AASRI Procedia最新文献_第10页

Design Reusability and Adaptability for Concurrent Software 并行软件设计的可重用性和适应性

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.069

Paniti Netinant

{"title":"Design Reusability and Adaptability for Concurrent Software","authors":"Paniti Netinant","doi":"10.1016/j.aasri.2013.10.069","DOIUrl":"10.1016/j.aasri.2013.10.069","url":null,"abstract":"<div><p>Developing reusable and adaptable concurrent software are very difficult. Reusability and adaptability in concurrent software become minimal. These collaborations not only perimeter reusability, but also make modification invasive changes to meet new requirements in the design of the concurrent software. The concurrent system has to reengineer, in order to meet the future requirements. A misunderstanding, that a concurrent object-oriented programming generally endorses reusability and adaptability, as none of these problems is imposed. Software developers have to specifically deliberate software making reusability and adaptability. We present a concurrent aspect framework which better supporting reusability and adaptability. In the framework, functional components and system assets are relatively separated. This technique makes concurrent software developing better reusability and adaptability. A framework enables manageable reusability and adaptability for building of concurrent software. Our research focuses on decomposition of contact in concurrent software development and our goal is to demonstrate a better model of concurrent software design.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"5 ","pages":"Pages 133-139"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2013.10.069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84871509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Constrained Tunable-Q Wavelet Transform based Analysis of Cardiac Sound Signals 基于约束可调q小波变换的心音信号分析

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.010

Shivnarayan Patidar, Ram Bilas Pachori

引用次数: 12

A New Technique for Generating Minimal Cut Sets in Nontrivial Network 非平凡网络中生成最小割集的新技术

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.060

Mohamed-Larbi Rebaiaia , Daoud Ait-Kadi

引用次数: 18

Energy-efficient Relay Selection for Multicast Communication 节能中继选择的组播通信

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.064

Junxing Wang, Zhigang Chen, Yuan Yao

{"title":"Energy-efficient Relay Selection for Multicast Communication","authors":"Junxing Wang, Zhigang Chen, Yuan Yao","doi":"10.1016/j.aasri.2013.10.064","DOIUrl":"10.1016/j.aasri.2013.10.064","url":null,"abstract":"<div><p>Aimed at the problem that system energy consumption of the traditional cooperative multicast is large with increase of the number of users, four energy-efficient relay selection schemes are proposed to reduce system energy consumption. By using exhaustive search method, the optimal relay selection algorithm selects relays from all the possible combinations of relays, the scheme could reduce energy consumption and improve energy efficiency effectively at high computational complexity. According to the thought of iteration, greedy algorithm chooses relays using the selected relays, though the scheme doesn’t achieve the energy efficiency of the optimal relay selection algorithm, it reduces computational complexity. Besides, relay selection based on multicast rate of users selects relays using the multicast rate of each user by which the rest users with bad channel condition could decode data correctly, and relay selection based on channel state information (CSI) among users chooses relays according to the whole CSI between each user decoded data correctly and all users failed to decode data, these two schemes further reduce complexity compared to greedy algorithm. Results show that all the proposed energy-efficient relay selection approaches could improve energy efficiency while meeting the requirement of fairness.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"5 ","pages":"Pages 98-105"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2013.10.064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80801391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

On the Pursuit of Reliable Solutions for a Robotic Optimization Problem 机器人优化问题可靠解的追求

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.005

Ricardo Soto , Stéphane Caro , Broderick Crawford

引用次数: 4

Automatic Definition of Regions of Interest on Renal Scintigraphic Images 肾脏扫描图像感兴趣区域的自动定义

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.007

Yassine Aribi, Ali Wali, Mohamed Chakroun, Adel M. Alimi

引用次数: 11

Study of Qualitative Data Cluster Model based on Granular Computing 基于颗粒计算的定性数据聚类模型研究

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.048

Haiyan Li, Shen Yang, Hong Liu

引用次数: 3

Parallel Processing of Sensor Network Data Using Column-oriented Databases 基于列式数据库的传感器网络数据并行处理

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.051

Kyung-Chang Kim , Choung-Seok Kim

引用次数: 3

MKF-Cuckoo: Hybridization of Cuckoo Search and Multiple Kernel-based Fuzzy C-means Algorithm MKF-Cuckoo: Cuckoo搜索与基于多核的模糊c均值算法的杂交

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.037

D. Binu, M. Selvi, Aloysius George

{"title":"MKF-Cuckoo: Hybridization of Cuckoo Search and Multiple Kernel-based Fuzzy C-means Algorithm","authors":"D. Binu, M. Selvi, Aloysius George","doi":"10.1016/j.aasri.2013.10.037","DOIUrl":"10.1016/j.aasri.2013.10.037","url":null,"abstract":"<div><p>Discovering of optimal cluster through the help of optimization procedure is a recent trend in clustering process. Accordingly, several algorithms have been developed in the literature to mine optimal clusters. Most of the optimization- based clustering algorithms presented in the literature are only focused on the same objective given in the well-known clustering process, k-means clustering. Instead of k-means objective, some more effective objective functions are designed by the researchers for clustering. So, hybridization of those effective objectives with optimization algorithms can lead the effective clustering results. With the aim of this, we have presented a hybrid algorithm, called MKF-Cuckoo which is the hybridization of cuckoo search algorithm with the multiple kernel-based fuzzy c means algorithm. Here, MKFCM objective is taken and the same objective is solved through the cuckoo search algorithm which is one of the recent optimization algorithm proved effective in many optimization problems. For proving the effectiveness of the algorithm, the performance of the algorithm is comparatively analyzed with some other algorithm using clustering accuracy, rand coefficient, jaccard coefficient and computational time with iris and wine datasets. From the results, we can prove that the hybrid algorithm obtained 96% accuracy in iris data and 67% accuracy in wine data.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"4 ","pages":"Pages 243-249"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2013.10.037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86045389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Co-SRL: A Convex Optimization Algorithm for Anchor Localization in Wireless Sensor Networks 无线传感器网络中锚点定位的凸优化算法

AASRI Procedia Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.059

Wu Liu , Donghong Sun , Ping Ren , Yihui Zhang

引用次数: 1