2017 International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第2页

Integrated flame control system in closed furnace using PLC 采用PLC的闭式炉火焰综合控制系统

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282533

Aakanksha Taliwal, Tanvika M. Patel

引用次数: 0

Feasibility of music composition using artificial neural networks 利用人工神经网络作曲的可行性

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282520

K. Venugopal, P. Madhusudan

引用次数: 2

Upgrading cars running on Indian roads: Analyzing its impact on environment using ANN 升级在印度道路上运行的汽车:使用人工神经网络分析其对环境的影响

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282655

M. Tabrez, Md. Asif Hasan, N. Rafiuddin, F. I. Bakhsh

引用次数: 2

Image processing based body temperature estimation using thermal video sequence 基于图像处理的热视频序列体温估计

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282585

Arpita Sharma, Arvind R. Yadav

{"title":"Image processing based body temperature estimation using thermal video sequence","authors":"Arpita Sharma, Arvind R. Yadav","doi":"10.1109/ICCMC.2017.8282585","DOIUrl":"https://doi.org/10.1109/ICCMC.2017.8282585","url":null,"abstract":"Temperature is most significant vital sign in human body regulation system if this increases at certain level it may be dangerous because temperature support whole immune system, also supporting the healing process. However, high temperature causes serious reimbursements to the human body. Therefore, in this paper, authors propose a non-contact temperature algorithm based on thermography analysis. The purpose of developing this system is to provide body temperature estimation without any discomfort. In the proposed approach viola jones algorithm has been used for face detection in a video stream. Further, as a temperature is not going to change within few seconds, thus rather than measuring the temperature of the face in each of the frame, authors have incorporated a algorithm which selects best frame that contains all the features of the face and then the temperature for the same has been measured. At the end temperature is of the face is exhibited. Simulation results of this established algorithm shows the human face detection & temperature estimation of the FLIR and IR camera videos. Results have been validated against standard temperature measuring device.","PeriodicalId":163288,"journal":{"name":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127695335","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: 9

Framework for IoT applications in the cloud, is it needed? A study 云中的物联网应用框架，是否需要?一项研究

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282630

S. Shyam, G. V. Prasad

引用次数: 3

A practical method estimates on - load tap changers' operation status 一种实用的有载分接开关运行状态评估方法

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282599

Ming-Jong Lin

引用次数: 2

A machine learning approach for the classification of cardiac arrhythmia 心律失常分类的机器学习方法

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282537

P. Shimpi, S. Shah, Maitri Shroff, Anand Godbole

引用次数: 38

Efficient heart disease prediction system using optimization technique 基于优化技术的高效心脏病预测系统

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282712

C. Suvarna, A. Sali, Sakina Salmani

{"title":"Efficient heart disease prediction system using optimization technique","authors":"C. Suvarna, A. Sali, Sakina Salmani","doi":"10.1109/ICCMC.2017.8282712","DOIUrl":"https://doi.org/10.1109/ICCMC.2017.8282712","url":null,"abstract":"In this modern society where large number of humans follow a sedentary lifestyle following an 8 hour job cycle, cardio vascular diseases or heart diseases is one of the leading causes of mortality worldwide. The computers at the hospitals of the healthcare industries are used to collect huge amounts of information regarding the patients and their ailments. This huge repository of information contains wealth of knowledge. The hidden patterns and relationships in the data is mostly overlooked. Diagnosing cardio vascular diseases in patients is a difficult task and doctors who can accurately predict such diseases are few in number. This research paper focuses on developing a prediction algorithm with the help of data mining and optimization techniques. Data Mining refers to using a variety of techniques to identify information or decision making knowledge in the database and extracting these in a way that they can put to use in areas such as decision support, predictions, forecasting and estimation. We will be using the Particle Swarm Optimization technique which is an inherently distributed algorithm where the solution for a problem emerges from the interactions between many simple individual agents called particles. The data source we have used for experimental testing are commonly used and considered as a de facto standard for heart disease prediction reliability ranking. We will also be using a slightly modified version of PSO with constriction factor called Constricted PSO. The results obtained show that Particle Swarm Data Mining Algorithms are competitive, not only with other evolutionary techniques, but also with industry standard algorithms, and can be successfully applied to heart disease prediction.","PeriodicalId":163288,"journal":{"name":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1982 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130307094","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

Performance comparison of IST and multi scale principal component analysis in the EEG signal processing IST与多尺度主成分分析在脑电信号处理中的性能比较

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282523

Dr. B. Krishna Kumar, Dr. K. V. S. V. R. Prasad

{"title":"Performance comparison of IST and multi scale principal component analysis in the EEG signal processing","authors":"Dr. B. Krishna Kumar, Dr. K. V. S. V. R. Prasad","doi":"10.1109/ICCMC.2017.8282523","DOIUrl":"https://doi.org/10.1109/ICCMC.2017.8282523","url":null,"abstract":"The removal of Ocular Artifacts (OA) in Electroencephalogram (EEG) data is one of the key challenges in the analysis of brain recordings. Brain activity produces electroencephalogram signals, which consists of some of vital signs of neurological disorders such as epilepsy, tumor cerebrovascular lesions and the problems associated with the trauma. These signals can be acquired by placing the electrodes on the scalp at specified positions and exists in order of 1–5μv, whose frequency range is DC-64 Hz. Acquisition of these signals mainly suffers from different unwanted signals (artifacts or noise) resulting in less signal information for identification. In this paper, two algorithms are proposed namely, Multi Scale Principal Component Analysis (MSPCA) and Iterative Soft Thresholding (IST) using wavelets in removing the Ocular Artifacts (OA) present in the EEG signals. This paper discusses not only the performance comparison of two algorithms on statistical parameters of EEG signals such as Signal to Noise Ratio, (SNR), SNRI or Noise Figure (NF) and Absolute Average Error (AAE) but also estimated the run time of each algorithm i.e., computational time of each algorithm.","PeriodicalId":163288,"journal":{"name":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133141301","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

Automatic text summarization by local scoring and ranking for improving coherence 通过局部评分和排序来提高连贯性的自动文本摘要

2017 International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2017-07-18 DOI: 10.1109/ICCMC.2017.8282539

P. Krishnaveni, S. Balasundaram

{"title":"Automatic text summarization by local scoring and ranking for improving coherence","authors":"P. Krishnaveni, S. Balasundaram","doi":"10.1109/ICCMC.2017.8282539","DOIUrl":"https://doi.org/10.1109/ICCMC.2017.8282539","url":null,"abstract":"Existence of large amount of textual information available on the internet emerged serious research in the area of machine generated summarization. Manual summarization of these online text documents is a very difficult task for human beings. So we need an automatic text summarizer. Automatic Text Summarization (ATS) is “condensing the source text into a shorter version, while preserving its information content and overall meaning”. Even though the work of automatic text summarization started in 1950's, still it is lacking to achieve more coherent and meaningful summaries. The proposed approach provides automatic feature based extractive heading wise text summarizer to improve the coherence thereby improving the understandability of the summary text. It summarizes the given input document using local scoring and local ranking that is it provides heading wise summary. Headings of a document give contextual information and permit visual scanning of the document to find the search contents. The proposed approach applies the same features to all document sentences. But it ranks the sentences heading wise and selects top n sentences from each heading where n depends upon compression ratio. The final heading wise summary produced by this approach is a collection of summary of individual headings. Since the heading wise summary contains the equal proportion of sentences from each heading, it reduces the coherent gap of the summary text. Also it improves the overall meaning and understanding of the summary text. The outcomes of the experiment clearly show that heading wise summarizer provides better precision, recall and f-measure over the main summarizer, Ms-word summarizer, free summarizer and Auto summarizer.","PeriodicalId":163288,"journal":{"name":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114991756","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: 23