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International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Pisit Vanichchanunt Sirapop Saengthongkam Natthapong Waichampa Navy Wuttiananchai Pruk Sasithong Vitawat Sittakul Lunchakorn Wuttisittikulkij Sukritta Paripurana Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electronic Engineering Technology College of Industrial Technology King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

Designing, implementing, and testing a practical 5G use case usually consumes large amount of time, budget, and effort. To alleviate unexpected problems and also ensure the functionalities of a 5G project, this paper proposes the integration of 5G system and a virtual use case in metaverse for designing and pretesting by using open source software. This software-based approach in metaverse not only enhances the perspectives on the consideration for designing and testing but also escalates the project ready for 5G digital twin. A virtual smart warehouse is selected to demonstrate 5G use cases since it employs smart components/machines, such as Automated Guided Vehicles (AGVs) and autonomous forklifts, as well as uses various types of IoT devices including temperature sensors, humidity sensors, CCTV cameras, light detectors, and RFID cards. To enable such smart components and devices to function in metaverse, the 5G network slices are designed to support three types of IoT services including Broadband IoT, Critical IoT, and Massive IoT which require high data rate, low-latency, and massive connectivity respectively.

关键词： Temperature sensors 5G mobile communication Metaverse Robot vision systems Cameras Digital twins Internet of Things

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New In-Air Signature Datasets

New In-Air Signature Datasets

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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Alobaidi, Abdulazeez R. Dhieb, Thameur Nuimi, Zeina N. Hamdani, Tarek M. Wali, Ali Alimi, Adel M. University of Sfax REGIM-Lab.: REsearch Groups in Intelligent Machines Enis Tunisia Imam ja'Afar Al-Sadiq University Faculty of Information Technology Department of Computer Techniques Engineering Iraq Higher Institute of Business Administration University of Gafsa Tunisia College of Engineering Department of Electrical Engineering University of Misan Iraq Higher Institute of Computer Science Mahdia University of Monastir Tunisia Higher Institute of Computer Science and Multimedia of Sfax University of Sfax Tunisia University of Johannesburg Faculty of Engineering and the Built Environment Department of Electrical and Electronic Engineering Science South Africa

ISBN: (纸本)9798350335590

Compared to traditional biometric systems, in-air signatures are considered more robust and secure than classical pen paper. A few datasets capturing in-air signatures have been introduced, utilizing various devices such as the Leap Motion and the Microsoft Kinect sensor camera. However, these devices are not exempt from shortcomings and exhibit certain limitations. The expenses associated with their implementation and the requirement for technical proficiency in operating them present notable challenges for in-air signature analysis. Additionally, users may encounter difficulties in adapting their finger movements to fit within the device's limited field of view, particularly if they lack familiarity with these devices. To address these concerns, this paper proposes the creation of three in-air signature datasets using solely the camera of a laptop or a smartphone, eliminating the need for any additional specialized equipment. Our datasets were collected in three ways. The first is the In-Air Signature dataset (IAS dataset) and the second is the In-Air Signature dataset using a transparent Glass Plate (IASGP dataset) while the third is the In-Air Signature dataset using Smart Phone (IASSP dataset). Forty volunteers participated in the construction of these datasets. Their ages ranged from 21 to 40 years. Each volunteer signs in the air five signatures and imitates five signatures of five other volunteers. Our in-air signatures datasets are publicly available and can be used for various research tasks like in-air signature verification and identification. © 2023 IEEE.

关键词： Cameras

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Design and Implementation of 5G IoT for Retirement Village in Metaverse

Design and Implementation of 5G IoT for Retirement Village i...

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Research, Invention, and Innovation Congress (RI2C)

作者： Pisit Vanichchanunt Sirapop Saengthongkam Natthapong Waichampa Navy Wuttiananchai Bancha Janthong Khatathap Swatdipisal Vitawat Sittakul Lunchakorn Wuttisittikulkij Sukritta Paripurana Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electronic Engineering Technology College of Industrial Technology King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798331506018

ISBN: (纸本)9798331506025

This paper proposes the use of metaverse in the design, implementation, and pretest of 5G IoT systems for smart cities, in which this paper, a retirement village is selected as a preliminary example for the demonstration. Metaverse not only enables the system design and integration under multidisciplinary considerations including electrical system, solar energy system, 5G IoT system, communication, and automation, to be carried out economically but the system functionalities can also be carefully tested under various scenarios due to less limitation in the virtual world. The developed 5G IoT system for the retirement village monitors electrical power usage, solar power generation and consumption, air pollution, and environmental status. Moreover, the developed system also allows users to directly control lights and CCTV cameras using dashboards. To support various demands of such IoT services, the 5G network slice templates are designed and prepared according to the service requirements. In the system test, the monitoring data is shown on the dashboards to confirm the system connections and functionalities. Besides, wireless CCTV cameras via the developed 5G IoT systems are tested and compared between the virtual video in metaverse and the actual video from the real world. The results of both cases reveal no significant difference in terms of video quality degradation and latency. This shows the benefits and potentials of using metaverse in the design, implementation, and testing especially the system integration.

关键词： Workability Technological innovation 5G mobile communication Metaverse Smart cities System integration Cameras Internet of Things Retirement Monitoring

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Experimental results on FMCW radar based Human Recognition using only Doppler information

Experimental results on FMCW radar based Human Recognition u...

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International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Patipon Petchtone Denchai Worasawate Tiwat Pongthavornkamol Kazuhiko Fukawa Yuyuan Chang Department of Electrical Engineering Faculty of Engineering Kasetsart University Bangkok Thailand National Electronic and Computer Technology Center National Science and Technology Development Agency Pathum Thani Thailand School of Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The demand of indoor human identification systems that prioritize privacy has led to an increased interest in wireless sensing devices such as radar. Several studies have identified distinctive characteristics of human movement that cause Doppler signatures, which can be used for subject identification. Following them, this paper proposes an alternative machine learning approach for human identification, which uses only Doppler information from each subject by using FMCW radar. Experimental results in the two-subject scenarios show that the proposed method can achieve an accuracy of 96.2% (±1.1%) when data for both training and verification are obtained from the same scenarios, while an accuracy of 67.0% (±2.8 % ) can be achieved when data for the verification are obtained from different scenarios

关键词： Wireless communication Training Wireless sensor networks Privacy Accuracy Doppler radar Telecommunications

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Broadband Unidirectional Vivaldi Antenna for Radar Application

Broadband Unidirectional Vivaldi Antenna for Radar Applicati...

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International ECTI Northern Section Conference on Electrical, electronics, computer and Telecommunications engineering (ECTI-NCON)

作者： Pattawin Changnam Pisit Janpangngern Apichart Intarapanich Chanchai Thongsopa Nuchanart Santalunai Samran Santalunai School of Electronic Engineering Institute of Engineering Suranaree University of Technology Nakhon Ratchasima Thailand National Electronics and Computer Technology Center (NECTEC) National Science and Technology Development Agency (NSTDA) Thailand Department of Telecommunication Engineering Faculty of Engineering and Technology Rajamangala University of Technology Isan Nakhon Ratchasima Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This paper presents the design of a broadband Vivaldi antenna intended for radar systems operating across the 2-6 GHz frequency range. The antenna design employs an optimized corrugated Vivaldi antenna and a coaxial feed structure to ensure wideband performance. A 50-ohm N-type connector is integrated for efficient signal transmission between the antenna feed, transmitter, and receiver, minimizing reflection losses and enhancing overall system efficiency. Measurements show that the antenna achieves Half-Power Beamwidth (HPBW) values of 100° for the xz-plane and 80° for the yz-plane at 2.45 GHz, 80° for the xz-plane and 60° for the yz-plane at 3.5 GHz, and 80° for the xz-plane and 40° for the yz-plane at 5.5 GHz. Additionally, the antenna gains increase with frequency, reaching 6.60 dBi at 2.45 GHz, 8.34 dBi at 3.5 GHz, and 11.74 dBi at 5.5 GHz. The proposed Vivaldi antenna configuration is particularly suited for radar applications that require multi-band operation, facilitating the detection and tracking of various target sizes and distances. By covering a broad bandwidth, this design improves radar system performance, particularly in frequency-modulated continuous wave (FMCW) radar environments, enabling robust target detection in diverse operating conditions.

关键词： Antenna measurements Target tracking Vivaldi antennas Transmitting antennas Radar detection Directive antennas Radar antennas Broadband communication Frequency measurement Wideband

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A Low-power High-gain Inverter Stacking Amplifier with Rail-to-Rail Output 3

A Low-power High-gain Inverter Stacking Amplifier with Rail-...

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3rd IEEE International Conference on Design and Test of Integrated Micro and Nano-Systems, DTS 2021

作者： Shad, Erwin H. T. Moeinfard, Tania Molinas, Marta Ytterdal, Trond Faculty of Information Technology and Electrical Engineering Engineering Cybernetics Trondheim Norway York University Faculty of Electrical Engineering and Computer Science Toronto Canada Faculty of Information Technology and Electrical Engineering Electronic Systems Trondheim Norway

ISBN: (纸本)9780738132631

In this article, a rail-to-rail low-power amplifier is presented based on stacking inverter-based amplifiers. The output voltages of each inverter-based amplifier are converted to a current and then mirrored to the output so that a rail-to-rail output is achieved. Besides, extensive simulations have been carried out to show the effect of drain-source voltage on the intrinsic gain of a transistor. Based on these simulations, a minimum supply voltage is chosen to achieve high open-loop gain and low closed-loop gain error. All the simulations are carried out in a commercially available 0.18 μm CMOS technology. The proposed amplifier achieves 88 dB open-loop gain. It is exploited in a capacitively-coupled amplifier structure. The closed-loop gain is 40 dB in the bandwidth of 0.1 Hz to 10 kHz when the power consumption is 0.54 μW at a 1.2 V supply voltage. The total input-referred noise is 4.7 μVrms in the whole bandwidth. The proposed neural amplifier achieved 0.02 SEF in the bandwidth from 200 Hz to 10 kHz. The proposed amplifier achieved a rail-to-rail output swing while the SEF is among the best reported SEF in the literature. Besides, to show the robustness of the proposed structure in the presence of process and mismatch variation, 500 Monte Carlo simulations are carried out. The PSRR and CMRR mean values are 89 dB and 68 dB, respectively. Finally, the proposed neural amplifier area consumption is 0.03 mm2 without pads. © 2021 IEEE.

关键词： Bandwidth

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MetaCon: Revitalizing Internet Congestion Control with Meta-Reinforcement Learning

MetaCon: Revitalizing Internet Congestion Control with Meta-...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： He Bai Hui Li Jianming Que Minglong Zhang Peter Han Joo Chong Kalupahana Liyanage Kushan Sudheera Xinyuan Pei School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Fuyao University of Science and Technology Fuzhou China Department of Electrical and Computer Engineering Mississippi State University Starkville USA School of Engineering Computer and Mathematical Sciences Auckland University of Technology Auckland New Zealand Department of Electrical and Information Engineering Faculty of Engineering University of Ruhuna Sri Lanka

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Effective congestion control algorithms (CCAs) are crucial for the smooth operation of Internet communication infrastructure. CCAs adjust transmission rates based on congestion signals, optimizing resource utilization and user experience. However, existing studies, both rule-based and learning-based CCAs, often struggle with generalization and underperform when deployed in real-world environments. When applied to unseen network conditions, hand-crafted schemes or pre-trained models may experience significant performance degradation. To address this challenge, we propose MetaCon, a novel adaptive Internet congestion control approach based on meta-reinforcement learning. MetaCon leverages knowledge learned from prior scenarios to quickly adapt to new environments. Experimental results show that MetaCon outperforms existing algorithms by exhibiting superior generalization and achieving better transmission performance across a wide variety of network conditions.

关键词： Degradation Adaptation models Signal processing algorithms Signal processing User experience Acoustics Internet Resource management Speech processing

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Comparison of Algebraic Reconstruction Technique Methods and Generative Adversarial Network in Image Reconstruction of Magnetic Induction Tomography (MIT)

Comparison of Algebraic Reconstruction Technique Methods and...

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2021 International Conference on Biomedical engineering, ICoBE 2021

作者： Lubis, A.J. Nasir, N.F. Mohd Zakaria, Z. Jusoh, M. Azizan, M.M. Zakaria, M.Z. Kazim, M.N.F.M. Rahman, S. Faculty of Engineering and Computer Science Universitas Harapan Medan Medan Indonesia Computer Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Biomedical Electronic Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Universiti Malaysia Perlis Perlis Malaysia Department of Electrical and Electronic Department Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia Negeri Sembilan Malaysia Faculty of Mechanical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Mechatronic Engineering Program Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia

Magnetic induction tomography (MIT) is a technique used for imaging electromagnetic properties of objects using eddy current effects. The non-linear characteristics had led to more difficulties with its solution especially in dealing with low conductivity imaging materials such as biological tissues. Two methods that could be applied for MIT image processing which is the Generative Adversarial Network (GAN) and the Algebraic Reconstruction Technique (ART). ART is widely used in the industry due to its ability to improve the quality of the reconstructed image at a high scanning speed. GAN is an intelligent method which would be able to carry out the training process. In the GAN method, the MIT principle is used to find the optimum global conductivity distribution and it is described as a training process and later, reconstructed by a generator. The output is an approximate reconstruction of the distribution's internal conductivity image. Then, the results were compared with the previous traditional algorithm, namely the regularization algorithm of BPNN and Tikhonov Regularization method. It turned out that GAN had able to adjust the non-linear relationship between input and output. GAN was also able to solve non-linear problems that cannot be solved in the previous traditional algorithms, namely Back Propagation Neural Network (BPNN) and Tikhonov Regularization method. There are several other intelligent algorithms such as CNN (Convolution Neural Network) and K-NN (K-Nearest Neighbor), but such algorithms have not been able to produce the expected image quality. Thus, further study is still needed for the improvement of the image quality. The expected result in this study is the comparison of these two techniques, namely ART and GAN to get the best results on the image reconstruction using MIT. Thus, it is shown that GAN is a better candidate for this purpose. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Generative adversarial networks

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Multi-dimensional Resource Allocation in HAP-assisted UAV Wireless Networks for IoRT Data Collection

Multi-dimensional Resource Allocation in HAP-assisted UAV Wi...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Hui Zhao Xinran Zhang Weilong Chen Xiaobin Xu Li Wang Zheng Chang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science Beijing University of Posts and Telecommunications Beijing China Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, we propose a multi-dimensional resource allocation scheme for Internet of Remote Things (IoRT) data collection in a high altitude platform (HAP)-assisted unmanned aerial vehicle (UAV) network. Considering the quality of service (QoS) requirements of delay-sensitive IoRT data, we propose a UAV-HAP double relay data transmission mode to reduce the transmission delay for delay-sensitive data. Since the resources of the UAV are limited, we jointly optimize communications, computing and storage resources to maximize the utility of the considered system. Due to the high dimensionality of the solution space, we design a Twin Delayed Deep Deterministic policy gradient-based multi-dimensional resource allocation (TD3-MDRA) algorithm to find the optimal resource allocation strategy. Extensive simulation results are presented to demonstrate the superior performance of TD3-MDRA for IoRT data collection with delay and resource constraints.

关键词： Wireless networks Simulation Quality of service Data collection Autonomous aerial vehicles Delays Telecommunication computing Internet Resource management Relays

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Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

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