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Robust Beamforming for RIS-Assisted NOMA systems With CSI Imperfection and Low-Resolution Phase Shifters 6

Robust Beamforming for RIS-Assisted NOMA Systems With CSI Im...

引用

6th international conference on Information Communication and signal processing, ICICSP 2023

作者： Liu, Xiang Wei, Tong Liang, Hao Guo, Chongtao Liao, Bin College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Luxembourg

ISBN: (纸本)9798350339994

In this paper, we investigate the robust beamforming design for reconfigurable intelligent surface (RIS) assisted non-orthogonal multiple access (NOMA) communication systems with imperfect channel state information (CSI). More specifically, we propose to perform the joint design of base station (BS) active beamforming and RIS passive beamforming, by minimizing the total transmit power while guaranteeing the worst-case signal-to-interference-plus-noise ratio (SINR) of each user under the assumption of bounded CSI error. This result in a quadratic programming problem with unit-modulus and SINR constraints is non-convex and challenging to solve. Towards that end, the original problem is decoupled into two sub-problems, such that we can tackle the problem under the alternating optimization (AO) framework. Further, the design with low resolution of RIS phase shifters is also addressed. Numerical results are provided to demonstrate the effectiveness of the proposed algorithm. © 2023 ieee.

关键词： channel state information (CSI) non-orthogonal multiple access (NOMA) Reconfigurable intelligent surface (RIS) robust beamforming

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Prediction of Colon Cancer using DenseNet121, CNN, and REsNET50 Machine Learning Models and using Image processing Techniques

Prediction of Colon Cancer using DenseNet121, CNN, and REsNE...

引用

2023 international conference on Artificial Intelligence robotics, signal and Image processing, AIRoSIP 2023

作者： Hasan, Mahadi Islam, Jahirul Ahmed, Minhaz Hasan, Md Maruf The University of Tennessee at Chattanooga Ms in Data Analytics ChattanoogaTN United States New Mexico Institute of Mining and Technology Ms in Cse SocorroNM United States Ms in Cse *** United States The University of South Dakota Department of Comuter Science VermillionSD United States

ISBN: (纸本)9798350327472

Colon cancer is a matter of great importance in the field of global health, as it stands as one of the primary contributors to mortality rates associated with cancer. The timely identification and precise prognostication of colon cancer have the potential to significantly enhance patient outcomes and diminish mortality rates. The global public health systems face a significant challenge in addressing the impact of colon cancer, which underscores the need for efficient screening and prediction techniques. Machine learning techniques present potential solutions by utilizing extensive datasets to detect intricate patterns that may be imperceptible to human observers. This study investigates the viability of employing machine learning techniques to predict colon cancer by utilizing a dataset consisting of 10,000 colonoscopy images that have been classified into two categories: cancerous and non-cancerous cases. The main aim of this study is to assess the efficacy of various machine learning algorithms, namely DenseNet-121, CNN, and ResNet50, in the prediction of colon cancer. The models' performance was comprehensively assessed in terms of their accuracy in predicting colon cancer. Among the models that were evaluated, DenseNet-121 demonstrated exceptional performance, achieving the highest accuracy of 99.6%. © 2023 ieee.

关键词： Lung cancer

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Design and Implementation of Smart Wheelchair with Advanced Control Interfaces 3

Design and Implementation of Smart Wheelchair with Advanced ...

引用

3rd international conference on robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Shifa, Shina Mifta Mridul, Towfiq Mahmud Rafat, Sadman Sakib Monjur, Md. Hasan Islam, Md. Rokibul Hassan, Md. Kamrul American International University-Bangladesh Department of Electrical and Electronics Engineering Dhaka Bangladesh American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronics Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

As wheelchair users demand support and assistance from others in order to travel, the study intends to assist physically impaired persons with their mobility, particularly those who have lost their capacity to use their legs due to paralysis, an accident, or old age, as well as those who have feeling issues. The proposed project would provide wheelchair users with location-based services using one-finger control, voice control, and GPS tracking. In comparison to the expensive imported wheelchairs now on the market, the technology will be more affordable and user-friendly. With the support of a user command, the intelligent wheelchair gadgets will be able to maneuver themselves. Users will exert less effort because to the effortless mobility. The project will primarily use an E-bike motor and motor driver, an Arduino, a GPS module, and a solar panel. The voice control signal and manual control utilizing a joystick are used by the motor driver to operate. The Arduino includes a voice-activated device for physically challenged persons who are unable to control their hand motions. Family members will be able to trace the precise position in the case of emergencies due to the usage of GPS. The system will use a solar panel in addition to it to charge the battery. As an additional security measure, an emergency power OFF (EPO) switch is included. This switch is intended to turn the system off in an emergency or when it cannot be switched off normally. Using Porteous, the project simulation is carried out. © 2023 ieee.

关键词： Global positioning system

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Dynamic Frequency-Selective Through-Wall Wireless Transmission with Cascaded Metasurfaces

Dynamic Frequency-Selective Through-Wall Wireless Transmissi...

引用

2023 ieee international conference on signal processing, Communications and Computing, ICSPCC 2023

作者： Hao, Han Yang, Fengyuan Wang, Nan School of Microeletronics Shanghai University Shanghai Key Laboratory of Chips and Systems for Intelligent Connected Vehicle Shanghai China

ISBN: (纸本)9798350316728

Efficient through-wall wireless transmission is vital in modern wireless communications systems. Development of the 5th generation wireless systems (5G) provides faster and broader wireless connectivities. Despite this, seamless connections remain challenging in densely built cities. The daily used Wi-Fi signals face significant reflection when passing through walls. To address this issue, we proposed a tunable cascaded metasurface design concept that enables near-reflectionless through-wall wireless transmission with dynamic frequency selection. The cascaded metasurface designed with bianisotropic electromagnetic wave responses provides excellent air-wall impedance matching, solving the reflection problem in fundamentals. Meanwhile, the multilayer cascading structures allow for flexible tuning of the interlayer spacing, leading to dynamic frequency selection and expanded communication capacity. This reconfigurable cascaded metasurface design optimizes the through-wall wireless communication channels, hence, possesses a high potential to assist future 5G and 6G ubiquitous wireless connectivity. © 2023 ieee.

关键词： Electromagnetic waves

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Research About the Impact of Cms on the Reliability of Wind Turbines in Application Scenarios 14

Research About the Impact of Cms on the Reliability of Wind ...

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14th international conference on Power and Energy systems, ICPES 2024

作者： Jiang, Peng Huang, Tao Li, Jie Wang, Xiaolei Wang, Junjie Dong, Zhanzhao Huaneng Shandong Power Generation Co. Ltd. Jinan China China Huaneng Renewable Energy Co. Jinan China Huaneng International Power Co. Ltd. Rizhao Power Plant Rizhao China

ISBN: (纸本)9798350391329

This paper proposes a reliability assessment method for wind turbines based on CMS data. Combined with multi-scenario applications in complex operating environments, the role of CMS technology in fault diagnosis and early warning is analyzed. In terms of vibration signal processing, an improved wavelet transform algorithm and a health index quantification model were adopted, and their adaptability and accuracy under complex nonlinear conditions were verified through case studies. It is proposed a standardized data analysis framework and optimization strategies in response to the issue of non-uniform data in CMS systems of wind turbines from different brands;through practical verification of early fault warning and diagnostic functions, solutions to optimize the factors affecting the stability of wind turbines were studied and proposed. This provides technical support for wind farms to move towards intensive and intelligent management and offers a scientific basis for enterprises to improve quality and efficiency. © 2024 ieee.

关键词： Wavelet transforms

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Stand Alone or Non Stand Alone 5G Tactical Edge Network Architecture for Military and Use Case Scenarios

Stand Alone or Non Stand Alone 5G Tactical Edge Network Arch...

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2024 ieee international conference on intelligent signal processing and Effective Communication Technologies, INSPECT 2024

作者： Malik, Mandeep Kothari, Ashwin Pandhare, Rashmi A. IIIT Nagpur India VNIT Nagpur India

ISBN: (纸本)9798350379525

The advent of fifth-generation (5G) technology marks a paradigm shift in global communication infrastructure, transcending the incremental enhancements seen in previous generations. Far from being a mere upgrade in speed, 5G represents a holistic digital transformation, characterized by unprecedented multi-platform connectivity, advanced network slicing, and enhanced virtualization capabilities. As 5G continues to be deployed across India and internationally, the technology heralds the arrival of a unified communication network capable of supporting millions of concurrent devices with ultra-low latency and exceptional reliability. Unlike previous network generations, 5G is no longer defined solely by its throughput. Instead, it is poised to serve as the foundation for diverse services, encompassing both public and private networks. Within this ecosystem, two key deployment architectures emerge: 5G Non-Standalone (NSA) and 5G Standalone (SA). Each model offers unique advantages and challenges, necessitating a detailed evaluation of their respective capabilities to align with specific operational requirements, particularly in mission-critical domains such as military communications. Military communications, often built upon civilian technological frameworks, stand to benefit profoundly from the efficiency, precision, and enhanced decision-making afforded by 5G. The increased capacity, faster data transmission, and reliability inherent in 5G networks can dramatically augment the effectiveness of military operations and decision support systems. This paper undertakes a comprehensive performance evaluation of 4G/LTE, 5G NSA, and 5G SA architectures, with a focus on their applicability to military use cases. Leveraging simulations and key performance indicators (KPIs) derived from campus network studies, the analysis will critically assess whether these network configurations can meet the stringent requirements of military communications. The study will culminate in a rec

关键词： 5G mobile communication systems

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology 33

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

引用

33rd ieee international conference on Microelectronics, MIEL 2023

作者： Bogacki, P. Dlugosz, M. Talaska, T. Dlugosz, R. Aptiv Services Poland Kraków30-399 Poland Agh University of Science and Technology Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications Kraków30-059 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350347760

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock. © 2023 ieee.

关键词： Pixels

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MRI Denoising Neural Network Architecture Convolution 12

MRI Denoising Neural Network Architecture Convolution

引用

12th ieee international conference on intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, IDAACS 2023

作者： Sliusarenko, Denys Netreba, Andrii Radchenko, Sergiy University of Kyiv Faculty of Radiophysics Electronics and Computer Systems National Taras Shevchenko Kyiv01601 Ukraine

ISBN: (纸本)9798350358056

Ensemble learning of machine vision (ML) models, particularly deep neural networks, has emerged as a powerful technique for enhancing the quality of medical image processing. In this research endeavor, we investigated the application of the Deep Convolutional Neural Network (DnCNN) to the denoising of medical images. The DnCNN model was trained using a diverse dataset comprising medical images encompassing various noise levels and types. The primary objective was to train the model to restore a clean version of the image from its noisy counterpart. To evaluate the performance of the proposed approach, we employed widely-used quality metrics, namely the Structural Similarity Index (SSIM) and Peak signal-to-Noise Ratio (PSNR). The experimental results demonstrated the efficacy of the DnCNN model in effectively reducing noise while preserving crucial image details, thus offering a promising solution for denoising medical images. © 2023 ieee.

关键词： AI backpropagation DnCNN MRI Noise residual

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Transformer-Based Multi-Head Attention for Noisy Speech Recognition

Transformer-Based Multi-Head Attention for Noisy Speech Reco...

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2024 international conference on Telecommunications and intelligent systems, ICTIS 2024

作者： Djeffal, Noussaiba Kheddar, Hamza Addou, Djamel Selouani, Sid Ahmed University of Sciences and Technology USTHB Speech and Signal Processing Laboratory Algiers Algeria University of MEDEA LSEA Laboratory Dept. Electrical Engineering Medea Algeria Universite de Moncton Research Laboratory in Human-System Interaction Shippagan Campus Shippagan Canada

ISBN: (纸本)9798331527396

This paper presents an advanced transformer-based multi-head attention approach for automatic speech recognition (ASR) in noisy speech environments. The study focuses on four distinct noise scenarios: subway, babble, car, and exhibition hall, each rigorously evaluated across different signal-to-noise ratios (SNRs) and a clean condition. Utilizing the AURORA 2 dataset, this research investigates the performance and robustness of the proposed model under these varied acoustic conditions. To further enhance the transformer-based attention's performance in ASR, we compare its effectiveness against sound classification in environmental noise using the ESC-50 dataset. The experimental results provide a comprehensive analysis, demonstrating that the model with transformer-based multi-head attention, incorporating merging and gammatone frequency cepstral coefficients (GFCC) features, significantly outperforms a baseline model using GFCC features with transformer-based multi-head attention alone, without merging. The model achieves an accuracy of 98.75% on the AURORA 2 dataset in clean conditions, and maintains a high accuracy of 92.38% under noisy conditions. When evaluated on the ESC-10 dataset, it achieves an accuracy of 81.25%, underscoring its robustness and potential for practical deployment in diverse acoustic settings. © 2024 ieee.

关键词： Exhibition buildings

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Adaptive Control for Nonlinear State-Constrained systems with Time-Varying Delays and Unknown Control Direction 5

Adaptive Control for Nonlinear State-Constrained Systems wit...

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5th international conference on intelligent Control, Measurement and signal processing, ICMSP 2023

作者： Xu, Tian Li, Yulin Yang, Ling Lin, Qinyong Li, Wei College of Automation Zhongkai University of Agriculture and Engineering Guangzhou China

ISBN: (纸本)9798350336030

This paper presents an adaptive tracking control strategy for nonlinear state-constrained systems subject to time-varying delays and unknown control direction. In the backstepping process, the challenges of time-varying full state constraints and time-delays are solved by combining the time-varying barrier Lyapunov functions (BLFs) with the Lyapunov-Krasovskii functionals (LKFs). The Nussbaum function and neural networks (NNS) are used to handle the unknown control direction and approximate the unknown functions, respectively. The satisfactory tracking performance can be achieved without violating state constraints under our presented control method. Finally, the simulation study is implemented to illustrate the feasibility of the presented method. © 2023 ieee.

关键词： Lyapunov functions

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