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9th International Conference on Cloud Computing and Internet of Things, CCIOT 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Thi, Luong Nguyen Lee, Seon-Woo Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Mathematics and Informatics Dalat University Dalat Viet Nam Faculty of Information Technology Dalat University Dalat Viet Nam Division of Software Hallym University Chuncheon Korea Republic of Department of Electronics and Telecommunications Dalat University Dalat Viet Nam

ISBN: (纸本)9798400717161

Recently, WiFi Fingerprinting-based indoor positioning systems have gained significant attention due to the low cost of infrastructure deployment. In the data collection process, a higher density of reference points may lead to better positioning results. However, it makes this process time-consuming and laborious. To solve this problem, this study applies and compares different interpolation methods to enrich the fingerprint database without increasing the cost of the collection process. To evaluate the performance of the chosen methods, five interpolation methods are implemented in a multi-condition WiFi Fingerprinting dataset. Moreover, to check the robustness of the methods, different numbers of reference points are considered when creating the new interpolated fingerprint databases. According to the results, inverse distance weighting (IDW) is the most suitable interpolation method with low complexity and stable performance. The IDW-based database achieves an average interpolation error of less than 6 dBm compared to the original database. When applying this interpolated database to perform positioning tasks, it helps reduce the collection cost by 30% with slightly lower positioning results compared to the original database. This work demonstrates the feasibility of using interpolation to ease the data collection process of WiFi Fingerprinting, especially in complex and big areas such as airports or hospitals. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wi-Fi

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Social Robots - Robotics and Toy Computing Minitrack 58

Social Robots - Robotics and Toy Computing Minitrack

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58th Hawaii International Conference on System Sciences, HICSS 2025

作者： Hung, Patrick C.K. Huang, Shih-Chia Peres, Sarajane Marques Lee, Ha-Eun Yoon, Young Faculty of Business and Information Technology Ontario Tech University Canada Department of Electronic Engineering National Taipei University of Technology Taiwan School of Arts Sciences and Humanities University of Sao Paulo Brazil Department of AI Immersive Content Hongik University Korea Republic of Department of Computer Engineering Hongik University Korea Republic of

ISBN: (纸本)9780998133188

This HICSS-58 mini-track aims to present novel and industrial solutions to challenging technical issues of Human-Robot Interaction (HRI) and compelling social robot use cases. In addition, this mini-track will share related practical experiences to benefit the reader and provide clear proof that social robots play an ever-increasing essential and critical role in supporting robotic and toy computing applications - a new cross-discipline research topic in computer science, decision science, management sciences, and information systems. This year, we also have a symposium on Social Robots and Smart Toys at HICSS-58, which is co-organized with MR Media Lab, Hongik University, Korea. © 2025 IEEE computer Society. All rights reserved.

关键词： Social robots

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Sliding Mode Control Based on Super Twisting Algorithm for Single-Stage On-Board Charger 17

Sliding Mode Control Based on Super Twisting Algorithm for S...

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17th IEEE International Conference on Compatibility, Power electronics and Power engineering, CPE-POWERENG 2023

作者： Guler, Naki Komurcugil, Hasan Bayhan, Sertac Vinnikov, Dmitri Blinov, Andrei Gazi University Technology Faculty Department of Electrical-Electronic Engineering Ankara Turkey Qatar Environment and Energy Research Institute Doha Qatar Eastern Mediterranean University Famagusta Department of Computer Engineering Via Mersin 10 Turkey Tallinn University of Technology Electrical Power Engineering and Mechatronics Department Tallinn Estonia

ISBN: (纸本)9798350300048

This paper presents a super-Twisting algorithm-based sliding mode control (STA-SMC) method for a single-stage on-board charger (OBC). Constant current (CC) and constant voltage (CV) charging modes are determined by a simple algorithm that works depending on the battery's state of charge (SOC) level. Based on the mode detection algorithm, a proportional-integral (PI) controller is used to generate the amplitude of the inductor current reference that is identical to the grid current's amplitude. The inductor current is controlled by the proposed STA-SMC method. Simulation studies are carried out through the MATLAB/Simulink environment. The results reveal that the proposed control method successfully regulates battery voltage or current and grid current under dynamic and steady-state conditions. Furthermore, the proposed method exhibits a smooth transition from CC to CV modes and vice versa. Also, the spectrums of grid current show that the total harmonic distortion in grid current is under the recognized limits by the standards. © 2023 IEEE.

关键词： Sliding mode control

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Bangla Text Summarization Analysis Using Machine Learning: An Extractive Approach 1

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2nd International Human engineering Symposium, HUMENS 2023

作者： Rahman, Mizanur Debnath, Sajib Rana, Masud Murad, Saydul Akbar Muzahid, Abu Jafar Md Rashid, Syed Zahidur Gafur, Abdul Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia Department of Computer Science and Engineering United International University Dhaka Bangladesh Information and Communication Engineering Noakhali Science and Technology University Noakhali Bangladesh Department of Electronic and Telecommunication Engineering International Islamic University Chittagong Chittagong Bangladesh

ISBN: (数字)9789819968909

ISBN: (纸本)9789819968893

A notable expansion of information in digital space provides quick access to these massive amounts of news, literature, and so on. Although maximum news is available in English, people are interested in reading in their language. Almost all Bangla newspapers now have their online version, so people prefer to read newspapers online. Without reading the whole news, it is not possible to obtain significant information and a summary from a news article. A news summary is a process of extracting the most significant information from a news article in a precise manner. In this case, we require an effective Bangla text summarizer tool to get insight from the news easily. Text summarizers use linguistic methods to generate and interpret text before uncovering natural concepts and phrases to represent the content by compressing the original text document into a shorter text that contains the most relevant information. Summarizing lengthy and important text by enforcing specific guidelines is a challenging task. Therefore, a method based on intelligent machine learning is widely anticipated in this content. This paper uses extractive automatic text summarization techniques to condense the source text into a shorter version by preserving the significant information of the original text. Here we have adopted two machine learning-based techniques (i.e., word2vec, and similarity matrix) and a rule-based technique (word count) for Bangla text summarization. The results show that the word2vec technique performs very well compared to the summary performed by other techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

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Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

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computers, Materials & Continua 2024年第9期80卷 4895-4916页

作者： Brij Bhooshan Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPuneMaharashtra411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Ronin Institute MontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)HomantinHong KongChina

Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape,necessitating the development of more sophisticated detection *** machine learning approaches to phishing detection have relied heavily on feature engineering and have often fallen short in adapting to the dynamically changing patterns of phishingUniformResource Locator(URLs).Addressing these challenge,we introduce a framework that integrates the sequential data processing strengths of a Recurrent Neural Network(RNN)with the hyperparameter optimization prowess of theWhale Optimization Algorithm(WOA).Ourmodel capitalizes on an extensive Kaggle dataset,featuring over 11,000 URLs,each delineated by 30 *** WOA’s hyperparameter optimization enhances the RNN’s performance,evidenced by a meticulous validation *** results,encapsulated in precision,recall,and F1-score metrics,surpass baseline models,achieving an overall accuracy of 92%.This study not only demonstrates the RNN’s proficiency in learning complex patterns but also underscores the WOA’s effectiveness in refining machine learning models for the critical task of phishing detection.

关键词： Phishing detection Recurrent Neural Network(RNN) Whale Optimization Algorithm(WOA) cybersecurity machine learning optimization

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Analyzing Land Cover and Land Use Changes Using Remote Sensing Techniques: A Temporal Analysis of Climate Change Detection with Google Earth Engine 22

Analyzing Land Cover and Land Use Changes Using Remote Sensi...

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22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023

作者： Afzal, Mozina Ali, Kamran Kasi, Mumraiz Khan Ur Rehman, Masood Khoshkholgh, Mohammad Ali Haq, Bushra Shah, Syed Ahmed Balochistan University of Information Technology Engineering and Management Sciences Quetta Pakistan Middlesex University Faculty of Science and Technology London United Kingdom Balochistan University of Information Technology Engineering and Management Sciences Department of Computer Science Quetta Pakistan University of Glasgow Department of Electronic Engineering Glasgow United Kingdom Lahore University of Management Sciences Lahore Pakistan

ISBN: (纸本)9798350381993

The detection of changes in land cover and land use (LCLU) is crucial for various geospatial applications, including urban development and environmental management. One vital aspect of LCLU research involves identifying modifications in impervious surface cover, which has significantly increased due to global economic growth and the rising urban population in many parts of the world. This investigation employs Landsat 9 OLI- 2/TIRS-2 imagery with a 30m spatial resolution to map structures in the Ziarat District of Pakistan, encompassing forests, water bodies, and barren land. It aims to detect changes in tree cover and canopy height. A time series of Landsat 9 OLI-2/TIRS-2 images were utilized to create change detection and land cover maps. The Analysis of Land Cover and Land Use (LCLU) for the Ziarat District was conducted using the GEE platform. The satellite images were classified into broad land cover classes, which include impervious surfaces, forest/tree cover, grassland/cropland, and water. The generated change detection map facilitates the identification of locations that have undergone modifications due to new constructions, offering valuable insights for the implementation of urban development policies and disaster management on a global scale. © 2023 IEEE.

关键词： Land use

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Distributed Robust Optimization Method for AC/MTDC Hybrid Power Systems with DC Network Cognizance

arXiv

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arXiv 2024年

作者： Li, Hai-Xiao Lekić, Aleksandra Faculty of Electrical Engineering Mathematics & Computer Science Delft University of Technology Delft Netherlands School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing China

AC/multi-terminal DC (MTDC) hybrid power systems have emerged as a solution for the large-scale and long-distance accommodation of power produced by renewable energy systems (RESs). To ensure the optimal operation of such hybrid power systems, this paper addresses three key issues: system operational flexibility, centralized communication limitations, and RES uncertainties. Accordingly, a specific AC/DC optimal power flow (OPF) model and a distributed robust optimization method are proposed. Firstly, we apply a set of linear approximation and convex relaxation techniques to formulate the mixed-integer convex AC/DC OPF model. This model incorporates the DC network-cognizant constraint and enables DC topology reconfiguration. Next, generalized Benders decomposition (GBD) is employed to provide distributed optimization. Enhanced approaches are incorporated into GBD to achieve parallel computation and asynchronous updating. Additionally, the extreme scenario method (ESM) is embedded into the AC/DC OPF model to provide robust decisions to hedge against RES uncertainties. ESM is further extended to align the GBD procedure. Numerical results are finally presented to validate the effectiveness of our proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Hybrid power

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Expanding Horizon: The Role of Reconfigurable Intelligent Surfaces in Enabling Massive Connectivity

Expanding Horizon: The Role of Reconfigurable Intelligent Su...

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2024 International Conference on Horizons of Information technology and engineering, HITE 2024

作者： Ayub, Muhammad Shoaib Adasme, Pablo Rodriguez, Demostenes Zegarra Saadi, Muhammad Shongwe, Thokozani Kanadilovna, Ainur Zhumadillayeva Universidad de Santiago de Chile Department of Electrical Engineering Santiago Chile Federal University of Lavras Brazil Department of Computer Science Lavras Brazil Nottingham Trent University Department of Computer Science United Kingdom University of Johannesburg Department of Electrical & Electronic Engineering Technology Johannesburg South Africa L. N. Gumilev Eurasian National University Faculty of Information Technology Astana Kazakhstan

ISBN: (纸本)9798331516055

This comprehensive article explores the integration of reconfigurable intelligent surfaces (RIS) with massive multiple input and multiple output (mMIMO) systems for future wireless networks, focusing on millimeter-wave (mmWave), beyond 5G (B5G), and sixth-generation (6G) technologies. It provides an in-depth understanding of the theoretical foundations of RIS and mMIMO, discussing their advantages, limitations, and unique capabilities in achieving massive connectivity. This article also highlights role of RIS in enhancing the performance of various wireless systems, including IoT, 5G, B5G, and 6G communications. The paper concludes by identifying open challenges and opportunities in RIS for massive connectivity, offering a roadmap for future research in this rapidly evolving field. © 2024 IEEE.

关键词： 5G mobile communication systems

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Distributed Robust Optimization Method for AC/MTDC Hybrid Power Systems with DC Network Cognizant

Distributed Robust Optimization Method for AC/MTDC Hybrid Po...

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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Haixiao Li Aleksandra Lekić Faculty of Electrical Engineering Mathematics & Computer Science Delft University of Technology Delft The Netherlands School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing China

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

AC/multi-terminal DC (MTDC) hybrid power systems have emerged as a solution for the large-scale and long-distance accommodation of power produced by renewable energy systems (RESs). To ensure the optimal operation of such hybrid power systems, this paper addresses three key issues: system operational flexibility, centralized communication limitations, and RES uncertainties. Accordingly, a specific AC/DC optimal power flow (OPF) model and a distributed robust optimization method are proposed. Firstly, we apply a set of linear approximation and convex relaxation techniques to formulate the mixed-integer convex AC/DC OPF model. This model incorporates the DC network-cognizant constraint, enabling DC topology reconfiguration. Next, generalized Benders decomposition (GBD) is employed to provide distributed optimization. Enhanced approaches are incorporated into GBD to achieve parallel computation and asynchronous updating. Additionally, the extreme scenario method (ESM) is embedded into the constructed AC/DC OPF model to provide robust decisions to hedge against RES uncertainties. ESM is further extended to align the GBD procedure. Numerical results are finally presented to validate the effectiveness of our proposed optimization method.

关键词： Renewable energy sources Uncertainty Network topology Computational modeling Optimization methods Linear approximation Hybrid power systems Topology Numerical models Load flow

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Simulation of IoT-based Pool Water Quality Monitoring System with Node-RED 13

Simulation of IoT-based Pool Water Quality Monitoring System...

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13th IEEE Global Conference on Consumer electronic, GCCE 2024

作者： Hang, Lim Wei Saon, Sharifah Mahamad, Abd Kadir Kadir, Herdawatie Binti Abdul Ahmadon, Mohd Anuaruddin Yamaguchi, Shingo Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Johor Batu Pahat Malaysia Universiti Teknologi Petronas Department of Computer and Information Sciences Perak Seri Iskandar Malaysia Yamaguchi University Graduate School of Sciences and Technology for Innovation Japan

ISBN: (纸本)9798350355079

In this study, we present a simulation-based approach to pool water quality monitoring, leveraging Internet of Things (IoT) technology using the Wokwi simulator. The main objective of this research is to ensure the hygiene and safety of swimming pools by monitoring key parameters which are temperature, pH, chlorine levels, and total dissolved solids (TDS). With Node-RED, real-time data received by the ESP32 within the Wokwi simulator is visualized, enabling users to assess the pool's condition at a glance. To enhance user awareness, proactive measures such as Telegram notifications and LED alerts are implemented to indicate deviations from predefined ranges. This research showcases the effectiveness of simulation-based solutions in maintaining optimal water quality standards and underscores the potential of IoT technologies in addressing challenges in aquatic environments. © 2024 IEEE.

关键词： IoT Monitoring system Node-RED Telegram Water quality

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