2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)最新文献_第10页

Improving resource management of IaaS providers in cloud federation 改进云联盟中IaaS提供商的资源管理

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436137

Behnam Bagheri Ghavam Abadi, Mostafa Ghobaei Arani

{"title":"Improving resource management of IaaS providers in cloud federation","authors":"Behnam Bagheri Ghavam Abadi, Mostafa Ghobaei Arani","doi":"10.1109/KBEI.2015.7436137","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436137","url":null,"abstract":"With daily increasing use of cloud services, saving energy and using needed resources regardless of time and place, for both providers and users, have great importance. Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. Most cloud providers conduct requests with a limited amount of resources that may be cause to reject the request of customers at the peak of workloads. Federated cloud is a mechanism for sharing resources thereby increasing scalability. Allocating resources in cloud is a complex procedure. Today with development of cloud-based data centers and increasing demand for cloud services, the main problems are high energy consumption and the profit of the services. In this paper, we propose an approach to reduce power consumption in data centers and increase profits for the satisfaction of service providers offering cloud services. The proposed approach is offered based on a real model for cloud federation. Experimental results show that the proposed approach, compared to the other similar approaches, causes to increase utilization and turns off idle servers to decrease consumed power which followed by an increase in providers' profit.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630528","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

Survey on sequential pattern mining algorithms 序列模式挖掘算法综述

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436211

Sedigheh Abbasghorbani, Reza Tavoli

引用次数: 11

Real time earthquake prediction using cross-correlation analysis & transfer function model 利用互相关分析和传递函数模型进行实时地震预报

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436053

Navid Rajabi, Omid Rajabi

{"title":"Real time earthquake prediction using cross-correlation analysis & transfer function model","authors":"Navid Rajabi, Omid Rajabi","doi":"10.1109/KBEI.2015.7436053","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436053","url":null,"abstract":"IRAN is located in a region of high seismic potential. This paper presents a real-time method of predicting earthquake before its arrival. Our proposed method is based on cross-correlation calculation of data sensed by Wireless Sensor Network (WSN) as well as, Transfer Function (TF) calculation for the seismic wave propagation path between a location close to the hypo-center and the location where vibration is going to be predicted. The information which was obtained during a long period of continuous monitoring, have been used and deployed for mathematical calculations. This information was relayed to the main server to collect data and store it for future evaluations. We show that there is some consistency between discrepant faults in such a way that releasing energy in one area can lead to another vibration and quake. Our proposed working procedure consists of two algorithms first is named learning algorithm which concentrates on long-term waveform collection, Signal to Noise Ratio (SNR) enhancement, cross-correlation calculations, and finally transfer function calculation during foreshock time, and second is named Prediction Algorithm which calculates the seismic output waveform based on earthquake around hypo-center as input for already determined transfer function. By this approach, we have introduced a novel solution as Earthquake Early-Warning System (EEWS) gives golden time which can preserve human's life and mitigate economical loss by mentioned elaborated process.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130299243","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

A machine vision system for defect detection of a traveling grate conveyor 一种用于移动篦机缺陷检测的机器视觉系统

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436192

Ahmad Pouramini, H. Varaee

引用次数: 0

Classification of Persian handwritten digits using spiking neural networks 波斯语手写数字的脉冲神经网络分类

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436202

K. Kiani, Elmira Mohsenzadeh Korayem

{"title":"Classification of Persian handwritten digits using spiking neural networks","authors":"K. Kiani, Elmira Mohsenzadeh Korayem","doi":"10.1109/KBEI.2015.7436202","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436202","url":null,"abstract":"In recent years Spiking Neural Networks (SNNs) have gained in popularity due to their low complexity. They have been used in many processes like learning and classification of data such as images. In this paper we have used the SNN Model, in order to have robust learning and classification of handwritten digits, i.e., to have a learning process which is persistent against changes and high noise levels. Due to the similarities among handwritten digits, the classifications have been erratic but the Deep Belief Network we have used in this paper solves this problem to a great extent. Our model consists of three layers. The first layer, composed of 225 neurons (15*15 pixels for each image), works as the receptor of input images. The middle layer is used for processes, encoding and network learning, while the last layer, which is composed of 10 neurons (as we have 10 distinct classes), does the job of prediction and classification of images. The model was implemented using MATLAB and we have used Hoda Persian handwritten digits dataset as our input images. The obtained results show that the implemented model can carry out, with good accuracy (95%), the learning and classification of images of handwritten digits with high levels of noise.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127913707","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

On the performance evaluation of hybrid decode-amplify-forward relaying protocol with adaptive M-QAM modulation over Rayleigh fading channels 瑞利衰落信道下自适应M-QAM调制混合译码-放大-前向中继协议性能评价

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436099

Amin Aref, Sonia Naderi, O. R. Ma'rouzi

引用次数: 4

Robust speed control of induction machine using synergetic controller 基于协同控制器的感应电机鲁棒速度控制

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436159

A. R. Noei, H. Kholerdi

引用次数: 1

Adaptive control of human posture in a specific movement 人体姿势在特定运动中的自适应控制

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436091

S. Haghpanah, Fatemeh Haghpanah

引用次数: 1

A modified ant colony based approach to digital image edge detection 基于改进蚁群的数字图像边缘检测方法

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436096

Aydin Ayanzadeh, Hossein Pourghaemi, Yousef Seyfari

引用次数: 1

A new hybrid evolutionary biclustring algorithm based on transposed virtual error 一种基于转置虚误差的混合进化双串算法

2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI) Pub Date : 2015-11-01 DOI: 10.1109/KBEI.2015.7436101

S. Mahmoudi, M. Menhaj

引用次数: 1