2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第2页

Natural Language Processing based Jaro-The Interviewing Chatbot 基于自然语言处理的面试聊天机器人jaro

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819708

Jitendra Purohit, Aditya Bagwe, Rishab Mehta, Ojaswini Mangaonkar, E. George

{"title":"Natural Language Processing based Jaro-The Interviewing Chatbot","authors":"Jitendra Purohit, Aditya Bagwe, Rishab Mehta, Ojaswini Mangaonkar, E. George","doi":"10.1109/ICCMC.2019.8819708","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819708","url":null,"abstract":"Recently, recruiters have find the taxing to communicate with all their candidates about the interview process and it results in the hassle of conducting interviews. Also, in cases, where there are large volumes of applicants, communicating with thousands of candidates and conducting other screening duties add to the heap of recruitment problems. The proposed system, JARO addresses the common concerns that a candidate faces when it comes to attend the mass interviews. Some of the challenges faced are inconsistency in questions, different days, different times of the day, interviewer’s mood, venue of the interview and the list goes on. Therefore, JARO accelerates the interview process towards an unbiased decision-making process by proposing a chatbot that would conduct interviews by analyzing the candidates Curriculum Vitae (CV), based on which, it then prepares a set of questions to be asked to the candidate. The system will consist of features like resume analysis and automatic interview processes. The software would also ask questions based on the previous responses of the candidate by utilizing a Natural Language Processing (NLP) model which is very helpful in this process. After the interview process, the software would analyze the data collected to determine the right choice for the position offered. Thus, the project, JARO chatbot mainly intends to streamline the process of hiring employees.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123479118","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

Performing an assortment of tasks on Machine Learning and Benchmarking based Clinical Time Series Data 在基于临床时间序列数据的机器学习和基准测试上执行各种任务

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819783

P. Ramya, G. Geetha, V. Sindhura

{"title":"Performing an assortment of tasks on Machine Learning and Benchmarking based Clinical Time Series Data","authors":"P. Ramya, G. Geetha, V. Sindhura","doi":"10.1109/ICCMC.2019.8819783","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819783","url":null,"abstract":"Conceptual— Health care is one of the most exciting borders in data mining and machine learning. Appropriation of electronic health records (EHRs) made a blast in advanced clinical information which is accessible for examination, but progress in machine learning for healthcare research has been complicated to measure because of the absence of openly available benchmark data sets. In this paper we propose three clinical expectation benchmarks to overcome the issue of utilizing the information got from the freely accessible Medical Information Mart for Intensive Care (Emulate III) database. These assignments cover a scope of clinical issues counting demonstrating danger of mortality, anticipating length of remain and distinguishing physiologic decay. MIMIC-III (Medical Information Mart for Intensive Care III) is a considerable, openly accessible database containing de-identified wellbeing related information related with more than forty thousand patients who remained in basic consideration units of the Beth Israel Deaconess Medical Center somewhere in the range of 2001 and 2012. Our plan is to perform various tasks with an objective to mutually take in a variety of clinically important forecast assignments based on similar time arrangement information.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133449758","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

Comparative Analysis of Segmentation Techniques using Histopathological Images of Breast Cancer 乳腺癌组织病理图像分割技术的比较分析

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819659

Chetna Kaushal, D. Koundal, Anshu Singla

引用次数: 5

Multimodal Medical Image Fusion Enhancement Technique for Clinical Diagnosis 用于临床诊断的多模态医学图像融合增强技术

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819840

K. S. Asish Reddy, K. Kalyan Kumar, K. N. Kumar, V. Bhavana, H. Krishnappa

引用次数: 1

Medical Image Fusion Techniques Using Discrete Wavelet Transform 基于离散小波变换的医学图像融合技术

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819672

P. Prasad, S. Subramani, V. Bhavana, H. Krishnappa

{"title":"Medical Image Fusion Techniques Using Discrete Wavelet Transform","authors":"P. Prasad, S. Subramani, V. Bhavana, H. Krishnappa","doi":"10.1109/ICCMC.2019.8819672","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819672","url":null,"abstract":"Identifying the ailments and to cure these ailments require accurate and defined evidence that has to be obtained from different kinds of medical images, like Positron Emission tomography(PET), Computed tomography(CT), Magnetic Resonance Imaging(MRI) etc. By undergoing their respective procedure and scans, these methods are commonly used, since they provide necessary evidence and indications about the disease whose information is insufficient and vague. In the given situation, fusion of medical images can be of greatest importance as the complete standard of scans can be improvised and upgraded. Hence, combining various multimodality medical images provides an adverse image with more properly specified data of body structure and high spectral data. Image fusion is highly opted in therapeutic analysis and testing. In this paper, the MRI and PET scans are processed. Before applying any further transformations, we enhance the standard of the images, as these images are tainted and non-readable due to numerous aspects. With the help of Gaussian filters, this is one of the important spatial filtering techniques. Discrete wavelet transform is applied on the images obtained after filtering two kinds of approaches are used 1) Averaging method 2) min-max method.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122807318","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

Adaptive Prediction of Spam Emails : Using Bayesian Inference 垃圾邮件的自适应预测:使用贝叶斯推理

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819744

L. Maguluri, R. Ragupathy, Sita Rama Krishna Buddi, Vamshi Ponugoti, Tharun Sai Kalimil

{"title":"Adaptive Prediction of Spam Emails : Using Bayesian Inference","authors":"L. Maguluri, R. Ragupathy, Sita Rama Krishna Buddi, Vamshi Ponugoti, Tharun Sai Kalimil","doi":"10.1109/ICCMC.2019.8819744","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819744","url":null,"abstract":"As the recent advancement in communication technologies revolutionizes the world, Email is emerging as a wide-known communication paradigm in various business processes. Email is an effective, brisk and minimal effort correspondence approach. Email Spam is non-asked for information sent to the E-letter drops. Spam could be an enormous downside each for clients and for ISPs. As per examination these days client gets a considerable measure of spam messages then non-spam messages. In some cases spam messages may damage the reputation of a particular business process. It can be observed that in most of the popular mailing services the spam filters are being biased for the profit from the ads, i.e. they are allowing some exception for some companies that pay for advertising. This is not an ethical practice, but it is very profitable for their future business processes. Our aim is to build a spam detector using machine learning in python with the packages NLTK, Matplotlib, Word cloud, Math, pandas, NumPy. With this proposed model, we can state a specified message as spam or non-spam. It can be implemented by using Bayes’ Theorem, a simple yet powerful theorem.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133644085","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

Decoding Parallel Program Execution by using Java Interactive Visualization Environment (JIVE): Behavioral and Performance Analysis 用Java交互式可视化环境(JIVE)解码并行程序执行:行为与性能分析

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819754

Ajaz Abdul Aziz, Malavika Unny, S. Niranjana, M. Sanjana, J. Swaminathan

引用次数: 5

Electrouter-An Automated Wireless Charging Gadget Zone 电动汽车-自动无线充电设备区

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819704

Akshay Sonawane, Saurabh Vinerkar, Ujwal Thote, A. Suryavanshi, S. Waykar

{"title":"Electrouter-An Automated Wireless Charging Gadget Zone","authors":"Akshay Sonawane, Saurabh Vinerkar, Ujwal Thote, A. Suryavanshi, S. Waykar","doi":"10.1109/ICCMC.2019.8819704","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819704","url":null,"abstract":"Objective of this paper is to introduce an evolutionary-based wireless charging system. Wireless charging is a technology which is inspired by Sir Nikola Tesla's basic principles of wireless power transfer. Because of which we are able to transmit an electrical power through the air gap. Many people face low battery issues in their daily life. And it becomes worst in public places where electrical sockets are limited and not available. Moreover, they also need to take care of their traditional charging chords in their hectic day to day life. In order to abate all these difficulties of people, we developed a system which provides charging wirelessly in public area as like free public WIFI provided to the user on public area. Our system is based on Electromagnetic Induction coupling as a core functionality to possess wireless charging. In this article, we also introduced a mobile application which helps to automate charging with respect to threshold charging percentage and guard our users against harmful accidental charging disaster. Also in this article, we provide a smart automation system which focuses on electricity conservation via the Internet of Things (IoT).","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129320954","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

Player Performance Analysis in Sports: with Fusion of Machine Learning and Wearable Technology 运动员在运动中的表现分析:机器学习和可穿戴技术的融合

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819815

P. S. Harsha Vardhan Goud, Y. Mohana Roopa, B. Padmaja

{"title":"Player Performance Analysis in Sports: with Fusion of Machine Learning and Wearable Technology","authors":"P. S. Harsha Vardhan Goud, Y. Mohana Roopa, B. Padmaja","doi":"10.1109/ICCMC.2019.8819815","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819815","url":null,"abstract":"Sports are the most important recreational activity. Sports are of many types. Some may be played individually, while some are played in teams. Every country wants to get fame at the global level in different sports. In order to achieve fame, countries are investing in sports and games to enhance the performance of their teams and players. Many people are involved in the analysis of the performances in a sport like notational analyst, who make strategies and tactics for a game; bio-mechanist, who takes the responsibility of fitness of players and tries to get extraordinary results; team managers and coaches. With the advent of machine learning in sports, there is a lot of improvement in the analysis of performances. In mere future, the teams may not have coaches to analyze their performances. In this paper, I am going to discuss about the analysis role of machine learning in the improvement of performances of players and the team in different sports and how the wearable technology helps the players to know their performance levels and further improvements","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133965417","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: 6

Designing Disease Prediction Model Using Machine Learning Approach 用机器学习方法设计疾病预测模型

2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-27 DOI: 10.1109/ICCMC.2019.8819782

Dhiraj Dahiwade, Gajanan Patle, Ektaa Meshram

{"title":"Designing Disease Prediction Model Using Machine Learning Approach","authors":"Dhiraj Dahiwade, Gajanan Patle, Ektaa Meshram","doi":"10.1109/ICCMC.2019.8819782","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819782","url":null,"abstract":"Now-a-days, people face various diseases due to the environmental condition and their living habits. So the prediction of disease at earlier stage becomes important task. But the accurate prediction on the basis of symptoms becomes too difficult for doctor. The correct prediction of disease is the most challenging task. To overcome this problem data mining plays an important role to predict the disease. Medical science has large amount of data growth per year. Due to increase amount of data growth in medical and healthcare field the accurate analysis on medical data which has been benefits from early patient care. With the help of disease data, data mining finds hidden pattern information in the huge amount of medical data. We proposed general disease prediction based on symptoms of the patient. For the disease prediction, we use K-Nearest Neighbor (KNN) and Convolutional neural network (CNN) machine learning algorithm for accurate prediction of disease. For disease prediction required disease symptoms dataset. In this general disease prediction the living habits of person and checkup information consider for the accurate prediction. The accuracy of general disease prediction by using CNN is 84.5% which is more than KNN algorithm. And the time and the memory requirement is also more in KNN than CNN. After general disease prediction, this system able to gives the risk associated with general disease which is lower risk of general disease or higher.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127857897","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: 107