2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)最新文献_第5页

Towards Smart Blockchain-Based System for Privacy and Security in a Smart City environment 智慧城市环境中基于区块链的隐私和安全系统

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365905

Driss El Majdoubi, H. Bakkali, Souad Sadki

{"title":"Towards Smart Blockchain-Based System for Privacy and Security in a Smart City environment","authors":"Driss El Majdoubi, H. Bakkali, Souad Sadki","doi":"10.1109/CloudTech49835.2020.9365905","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365905","url":null,"abstract":"Nowadays, the digitalization of urban environments is redefining the public and private sectors. Moreover, Internet of Things (IoT) platforms, cloud computing infrastructure and smart devices are exchanging tremendous amount of data. This harmonious integration of the cyber capabilities of the corresponding devices with the physical world generates new opportunities in many areas; however it raises a lot of security and privacy challenges due to the diversity of sources and stakeholders, the centralized data management and the resulting lack of trust and governance. Hence, we introduce \"SmartPrivChain\" a Smart Blockchain Based System for preserving privacy and security in a smart city environment. The proposed scheme is different from the existing approaches on many points. The data privacy is preserved by combining data access control and data usage auditing measures based on smart contracts. In addition, the proposed solution is compliant with the main privacy laws and regulations especially the obligations of the European Union General Data Protection Regulation (GDPR). Lastly, we propose an enhanced Proof of Reputation (PoR) consensus scheme using a multidimensional Trust model.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122742939","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: 7

A New Recurrent Neural Network Fuzzy Mean Square Clustering Method 一种新的递归神经网络模糊均方聚类方法

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365873

K. E. Moutaouakil, A. Touhafi

引用次数: 8

Parameters extraction of photovoltaic modules using a combined analytical - numerical method 基于解析-数值结合方法的光伏组件参数提取

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365901

Khalid Chennoufi, M. Ferfra

引用次数: 4

Medical Image Registration via Similarity Measure based on Convolutional Neural Network 基于卷积神经网络相似度度量的医学图像配准

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365908

Li Dong, Yongzheng Lin, Yishen Pang

引用次数: 0

Run Time Optimization using a novel implementation of Parallel-PSO for real-world applications 对实际应用程序使用Parallel-PSO的新颖实现进行运行时优化

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365867

Amine Chraibi, Said Ben Alla, A. Touhafi, Abdellah Ezzati

{"title":"Run Time Optimization using a novel implementation of Parallel-PSO for real-world applications","authors":"Amine Chraibi, Said Ben Alla, A. Touhafi, Abdellah Ezzati","doi":"10.1109/CloudTech49835.2020.9365867","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365867","url":null,"abstract":"The majority of optimization algorithms and methods generally necessitate a considerable run time to reach their goal. Most of them are used mainly in real-world applications. This article concentrates on an efficient and well-known algorithm to solve optimization problems: the Particle Swarm Optimisation algorithm (PSO). This algorithm needs a considerable run time to solve an optimization problem with a high dimension space and data. The article also concentrates on OpenCL, which defines a common parallel programming language for various devices such as GPU, CPU, FPGA, etc. In order to minimize the run time of PSO, this paper introduces a new implementation of PSO in OpenCL. By decomposing the PSO code into two fragments, each one can run simultaneously. The experimental results covered both the sequential and parallel implementations. Furthermore, show that the PSO’ OpenCL implementation is faster than the Sequential-PSO implementation. The OpenCL profiling results show the timing of each part of the executing of PSO in OpenCL.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130262825","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

Learning Analytics based on Bayesian Optimization of Support Vector Machines with Application to Student Success Prediction in Mathematics Course 基于贝叶斯优化支持向量机的学习分析及其在数学课程学生成功预测中的应用

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365915

S. Lahmiri, R. Saadé, Danielle Morin, F. Nebebe

{"title":"Learning Analytics based on Bayesian Optimization of Support Vector Machines with Application to Student Success Prediction in Mathematics Course","authors":"S. Lahmiri, R. Saadé, Danielle Morin, F. Nebebe","doi":"10.1109/CloudTech49835.2020.9365915","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365915","url":null,"abstract":"Learning analytics is receiving a growing attention from both machine learning and education communities, where support vector machines (SVM) are gaining popularity over existing data mining techniques. In the scope of this work, we employ SVM to predict student success in mathematics course in Portugal under two common nonlinear kernel functions: polynomial and radial basis function kernel. In addition, we employ the k-nearest-neighbor (kNN) algorithm as a reference model since it is known to be fast and effective in various classification problems. Furthermore, we adopt the Bayesian optimization (BO) technique in a cross-validation framework to optimize SVM key parameters; namely, the slack parameter and penalty coefficient. The obtained experimental results show that the SVM outperform k-nearest-neighbor algorithm under both nonlinear kernel functions. Additionally, processing time associated with SVM optimization process increases with polynomial order. Furthermore, the SVM trained with third-order polynomial kernel performs the best. Finally, k-nearest-neighbor algorithm is found to be faster compared to all SVM classifiers.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121849451","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

Quality Approach to Analyze the Causes of Failures in MOOC 质量方法分析MOOC教学失败原因

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365904

Sraidi Soukaina, Smaili El Miloud, Salma Azzouzi, M. E. H. Charaf

引用次数: 3

Efficient Mobile User Authentication Service with Privacy Preservation and User Untraceability 具有隐私保护和用户不可追溯性的高效移动用户认证服务

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365896

An Braeken, A. Touhafi

{"title":"Efficient Mobile User Authentication Service with Privacy Preservation and User Untraceability","authors":"An Braeken, A. Touhafi","doi":"10.1109/CloudTech49835.2020.9365896","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365896","url":null,"abstract":"Security questions and answers for authentication are a common approach to enable the user to reset forgotten passwords. Moreover, they are also sometimes used as alternative for the classical username-password system, which fails in offering a good balance between user friendliness and security as long and complex passwords are required. However, in order to guarantee the privacy of the user as imposed by the new General Data Protection Regulation (GDPR), it should be impossible to derive the answer of the user by any other entity, including the server provider or the server managing the authentication.In this paper, we present an efficient mobile based security mechanism to realise this goal. The proposed scheme can be applied on top of any type of question-answer based authentication system. In addition, our solution also offers anonymity and untraceability of the user, such that no activity patterns can be drawn by simply eavesdropping on the communication channel to the service provider or the authentication server. We show that our proposed mechanism not only offers more security features compared to related work, but it is also significantly faster, in particular at the side of the user.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127948246","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

An Overview of Recommender Systems in the Context of Smart Cities 智慧城市背景下的推荐系统综述

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365877

Rabie Madani, Abderrahmane Ezzahout, A. Idrissi

引用次数: 1

Big Data Architectures Benchmark for Forecasting Electricity Consumption 预测用电量的大数据架构基准

2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) Pub Date : 2020-11-24 DOI: 10.1109/CloudTech49835.2020.9365912

Houda Daki, A. Hannani, H. Ouahmane

{"title":"Big Data Architectures Benchmark for Forecasting Electricity Consumption","authors":"Houda Daki, A. Hannani, H. Ouahmane","doi":"10.1109/CloudTech49835.2020.9365912","DOIUrl":"https://doi.org/10.1109/CloudTech49835.2020.9365912","url":null,"abstract":"Now a day, educational institutions present one of the highest power consuming sector due to their new activities and occupancy pattern. This enormous amount of energy consumption at the university need a huge effort to reduce it. Smart grid is among the efficient solution to save energy and balance supply and demand. For the same purpose, the National School of Applied Sciences of El Jadida-Morocco wants take advantage from smart grid to maintain the balance between energy production and consumption. Despite of all added value of this smart grid solution for the school, it has the issue of managing energy production surplus, because it cannot inject it into Moroccan electrical infrastructure neither store it using storage devices. So, to overcome this challenge the system need to predict electrical consumption to be able to produce exactly the same value. Recently, Big Data contributed very well in analysing electrical consumption data using many tools and advanced techniques. It process, interprets and analyzes huge quantity of data to make it more profitable and valuable. For that reason, the school will take refuge in Big data technology to implement a custom system to predict electrical energy consumption by analyze all factors that influence electrical energy use. In this paper, we propose a benchmark of the main Big Data architectures in the field and that will cover all electrical energy data processing from data collection, data storage, data analytic and data visualization. The aim of this benchmark is to choose the optimal architecture in term of fault tolerance, resource management, data storage and data modelling to forecast electricity consumption in educational institutions.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128313442","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