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Model-Driven Engineering for Embedded Systems with Non-Functional Properties Analysis Integration: A Review 16

Model-Driven Engineering for Embedded Systems with Non-Funct...

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16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Kadhim, Omar Jawad Nafea, Ahmed Adil Al-Thiabi, Mohamed Kareem Sallibi, Anas D. Modern Uuniversity for Business & Science Dept. Computer Science Beirut Lebanon College of Computer Science and Information Technology University of Anbar Dept. Artificail Inteligence Ramadi Iraq College of Computer Science and Information Technology University of Anbar Dept. Computer Science Ramadi Iraq College of Computer and Information Technology University of Anbar Department of Computer Sciences Ramadi Iraq

ISBN: (纸本)9798350381344

Model-Driven Engineering (MDE) has revolutionized the realm of embedded system development, providing an avenue for systematic, high-level system design, and automatic code generation. This paper delves into an enhanced approach to MDE, emphasizing the integration of nonfunctional properties analysis. Such an integration ensures that embedded systems not only perform their primary functions, but also adhere to crucial parameters like security, reliability, and efficiency. Through a comprehensive exploration of current tools and technologies, we identify gaps and opportunities in the current landscape. We further discuss the challenges inherent in marrying non-functional attributes with traditional system design and propose innovative solutions to navigate these complexities. Real-world case studies punctuate the discussion, offering tangible insights into the tangible benefits and practical challenges of this integrated approach. In conclusion, the seamless integration of nonfunctional properties into MDE emerges as a pivotal progression, heralding a new era of robust, efficient, and holistic embedded system development. © 2023 IEEE.

关键词： Embedded systems

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Tourist Place Classification Using Topic Modeling Algorithms 56

Tourist Place Classification Using Topic Modeling Algorithms

引用

56th International Carnahan Conference on Security technology, ICCST 2023

作者： Wadhe, Apeksha Arun Suratkar, Shraddha S. Vjti Mumbai Dept. of Computer Engineering & Information Technology 400019 India

ISBN: (纸本)9798350315875

Today social media is one of the most powerful and popular tool which is expanding rapidly in the world. Many tourism websites publish tourist places data for describing places in the form of Description. Over this data, Analysis can be performed and meaningful insights can be drawn. By analyzing this data we can find the subject or topic discussed in Description. By performing topic modeling over these data we can predict the category of tourist place. Also topic Modeling can help to cluster textual content into groups as per the subject of the text. In research study, Comparative analysis of topic modeling algorithms has been performed which will find a category of tourist places. Tourist place description blog data was gathered from tourism websites. Using tourist place Description dataset, comparative study of Topic modeling algorithms i.e. LDA Variational Inference(VI) algorithm and LDA Gibbs Sampling(GS) algorithm has been performed. Results of experiments has been analyzed with performance evaluation using various factors such as coherence score, perplexity, training execution time and accuracy percentage. LDA Gibbs Sampling(GS) algorithm outperforms LDA Variational Inference (VI) algorithm in terms of coherence score, perplexity, accuracy percentage. Whereas, LDA Variational Inference(VI) algorithm requires less execution time as compared to the LDA Gibbs Sampling(GS) algorithm © 2023 IEEE.

关键词： Websites

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Internet of Things(IoT) security: Approaches and existing solutions

Internet of Things(IoT) security: Approaches and existing so...

引用

2023 TRON Symposium, TRONSHOW 2023

作者： Upadhyay, Vatsala Vaish, Abhishek Kokila, J. Indian Institute of Information Technology Allahabad Dept. of Information Technology Prayagraj211015 India Indian Institute of Information Technology Trichy Dept. of Computer Science and Engineering Tiruchirappalli620012 India

ISBN: (纸本)9784893624093

The world has become dependent on using the Internet of Things(IoT) owing to its unique features - sensing the environment, acting upon the results obtained by sensors, connecting a network of devices for communication, and many more have made human lives simpler. Research done in the area of the Internet of Things(IoT) has revealed that these devices are vulnerable to physical and network attacks that can directly/indirectly result in the malfunctioning in the normal parameters of the devices, as well as cause important data loss or secret information being leaked which can become useful for the hackers to attack the device and tamper with the stored contents in the device. These problems pave the way for designing a robust, security mechanism for the Internet of Things(IoT). This paper shall present an overview of the security aspects of the Internet of Things(IoT) - starting with the attacks that can occur on this network, the survey done in this area, and towards the end, presenting some solutions for making the IoT secure and resilient to vulnerabilities. © 2023 TRON Forum.

关键词： Internet of things

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Integrating technology and Environmental Policy for Effective Air Quality Monitoring in Indonesia 3

Integrating Technology and Environmental Policy for Effectiv...

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3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Sanni, Mohammad Ifran Pramudya, Reza Dani Hery Jamaludin, Dieng Asep Sihotang, Sondang Visiana Hikam, Ihsan Nuril University of Raharja Dept. of Computer Systems Tangerang Indonesia Pandawan Sejahtera Indonesia Dept. of Information Technology Tangerang Indonesia Pelita Harapan University Dept. of Information Systems Tangerang Indonesia Bina Bangsa University Dept. of Information Technology Serang Indonesia Pandawan Sejahtera Indonesia Dept. of Digital Business Tangerang Indonesia

ISBN: (纸本)9798350367492

Air quality monitoring is crucial for protecting ecosystems and public health, especially in Indonesia, a country with unique geographical and socio-economic characteristics facing complex environmental challenges. This study examines the multifaceted interactions of various factors affecting Indonesia's air quality monitoring system, including industrial emissions, vehicular traffic, agricultural activities, and forest fires. Geographic factors like topography, wind patterns, and regional diversity significantly influence pollutant distribution and concentrations. Social and economic dimensions, such as rapid industrialization, urbanization, and population growth, also impact energy consumption patterns and air quality. This research employs a comprehensive methodological approach, combining literature review, data analysis, and the SmartPLS analytical model to understand these complexities. Data were collected from air monitoring agencies and scientific sources, focusing on variables such as industrial activity levels, traffic density, meteorological conditions, urbanization, and health impacts. The SmartPLS model was utilized to analyze complex cause- and-effect relationships between these variables. Results highlight significant variations in air quality across different regions and times, influenced by both environmental and human factors. Advanced sensor technologies and remote monitoring systems are identified as potential solutions to enhance monitoring coverage and accuracy, especially in remote areas. Collaboration between government, academia, and the private sector is emphasized as vital for developing a sustainable and effective air quality monitoring infrastructure. The study provides actionable recommendations for improving Indonesia's air quality monitoring system, aiming to foster a cleaner and healthier environment. Enhanced monitoring can help identify and mitigate air quality issues, ensuring better public health outcomes and environmental protec

关键词： Air quality

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Mobile Health Intervention System in Optimizing Healthcare Delivery for Cardiac Patients 5

Mobile Health Intervention System in Optimizing Healthcare D...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Prabashana, R.P.K. Nanayakkara, G.A.J.W. Wanniachchi, W.K.D.C. Arampath, S.B.A.M.B.S. Rajapaksha, Samantha Harshanath, S.M.B. Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350358131

The advent of mobile health (mHealth) technologies has ushered in a new era in healthcare delivery, transforming the way cardiac patients receive medical care and support. This research paper explores the role of a mobile health intervention system in optimizing healthcare delivery for cardiac patients. The prevalence of heart attacks has necessitated innovative solutions to enhance patient outcomes and reduce the burden on healthcare systems. The proposed mHealth intervention system leverages the ubiquity of mobile devices to provide real-time monitoring, personalized interventions with environment prediction, and seamless communication between patients and healthcare providers. Through a comprehensive review of existing literature and empirical studies, this paper examines the impact of the mHealth intervention system on patient engagement, adherence to treatment plans, early detection of cardiac events, and overall quality of care. The integration of wearable device, CardioCare mobile application, and telemedicine platforms creates a holistic approach to cardiac care, empowering patients to actively participate in their health management and enabling healthcare professionals to make informed decisions. The potential benefits, challenges, and ethical considerations surrounding the implementation of this system are discussed. © 2023 IEEE.

关键词： Wearable technology

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Programming Exercise System to Ascertain Students' Coding Status 11

Programming Exercise System to Ascertain Students' Coding St...

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11th International Conference on information and Education technology, ICIET 2023

作者： Tanaka, Tetsuo Ueda, Mari Kasuga, Hideo Matsumoto, Kazuonri Kanagawa Institute of Technology Faculy of Information Technolofy Dept. of Information and Computer Sciences Atsugi Japan Kanagawa Institute of Technology Faculy of Information Technolofy Dept. of Information Media Atsugi Japan

ISBN: (纸本)9781665465489

Teachers need to monitor students' progress in coding classes, which becomes difficult when there are many students. In this study, we developed a programming exercise support system that presents students' coding status to the teachers with the aim of improving lessons. This system provides a Web-based programming environment for students. The system accumulates the exercise numbers that students work on as operation logs, as well as the operations and results of editing, building, execution, and testing programs. In addition, it presents teachers with each student's progress, the source code creation process, and the occurrence of errors. This system consists of functions for students, instructors in charge of seminars and teaching assistants, and course chiefs. The system currently only focuses on C language. Approximately 230 students used this system for seven weeks on two subjects taught in class. The number of logs varied from day to day, thousands to over 100,000 logs were collected and accumulated per day. Based on user comments, we evaluated the system from five viewpoints of FURPS (Functionality, Usability, Reliability, Performance, Supportability). It was confirmed that the function of "ascertaining the student's coding status,"which is the purpose of this research, was achieved. Teachers can use the insights provided by our system to guide students in real time. © 2023 IEEE.

关键词： Students

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An Optimal Optimization of Software Development Cost Estimation Using Genetic Algorithm 4

An Optimal Optimization of Software Development Cost Estimat...

引用

4th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2024

作者： Amarif, Mabroukah Owaydat, Salha Sebha University of Libya Faculty of Information Technology Dept. of Information Systems Sebha Libya Sebha University of Libya Faculty of Sciences Dept. of Computer Sciences Sebha Libya

ISBN: (纸本)9798350372632

Estimating effort allows managers and software engineers to accurately anticipate, forecast, and quote schedule, budget, and manpower requirements. Determining estimated project cost, duration, and maintenance efforts well in advance Of the development stages is the biggest defiance to be attained for software projects. Formal models for cost estimation, such as the Constructive Cost Model (COCOMO) are limited by their inability to manage uncertainty in software projects early development cycle. This research presents an optimal optimization of software development cost estimation using genetic algorithm. It provides a fine solution to set the uncertain and ambiguous properties of software factors. It adopts COCOMO II model formulas and manages fine-tuning parameters for accurate effort and scheduled time software cost estimation. An experiment has been carried out using a NASA data set in order to improve the proposed algorithm. The experimental results show a significant optimization for both software effort up to 97.27% accuracy and scheduled time up to 98.88%. This research has emphasized that applying the genetic algorithm with fine-tuning parameters of COCOMO II model definitely improve the software development cost estimation. © 2024 IEEE.

关键词： Genetic algorithms

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information technology Risk Management Model for Remote Control Vehicles 14

Information Technology Risk Management Model for Remote Cont...

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14th International Conference on information and Knowledge technology, IKT 2023

作者： Naji, Hamid Reza Ayati, Aref Graduate University of Advanced Technology Dept. of Computer Engineering and Information Technology Kerman Iran

ISBN: (纸本)9798350349412

This paper presents a lightweight and quick IT risk management model for Remote Control Vehicles (RCVs). The increasing use of RCVs in many fields and the existence of different threats are the main reasons for having an efficient risk management method in this field. This paper will cover the information technology risks based on a continuous, iterative, and cyclic flow. This structure is adaptable to agile methods and decreases the chance of losing data, failing any equipment or system, and losing the reputation of the enterprise. Our risk management model is based on qualitative measures and can cover most IT-based risks in this area. © 2023 IEEE.

关键词： Drones

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Samarjini - Revolutionizing Household Cleaning with an Affordable IoT-Based Automatic Mopper 3

Samarjini - Revolutionizing Household Cleaning with an Affor...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Joshi, Siddharth Kate, Vandana Bhalerao, Shilpa Tripathi, Prasoon Sharma, Sudhanshu Acropolis Institute of Technology and Research Dept. of Computer Science and Information Technology Indore India

ISBN: (纸本)9798350343274

The title 'Samarjini' draws its inspiration from the Sanskrit word for a cleaning tool, and this research paper introduces the development of an automatic mopper machine designed to streamline household cleaning tasks while maintaining affordability. In a market filled with high-cost alternatives, this IoT-based device stands out by offering autonomous navigation, obstacle detection and avoidance, and effective floor cleaning at a lower price. The paper explores the machine's design, hardware and software components, evaluates its performance in various scenarios, and underscores its relevance in today's fast-paced lifestyles. Extensive experimentation was conducted to assess the machine's performance in diverse environments and scenarios. The outcomes affirm that 'Samarjini' excels in floor cleaning, adept.y avoiding obstacles and autonomously navigating through spaces. © 2023 IEEE.

关键词： Floors

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A Convolution Neural Network Based Classifier for Discerning AI Generated Images and Real Images 4

A Convolution Neural Network Based Classifier for Discerning...

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Kumar, Uppala Eswar Basava Vivekreddy, Chintakuntla Sujatha, Kamepalli Vignan's Foundation for Science Technology & Research Deemed to be University Dept. Information Technology & Computer Applications Guntur India

ISBN: (纸本)9798350354218

The exponential advancement of artificial intelligence (AI) has led to the creation of synthetic images that closely resemble real-world photographs. However, the widespread distribution of AI-generated content poses significant challenges in distinguishing between genuine and synthetic imagery, particularly in cybersecurity, content moderation, and image forensics. Traditional image classification methods struggle with this task due to the striking visual similarities between the two types of images. Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, leveraging their ability to extract complex features from raw pixel data. In this study, we propose an enhanced CNN methodology to differentiate between AI-generated and real images. Specifically, we focus on three popular CNN architectures: ResNet-50, RexNet-150, and RexNet-200. By augmenting these models with advanced architectural enhancements and training strategies, we aim to improve their discriminative capabilities. Our experimental findings reveal that RexNet-150 surpasses ResNet-50 and RexNet-200, achieving superior accuracy in distinguishing between AI-generated and real images. RexNet-150 attained an impressive 97.9% accuracy on the test dataset, outperforming ResNet-50 (93.1%) and RexNet-200 (90.3%). Moreover, RexNet-150 demonstrated enhanced training convergence and speed, indicating its effectiveness in learning discriminative features for image classification tasks. The superior performance of RexNet-150 holds significant implications for online safety, content moderation, and image authenticity detection. These advancements in CNN technology foster trust in digital imagery and enhance confidence in AI applications across diverse domains. © 2024 IEEE.

关键词： Convolutional neural networks

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