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Requirements Metamodeling for Self-Adaptive Embedded Systems 自适应嵌入式系统的需求元建模
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.311508
Zina Mecibah, Fateh Boutekkouk
{"title":"Requirements Metamodeling for Self-Adaptive Embedded Systems","authors":"Zina Mecibah, Fateh Boutekkouk","doi":"10.4018/ijsi.311508","DOIUrl":"https://doi.org/10.4018/ijsi.311508","url":null,"abstract":"Embedded systems (ES) ubiquity has increased in the last two decades; it is seldom to find any electronic device that is not controlled by ES. Additionally, there are a large number of ES which need to modify their behavior at run time in response to changing environmental conditions or in the cases where the requirements themselves need to be changed. Up to now, few researchers are interested in the high-level design process of the self-adaptive embedded systems (SAES) specifically in the field of requirement engineering (RE). While there exit some metamodels on RE for SAES, to the best of the authors' knowledge, there is no comprehensive metamodel that can be used as a reference for the development of RE for SAES. For this reason, the objectives of this paper are twofold, first, to review the literature state of the art and practice of requirements engineering for self-adaptive embedded systems and secondly to propose a complete metamodel (MM4SAES) that defines all concepts and relationships that must be taken into account in the development of SAES","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123612763","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
A Comparative Study of Machine Learning Techniques for Android Malware Detection Android恶意软件检测的机器学习技术比较研究
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309719
Mohamed Guendouz, Abdelmalek Amine
{"title":"A Comparative Study of Machine Learning Techniques for Android Malware Detection","authors":"Mohamed Guendouz, Abdelmalek Amine","doi":"10.4018/ijsi.309719","DOIUrl":"https://doi.org/10.4018/ijsi.309719","url":null,"abstract":"The rapid growth and wide availability of Android applications in recent years has resulted in a spike in the number of sophisticated harmful applications targeting Android users. Because of the popularity and amount of open-sourced supported features of Android OS, cyber attackers prefer to target Android-based devices over other smartphones. Malicious programs endanger user privacy and device integrity. To address this issue, the authors investigated machine learning algorithms for detecting malware in Android in this study. They employed a static analysis approach, collecting permissions from each application's APK and then generating feature vectors based on the extracted permissions. Finally, they trained several machine learning algorithms to create classification models that can distinguish between benign and malicious applications. According to experimental findings, random forest and multi-layer perceptron approaches, which have accuracy levels of 95.4% and 95.1%, respectively, have the best classification performance.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"414 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124813093","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: 1
Formal Verification and Implementation of an E-Voting System 电子投票系统的正式验证和实施
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309731
Said Meghzili, A. Chaoui, R. Elmansouri, Bardis Nadjla Alloui, Amina Bouabsa
{"title":"Formal Verification and Implementation of an E-Voting System","authors":"Said Meghzili, A. Chaoui, R. Elmansouri, Bardis Nadjla Alloui, Amina Bouabsa","doi":"10.4018/ijsi.309731","DOIUrl":"https://doi.org/10.4018/ijsi.309731","url":null,"abstract":"The organization of free, democratic, and transparent elections requires on the one hand an independent national electoral authority that manages all the stages of the electoral process and on the other hand the use of new information and communication techniques to manage the election process. E-voting offers the ability to vote online anytime and from anywhere using a computer, smartphone, or tablet. In addition, it saves time and reduces costs and effort spent in the process. However, the security of e-voting applications deployed on the internet is a difficult task due to the increasing number of cyber-attacks and application vulnerabilities. On the other hand, blockchain technology is an emerging technology with a strong cryptographic foundation. In this paper, the authors propose a new secure e-voting system based on Ethereum blockchain. In addition, they propose a hierarchical coloured petri net (HCPN) model for their e-voting system using CPN Tools. They verify by means of simulation techniques and state space analysis important properties such as absence of deadlocks and livelocks.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128687263","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
Prioritizing COVID-19 Vaccine Delivery for the Indian Population 优先为印度人口提供COVID-19疫苗
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.301228
M. Singh, S. Modak, D. Sarkar
{"title":"Prioritizing COVID-19 Vaccine Delivery for the Indian Population","authors":"M. Singh, S. Modak, D. Sarkar","doi":"10.4018/ijsi.301228","DOIUrl":"https://doi.org/10.4018/ijsi.301228","url":null,"abstract":"As India has successfully developed vaccine to fight against the Covid-19 pandemic, the government has started its immunization program to vaccinate the population. Initially with the limited availability in vaccines a prioritized roadmap is required to suggest public health strategies and target priority groups on the basis of population demographics, health survey information, city/region density, cold storage facilities, vaccine availability and epidemiologic settings. In this paper, a machine learning based predictive model is presented to help the government make informed decisions/insights around epidemiological and vaccine supply circumstances by predicting India's more critical segments that need to be catered with vaccine deliveries as prior as possible. Public data were scraped to create the dataset, exploratory data analysis was performed on the dataset to extract important features on which clustering and ranking algorithms were performed to figure out the importance and urgency of vaccine deliveries in each region.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121437125","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
Factors Affecting Successful Implementation of Smart Manufacturing Systems 影响智能制造系统成功实施的因素
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.301569
Jaehyeon Jun, Insu Cho
{"title":"Factors Affecting Successful Implementation of Smart Manufacturing Systems","authors":"Jaehyeon Jun, Insu Cho","doi":"10.4018/ijsi.301569","DOIUrl":"https://doi.org/10.4018/ijsi.301569","url":null,"abstract":"Although the introduction and utilization of smart manufacturing systems within the industry is accelerating, it is difficult to quantitatively analyze the effects of smart manufacturing systems. It is also difficult to grasp the factors that influence the success of system implementation. In this study, we measured the factors affecting the successful implementation of various types of smart manufacturing systems by confirming the factors affecting user satisfaction of smart manufacturing system. Based on the 282 samples, this study empirically tests a structural model using PLS 3.0 for the explanation of the successful implementation of smart manufacturing system. As a result of this study, it is expected to find that which factors affect to the user satisfaction of the system among the sub-factors representing aspects of information, systemic, organizational, and user background.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131470950","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
XHDLNet Classification of Virus-Borne Diseases for Chest X-Ray Images Using a Hybrid Deep Learning Approach 基于混合深度学习方法的XHDLNet胸透图像病毒传播疾病分类
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.311505
Srishti Choubey, S. Barde, Abhishek Badholia
{"title":"XHDLNet Classification of Virus-Borne Diseases for Chest X-Ray Images Using a Hybrid Deep Learning Approach","authors":"Srishti Choubey, S. Barde, Abhishek Badholia","doi":"10.4018/ijsi.311505","DOIUrl":"https://doi.org/10.4018/ijsi.311505","url":null,"abstract":"Various forms and symptoms of corona virus have been observed in human body especially in heart, chest and affects the respiratory system. In the initial phase, RT-PCR examination is applied to monitor the target disease, but suffers from low sensitivity and a laborious process. Apart from this, another mechanism for corona virus detection involves the analysis the CT image has become an imperative device for clinical judgment. However, manual investigation of such disease in numerous amounts of images is not the optimal approach. Additionally, recent advancement in artificial intelligence techniques have assisted medical diagnosis to identify the virus in a standard environment. In this work, the potential of such intelligence methods is analyzed and extended by considering the optimal feature extraction capability and proposes a hybrid approach in which three universal architectures namely: Inception V4, DenseNet 201 and Xception have been utilized which not only classify the corona virus disease but may also provide a pathway to apply similar method in other medical diagnosis.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127564474","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
Deep Belief Neural Network (DBNN)-Based Categorization of Uncertain Data Streams 基于深度信念神经网络(DBNN)的不确定数据流分类
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.312262
G. J. Raju, G. Raju
{"title":"Deep Belief Neural Network (DBNN)-Based Categorization of Uncertain Data Streams","authors":"G. J. Raju, G. Raju","doi":"10.4018/ijsi.312262","DOIUrl":"https://doi.org/10.4018/ijsi.312262","url":null,"abstract":"In the data mining era, the research field is paying attention to data stream mining, which offers a substantial influence on a variety of applications such as networking, wireless communications, education, economics, weather prediction, financial sector, and so on. Moreover, processing of this uncertain data stream faces two major challenges, which are computational difficulty and long processing time of data. Thus, to overcome this, this work proposes a technique that employs a deep belief neural network to categorize uncertain data streams. Initially, this work utilized a hybrid method that combines ensemble, grid, and density-dependent clustering approaches to acquire the local optimum value in uncertain data streams. Furthermore, for classification, a deep belief neural network (DBNN) has been used. As a result of mining, target semantics or chunks will be obtained from the classified data. The suggested technique performs well, and its effectiveness has been assessed in terms of time and accuracy. Thus, the proposed method outperforms the existing techniques.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132001907","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
Analysis of Psychological Distress During COVID-19 Among Professionals 新型冠状病毒肺炎期间专业人员心理困扰分析
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.309109
Supriya Raheja
{"title":"Analysis of Psychological Distress During COVID-19 Among Professionals","authors":"Supriya Raheja","doi":"10.4018/ijsi.309109","DOIUrl":"https://doi.org/10.4018/ijsi.309109","url":null,"abstract":"The aftermath of the lockdown caused by the current pandemic generates many challenges and opportunities for the professionals as well as for organizations. Several organizations forced the people to work on-site whereas many of the organizations have been allowing work from home. However, both ways of working are challenging and cause psychological distress. The present work analyses the psychological distress among professionals residing in India during the COVID-19 pandemic. The work considers both the scenarios of working professionals: professionals working from home and professionals working onsite. The work introduces a novel hybrid machine learning approach called GBETRR. GBETRR combines two approaches, namely gradient-boosting classifier and extra-trees regressor repressor. The present work also uses a hybrid parameter optimization algorithm. Multiple performance metrics are used to evaluate the performance evaluation. Results revealed that the professionals with work from home are more stressed as compared to the professionals working onsite.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114217241","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
Contextual Fuzzy Ranking for Web Services Discovery in a Hybrid Architecture 混合体系结构中Web服务发现的上下文模糊排序
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.303583
D. E. Abdelli, F. M. Bouyakoub
{"title":"Contextual Fuzzy Ranking for Web Services Discovery in a Hybrid Architecture","authors":"D. E. Abdelli, F. M. Bouyakoub","doi":"10.4018/ijsi.303583","DOIUrl":"https://doi.org/10.4018/ijsi.303583","url":null,"abstract":"The fast increasing number of web services is transforming the web from a data-oriented repository to a service-oriented repository. This repositories offers a single search point for all shared services which makes the discovery of web services is one of main action in the service-oriented architecture. After a deep study of the existing repositories authors propose a hybrid architecture for web service discovery with multi-level domain services implemented with mult-iagent technology to fulfill some of the lacks in previous works. Also, propose a contextual fuzzy ranking approach to help the user to select the best services according to his needs.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114616498","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
A Study on the Factors Causing the Intention to Use a Smart Tolling System 智能收费系统使用意向的影响因素研究
Int. J. Softw. Innov. Pub Date : 2022-01-01 DOI: 10.4018/ijsi.304877
Sung il Hur, Yong Gi Park, J. Jang
{"title":"A Study on the Factors Causing the Intention to Use a Smart Tolling System","authors":"Sung il Hur, Yong Gi Park, J. Jang","doi":"10.4018/ijsi.304877","DOIUrl":"https://doi.org/10.4018/ijsi.304877","url":null,"abstract":"Smart tolling, which improved the drawbacks of the existing high-pass system, was developed and built through the Smart Highway R & D project in 2007. To successfully introduce and spread Smart Tolling, it needs to analyze factors that affected by intent to use. This study conducted research based on literature studies and empirical studies and developed a research model to analyze factors causing the users' intention of smart tolling system based on technology acceptance model (TAM) and value-based acceptance model. The main variables of the research model are service characteristics (convenience, reliability), technical characteristics (flexibility, stability), environmental characteristics (switching cost, effectiveness of policy), and intention to use. To test the hypotheses set in this study, frequency analysis, exploratory factor analysis, and confirmatory factor analysis were performed using the SPSS 22.0 program statistical package and AMOSS 18.0. The convenience and reliability presented by service characteristics did not affect the intention to use.","PeriodicalId":396598,"journal":{"name":"Int. J. Softw. Innov.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123178483","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
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