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Streamflow Prediction in the Mekong River Basin Using Deep Neural Networks

IEEE Access 2023年 11卷 97930-97943页

作者： Nguyen, Thi-Thu-Ha Vu, Duc-Quang Mai, Son T. Dang, Thanh Duc National Taiwan University Department of Bioenvironmental Systems Engineering Taipei10617 Taiwan National Central University Department of Computer Science and Information System Taoyuan320317 Taiwan Thai Nguyen University of Education Thai Nguyen250000 Viet Nam Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Institute for Computational Science and Artificial Intelligence Van Lang University Laboratory of Environmental Sciences and Climate Change Ho Chi Minh City70000 Viet Nam Van Lang University Faculty of Environment Ho Chi Minh City70000 Viet Nam

In recent years, the Mekong River Basin (MRB), one of the largest river basins in Southeast Asia, has experienced severe impacts from extreme droughts and floods. Streamflow forecasting has become crucial for effective risk management strategies in the region. However, this task presents significant challenges due to rapid climate changes and the presence of numerous newly constructed upstream dams, which disrupt the natural flow. In this paper, we develop multiple deep learning models (incl. Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long short-term Memory (LSTM), and Transformer) to predict streamflow with different lead time forecasts based on observed meteorological variables and climatic indices (i.e., discharge, water level, precipitation, and temperature) from 1979 to 2019. The results indicate that LSTM obtains high performance for streamflow prediction in both dry and wet seasons while Transformer is not recommended for long-term prediction, especially in the dry season. The proposed deep learning models capture well the fluctuation of river flow in the MRB during the period of high-dam development, especially LSTM (NSE ≥ 0.8). The models' performances are enhanced with the adding of temperature for short-term prediction while precipitation was the most sensitive variable for long-term one. Such proposed models are essential for government agencies to plan mitigation and adaptation strategies at different periods, which can range from days to years. © 2013 IEEE.

关键词： Floods

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Experimental demonstration of deep-learning-enabled adaptive optics

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Physical Review Applied 2024年第3期22卷 034047页

作者： Hao-Bin Fu Zu-Yang Wan Yu-huai Li Bo Li Zhen Rong Gao-Qiang Wang Juan Yin Ji-Gang Ren Wei-Yue Liu Sheng-Kai Liao Yuan Cao Cheng-Zhi Peng Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences Shanghai Research Center for Quantum Sciences and CAS Center for Excellence in Quantum Information and Quantum Physics Hefei National Laboratory Faculty of Electrical Engineering and Computer Science

Satellite-based quantum communication is a promising approach for establishing global-scale quantum networks. In free-space quantum channels, single-mode-fiber coupling plays a crucial role in increasing the signal-to-noise ratio of daylight quantum key distribution (QKD) and ensuring compatibility with standard fiber-based QKD protocols. However, consistently achieving high efficiency and stable single-mode-fiber coupling under strong atmospheric turbulence remains an ongoing experimental challenge. In this study, we experimentally demonstrate an adaptive method based on convolutional neural networks capable of directly estimating phase information from a single defocused image. We developed a convolutional neural network to establish the relationship between intensity distribution and phase information of turbulent distortions. We demonstrate the real-time performance of our deep-learning adaptive method in increasing single-mode-fiber coupling efficiency across various turbulence scales and quantify turbulence frequencies. Notably, the method proved highly effective in strong-turbulence scenarios, with frequencies reaching up to 200 Hz, leading to a significant increase in single-mode-fiber coupling efficiency. We demonstrate the corrective capability of our adaptive method for strong turbulence, enabled by the generalization of the convolutional neural network. Our results offer an efficient solution for daytime free-space QKD applications.

关键词： Optical quantum information processing Quantum communication, protocols & technology Turbulence Communication networks Convolutional neural networks Earth's atmosphere Optical fibers Deep learning

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A New Lightweight Attention-based Model for Emotion Recognition on Distorted Social Media Face Images

TechRxiv

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TechRxiv 2023年

作者： Roy, Ayush Shivakumara, Palaiahnakote Pal, Umapada Gornale, Shivanand S. Liu, Cheng-Lin Jadavpur University India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Computer Science Rani Channamma University Belagavi India Institute of Automation Chinese Academy of Sciences China

The recognition of human emotions remains a challenging task for social media images. This is due to distortions created by different social media conflict with the minute changes in facial expression. This study presents a new model called the Global Spectral-Spatial Attention Network (GSSAN), which leverages both local and global information simultaneously. The proposed model comprises a shallow Convolutional Neural Network (CNN) with an MBResNext block, which integrates the features extracted from MobileNet, ResNet, and DenseNet for extracting local features. In addition, to strengthen the discriminating power of the features, GSSAN incorporates Fourier features, which provide essential cues for minute changes in the face images. To test the proposed model for emotion recognition using social media images, we conduct experiments on two widely-used datasets: FER-2013 and AffectNet. The same benchmark datasets are uploaded and downloaded to create a distorted social media image dataset to test the proposed model. Experiments on distorted social media images dataset show that the model surpasses the accuracy of SOTA models by 0.69% for FER-2013 and 0.51% for AffectNet social mediad datasets. The same inference can be drawn from the experiments on standard datasets. © 2023, CC BY.

关键词： Face recognition

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Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

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IEEE Transactions on Communications 2024年 1-1页

作者： Zhang, Yuchen Ni, Wanli Wang, Jianquan Tang, Wanbin Jia, Min Eldar, Yonina C. Niyato, Dusit National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu China Department of Electronic Engineering Tsinghua University Beijing China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Computer Science and Engineering Nanyang Technological University Singapore

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint transceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring the communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems. IEEE

关键词： Linear matrix inequalities

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Brain Cancer Ontology Construction 6th

Brain Cancer Ontology Construction

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6th International Conference on Business Intelligence, CBI 2021

作者： El Hakym, Fatiha Mahi, Btissame Information Processing and Decision Support Laboratory Department of Computer Science Faculty of Science and Technology PO Box. 523 Beni Mellal Morocco

ISBN: (纸本)9783030765071

An ontology is an integral part of a semantic web. Ontology can be designed and create the necessary metadata elements to develop a semantic web applications. The evolution of semantic web has encouraged creation of ontologies in many domains. This work aims to create an ontology of brain cancer to do this we need to define the steps of creation of an ontology;first, we need a lot of information about brain cancer. This article describes the different steps involved in creating a brain cancer ontology. We have used a Protege 4. 2 to for the construction of a brain cancer ontology. © 2021, Springer Nature Switzerland AG.

关键词： Semantic Web

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Imperceptible and Sparse Adversarial Attacks via a Dual-Population-Based Constrained Evolutionary Algorithm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 268-281页

作者： Tian, Ye Pan, Jingwen Yang, Shangshang Zhang, Xingyi He, Shuping Jin, Yaochu Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Anhui University School of Computer Science and Technology Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Hefei230601 China Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Hefei230601 China Bielefeld University Faculty of Technology Bielefeld33619 Germany

The sparse adversarial attack has attracted increasing attention due to the merit of a low attack cost via changing a small number of pixels. However, the generated adversarial examples are easily detected in vision since the perturbation to each pixel is relatively large. To achieve imperceptible and sparse adversarial attacks, this article formulates a bi-objective constrained optimization problem, simultaneously minimizing the 0 and 2 distances to the original image, and proposes a dual-population-based constrained evolutionary algorithm to solve it. The proposed method solves the optimization problem by evolving two populations, where one population is responsible for finding feasible solutions (i.e., successful attacks) and the other one is to minimize both the 0 and 2 distances. Moreover, a population initialization strategy and two genetic operators are customized to accelerate the convergence speed. Experimental results indicate that the proposed method can achieve high success rates with low attack costs, and strikes a better balance between the 0 and 2 distances than state-of-the-art methods. © 2020 IEEE.

关键词： Evolutionary algorithms

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Near-eye light field display based on biological stereoscopic vision

Near-eye light field display based on biological stereoscopi...

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The 2023 International Conference on Display Technology, (ICDT 2023)

作者： Zhao, Jian Xia, Jun Xu, Yue Jiang, Yujin School of Computer Engineering Nanjing Institute of technology No.1 Hongjing Road Jiangsu Nanjing211167 China Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and Engineering Southeast University Nanjing210018 China SuXin Vision Technologies Co Ltd No.2888 Dongwu Road Jiangsu Suzhou215000 China

Near-eye display technology can provide users with an immersive visual experience. However, there are still many challenges in this technology, the most urgent of which is visual comfort. The main reason is that the display device cannot render the correct depth cues to solve the conflict between the human eye's radial angle and adjustment, resulting in dizziness, nausea, binocular fatigue and other problems for users to use for a long time. In this paper, we will analyze and review the technical schemes which can provide accurate or near-accurate depth clues in the current near-eye display technology. © 2023, John Wiley and Sons Inc. All rights reserved.

关键词： Stereo image processing

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Implementation of a Geographical information System (GIS) for E-commerce 4th

Implementation of a Geographical Information System (GIS) fo...

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4th Doctoral Symposium on Computational Intelligence, DoSCI 2023

作者： Mohamed, Shili Sethom, Kaouthar Obaid, Ahmed J. Alkhafaji, Mohammed Ayad Mohsen, Karrar Shareef Innov’COM at Sup’Com Laboratory University of Carthage Carthage Tunisia Faculty of Computer Science and Mathematics University of Kufa Kufa Iraq College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq

ISBN: (纸本)9789819937158

Nowadays Geographic information systems (GIS) have developed quickly in recent years and are now utilized in a wide range of industries, including e-health, agriculture, and more. However, compared to other industries, the application of GIS in electronic commerce lags far behind. This paper consists of a web GIS application that aims to help businesses reduce driving time and costs by generating an optimal route between the delivery drivers and the customer’s locations. Using the programmable APIs provided by Google maps, we built an online shopping system with map features to research the potential of GIS in online commerce. The system incorporates Google maps into the system website using the Google maps API and adheres to the three-tier architectural paradigm. The geographical data is based on Google maps data, and the system data is stored in a MySQL database. The system MySQL database and the spatial data from Google maps are connected by latitude and longitude. These can drastically reduce the work and cost of development while simultaneously greatly increasing the system's extensibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： information systems

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Testing Timed Systems Using Determinization Techniques for One-Clock Timed Automata

Testing Timed Systems Using Determinization Techniques for O...

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2021 Tunisian-Algerian Joint Conference on Applied Computing, TACC 2021

作者： Krichen, Moez Faculty of Computer Science and Information Technology Al-Baha University Saudi Arabia ReDCAD Research Laboratory University of Sfax Tunisia

In this work, we are interested in formal Model-Based Testing for Real-Time Systems. The proposed approach is based on the use of the model of Timed Automata with continuous clocks for which we adopt the reset-point semantics. We remind the definition of timed conformance relation tioco. We extend the notion of soundness and completeness of test suites. We also consider specifications in form of one-clock input-complete timed automata. Moreover, we provide interesting decidability results for the considered classes of specifications. More specifically, we consider the case when some parameters of the timed-automaton tester are fixed in advance, namely the number of clocks of the timed-automaton and its maximal time-constraint constants. Finally, several possible extensions of the present work in different directions are proposed. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Clocks

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE Transactions on Image Processing 2025年 34卷 3139-3153页

作者： Chen, Jun Yang, Liling Yu, Wei Gong, Wenping Cai, Zhanchuan Ma, Jiayi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China University of Geosciences Faculty of Engineering Wuhan430074 China Macau University of Science and Technology School of Computer Science and Engineering Taipa China Wuhan University Electronic Information School Wuhan430072 China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. © 1992-2012 IEEE.

关键词： Image coding

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