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Analysis of Electromagnetic Scattering from Composite Objects using a Multi-trace Surface Integral Equation Method

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Analysis of Electromagnetic Scattering from Composite Object...

IEEE International Symposium on Antennas and Propagation

作者： Ran Zhao Jun Hu Hakan Bagci Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia School of Electronic Science and Engineering University of Electronic Science and Technology Chengdu China

ISBN: (纸本)9781728146713

The multi-trace domain-decomposition surface integral equation (MT-DD-SIE) originally proposed to analyze electromagnetic scattering from dielectric composite objects is extended to efficiently account for perfect electrically conducting (PEC) bodies. This extension uses a special form of Robin transmission conditions (RTCs) on the surfaces of the PEC bodies to "couple them to the dielectric bodies. Rao-Wilton-Glisson (RWG)-based discretization of these RTCs, which are the only governing equations on PEC surfaces, yields a well-conditioned matrix block. Therefore, PEC bodies are accounted for within the MT-DD-SIE solver without negatively affecting the convergence of the iterative solution. The accuracy and the efficiency of this approach are demonstrated by numerical examples.

关键词： Integral equations Electromagnetic scattering Meetings Dielectrics Convergence

Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning

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arXiv 2023年

作者： Hu, Zhihang Yu, Qinze Guo, Yucheng Wang, Taifeng king, Irwin Gao, Xin Song, Le Li, Yu Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Intelligence Technology Limited Beijing China Computational Bioscience Reseach Center King Abdullah University of Science and Technology Thuwal Saudi Arabia The CUHK Shenzhen Research Institute Hi-Tech Park Shenzhen Nanshan China

Drug combination therapy is a well-established strategy for disease treatment with better effectiveness and less safety degradation. However, identifying novel drug combinations through wet-lab experiments is resource intensive due to the vast combinatorial search space. Recently, computational approaches, specifically deep learning models have emerged as an efficient way to discover synergistic combinations. While previous methods reported fair performance, their models usually do not take advantage of multi-modal data and they are unable to handle new drugs or cell lines. In this study, we collected data from various datasets covering various drug related aspects. Then, we take advantage of large-scale pre-training models to generate informative representations and features for drugs, proteins, and diseases. Based on that, a message-passing graph is built on top to propagate information together with graph structure learning flexibility. This is first introduced in the biological networks and enables us to generate pseudo-relations in the graph. Our framework achieves the state-of-the-art results in comparison with other deep learning-based methods on synergistic prediction benchmark datasets. We are also capable of inferencing new drug combination data in a test on an independent set released by AstraZeneca, where 10% of improvement over previous methods is observed. In addition, we’re robust against unseen drugs and surpass almost 15% AU ROC compared to the second best model. We believe our framework contributes to both the future wet-lab discovery of novel drugs and the building of promising guidance for precise combination medicine. © 2023, CC BY-NC-ND.

关键词： Graphic methods

H2OPUS: A distributed-memory multi-GPU software package for non-local operators

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arXiv 2021年

作者： Zampini, Stefano Boukaram, Wajih Turkiyyah, George Knio, Omar Keyes, David E. Extreme Computing Research Center Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

Hierarchical H2-matrices are asymptotically optimal representations for the discretizations of non-local operators such as those arising in integral equations or from kernel functions. Their O(N) complexity in both memory and operator application makes them particularly suited for large-scale problems. As a result, there is a need for software that provides support for distributed operations on these matrices to allow large-scale problems to be represented. In this paper, we present high-performance, distributed-memory GPU-accelerated algorithms and implementations for matrix-vector multiplication and matrix recompression of hierarchical matrices in the H2 format. The algorithms are a new module of H2Opus, a performance-oriented package that supports a broad variety of H2 matrix operations on CPUs and GPUs. Performance in the distributed GPU setting is achieved by marshaling the tree data of the hierarchical matrix representation to allow batched kernels to be executed on the individual GPUs. MPI is used for inter-process communication. We optimize the communication data volume and hide much of the communication cost with local compute phases of the algorithms. Results show near-ideal scalability up to 1024 NVIDIA V100 GPUs on Summit, with performance exceeding 2.3 Tflop/s/GPU for the matrix-vector multiplication, and 670 Gflops/s/GPU for matrix compression, which involves batched QR and SVD operations. We illustrate the flexibility and efficiency of the library by solving a 2D variable diffusivity integral fractional diffusion problem with an algebraic multigrid-preconditioned Krylov solver and demonstrate scalability up to 16M degrees of freedom problems on 64 *** Codes 65Y05, 65F55, 65R20, 65-04 © 2021, CC BY.

关键词： program processors

Enriching Context Information for Entity Linking with Web Data

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Journal of computer science & technology 2020年第4期35卷 724-738页

作者： Yi-Ting Wang Jie Shen Zhi-Xu Li Qiang Yang An Liu Peng-Peng Zhao Jia-Jie Xu Lei Zhao Xun-Jie Yang Institute of Artificial Intelligence School of Computer Science and TechnologySoochou University Suzhou 215006China iFLYTEK Research Suzhou 215000China State Key Laboratory of Cognitive Intelligence iFLYTEKHefei 230000China Computer Electrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology Jeddah 23955Saudi Arabia Anhui Toycloud Technologg Co. Ltd.Hefei 230000Chira

Entity linking(EL)is the task of determining the identity of textual entity mentions given a predefined knowledge base(KB).Plenty of existing efforts have been made on this task using either"local"information(contextual information of the mention in the text),or"global"information(relations among candidate entities).However,either local or global information might be insufficient especially when the given text is *** get richer local and global information for entity linking,we propose to enrich the context information for mentions by getting extra contexts from the web through web search engines(WSE).Based on the intuition above,two novel attempts are *** first one adds web-searched results into an embedding-based method to expand the mention's local information,where we try two different methods to help generate high-quality web contexts:one is to apply the attention mechanism and the other is to use the abstract extraction *** second one uses the web contexts to extend the global information,i.e.,finding and utilizing more extra relevant mentions from the web contexts with a graph-based ***,we combine the two models we propose to use both extended local and global information from the extra web *** empirical study based on six real-world datasets shows that using extra web contexts to extend the local and the global information could effectively improve the F1 score of entity linking.

关键词： entity linking web search engine (WSE) attention mechanism abstract extraction

Wetting challenges in treatment of raw textile wastewater by membrane distillation: A case study

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Case Studies in Chemical and Environmental Engineering

Case Studies in Chemical and Environmental engineering 2025年 11卷

作者： Rodrigues, Mariana E. Cucciniello, Raffaele Farinha, Andreia Vrouwenvelder, Johannes Fortunato, Luca Biological & Environmental Science & Engineering Division (BESE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Environmental Science & Engineering Program (EnSE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Dipartimento di Chimica e Biologia Università di Salerno Via Papa Paolo Giovanni II Fisiciano SA 84100 Italy Department of Biotechnology Faculty of Applied Sciences Delft University of Technology Van der Maasweg 9 HZ Delft 2629 Netherlands Department of Civil Building and Environmental Engineering University of Napoli Federico II Via Claudio 21 Napoli 80125 Italy

This case study investigated the effectiveness of Direct Contact Membrane Distillation (DCMD) in treating real textile wastewater. Textile wastewater treatment presents a critical challenge in the field of environmental sustainability, requiring innovative approaches for its treatment to mitigate adverse impacts on ecosystems. DCMD emerges as a promising solution for the treatment and reuse of textile wastewater. However, the intricate composition of real textile wastewater represents a major bottleneck for the process, as the effectiveness of DCMD is influenced by numerous factors, complicating its application. In this study, experiments with an untreated sample demonstrate the detrimental impact of suspended solids on membrane performance. The application of simple pretreatment steps prior to DCMD, involving sedimentation and filtration, substantially enhanced the quality of the permeate, resulting in 100 % color removal, 99.99 % turbidity removal, and considerable removal rates for Chemical Oxygen Demand (COD) and Total Organic Carbon (TOC). Nevertheless, wetting remained a significant issue, as evidenced by the persistence of commonly used volatile organic contaminants and surfactants in the textile industry detected within the permeate. The findings in this case study reinforce that DCMD holds promise for textile wastewater treatment but emphasize the necessity of pretreatment and wetting mitigation strategies to fully unlock its potential. This research offers crucial insights for future MD applications in addressing the complexities of textile wastewater treatment. © 2025 The Authors

关键词： Direct contact membrane distillation (DCMD) Industrial wastewater reuse Membrane wetting Optical coherence tomography (OCT) Pretreatment strategies Textile wastewater treatment Volatile organic contaminants

STGIC: a graph and image convolution-based method for spatial transcriptomic clustering

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arXiv 2023年

作者： Zhang, Chen Gao, Junhui Kong, Lingxin Cao, Guangshuo Guo, Xiangyu Liu, Wei School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang China Smart-Health Initiative King Abdullah University of Science and Technology Jeddah Saudi Arabia Marine Science and Technology College Zhejiang Ocean University Zhoushan China

Spatial transcriptomic (ST) clustering employs spatial and transcription information to group spots spatially coherent and transcriptionally similar together into the same spatial domain. Graph convolution network (GCN) and graph attention network (GAT), fed with spatial coordinates derived adjacency and transcription profile derived feature matrix are often used to solve the problem. Our proposed method STGIC (spatial transcriptomic clustering with graph and image convolution) utilizes an adaptive graph convolution (AGC) to get high quality pseudo-labels and then resorts to dilated convolution framework (DCF) for virtual image converted from gene expression information and spatial coordinates of spots. The dilation rates and kernel sizes are set appropriately and updating of weight values in the kernels is made to be subject to the spatial distance from the position of corresponding elements to kernel centers so that feature extraction of each spot is better guided by spatial distance to neighbor spots. Self-supervision realized by Kullback–Leibler (KL) divergence, spatial continuity loss and cross entropy calculated among spots with high confidence pseudo-labels make up the training objective of DCF. STGIC attains state-of-the-art (SOTA) clustering performance on the benchmark dataset of 10x Visium human dorsolateral prefrontal cortex (DLPFC). Besides, it’s capable of depicting fine structures of other tissues from other species as well as guiding the identification of marker genes. Also, STGIC is expandable to Stereo-seq data with high spatial resolution. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolution

SLA-SCA: Secure and Lightweight Authentication and Key Agreement Mechanism for Smart City Applications

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SLA-SCA: Secure and Lightweight Authentication and Key Agree...

Communications, Computing, Cybersecurity, and Informatics (CCCI), International Conference on

作者： Bhairvi Pant Mohammad S. Obaidat Shreya Singh Mudita Pant Mohammad Wazid Ashok Kumar Das Kuei-Fang Hsiao Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India King Abdullah II School of Information Technology The University of Jordan Amman Jordan University of Science and Technology Beijing Beijing China School of Computing SRM University Kattankulathur TN India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Computer Science Department University of Texas-Permian Basin Odessa USA

The notion of a smart city is a modern concept characterized by the widespread integration of the Internet of Things (IoT) across various facets of urban life, including healthcare, traffic management, agriculture, and more. This establishes real-time communication and data exchange between all users, servers and devices through the Internet. As we begin to discuss communication between parties, one must also recognize the imperative need for this exchange to be secure and private, as such exchanges are extremely vulnerable to attacks such as man-in-the-middle and replay attacks and even situations like compromising of anonymity during exchanges. This paper focuses on finding an innovative solution to the same challenge. It proposes a mechanism to establish secure communication between the smart IoT devices and the connected cloud servers through a secure mutual authentication and key establishment process with a short name “SLA-SCA”. The security analysis of the proposed SLA-SCA is done, which proves its resilience against the various potential attacks of such a communication. The proposed SLA-SCA outperformed the other existing schemes regarding important security and functionality features.

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Efficient and broadband terahertz polarization convertor enabled by an all-metal stereo reflective metasurface

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Efficient and broadband terahertz polarization convertor ena...

International Conference on Infrared and Millimeter Waves

作者： Yuehong Xu Quan Xu Xueqian Zhang Xi Feng Yongchang Lu Xixiang Zhang Jiaguang Han Weili Zhang Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering and the Key Laboratory of Optoelectronics Information and Technology (Ministry of Education) Tianjin University China RIKEN Center for Advanced Photonics RIKEN 519-1399 Aramaki-Aoba Aoba-ku Sendai Miyagi Japan Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia School of Electrical and Computer Engineering Oklahoma State University Stillwater Oklahoma USA

The pursuit of novel concepts and design schemes for metasurfaces to develop Terahertz (THz) polarization-related devices with exceptional performance is an ongoing and highly demanding project. Here, A new all-metal stereo U-shaped meta-atom based design scheme for manipulating terahertz polarization is proposed. The design functions as an efficient and broadband THz waveplate with tailorable birefringence by controlling sunken depth. The polarization conversion ratio (PCR) is $\gt90$% with 69% relative bandwidth and 85° angle tolerance. The proposed meta-grating based on Pancharatnam-Berry (PB) phase method is also demonstrated, enriching design degrees of freedom for metasurfaces and offering potential for various functional devices.

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Existence of Vortex Patch Equilibria for Active Scalars Equations

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arXiv 2024年

作者： Cuba, Edison Mathematical and Computer Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics State University of Campinas Rua Sérgio Buarque de Holanda 651 Cidade Universitária Campinas São Paulo13083-859 Brazil

In this paper, we investigate the existence of a finite number of vortex patches for the generalized surface quasi-geostrophic (gSQG) equations with α ∈ [1,2), focusing on configurations that may rotate uniformly, translate, or remain stationary. Using a desingularization technique, we reformulate the problem to resolve singularities arising in the point vortex limit. Assuming a nondegenerate equilibrium of the point vortices, we apply the implicit function theorem to construct time-periodic solutions to the gSQG equations, offering asymptotic descriptions of the vortex patch *** Codes 35Q35, 76B03, 76B47 Copyright © 2024, The Authors. All rights reserved.

关键词： Vortex flow