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arXiv 2023年

作者： Yang, Xinge Fu, Qiang Elhoseiny, Mohamed Heidrich, Wolfgang Department of Computer Science and Electrical and Computer Engineering King Abdullah University of Science and Technology 23955 Saudi Arabia King Abdullah University of Science and Technology Saudi Arabia

—computer vision methods for depth estimation usually use simple camera models with idealized optics. For modern machine learning approaches, this creates an issue when attempting to train deep networks with simulated data, especially for focus-sensitive tasks like Depth-from-Focus. In this work, we investigate the domain gap caused by off-axis aberrations that will affect the decision of the best-focused frame in a focal stack. We then explore bridging this domain gap through aberration-aware training (AAT). Our approach involves a lightweight network that models lens aberrations at different positions and focus distances, which is then integrated into the conventional network training pipeline. We evaluate the generality of network models on both synthetic and real-world data. The experimental results demonstrate that the proposed AAT scheme can improve depth estimation accuracy without fine-tuning the model for different datasets. The code will be available in ***/vccimaging/Aberration-Aware-Depth-from-Focus. © 2023, CC BY-NC-ND.

关键词： Aberrations

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Improved High Step-Up Cockcroft-Walton Magnetic Coupling Inverter

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IEEE Transactions on Circuits and Systems II: Express Briefs 2023年第6期70卷 1981-1985页

作者： Esmaeili, Soroush Khan, Ashraf Ali Jamil, Mohsin Khan, Usman Ali Ahmed, Hafiz Furqan Ahmed, Shehab Memorial University of Newfoundland Department of Electrical and Computer Engineering St. John'sNLA1B 3X7 Canada Yonsei University Department of Electrical and Electronics Engineering Seoul03722 Korea Republic of National Sun Yat-sen University Department of Electrical Engineering Kaohsiung804 Taiwan King Abdullah University of Science and Technology Cemse Division Thuwal23955 Saudi Arabia

An improved dual winding magnetically coupled-inductors inverter based on a Cockcroft-Walton multiplier voltage cell is proposed in this brief. Compared with the conventional generalized Cockcroft-Walton multiplier voltage Z-source inverters, the proposed inverter attains higher voltage gain by decreasing the transformer's turns number. As a result, lower cost, higher efficiency, larger voltage boost factor, and higher density can be realized in the proposed inverter. Furthermore, unlike conventional magnetically coupled impedance source inverters, the proposed topology offers a larger voltage boost factor for small shoot-through duty ratios with a smoother slope, which enhances the practical controllability of the inverter. Hence, a higher modulation ratio can be applied, which results in a better quality of the inverter's waveforms. A clamping circuit is used to reduce the leakage inductance effects of the coupled inductors. As a result, the huge voltage spikes across the inverter bridge are eliminated. In addition, the proposed inverter draws a smooth and continuous input current from the input dc source, which is suitable for renewable energy sources. Detailed, theoretical analysis, simulation and experimental results are provided. © 2004-2012 IEEE.

关键词： Inductance

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Joint Modeling of Multivariate Longitudinal and Survival Outcomes with the R package INLAjoint

arXiv

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arXiv 2024年

作者： Rustand, Denis van Niekerk, Janet Krainski, Elias Teixeira Rue, Håvard Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

This paper introduces the R package INLAjoint, designed as a toolbox for fitting a diverse range of regression models addressing both longitudinal and survival outcomes. INLAjoint relies on the computational efficiency of the integrated nested Laplace approximations methodology, an efficient alternative to Markov chain Monte Carlo for Bayesian inference, ensuring both speed and accuracy in parameter estimation and uncertainty quantification. The package facilitates the construction of complex joint models by treating individual regression models as building blocks, which can be assembled to address specific research questions. Joint models are relevant in biomedical studies where the collection of longitudinal markers alongside censored survival times is common. They have gained significant interest in recent literature, demonstrating the ability to rectify biases present in separate modeling approaches such as informative censoring by a survival event or confusion bias due to population heterogeneity. We provide a comprehensive overview of the joint modeling framework embedded in INLAjoint with illustrative examples. Through these examples, we demonstrate the practical utility of INLAjoint in handling complex data scenarios encountered in biomedical research. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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A Discontinuous Galerkin Time-Domain Scheme to Model Lasing Dynamics in Four-Level Two-Electron Atomic Systems

A Discontinuous Galerkin Time-Domain Scheme to Model Lasing ...

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European Conference on Antennas and Propagation, EuCAP

作者： Ming Dong Liang Chen Ran Zhao Hakan Bagci Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia School of Electronic Science and Engineering Univesirty of Electronic Science and Technology of China (UESTC) Chengdu China

A discontinuous Galerkin time-domain scheme is formulated and implemented to analyze three-dimensional transient lasing dynamics. The proposed scheme solves a coupled system of the Maxwell and the rate equations. The atomic transitions through different energy levels are quantum-mechanically described by a four-level two-electron model, while the electro-magnetic interactions are treated using the Maxwell equations. The resulting solver accounts for the Pauli Exclusion Principle and permits robust simulation of lasing dynamics under optical pumping. Numerical results are presented to demonstrate the applicability and the accuracy of the proposed scheme.

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Near-Perfect Coverage Manifold Estimation in Cellular Networks via Conditional GAN

IEEE Networking Letters

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IEEE Networking Letters 2024年第2期6卷 97-100页

作者： Mondal, Washim Uddin Goyal, Veni Ukkusuri, Satish V. Das, Goutam Wang, Di Alouini, Mohamed-Slim Aggarwal, Vaneet Purdue University School of Industrial Engineering The School of Civil Engineering West LafayetteIN47907 United States Purdue University School of Civil Engineering West LafayetteIN47907 United States Indian Institute of Technology Kharagpur G. S. Sanyal School of Telecommunications Kharagpur721302 India Purdue University School of Industrial Engineering West LafayetteIN47907 United States King Abdullah University of Science and Technology Computer Electrical and Mathematical Sciences and Engineering Division Thuwal23955-6900 Saudi Arabia

This letter presents a conditional generative adversarial network (cGAN) that translates base station location (BSL) information of any Region-of-Interest (RoI) to location-dependent coverage probability values within a subset of that region, called the region-of-evaluation (RoE). We train our network utilizing the BSL data of India, the USA, Germany, and Brazil. In comparison to the state-of-the-art convolutional neural networks (CNNs), our model improves the prediction error (L1 difference between the coverage manifold generated by the network under consideration and that generated via simulation) by two orders of magnitude. Moreover, the cGAN-generated coverage manifolds appear to be almost visually indistinguishable from the ground truth. © 2019 IEEE.

关键词： Stochastic systems

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Optimizing Propagation Predictions for Last-mile Connectivity in a CubeSat Perspective 3

Optimizing Propagation Predictions for Last-mile Connectivit...

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3rd International Conference on Computing and Information technology, ICCIT 2023

作者： Almalki, Faris A. Aljahdalia, Haitham College of Computers and Information Technology Taif University Computer Engineering Department Taif Saudi Arabia King Abdullah University of Science and Technology Core Labs Thuwal Saudi Arabia

ISBN: (纸本)9798350321487

CubeSats is seen as an innovative approach to provide many wireless communications services in a wide footprint coverage manner. However, this could lead to electromagnetic spectrum congestion, which requires larger bandwidths. Thus, optimization approaches and considering of high frequency bands are needed. This work aims to develop an optimized propagation model to enhance the last-mile connectivity of a CubeSat system using an enhanced version of the log-normal shadowing propagation model by considering elevation angle in its formulation. Then, a linear iterative feedback scheme is applied to produce an enhanced approximate solution of the propagation problem. Link budget parameters, Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE) have been used as performance indictors to validate the proposed scheme. Results show that the optimized model outperforms the non-optimized one from link budget and the two regression metric validation perspectives. © 2023 IEEE.

关键词： Mean square error

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Surface Defects Detection of Cylindrical High-Precision Industrial Parts Based on Deep Learning Algorithms: A Review

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Operations Research Forum 2024年第3期5卷 58页

作者： Wei, Li Solihin, Mahmud Iwan Saruchi, Sarah ‘Atifah Astuti, Winda Hong, Lim Wei Kit, Ang Chun School of Computer Science and Technology (School of Software) Guangxi University of Science and Technology Guangxi 545006 China Faculty of Engineering Technology and Built Environment UCSI University Kuala Lumpur 56000 Malaysia Faculty of Manufacturing and Mechatronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan 26600 Malaysia Computer Engineering Department Automotive and Robotics Engineering Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the performance and safety of the systems they are integrated into, they are often subject to stringent quality control measures. Defects on the interior and exterior wall surfaces of these cylindrical parts can severely undermine their function, leading to degraded performance, increased wear, and even catastrophic failures in extreme cases. This article aims to comprehensively summarize the task definition, challenges, mainstream methods, public datasets, evaluation metrics, and other aspects of surface defect detection for high-precision cylindrical parts, in order to help researchers quickly grasp this field. Specifically, the background and characteristics of industrial defect detection are first introduced. Owing to the unique geometric features of cylindrical part surfaces, algorithms and equipment for image data acquisition used in surface defect detection are elaborated in detail. This article presents an extensive overview of state-of-the-art surface defect detection techniques designed for high-precision cylindrical components, all rooted in deep learning. The methods are systematically classified into three main categories: fully supervised, unsupervised, and alternative approaches, based on their data labeling strategies. Additionally, the paper conducts a comprehensive analysis within each category, shedding light on their unique strengths, limitations, and practical use cases. Concluding the discussion, the paper provides insights into future development trends and potential research directions in this field that will lead to manufacturing innovation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Anomaly detection computer vision Deep learning Defect detection High-precision cylindrical parts Image processing Optical illumination

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Sintering-based lithography metal additive manufacturing of chiral mechanical metamaterials with a twist 1

Sintering-based lithography metal additive manufacturing of ...

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1st International Conference on Digital Sovereignty, ICDS 2024

作者： Melentiev, Ruslan Wagih, Ahmed Van Der Heijden, Bram Lubineau, Gilles Grande, Carlos A. Thuwal23955-6900 Saudi Arabia Thuwal23955-6900 Saudi Arabia Mechanical Engineering Program Physical Sciences and Engineering Division Saudi Arabia Thuwal23955-6900 Saudi Arabia Chemical Engineering Program. Physical Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia

Metamaterials are a cla b of materials with extraordinary capabilities derived from their engineered structure. In 2017, Frenzel et al. (science 358, 2017) conceptualized "three-dimensional mechanical metamaterials with a twist,"which convert linear deformation into rotational motion - a mechanical response that surpa bes the bounds of Cauchy continuum mechanics. However, the lack of suitable manufacturing technologies for producing metallic twist metamaterials has precluded their experimental validation and potential applications to date. Herein, 316L-stainle b-steel twist metamaterials are fabricated at various scales using an emerging sintering-based technology - lithography metal manufacturing (LMM) - and their mechanical responses are tested using stereo digital image correlation. Results provide the first empirical evidence of compre bion-induced rotation in steel twist metamaterials and highlight their sensitivity to manufacturing defects. Video, Application 1 Supplementary 1 Video, Application 2 Supplementary 2 Video, Application 3 Supplementary 3 © 2025 The Author(s).

关键词： Sintering

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Towards Efficient In-memory Computing Hardware for Quantized Neural Networks: State-of-the-art, Open Challenges and Perspectives

arXiv

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arXiv 2023年

作者： Krestinskaya, Olga Zhang, Li Salama, Khaled Nabil Electrical and Computer Engineering Program the Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

The amount of data processed in the cloud, the development of Internet-of-Things (IoT) applications, and growing data privacy concerns force the transition from cloud-based to edge-based processing. Limited energy and computational resources on edge push the transition from traditional von Neumann architectures to In-memory Computing (IMC), especially for machine learning and neural network applications. Network compression techniques are applied to implement a neural network on limited hardware resources. Quantization is one of the most efficient network compression techniques allowing to reduce the memory footprint, latency, and energy consumption. This paper provides a comprehensive review of IMC-based Quantized Neural Networks (QNN) and links software-based quantization approaches to IMC hardware implementation. Moreover, open challenges, QNN design requirements, recommendations, and perspectives along with an IMC-based QNN hardware roadmap are provided. © 2023, CC BY.

关键词： Energy utilization

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Tethered UAV-based Communications for Under-connected Near-shore Maritime Areas

Tethered UAV-based Communications for Under-connected Near-s...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Sahar Ammar Osama Amin Basem Shihada Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

Maritime activities, including fisheries, maritime transportation, and surveillance, are expected to transfer mul-timedia data to remote users, which requires the establishment of reliable backhaul communication links from the marine vessels to the core network. Tethered Unmanned Aerial Vehicles (UAV s), which are connected to a sufficient power source and high-data-rate optical fiber, can be adopted in near-shore maritime communications for coverage extension. In this paper, we investigate the use of tethered UAV s in three scenarios, where the UAV can be either installed on the shore, tethered to the ship, or both. To study the coverage performance, we examine the outage probability in each scenario for both uplink and downlink, and we optimize it to derive the optimal UAV placement. Although the optimization problem, in terms of the UAV tether length and the angle it makes with the horizontal, is non-convex, we formulate and solve a simplified problem where the outage probability is minimized with respect to the channel gain to obtain the optimal UAV position. The simulation results show that using two UAVs, one onshore and one on the ship, provides more reliable connectivity on the uplink and downlink compared to the other two scenarios.

关键词： Simulation Probability Autonomous aerial vehicles Downlink Power system reliability Reliability Uplink

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