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2024 International Conference on Electrical, Electronics and computing Technologies, ICEECT 2024

作者： Verma, Aishwarya Panda, Krishna Tanaya Sharma, Vandana Tripathy, Hrudaya Kumar Al-Khasawneh, Mahmoud Ahmad Alkhayyat, Ahmed Kalinga Institute of Industrial Technology India CHRIST University Computer Science Department India Skyline University College University City Sharjah School of Computing Sharjah1797 United Arab Emirates Applied Science Private University Applied Science Research Center Amman Jordan Jadara University Research Center Jadara University Jordan The Islamic University College of Technical Engineering Najaf Iraq

ISBN: (纸本)9798350378092

Mental illness is one of the most common disabilities in the world. The term "mental illness stigma"describes harmful practices and misconceptions that lead to a detrimental effect on the mental health, motivation, and self-worth of those who suffer from mental illnesses. Health care services are important for treating and reducing the negative stigma of mental health, as they are areas where patients seek relief and support. The study aims to investigate the causes and how to reduce them. Explores ways to disrupt the health care environment, specifically the RESHAPE program, which focuses on the concept of "critical". This review paper looks at 8-10 papers on mental health and stigma and how stigma will be reduced. The results show that a large number of doctors and students are stigmatized, negatively affecting the lives of people affected by mental illness. RESHAPE, KAP, and IBH therapies are also effective ways to minimize mental health stigma. This intervention aims to educate public health workers, promote social cohesion, and integrate treatment into primary health care, improving treatment into primary health care, improving treatment quality and patient outcomes. The study draws attention to the importance of stigma reduction efforts in the long term in health education and practice emphasis. © 2024 IEEE.

关键词： Electronic health record

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A Fast Exponential Analysis and Variable Projection Based Method for Linear Array Synthesis

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IEEE Antennas and Wireless Propagation Letters 2025年第6期24卷 1527-1531页

作者： Sengupta, Ramonika Knaepkens, Ferre Cuyt, Annie Prinsloo, David S. Schäfer, Thomas Smolders, A. Bart Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Faculty of Applied Engineering University of Antwerp Groenenborgerlaan 171 Antwerp2020 Belgium Computing Science and Mathematics Division University of Stirling Scotland StirlingFK9 4LA United Kingdom ASTRON Dwindloo Oude Hoogeveensedjik 4 7991 PD Netherlands SATCUBE Nellickevägen 22 Gothenburg41263 Sweden

This paper presents a fast exponential analysis and variable projection method to reduce the number of elements in linear phased arrays. The numerical examples given in this work demonstrate a reduction of approximately 20% or 10% in the number of elements, with only a slight decrease in directivity of 0.63 dBi observed for a scan range of [−45◦, 45◦]. Compared to the combined matrix pencil and Tabu search algorithm, the proposed technique converges in fewer iterations and exhibits ≈ 5 dB reduction in maximum side lobe level. © 2002-2011 IEEE All rights reserved.

关键词： Antenna phased arrays

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ON NON-REFLECTIVE BOUNDARIES FOR OUTDOOR SOUND PROPAGATION USING THE DISCONTINUOUS GALERKIN METHOD 10

ON NON-REFLECTIVE BOUNDARIES FOR OUTDOOR SOUND PROPAGATION U...

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10th Convention of the European Acoustics Association, EAA 2023

作者： Feriani, Sophia Julia Engsig-Karup, Allan P. Pind, Finnur Cosnefroy, Matthias Jeong, Cheol-Ho Acoustic Technology Department of Electrical and Photonics Engineering Technical University of Denmark Denmark Scientific Computing Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Treble Technologies Hafnartorg Kalkofnsvegur 2 Reykjavík101 Iceland

ISBN: (纸本)9788888942674

In environmental acoustics, sound propagates in open air and can be mathematically modelled in terms of a semi-infinite domain. The calculations for accurate numerical solutions for outdoor acoustics are computationally heavy when the chosen computation domain is large enough to fulfil the Sommerfeld radiation condition. To lower the computational cost, the domain must therefore be truncated to not significantly impact the numerical solution inside the domain and allow outgoing acoustic waves to leave the domain undisturbed. Various radiation conditions (sometimes considering the wind) have been developed to achieve this goal such as the Perfectly Matched Layer method. The aim of this study is to compare the accuracy of different non-reflecting boundaries using the high-order nodal discontinuous Galerkin finite element method (DG-FEM) for the case of an acoustic pulse propagating in a static and moving medium in an unstructured mesh. For each boundary treatment, the tunable parameters of the methods are defined to balance accuracy and computational cost. © 2023 S.J. Feriani et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Galerkin methods

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The Importance of Dark Web Access in Cyber Threat Intelligence

The Importance of Dark Web Access in Cyber Threat Intelligen...

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International Symposium on Digital Forensic and Security (ISDFS)

作者： Victor Obojo Richard A. Ikuesan AbdulKabir Adekanye Elias Iortom Cyber Threat Intelligence Division CyberDome Nigeria Abuja Nigeria Computing and Applied Technology College of Technological Innovation Zayed University Abu Dhabi UAE

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

Cyber Threat Intelligence (CTI) is essential in in-forming proactive cyber defence, especially in Nigeria's most significant sectors: financial services, telecommunications, and healthcare. This study reviews the current body of CTI lit-erature, examines intelligence obtained from the Dark Web, and determines impending threats, including Ransomware-as-a-Service, zero-day exploits, and phishing toolkits aimed at these sectors. Performing qualitative platform analysis of the likes of RaidForums and ***, we determine sectoral vulnerabilities and offer pragmatic suggestions on developing Nigeria's cyber defence system. The findings underscore the Dark Web's role as a vital source of intelligence to counter cyber threats under low-resource conditions, filling Nigeria's gaps in CTI capabilities.

关键词： Industries Dark Web Reviews Phishing Medical services Stability analysis Cyber threat intelligence Telecommunications Ransomware Monitoring

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Improved Multiple Linear Regression for Forecasting Water Quality of Vegetable and Fruit Wastewater 2

Improved Multiple Linear Regression for Forecasting Water Qu...

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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Alsalami, Zaid Divya, G. Hussaian Basha, C.H. Rafikiran, Shaik Dhandayuthapani, Bala V. The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Electrical and Electronics Engineering School of Engineering SR University Warangal India Department of Electrical and Electronics Engineering Sri Venkateswara College of Engineering Tirupati India Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Oman

ISBN: (纸本)9798331504960

The waste and wash waters from vegetable and fruits process industry are categorized with solids and organic component which needs treatment for meeting regular standards in use. Every treatment is assigned with minimizing postponed solids, whole phosphorus, biochemical, chemical oxygen and nitrogen demanded. From produced data, that is probable for developing prediction model to every tested water treatment. The methods for predicting post treatment water quality and created by Improved Multiple Linear Regression (IMLR), that is enhanced through Generalized Structure of Group Method in data handling methods (GSGMDH). The selection of IMLR and generalized architecture of group technique of data handling methods because of capability of methods for generating equations to utilize. The huge variability and difficult nature of waste water quality parameters are difficult in representing linear methods, but it is perfectly matched for group model of data handling method. The method provided an significant tool for end user in choosing correct treatment depended on actual characteristics of waste water and needed standards for treating waste. © 2024 IEEE.

关键词： Multiple linear regression

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Resource Allocation in Edge computing Environment Using Deterministic Policy Gradient Algorithm

Resource Allocation in Edge Computing Environment Using Dete...

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International Conference on Advanced computing and Communication Systems (ICACCS)

作者： C. P. Shabariram N. Shanthi P. Priya Ponnuswamy V. Subramaniyaswamy V. Sathana Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Erode India Department of Computer Science and Engineering School of Computing SASTRA University Thanjavur India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

In recent years, the edge computing paradigm enables the movement of processing units and storage nearer to the data available locations. The mechanism completes the computation in a short span of time in minimum bandwidth. Edge ecosystem is a type of distributed computing that is sensitive to topology and geography; the Internet of Things is a prime instance of this. Rather than referring to a single technology, Edge computing refers to an architecture. This paper proposes a resource allocation methodology that will enliven the situation between users and edge servers. By creating continuous control at the edge servers to determine resource allocation, edge computing improves reaction time, provides high security with decreased risk, scalability, lowers transmission costs, and versatility (offload targets, migration bandwidth and computing resources). The Deterministic Policy Gradient, Deep learning and Quality Network concepts are combined in the proposed system. The continuous action space is achieved by a deterministic policy gradient. The experience relay includes a quality network. In the proposed system, the actor-critic network produces a single continuous action instead of resulting probability based actions. The critic-part uses Q-value from a quality network based on current status and activity. The goal of the proposed system is to develop a Deep Deterministic Policy Gradient methodology to allocate servers for mobile users with the help of the Edge computing while taking computation resources, offloading goals and migration bandwidth into consideration. The simulation result indicates that deterministic policy gradients integrated deep learning models improve the system performance compared with Game theory.

关键词： Deep learning System performance Simulation Scalability Bandwidth Topology Servers Resource management Security Edge computing

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Deep Learning Scheme for Modulation Classification under Fading Channels 7

Deep Learning Scheme for Modulation Classification under Fad...

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7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Ghauri, Sajjad A. Sarfraz, Mubashar Chhabra, Gunjan Kaushik, Keshav Zafar, Asim Khan, Inam Ullah Isra University School of Engineering & Applied Sciences Islamabad Pakistan Numl University Faculty of Engineering and Computing Islamabad Pakistan Graphic Era Hill University Graphic Era Deemed to be University Department of Cse Uttarakhand Dehradun India Amity University Amity School of Engineering and Technology Punjab India National University of Technology Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350350067

The field of automatic modulation classification using deep neural networks has undergone significant development in recent years. In this research, M-QAM and N-PSK modulation formats have been considered for classification. The deep neural network architecture is directly fed with raw signals that are often corrupted with channel noise and fading effects such as Rayleigh and Nakagami. The proposed classifier structure also incorporates normalized cumulants of higher order from the received signal. The proposed DNN architecture's performance is evaluated by comparing its efficiency for raw data and extracted features-based classification. We have validated the classifier efficiency through three different cases. Our proposed classifier demonstrates remarkable capability in efficiently classifying modulation formats. © 2024 IEEE.

关键词： Signal modulation

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"Return-To-Work": Application of New Materials to Develop the Durable and Low Cost of Solid Ankle Cushion Heel (SACH) Prosthetic Foot

"Return-To-Work": Application of New Materials to Develop th...

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Human Engineering Symposium, HUMENS 2021

作者： Wan Ramli, Wan Syahira Mat Zin, Mohd Isyraf Irfan Mat Desa, Mohd Shaiful Zaidi Ramli, Azizan Faculty of Industrial Sciences and Technology College of Computing and Applied Sciences Universiti Malaysia Pahang Gambang Pahang26300 Malaysia Faculty of Chemical and Process Engineering Technology Universiti Malaysia Pahang Gambang Pahang26300 Malaysia

ISBN: (纸本)9789811641145

This paper presents the conceptual design and development of an ergonomic and polymeric prosthetic foot. This study was done in two phases the prototype design and the selection of materials with fabrication. During the design stage, the inputs from the Certified Prosthetists and Orthotists (CPO) and literature review were discussed amongst four interested parties (UMP-ADTEC Jerantu-JasaMedik Enterprise-Hospital Pulau Pinang). In addition, the design was also developed based on the knowledge gathered during industrial training period with a prosthetic company, in which the company provides prosthetic and orthotic services. A series of discussions has been organized and in consensus with all interested parties, the prototype design was successfully developed. This design then simulates using Solidworks software to determine its stress, strain and displacement. The result show the von-mises stress for Solid Ankle Cushion Heel (SACH) foot was higher. In addition, the selection and analysis on material development has been carried out in one go. Finally, the prototype prosthetic foot known as Solid Ankle Cushion Heel (SACH) has been fabricated and the field test is to be carried out at a rehabilitation center. From this analysis, the prosthetic foot uses new materials which are polyurethane and neoprene, 99.4 and 0.6% because it gives good tensile strength and also young modulus for the designing process until the casting process. It also best production method that can be used. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Ergonomic Neoprene Polymeric Polyurethane Prosthetic foot

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Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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MedX-Net: Hierarchical Transformer with Large Kernel Convolutions for 3D Medical Image Segmentation

MedX-Net: Hierarchical Transformer with Large Kernel Convolu...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Lu, Lin Zou, Qingzhi Key Laboratory of Computing Power Network and Information Se-curity Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9781665410205

Due to the exceptional performance of Transform-ers in 2D medical image segmentation, recent work has also introduced them into 3D medical segmentation tasks. For instance, Swin UNETR and other hierarchical Transformers have reintroduced prior knowledge from several convolutional networks, further enhancing the volume segmentation capabilities of models. The efficacy of these hybrid methodologies is primarily attributed to the substantial quantity of parameters and the nonlocal self-attention mechanism with a large receptive field. We argue that the behavior of these methods' large receptive fields can be simulated by employing fewer parameters through the utilization of depth-wise convolutions with large kernel. Within this manuscript, we introduce a lightweight volume segmentation model called MedX-Net, which uses convolutional network modules to simulate hierarchical Transformers for robust volume segmentation. Firstly, inspired by the hierarchical Transformer module of Swin UNETR, we investigate large-kernel depth-wise convolutions with different sizes to achieve a reduced model parameter count while maintaining a large global receptive field. Secondly, we replace the multilayer perceptron (MLP) in the hierarchical Transformer module with Inverted Bottleneck with Depthwise Convolution Enhancement(DWCE) to improve model performance with fewer activation and normalization layers, further reducing the parameter count. We validate the effectiveness and efficiency of our model for volume segmentation on three public datasets: Synapse, BTCV and ACDC. On the Synapse dataset, compared to Swin UNETR, our model achieves an improvement from 83.48% to 87.21% in Dice score. Compared to the result of 86.57% achieved by nnFormer, our model achieves superior performance while reducing the model parameter count by 64%. © 2024 IEEE.

关键词： Image segmentation

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