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Possibilities of the Investigations of the Thermal Parameters of the Polybutyl Methacrylate Siloxane Coatings with the Use of the Photothermal Radiometry

Possibilities of the Investigations of the Thermal Parameter...

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Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-electronics and Micro-Systems EuroSimE

作者： Ł. Chrobak M. Maliński D. Korte S. Janta-Lipińska Faculty of Electronics and Computer Science Sniadeckich 2 Koszalin University of Technology Koszalin Poland Laboratory for Environmental and Life Sciences Vipavska cesta 13 University of Nova Gorica Nova Gorica Slovenia Faculty of Civil Engineering Environmental and Geodetic Science Sniadeckich 2 Koszalin University of Technology Koszalin Poland

This article presents the results of theoretical and experimental investigations of thermal parameters of Polybutyl Methacrylate Siloxane (PBMA-siloxane) anticorrosion coatings by the use of the Photothermal Radiometry (PTR) method. The goal of the study was to investigate possibilities of application of this method for the thermal characterization of PBMA-siloxane coatings. Three different theoretical models of the PTR signal describing the two-layer system of the analyzed coatings deposited on a substrate have been discussed and investigated. The character of the experimental results was interpreted in the framework of the model that exhibits their best reproduction enabling the extraction of the thermal parameters of the coatings.

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Success Probability and Spectral Efficiency Estimation Using Successive Interference Cancellation for B5G Network

Success Probability and Spectral Efficiency Estimation Using...

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Computing (ICOCO), IEEE International Conference on

作者： Faizan Qamar Anand Gachhadar Syed Hussain Ali Kazmi Rosilah Hassan Center for Cyber Security Faculty of Information Science and Technology (FTSM) Universiti Kebangsaan Malaysia (UKM) UKM Bangi Selangor Malaysia Department of Electronics and Computer Engineering Institute of Engineering Tribhuvan University Kathmandu Nepal Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Malaysia

This research paper investigates the examination of Successive Interference Cancellation (SIC) implementation within ultra-dense 5G networks. The study focuses on the theoretical foundations of SIC, encompassing its system and channel models modified for Ultra-Dense Networks (UDNs). A mathematical model is formulated to assess critical network performance metrics such as Signal-to-Interference-plus-Noise Ratio (SINR), Success Probability and Spectral Efficiency after the application of SIC in the network. The effectiveness of SIC is evaluated through simulations and compared against existing interference mitigation techniques like Zero Forcing. The simulations results show that the proposed model has potential to subdue the interference-related issues, such as improved success and probability. By knowing the capabilities and limitations of SIC, network operators can make informed decisions to optimize network performance and provide enhanced user experiences. Through an exploration of SIC's principles and advantages, this study aims to shed light on its potential for effectively mitigating interference and improving the Success Probability and Spectral Efficiency of B5G networks in real-world scenarios.

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Application of soft computing algorithms for hybrid modular multilevel inverters

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Measurement: Sensors 2024年 31卷

作者： Gireesh Kumar, Devineni Venkata Sireesha, Nagineni Bhoopal, Neerudi Kumar Gatla, Ranjith Kotb, Hossam AboRas, Kareem M. Elrashidi, Ali Alqarni, Mohammed Yasin Ghadi, Yazeed Oubelaid, Adel Department of Electrical & Electronics Engineering B V Raju Institute of Technology Narsapur502313 India Department of Information Technology Institute of Aeronautical Engineering Hyderabad500043 India Department of Electrical & Electronics Engineering Institute of Aeronautical Engineering Hyderabad500043 India Department of Electrical Power and Machines Faculty of Engineering Alexandria University Alexandria21544 Egypt Electrical Engineering Department University of Business and Technology Ar Rawdah Jeddah23435 Saudi Arabia Engineering Mathematics Department Faculty of Engineering Alexandria University Alexandria21544 Egypt Department of Computer Science and Software Engineering Al Ain University Abu Dhabi15322 United Arab Emirates Laboratoire de Technologie Industrielle et de L'Information Faculté de Technologie Université de Bejaia Bejaia06000 Algeria

This study utilized Harris Hawk optimization to analyze the harmonic distortions of a symmetric capacitor based multilevel converter. The proposed multilevel converter uses identical and symmetric DC sources in its input. The proposed topology for a multilevel converter uses fewer switches than typical cascaded designs. It can output 9-level outputs and can be scaled up to higher levels. The proposed multilevel converter can be improved by implementing a low frequency pulse width modulation technique to reduce the stress on the switches. The optimization of the switching angles using Harris Hawk was able to solve the non-linear aspects of the Selective Harmonic Elimination Pulse Width Modulation. The output voltage's THD was compared with that of other optimization methods, such as ant colony and particle swarm. The comparison shows that the output THD of the Harris Hawk optimizer is lower than that of other methods, which is about 5 %, according to the standards of IEEE-519. © 2023

关键词： Pulse width modulation

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An upgraded Multifunctional Radiology Program based on NSST that uses Optimization Technique and also the NLM Method for computer Vision

An upgraded Multifunctional Radiology Program based on NSST ...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Deepak Kumar Sinha Sunil M P Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore Karnataka India. Department of Electronics and Communication Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore Karnataka India.

Multifunctional health plasma imagery is an important component of several computer-assisted surgical treatments as well as appearance healthcare therapy and diagnostics. This study presents a- anti Shear let Transforming (NSST) + Gray Wolf optimized (GWO) technique-based advanced healthcare fused measurement device. Its GWO methodology as well as the ideal gain settings decide here on optimal sub band. Furthermore, a noise removal and improvement phase is applied to the whole method in order to increase the video appearance and also the degree of detail. Whenever the pictures are distorted by pollution, such classic merging methods’ productivity is severely hindered. Therefore, it is necessary to create a transformation that can maintain specific data even though photos are damaged. The equal achievement of low noise plus improved texture is likewise difficult. The objective of the proposed research is to correlate advanced NSST fuse imagery with conventional geographical, translation, filter, etc artificial neural area merging approaches.

关键词： Radiography Productivity Databases Merging Surgery Transforms Radiology

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Pelican optimized extreme learning machine based prognosis of heart failure using textural patterns in CMR images

Pelican optimized extreme learning machine based prognosis o...

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technology & engineering Management Conference - Asia Pacific (TEMSCON-ASPAC), IEEE

作者： M Muthulakshmi K Ashwini R Jansi Batchu Bhanu Sai Mani Kiran Nimmagadda Greeshma Pulimi Keerthi Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Dept. of Electronics And Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Dept. of Computer and Communication Engineering Amrita School Of Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798350384659

ISBN: (纸本)9798350384666

One of the abnormal cardiovascular conditions with the greatest rate of increase is heart failure (HF). There is a lot of correlation in the exterior symptoms observed that are typically ignored, particularly when there is progression from one stage to another. Planning an efficient treatment requires grouping patients into different phenotypic categories. In CMR imaging, these conditions show damaged heart muscles. Understanding the classification performance of ELM aided by optimal texture features is the main aim of the proposed work. In this study, Krawtchouk moment and the co-occurrence of neighboring sparse local ternary pattern descriptors are used to extract texture and anatomical information of LV. However, an effective feature selection strategy is required to handle the high dimensionality of the feature vector. The primary benefit of the Pelican optimization algorithm (POA), which takes inspiration from nature, is its capacity to carry out both global and local searches effectively. This paper suggests usage of multi-objective POA to optimize the proportion of extracted features and improve the performance of the ELM classifier. The people with various HF stages have been diagnosed with the maximum accuracy of 95.7 % as a result of this inclusion. The enhanced traits have distinguished moderate and severe HF patients from control participants with significant performance. The proposed work further shows the impact of tissue characterization from CMR image and optimized features-based classification on the HF stage detection.

关键词： Heart Magnetic resonance imaging Myocardium Feature extraction Prediction algorithms Vectors Planning

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An Enhanced System on Chip-Based Sobel Edge Detector

An Enhanced System on Chip-Based Sobel Edge Detector

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Telecommunications Conference (ITC-Egypt), International

作者： Ahmed S. Khalil Mohamed Shalaby Emad Hegazi Electronics & Communications dept Faculty of Engineering Ain-Shams University Cairo Egypt Computer Science dept Arab Academy for Science Technology Maritime Transport Heliopolis Cairo Egypt

Nowadays real-time image processing has become a great challenge because of the use of high-resolution camera sensors, which produce HD video streaming with high resolution and frame rate. As a result, processing this huge amount of data on serial processor became a big challenge. Programmable logic such as FPGA plays an important role in solving this problem by using parallel processing techniques like pipelining. The advances in the system on chip (SOC) technology allow researchers to develop complex heterogeneous systems that can be used in real-time image processing. In this paper, we present a hardware design implementation for accelerating Sobel edge detector by applying some optimization techniques such as line buffer and memory window technique, pipeline technique, unrolling for parallel processing technique, and loop-flatten technique. The experimental results of this design are presented and a comparison between this design and related work is discussed.

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Enhanced LSTM with Attention Mechanism for Early Detection of Parkinson’s Disease through Voice Signals

arXiv

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arXiv 2025年

作者： Mohammadigilani, Arman Attar, Hani Chimeh, Hamidreza Ehsani Karami, Mostafa Electrical and Computer Engineering Polytechnic University of Turin Turin Italy Faculty of Engineering Zarqa University Zarqa Jordan College of Business Administration University of Business and Technology Jeddah Saudi Arabia Electronics and Telecommunications Memorial University of Newfoundland St. John’s Canada

Parkinson’s disease (PD) is a neurodegenerative condition characterized by notable motor and non-motor manifestations. The assessment tool known as the Unified Parkinson’s Disease Rating Scale (UPDRS) plays a crucial role in evaluating the extent of symptomatology associated with Parkinson’s Disease (PD). This research presents a complete approach for predicting UPDRS scores using sophisticated Long Short-Term Memory (LSTM) networks that are improved using attention mechanisms, data augmentation techniques, and robust feature selection. The data utilized in this work was obtained from the UC Irvine Machine Learning repository. It encompasses a range of speech metrics collected from patients in the early stages of Parkinson’s disease. Recursive Feature Elimination (RFE) was utilized to achieve efficient feature selection, while the application of jittering enhanced the dataset. The Long Short-Term Memory (LSTM) network was carefully crafted to capture temporal fluctuations within the dataset effectively. Additionally, it was enhanced by integrating an attention mechanism, which enhances the network’s ability to recognize sequence importance. The methodology that has been described presents a potentially practical approach for conducting a more precise and individualized analysis of medical data related to Parkinson’s disease. © 2025, CC BY.

关键词： Long short-term memory

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Effect of TiO2 Nanoparticle on PEMA-Based Solid Polymer Electrolyte

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Macromolecular Symposia 2023年第1期407卷 2200121-2200121页

作者： Singh, Palvinder Sachdeva, Amit Bhargava, Cherry Kakroo, Sunanda Department of Computer Science and Engineering Chandigarh University Gharuan Punjab Mohali140413 India School of Electrical and Electronics Engineering Lovely Professional University Punjab Phagwara144411 India Department of Electronics and Telecommunication Engineering Symbiosis Institute of Technology Maharashtra Pune India Department of Physics Faculty of Science Jazan University Jazan Saudi Arabia

The key goals in developing electrolytes for batteries and solar panels are mechanical strength, ionic conductivity, leakage resistance, and safety. To improve ionic conductivity and mechanical strength, a PEMA-based electrolyte with potassium iodide as salt, ethylene carbonate as plasticizer, and nanofillers is used. To make a thin polymer matrix film, a solution casting approach is used. PEMA+40% wt. KI+60% wt. EC has a maximum ionic conductivity of 4.65×10−5 S cm-1 when measured using the LC method. After adding CNT, the conductivity of this sample reaches 2.95×10−3 S cm-1. Scanning electron microscopy is used to analyze the surface morphology and crystallinity determined by XRD measurements. FTIR research verifies the existence of several components in solid polymer electrolyte. © 2023 Wiley-VCH GmbH.

关键词： Ionic conductivity

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Enhanced Beam Controllability ⨉ Butler Matrix with Digital Phase Shifters

Enhanced Beam Controllability ⨉ Butler Matrix with Digital ...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Hao Wan Jin Xu Lei Zhu School of Electronics and Information Northwestern Polytechnical University Xi’an P.R. China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China

In this paper, a new method for designing a reconfigurable $4 \times 4$ Butler matrix is proposed with digital phase shifters (PSs). The equation for the relationship between digital PSs and phase differences (PD) of the sequenced ports is derived and discussed. With these derived equations, more PDs can be achieved by changing the value of the PSs. The design concept is demonstrated by a Butler Matrix composed of 4 transformer-based couplers and 4 PSs based on open-/short-circuit microstrip line-loaded slotline, which produce total of 16 PDs with compact size approximately to 4th order Butler matrix.

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One-for-all: bridge the gap between heterogeneous architectures in knowledge distillation 23

One-for-all: bridge the gap between heterogeneous architectu...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Zhiwei Hao Jianyuan Guo Kai Han Yehui Tang Han Hu Yunhe Wang Chang Xu School of information and Electronics Beijing Institute of Technology and Huawei Noah's Ark Lab. School of Computer Science Faculty of Engineering The University of Sydney Huawei Noah's Ark Lab. School of information and Electronics Beijing Institute of Technology

Knowledge distillation (KD) has proven to be a highly effective approach for enhancing model performance through a teacher-student training scheme. However, most existing distillation methods are designed under the assumption that the teacher and student models belong to the same model family, particularly the hint-based approaches. By using centered kernel alignment (CKA) to compare the learned features between heterogeneous teacher and student models, we observe significant feature divergence. This divergence illustrates the ineffectiveness of previous hint-based methods in cross-architecture distillation. To tackle the challenge in distilling heterogeneous models, we propose a simple yet effective one-for-all KD framework called OFA-KD, which significantly improves the distillation performance between heterogeneous architectures. Specifically, we project intermediate features into an aligned latent space such as the logits space, where architecture-specific information is discarded. Additionally, we introduce an adaptive target enhancement scheme to prevent the student from being disturbed by irrelevant information. Extensive experiments with various architectures, including CNN, Transformer, and MLP, demonstrate the superiority of our OFA-KD framework in enabling distillation between heterogeneous architectures. Specifically, when equipped with our OFA-KD, the student models achieve notable performance improvements, with a maximum gain of 8.0% on the CIFAR-100 dataset and 0.7% on the ImageNet-1K dataset. PyTorch code and checkpoints can be found at https://***/Hao840/OFAKD.

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