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A review on the Challenges and Prospects in Harnessing Virtual Reality in Education

A review on the Challenges and Prospects in Harnessing Virtu...

引用

2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Adetunla, Adedotun Akinlabi, Esther Jen, Tien Chien Okokpujie, Imhade P. Ajibade, Samuel-Soma University of Johannesburg Dept. of Mechanical Engineering Science South Africa Northumbria University Dept. of Mechanical & Construction Engineering Newcastle United Kingdom Afe Babalola University Dept. of Mechanical & Mechatronics Engineering Ado Nigeria Sunway University School of Engineering & Technology Dept. of Computing & Information Systems Malaysia

ISBN: (纸本)9798350358155

Virtual Reality (VR) has emerged as a revolutionary technology with immense potential in transforming the landscape of education. This manuscript explores the integration of VR into educational settings, examining its benefits, challenges, and the promising future it holds in enhancing teaching and learning experiences across various disciplines. The result of this study shows that the existing literature showcases the diverse applications of VR, ranging from immersive simulations in medical training to enhancing language acquisition and making science, technology, engineering and mathematics (STEM) subjects more accessible. As educators and researchers continue to explore the possibilities offered by virtual reality, it is evident that this technology has the potential to redefine traditional educational paradigms. The emphasis on creating inclusive, interactive, and dynamic learning environments through VR not only caters to diverse learning styles but also addresses the ever-evolving needs of modern education. As this field evolves, ongoing research endeavors will undoubtedly uncover new insights, refine existing applications, and contribute to the continual improvement of educational methodologies in the digital age. © 2024 IEEE.

关键词： Virtual environments

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Enhancing Communication through Speech to Sign Language Converter 2

Enhancing Communication through Speech to Sign Language Conv...

引用

2nd IEEE North Karnataka Subsection Flagship International Conference, NKCon 2023

作者： Gayana, M.N. Rumaiz, Mohammed Hussain, Shaz Rasheed Shravya, A. Acharya, Shreenath Parveen, Sana Systems St Joseph Engineering College Dept. of Intelligent Computing & Business Mangaluru India St Joseph Engineering College Dept. of Computer Science and Engineering Mangaluru India

ISBN: (纸本)9798350314045

There are millions of people suffering from speaking and hearing disabilities. Sign language is the only way to communicate for such people to convey their message. The advancement in technology has highly impacted this section of society, hence there is a need to deal with them. This paper describes the Application, "Speech to Sign Language Converter"for communicating with people having hearing and speaking impairments. The primary function of the Application is to convert input sentences into Indian Sign Language (ISL) actions in real time. It takes input in the form of speech or text and produces corresponding sign language using an Avatar which acts based on SiGML code. It can also be used to convert PDF based texts into sign language. In addition, the users can learn Indian Sign Language (ISL) using the tutorials provided within it. The application focuses mainly on converting local languages such as Kannada into ISL. © 2023 IEEE.

关键词： Audition

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Dual-Polarized Reflectarray for Coverage-Enhancing Applications in sub-THz 6G Networks

Dual-Polarized Reflectarray for Coverage-Enhancing Applicati...

引用

URSI Atlantic Radio Science Conference (URSI AT-RASC)

作者： Alejandro Feito-Rojo Jesús Palací Eduardo Martinez-de-Rioja Ana Arboleya Dept. of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Madrid Spain

ISBN: (数字)9789463968102

ISBN: (纸本)9798350360257

This contribution presents the design and simulation results of a dual-polarized reflectarray antenna for coverage-enhancing applications in sub-THz 6G communication networks. A 68 mm x 68 mm reflectarray panel, comprising a planar array of 40 x 40 cells, has been designed to produce two independent beams in orthogonal linear polarizations at 100 GHz, in order to cover two different regions of mobile users. The beams have been broadened by the application of a beamforming technique to cover a wider angular region. The proposed design procedure can be applied to design passive reflectarrays for operation as base station antennas or reflecting intelligent surfaces, capable of improving wireless coverage in future sub-THz 6G systems.

关键词： 6G mobile communication Wireless communication Antenna measurements Base stations Array signal processing Simulation Planar arrays

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Forecasting Air Pollution of Urban Chennai Localities using Artificial Intelligence 3

Forecasting Air Pollution of Urban Chennai Localities using ...

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3rd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Faiz, Rayaan Agarwal, Tisha Rajeswari, D. Srm Institute of Science and Technology School of Computing College of Engineering and Technology Dept. of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798350375190

India's air quality deteriorated significantly in 2023, ranking third worst globally, highlighting the urgency for effective monitoring and mitigation measures. To comprehend past trends and predict future patterns, historical air pollution data from seven urban areas in Chennai was analyzed using the XGBoost Algorithm. This study aims to gain insights into Chennai's air quality, identify abnormalities, and issue timely warnings to the public and governing authorities. XGBoost was employed to forecast AQI, NO2, PM2.5, NOx, PM10, CO, SO2, NH3, and Ozone levels, outperforming traditional LSTM, Prophet, and ARIMA models. Evaluation using RMSE and MAE scores revealed XGBoost's efficacy, with scores of 20.65 and 14.35, respectively. The research highlights regions like Alandur, Arumbakkam, and Manali with notable concentrations of contaminants, emphasizing the need for immediate action. These findings highlight the significance of utilizing advanced algorithms for accurate air quality forecasting and proactive pollution management. © 2024 IEEE.

关键词： Air quality

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Cirrhosis Prediction in Chronic Liver Disease Patients Using Machine Learning Techniques 3

Cirrhosis Prediction in Chronic Liver Disease Patients Using...

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3rd International Conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Athish, V.P. Sree Nandha, S.S. Rajeswari, D. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Dept. of Data Science and Business Systems Tamilnadu Kattankulathur603203 India

ISBN: (纸本)9798350322842

Liver failure is a serious medical condition that can have life-threatening consequences. The liver is responsible for filtering blood and performing many other important functions. With the rise of machine learning in healthcare, there is an opportunity to use past datasets to predict liver failure early on. The main focus of this research work is to explore the application of supervised machine learning algorithms in predicting liver failure. The study involved pre-processing techniques such as univariate and bivariate analysis, and data visualization to gain better insights into the features of the dataset. Using these techniques, a multi-class classification model was built with machine learning algorithms, and the performance metrics of accuracy, F1 score, and recall were used to compare the algorithms. The results show that machine learning algorithms can accurately predict liver failure and can be an effective tool in healthcare. This study demonstrates the potential of machine learning in predicting liver failure and can contribute to the development of future models in the field. The results of this research study indicates that the proposed algorithm achieved an accuracy of 94.48%. The proposed work will be beneficial to researchers in this field and inspire them to build more advanced and accurate models. © 2023 IEEE.

关键词： Support vector machines

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Transient stability improvement of Croatian power system using FACTS 11

Transient stability improvement of Croatian power system usi...

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11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022

作者： Šešok, Anica Pavić, Ivica University of Zagreb Faculty of Electrical Engineering and Computing Dept. of Energy and Power Systems Zagreb Croatia

ISBN: (纸本)9798350399660

In the last twenty years, the share of renewable energy sources (RES) in total electricity production has increased significantly, which has led to certain problems in power system operation. In systems with a significant share of RES, connected to the transmission network via power electronics devices, the inertial response of the system is reduced. Due to the reduced inertia of the power system, synchronous generators are more sensitive to their disturbed states and as a result, can easily lose stability. Loss of stability of one generator can lead to failure of other system elements, which may ultimately result in partial or even complete breakdown of the power system. Recently, a large increase in production from renewable sources has been recorded in the Croatian power system, therefore this paper investigates their impact on the system's transient stability and the possibilities of its improvement using Flexible AC Transmission systems (FACTS). © 2022 IEEE.

关键词： Flexible AC transmission systems

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A Comparative Study of Hough Transform and PCA for Bolt Orientation Detection 22

A Comparative Study of Hough Transform and PCA for Bolt Orie...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Gambale, Antonio Coleman, Sonya Kerr, Dermot Vance, Philip Kerr, Emmett Fermuller, Cornelia Aloimonos, Yiannis School of Computing Engineering & Intelligent Systems Ulster University Londonderry United Kingdom Dept. of Electronic & Mechanical Engineering Atlantic Technological University Letterkenny Ireland Institute for Advanced Computer Studies University of Maryland United States

ISBN: (纸本)9798331527471

In the fields of manufacturing and robotics, accurately determining the orientation of manufacturing components, such as bolts, is a critical yet challenging problem due to the limitations of existing detection methods. This study introduces a novel methodology for addressing this issue, leveraging traditional computer vision techniques, by proposing a streamlined approach that exploits the inherent geometric properties of bolts for orientation detection. Two methods are presented to ascertain the initial axis angle of the bolt: the Progressive Probabilistic Hough Transform (PPHT) and Principal Component Analysis (PCA). These methods are used in conjunction with a novel tip direction detection approach. The results of the study demonstrate consistent accuracy in angle determination, with PPHT and PCA both achieving angular deviations below ±0.5◦ in the simple dataset, and PCA showing enhanced robustness in the dataset degraded by shadows, with a maximum error under ±1.5◦. This research not only reaffirms the viability of fundamental computer vision techniques in modern robotic applications but also sets a precedent for simple, generalisable, and reliable orientation detection solutions. These methods effectively bridge the gap between highly specialised machine learning systems, which often require tailored, complex models and extensive training data, and more universally applicable, straightforward approaches. © 2024 IEEE.

关键词： Bolts

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An Intelligent Battery Management System for an Electric Vehicle Powered by Solar PV Array 59

An Intelligent Battery Management System for an Electric Veh...

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59th International Universities Power engineering Conference, UPEC 2024

作者： Challoob, Ali Falih Bin Rahmat, Nur Azzammudin Ramachandaramurthy, Vigna K. Saeed, Nagham Humaidi, Amjad Jaleel Institute of Power Engineering Universiti Tenaga Nasional Strategic Planning Centre Malaysia School of Computing and Engineering University of West London London United Kingdom University of Technology Control and Systems Eng. Dept. Baghdad Iraq

ISBN: (纸本)9798350379730

Implementing a Battery Management System (BMS) in Electric Vehicles (EVs) offers several benefits that enhance the efficiency, security, and durability of the vehicle's battery system. The BMS oversees and controls the performance of each cell in the battery pack, guaranteeing that they function within predetermined voltage and temperature thresholds to maintain safety. In this paper, an intelligent BMS for an EV model powered by a solar PV array was proposed using a fuzzy logic (FL) controller. The proposed method was applied to EVs consisting of four Lithium-ion batteries. The simulation results are achieved using MATLAB/Simulink software. The estimation of the state of charge (SOC) for each battery was used as input to the FL which controls the discharging/ charging mode for each battery via power semiconductor switches. Three different scenarios are used to verify the suggested method. A full control FL operation was obtained, and the batteries were protected successfully against overcharging and over-discharging. © 2024 IEEE.

关键词： MATLAB

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An Image Analysis-Based Automated Method using Deep Learning for Grain Counting 17

An Image Analysis-Based Automated Method using Deep Learning...

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17th IEEE International Conference on Industrial and Information systems, ICIIS 2023

作者： Ajikaran, Ramesh Hewarathna, Ashen Iranga Palanisamy, Vigneshwaran Joseph, Charles Thuseethan, Selvarajah Sabaragamuwa University of Sri Lanka Dept. of Computing and Infromation Systems Sri Lanka Sabaragamuwa University of Sri Lanka Dept. of Software Engineering Sri Lanka Fau Dept. of Computer Science Germany School of Information Technology Deakin University Australia

ISBN: (纸本)9798350323634

In the process of quality analysis of grains, number counting is one of the key steps for agricultural production. Traditional manual grain counting methods are time-consuming and subject to human error, and automated methods have the potential to improve accuracy and save time. In this study, we aimed to develop an image analysis-based method to automatically quantify the number of grains in a quicker manner. The 576 grain images were collected manually, and labelImg tagging tool used to annotate to generate a text file with their respective positions by drawing bounding boxes manually. The datasets consist were separated into three groups: training, validation, and test. For object detection, the YOLOv5, YOLOv4, and YOLOv3 algorithms represent cutting-edge deep learning frameworks. They replace the tedious and error-prone manual counting process by precisely identifying and counting grains in images obtained from agricultural fields. This technique helps to increase grain counting's precision and effectiveness. We believe this method will be extremely beneficial in guiding the development of high throughput systems for counting the number of grains in other crops as it performs well with a wide range of backgrounds, picture sizes, grain sizes, as well as various quantities of grain crowding. When compared to the other two approaches, YOLOv4 performed well in terms of accuracy, speed, and robustness (97.65%), demonstrating that the suggested strategy is competitive with other cutting-edge deep networkst. © 2023 IEEE.

关键词： Grain (agricultural product)

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Visual Field Prediction for Fundus Image with Generative AI 18

Visual Field Prediction for Fundus Image with Generative AI

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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Kang, Honggu Ko, Seonghyeon Kim, Juchan Le, Duc-Tai Bum, Junghyun Han, Jongchul Choo, Hyunseung Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Sungkyun AI Research Institute Sungkyunkwan University Suwon Korea Republic of Dept. of Ophthalmology Samsung Medical Center Seoul Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798350331011

Accurate diagnosis of glaucoma is crucial due to its high risk of blindness, but the long examination time often undermines the reliability of results by examinee's subjective factors. We propose a method to reduce examination time by generating static perimetry results with Conventional Fundus Images (CFIs) utilizing the CFI2GM technique, which leverages multimodal data. Based on data from 3,306 glaucoma patients at Samsung Medical Center in Seoul, we conducted ophthalmic image translation utilizing the Pix2Pix model. Our method, combining cGAN, L1, and SSIM loss, achieved MSE 57.9886 and PSNR 30.6057 dB. Furthermore, we received positive feedback from ophthalmologist regarding the high practical applicability of the images generated by our method. This indicates that CFI2GM can enhance the reliability of glaucoma examination results as well as reduce testing time. © 2024 IEEE.

关键词： Diagnosis

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