Pub Date : 2020-04-01DOI: 10.1109/iraset48871.2020.9092334
{"title":"IRASET 2020 Foreword","authors":"","doi":"10.1109/iraset48871.2020.9092334","DOIUrl":"https://doi.org/10.1109/iraset48871.2020.9092334","url":null,"abstract":"","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"360 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134405918","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092297
Mohammed Qbadou, M. Zaggaf, Intissar Salhi, K. Mansouri
Language barriers are one of the biggest challenges that humans in general and children in particular face in their verbal interactions. Many reseach projets with mutli-countries scope are expected to give a significant help to teachers and doctors to support children with verbal communication disabilities by using humanoid robots. The usage of robot agent is excpected to stimulate the verbal communication based on natural language interactions with this kind of children. Such stimulation may be of great importance in improving the ability of these children to interact verbally with their teachers and classmates. In this context, we propose through this work to extend the language capabilities of humanoid robots to be able to communicate with children using differnet natural languages. This should allow a humanoid robot to recognize the spoken or written message of each children group and thus use this language to interact with. In this paper, we present the design of a generic models and the implementation of a software components to allow language neutral verbal interactions between children and humanoid robots. An extended ontology models will be provided to serve as a knowledge database of a set of concepts and theirs propoerties to represent the semantic aspects describing the relations between human-robot vebal communications. Based on thus generic models, we will provide an optimized new algorithms and their Python implementation to extend the natural language processing Python pakages. In this paper, a set of human-Robot verbal ineractions models are presented and the resultant conclusions and perspectives are discussed
{"title":"Multilingual verbal interaction between humans and robots - Modeling and Implementation","authors":"Mohammed Qbadou, M. Zaggaf, Intissar Salhi, K. Mansouri","doi":"10.1109/IRASET48871.2020.9092297","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092297","url":null,"abstract":"Language barriers are one of the biggest challenges that humans in general and children in particular face in their verbal interactions. Many reseach projets with mutli-countries scope are expected to give a significant help to teachers and doctors to support children with verbal communication disabilities by using humanoid robots. The usage of robot agent is excpected to stimulate the verbal communication based on natural language interactions with this kind of children. Such stimulation may be of great importance in improving the ability of these children to interact verbally with their teachers and classmates. In this context, we propose through this work to extend the language capabilities of humanoid robots to be able to communicate with children using differnet natural languages. This should allow a humanoid robot to recognize the spoken or written message of each children group and thus use this language to interact with. In this paper, we present the design of a generic models and the implementation of a software components to allow language neutral verbal interactions between children and humanoid robots. An extended ontology models will be provided to serve as a knowledge database of a set of concepts and theirs propoerties to represent the semantic aspects describing the relations between human-robot vebal communications. Based on thus generic models, we will provide an optimized new algorithms and their Python implementation to extend the natural language processing Python pakages. In this paper, a set of human-Robot verbal ineractions models are presented and the resultant conclusions and perspectives are discussed","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122175902","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092260
S. Kririm, B. Boukili, A. El‐Amrani, A. Hmamed
In this paper, we study $H_{infty}$ performance for the descriptor systems with continuous-time. By using Finsler’s lemma technique and LMI approach, the sufficient condition is given in form of strict LMI for the problem that such descriptor systems are admissible with $H_{infty}$ disturbance attenuation level. Finally, a numerical examples are given to validate our results.
{"title":"H∞ Analysis For Descriptor Systems: A Strict LMI Approach","authors":"S. Kririm, B. Boukili, A. El‐Amrani, A. Hmamed","doi":"10.1109/IRASET48871.2020.9092260","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092260","url":null,"abstract":"In this paper, we study $H_{infty}$ performance for the descriptor systems with continuous-time. By using Finsler’s lemma technique and LMI approach, the sufficient condition is given in form of strict LMI for the problem that such descriptor systems are admissible with $H_{infty}$ disturbance attenuation level. Finally, a numerical examples are given to validate our results.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125586852","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092056
My Elhoussine Ech-chhibat, L. Zahiri, L. A. E. Maalem
Industrial production workshops in all fields are becoming more and more robotized. Flexible workshops have several types of robots, namely mobile robots that move products from one machine to another, flexible cells are loaded and unloaded by robot manipulators. In this work we will discuss the design of a serial robot with six degrees of freedom. Three degrees of freedom to position the effector and three others to guide the wrist. In this context the manipulator arm must load and unload a CNC milling machine ‘TORMACH PCNC 440’ which is installed in our lab. The dimensions of the robot are adapted to the size of the machine, these organs are sized by another research team. In what follows we will discuss the different models allowing us the control of the manipulator. We start with the geometric model, the kinematic model and the static model. The goal is to enslave the arm in position and velocity. Several simulations have been carried out to validate this part of our study. Homogeneous transformation and modified DENAVIT-HARTENBURG (DH) parameters are adopted in this approach.
{"title":"Modeling and simulation of a loader and unloader manipulator","authors":"My Elhoussine Ech-chhibat, L. Zahiri, L. A. E. Maalem","doi":"10.1109/IRASET48871.2020.9092056","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092056","url":null,"abstract":"Industrial production workshops in all fields are becoming more and more robotized. Flexible workshops have several types of robots, namely mobile robots that move products from one machine to another, flexible cells are loaded and unloaded by robot manipulators. In this work we will discuss the design of a serial robot with six degrees of freedom. Three degrees of freedom to position the effector and three others to guide the wrist. In this context the manipulator arm must load and unload a CNC milling machine ‘TORMACH PCNC 440’ which is installed in our lab. The dimensions of the robot are adapted to the size of the machine, these organs are sized by another research team. In what follows we will discuss the different models allowing us the control of the manipulator. We start with the geometric model, the kinematic model and the static model. The goal is to enslave the arm in position and velocity. Several simulations have been carried out to validate this part of our study. Homogeneous transformation and modified DENAVIT-HARTENBURG (DH) parameters are adopted in this approach.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671372","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092265
Hayat Haroun, A. R. Ghomari, Mounir Lahlouh, Anis Mehdi
Risk assessment is an essential part of any occupational health (OH) management system. Occupational Risk Management Process, is characterized by multiple types of data (activity sector, occupations, risks exposures, diseases, etc.). This multidimensional aspect of data strengthens the need for appropriate tools to enhance OH analysis. This paper examines the opportunity of using spatial data warehousing technique in the OH management framework to integrate various data formats such as geographic (workplace data) and thematic data which are usually scattered across multiple, dispersed and fragmented systems. We propose a SOLAP architecture that supports the whole process of risk management for prevention purposes. We then instantiate the architecture to build a SOLAP-Based System for SMT Company to enhance risk assessment in OH for electrical and gas industries.
{"title":"Towards a Spatial Data Warehouse for Occupational Health Risk Management","authors":"Hayat Haroun, A. R. Ghomari, Mounir Lahlouh, Anis Mehdi","doi":"10.1109/IRASET48871.2020.9092265","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092265","url":null,"abstract":"Risk assessment is an essential part of any occupational health (OH) management system. Occupational Risk Management Process, is characterized by multiple types of data (activity sector, occupations, risks exposures, diseases, etc.). This multidimensional aspect of data strengthens the need for appropriate tools to enhance OH analysis. This paper examines the opportunity of using spatial data warehousing technique in the OH management framework to integrate various data formats such as geographic (workplace data) and thematic data which are usually scattered across multiple, dispersed and fragmented systems. We propose a SOLAP architecture that supports the whole process of risk management for prevention purposes. We then instantiate the architecture to build a SOLAP-Based System for SMT Company to enhance risk assessment in OH for electrical and gas industries.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125045515","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092256
Aissam Jadli, M. Hain
Documents in an ERP system flow from different sources (customer, supplier, etc.) and can have different layouts, sizes and subjects (invoices, delivery forms, checks, etc.). The classification of these documents is usually done manually before being saved in the ERP system or processed by an Optical Character Recognition (OCR) engine. In this paper, we investigate using different deep convolutional neural networks (CNN) to extract deep features from images of scanned documents. The extracted features are further processed using various machine learning classifiers such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Gaussian Naive Bayes (GNB). Different metrics were used (accuracy, precision, etc.) and examined to compare all models performances, while cross-validation approach at different folds sizes (4, 6, 8 and 10) was used to assess their generalization ability. The effect of dimensionality reduction techniques on overall performances was also explored. The best classification rate was 96.1%, which was achieved by combining LR and the VGG19 model. This very good performance despite the small dataset used (200 images) can allow using this approach in an ERP system as a preprocessing step in document manipulation for ERP users.
{"title":"Automatic Document Classification using Deep Feature Selection and Knowledge Transfer","authors":"Aissam Jadli, M. Hain","doi":"10.1109/IRASET48871.2020.9092256","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092256","url":null,"abstract":"Documents in an ERP system flow from different sources (customer, supplier, etc.) and can have different layouts, sizes and subjects (invoices, delivery forms, checks, etc.). The classification of these documents is usually done manually before being saved in the ERP system or processed by an Optical Character Recognition (OCR) engine. In this paper, we investigate using different deep convolutional neural networks (CNN) to extract deep features from images of scanned documents. The extracted features are further processed using various machine learning classifiers such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Gaussian Naive Bayes (GNB). Different metrics were used (accuracy, precision, etc.) and examined to compare all models performances, while cross-validation approach at different folds sizes (4, 6, 8 and 10) was used to assess their generalization ability. The effect of dimensionality reduction techniques on overall performances was also explored. The best classification rate was 96.1%, which was achieved by combining LR and the VGG19 model. This very good performance despite the small dataset used (200 images) can allow using this approach in an ERP system as a preprocessing step in document manipulation for ERP users.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132573561","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092137
Abdallah Aijjou, L. Bahatti, A. Raihani
Toughening requirements on reducing ship energy consumption and gas emissions raise the importance of the adoption of various energy-saving systems on marine engine and ship machinery design.Energy recovery from exhaust gases has a great potential considering the amount of mechanical or electrical work which could be generated onboard.This paper presents the study for the enhancement of the total energy efficiency of a vessel power-plant is developed by using a high-efficiency turbocharger. In this case, the study is focused on the Diesel operation mode of the engine to calculate the potential of energy that can be recovered from exhaust gas flow by the turbocharger.
{"title":"Improving ship energy efficiency by waste heat recovery: Case of turbocharger","authors":"Abdallah Aijjou, L. Bahatti, A. Raihani","doi":"10.1109/IRASET48871.2020.9092137","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092137","url":null,"abstract":"Toughening requirements on reducing ship energy consumption and gas emissions raise the importance of the adoption of various energy-saving systems on marine engine and ship machinery design.Energy recovery from exhaust gases has a great potential considering the amount of mechanical or electrical work which could be generated onboard.This paper presents the study for the enhancement of the total energy efficiency of a vessel power-plant is developed by using a high-efficiency turbocharger. In this case, the study is focused on the Diesel operation mode of the engine to calculate the potential of energy that can be recovered from exhaust gas flow by the turbocharger.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"288 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121074277","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9091982
Sabbane Fadoua, Tairi Hamid
Recent advancements in a new era of e-health and telemedicine technologies present newer opportunities for sharing medical data when an open communication channel is used. However, this exchange is facing critical challenges of copyright protection, content authentication, and integrity verification. Therefore, due to the high demand for safe manipulation of patient’s medical information, digital watermarking is required, as a value-added tool, for secure medical data management. In this study, a new reversible watermarking technique for the security of medical videos is proposed. The patient identity is embedded, as a watermark, into the host medical videos. An algorithm is adopted for selecting the optimal frames in each video shot. This approach includes the use of polynomial transform methods, in order to identify the best watermark embedding areas in the optimal frames. Experimental results demonstrate high imperceptibility of the watermark and strong robustness against different attacks. Hence, our algorithm validates the security measures that ensure an effective manipulation of medical videos.
{"title":"Medical Video Watermarking Scheme for Telemedicine Applications","authors":"Sabbane Fadoua, Tairi Hamid","doi":"10.1109/IRASET48871.2020.9091982","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9091982","url":null,"abstract":"Recent advancements in a new era of e-health and telemedicine technologies present newer opportunities for sharing medical data when an open communication channel is used. However, this exchange is facing critical challenges of copyright protection, content authentication, and integrity verification. Therefore, due to the high demand for safe manipulation of patient’s medical information, digital watermarking is required, as a value-added tool, for secure medical data management. In this study, a new reversible watermarking technique for the security of medical videos is proposed. The patient identity is embedded, as a watermark, into the host medical videos. An algorithm is adopted for selecting the optimal frames in each video shot. This approach includes the use of polynomial transform methods, in order to identify the best watermark embedding areas in the optimal frames. Experimental results demonstrate high imperceptibility of the watermark and strong robustness against different attacks. Hence, our algorithm validates the security measures that ensure an effective manipulation of medical videos.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117043055","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092186
Hamid El Malali, Abdelhadi Assir, Mohammed Harmouchi, A. Lyazidi, M. Rattal, A. Mouhsen
Breast cancer is the second disease causing death in women. The screening of breast cancer for early detection is an effective way to reduce mortality. Generally, mammography is the most effective imaging modality recommended by radiologists. Therefore, a high number of mammogram images have to be analyzed. Indeed, the expertise of radiologists and the quality of the images to be analyzed play a crucial role in the accuracy of the diagnosis. The use of CAD systems allow improving the accuracy of diagnosis by reducing the number of false-positive and the false-negative. In this paper, to assist radiologists to make the right decision by showing them the probably suspect area, a full automatic CADe is presented. The preprocessing step aims at delimiting the ROI by removing artifact and pectoral muscle using global thresholding method, morphological operators and seeded region growing method, followed by contrast enhancement of the ROI found in the first step using the technique named “adaptive local gray level transformation based on variable s-curve”. At last, the ROI is segmented using k-means clustering. Both contrast enhancement method and the segmentation method are performed by genetic algorithm to optimize the outcomes of each step.
{"title":"Fully Automatic Computer-Aided Detection of Breast Cancer based on Genetic Algorithm Optimization","authors":"Hamid El Malali, Abdelhadi Assir, Mohammed Harmouchi, A. Lyazidi, M. Rattal, A. Mouhsen","doi":"10.1109/IRASET48871.2020.9092186","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092186","url":null,"abstract":"Breast cancer is the second disease causing death in women. The screening of breast cancer for early detection is an effective way to reduce mortality. Generally, mammography is the most effective imaging modality recommended by radiologists. Therefore, a high number of mammogram images have to be analyzed. Indeed, the expertise of radiologists and the quality of the images to be analyzed play a crucial role in the accuracy of the diagnosis. The use of CAD systems allow improving the accuracy of diagnosis by reducing the number of false-positive and the false-negative. In this paper, to assist radiologists to make the right decision by showing them the probably suspect area, a full automatic CADe is presented. The preprocessing step aims at delimiting the ROI by removing artifact and pectoral muscle using global thresholding method, morphological operators and seeded region growing method, followed by contrast enhancement of the ROI found in the first step using the technique named “adaptive local gray level transformation based on variable s-curve”. At last, the ROI is segmented using k-means clustering. Both contrast enhancement method and the segmentation method are performed by genetic algorithm to optimize the outcomes of each step.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124419364","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}
Pub Date : 2020-04-01DOI: 10.1109/IRASET48871.2020.9092294
A. Mokhtari, M. Azizi, M. Gabli
One of the main challenges in cloud computing is how to manage optimally the cloud resources in response of execution needs; so that both the cost and the time of running users applications are reduced. However, prices may change over time. In this paper, we propose an optimization-based solution which combines a Dynamic Genetic Algorithm (DGA) approach and fuzzy logic. First, we presented the DGA which provides a fair consideration of objectives. Then, we introduced a model based on possibility theory where each cost is taken as a fuzzy variable. For that, we used both possibility and necessity measures. In order to validate our solution, we tested it over some real applications using a set of cloud resources available on the market. The obtained results demonstrate clearly that our algorithms succeeded to find reasonable solutions that fulfill successfully our objectives function.
{"title":"A fuzzy dynamic approach to manage optimally the cloud resources","authors":"A. Mokhtari, M. Azizi, M. Gabli","doi":"10.1109/IRASET48871.2020.9092294","DOIUrl":"https://doi.org/10.1109/IRASET48871.2020.9092294","url":null,"abstract":"One of the main challenges in cloud computing is how to manage optimally the cloud resources in response of execution needs; so that both the cost and the time of running users applications are reduced. However, prices may change over time. In this paper, we propose an optimization-based solution which combines a Dynamic Genetic Algorithm (DGA) approach and fuzzy logic. First, we presented the DGA which provides a fair consideration of objectives. Then, we introduced a model based on possibility theory where each cost is taken as a fuzzy variable. For that, we used both possibility and necessity measures. In order to validate our solution, we tested it over some real applications using a set of cloud resources available on the market. The obtained results demonstrate clearly that our algorithms succeeded to find reasonable solutions that fulfill successfully our objectives function.","PeriodicalId":271840,"journal":{"name":"2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122129924","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}
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