2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)最新文献_第7页

Predictive analysis of diabetes using J48 algorithm of classification techniques 糖尿病的预测分析采用J48算法的分类技术

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917987

K. Pradeep, N. Naveen

引用次数: 24

Educational intelligence: Applying cloud-based big data analytics to the Indian education sector 教育智能:将基于云的大数据分析应用于印度教育部门

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917930

Samiya Khan, K. A. Shakil, Mansaf Alam

{"title":"Educational intelligence: Applying cloud-based big data analytics to the Indian education sector","authors":"Samiya Khan, K. A. Shakil, Mansaf Alam","doi":"10.1109/IC3I.2016.7917930","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917930","url":null,"abstract":"Big Data technology is a generic technology, which can be applied to any real-world problem that involves a lot of data. Moreover, the use of cloud-based infrastructure to implement the big data technology makes it a cost-effective solution to the big data problem. One of the fundamental sectors that can benefit from this technology is education and research. The education system can use big data analytics to provide better education and administer the institutional operations. Research, which is an extension of education, can use analytics of big scholar data, for diverse applications, to facilitate research at the individual, team and organization level. With that said, the practical implementation and adoption of big data for education and research, collectively referred to as ‘Educational Intelligence’, faces several challenges, particularly in a developing country like India. This research paper explores how cloud-based big data analytics can be applied to Indian education and research and reviews the challenges that need to be addressed before the true benefits of this technology can be obtained.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133139199","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: 20

Load forecasting at distribution transformer using IoT based smart meter data from 6000 Irish homes 使用来自6000个爱尔兰家庭的基于物联网的智能电表数据进行配电变压器负荷预测

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918062

Mantinder Jit Singh, Prakhar Agarwal, K. Padmanabh

{"title":"Load forecasting at distribution transformer using IoT based smart meter data from 6000 Irish homes","authors":"Mantinder Jit Singh, Prakhar Agarwal, K. Padmanabh","doi":"10.1109/IC3I.2016.7918062","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918062","url":null,"abstract":"Energy Consumption in a neighborhood depends upon its socioeconomic parameters. Demographical diversities in a neighborhood in India warrants load prediction at distribution transformer (DT) rather than at utility level. In this paper two interesting techniques of load forecasting have been proposed which have not be explored till date. In both these technique a unique pattern of consumption has been deciphered for a day using parametric estimation and subsequently regression, neural network and support vector regression have been used to find the total consumption of the day which is subsequently redistributed according to pattern of the day to deduce final load pattern. In the first technique a unique model has been created for each day of the week. Though the results have been very encouraging with average error of 12% however it is not sufficient for many applications. In the second approach a set of model is created for the entire year and depending upon the previous pattern. A particular model having correlation more than 95% and similar total consumption is selected out of these models. In this case mean error has been reported as approximately 7%. Neural network considers all factors affecting the consumption and hence its corresponding predictions have been found more accurate.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133153111","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

Performance analysis of second order adaptive filter using Matlab Simulink 基于Matlab Simulink的二阶自适应滤波器性能分析

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917985

B. Misra, B. Nayak

{"title":"Performance analysis of second order adaptive filter using Matlab Simulink","authors":"B. Misra, B. Nayak","doi":"10.1109/IC3I.2016.7917985","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917985","url":null,"abstract":"Grid-tied distributed energy sources needs a proper synchronization technique which will estimate the phase angle of the grid voltage. The most common synchronisation techniques are being the phase locked loops (PLL)s, which decides the quality of grid utility power. By using different filtering techniques, the disturbance rejection capability in the (PLL)s can be improved. Synchronous reference frame phase locked loop (SRF-PLL) is the most commonly used synchronisation technique because of its simple operation good dynamic response. The conventional (SRF-PLL) controller with high bandwidth when used for synchronization work provides satisfactory performance when the grid voltage is undistorted and balanced. However SRF-PLL does not work properly in case of distorted and polluted grid conditions, so the estimated phase can have a substantial amount of unnecessary ripple. In case the grid voltage is balanced but polluted with higher order harmonic with reasonable amplitude, the detection system bandwidth can be reduced in order to attenuate the effect of harmonics on the output. Here second order adaptive filters (SOAF) are used to extract the harmonic components existing in balanced and polluted harmonic grid signals.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116430009","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: 5

Arduino based door unlocking system with real time control 基于Arduino的实时控制开门系统

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917989

Somjit Nath, Paramita Banerjee, R. Biswas, S. Mitra, M. K. Naskar

引用次数: 32

Locate, promote and split: An exponentially fast localization algorithm for wireless sensor networks 定位、提升和分割:无线传感器网络的指数级快速定位算法

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917947

A. Abbas, H. Qasem

引用次数: 0

Impact of big data in healthcare: A survey 大数据对医疗保健的影响:一项调查

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918057

D. Thara, B. Premasudha, V. Ram, R. Suma

{"title":"Impact of big data in healthcare: A survey","authors":"D. Thara, B. Premasudha, V. Ram, R. Suma","doi":"10.1109/IC3I.2016.7918057","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918057","url":null,"abstract":"As the volume of data generating is increasing day by day in this internet world, the term Big Data is becoming a very popular buzzword in today's market. Big Data is used in various sectors of the internet world. In this paper an effort is made to demonstrate that even the healthcare industries are stepping into Big Data pool to take all benefits from its various advanced tools and technologies. The paper presents the review of various research efforts made in healthcare domain using Big Data concepts and methodologies. The thought of Big Data can be used for better health planning. Its methodologies can be used for healthcare data analytics which helps in better decision making to increase the business value and customer interest and to provide eHealth services among various healthcare stakeholders by using messaging standards like Health Level?, Digital Imaging and Communications in Medicine (DICOM), Health Insurance Portability and Accountability (HIPAA), message broker etc. Big Data techniques can be applied to develop systems for the early diagnosis of disease, understand connection between HATS (HIV/AIDS Tuberculosis and Silicosis) and also to develop integrated data analytics platforms. After presenting these many positive progresses of Big Data on healthcare, the paper also presents the hurdles faced by healthcare systems in using Big Data technologies. Further the paper includes the list of various Big Data tools, few case studies, few applications which are worth implementing using Big Data in healthcare followed by the concluding remarks.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744261","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: 15

A review of the application of data mining techniques for decision making in agriculture 数据挖掘技术在农业决策中的应用综述

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917925

N. Gandhi, L. Armstrong

引用次数: 50

Two factor verification using QR-code: A unique authentication system for Android smartphone users 使用qr码的两因素验证:Android智能手机用户的独特认证系统

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7918008

Brinzel Rodrigues, Anita Chaudhari, Shraddha S. More

引用次数: 17

Selective flooding techniques for dissemination in VANETs 在VANETs中传播的选择性泛洪技术

2016 2nd International Conference on Contemporary Computing and Informatics (IC3I) Pub Date : 2016-12-01 DOI: 10.1109/IC3I.2016.7917991

M. U. Farooq, K. Khan, Salwa Mohammed

引用次数: 3