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Deep Feature Fusion Based Brain Tumor Classification From Imbalance MRI Dataset Using Weighted Loss Functions

Deep Feature Fusion Based Brain Tumor Classification From Im...

引用

Power, electrical, and Electronics and Industrial Applications (PEEIACON), IEEE International Conference on

作者： Taieba Tasnim Farjana Parvin Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798331517984

ISBN: (纸本)9798331517991

Deep learning using MRI images to classify brain tumours presents a significant challenge due to imbalanced training datasets, where one tumor type may have far more samples than others. The overrepresented class may perform worse in classifiers as a result of this imbalance. In order to tackle this issue, the paper examines how feature learning in CNNs is affected by weighted loss functions to manage data imbalance. The article propose deep feature fusion, where particular CNN model features that were trained using three distinct loss functions are fused and classified using softmax classifier. This approach lead to notable improvements in brain tumor classification compared to a CNN trained with standard cross-entropy loss. Notably, the proposed methods substantially reduce classification errors between uneven class samples. The proposed model achieved an impressive 94.5% classification accuracy, accompanied by an average Fl-score of 94.6%, average precision of 94.6 %, and average recall of 95%. These findings underscore the effectiveness of our methodology in improving brain tumor classification accuracy, offering a promising avenue for more reliable diagnosis and treatment planning in clinical settings,

关键词： Training Representation learning Adaptation models Accuracy Magnetic resonance imaging Brain tumors Brain modeling Planning Reliability Standards

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Designing a Graphics Processing Unit for 2D Rendering on FPGA for Educational Purpose

Designing a Graphics Processing Unit for 2D Rendering on FPG...

引用

International Conference on Advancement in electrical and Electronic engineering (ICAEEE)

作者： Rupak Saha Nahin Ul Sadad Md. Nazrul Islam Mondal Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

In this paper, design and implementation of a 2D graphics processing hardware unit using FPGA for educational purpose is presented. We propose a more simple & minimalist GPU architecture, which is flexible and easy to understand than existing industrial GPUs. We present a platform for understanding GPU architecture by implementing of graphics algorithms on FPGA for students to use this in laboratories. Students can be benefited from this work as it can be used as a base understanding tool in terms of GPU architecture. It can also be extended to be used in cross disciplinary applications like 3D rendering, computer vision and signal processing visualisation. This research includes descriptions of hardware realization of 2D rasterization rendering algorithms. Hardware Description Language (HDL) called verilog is utilized in designing the architecture. Xilinx Vivado Design Suite software is used for FPGA implementation, targeting Artix 7 FPGA board, which allows users to comprehend the fundamental ideas of hardware design and their applications in graphics rendering.

关键词： Visualization Three-dimensional displays Heuristic algorithms Graphics processing units Signal processing algorithms computer architecture Rendering (computer graphics)

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DC Fault Detection Using Time Derivative of High-Pass Filter Response in MTDC Systems

DC Fault Detection Using Time Derivative of High-Pass Filter...

引用

Annual Conference of Industrial Electronics Society

作者： Saad Ahmed Khan Abhisek Ukil Nirmal-Kumar C. Nair Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In the DC fault event, DC link capacitors immediately discharge a colossal current of high frequency. These large currents of high frequencies can instantly damage the components attached to the DC transmission system. Therefore, a rapid and robust DC fault detection topology is necessary, facilitating protection coordination in forthcoming Multi-Terminal Direct Current (MTDC) systems. This study introduces a novel fault detection technique using the time derivative of the High Pass Filter (HPF) response to identify fault currents in just a few microseconds (µs). This topology enables protection coordination for modern MTDC systems. Furthermore, this technique can identify different types of DC faults and remains unaffected by AC faults and load variation.

关键词： Fault diagnosis Accuracy Fault detection Load management electrical fault detection Topology Power systems High frequency Passband Protection

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Enhancement of information propagation on the highway in VANET based on Multiple Vehicle Class 13

Enhancement of information propagation on the highway in VAN...

引用

13th International Conference on Information and Communication Technology Convergence, ICTC 2022

作者： Mahmood, Dhari Ali Reja, Ahmed Hameed Mahmood, Ahmed Mamoon University of Technology- Iraq Dept. of Computer Engineering Baghdad Iraq University of Technology- Iraq Dept. of Electromechanical Engineering Baghdad Iraq College of Engineering Salahhdin University Electrical and Electric Dept. Erbil Iraq

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

The Intelligent Transportation System (ITS) has become a part of smart cities and road safety. Based on communication systems technologies, ITS can solve several road issues, such as accidents. A vehicular ad-hoc network can be part of ITS. We analyze the connectivity characteristics, the effectiveness of message propagation distance on the network connectivity, and the delivery of alert message delay. Several factors can affect the delivery of alert messages within a suitable time(i.e., low connectivity between vehicles). The free-flow state allows drivers to drive their vehicles as they want;the flow and speed of vehicles are independent. The different lanes on the highway have associated speed limits;multi-speed on the road can increase the connectivity among the vehicles and lead to minimizing the message delivery time. The fast vehicle acts as a bridge node, and it can bridge the gap between different clusters and allow information to be shared with other clusters. © 2022 IEEE.

关键词： Vehicles

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Effects of Mismatch on IC-Equipped Programmable Metasurfaces with Multibeam Functionality

Effects of Mismatch on IC-Equipped Programmable Metasurfaces...

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Antennas and Propagation Society International Symposium

作者： Kypros M. Kossifos Julius Georgiou Marco A. Antoniades Dept. of Electrical & Computer Engineering University of Cyprus Nicosia Cyprus Dept. of Electrical Computer & Biomedical Engineering Toronto Metropolitan University Ontario Canada

Integrated circuit (IC) technology can be incorporated in programmable metasurfaces (PMSFs) and reduce their cost and power consumption while increasing their electromagnetic manipulation capabilities. Such improvements can succour the incorporation of PMSFs as a common telecommunication technology. In order for this to be realised, the reproducibility and reliability of IC-equipped PMSFs need to be addressed. A study is presented on effects of IC mismatch on the performance of a PMSF with multibeam functionality. A mismatch of 10% to 40% of the nominal IC response is used and the effects on the far field are presented.

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Model Predictive Virtual Oscillator Controlled Inverters in Islanded Mode of Operation

Model Predictive Virtual Oscillator Controlled Inverters in ...

引用

Annual Conference of Industrial Electronics Society

作者： Sima Azizi Aghdam Mohammed Agamy Dept. of Electrical and Computer Engineering University at Albany SUNY Albany NY USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Virtual Oscillator Control (VOC) represents a decentralized control technique in the time domain, offering promising prospects such as fast dynamic response, accurate power sharing, and synchronization among paralleled inverters in islanded mode. However, it requires inner voltage-current loops for voltage regulation at the inverter output. These inner loops have conventionally relied on linear controllers such as Proportional–integral(PI) or Proportional-Resonant (PR), contributing to complexity and limiting dynamic response. This paper introduces an alternative to conventional linear loops by employing Finite-set Model Predictive Control (FS-MPC). By integrating the VOC and FS-MPC, the voltage at the output of the inverter can be predicted, and the error of tracking reference be minimized. Also, within the proposed method, a multi-objective optimization problem can be formulated enabling over-current limiting capabilities. It also facilitates a simplified control structure, broad bandwidth, and faster dynamic response by removing the need for PWM and inner linear controllers. Simulation results validate the efficacy of the proposed approach for single and multiple paralleled inverters.

关键词： Dynamic response Limiting Simulation Pulse width modulation Inverters Synchronization Voltage control Time-domain analysis Oscillators Predictive control

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Duration-Based Investigation of User Content Choices in the Exit of Filter Bubbles

Duration-Based Investigation of User Content Choices in the ...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Rabiatu Bunza Dept. of Computer Science Faculty of Science and Engineering Swansea University United Kingdom

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

Content personalization on social platforms has been linked to the creation of filter bubbles. The algorithms provide content recommendations based on the user’s browsing history and interests, which limits content diversity. Studies have been conducted on platforms such as Facebook and YouTube to investigate user awareness and strategies to exit filter bubbles. However, no study has employed a multi-platform, user-centered perspective in investigating filter bubble exit through change in search content, as well as the duration of the content transition across multiple platforms. This study examines the duration of user exit of filter bubbles, across three social platforms; TikTok, YouTube Shots, and Instagram Reels, as well as the impact of word similarity on the duration of the transition between contents, across the platforms. The methodology applied involved triggering the filter bubble effect through user interactions with the search content across the different platforms. Findings revealed that the mean time of a transition between search terms on TikTok is significantly higher than the mean time on Instagram reels, and YouTube shorts. Similarly, the study identified differences in the duration of transition across the different platforms, due to the similarity of the search terms. Apart from improving user awareness of a filter bubble exit strategy, this study contributes to Human-computer Interaction research by highlighting some design implications for future social media application design.

关键词： Human computer interaction Video on demand Social networking (online) Psychology Filtering algorithms Web sites Multimedia communication

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Adaptive Strategies for Scalable and Heterogeneous VANET Network 5

Adaptive Strategies for Scalable and Heterogeneous VANET Net...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Thangam, S. Jha, Priyanshu Hawari, Jawed Sah, Nabin Kumar Jain, Nikunj Jesy Janet Kumari, J.J. Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India College of Computing and Information Sciences University of Technology and Applied Sciences It Department Shinas Oman

ISBN: (纸本)9798350385649

Despite technological advancements, Vehicular Ad-hoc Networks (VANETs) continue to face challenges related to reliability and high-speed mobility. This study focuses on enhancing scalability, improving mobility, and addressing network heterogeneity in the context of data dissemination. Data dissemination involves the distribution or transmission of statistical data to users. Tools like NS3, SUMO utilizing OSM for realistic traffic simulations, MATLAB for Data Analysis and evaluation of various protocols like ADHOC, Dynamic Source Routing (DSR), Optimized Link State Routing Protocol (OLSR), Destination Sequenced Distance Vector Routing (DSDV). The research aimed to refine VANET simulations for effective decision making, as its primary objective data dissemination i.e. distribution or transmission of statistical data to users, forming the central focus of this investigation. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Exploring the Efficacy of Modified Transfer Learning in Identifying Parkinson's Disease Through Drawn Image Patterns

Exploring the Efficacy of Modified Transfer Learning in Iden...

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Information and Communication Technology (ICICT), International Conference on

作者： Nabil Daiyan Md Rakibul Haque Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798331508227

ISBN: (纸本)9798331508234

Parkinson's disease (PD) is a progressive neurode-generative condition characterized by the death of dopaminergic neurons, leading to various movement disorder symptoms. Early diagnosis of PD is crucial to prevent adverse effects, yet traditional diagnostic methods are often cumbersome and costly. In this study, a machine learning-based approach is proposed using hand-drawn spiral and wave images as potential biomarkers for PD detection. Our methodology leverages convolutional neural networks (CNNs), transfer learning, and attention mechanisms to improve model performance and resilience against overfitting. To enhance the diversity and richness of both spiral and wave categories, the training dataset undergoes augmentation to increase the number of images. The proposed architecture comprises three phases: utilizing pre-trained CNNs, incorporating custom convolutional layers, and ensemble voting. Employing hard voting further enhances performance by aggregating predictions from multiple models. Experimental results show promising accuracy rates. For spiral images, weighted average precision, recall, and F1-score are 90%, and for wave images, they are 96.67%. After combining the predictions through ensemble hard voting, the overall accuracy is 93.3%. These findings underscore the potential of machine learning in early PD diagnosis, offering a non-invasive and cost-effective solution to improve patient outcomes.

关键词： Training Spirals Attention mechanisms Accuracy Parkinson's disease Computational modeling Transfer learning Transforms Predictive models Resilience

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DiracDiffusion: denoising and incremental reconstruction with assured data-consistency 24

DiracDiffusion: denoising and incremental reconstruction wit...

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Proceedings of the 41st International Conference on Machine Learning

作者： Zalan Fabian Berk Tinaz Mahdi Soltanolkotabi Dept. of Electrical and Computer Engineering University of Southern California Los Angeles CA

Diffusion models have established new state of the art in a multitude of computer vision tasks, including image restoration. Diffusion-based inverse problem solvers generate reconstructions of exceptional visual quality from heavily corrupted measurements. However, in what is widely known as the perception-distortion tradeoff, the price of perceptually appealing reconstructions is often paid in declined distortion metrics, such as PSNR. Distortion metrics measure faithfulness to the observation, a crucial requirement in inverse problems. In this work, we propose a novel framework for inverse problem solving, namely we assume that the observation comes from a stochastic degradation process that gradually degrades and noises the original clean image. We learn to reverse the degradation process in order to recover the clean image. Our technique maintains consistency with the original measurement throughout the reverse process, and allows for great flexibility in trading off perceptual quality for improved distortion metrics and sampling speedup via early-stopping. We demonstrate the efficiency of our method on different high-resolution datasets and inverse problems, achieving great improvements over other state-of-the-art diffusion-based methods with respect to both perceptual and distortion metrics.

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