 days provided a similar result with minor variation result reveals that 14 days provided a lesser standard deviation of 0.17 than 21 days standard deviation which is 0.98.","PeriodicalId":253040,"journal":{"name":"2020 2nd International Conference on Advancements in Computing (ICAC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124902534","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