2021 2nd International Informatics and Software Engineering Conference (IISEC)最新文献_第3页

Secure IoT Update Using Blockchain 使用区块链进行安全的物联网更新

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672424

M. Kaptan, E. Tomur, Tolga Ayav, Y. M. Erten

{"title":"Secure IoT Update Using Blockchain","authors":"M. Kaptan, E. Tomur, Tolga Ayav, Y. M. Erten","doi":"10.1109/iisec54230.2021.9672424","DOIUrl":"https://doi.org/10.1109/iisec54230.2021.9672424","url":null,"abstract":"In this study a platform is devised to send automatic remote updates for embedded devices. In this scenario there are Original Equipment Manufacturers (OEMs), Software suppliers, blockchain nodes, Gateways and embedded devices. OEMs and software suppliers are there to keep their software on Inter Planetary File System (IPFS) and send the meta-data and hashes of their software to the blockchain nodes in order to keep this information distributed and ready to be requested and used. There are also gateways which are the members of the blockchain and the IPFS network. Gateways are responsible for asking for a specific update for specific devices from IPFS database using the meta-data kept on the blockchain, and they will send those hashed secure updates to the devices. In order to provide a traceable data keeping platform, gateway update operations are handled as transactions in a second blockchain network which is the clockchain of the gateways. The system was implemented as of the two separate blockchain networks and it has been shown that, despite the calculation overhead of the member devices, by separating the functions between the two blockchain networks a more reliable and secure platform can be achieved.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132559391","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

Social Commerce Adoption Based UTAUT Model for Consumer Behavior: Iraq Small and Medium Enterprise 基于UTAUT模型的消费者行为社会商务采用:伊拉克中小企业

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672383

Rasha Jasim Habeeb Habeeb, Shadi M. S. Hilles, Alaa M. Momani

{"title":"Social Commerce Adoption Based UTAUT Model for Consumer Behavior: Iraq Small and Medium Enterprise","authors":"Rasha Jasim Habeeb Habeeb, Shadi M. S. Hilles, Alaa M. Momani","doi":"10.1109/iisec54230.2021.9672383","DOIUrl":"https://doi.org/10.1109/iisec54230.2021.9672383","url":null,"abstract":"Using of e-commerce is one of the Internet's most far-reaching influences. Particularly, in terms of business and market models where Social commerce is proved to be a significant topic in information systems, where fast increasing online shops e-commerce platforms assisting in increasing customer engagement and sales. As a result, social media has evolved into a far more significant platform for the retail business. This research examines the impact of social commerce on customer behavior and intention to use electronic purchasing in the Iraqi local market, based on the suggested expanded Unified Theory of Acceptance and Use of Technology (UTAUT) model. The purpose of this paper is to analyses crucial elements using an empirical research as well as a quantitative survey questionnaire administered to social media users, with 410 valid responses where we conducted analysis on these responses by using SPSS package All participants can envisage the importance of e-commerce. The results also showed that the majority of the participants embrace the concept of e-commerce and react favorably to it. Further, the findings highlight that performance expectancy has a positive effect on behavioral intention and the actual use to adopt social commerce. The inclusion into the proposed model of relevant insights obtained from the interviews, the questionnaire, and the focus group ensures that the model has both theoretical and practical validity where study considers the major effect of Iraqi customers' behavioral intentions and their culture on social commerce. The analysis also considered nine dependent variables, including customer adoption and confidence in social commerce.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128915810","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

[Copyright notice] (版权)

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672384

引用次数: 0

Development of IoT Based Battery Management System 基于物联网的电池管理系统开发

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672346

Süleyman Çeven, Enver Küçükkülahli, A. Albayrak, Yunus Biçen

引用次数: 2

Machine Learning Based Web Application Firewall 基于机器学习的Web应用防火墙

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672335

Batuhan IŞiker, I. Sogukpinar

引用次数: 2

Model-Based Systems Engineering to Design An Onboard Surround Vision System for Cooperative Automated Vehicles 基于模型的系统工程设计协同自动驾驶车载环绕视觉系统

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672396

Narsimlu Kemsaram, Anwesha Das, Gijs Dubbelman

引用次数: 0

Understanding the Relation between System Usability and End User Performance 理解系统可用性和最终用户性能之间的关系

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672429

Layth Nabeel Alrawi

引用次数: 1

The model of conjoint servicing of real time traffic of surveillance cameras and elastic traffic devices with access control 基于门禁的监控摄像头与弹性交通设备的实时流量联合服务模型

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672443

U. Andrabi, S. Stepanov

{"title":"The model of conjoint servicing of real time traffic of surveillance cameras and elastic traffic devices with access control","authors":"U. Andrabi, S. Stepanov","doi":"10.1109/iisec54230.2021.9672443","DOIUrl":"https://doi.org/10.1109/iisec54230.2021.9672443","url":null,"abstract":"There has been a massive increase in the capacities and diversity of data being collected over the Internet of Things (IoT) applications and the management of such enormous data is one of the critical tasks for networking corporations as they advance from 4G+ to true 5G systems. Predominantly the majority of this traffic comprises complex, unstructured, and varied data (Big Data) originating from smart networking environments (LTE-devices, NB-IoT devices). Though 5G proposes various low power wide area technologies (Lora WAN, GSM, and NB-IoT, etc.), predominantly NB-IoT appears very promising to address the challenge because of its evident features such as high fault tolerance, delay tolerance, higher coverage area, etc. However, due to the constricted bandwidth (180 kHz) accessibility, one of the challenges is how to proficiently use these resources to support and handle a massive number of growing IoT devices, also resource management and allocation methodology between real time traffic and NB-IoT traffic flows resources. To address such a challenge, we have developed a dynamic scheduling model based on processor scheduling (PS) to manage radio resources, especially for shared servicing of real-time and elastic IoT traffic flows. Dynamic Scheduling based on processor sharing (PS) has been considered for an Operator Surveillance system for shared servicing of real-time video traffic coming from surveillance cameras and NB-IoT data traffic coming from devices such as smart meters and actuators over L TE cell facilities.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126999750","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

Multi-Features Classification of SMD Screen in Smart Cities using Randomised Machine Learning Algorithms 基于随机机器学习算法的智慧城市SMD屏幕多特征分类

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672380

Muhammad Imran Ghafoor, Muhammad Sohaib Roomi, Mubashar Aqeel, U. Sadiq, S. Bazai

{"title":"Multi-Features Classification of SMD Screen in Smart Cities using Randomised Machine Learning Algorithms","authors":"Muhammad Imran Ghafoor, Muhammad Sohaib Roomi, Mubashar Aqeel, U. Sadiq, S. Bazai","doi":"10.1109/iisec54230.2021.9672380","DOIUrl":"https://doi.org/10.1109/iisec54230.2021.9672380","url":null,"abstract":"Urban informatization applications are getting better and better, and smart cities are now taking shape because of the emergence of the Internet of Things (IoT), cloud computing, mobile Internet, and other new technologies. Smart cities allow information about a city's economic viability and culture to be shared and transmitted more rapidly. There is an increase in interconnection and communication using this method. People's living standards will rise because of the government's increased management and service capabilities. As smart cities become more common, new data sources, such as user behavior, preferences, and other insights, will be developed. A lot of data mining and analysis will be required. Urban informatization and industrialization will be achieved by implementing new information technology into a wide range of industries around the city. Efficiencies in urban management and the quality of life for residents will be enhanced by this reform. Many parts of city planning might be called “smart,” including transportation, health care, public safety, and education. Machine learning methods are being used to detect abnormalities in SMD Screen data, which includes information on all networking protocols. SMD LEDs used in LED displays are the subject of this research, which focuses on the most common causes of failure. When it comes to SMD LEDs' wet stress, antistatic capabilities, and hidden circuitry defects, we thoroughly inspect them. Following this research, we offer practical preventive solutions based on machine learning categorization models.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114259111","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 Performance Based Study on Deep Learning Algorithms in the Efficient Prediction of Heart Disease 基于性能的深度学习算法在心脏病有效预测中的研究

2021 2nd International Informatics and Software Engineering Conference (IISEC) Pub Date : 2021-12-16 DOI: 10.1109/iisec54230.2021.9672415

Rakibul Islam, Abhijith Reddy Beeravolu, Md. Al Habib Islam, Asif Karim, S. Azam, Sanzida Akter Mukti

{"title":"A Performance Based Study on Deep Learning Algorithms in the Efficient Prediction of Heart Disease","authors":"Rakibul Islam, Abhijith Reddy Beeravolu, Md. Al Habib Islam, Asif Karim, S. Azam, Sanzida Akter Mukti","doi":"10.1109/iisec54230.2021.9672415","DOIUrl":"https://doi.org/10.1109/iisec54230.2021.9672415","url":null,"abstract":"Heart disease is the leading cause of death worldwide, nearly accounting for one-third of deaths. Heart disease describes a range of conditions that affect your heart. Most of these symptoms are dependent on the type of heart disease and their risk factors, such as high blood pressure, high cholesterol, and smoking. It is important to control the conditions before they become severe, it can save countless lives. Especially in remote areas and underdeveloped countries where there's no access to necessary medical systems and medical experts at the right time. Therefore, it is important to develop a 'medical system’ that can provide heart disease assessments classifications from the clinical data, so that a clinician at a faraway location can reach a decision quickly, allowing them to manage a large number of patients. To do so, collecting clinical data related to heart disease is crucial. An open source dataset that consists of 1,190 samples and multi-variate features is collected from UCI machine learning repository. A total of 14 features are selected for this research. Data normalization is performed on these features to take care of irrelevant values, so that better results can be achieved by the trained models. This research uses three deep learning algorithms, namely Radial Basis Function Network (RBFN), Convolutional Neural network (CNN) and Artificial Neural Network (ANN) to train, validate, and test them with the selected, normalized, and separated data features. Various evaluation metrics were generated to understand the performance of the classification. This research has achieved classification scores of 98.24 % and 98.49% for RBFN and ANN, respectively. Overall, the CNN model has achieved higher accuracy than the other models, with 98.75 %.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115501687","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: 4