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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Ashraf, Abdulrahman Yousef, Ahmed Hassan Mahdi, Hani Ain Shams University Itworx Education Yas Holding Computer and Systems Engineering Department Egypt Egypt University of Informatics Ain Shams University Egypt Ain Shams University Computer and Systems Engineering Department Egypt

ISBN: (纸本)9798350378511

Migrating from Monolithic architecture to Microservices architecture is a major change in how applications are designed, developed, and managed. This paper introduces an innovative approach for Microservices identification. Advanced techniques, including the OpenAI ChatGPT API, BERT embeddings, and community detection algorithms, are used to analyze both the database and the source code to find the optimal service boundaries. Thorough evaluations on benchmark applications demonstrate that this proposed technique surpasses cutting-edge solutions in structural modularity and maintains favorable values for other software quality metrics. This aids in identifying scalable Microservices. This research not only supports the modernization of software infrastructure but also advocates for sustainable development practices within the ever-changing field of distributed systems. © 2024 IEEE.

关键词： Decentralized systems

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IoT Task Offloading in Edge Computing Using Non-Cooperative Game Theory for Healthcare Systems

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computer Modeling in engineering & Sciences 2024年第5期139卷 1487-1503页

作者： Dinesh Mavaluru Chettupally Anil Carie Ahmed I.Alutaibi Satish Anamalamudi Bayapa Reddy Narapureddy Murali Krishna Enduri Md Ezaz Ahmed School of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Computer Engineering SRM University APGunturIndia College of Computer and Information Sciences Majmaah UniversityAl Majma’ahSaudi Arabia Department of Public Health College of Applied Medical SciencesKing Khalid UniversityAbhaSaudi Arabia

In this paper,we present a comprehensive system model for Industrial Internet of Things(IIoT)networks empowered by Non-Orthogonal Multiple Access(NOMA)and Mobile Edge Computing(MEC)*** network comprises essential components such as base stations,edge servers,and numerous IIoT devices characterized by limited energy and computing *** central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy *** system operates in discrete time slots and employs a quasi-static approach,with a specific focus on the complexities of task partitioning and the management of constrained resources within the IIoT *** study makes valuable contributions to the field by enhancing the understanding of resourceefficient management and task allocation,particularly relevant in real-time industrial *** results indicate that our proposed algorithmsignificantly outperforms existing approaches,reducing queue backlog by 45.32% and 17.25% compared to SMRA and ACRA while achieving a 27.31% and 74.12% improvement in Qn ***,the algorithmeffectively balances complexity and network performance,as demonstratedwhen reducing the number of devices in each group(Ng)from 200 to 50,resulting in a 97.21% reduction in complexity with only a 7.35% increase in energy *** research offers a practical solution for optimizing IIoT networks in real-time industrial settings.

关键词： Internet of Things edge computing offloading NOMA

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IoT-Integrated Machine Learning for Real-Time Soil Nutrient Monitoring and Horticultural Crop Recommendations 10

IoT-Integrated Machine Learning for Real-Time Soil Nutrient ...

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10th IEEE Information Technology International Seminar, ITIS 2024

作者： Wahid, Abdul Parenreng, Jumadi Mabe Aswandi Alwi, Ananta Dwi Prayoga Zain, Satria Gunawan Setialeksana, Wirawan Universitas Negeri Makassar Informatics and Computer Engineering Department Makassar Indonesia Politeknik Negeri Lhokseumawe Network Engineering Technology Study Program Lhokseumawe Indonesia

ISBN: (纸本)9798331521295

Farmers and agricultural newcomers often rely on intuition for plant nutrient management, leading to inaccuracies. This study presents a real-time soil nutrient monitoring and plant recommendation system using IoT and machine learning. The prototype integrates an ESP32 microcontroller, NPK sensor, soil pH sensor, and DHT11 with an application and a machine learning model. The model employs a hard voting method combining random forest, LightGBM, and support vector machine algorithms, deployed via Flask API and hosted on Vercel. Testing showed the system effectively monitors soil nutrients in real-time, with a pH sensor error margin of ±0.51 and NPK sensor readings displaying a non-linear increase in levels. The hard voting method achieved 98.5% accuracy, with recommendation processing taking less than one second (371.17ms) and CPU usage at 7%. System performance depends on internet speed, while recommendation accuracy is influenced by temperature and humidity. This system offers a practical solution for precision agriculture by optimizing nutrient application and plant recommendations. © 2024 IEEE.

关键词： pH sensors

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SmartDetect: Safe Driving by Detecting Steering-Wheel Handling With a Single Smartwatch

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IEEE Sensors Journal 2024年第10期24卷 16325-16335页

作者： Mardi Putri, Rekyan Regasari Chang, Chin-Chun Putra, Aditya Fitri Hananta Pamungkas, Setyan Liang, Deron National Central University Department of Computer Science and Information Engineering Taoyuan City32001 Taiwan Brawijaya University Department of Informatics Engineering Malang65145 Indonesia National Taiwan Ocean University Department of Computer Science and Engineering Keelung City20224 Taiwan Astral Web Taipei City234-011 Taiwan Pahamify Bogor16128 Indonesia Nomura Research Institute Indonesia Jakarta10220 Indonesia

Holding the steering wheel with both hands is essential for safe driving. This article proposes a novel approach using only one off-the-shelf smartwatch to determine whether the driver is holding the steering wheel with both hands. Two classification models, namely, the individual and universal models, are proposed. An individual model focuses on a particular driver, while the universal model is applicable to all drivers. Both models extract vibration features from the watch's accelerometer signals using the Hilbert-Huang transform and classify the signal pattern by using support vector machines with a radial basis function kernel. Data samples were collected from 35 drivers. The universal model can achieve an accuracy of 98.51% for the hand on which a smartwatch is worn and 90.29% for the hand on which the smartwatch is not worn;the individual model achieves a higher accuracy of 99.21% for the hand on which a smartwatch is worn and 97.18% for the hand on which the smartwatch is not worn. © 2001-2012 IEEE.

关键词： Accelerometers

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A Novel Framework for Preserving Patient Health Record in IoT Healthcare 3

A Novel Framework for Preserving Patient Health Record in Io...

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3rd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2024

作者： Belgaum, Mohammad Riyaz Pothureddy, Priyanka Patnam, Sai Suraksha Gadda, Parimala Deepthi G. Pullaiah College of Engineering and Technology Department of Computer Science and Engineering Kurnool India Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia

ISBN: (纸本)9798350391565

As artificial intelligence, the Internet of Things (IoT), and next-generation mobile communication continue to evolve at a rapid pace, an increasingly popular application called the Internet of Medical Things (IoT) has arisen to provide ease and practicality in healthcare. Nonetheless, privacy preservation issues are brought up by accessing patient medical information inside the IoT framework, which calls for the creation of safe and private-preserving solutions. To address these issues, we provide in this study an IoT-Framework for preserving patient health record (FFPPHR) based on ELGamal blind signatures. We provide an enhanced privacy protection medical record searching technique (FFPPHR) based on the elliptic curve discrete logarithm problem (ECDLP) and point out security vulnerabilities in the current FFPPHR. Our security research shows that by utilizing the hard problem assumption of ECDLP, the FPMR guarantees identity privacy and accuracy. Furthermore, the use of Blind ECDSA Signatures improves data security. Performance assessments confirm the FFPPHR efficiency, and theoretical findings agree with simulations. The suggested FFPPHR approach yields lower time costs when compared to state-of-the-art techniques, which makes it a potential option for safe and effective medical record searches in IoT contexts. © 2024 IEEE.

关键词： Electronic health record

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Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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Assessing Predictor Influence in LSTM Models for Enhanced Solar Energy Forecasting 26

Assessing Predictor Influence in LSTM Models for Enhanced So...

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26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2024

作者： Ciobanu, Alexandru-Adrian Bacanin, Nebojsa Sanders, Tilman Stoean, Catalin University of Craiova Department of Computer Science Craiova Romania Singidunum University Faculty of Informatics and Computing Belgrade Serbia FH Muenster Department of Electrical Engineering and Computer Science Steinfurt Germany

ISBN: (纸本)9798331532833

Accurate forecasting of solar energy production is highly important for an adequate integration of renewable energy into the power grid. This study explores the importance of various predictors for enhancing the accuracy of solar energy forecasting using two distinct Long Short-Term Memory models: one that relies solely on historical power production data and past exogenous weather data, and another that additionally incorporates future exogenous weather data. Various settings are tried to improve the results and relatively similar parameters are used by both, yielding more accurate results for the model that also uses information from the future. The results also demonstrate that predictor importance varies significantly between the two models. These findings suggest that different models benefit from distinct predictor combinations and incorporating exogenous data can significantly enhance forecasting performance. © 2024 IEEE.

关键词： Prediction models

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Improving Information Delivery Effectiveness and Efficiency Using WebVR Technology 23

Improving Information Delivery Effectiveness and Efficiency ...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Pratama, Ardiyan Nur Akbar, Muhammad Aminul Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

In this digital era, attracting new students from outside the region to enter a college or university is difficult. This problem can be solved with good marketing and information dissemination techniques. Information is a type of data that has been processed and organized so that it has relevant meaning for the recipient. Useful information can be used to help make decisions, gain new knowledge, or solve problems. One medium for providing information is by using videos that can be uploaded to YouTube for dissemination. However, problems arise when the information depends on the point of view of the video content creator, who may not provide enough information sought by users in their videos. Virtual reality (VR) technology can be pursued as one of the solutions to overcome the lack of detail and control in videos for users to get the expected information. One of the technologies in VR that allows people to explore a three-dimensional virtual world on a web platform is the 360° WebVR technology. Since users have full control over what can be seen using WebVR, it is expected that this technology can assist users in getting deeper and detailed information related to their needs. This study aims to determine the effectiveness and efficiency of using YouTube videos and WebVR in distributing information and delivering detailed information to users. The results show that WebVR technology has the potential to provide greater control over more detailed information to users who use it, in contrast to traditional two-dimensional video playback technology. © 2023 ACM.

关键词： Virtual reality

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Variational Voxel Pseudo Image Tracking

Variational Voxel Pseudo Image Tracking

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Oleksiienko, Illia Nousi, Paraskevi Passalis, Nikolaos Tefas, Anastasios Iosifidis, Alexandros Digit Aarhus University Department of Electrical and Computer Engineering Denmark Aristotle University of Thessaloniki Department of Informatics Greece

ISBN: (纸本)9781665430654

Uncertainty estimation is an important task for critical problems, such as robotics and autonomous driving, because it allows creating statistically better perception models and signaling the model's certainty in its predictions to the decision method or a human supervisor. In this paper, we propose a Variational Neural Network-based version of a Voxel Pseudo Image Tracking (VPIT) method for 3D Single Object Tracking. The Variational Feature Generation Network of the proposed Variational VPIT computes features for target and search regions and the corresponding uncertainties, which are later combined using an uncertainty-aware cross-correlation module in one of two ways: by computing similarity between the corresponding uncertainties and adding it to the regular cross-correlation values, or by penalizing the uncertain feature channels to increase influence of the certain features. In experiments, we show that both methods improve tracking performance, while penalization of uncertain features provides the best uncertainty quality. © 2023 IEEE.

关键词： 3D Single Object Tracking Bayesian Neural Networks Machine Learning for Embedded Devices Point Cloud Uncertainty Estimation Variational Neural Networks

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Performance Analysis of 3D Rendering Method on Web-Based Augmented Reality Application Using WebGL and OpenGL Shading Language 23

Performance Analysis of 3D Rendering Method on Web-Based Aug...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Hamzaturrazak, Multohadi Jonemaro, Eriq Muhammad Adams Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

In recent years, web programming has increased to the extent where it is capable of rendering 3D objects on the web. Its rendering performance varied depending on where it ran and what library was used to render the objects. This study aims to investigate the rendering performance of several 3D renderer libraries that render 3D objects in an augmented reality application. WebGL is one of the APIs that uses the Javascript programming language to render 3D objects in web applications. To create augmented reality on the web, a JavaScript library called *** is needed, which allows developers to create augmented reality on the web without the need to use additional plugins. *** supports various types of augmented reality, i.e., bookmarks, images, and location-based types. It also allows developers to incorporate visual and audio effects into augmented reality. This study aims to investigate the rendering performance of WebGL raw shaders and GLSL shaders in an HTML-based augmented reality application. The results suggested that both WebGL and GLSL could render low-poly and medium-poly 3D objects well. However, according to the test, WebGL performance drops significantly when rendering high-polygon 3D objects. Nonetheless, the GLSL library could render the same high-poly 3D objects at a similar level with native library rendering performance. Thus, suggest GLSL shaders as the recommended library to render 3D objects on the web. © 2023 ACM.

关键词： Augmented reality

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