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2022 Advances in Science and engineering Technology International Conferences, ASET 2022

作者： Mohamed Gad, Omar Mohamed Saleh, Suhaib Ziad Mohammad Bulbul, Maleck Ayman Khadraoui, Sofiane University of Sharjah College of Engineering Department of Electrical Engineering Sharjah United Arab Emirates University of Sharjah College of Computing and Informatics Department of Computer Engineering Sharjah United Arab Emirates

ISBN: (纸本)9781665418010

Two wheeled self-balancing robots can achieve better mobility and rotation in confined spaces and narrow gaps compared to multi-wheeled robots while maintaining balance. The paper aims mainly to design, model and control Two-wheeled Self-balancing Robot (TWSBR) utilizing MATLAB and Arduino IDE. The mathematical modeling to derive the transfer functions of TWSBR is performed using Lagrange equations. Based on the mathematical model, the system has two output (robot speed and tilt angle) that should be controlled through one manipulated input (voltage). Therefore, two PID control loops in cascade are needed to successfully control both outputs and maintain balance of the robot. As expected, after tuning the PID gains using MATLAB, the designed robot is capable of maintaining its balance while moving and carrying objects of different sizes, shapes, and weights. Moreover, the robot can travel at different desired speeds specified by the user. © 2022 IEEE.

关键词： Inverted pendulum

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Prototype Generation with the sUpervised Classifier System on kNN Matching 13

Prototype Generation with the sUpervised Classifier System o...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Yatsu, Naoya Shiraishi, Hiroki Sato, Hiroyuki Takadama, Keiki The University of Electro-Communications Department of Informatics Tokyo182-8585 Japan Yokohama National University Department of Electrical Engineering and Computer Science Yokohama240-8501 Japan University of Tokyo Interdisciplinary Information Science Research Division Chiba277-0882 Japan

ISBN: (纸本)9798350308365

This paper focuses on 'prototypes' as representative samples that can serve as a summary of the original dataset and proposes a novel Learning Classifier System (LCS) to generate a small number of prototypes that can achieve high classification accuracy in class classification. Concretely kNNUCS-PG is proposed to improve the sUpervised Classifier System (UCS) as one of LCSs by changing from the interval (rule) representation to the point representation to represent a prototype by employing k-nearest neighbors (kNN) to match the neighborhood prototypes. For a high classification accuracy with data reduction, selecting and generating prototypes that can maintain decision boundaries is necessary. Since UCS has generalization mechanisms, including rule merging, unnecessary rule deletion, and new rule discovery using niche Genetic Algorithm (GA), such techniques are highly useful for evolving indispensable prototypes as generalized prototypes. This paper compared conventional prototype-based methods with kNNUCS-PG in experiments using three benchmark problems and eight table datasets. kNNU CS-PG can maintain high classification accuracy even for complex problems with much overlap in the datasets. The results show that kNNUCS-PG is a robust PG that can maintain high classification accuracy while reducing data for various complex problems. © 2024 IEEE.

关键词： Self-supervised learning

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Ionospheric Response to the X2.8 Solar Flare on 14 December 2023

Ionospheric Response to the X2.8 Solar Flare on 14 December ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Krishnendu Sekhar Paul Haris Haralambous Frederick Research Center Nicosia Cyprus Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Solar flares are violent eruptions on the Sun that affect the Earth’s sunlit ionosphere almost instantly. Understanding how corresponding ionospheric characteristics vary is crucial for evaluating such effects. This study aims to highlight the importance of ionosondes in monitoring such effects by utilising foF2, fminF and hmF2 data from nine Digisonde stations to demonstrate their response to the X-2.8 class flare that occurred on December 14, 2023. According to this event the solar flare is shown to cause a decrease in the foF2 profile and an increase in fminF and hmF2. We suggest that these digisonde data, along with high-resolution observations of solar EUV flux emissions and ionospheric models, might help us gain a better understanding of the ionospheric dynamics and photochemistry that support the capacity to evaluate these effects on relevant communication systems such as HF.

关键词： Analytical models Communication systems Geoscience and remote sensing Data models Continents Sun Monitoring

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Noise Reduction in Industry Based on Virtual Instrumentation

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computers, Materials & Continua 2021年第10期69卷 1073-1096页

作者： Radek Martinek Rene Jaros Jan Baros Lukas Danys Aleksandra Kawala-Sterniuk Jan Nedoma Zdenek Machacek Jiri Koziorek Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical EngineeringVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia Faculty of Electrical Engineering Automatic Control and InformaticsOpole University of TechnologyOpolePoland Faculty of Electrical Engineering and Computer Science Department of TelecommunicationsVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia

This paper discusses the reduction of background noise in an industrial environment to extend *** the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G *** study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a *** experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from *** tested a hybrid algorithm for noise reduction and its impact on voice command recognition *** virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested *** welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+*** workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

关键词： 5G hybrid algorithms signal processing speech recognition

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Secure mmWave-NOMA Multi-BS Vehicular Communications Using Cooperative Jamming

Secure mmWave-NOMA Multi-BS Vehicular Communications Using C...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Yan, Yiting Ju, Ying Hu, Jiawei Liu, Lei Pei, Qingqi Yau, Kok-Lim Alvin Wu, Celimuge Zhang, Ning Xidian University School of Telecommunications Engineering Xi'an710071 China Universiti Tunku Abdul Rahman School of Internet Engineering and Computer Science Selangor 43200 Malaysia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan University of Windsor Department of Electrical and Computer Engineering WindsorN9B-3P4 Canada

ISBN: (纸本)9798350351255

The fronthaul network architecture is the key to dealing with the massive traffic effectively and providing high-quality service, and the multiple base stations (BSs) deployed by it face the gigantic data transmission, which has given the demand for high-capacity communication and information security in the vehicular network. In this paper, we combine the millimeter wave (mmWave) communication and non-orthogonal multiple access (NOMA) technologies to escalate the communication capacity of multiple vehicle users (VUs), and propose a blockage-based cooperative jamming strategy to solve potential security risks in the vehicular network. In particular, with the help of jam-mers selected by this strategy, transmission security is enhanced simultaneously without escalating the instability of connections caused by the time-varying nature of vehicular networks under the NOMA transmission mechanism when the base station (BS) does not fully understand the channel state information (CSI) of VUs. Then we comprehensively analyze the specific distribution of roadways and the distance distribution of VUs under the NOMA strategy, and derive the performance metrics of the network based on the stochastic geometry method. Numerical results show that the proposed cooperative jamming scheme can effectively improve the secrecy performance of the vehicular network. © 2024 IEEE.

关键词： Jamming

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Progressive Motion Boosting for Video Frame Interpolation

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IEEE Transactions on Multimedia 2023年 25卷 8076-8090页

作者： Xiao, Jing Xu, Kangmin Hu, Mengshun Liao, Liang Wang, Zheng Lin, Chia-Wen Wang, Mi Satoh, Shin'Ichi The School of Computer Science Wuhan University Wuhan430072 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430072 China The Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo101-8430 Japan

Video frame interpolation has made great progress in estimating advanced optical flow and synthesizing in-between frames sequentially. However, frame interpolation involving various resolutions and motions remains challenging due to limited or fixed pre-trained networks. Inspired by the success of the coarse-to-fine scheme for video frame interpolation, i.e., gradually interpolating frames of different resolutions, we propose a progressive boosting network (ProBoost-Net) based on a multi-scale framework to achieve flexible recurrent scales and then gradually optimize optical flow estimation and frame interpolation. Specifically, we designed a dense motion boosting (DMB) module to transfer features close to real motion to the decoded features from the later scales, which provides complementary information to refine the motion further. Furthermore, to ensure the accuracy of the estimated motion features at each scale, we propose a motion adaptive fusion (MAF) module that adaptively deals with motions with different receptive fields according to the motion conditions. Thanks to the framework’s flexible recurrent scales, we can customize the number of scales and make trade-offs between computation and quality depending on the application scenario. Extensive experiments with various datasets demonstrated the superiority of our proposed method over state-of-the-art approaches in various scenarios. © 2023 Institute of electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Motion estimation

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Object Detection for Vehicles with Yolo 22

Object Detection for Vehicles with Yolo

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2024 IEEE 22nd World Symposium on Applied Machine Intelligence and informatics, SAMI 2024

作者： Maleki, Pouria Ramazani, Abbas Khotanlou, Hassan Ojaghi, Sina Mousavi, Milad Kalinin, Alexey Mosavi, Amir Bu-Ali Sina University Department of Electrical Engineering Hamedan Iran Bu-Ali Sina University Department of Computer Engineering Hamedan Iran University of Tehran School of Computer and Electrical Engineering Tehran Iran K. N. Toosi University of Technology Tehran Iran Abylkas Saginov Karaganda Technical University Kazakhstan Obuda University John von Neumann Faculty of Informatics Budapest Hungary Ludovika University of Public Service Budapest Hungary

ISBN: (纸本)9798350317206

The rapid urban population growth has intensified the challenges associated with urban and suburban traffic, necessitating effective traffic control and management. The efficient movement of emergency vehicles, particularly ambulances and fire trucks, has emerged as a critical concern. This article presents the Vehicle Dataset, a comprehensive benchmark for object detection, encompassing seven vehicle classes, including cars, motorcycles, buses, trucks, vans, ambulances, and fire trucks. The dataset, includes 29,759 meticulously labeled images obtained from freely available online sources, enables the identification of traffic patterns through deep neural networks. Notably, the dataset emphasizes the facilitation of emergency vehicle movement. The Vehicle Dataset in this study is divided into three subsets, with 25,369 images assigned for training, 2,896 for validation, and 1,494 for testing. Through the utilization of the dataset, object detection algorithms based on YOLO versions 5, 6, and 7 have been trained. Remarkably, YOLO version 7 has yielded outstanding results, achieving a final precision of 85% and a mAP of 85% at an IoU threshold of 0.5. Moreover, at IoU thresholds ranging from 0.5 to 0.9, a mAP of 64% has been attained. The Vehicle Dataset represents significant resource for researchers and practitioners in the transportation and traffic management field. Its inclusion of emergency vehicles such as ambulances and fire trucks contribute to its unique value. This article presents a detailed exploration of the dataset, underscoring its significance in advancing object detection methodologies. © 2024 IEEE.

关键词： Object detection

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Increasing Reliability in Hybrid RF-Optical Networks: A Cross-Band Modulation Design

Increasing Reliability in Hybrid RF-Optical Networks: A Cros...

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IEEE Conference on Wireless Communications and Networking

作者： Thrassos K. Oikonomou Sotiris A. Tegos Panagiotis D. Diamantoulakis Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Department of Applied Informatics University of Macedonia Thessaloniki Greece

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

This paper presents a novel hybrid cross-band radio frequency (RF)-optical system that utilizes coherent RF detection with $M$ -QAM modulation and optical intensity modulation and direct detection (IM/DD) to fully utilize the diversity gains of cross-band architectures. By performing joint signal processing in the RF and optical domains, the proposed system achieves significant improvements in reliability, spectral efficiency, and data rates compared to conventional approaches. A key feature of the system is an optimized linear mapping between the RF and optical signals, which ensures seamless signal integration and improved performance. To evaluate the system, we derive the theoretical mutual information (MI) and a tight closed-form approximation for the symbol error probability (SEP) of the proposed modulation scheme. Numerical results validate the theoretical analysis and show that the proposed scheme significantly outperforms state-of-the-art cross-band modulations in terms of MI and SEP. The proposed scheme, with its low-complexity design and superior performance, is a promising candidate for next-generation wireless networks.

关键词： Radio frequency Error probability Spectral efficiency Wireless networks Symbols Reliability theory Optical receivers Adaptive optics Optical signal processing Mutual information

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Assessing the Time Evolution of COVID-19 Effective Reproduction Number in Brazil

arXiv

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arXiv 2023年

作者： Porto da Silva, Edson Lima, Antonio M.N. The Department of Electrical and Computer Engineering Center for Electrical Engineering and Informatics Universidade Federal de Campina Grande Brazil

In this paper, we use a Bayesian method to estimate the effective reproduction number (R(t)), in the context of monitoring the time evolution of the COVID-19 pandemic in Brazil at different geographic levels. The focus of this study is to investigate the similarities between the trends in the evolution of such indicators at different subnational levels with the trends observed nationally. The underlying question addressed is whether national surveillance of such variables is enough to provide a picture of the epidemic evolution in the country or if it may hide important localized trends. This is particularly relevant in the scenario where health authorities use information obtained from such indicators in the design of non-pharmaceutical intervention policies to control the epidemic. A comparison between R(t) estimates and the moving average (MA) of daily reported infections is also presented, which is another commonly monitored variable. The analysis carried out in this paper is based on the data of confirmed infected cases provided by a public repository. The correlations between the time series of R(t) and MA in different geographic levels are assessed. Comparing national with subnational trends, higher degrees of correlation are found for the time series of R(t) estimates, compared to the MA time series. Nevertheless, differences between national and subnational trends are observed for both indicators, suggesting that local epidemiological surveillance would be more suitable as an input to the design of non-pharmaceutical intervention policies in Brazil, particularly for the least populated states. © 2023, CC BY.

关键词： COVID-19

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Development of Mutal Recognition of Education Approach in Advanced computer-Oriented engineering Technologies in the Baltic Region 64

Development of Mutal Recognition of Education Approach in Ad...

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64th IEEE Annual International Scientific Conference on Power and electrical engineering of Riga Technical University, RTUCON 2023

作者： Kunicina, Nadezhda Rassolkin, Anton Bruzgiene, Rasa Plonis, Darius Caiko, Jelena Riga Technical University Institute of Electrical Engineering and Electronics Feee Riga Latvia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Kaunas University of Technology Faculty of Informatics Department of Computer Sciences Kaunas Lithuania Vilnius Gediminas Technical University Department of Electronic Systems Vilnius Lithuania

ISBN: (纸本)9798350317732

The continued improvement and development of study programmes content for mutual recognition of study programmes among the largest technical universities in the Baltic region provides a very good opportunity for regional development as it brings a good advancement in academics and research at the involved universities, allows for more flexible and reliable collaboration with industrial partners, and provides an opportunity to develop new technologies and implement them for regional support. The goal of the development is to promote the involvement of students in the design of adaptive systems by providing them with the necessary set of skills that will allow them to immediately engage in the design of innovative adaptive systems and successfully solve technological challenges that have been identified through the cooperation of educational and research institutions. The adoption of an innovative educational strategy will aid in the creation of new technology and creative solutions even before students begin their studies. Collaboration between academic personnel and industry will help students build their abilities. © 2023 IEEE.

关键词： Students

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