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arXiv 2025年

作者： Deschênes, Anthony Georges, Rémi Subakan, Cem Ugulino, Bruna Henry, Antoine Morin, Michael Dep. of Wood and Forest Sciences QC Canada Dep. of Computer Science and Software Engineering Dep. of Operations and Decision Systems QC Canada FORAC Research Consortium Université Laval QC Canada Mila-Quebec AI Institute QC Canada FPInnovations QC Canada Concordia University QC Canada

In recent years, the wood product industry has been facing a skilled labor shortage. The result is more frequent sudden failures, resulting in additional costs for these companies already operating in a very competitive market. Moreover, sawmills are challenging environments for machinery and sensors. Given that experienced machine operators may be able to diagnose defects or malfunctions, one possible way of assisting novice operators is through acoustic monitoring. As a step towards the automation of wood-processing equipment and decision support systems for machine operators, in this paper, we explore using a deep convolutional autoencoder for acoustic anomaly detection of wood planers on a new real-life dataset. Specifically, our convolutional autoencoder with skip connections (Skip-CAE) and our Skip-CAE transformer outperform the DCASE autoencoder baseline, one-class SVM, isolation forest and a published convolutional autoencoder architecture, respectively obtaining an area under the ROC curve of 0.846 and 0.875 on a dataset of real-factory planer sounds. Moreover, we show that adding skip connections and attention mechanism under the form of a transformer encoder-decoder helps to further improve the anomaly detection capabilities. © 2025, CC BY.

关键词： Competition

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Studying Risks of Hybrid Reengineering on Air-Transportation Systems Management “A Case Study on Jordanian Civil Aviation Regulatory Commission (CARC)”

Studying Risks of Hybrid Reengineering on Air-Transportation...

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Information Technology (ACIT)

作者： Al Refai Mohammed N. Taani M.K. K. Ahmed Ali Otoom Ghassan Samara Hanandeh E. S Hayel Khafajeh Software Engineering Dep. Zarqa University Zarqa Jordan Cybersecurity and Cloud Computing Dep. Applied Science Private University Amman Jordan Department of Computer Science Zarqa University Zarqa Jordan Artificial Intelligence Dep. Zarqa University Zarqa Jordan

This study examines decision-making in software re-engineering within businesses, focusing on the challenges and considerations involved. Financial constraints, time, and staff efforts are critical factors in these decisions. The study identifies difficulties faced by top-level management with legacy systems, existing systems, underused systems, and packaged software due to user resistance and customer dissatisfaction. The primary goal of the study is to assess the importance of software quality factors, especially from the users' perspective, in making re-engineering decisions. It uses the ISO 9126 Model to analyze quality elements in the case study software, aiming to provide guidance for deciding whether to proceed with re-engineering. The study explores functionality, reliability, usability, efficiency, maintainability, and portability as factors influencing re-engineering decisions, based on the ISO 9126 model. To understand user interactions and program performance, the study used unstructured participant observation in the case study software, highlighting the challenges faced by top management due to user resistance. These findings were further confirmed through face-to-face interviews with software users and dep.rtment employees, offering insights into their perspectives on software quality elements. The results reveal that, despite some flaws, the system has valuable features and capabilities. Most employees express a desire to undergo re-engineering to enhance service quality, align with ISO 9126 standards, and leverage the expertise of competent staff for re-engineering activities.

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Standardization Review on Non-Terrestrial Networks

Standardization Review on Non-Terrestrial Networks

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International Conference on Information Networking

作者： Yeunwoong Kyung Jaewook Lee Haneul Ko Seungmin Oh Jaehwan Lee Youngjun Kim Div. of Info. & Comm. Eng Kongju National University Cheonan Korea Dep. of Info. and Comm. Engineering Pukyong National University Busan Korea Dep. of Electronic Eng Kyung Hee University Yongin-si Korea Dep. of Computer Science and Eng Kongju National University Cheonan Korea School of Computer Science and Eng Kyungnam University Changwon Korea

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

As the demand for global connectivity increases, non-terrestrial networks (NTNs), particularly satellite-based systems, have gained significant attention in communication network standardization. The 3rd Generation Partnership Project (3GPP) has been at the forefront of developing standards that incorporate satellite communications into the broader terrestrial network framework. This paper reviews the progression of NTN standardization, focusing on three key stages: (1) the use of satellites as relays or the next generation NodeBs (gNBs), (2) the integration of user plane functions (UPF) within satellites, and (3) the inclusion of control plane network functions (NFs) within satellites. These developments in standardizations reflect a shift from basic relay functions to fully integrated satellite networks.

关键词： Satellites 3GPP Standards Reviews Trajectory 3GPP Relays Low latency communication Satellite communications Standards Next generation networking

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Exploring Genetic Programming Models in computer-Aided Diagnosis of Skin Cancer Images

Exploring Genetic Programming Models in Computer-Aided Diagn...

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Congress on Evolutionary Computation

作者： Qurrat UI Ain Harith Al-Sahaf Bing Xue Mengjie Zhang School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand Dep. of Cybersecurity Engineering College of Engineering and Info. Technology AlShaab University Baghdad Iraq

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Extracting important information from complex skin lesion images is vital to effectively distinguish between different types of skin cancer images. In addition to providing high classification performance, such computer-aided diagnostic methods are needed where the models are interpretable and can provide knowledge about the discriminative features in skin lesion images. This underlying information can significantly assist dermatologists in identifying a particular stage or type of cancer. With its flexible representation and global search abilities, Genetic Programming (GP) is an ideal learning al-gorithm to evolve interpretable models and identify important features with significant information to discriminate between skin cancer classes. This paper provides an in-dep.h analysis of a recent GP-based feature learning method where different well-developed feature descriptors are integrated into the learning algorithms to extract high-level features for skin cancer image classification. The study explores the effectiveness of utilizing feature learning for this complex task and designing program structure to suit the problem domain as it has shown promising results compared to commonly used feature descriptors and an existing GP-based feature learning method developed for general image classification. This study analyzes the GP-evolved models to identify the prominent features and most effective feature descriptors important for the classification of these skin cancer images. The evolved models are interpretable, they provide knowledge that can assist dermatologists in making diagnoses in real-time clinical situations by identifying prominent skin cancer characteristics captured by the feature descriptors and learned during the evolutionary process.

关键词： Representation learning Visualization Computational modeling Genetic programming Feature extraction Skin Lesions

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Investigation and Study of the Performance of a DVB over Satellite Link Using M-Ary PSK 2

Investigation and Study of the Performance of a DVB over Sat...

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2nd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2022

作者： Bishi, Hager Alshepane, Somya H. Alhaddar, Kheriya F. Alnour, Saaida E. Electronic Technology Collage Communication Dep. Tripoli Libya Higher Institute of Science and Technology EE Department Al Khomes Libya Al-Mergib University Department of Electrical and Computer Engineering Al Khomes Libya Al-Gharefa College of Technical Engineering EE Department Al-Gharefa Libya

ISBN: (数字)9781665479189

ISBN: (纸本)9781665479189

In this paper, the performance of a Digital Video Broadcasting Over Satellite Link, a digital Video second-generation for satellite broadcasting (DVB-S2), was investigated and studied as a case study. The simulation was done by using Matlab in order to evaluate DVB-S2 performance developments in channel coding (LDPC codes) combined with modulation schemes (QPSK and 8-PSK ), code rates, forward error correction (FEC) and transmission channels. The obtained simulation results were graphically presented, where the bit error rate as a function of the signal to noise ratio (S/N) was evaluated as well. © 2022 IEEE.

关键词： Signal to noise ratio

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Robotics in Primary and Secondary Education - The Lego Mindstorms EV3 implementation 6

Robotics in Primary and Secondary Education - The Lego Minds...

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6th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2021

作者： Samara, Elpida Angelidis, Pantelis Kotsiari, Aspasia Kilintzis, Pavlos Giorgos, Avlogiaris Dep. of Regional and Cross Border Development University of Western Macedonia Kozani Greece Dep. of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Dep. of IT Engineering University of Western Macedonia Kozani Greece Dep. Of Mechanical Engineering University of Western Macedonia Kozani Greece Dep. of Statistics and Insurance Science University of Western Macedonia Kozani Greece

ISBN: (纸本)9781665427425

The implementation of educational robotics has been increasingly popular over the recent years, highlighting the benefits that digital technology has brought to education. The ulterior aim of this paper is to investigate the level of acceptance of robotics' implementation on the educational process by the primary and secondary education students in Greece. This is conducted by first presenting Lego Mindstorms EV3 robotic device to the students, by implementing a step-by-step workshop, to introduce them to the basic characteristics of an educational robotic platform. Next, the students are answering a questionnaire indicating their experiences and remarks about the learning process. Their answers are being statistically processed to reveal the crucial points, regarding the implementation of educational robotics in the educational process. The study contains key elements regarding students' perceptions over educational robotics' sector, applied as a primary educational tool. © 2021 IEEE

关键词： Students

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Genetic Optimization Techniques for Enhancing Web Attacks Classification in Machine Learning

Genetic Optimization Techniques for Enhancing Web Attacks Cl...

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IEEE International Symposium on dep.ndable, Autonomic and Secure Computing (DASC)

作者： Ameera S. Jaradat Ahmad Nasayreh Qais Al-Na'amneh Hasan Gharaibeh Rabia Emhamed Al Mamlook Dep. of Computer Science Yarmouk University Irbid Jordan Dep. of Cyber Security and Cloud Computing Applied Science Private University Amman Jordan Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia

Web-based applications are now the preferred approach for delivering a variety of services via the Internet. As a result of the globalization of commerce, web applications have been growing quickly and becoming increasingly complicated. Such applications have a significant security vulnerability in the online environment since they were developed with little experience and without testing or validation. Numerous attackers use this security vulnerability to take control of the program, modify the data, and steal the most crucial information. They may also access all internal, unauthorized items. This work presents a hybrid model that classifies website attacks as benign through the integration of four machine learning algorithms: gradient boost (GB), multilayer perceptron (MLP), logistic regression (LR) and K nearest neighbor (KNN). The work dep.oyed Tree-based Pipeline Optimization Tool (TPOT) that utilizes the Genetic algorithm (GA) to extract the optimal parameter and consequently enhance the model performance. The model underwent evaluation utilizing a data set from the Canadian Institute 2023 that contains various types of attacks. Among these algorithms, GB achieved the best accuracy scores of 95%, 94% and 95% for accuracy, recall and F1-score, respectively.

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Enhanced Patch Antenna Characteristics Analysis and Implementation with DGS and SMS

Enhanced Patch Antenna Characteristics Analysis and Implemen...

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Telecommunications Conference (ITC-Egypt), International

作者： Ahmed F. Miligy Assem H. Elfeky Ahmed S.I Amar M. Abdel-Aleim M Alla M. Eid Mohamed Fathy Abo Sree Electronics and Communication Dep. Air Defence College Alexandria Univerisity Alexandria Egypt Department of Electronics and Communications Engineering Faculty of Engineering Ahram Candian University Cairo Egypt Electronics and Communication Dep. Air Defence College Ain Shams University Cairo Egypt Department of Electronics and Communications Engineering Arab Academy for Science Technology and Maritime Transport Cairo Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

The development of Defected Ground Structures (DGS) and Slab microstrip Structures (SMS) techniques improved the properties of numerous microwave devices. While the DGS and SMS are advantageous in the design of microwave filters and microwave oscillators, they are also utilised in the design of microstrip antennas for various purposes for enhanced patch antenna characteristics, including reducing antenna size, suppressing harmonics, and improving matching. In this paper, the combination of the two techniques helped in enhancing patch antenna characteristics such as return loss, bandwidth, gain, and radiation efficiency. The proposed structures are analyzed, simulated, and implemented using a Roger substrate with ε r = 3.4 and tan = 0.004 using HFSS. The proposed structure introduces improvement of the antenna parameters such as RL = -58 dB, BW = 290 MHz, G = 6 dB, and 90% radiation efficiency at 9 GHz for wireless applications in the x-band.

关键词： Microwave antennas Wireless communication Microstrip filters Patch antennas Microstrip antennas Microwave theory and techniques Microwave oscillators

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Prediction of Electrical Characteristics of a-IGZO TFT Based on Transfer Learning-Based Variational Autoencoder

Prediction of Electrical Characteristics of a-IGZO TFT Based...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Khean-Thye Bea Shih-Shin Hu Wei-Hsuan Lin Da-Zheng Lin Hsin-Hui Hu Xiu-Zhi Chen Ting-Ru Lin Yen-Lin Chen Kun-Ming Chen Wai Khuen Cheng Dep. of Electronic Engineering National Taipei University of Technology Taipei Taiwan Dep. of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Taiwan Semiconductor Research Institute Hsinchu Taiwan Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Malaysia

In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation.

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Deep Learning Technology Used High Dynamic Range Image Reconstruction And Detection

Deep Learning Technology Used High Dynamic Range Image Recon...

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

作者： Bheemalingaiah, M. Srinivasan, R. Nathan, V. Vijey Kolluri, Raju Gupta, Amit J.B Institute of Engineering and Technology Department of CSE Telangana Hyderabad India School of Computer Science and Engineering Galgotia University Department of CSE U.P India SRM TRP Engineering College Department of CSE Tamilnadu Tiruchirappalli India Narasaraopet Engineering College Department of ECE Andhra Pradesh Narasaraopet India J.B Institute of Engineering and Technology Dep. of AI & ML Telangana Hyderabad India

ISBN: (纸本)9798350378092

The suggested remedy for saturated pixels in digital camera photos introduces a brand-new learning-based method for reconstructing images with high dynamic range (HDR). While current techniques concentrate on increasing brightness range, they frequently fall short in producing realistic textures, leading to errors in places that are too saturated. Our method reconstructs an HDR image by using aesthetically beautiful saturated pixels from a low dynamic range (LDR) image. We provide a feature masking strategy to address problems discovered during training, when saturated and well-exposed pixels got comparable convolutional filters, resulting in uncertainty and checkerboard and halo aberrations. This method improves the overall quality of the reconstruction by reducing the contribution of features from saturated regions. Furthermore, in order to guarantee visually pleasing textures in the reconstructed HDR photos, we adjust the perceptual loss function based on *** use a two-step procedure in order to properly train our system. We first train the system for picture in painting on a sizable dataset, and then we modify it for HDR reconstruction. Our method performs exceptionally well even with a small number of HDR photos because it uses an advanced sampling strategy to choose hard training patches from a wide range of settings. Convolutional neural networks, feature masking, perceptual loss, and high dynamic range imagery are important components of our methodology. © 2024 IEEE.

关键词： Convolutional neural networks

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