2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)最新文献_第2页

Intrusion Detection using NBHoeffding Rule based Decision Tree for Wireless Sensor Networks 基于NBHoeffding规则的无线传感器网络决策树入侵检测

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479483

S. Geetha, U. N. Dulhare, S.S. Sivatha Sindhu

{"title":"Intrusion Detection using NBHoeffding Rule based Decision Tree for Wireless Sensor Networks","authors":"S. Geetha, U. N. Dulhare, S.S. Sivatha Sindhu","doi":"10.1109/ICAECC.2018.8479483","DOIUrl":"https://doi.org/10.1109/ICAECC.2018.8479483","url":null,"abstract":"The objective of this paper is to build a practical intrusion detection system for wireless sensor networks which analyze the characteristics of traffic patterns and identify the intrusive activities in the network. It is to show that the choice of efficient and fast decision tree paradigm for intrusion detection with optimal features enhance the detection capability as well as saves energy, computation and memory of sensor networks. In addition, various rule based decision tree classifiers like Alternating Decision Tree, Decision Stump, J48, Logical Model Tree, Naive Bayes Tree and Fast Decision Tree learner have been compared with a family of Hoeffding rule based decision tree which shows better and fast detection capability. The evaluation of the enhanced feature space and the decision tree paradigm, on three different public dataset containing normal and anomalous data have been performed for various Hoeffding as well as other decision tree algorithms. With this approach it is proved that Hoeffding tree are best suited for online detection and handling of streaming sensor data with the efficient usage of memory in a resource constraint environment like sensor networks","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131085108","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

IOT enabled comprehensive, plug and play gateway framework for smart health 支持物联网的智能健康全面即插即用网关框架

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479431

S. Kesavan, Ganesh Kumar Kalambettu

{"title":"IOT enabled comprehensive, plug and play gateway framework for smart health","authors":"S. Kesavan, Ganesh Kumar Kalambettu","doi":"10.1109/ICAECC.2018.8479431","DOIUrl":"https://doi.org/10.1109/ICAECC.2018.8479431","url":null,"abstract":"With convergence of digital technology and smart devices, monitoring and tracking data in real time become true. Given the invention of many health vital sensors and activity tracking devices, dynamically measure and monitoring of vital health parameters become easy. The sensors and devices uses numerous protocols and communication methods for transmitting the data. In a conventional setup, it is difficult to connect multiple devices with different proprietary applications and monitor. Moreover, it is cumbersome to control multiple devices and store, analyses all the vitals parameter data. There is no common platform or frameworks available to connect the multiple health sensors and to monitor the vitals simultaneously. This paper proposes the comprehensive, scalable, plug and play smart health gateway for connecting variety of health sensors and allows the devices seamless communication for transmit and control. With IoT enabled, the framework seamlessly connects with cloud services and stream the data for storage, analysis and prediction. The proposed unified framework is not only an efficient building block for connecting many health sensors but also enable seamless connectivity between gateway and cloud platform and services.","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133233215","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

A Heterogeneous Dynamic Scheduling Minimized Make-span For Energy and Performance Balancing 一种能量与性能平衡的异构动态调度最小化制作时间

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479505

Saba Fatima, V. M. Vishwanath

{"title":"A Heterogeneous Dynamic Scheduling Minimized Make-span For Energy and Performance Balancing","authors":"Saba Fatima, V. M. Vishwanath","doi":"10.1109/ICAECC.2018.8479505","DOIUrl":"https://doi.org/10.1109/ICAECC.2018.8479505","url":null,"abstract":"CPU-GPU accelerator based heterogeneous cloud computing systems can give enhanced energy efficiency and performance. Both energy efficiency and performance parameters are the vital factors in achieving High Performance Computing (HPC). To completely understand the strength of heterogeneous cloud computing architectures, software must efficiently use CPU-GPU processing and their power conserves capability. Dynamic Voltage and Frequency Scaling (DVFS) technique can be used to enable power conserving capabilities of CPU-GPU core architectures. Therefore, to distribute task load between host CPUs and GPU accelerators and reduce energy consumption, here, we have introduced a Heterogeneous Dynamic Scheduling Minimized Makespan (HDSMM) using CPU-GPU cores for heterogeneous cloud computing devices. Here, DVFS technique is distributed into CPU-DVFS and GPU-DVFS, for efficient resource utilization and to exploit power conserving features. Our proposed HDSMM model presents precise modeling for performance and energy efficiency distribution and finest frequency to achieve either best performance or lowest power consumption. Experimental results verify the superiority of our proposed HDSMM model in terms of energy consumption, average execution time and average power for scientific benchmark Montage.","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123918355","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

Nepal Stock Exchange Prediction Using Support Vector Regression and Neural Networks 尼泊尔证券交易预测使用支持向量回归和神经网络

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479456

Top Bahadur Pun, T. B. Shahi

{"title":"Nepal Stock Exchange Prediction Using Support Vector Regression and Neural Networks","authors":"Top Bahadur Pun, T. B. Shahi","doi":"10.1109/ICAECC.2018.8479456","DOIUrl":"https://doi.org/10.1109/ICAECC.2018.8479456","url":null,"abstract":"Stock Exchange price prediction is the task of estimating future price of certain stock listed in stock exchange by extracting the trend with the help of confidence learned from historical training data. In this research work, the data set has been created by extracting raw data from Nepal Stock Exchange (NEPSE) website. Data preprocessing is performed in order compute an accurate result. The data belonging to promoter share and unwanted feature are eliminated from considered data. The resulting data are normalized for better performance, before applying the machine learning methods. Min-Max and Z-score normalization are used for this purpose. Overall stock data are further divided into ten different sector of investment for sectorwise analysis. Support Vector Regression (SVR) and Artificial Neural Network (ANN) are applied in order to predict stock price for a next day. In order to measure the performance of two learning models, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE) and Coefficient of Determination (R2) are used. The result shows that SVR with min max normalization is performing better than ANN in all sectors except on Development bank, Finance, and Mutual Fund.","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124563422","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: 12

Charge Plasma Based VVD-SJ VDMOS Employing Reversed Doping Concentration 基于反向掺杂浓度的电荷等离子体VVD-SJ VDMOS

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479495

Payal Nautiyal, Alok Naugarhiya, Shrish Verma

引用次数: 1

Comeal Endothelium cell segmentation and count using K-means and watershed algorithms 使用K-means和分水岭算法分割和计数角膜内皮细胞

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479526

KV Kiran Kumar, G. Srinivasa

引用次数: 4

Bengali Handwriting Recognition and Conversion to Editable Text 孟加拉手写识别和转换到可编辑的文本

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479487

Sadia Chowdhury, Farhan Rahman Wasee, M. S. Islam, Hasan U. Zaman

引用次数: 2

Bezier Curve based Multipath Routing in VANET VANET中基于Bezier曲线的多路径路由

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479488

A. D. Devangavi, R. Gupta

引用次数: 6

Design and implementation of 16 tap FIR filter for DSP Applications 用于DSP的16分路FIR滤波器的设计与实现

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479480

N. Rai, Pannaga Shree B S, Meghana Y P, A. Chavan, RAVISH ARADHYA H V

引用次数: 12

High Speed Bootstrapping Generic Voltage Level Shifter 高速自启动通用电压电平移位器

2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) Pub Date : 2018-02-01 DOI: 10.1109/ICAECC.2018.8479461

Mahesh Vaidya, Alok Naugarhiya, Shrish Verma

引用次数: 2