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Real-Time Vehicle Tracking Mobile Application for University Campus Mobility Aid

Real-Time Vehicle Tracking Mobile Application for University...

引用

International Conference on Electrical, Control and Instrumentation engineering (ICECIE)

作者： Nicole A. Respecia Angelie Bernadette J. Tuazon Maria Leonora C. Guico Jan Kevin A. Galicia Department of Electronics Computer and Communications Engineering Ateneo de Manila Univeristy Quezon City Philippines

ISBN: (数字)9798350380040

ISBN: (纸本)9798350380057

The campus e-jeep system is intended to provide a convenient means of transportation within the campus. However, the lack of accessible ride information-such as the current location of e-jeeps, estimated time of arrival (ETA), and passenger count-often results in an inconvenient and inefficient experience for passengers. This study aimed to develop a cross-platform mobile application to enhance campus mobility by visualizing critical ride information, including e-jeep locations, station ETAs, and the number of available seats. To assess the application's user-friendliness, a prototype was tested by riders, which allowed the researchers to refine the application with a focus on improving the e-jeep riding experience. The application utilizes a database of near real-time e-jeep information stored in Firebase. The prototype was designed using Figma, and the mobile application was developed using several key technologies: Visual Studio Code, Expo Go, React Native, Tailwind CSS, and Google Maps. The application demonstrated 100% accuracy with an average latency of 414.7365 ms. It was also found to be scalable, capable of accommodating 10 e-jeeps and 500 simultaneous users. Finally, installer files for both Android and iOS were built and made available for download.

关键词： Visualization Accuracy Databases Web services Prototypes Transportation Real-time systems Mobile applications Satellite images Testing

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Optimized Deep Networks for Indoor Position and Localization Based on IEEE P802.11az

Optimized Deep Networks for Indoor Position and Localization...

引用

International Conference on Advanced Technologies for communications, ATC

作者： Nguyen Nhat Tung Thien Huynh-The Quynh-Nhu Thi Tran Department of Computer and Communications Engineering Ho Chi Minh City University of Technology and Education Vietnam

ISBN: (数字)9798350353983

ISBN: (纸本)9798350353990

With the exponential growth of mobile devices and wireless networks, the IEEE 802.11az standard has emerged as a leading technology, offering distinct advantages in localization and positioning tasks compared to other wireless solutions. This standard boasts superior accuracy, enhanced scalability, robust security features, and reduced energy consumption. This research investigates localization and positioning through experimentation with simulated datasets based on the IEEE 802.11az standard. We propose a deep convolutional neural network (CNN) architecture for positioning and localization tasks. Specifically, we simulate a simplified three-dimensional (3D) map and generate a synthetic dataset of channel impulse response (CIR) fingerprints by leveraging the IEEE P802.11az standard. Our optimized network architecture then predicts the location of a station (STA) based on a subset of the fingerprints, enabling the precise prediction of the exact position within this virtual indoor environment. Simulation results demonstrate that our proposed architecture outperforms the baseline model, achieving up to 93.04% accuracy and 0.92 root mean square error (RMSE), compared with 86.68% accuracy and 1.63 RMSE of the baseline.

关键词： Location awareness Accuracy Scalability computer architecture Network architecture Convolutional neural networks Security Standards IEEE 802.11 Standard Synthetic data

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Sensing-Based Channel Estimation in 6G mmWave Ultra-Dense Networks

Sensing-Based Channel Estimation in 6G mmWave Ultra-Dense Ne...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jihoon Moon Byonghyo Shim Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

As a key enabler for 6th generation (6G) communications, millimeter-wave (mmWave) ultra-dense network (UDN) has been studied. To utilize beamforming technique in mmWave UDN, accurate channel information is needed. By exploiting the small coverage of a BS in UDN, we can obtain accurate channel information via sensing-based channel estimation. Using sensing images and deep learning technique, the proposed sensing-based channel estimation technique can accurately extract the positions of mobile devices as well as the positions and orientations of wireless entities influencing signal propagation. From simulations, we observe that the proposed scheme achieves more than 52% channel estimation accuracy gain over conventional schemes.

关键词： Wireless communication 6G mobile communication Wireless sensor networks Accuracy Channel estimation Cameras Mobile handsets Sensors Millimeter wave communication Ultra-dense networks

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AI Virtual Assistant for Online Laboratory Experiments Based on Multi-threshold Technique and Genetic Algorithm for Analyzing the Student's Mouse Interaction Activities 14

AI Virtual Assistant for Online Laboratory Experiments Based...

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14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022

作者： Elmesalawy, Mahmoud M. Abd El-Haleem, Ahmed M. Hamdy, Alaa Helwan University Faculty of Engineering Electronics and Communications Engineering Department Cairo Egypt Misr International University Faculty of Computer Science Cairo Egypt

ISBN: (纸本)9781665487719

There is a great interest in online learning systems, especially due to COVID-19 pandemic. However, there are a lot of limitations and challenges of online laboratory learning systems. This paper presents an efficient technique that provides an intelligent virtual tutor for online laboratory environment, as in engineering and science sectors. Based on the analysis of the student's mouse activities, the AI virtual Assistant or virtual tutor will automatically estimate the difficulties that the student stuck during conducting the steps of lab's experiment. Hence, the virtual tutor can assist the student, accordingly. The technique is based on multi-threshold that are used to discriminate different levels of difficulties. The values of these thresholds are estimated and optimized via the genetic algorithm. The experimental results show that discrimination between different student behaviors can be achieved accurately and efficiently. © 2022 IEEE.

关键词： Genetic algorithms

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Influence of Gender and Physical Constitution on the ISK-CC-HBC Modulation Scheme

Influence of Gender and Physical Constitution on the ISK-CC-...

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International Conference on Smart Systems and Technologies (SST)

作者： Luka Filipović Marijan Herceg Domagoj Bilandžija Jelena Šuljug Department of Communications Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

In this paper, the influence of the human body communication (HBC) channel conditions changes on Inductance Shift Keying (ISK-CC-HBC) is analyzed. In particular in ISK-CC-HBC, information is mapped by impedance change at the transmitter side through switching inductance between signal and ground electrode. To achieve maximum Euclidean distance between the constellation points, and consequently a low bit error rate (BER), correct inductance value is crucial. However, the state of the HBC channel varies depending on the person on which the communication takes place. Therefore, in this paper, the performance of the ISK-CC-HBC system was analyzed to determine the optimal inductance and BER for five persons of different ages and genders.

关键词： Inductance Transmitters Bit error rate Modulation Euclidean distance Switches Smart systems Robustness Permittivity IEEE Constitution

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computer Vision-Based Cell Association for mmWave/THz Ultra-Dense Networks

Computer Vision-Based Cell Association for mmWave/THz Ultra-...

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IEEE Conference on Vehicular Technology (VTC)

作者： Khoa Anh Ngo Jihoon Moon Byonghyo Shim Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Korea

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Ultra-dense networks (UDN) are anticipated to fulfill the high-performance demands for future applications of 5G and beyond communication networks. By exploiting recent advances in computer vision techniques, we propose a novel cell association technique, referred to as computer vision-based cell association (CV-CA), that circumvents the cumbersome CSI acquisition. The computer vision technique provides accurate 3D position and determines the line-of-sight communication link of all users within the UDN using RGB images. We demonstrate from the simulations that the proposed CV-CA outperforms 5G-NR and conventional cell association techniques in terms of total data rate.

关键词： computer vision Visualization Vehicular and wireless technologies Three-dimensional displays Line-of-sight propagation Rendering (computer graphics) Vectors

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Smart Contract-Based Blockchain for Delegation of Trustworthiness Between Intra-Communicating Vehicles in VANET

Smart Contract-Based Blockchain for Delegation of Trustworth...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Shawky, Mahmoud A. Abdellatif Ibrahim, Ahmed Gamal Ahmed, Mostafa M. Hadhouda, Mostafa Zahran, Shady Moussa, Mohamed Zaghlool, Ahmed S. Pervaiz, Haris Shah, Syed T. University of Glasgow GlasgowGI2 8QQ United Kingdom ADC Department of Electronics and Electrical Communications Engineering Alexandria Egypt University of Calgary Department of Geomatics Calgary Canada School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

ISBN: (纸本)9798350351408

The increasing complexity and connectivity of modern vehicular networks underscore the necessity for efficient authentication mechanisms to ensure secure and reliable communication among vehicles. This paper introduces a novel approach using smart contract-based blockchain technology for trust delegation among vehicles in VANETs. Addressing challenges in 5G-enabled vehicular networks, the proposed scheme aims to optimise authentication processes, reducing computation and communication costs while enhancing handover mechanisms. Through comprehensive analysis, the scheme's security robustness against potential active attacks is evaluated, demonstrating its effectiveness in reducing costs. The numerical analysis reveals a remarkable reduction of computation and communication costs by 66% and 81 %, respectively, showcasing the superior efficiency of the proposed smart contract-based blockchain solution compared to conventional authentication methods. © 2024 IEEE.

关键词： Authentication Protocol

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Convolutional Neural Network Based Deep Neural Network Model for Electrocardiogram Records Classification 7

Convolutional Neural Network Based Deep Neural Network Model...

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7th International Conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Khudhur, Ahmed Mahmood Alwan, Mohammed Hasan Al Omairi, Qayssar Mahmood, Omar Abdulkareem Hammadi, Yousif I Muthanna, Mohammed Saleh Ali Aziz, Ahmed Muthanna, Ammar Information Technology Department College Of Computer Science And Information Technology Kirkuk University Iraq Department Of Communications Engineering College Of Engineering University Of Diyala Baqubah32001 Iraq Department Of Computer Engineering College Of Engineering University Of Diyala Iraq Bilad Alrafidain University College Diyala32001 Iraq Institute Of Computer Technologies And Information Security Southern Federal University Taganrog344006 Russia Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan Department Of Telecommunication Networks And Data Transmission The Bonch Bruevich Saint Petersburg State University Of Telecommunications Russia Department Of Applied Probability And Informatics Peoples Friendship University Of Russia Russia

ISBN: (纸本)9798400709036

Cardiovascular diseases, also known as CVDs, currently rank as the primary incidence of mortality. The present approach for identifying illnesses involves the analysis of the Electrocardiogram (ECG), an electronic diagnostic device utilized to capture the rhythm of the heart. Regrettably, the process of seeking out specialists to conduct analysis on a substantial volume of electrocardiogram (ECG) data results in a significant depletion of medical capabilities. Hence, the utilization of deep learning algorithms for the identification of ECG characteristics has progressively gained prominence. Nevertheless, there exist certain limitations associated with these conventional approaches, which necessitate the need for manual characteristic identification, intricate models, and extensive training duration. This study presents a novel and effective approach for categorizing the five different types of heartbeats in the MIT-BIH Arrhythmia database. The proposed method involves the utilization of a 16-layer deep one-dimensional convolutional neural network, which exhibits both robustness and efficiency in its classification performance. Thus, the designed model is consisting of five-groups, first to fourth groups are the main feature extraction and mapping blocks, while the fifth group is fully connected and classification layers. The findings indicate that the model presented in this study has superior performance in terms of accuracy, precision, and F1-score. The proper classification of medical cases has a significant impact on the conservation of medical resources, hence positively influencing clinical practice. Additionally, the model training phase is characterized by its efficiency, since it does not significantly deplete resources. © 2023 ACM.

关键词： Electrocardiograms

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Microprocessor Interfacing: Bidirectional Motor, Automata Vehicular Locomotion Programmed with MATLAB and Arduino IDE

Microprocessor Interfacing: Bidirectional Motor, Automata Ve...

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2022 International Conference on Electronics and Renewable Systems, ICEARS 2022

作者： Abuan, Donabel Gaticales, Konstantin Dadios, Elmer P. Gokongwei College of Engineering Department of Electronics and Communications Engineering Manila Philippines Gokongwei College of Engineering Department of Computer Engineering Manila Philippines Gokongwei College of Engineering Department of Manufacturing Engineering and Management Manila Philippines

ISBN: (纸本)9781665484251

This paper intends to establish an automaton capable of serial communication and performing basic vehicular locomotion as means of enhancing applications over various fields not limited to: (1) uses in environments hazardous towards personnel, or (2) serve as a baseline for control systems acting as a safety net for correcting erroneous human input, like adjusting motor actuators when the user is recklessly driving. Using a programming block to provide instructions on the two motors, the automaton is test fitted with instructions to perform vehicular movement. © 2022 IEEE.

关键词： Control systems

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Highly Dispersive Fiber with Two Graded-Index Concentric Cores 21

Highly Dispersive Fiber with Two Graded-Index Concentric Cor...

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21st International Conference on Optical communications and Networks, ICOCN 2023

作者： Peng, Qinru Geng, Wenpu Zhao, Wenqian Liu, Yuanpeng Pan, Zhongqi Yue, Yang Xi'an Jiaotong University School of Information and Communications Engineering Xi'an China Institute of Modern Optics Nankai University Tianjin China University of Louisiana at Lafayette Department of Electrical & Computer Engineering Lafayette United States

A highly dispersive fiber with two graded-index concentric cores is proposed with -34948 ps /(nm · km) chromatic dispersion at 1480nm. The influence of structural and material parameters on dispersion of the fund... 详细信息

ISBN: (纸本)9798350343502

关键词： Chromatic dispersion

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