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Conference on Lasers and Electro-Optics (CLEO)

作者： Zhican Zhou Yuetong Fang Xiangpeng Ou William He Xuhao Wu Renjing Xu David Z. Pan Yating Wan Integrated Photonics lab King Abdullah University of Science and Technology Thuwal Makkah Saudi Arabia Function Hub The Hong Kong University of Science and Technology (Guangzhou) China Department of Electrical and Computer Engineering The University of Texas at Austin United States

We present an optical neural network architecture driven by on-chip quantum dot lasers, achieving 3.5 TOPS/mm 2 theoretical computational density. With an optimized model (reducing programming operations by over 75%)... 详细信息

ISBN: (纸本)9798350369311

关键词： Laser theory Quantum dot lasers Neural networks computer architecture Optical computing programming Optical fiber networks Laser modes System-on-chip High-speed optical techniques

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Age and Gender Classification Using Backpropagation and Bagging Algorithms

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computers, Materials & Continua 2023年第2期74卷 3045-3062页

作者： Ammar Almomani Mohammed Alweshah Waleed Alomoush Mohammad Alauthman Aseel Jabai Anwar Abbass Ghufran Hamad Meral Abdalla Brij B.Gupta Research and Innovation Department Skyline University CollegeP.O.Box 1797SharjahUAE IT-department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan Prince Abdullah Ben Ghazi Faculty of Information and Communication Technology Al-Balqa Applied UniversityAl-SaltJordan School of Information Technology Skyline University CollegeSharjah P.O.Box 1797United Arab Emirates Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Department of Computer Science and Information Engineering Asia UniversityTaizhongTaiwan Department of Computer Science King Abdulaziz UniversityJeddahSaudi Arabia

Voice classification is important in creating more intelligent systems that help with student exams,identifying criminals,and security *** main aim of the research is to develop a system able to predicate and classify gender,age,and ***,a newsystem calledClassifyingVoice Gender,Age,and Accent(CVGAA)is *** and bagging algorithms are designed to improve voice recognition systems that incorporate sensory voice features such as rhythm-based features used to train the device to distinguish between the two gender *** has high precision compared to other algorithms used in this problem,as the adaptive backpropagation algorithm had an accuracy of 98%and the Bagging algorithm had an accuracy of 98.10%in the gender identification *** has the best accuracy among all algorithms,with 55.39%accuracy in the voice common dataset and age classification and accent accuracy in a speech accent of 78.94%.

关键词： Classify voice gender accent age bagging algorithms back propagation algorithms AI classifiers

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Wafer-scale Semiconductor Grafting: Enabling High-Performance, Lattice-Mismatched Heterojunctions

arXiv

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arXiv 2024年

作者： Zhou, Jie Zhang, Qiming Gong, Jiarui Lu, Yi Liu, Yang Abbasi, Haris Qiu, Haining Kim, Jisoo Lin, Wei Kim, Donghyeok Li, Yiran Ng, Tien Khee Jang, Hokyung Liu, Dong Wang, Haiyan Ooi, Boon S. Ma, Zhenqiang Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Electrical and Computer Engineering King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia School of Materials Engineering Purdue University West LafayetteIN47907 United States

Semiconductor heterojunctions are foundational to many advanced electronic and optoelectronic devices. However, achieving high-quality, lattice-mismatched interfaces remains challenging, limiting both scalability and device performance. Semiconductor grafting offers a promising solution by directly forming electrically active, lattice-mismatched heterojunctions between dissimilar materials. However, its scalability and uniformity at the wafer level have yet to be demonstrated. This work demonstrates the achievement of highly uniform, reproducible results across silicon, sapphire, and gallium nitride (GaN) substrates using wafer-scale semiconductor grafting. To illustrate this scalability, we conducted an in-depth study of a grafted Si/GaN heterojunction, examining band alignment through X-ray photoelectron spectroscopy and confirming crystallinity and interfacial integrity with scanning transmission electron microscopy. The resulting p-n diodes exhibit significantly enhanced electrical performance and wafer-scale uniformity compared to conventional approaches. This work establishes wafer-scale semiconductor grafting as a versatile and scalable technology, bridging the gap between laboratory-scale research and industrial manufacturing for heterogeneous semiconductor integration, and paving the way for novel, high-performance electronic and optoelectronic devices. Copyright © 2024, The Authors. All rights reserved.

关键词： Gallium nitride

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Delay Analysis of Multi-Hop Satellite-Terrestrial Networks with Hybrid RF/FSO Links

Delay Analysis of Multi-Hop Satellite-Terrestrial Networks w...

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IEEE International Conference on Communications (ICC)

作者： Fahad S. Alqurashi Osama Amin Basem Shihada Computer Electrical and Mathematical Sciences & Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Makkah Province Kingdom of Saudi Arabia

Industry and academics have shown a strong interest in satellite-terrestrial networks combined with new technologies such as free-space optics (FSO). We propose a downlink satellite-terrestrial network solution combining FSO with site diversity and multi-hop hybrid radio-frequency (RF)/FSO links. Although the proposed network architecture is a cost-effective solution with wide coverage and immunity against different weather conditions, the multi-hop links can degrade its delay performance. Hence, we analyze the network dropping probability and latency to address the hop-count problem for various applications. We validated the derived network performance by Monte-Carlo simulation and showed that this setting could support ultra low latency applications such as medical applications with latency between 3–10 milliseconds, audio/video 2–50 milliseconds, and augmented reality 7–20 milliseconds. Also, the proposed network guarantees 98 % data delivery with 20 nodes.

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Parallel DGTD Algorithm with LTS Scheme for electrical Large Problems Based on Supercomputer

Parallel DGTD Algorithm with LTS Scheme for Electrical Large...

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Electronics Design Automation (ISEDA), International Symposium of

作者： Wenhao Liu Liang Chen Ping Li State Key Laboratory of Radio Frequency Heterogeneous Integration Shanghai Jiao Tong University Shanghai China Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798350352030

ISBN: (纸本)9798350352047

In this paper, we present a nodal discontinuous Galerkin time-domain (NDGTD) algorithm with a parallel scheme for solving transient Maxwell's equations. With the objective of analyzing the electromagnetic characteristics of electrical-large problems, the NDGTD algorithm is implemented on the supercomputer named “Tian- He” utilizing the message passing interface (MPI) for inter-thread communication. Additionally, to enhance time-marching efficiency in dealing with multi-scale problems, the local time stepping (L TS) technique is implemented based on the leapfrog integration scheme. To assess the efficiency and accuracy of the proposed parallel NDGTD algorithm, an investigation into the scattering properties of a stealthy aircraft model and the far-field characteristics of a patch antenna array is conducted.

关键词： Patch antennas Message passing Scattering Aerospace electronics Supercomputers Time-domain analysis Transient analysis

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Dilated convolution neural operator for multiscale partial differential equations

arXiv

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arXiv 2024年

作者： Xu, Bo Liu, Xinliang Zhang, Lei Shanghai Jiao Tong University School of Mathematical Sciences Shanghai200240 China King Abdullah University of Science and Technology Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Shanghai Jiao Tong University School of Mathematical Sciences Institute of Natural Sciences MOE-LSC Shanghai200240 China

This paper introduces a data-driven operator learning method for multiscale partial differential equations, with a particular emphasis on preserving high-frequency information. Drawing inspiration from the representation of multiscale parameterized solutions as a combination of low-rank global bases (such as low-frequency Fourier modes) and localized bases over coarse patches (analogous to dilated convolution), we propose the Dilated Convolutional Neural Operator (DCNO). The DCNO architecture effectively captures both high-frequency and low-frequency features while maintaining a low computational cost through a combination of convolution and Fourier layers. We conduct experiments to evaluate the performance of DCNO on various datasets, including the multiscale elliptic equation, its inverse problem, Navier-Stokes equation, and Helmholtz equation. We show that DCNO strikes an optimal balance between accuracy and computational cost and offers a promising solution for multiscale operator learning. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolution

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Multi-Modal Sensing and Communication for V2V Beam Tracking via Camera and GPS Fusion

Multi-Modal Sensing and Communication for V2V Beam Tracking ...

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Asilomar Conference on Signals, Systems & computers

作者： Mattia Fabiani Diego Silva Asmaa Abdallah Abdulkadir Celik Ahmed M. Eltawil Department of Elect. Energy and Information Engineering “Guglielmo Marconi” University of Bologna Bologna Italy Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal KSA

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Beam alignment is a critical challenge in vehicle-to-vehicle (V2V) communications, particularly at millimeter-wave (mmWave) frequencies, where massive multi-input multi-output (mMIMO) systems rely on high directivity to mitigate propagation losses. The highly dynamic nature of V2V scenarios, characterized by short channel coherence times, complicates channel state information (CSI) acquisition and increases the overhead associated with traditional beam training processes. To address these challenges, we propose a transformer-based beam tracking framework that leverages sensory data, including GPS and camera inputs, to enable efficient and proactive beam alignment without extensive training overhead. GPS data is transformed into relative coordinates, while features including relative velocity and orientation are extracted from this data. Moreover, camera images provide complementary contextual information about the surrounding environment, enhancing the accuracy of beam predictions. The model predicts beam states up to 500 ms ahead using predefined beamforming codebooks, facilitating both precise beam selection and effective blockage mitigation. Trained on the DeepSense V2V dataset, our method demonstrates a reduction of up to 7 dB in power loss and a 26 % improvement in top-5 accuracy compared to a linear interpolation baseline, highlighting the potential of GPS and camera fusion for advancing beam alignment in dynamic V2V mmWave networks.

关键词： Training Accuracy Vehicular ad hoc networks Cameras Transformers Feature extraction Sensors Millimeter wave communication Vehicle dynamics Global Positioning System

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Time and Space Complexity of Deterministic and Nondeterministic Decision Trees: Local Approach

Time and Space Complexity of Deterministic and Nondeterminis...

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IEEE International Conference on Big Data

作者： Kerven Durdymyradov Mikhail Moshkov Computer Electrical and Mathematical Sciences & Engineering Division and Computational Bioscience Research Center King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Extensive research has been conducted on rough set theory, specifically focusing on the study of decision trees (DTs) and decision rule systems (DRSs). This theory addresses several important questions, including the relationship between DTs and DRSs, the tradeoff between time and space for DTs, and the tradeoff for *** objective of this paper is to investigate infinite binary information systems (ISs), each consisting of an infinite set (universe) and an infinite set of two-valued functions (features) defined on the universe. We examine the concept of a task within an IS, which is described by a finite number of features and a mapping that assigns a decision to each combination of feature values. Our analysis focuses on deterministic and nondeterministic DTs (DDTs and NDTs) as algorithms for task-solving, with the restriction that only features from the task description are *** serve as representations of DRSs and can sometimes have lower space complexity compared to the original DRSs. We study the time and space complexity of DTs, specifically examining the depth and the number of nodes in these trees. The obtained results allow us to classify the set of all ISs into three families, enabling the identification of nontrivial relationships between DDTs and DRSs represented by NDTs. For each family, we investigate the tradeoff between time and space for both DDTs and NDTs.

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Bayesian Inference for Non-Synchronously Observed Diffusions

arXiv

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arXiv 2025年

作者： Jasra, Ajay Kamatani, Kengo Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Institute of Statistical Mathematics Tokyo190-0014 Japan Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We consider the problem of Bayesian inference for bi-variate data observed in time but with observation times which occur non-synchronously. In particular, this occurs in a wide variety of applications in finance, such as high-frequency trading or crude oil futures trading. We adopt a diffusion model for the data and formulate a Bayesian model with priors on unknown parameters along with a latent representation for the the so-called missing data. We then consider computational methodology to fit the model using Markov chain Monte Carlo (MCMC). We have to resort to time-discretization methods as the complete data likelihood is intractable and this can cause considerable issues for MCMC when the data are observed in low frequencies. In a high frequency observation frequencies we present a simple particle MCMC method based on an Euler–Maruyama time discretization, which can be enhanced using multilevel Monte Carlo (MLMC). In the low frequency observation regime we introduce a novel bridging representation of the posterior in continuous time to deal with the issues of MCMC in this case. This representation is discretized and fitted using MCMC and MLMC. We apply our methodology to real and simulated data to establish the efficacy of our methodology. © 2025, CC BY.

关键词： Crude oil

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Experimental Impact Analysis of Cyberattacks in Power Systems Using Digital Real-Time Testbeds

Experimental Impact Analysis of Cyberattacks in Power System...

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Power Tech Conference

作者： Kalinath Katuri Ioannis Zografopoulos Ha Thi Nguyen Charalambos Konstantinou Department of Electrical and Computer Engineering Eversource Energy Center University of Connecticut Storrs CT USA CEMSE Division King Abdullah University of Science and Technology (KAUST)

Smart grid advancements and the increased integration of digital devices have transformed the existing power grid into a cyber-physical energy system. This reshaping of the current power system can make it vulnerable to cyber-attacks, which could cause irreversible damage to the energy infrastructure resulting in the loss of power, equipment damage, etc. Constant threats emphasize the importance of cybersecurity investigations. At the same time, developing cyber-physical system (CPS) simulation testbeds is crucial for vulnerability assessment and the implementation and validation of security solutions. In this paper, two separate real-time CPS testbeds are developed based on the availability of local research facilities for impact analysis of denial-of-service (DoS) attacks on microgrids. The two configurations are implemented using two different digital real-time simulator systems, one using the real-time digital simulator (RTDS) with a hardware-in-the-loop (HIL) setup and the other one using OPAL-RT with ExataCPS to emulate the cyber-layer infrastructure. Both testbeds demonstrate the impact of DoS attacks on microgrid control and protection operation.

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