{"title":"Rhythm metrics in MSA spoken language of six algerian regions","authors":"G. Droua-Hamdani, M. Boudraa","doi":"10.1109/ISDA.2015.7489248","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489248","url":null,"abstract":"This paper focuses in rhythm speech metrics of Modern Standard Arabic using speech material of six regions taken from ALGASD corpus. These regions are scattered across all the country: three regions from the north (Algiers, Tizi-Ouzou and Jijel) and three from the south (Bechar in the west -close to Morocco-, Ghardaia in the center of Algeria' south and El Oued is in the East -close to Tunisia-). To reveal differences in speech rhythm, metrics are computed using two rhythm models: Interval Measures and Pairwise Variability Indices. The main experiment assessed patterns in rhythm metric properties depending on speakers' location. Statistical analysis shows significant effects of speaker's origin (north/south) on vocalic and consonantal rhythm metrics.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"16 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":"117338360","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}
{"title":"MRI brain tumor classification using Support Vector Machines and meta-heuristic method","authors":"A. Kharrat, Mohamed Ben Halima, Mounir Ben Ayed","doi":"10.1109/ISDA.2015.7489271","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489271","url":null,"abstract":"We present a development of a new approach for automated diagnosis, based on classification of Magnetic Resonance (MR) human brain images. 2D Wavelet Transform and Spatial Gray Level Dependence Matrix (DWT-SGLDM) is used for feature extraction. For feature selection Simulated Annealing (SA) is applied to reduce features size. The next step in our approach is Stratified K-fold Cross Validation to avoid overfitting. To optimize support vector machine (SVM) parameters we use Genetic Algorithm and Support Vector Machine (GA-SVM) model. SVM is applied to construct the classifier. An intelligent classification rate of 95,6522% could be achieved using the support vector machine.","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":"127327892","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}
{"title":"Possibilistic Network based Information Retrieval Model","authors":"Kamel Garrouch, Mohamed Nazih Omri","doi":"10.1109/ISDA.2015.7489255","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489255","url":null,"abstract":"This paper proposes a new Information Retrieval Model based on Possibilistic Networks. The model structure integrates most relevant term to term dependence relationships. The approach used to extract the set of these dependencies focuses on local dependencies between terms within each document. The relevance of a document to a query is interpreted by two degrees: the necessity and the possibility. The necessity degree evaluates the extent to which a document is relevant to a query, whereas the possibility degree evaluates the reasons of eliminating irrelevant documents. These two measures are also used for quantifying terms-terms links and terms-documents links. Experiments carried out on three standard document collections show the effectiveness of the model.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"87 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":"124900953","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}
{"title":"Optimization algorithms, benchmarks and performance measures: From static to dynamic environment","authors":"R. Fdhila, T. M. Hamdani, A. Alimi","doi":"10.1109/ISDA.2015.7489185","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489185","url":null,"abstract":"This paper is a tentative to describe the basics of dynamic optimization using swarm & evolutionary methods. Computational intelligence methods based on swarming, collaborative computing and related techniques showed their potentials at solving classical static problems; for dynamic problems new paradigms needs to be established, this concerns the methods, the test benches and the performance evaluation processes. A review of the key population based computational techniques is performed prior to set some perspective guidelines on how to handle the multi-objective dynamic problems using these technique.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"15 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":"129818179","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}
{"title":"A new Hybrid Discrete Bat Algorithm for Traveling Salesman Problem using ordered crossover and 3-Opt operators for Bat's local search","authors":"Jihen Amara, T. M. Hamdani, A. Alimi","doi":"10.1109/ISDA.2015.7489217","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489217","url":null,"abstract":"In this paper we propose a new Hybrid Bat Algorithm to solve the traveling salesman problem (TSP) that has attracted many researchers applying exact and metaheuristic methods trying to solve it. The new proposed method is based on the basics of Bat Algorithm (BA) recently proposed as a new bio-inspired meta-heuristic algorithm. Accordingly, we use the concepts of Swap Operator (SO) and Swap Sequence (SS) to redefine respectively BA position and velocity operators for TSP. Additionally, based on ordered crossover and 3-Opt algorithm, we propose to redefine the Bat's local search method. We compare our algorithm to other state of the art methods from the literature by using benchmark datasets of symmetric TSP from TSPLIB library in order to test its effectiveness. Based on the recorded experiments our method outperforms most of the compared methods.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"55 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":"129070055","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}
{"title":"Recognizing Arabic Handwritten Script using Support Vector Machine classifier","authors":"M. Elleuch, Houssem Lahiani, M. Kherallah","doi":"10.1109/ISDA.2015.7489176","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489176","url":null,"abstract":"Handwriting recognition ranks among the highest and the most triumphant applications in the pattern recognition domain. Despite being a developed field, many enquiries are still needed and still represent a defiance mainly for the Arabic Handwritten Script (AHS). Recently, more regard has been given to Support Vector Machines (SVM) classifier for script recognition. Nevertheless, it has not been put in application yet to the handwritten Arabic field if compared with the other methods like ANN, CNN, RNN and HMM. SVMs for AHS recognition is examined in this paper. Handcrafted feature is handled as input by the suggested method and gets going with a supervised learning algorithm. We chose the Multi-class Support Vector Machine with an RBF kernel and we tested it on Handwritten Arabic Characters Database (HACDB) as well. It was proven that the proposed method was effective thanks to the simulation results. We compared the well-functioning of this method with character recognition reliabilities coming from state-of-the-art Arabic OCR which resulted in commendatory outcomes.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"109 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":"129339128","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}
{"title":"Implementation of skin color selection prior to Gabor filter and neural network to reduce execution time of face detection","authors":"Mejda Chihaoui, Akram Elkefi, W. Bellil, C. Amar","doi":"10.1109/ISDA.2015.7489251","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489251","url":null,"abstract":"This paper proposes a face detection system based on the skin color, the Gabor filter and the neural network. The use of Gabor filters and neural networks for face recognition is not new. However, the principal focus of the proposed paper is the implementation of skin color selection prior to Gabor filters and neural networks on order to reduce computation time. First, we analyze the skin color to extract skin areas which have an important probability to be faces. This technique robust to the lighting variation allows extracting, from an image, skin areas. We utilize this method to avoid wrong detection and to help the system detect the face in the right areas and minimize the research time. Second, to extract features, we propose a technique using the Gabor filter applied on the localized skin space. Finally, the vectors of the face features obtained by the Gabor filter are used as the input of a neural network classifier which classifies an input image pixel as a face or nonface pixel. Some results are shown to approve our approach efficiency.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"26 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":"123863405","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}
{"title":"Make or buy decision making for telcos towards an “Intelligent Transaction Cost Economics (TCE) Support System”","authors":"Mounir Boukadidi","doi":"10.1109/ISDA.2015.7489205","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489205","url":null,"abstract":"Because of the frequently changing environment and technologies, Telecom operators' value chain faces permanently challenges related to agility and cost effectiveness. Whether to vertically integrate or to delegate to the market is strategic decision making, influenced by a variety of factors. The theory presents rich findings about the most important factors, and we in this article are trying to apply them on the telecom industry while tuning them throughout the tmforum standard, a best known and worldwide accepted framework in the telecom industry. We are then suggesting a basis for identifying which Transaction Cost Economics (TCE) model might support decision makers in their understanding of the emerging behaviours related to the make or buy dilemma; a model that would definitely help them in adopting the best fit of internal and external execution tactics towards a cost effective execution strategy.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"37 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":"126458660","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}
{"title":"Video event detection using auto-associative neural network and incremental SVM models","authors":"M. Chakroun, A. Wali, Yassine Aribi, A. Alimi","doi":"10.1109/ISDA.2015.7489178","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489178","url":null,"abstract":"In this paper a new approach to video event detection is presented. This approach is based on HOG/HOF features optimized by an auto-associative neural network models for feature reduction and an incremental SVM model for event classification. This auto-associative neural network models are frequently used to reduce the size of feature vectors. In our approach, each event is modeled by a set of states, and each state is represented by a learning model containing a positive class (event) and a negative class (non-event). Experiments on real video sequences have shown encouraging results.","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":"134524068","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}
{"title":"Biomedical concept extraction based Information Retrieval model: application on the MeSH","authors":"Mondher Sendi, Mohamed Nazih Omri","doi":"10.1109/ISDA.2015.7489157","DOIUrl":"https://doi.org/10.1109/ISDA.2015.7489157","url":null,"abstract":"This paper proposes a new approximate model for biomedical concept extraction. This model is based on possibilistic network, statistical computing and semantic proximity. The possibilistic network is used for representing the MeSH structure in order to select the relevant concepts for a biomedical text. Moreover, we propose an enrichment model of the MeSH thesaurus by the identification of the semantic relations between concepts. The results of the extraction model serve to mapping a query in an information retrieval process. And, to prove the significance of our model in the Information Retrieval context, we used a vector model and the OHSUMED collection.","PeriodicalId":196743,"journal":{"name":"2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"41 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":"134302879","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}