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electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Mohammed Eskander Alshaghdari Muhammad Herman Jamaluddin Ala'a Essam Sabrah Faculty of Electrical Technology and Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Computer Science and IT International University of Technology Twintech Sana'a Yemen

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

This research aims to develop a sophisticated floor evenness measurement system for the construction industry, addressing the subjectivity, inefficiency, and labour-intensive nature of current methodologies. A mobile robot application is engineered, integrating an ATmega328P micro controller, MPU6050 gyroscope sensor, and NodeMCU (ESP32) for real-time data visualization on a synchronized dashboard tailored for bricklayers. The MPU6050 sensor's dual functionality, combining acceleration and gyroscope capabilities within a single chip, enhances measurement precision. A complementary filter mitigates noise and drifts, ensuring accurate floor evenness assessment. Adhering to the Malaysian Standard Construction Industry Standard (CIS 7:2014), which specifies floor evenness should not exceed 3mm over 1.2m (0.143 to -0.143 degrees), the system enables continuous monitoring for compliance. Leveraging the Blynk platform, real-time data transmission to a live dashboard empowers prompt intervention in case of deviations. This research successfully creates an innovative mobile robot application for precise floor evenness measurement by amalgamating state-of-the-art sensor technologies with IoT frameworks, presenting an objective, efficient, and technologically empowered paradigm for quality assessment in the construction domain.

关键词： Accuracy Data visualization Manuals Robot sensing systems Real-time systems Gyroscopes Quality assessment Mobile robots Floors Standards

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SwarmFlowVR: A Virtual Reality User Interface for Multi-Robot Control

SwarmFlowVR: A Virtual Reality User Interface for Multi-Robo...

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Iberian Robotics Conference (ROBOT)

作者： Adam Pooley Alexandre Gomes De Siqueira Matthew Hale School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer & Information Science & Engineering University of Florida Gainesville FL USA

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Intuitive control of multi-robot systems is an important feature of many applications requiring operator input. Accordingly, this work proposes a virtual reality (VR) user interface for easy, intuitive teleoperation of a team of mobile robots using point-and-click waypoint commands. The robots considered in this work are 4-wheeled mobile robots, and the proposed VR user interface, called SwarmFlowVR, was developed in Unity and deployed on a Meta Oculus Quest VR headset. SwarmFlowVR presents options to issue single or multiple commands to one or several robots simultaneously without requiring operator line of sight to the robots. To evaluate the effectiveness of SwarmFlowVR, a user study was conducted with 20 individuals, self-reporting a variety of levels of prior experience with virtual reality and mobile robot control. Among other results, 95% of users reported that SwarmFlowVR enabled effective control of both individual robots and multiple robots simultaneously. Our results indicate that SwarmFlowVR presents a promising user interface for the intuitive teleoperation of multiple mobile robots, accessible even to users with no prior experience in VR and/or robotics.

关键词： Training Headphones Robot control Buildings Virtual reality User interfaces Mobile robots Multi-robot systems Robots Remote control

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Comparative Study of Machine Learning and Holt-Winters Exponential Smoothing Models for Prediction of CPI's Seasonal Data 2

Comparative Study of Machine Learning and Holt-Winters Expon...

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2nd International Conference on Software engineering and information technology, ICoSEIT 2024

作者： Afrah, Ashri Shabrina Sari, Nur Fitriyah Ayu Tunjung Utama, Shoffin Nahwa Holle, Khadijah Fahmi Hayati Lestandy, Merinda Sintiya, Endah Septa Rizdania Universitas Islam Negeri Maulana Malik Ibrahim Malang Department of Informatics Engineering Malang Indonesia Universitas Muhammadiyah Malang Department of Electrical Engineering Malang Indonesia State Polytechnic of Malang Information Technology Department Malang Indonesia University of Pgri Wiranegara Computer Science Department Pasuruan Indonesia

ISBN: (纸本)9798350317503

Inflation is one of the factors influencing price stability. Inflation affects people's purchasing power and impacts their decisions as economic actors. Consumer Price Index (CPI) is one of the factors used by economists to measure the inflation or deflation in a country. This research focuses on comparing the prediction results of the CPI for the Education Goods and Services using the Holt's Winters Exponential Smoothing and Machine Learning Methods, namely Long Short-Term Memory (LSTM), Extreme Learning Machine (ELM), Ridge, and Least Absolute Shrinkage and Selection Operator (LASSO). The data used is univariate data on the CPI for the Education Goods and Services in Malang City in 1996-2013, which was obtained from the publication of the Statistics Indonesia (BPS), entitled 'Malang City in Figures' which was published in 1997-2014. The results of this research show that the Ridge Method produces the smallest Mean Absolute Percentage Error (MAPE) value compared to other Machine Learning Methods and the Multiplicative Holt-Winters Exponential Smoothing Method, with MAPE= 2.10723%%. Machine Learning models that have been simulated have very good accuracy values, with MAPE values © 2024 IEEE.

关键词： Forecasting

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Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

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computer Modeling in engineering & sciences 2024年第2期138卷 1385-1403页

作者： Muhammad Farman Ali Akgül Mir Sajjad Hashemi Liliana Guran Amelia Bucur Institue of Mathematics Khwaja Fareed University of Enginnering and Information TechnologyRaheem Yar KhanPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Mathematics Art and Science FacultySiirt UniversitySiirt56100Turkey Department of Mathematics Mathematics Research CenterNear East UniversityNicosiaTurkey Department of Computer Engineering Biruni UniversityIstanbul34010Turkey Department of Hospitality Services Babes-Bolyai UniversityCluj-Napoca400174Romania Department of Pharmaceutical Sciences Vasile Goldi竤Western University of AradArad310025Romania Department of Mathematics and Informatics Faculty of SciencesLucian Blaga University of SibiuSibiu550012Romania Department of Electronics and Communication Engineering Saveetha School of EngineeringSIMATSChennaiTamilnaduIndia

New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model areidentified. The uniqueness and existence have been established. Themodel’sUlam-Hyers stability analysis has beenfound. In order to justify the theoretical results, numerical simulations are carried out for the presented methodin the range of fractional order to show the implications of fractional and fractal *** applied very effectivenumerical techniques to obtain the solutions of themodel and simulations. Also, we present conditions of existencefor a solution to the proposed epidemicmodel and to calculate the reproduction number in certain state conditionsof the analyzed dynamic system. COVID-19 fractional order model for the case of Wuhan, China, is offered foranalysis with simulations in order to determine the possible efficacy of Coronavirus disease transmission in theCommunity. For this reason, we employed the COVID-19 fractal fractional derivative model in the example ofWuhan, China, with the given beginning conditions. In conclusion, again the mathematical models with fractionaloperators can facilitate the improvement of decision-making for measures to be taken in the management of anepidemic situation.

关键词： COVID-19 model fractal-fractional operator Ulam-Hyers stability existence and uniqueness numerical simulation

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Semantic Segmentation Based Real-Time Traffic Monitoring via Res-UNet Classifier and Kalman Filter

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SN computer science 2025年第1期6卷 1-17页

作者： Qureshi, Asifa Mehmood Algarni, Asaad Aljuaid, Hanan Alatiyyah, Mohammed Hamad Alnowaiser, Khaled Jalal, Ahmad Department of Creative Technologies Air University E-9 Islamabad 44000 Pakistan Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha 91911 Saudi Arabia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computer Science College of Sciences and Humanities in Aflaj Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Department of Computer Engineering College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Computer Science Air University E-9 Islamabad 44000 Pakistan

In computer vision, accurate vehicle recognition and tracking is a challenging research topic. Manual surveillance systems are cumbersome, labor-intensive, and inefficient in today's congested traffic environment. Automated traffic monitoring systems are needed in today's world because they provide potential solutions to these issues. However, there are still some challenges in automating these systems which need to be addressed. One of the challenges is the extraction of foreground from a complex environment that only contains vehicles along with spatial and temporal information. In this paper, a semantic segmentation-based foreground extraction model is proposed to overcome these challenges. After segmentation, a blob detection technique is applied to detect each vehicle. To overcome the issue of vehicle-to-vehicle occlusion we extracted Harris corner points and computed the separation line based on the vehicle geometry coordinates. Furthermore, we introduce an ID assignment mechanism based on VGG-16 extracted features. Based on the detections, the number of cars is also counted for each frame. For tracking, we first applied Farneback optical flow algorithm to detect motion in vehicles. Only those vehicles were passed to the tracking algorithm in which motion was detected. To estimate each vehicle's location in succeeding image frames Kalman filter was implemented. A vehicle reidentification and ID recovery module are also proposed to enhance the tracking outcome. Vehicle trajectories based on vehicle location midpoint were also estimated. Extensive experiments are used to validate the proposed system and achieved a precision score of 0.965 and 0.931 over Roundabout and AU-AIR datasets for vehicle detection. However, for vehicle tracking the precision is 0.948 over the Roundabout dataset and 0.839 for the AU-AIR dataset. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blob detection Detection and tracking Kalman filter Occlusion handling Res-Unet Semantic segmentation

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Wideband Four-Element L-Shaped Notch-Patch MIMO Antenna for 5G NR Networks

Wideband Four-Element L-Shaped Notch-Patch MIMO Antenna for ...

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13th International electrical engineering Congress, iEECON 2025

作者： Musika, Chanwit Supreeyatitikul, Nathapat Thitimahatthanakusol, Phatsakul Konpang, Jessada Rajamangala University of Technology Krungthep Faculty of Science and Technology Department of Computer Science Bangkok10120 Thailand Rajamangala University of Technology Krungthep Faculty of Engineering Department of Electrical and Telecommunication Engineering Bangkok10120 Thailand Rajamangala University of Technology Isan Faculty of Engineering and Technology Department of Telecommunication Engineering Ratchasima Thailand

ISBN: (纸本)9798331543952

This work proposes simply wideband four-element L-shaped notch-patch (LNP) MIMO antenna for 5G new radio (NR) networks. The proposed LNP MIMO antenna comprised of four-port antenna elements. The single antenna scheme contained L-shaped with notch microstrip patch antenna and modified ground plane. The proposed LNP MIMO antenna at 4.5 GHz (center frequency) can be provided impedance bandwidth (IBW) of 64% (3.57 - 6.45 GHz). The LNP MIMO antenna has been evaluated the MIMO performance metrics, including transmission coefficient (isolation), envelop correlation coefficient (ECC), diversity gain (DG), and mean effective gain (MEG). The simulated results of the LNP MIMO antenna achieved isolation of 20 dB, ECC of below 0.005, DG of above 9.975 dB, and MEG of approximately -3 dB. All simulated results are in good satisfactory, rendering the proposed LNP MIMO antenna suitable for 5G applications. © 2025 IEEE.

关键词： Antenna grounds

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Automated Parking Management with Real-Time Image Processing and OCR

Automated Parking Management with Real-Time Image Processing...

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International Conference on electrical, computer and Communication engineering (ECCE)

作者： Md Abu Talha Sheikh Ishaque Riajul Karim Adil Mahmudul Hasan Saron Abdul Al Mahmud Riaz Shaikat Ahmed Al Shahriar Zishan Department of Electrical and Electronics Engineering (EEE) Faculty of Engineering (FE) American International University-Bangladesh (AIUB) Dhaka Bangladesh Department of Computer Science and Engineering (CSE) Faculty of Engineering (FE) Ahsanullah University of Science and Technology (AUST) Dhaka Bangladesh Department of Computer Science and Engineering (CSE) Faculty of Science & Technology (FST) American International University-Bangladesh (AIUB) Dhaka Bangladesh Faculty of Computing Engineering and Science Computer Science (CS) University of South Wales UK

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Efficient parking management is a significant challenge in urban areas due to increasing vehicle density and limited space availability. This paper presents an automated parking management system that integrates real-time image processing and Optical Character Recognition (OCR) to detect vacant parking spaces and identify vehicle number plates, including both Bengali and English formats. The system utilizes deep learning models to address challenges such as low lighting, unstructured parking layouts, and diverse number plate formats. It is designed with a robust backend infrastructure, enabling real-time updates and parking space reservations. Tested in both simulated and real-world environments, the system achieves a parking space detection accuracy of 95.6% and a number plate recognition accuracy of 92.3%, with an average response time of 2.4 seconds for updating parking availability. This system provides a scalable and efficient solution for improving urban parking management.

关键词： Space vehicles Deep learning Accuracy Layout Urban areas Lighting Automated parking Real-time systems Time factors License plate recognition

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An Analysis of Machine Learning Algorithms for Smart Healthcare Systems 1

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International Conference on Cyber Security, Privacy and Networking, ICSPN 2022

作者： Alduailij, Mai Mishra, Anupama Zamzami, Ikhlas Fuad Psannis, Konstantinos Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia Department of Computer Science and Engineering Himalayan School of Science and Technology Swami Rama Himalayan University Dehradun India Faculty of Business King Abdulaziz University Rabigh Saudi Arabia University of Macedonia Thessaloniki Greece

ISBN: (数字)9783031220180

ISBN: (纸本)9783031220173

The epidemic taught us to keep digital health records. It also showed us how wearable observing gear, video conferences, and AI-powered chatbots may give good treatment remotely. Real-time data from health care devices across the globe helped attack and track the infection. Biomedical imaging, sensors, and machine learning have improved health in recent years. Medical care and biomedical sciences are now information science sectors that demand enhanced data mining approaches. Biomedical data have high dimensionality, class irregularity, and few tests. AI uses information and computations to imitate how people learn, continually improving its accuracy. ML is an important part of information science. Calculations utilising measurable methods reveal essential information about information mining operations. This paper explains and compares ML algorithms that can detect diseases sooner. We summarise ML’s algorithms and processes to extract information for a data-driven society. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Two-step Thompson Sampling for Multi-Armed Bandit Problem

Two-step Thompson Sampling for Multi-Armed Bandit Problem

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第43届中国控制会议

作者： Zhigang Shang Lifang Yang Mengmeng Li School of Electrical and Information Engineering Zhengzhou University Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

An important feature of sequential decision-making under uncertain conditions is to strike a balance between exploration(obtaining information about the value of actions) and utilization(selecting the best action based on existing knowledge). The multi-armed bandit is a classic task for balancing their relationship. As the agent has learnt the relationship between two options in a 2-armed bandit task,it will no longer explore but instead use them directly. Inspired by the research, an algorithm based on two-step Thompson sampling(T-TS)is proposed to solve multi-armed bandit problem. First, posterior Beta distributions for the reward of each arm and the probability of the superior arm were established respectively. In the first-step TS, Thompson sampling was used to extract the maximum value from the posterior distribution of probability for the superior arm, determining it as the selected arm. In the two-step TS, Thompson sampling was used to sample from the distributions of the reward. During the updating, the posterior distribution of the probability for the superior arm was updated based on observations including actions and reward, and the distribution of the reward was updated based on the reward feedback. We performed the comparative experiments to solve the static multi-bandit tasks with 10, 20, 40, and 80 arms respectively by the state-of-the-art B-UCB algorithm, Thompson sampling and the proposed T-TS. The results shown that our proposed T-TS can learn the superior action more quickly with the best robustness.

关键词： Thompson sampling multi-armed bandit Beta distribution cumulative regret cumulative reward

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A Semi-Supervised Learning Approach for Fault Detection and Diagnosis in Complex Mechanical Systems 19

A Semi-Supervised Learning Approach for Fault Detection and ...

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19th IEEE International Conference on Automation science and engineering, CASE 2023

作者： Askari, Bahman Cavone, Graziana Carli, Raffaele Grall, Antoine Dotoli, Mariagrazia The Department of Electrical and Information Engineering The Polytechnic of Bari Italy The Department of Civil Computer Science and Aeronautical Technologies Engineering The University Roma Tre Italy The LIST3N-LM2S University of Technology of Troyes France

ISBN: (纸本)9798350320695

The integration of artificial intelligence in mechanical fault detection and diagnosis (FDD) helps to increase reliability, reduce costs, and improve the overall performance of mechanical systems in Industry 4.0 applications. Most interesting industrial applications nowadays come from dynamic environments where data are generated continuously over time and where the labeled data are scarce and expensive. Therefore, semi-supervised learning (SSL) can be particularly useful in FDD because faults may be rare or difficult to identify, and may not be fully represented in the labeled data. By using a combination of labeled and unlabeled data, SSL can help to identify these rare or difficult-to-detect faults, leading to more effective FDD. In this paper, graph-based SSL relying on label propagation is combined with conventional classification algorithms to detect potential failures in complex mechanical systems. Experimental results on realistic pneumatic and hydraulic systems from the related literature show that the proposed method can effectively enlarge the labeled datasets and interestingly identify different types of non-nominal conditions with higher accuracy compared to baseline methodologies. © 2023 IEEE.

关键词： Graphic methods

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