2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)最新文献_第3页

High SNR outage analysis for power efficient multi-relay cooperative networks with ARQ assistance 基于ARQ辅助的高效多中继合作网络高信噪比停电分析

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489201

Ali Kamouch, A. Chaoub, Z. Guennoun

{"title":"High SNR outage analysis for power efficient multi-relay cooperative networks with ARQ assistance","authors":"Ali Kamouch, A. Chaoub, Z. Guennoun","doi":"10.1109/ISDA.2015.7489201","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489201","url":null,"abstract":"In this paper we consider a multi relay Decode and Forward (DF) relay network assisted by Hybrid automatic repeat request (HARQ) in a Rayleigh block fading environment. The system uses an incremental relaying strategy in which the best relay is selected to cooperate with source. A Space-Time Block coding (STB) is used for cooperation between source and selected relay to transmit the data to the destination. Relays and destination use maximum ratio combining (MRC) technique to decode the sent message using previously received versions. We derive a closed-form expression of asymptotic outage probability at high Signal-to-Noise Ratio (SNR) regime. We also derive the average delay and throughput in a delay constrained application. The derivation method is based on the Laplace transform, which proves to be a very effective analytical tool when combined with the properties of the special functions. In addition, we investigate the optimum power allocation strategy to minimize the outage probability and consequently maximize the average throughput perceived by the end user. The simulation results show that the obtained analytical bound for the outage probability is very tight at high SNR regime. In addition the proposed power allocation scheme clearly outperforms the equal power allocation.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124654126","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: 0

Cloud discrimination using K Nearest Neighbors classifier: Application to dataset generated by Sétif RADAR (Algeria) and MSG-SEVIRI satellite images 基于K近邻分类器的云识别:应用于ssamtif RADAR(阿尔及利亚)和MSG-SEVIRI卫星图像生成的数据集

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489272

F. Mokdad, B. Haddad, Z. Bala, Ilhem Tiblali

{"title":"Cloud discrimination using K Nearest Neighbors classifier: Application to dataset generated by Sétif RADAR (Algeria) and MSG-SEVIRI satellite images","authors":"F. Mokdad, B. Haddad, Z. Bala, Ilhem Tiblali","doi":"10.1109/ISDA.2015.7489272","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489272","url":null,"abstract":"Efficient classification depends strongly on the quality of the dataset used in experiments. In this paper, we generated a dataset consists of six spectral features extracted from the MSG-SEVIRI satellite images. Each feature represents the brightness temperature of the corresponding pixel. We are based on meteorological radar images acquired in Sétif region (Algeria) to assign a class to each feature vector, where we take account of the spatial and spectral resolution difference between radar and satellite images. We are interested to the identification of raining clouds, non-raining clouds and absence of clouds. The application of K Nearest Neighbors (KNN) classifier to the dataset generated performs very well. Using Euclidean metric for classifications, the overall accuracy is 99.46% and the Kappa coefficient attaint 99.13%. In order to validate the results obtained experimentally we have performed an in situ validation using eight ground measurements over the north Algeria. By computing different evaluation measure parameters, experimental results demonstrate the efficiency of the proposed methodology in discriminating between raining and non-raining clouds.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130143714","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: 0

Maximal frequent sub-graph mining for malware detection 恶意软件检测的最大频繁子图挖掘

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489265

Aya Hellal, L. Romdhane

{"title":"Maximal frequent sub-graph mining for malware detection","authors":"Aya Hellal, L. Romdhane","doi":"10.1109/ISDA.2015.7489265","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489265","url":null,"abstract":"Malware detection has been one of the current computer security topics of great interest. Traditional signature-based malware detection fails to detect variants of known malware or previously unseen malware. To deal with this issue, machine learning and data mining methods have been widely used to counter the obfuscation techniques of attackers by examining the underlying behavior of suspected malware. However, these methods still suffer from the large number of extracted features and the lack of precise specifications which affects badly scanning time and the accuracy of the malware detection process. In this paper, we present an automatic detection method based on graph mining techniques. Maximal frequent subgraphs in a set of code graphs, representing common behaviors with precise specifications in execution files, are extracted and used as features to generate semantic signatures. These semantic signatures are represented by a set of learning models and employed to distinguish malware programs from benign. Experimental results indicate that our method extracts a limited number of interesting features and achieves effective malware detection.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130525865","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

Model driven reverse engineering: Graph modeling for mobiles platforms 模型驱动的逆向工程:移动平台的图形建模

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489261

Khalid Lamhaddab, K. Elbaamrani

引用次数: 3

Practical modeling of the SLA life cycle in Cloud Computing 云计算中SLA生命周期的实用建模

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489170

A. Maarouf, A. Marzouk, A. Haqiq

引用次数: 12

Clustering impact on group-based traitor tracing schemes 聚类对基于组的叛逆者跟踪方案的影响

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489270

Faten Chaabane, Maha Charfeddine, C. Amar

引用次数: 4

A new comparative study of ad hoc routing protocol AODV and DSR in VANET environment using simulation tools 利用仿真工具对VANET环境下的自组织路由协议AODV和DSR进行了新的比较研究

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489158

S. Benkirane, M. Saadi, M. L. Hasnaoui, A. B. Hssane

引用次数: 7

Speech emotion recognition based on Arabic features 基于阿拉伯语特征的语音情感识别

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489165

Mohamed Meddeb, H. Karray, A. Alimi

引用次数: 17

Artificial neural networks for demand forecasting: Application using Moroccan supermarket data 需求预测的人工神经网络:摩洛哥超市数据的应用

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489236

Ilham Slimani, Ilhame El Farissi, S. Achchab

{"title":"Artificial neural networks for demand forecasting: Application using Moroccan supermarket data","authors":"Ilham Slimani, Ilhame El Farissi, S. Achchab","doi":"10.1109/ISDA.2015.7489236","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489236","url":null,"abstract":"The accuracy of sales forecasts in a supply chain is certainly an important key to competitiveness. Because, for any member of the supply chain system, having a clear vision of the future demand affects his planning, his performance so his profit. In the first study of this work, various Artificial Neural Network models were presented and utilized to predict demand of a costumer's product. The training and validating data are provided from a known supermarket in Morocco. In a previous study, the results indicated that the best neural network structure for demand forecasting is the Multi Layer Perceptron, which is by the way, the most commonly used model in the literature. This work focuses on finding the optimal Multi Layer Perceptron structure for demand forecasting. We also present a review of selected works done in the application of game theory and neural networks in the context of management science. The main contribution of our work is the use of neural networks in order to predict the consumer's demand and implement this demand forecasting in a two-echelon supply chain with a game theoretic approach.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122811760","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: 25

RUDA - Robot for search for human beings in debrits and avalanches RUDA -机器人搜索人类在废墟和雪崩

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA) Pub Date : 2015-12-01 DOI: 10.1109/ISDA.2015.7489264

R. Luza, M. Drahanský, F. Zboril

引用次数: 1