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arXiv 2023年

作者： Azad, Reza Heidari, Moein Yilmaz, Kadir Hüttemann, Michael Karimijafarbigloo, Sanaz Wu, Yuli Schmeink, Anke Merhof, Dorit Faculty of Electrical Engineering and Information Technology RWTH Aachen University Aachen Germany School of Electrical Engineering Iran University of Science and Technology Tehran Iran Faculty of Informatics and Data Science University of Regensburg Regensburg Germany

Semantic image segmentation, the process of classifying each pixel in an image into a particular class, plays an important role in many visual understanding systems. As the predominant criterion for evaluating the performance of statistical models, loss functions are crucial for shaping the development of deep learning-based segmentation algorithms and improving their overall performance. To aid researchers in identifying the optimal loss function for their particular application, this survey provides a comprehensive and unified review of 25 loss functions utilized in image segmentation. We provide a novel taxonomy and thorough review of how these loss functions are customized and leveraged in image segmentation, with a systematic categorization emphasizing their significant features and applications. Furthermore, to evaluate the efficacy of these methods in real-world scenarios, we propose unbiased evaluations of some distinct and renowned loss functions on established medical and natural image datasets. We conclude this review by identifying current challenges and unveiling future research opportunities. Finally, we have compiled the reviewed studies that have open-source implementations at our GitHub1 © 2023, CC BY.

关键词： Medical imaging

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Advancements in cheating detection algorithms in FPS games

Advancements in cheating detection algorithms in FPS games

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2024 International Conference on Computer Application and Information Security, ICCAIS 2024

作者： Xu, Ziwen Yu, Ruotong Liang, Yan Chen, Zihan Wan, Ye School of Computer Science and Technology Tongji University Shanghai201804 China Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College Guangdong Zhuhai519087 China Luddy School of Informatics Computing and Engineering Indiana University of Bloomington Indiana BloomingtonIN47405 United States Guangdong Guangya High School Guangdong Guangzhou510000 China School of Computer Science and Technology Northeastern University Hebei Qinhuangdao066000 China

ISBN: (纸本)9781510689312

Over the past two decades, the increasing variety of cheating techniques in FPS games has led to the development of cheating detection algorithms. This literature review provides a chronological review of advancements in cheating detection techniques. Early methods, such as avatar trajectory-based detection, focused on behavioral analysis and identified bots by analyzing movement patterns. A remote anomaly-based system called Fides was presented to detect client-side manipulations with client-server architectures. With the emergence of machine learning, a variety of supervised learning methods have been introduced into the field of game detection to achieve real-time detection. More recent studies have been more innovative. Traps like the "bait-target" technique were introduced to detect cheating mechanisms that mimic human behavior. Methods combining deep learning and computer vision were proposed to detect complex cheating based on visual images. Overall, this review shows the diversity of cheat detection algorithms that have evolved to maintain the fairness of competitive gaming environments. © The Authors.

关键词： Supervised learning

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A Novel Deep Reinforcement Learning Method for Computation Offloading in Multi-User Mobile Edge Computing with Decentralization

A Novel Deep Reinforcement Learning Method for Computation O...

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International Conference on Advanced Technologies for Communications, ATC

作者： Nguyen Chi Long Trinh Van Chien Ta Hai Tung Van Son Nguyen Trong-Minh Hoang Nguyen Ngoc Hai Dang School of Information and Communications Technology Hanoi University of Science and Technology Vietnam Faculty of Electrical and Electronic Engineering Hanoi Open University Vietnam Posts and Telecommunications Institute of Technology Hanoi Vietnam Faculty of Informatics University of Debrecen Hungary

ISBN: (数字)9798350353983

ISBN: (纸本)9798350353990

Mobile edge computing (MEC) allows appliances to offload workloads to neighboring MEC servers that have the potential for computation-intensive tasks with limited computational capabilities. This paper studied how deep reinforcement learning (DRL) algorithms are used in an MEC system to find feasible decentralized dynamic computation offloading strategies, which leads to the construction of an extensible MEC system that operates effectively with finite feedback. Even though Deep Deterministic Policy Gradient (DDPG) algorithm subject to their knowledge of the MEC system can be used to allocate powers of both computation offloading and local execution, to learn a computation offloading policy for each user independently, we realized that this solution still has some inherent weaknesses. Hence, we introduced a new approach for this problem based on the Twin Delayed DDPG algorithm, which enables us to overcome this proneness and investigate cases where mobile users are portable. Numerical results showed that individual users can autonomously learn adequate policies through the proposed approach. Besides, the performance of the suggested solution exceeded the conventional DDPG-based power control strategy.

关键词： Multi-access edge computing Heuristic algorithms Power control Deep reinforcement learning Servers

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EEG Analysis of Human Perception based on Video-Audio Stimuli 1

EEG Analysis of Human Perception based on Video-Audio Stimul...

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1st International Conference on Smart Technologies Communication and Robotics, STCR 2021

作者： Manochitra, S. Partheepan, Ravinthiran Kalasalingam Institute of Technology Faculty of Computer Science and Engineering Tamilnadu Virudhunagar India Vytautas Magnus University Faculty of Informatics Master Programme - Applied Informatics Kaunas Lithuania

ISBN: (纸本)9781665418065

Emotions plays a potential role in human computer interaction which are having an obligatory models of cognitive measures. The emotions are dominated by the human physiological communication channels. Those emotions could affect several human activities like learning, decision making, communication, perception, cognitive and so on. Also, some of the emotions are quite difficult to measure and interpret and having difficulty in incorporating them into a technology and design. On the other hand, state of the technologies has enabled us to capture the emotions and integrate them for the use of human computer interaction contexts. This paper delivers an attempt to model the emotions using electroencephalography (EEG). The video stimuli for the two representatives are based on a few negative, positive and neutral contents were shown to volunteers and EEG data was obtained. Further, EEG analysis were experimented and collected about their emotional states with subject's self reports. This study determines that the human emotions could be modelled for affect assessment module or for the usage in human computer interaction and affect based intelligent interactions. © 2021 IEEE.

关键词： Human computer interaction

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Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers

arXiv

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arXiv 2023年

作者： Azad, Reza Kazerouni, Amirhossein Sulaiman, Alaa Bozorgpour, Afshin Aghdam, Ehsan Khodapanah Jose, Abin Merhof, Dorit Faculty of Electrical Engineering and Information Technology RWTH Aachen University Germany School of Electrical Engineering Iran University of Science and Technology Iran Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Faculty of Informatics and Data Science University of Regensburg Germany Department of Electrical Engineering Shahid Beheshti University Iran

Medical image segmentation is a critical task that plays a vital role in diagnosis, treatment planning, and disease monitoring. Accurate segmentation of anatomical structures and abnormalities from medical images can aid in the early detection and treatment of various diseases. In this paper, we address the local feature deficiency of the Transformer model by carefully re-designing the self-attention map to produce accurate dense prediction in medical images. To this end, we first apply the wavelet transformation to decompose the input feature map into low-frequency (LF) and high-frequency (HF) subbands. The LF segment is associated with coarse-grained features, while the HF components preserve fine-grained features such as texture and edge information. Next, we reformulate the self-attention operation using the efficient Transformer to perform both spatial and context attention on top of the frequency representation. Furthermore, to intensify the importance of the boundary information, we impose an additional attention map by creating a Gaussian pyramid on top of the HF components. Moreover, we propose a multi-scale context enhancement block within skip connections to adaptively model inter-scale dependencies to overcome the semantic gap among stages of the encoder and decoder modules. Throughout comprehensive experiments, we demonstrate the effectiveness of our strategy on multi-organ and skin lesion segmentation benchmarks. The implementation code will be available upon acceptance. GitHub. © 2023, CC BY.

关键词： Diseases

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Size-dependent thermomechanical vibration of FGP microbeams using a higher-order shear deformable beam element

Size-dependent thermomechanical vibration of FGP microbeams ...

引用

International Symposium on Applied science 2024, ISAS 2024

作者： Dang, Ngoc Duyen Le, Ngoc Anh T. Le, Cong Ich Faculty of Mechanical Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Graduate University of Science and Technology VAST 18 Hoang Quoc Viet Hanoi Viet Nam Institute of Applied Mechanics and Informatics VAST 291 Dien Bien Phu Ho Chi Minh City Viet Nam Faculty of Mechanical Engineering Le Quy Don Technical University 236 Hoang Quoc Viet Hanoi Viet Nam

The thermoelastic vibration of porous microbeams is explored via a higher-order shear deformable element. The porosities are smoothly graded in the beam thickness, while the elastic moduli are temperature-dependent. The theory of third-order shear deformation is employed to formulate a size-dependent beam element, in which the theory of couple stress theory is used to model the microstructural size effect. The frequencies are predicted for microbeams with different and conditions. The performance of the formulated element is shown through a comparison study. The impacts of the size scale parameter, coefficient of porosities as well as the boundary conditions on the frequencies are highlighted. The impacts of temperature change on the vibration of the porous microbeams are also studied and discussed. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Elastic moduli

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UAV trajectory planning in NOMA-aided UAV-mounted RIS networks: A budgeted Multi-armed bandit approach 17

UAV trajectory planning in NOMA-aided UAV-mounted RIS networ...

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2024 17th International Conference on Computer and Electrical engineering, ICCEE 2024

作者： Hosny, Ramez Hashima, Sherief Hatano, Kohei Zaki, Rokaia M. ElHalawany, Basem M. Electrical Engineering Department Faculty of Engineering at Shoubra Benha University Cairo Egypt Computational Learning Theory Team RIKEN-AIP Fukuoka819-0395 Japan Engineering Dept Egyptian Atomic Energy Authority Cairo13759 Egypt Higher Technology Institute 10th of Ramadan Egypt Department of Informatics Kyushu University Fukuoka819-0395 Japan Higher Institute of Engineering and Technology Kafr El-Shaikh33514 Egypt Kuwait College of Science and Technology Doha District Block 4 93004 Kuwait

Reconfigurable Intelligent Surface (RIS) and Non-Orthogonal Multiple Access (NOMA) can be used as supporting technologies for driving the effective development of Unmanned Aerial Vehicles (UAV) communication systems. Herein, both technologies are combined to widen the millimeter-wave Base Stations (mmWave-BS) coverage range. In this work, we consider UAV Trajectory Planning (UTP) problem to enhance the performance of a NOMA-based UAV-mounted RIS communication network. The problem is formulated using two Budgeted Multi-Armed Bandits (BMAB) schemes. BMAB is a variant of the classical MAB algorithm that considers the random cost of selecting an arm. The UAV performs as a bandit player attempting to maximize its achievable rate (i.e., reward) via accessing different grids in its trajectory. This reward is accomplished simultaneously while minimizing the energy/cost of flying the UAV from one grid to another to preserve its battery lifetime. Hence, two variants of the Budgeted upper confidence bound (BUCB), namely the BUCB1 and BUCB2, are investigated, where the simulations show that both algorithms outperform other benchmarks. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Antennas

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Analysis of selected dielectric parameters of insulating liquids

Analysis of selected dielectric parameters of insulating liq...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Aleksandra Płużek Łukasz Nagi Michał Kozioł Małgorzata Zygarlicka Department of Electrical Power and Renewable Energy Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength.

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Enhancing the Performance of Open Winding Induction Generators for Variable Speed Generator Energy Applications

Enhancing the Performance of Open Winding Induction Generato...

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Electric And Power engineering (EPEi), IEEE International Conference And Exposition On

作者： Marcel Topor Feifei Bu Liu Haozhe Sorin Ioan Deaconu Electrical Engineering and Industrial Informatics Politechnica University of Timisoara Faculty of Engineering of Hunedoara Hunedoara Romania College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Department of Electrical Engineering Institute of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China Electrical Engineering and Industrial Informatics Faculty of Engineering of Hunedoara Hunedoara Romania

ISBN: (数字)9798350356199

ISBN: (纸本)9798350356205

This paper aims to investigate the potential of open winding induction generators (OWIGs) to enhance the efficiency and reliability of renewable energy systems. With the growing demand for sustainable energy solutions, optimizing generator performance is crucial. This study will focus on the design, control strategies, and practical implementation of OWIGs, emphasizing their advantages over conventional induction generators, particularly in wind and hydropower applications.

关键词： Power engineering Induction generators Scalability Windings Reliability engineering Vectors Generators Voltage control Turbines Sliding mode control

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ECG Data Forecasting Based on Linear Models Approach: A Comparative Study 20

ECG Data Forecasting Based on Linear Models Approach: A Comp...

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20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Othman, G. Ben Sidhom, L. Chihi, I. Kamavuako, E.N. Trabelsi, M. El Manar University LAPER Tunis Tunisia Carthage University National Engineering School of Bizerte Tunis Tunisia University of Luxembourg Faculty of Science Technology and Medicine Deptartement of Engineering Kirschberg Luxembourg King's College London E. N. Kamavuako Department of Informatics London United Kingdom Kuwait College of Science and Technology M. Trabelsi Electronic and Communications Engineering Department Kuwait City Kuwait

ISBN: (纸本)9798350332568

This paper investigates the replacement of the surface electrodes (physical sensors) measuring the electrocardiogram (ECG) signals by forecasting linear algorithms. The aim is to test the ability to overcome the loss of information in case of failure of any electrode. From real ECG signals measured in different auscultation sites, the ability to predict the ECG signal of one site depending on another site is evaluated by 3 methods. In this paper, based on quantitative criteria, a comparative study between Linear regression (LR) model, K-nearest neighbors model (KNN) and Random forest regression (RFR). The advantages and drawbacks of each one are also highlighted also that the three models are very accurate in building a new ECG *** similar to the real signal. © 2023 IEEE.

关键词： Forecasting

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