Computer science & information technology最新文献_第2页

Parallel Evolutionary Biclustering of Short-term Electric Energy Consumption 短期电能消耗的并行进化双聚类

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111110

D. Pinto-Roa, H. Medina, Federico Román, M. García-Torres, F. Divina, Francisco Gómez-Vela, Félix Morales, Gustavo Velázquez, Federico Daumas, José L. Vázquez-Noguera, Carlos Sauer Ayala, P. E. Gardel-Sotomayor

引用次数: 2

Secure Protocol for Four D2D Scenarios 四种D2D场景的安全协议

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111102

Hoda Nematy

{"title":"Secure Protocol for Four D2D Scenarios","authors":"Hoda Nematy","doi":"10.5121/CSIT.2021.111102","DOIUrl":"https://doi.org/10.5121/CSIT.2021.111102","url":null,"abstract":"In traditional cellular infrastructure, cellular devices communicate with each other directly even when they are close together. This strategy causes massive traffic to the cellular network therefore D2D communication has introduced to overcome this issue, bring more bandwidth and also higher rates to the cellular network. One of the major challenges for D2D Communication is to have one single secure protocol that can adapt in four D2D scenarios defined in references. These scenarios are Direct D2D and relaying D2D communication with and without cellular infrastructure. In this paper, we propose a Secure D2D protocol based on ARIADNE with TESLA. Also we use LTE-A AKA protocol for authentication and key agreement procedure between Source and Destination. Next, we adapt this scenario to be applicable in without cellular infrastructure ones. This protocol could be used in direct D2D also. Based on the results, our proposed protocol has a few computation overhead compare to recent works and have less communication overhead than SODE with preserve many security properties such as Authentication, Authorization, Confidentiality, Integrity, Secure Key Agreement, Secure Routing Transmission…. We check Authentication, Confidentiality, Reachability and Secure Key Agreement of the proposed protocol with ProVerif verification tools.","PeriodicalId":72673,"journal":{"name":"Computer science & information technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48217749","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

Using Multilinear Feature Space to Accelerate CNN Classification 利用多线性特征空间加速CNN分类

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111109

M. A. L. Vinagreiro, Edson C. Kitani, A. Laganá, L. Yoshioka

{"title":"Using Multilinear Feature Space to Accelerate CNN Classification","authors":"M. A. L. Vinagreiro, Edson C. Kitani, A. Laganá, L. Yoshioka","doi":"10.5121/CSIT.2021.111109","DOIUrl":"https://doi.org/10.5121/CSIT.2021.111109","url":null,"abstract":"Computer vision plays a crucial role in ADAS security and navigation, as most systems are based on deep CNN architectures the computational resource to run a CNN algorithm is demanding. Therefore, the methods to speed up computation have become a relevant research issue. Even though several works on acceleration techniques found in the literature have not yet been achieved satisfactory results for embedded real-time system applications. This paper presents an alternative approach based on the Multilinear Feature Space (MFS) method resorting to transfer learning from large CNN architectures. The proposed method uses CNNs to generate feature maps, although it does not work as complexity reduction approach. When the training process ends, the generated maps are used to create vector feature space. We use this new vector space to make projections of any new sample in order to classify them. Our method, named MFS-CNN, uses the transfer learning from pre trained CNN to reduce the classification time of new sample image, with minimal loss in accuracy. Our method uses the VGG-16 model as the base CNN architecture for experiments; however, the method works with any similar CNN model. Using the well-known Vehicle Image Database and the German Traffic Sign Recognition Benchmark we compared the classification time of original VGG-16 model with the MFS-CNN method and our method is, on average, 17 times faster. The fast classification time reduces the computational and memories demand in embedded applications that requires a large CNN architecture.","PeriodicalId":72673,"journal":{"name":"Computer science & information technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48568170","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

Product Quality Evaluation Method (PQEM): A Comprehensive Approach for the Software Product Life Cycle 产品质量评价方法（PQEM）：一种软件产品生命周期的综合方法

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111104

M. Falcó, Gabriela Robiolo

{"title":"Product Quality Evaluation Method (PQEM): A Comprehensive Approach for the Software Product Life Cycle","authors":"M. Falcó, Gabriela Robiolo","doi":"10.5121/CSIT.2021.111104","DOIUrl":"https://doi.org/10.5121/CSIT.2021.111104","url":null,"abstract":"Project managers, product owners, and quality assurance leaders need to visualize and understand the entire picture of the development process as well as comprehend the product quality level, in a synthetic and intuitive way in order to facilitate the decision of accepting or rejecting each iteration within the software life cycle. This idea is extremely important nowadays, due to the fact that time is a key resource and it should be managed wisely to obtain a feasible quality level for each software deliverable. This article presents a novel solution called Product Quality Evaluation Method (PQEM) to evaluate a set of quality characteristics for each iteration of a software product. PQEM is based on the Goal-Question-Metric approach, the standard ISO/IEC 25010, and the extension made of testing coverage in order to obtain the quality coverage of each quality characteristic. The outcome of PQEM is a single value representing the quality per each iteration of a product, as an aggregated measure. Even though a value it is not the regular idea of measuring quality, we believe that it can be useful to use this value to understand easily the quality level of each iteration. An illustrative example of the method was carried out with a web and mobile application, within the healthcare environment.","PeriodicalId":72673,"journal":{"name":"Computer science & information technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48976993","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: 3

Credit Card Fraud Detection using Supervised and Unsupervised Learning 使用监督和非监督学习的信用卡欺诈检测

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111107

Vikas Thammanna Gowda

引用次数: 0

A Generalized Approach to Data Supply Chain Management – Balancing Data Value and Data Debt 数据供应链管理的一种通用方法——平衡数据价值和数据债务

Computer science & information technology Pub Date : 2021-07-24 DOI: 10.5121/CSIT.2021.111105

Roberto Maranca, M. Staiano

引用次数: 0

Care – A Framework for a Multimedia Assistance System for Singletons “Does It Help?” Care——单身人士多媒体辅助系统的框架“它有帮助吗？”

Computer science & information technology Pub Date : 2021-07-10 DOI: 10.5121/CSIT.2021.111010

T. Schirgi

引用次数: 1

Enhancing Security in Internet of Things Environment by Developing an AuthenticationMechanism using COAP Protocol 利用COAP协议开发认证机制提高物联网环境下的安全性

Computer science & information technology Pub Date : 2021-07-10 DOI: 10.5121/CSIT.2021.111008

Hernandez Pedro, Espitia Edinson

引用次数: 0

Manufacturers, AI Models and Machine Learning, Value Chains, and 5th Generation Wireless Networks 制造商，人工智能模型和机器学习，价值链和第五代无线网络

Computer science & information technology Pub Date : 2021-07-10 DOI: 10.5121/CSIT.2021.111003

obert B. Cohen

{"title":"Manufacturers, AI Models and Machine Learning, Value Chains, and 5th Generation Wireless Networks","authors":"obert B. Cohen","doi":"10.5121/CSIT.2021.111003","DOIUrl":"https://doi.org/10.5121/CSIT.2021.111003","url":null,"abstract":"When AI models and machine learning are fully interconnected in factories with cabling-free 5G wireless networks, firms become “fully digital”. This analysis argues that it is not the initial efficiencies gained by optimizing a plant’s operations but rather a firm’s ability to build a collection of knowledge about each step of its operations, what we call “knowledge synthesis”. This is information about how each product is produced, how the process to produce it is managed and optimized, and the software and systems required. This knowledge is important because it permits firms to exploit network effects based upon connecting plants together or sharing expertise with partners. This greatly expands the potential for economic benefits from the use of AI and 5G. This review explores cases from firms with smart factories that have adopted AI and 5G communications including Moderna, Sanofi, Mercedes, Ford, and VW. It examines how these firms have benefitted from the move to smart factories with 5G communications networks. It also explores how firms have improved their value chains by building smart factories that connect nearly all manufacturing processes to machine learning and AI models that analyze machine and process data rapidly. Next, they take advantage of network effects – due to “knowledge synthesis” that permits early smart factories with 5G networks --to derive even larger benefits inside their production operations and in their supply chains. In both phases, the adoption of 5th Generation wireless in plants ramps up firms’ abilities to interconnect their digital systems. Once the interconnected systems exist, firms exploit network effects to create “knowledge synthesis” or knowledge platforms to consolidate insights gained from optimizing many machines and processes. Using “knowledge synthesis”, firms can also transfer knowledge from one group of equipment to another that is not optimized even when the equipment is in different facilities. This makes firms far more flexible, interoperable, and scalable.","PeriodicalId":72673,"journal":{"name":"Computer science & information technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47365838","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

Seasonal Heavy Rain Forecasting Method 季节性暴雨预报方法

Computer science & information technology Pub Date : 2021-07-10 DOI: 10.5121/CSIT.2021.111002

Jaekwang Kim

引用次数: 0