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Four-dimension efficient pixel-frequency transformer for light field spatial and angular super-resolution

Engineering Applications of Artificial Intelligence 2025年 154卷

作者： Wang, Sizhe Sheng, Hao Cong, Ruixuan Yang, Da Chen, Rongshan Cui, Zhenglong State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipments School of Mechano-Electronic Engineering Xidian University Shannxi Xi'an710071 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Key Laboratory of Data Science and Intelligent Computing International Innovation Institute Beihang University Zhejinag Hangzhou311115 China Faculty of Applied Sciences Macao Polytechnic University 999078 China

Super-resolution plays an important role in optical engineering, which can offer high-quality image information for vision applications. The light field camera can capture the intensity and direction information of light, providing abundant scene information. However, it faces the trade-off problem of spatial and angular resolution. Benefiting from global context modeling by self-attention mechanism, transformer-based artificial intelligence methods for the light field (LF) super-resolution (SR) provide superior performance. However, in these methods, the four-dimensional (4D) LF is reshaped into a large one-dimensional (1D) sequence to be processed, which leads to a significant increase in computation and memory and raises difficulties of 4D structure reconstruction for LF spatial and angular SR. This paper presents a 4D efficient pixel-frequency transformer (4DEPFT) for spatial and angular SR, which models 4D correlation in the pixel and frequency domains based on the proposed inner-outer transformer with 4D position encoding. Specifically, two parallel branches separately handle LF images and their corresponding frequency maps in 4DEPFT. In the pixel branch, sub-patch-based inner-outer pixel transformers are proposed to extract 4D pixel features inside and outside local windows, which deal with pixels with small and large disparity shifts separately. In the frequency branch, a multi-band-based inner-outer frequency transformer is proposed to reconstruct 4D frequency features from different frequency bands. Finally, an attention-based pixel and frequency feature fusion module is presented to acquire the high-resolution LF. Experimental results on real-world and simulated public datasets indicate that 4DEPFT outperforms other methods with less computational cost and graphics processing unit (GPU) consumption. © 2025 Elsevier Ltd

关键词： Photonics

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A Hybrid Deep Learning Paradigm for Robust Feature Extraction and Classification for Cataracts

Applied AI Letters

引用

applied AI Letters 2025年第2期6卷

作者： Ramakrishnan, Akshay Bhuvaneswari Madavan, Mukunth Manikandan, R. Gandomi, Amir H. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD United States Mukunth Madhavan AI Security Engineer Banglore India School of Computing SASTRA Deemed University Thanjavur India Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary Department of Computer Science Khazar University Baku Azerbaijan

The study suggests using a hybrid convolutional neural networks-support vector machines architecture to extract reliable characteristics from medical images and classify them as an ensemble using four different models. Manual processing of fundus images for the automated identification of ocular disorders is laborious, error-prone, and time-consuming. This necessitates computer-assisted technologies that can automatically identify different ocular illnesses from fundus images. The interpretation of the photos also plays a massive role in the diagnosis. Automating the diagnosing procedure reduces human mistakes and helps with early cataract detection. The oneDNN library available in the oneAPI Environment provided by Intel has been used to optimize all transfer learning models for better performance. The suggested approach is verified through a range of metrics in experiments using the openly accessible Ocular Disease Intelligent Recognition dataset. The MobileNet Model outperformed other transfer learning techniques with an accuracy of 0.9836. © 2025 The Author(s). applied AI Letters published by John Wiley & Sons Ltd.

关键词： cataract computer-assisted fundus hybrid ocular oneAPI oneDNN transfer learning

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Artificial intelligent approach for flow stability in Eyring Powell hybrid nanofluids via porous shrinking sheets

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Journal of Molecular Liquids 2025年 422卷

作者： Fatima, Nahid Kouki, Marouan Khan, Muhammad Imran Amjad, Arslan Bin Asghar, Zaheer Zeeshan, Ahmad Ijaz, Nouman Department of Mathematics and Sciences Prince Sultan University Riyadh11586 Saudi Arabia Department of Information System Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia Department of Mathematics and Statistics International Islamic University Islamabad 44000 Pakistan Centre for Mathematical Sciences Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan Department of Physics and Applied Mathematics Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad45650 Pakistan Department of Mathematics College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Department of Mathematics and Statistics Punjab Group of Colleges G.T. Road Jada Jhelum49600 Pakistan

This study aims to analyze flow stability using a computational intelligence technique that integrates a Levenberg-Marquardt approach utilizing artificial intelligence implemented through a backpropagation neural network. AI-based LMS-BPNN approach is utilized to examine the flow behavior of Eyring Powell hybrid nanofluid over a porous shrinking sheet. By applying skillful transformations, a set of ordinary differential equations is obtained from the partial differential equations that describe the hybrid nanofluid. Scenarios 1–5 illustrate how the built-in MATLAB function, bvp4c, solves ordinary differential equations systems by carefully modifying input parameters to get the initial or reference solution. The numerical data was split into three groups: 10 % for testing, 10 % for validation, and 80 % for training. The LMS-BPNN was used to find approximate solutions for these scenarios. To verify the effectiveness and reliability of LMS-BPNN, we employed regression analysis, error metrics, and correlation index (R)-based fitness curves. In each scenario, the temperature and velocity profiles gradually approached the boundary conditions as expected. The flow performance outcomes for the dual solution (Cfx and Nux) are also analyzed using the LMS-BPNN method. The perturbation scheme is applied to the boundary layer problem to obtain the eigenvalues problem. The unsteady solution f(η,τ) converges to steady solution fo(η) for τ→∞ when γ≥0. However, an unsteady solution f(η,τ) diverges to a steady solution fo(η) for τ→∞ when γ © 2025 Elsevier B.V.

关键词： Eigenvalues and eigenfunctions

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Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands

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Stochastic Environmental Research and Risk Assessment 2025年 1-27页

作者： Chand, Ravinesh Deo, Ravinesh C. Ghimire, Sujan Nguyen-Huy, Thong Ali, Mumtaz Artificial Intelligence Applications Laboratory School of Mathematics Physics and Computing University of Southern Queensland SpringfieldQLD4300 Australia Centre for Applied Climate Sciences University of Southern Queensland ToowoombaQLD4350 Australia Faculty of Information Technology Thanh Do University Kim Chung Hoai Duc Hanoi100000 Viet Nam UniSQ College University of Southern Queensland SpringfieldQLD4300 Australia Scientific Research Center Al-Ayen University Thi-Qar Nasiriyah64001 Iraq

Developing flood forecasting techniques at short timescales improve early warning systems to mitigate severe flood risk and facilitate effective emergency response strategies at vulnerable sites. In this study, we develop a hybrid deep learning algorithm, C-GRU, by integrating Convolutional Neural Networks (CNN) with Gated Recurrent Unit (GRU) model and evaluate its effectiveness in forecasting an hourly flood index () in five flood-prone, specific study sites in Fiji. The model incorporates statistically significant lagged with real-time hourly rainfall measurements obtained from rainfall stations, and comparative analysis is performed against benchmark models: CNN, GRU, Long Short-Term Memory and Random Forest Regression. The proposed model’s outputs comprise the predicted at each specific site at a lead time of 1-h. The results demonstrate that the proposed hybrid C-GRU model outperforms all the other models in accurately forecasting over a 1-hourly forecast horizon. Across all of the study sites, the proposed model consistently generates the highest r (0.996–0.999) and the lowest RMSE (0.007–0.014) and MAE (0.003–0.004) in the testing phase. The proposed hybrid C-GRU model also achieves the highest Global Performance Index (GPI) values and the largest percentage of forecast errors (FE) (98.9–99.9%) within smaller error brackets (i.e.,) across all study sites. Using the methodologies developed, we show the practical application of the proposed framework as a decision support system for early flood warning, demonstrating its potential to enhance real-time monitoring and early warning systems with broader application to flood-prone regions. © The Author(s) 2025.

关键词： Convolutional neural networks

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A roadmap to data science: Background, future, and trends

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International Journal of Intelligent Information and Database Systems 2021年第3期14卷 277-293页

作者： Khder, Moaiad Ahmad Fujo, Samah Wael Sayfi, Mohammad Adnan Department of Computer Science Applied Science University Bahrain Department of Computing Engineering and Technology Faculty of Applied Sciences University of Sunderland United Kingdom

Data science is a combination of several disciplines that aims to get accurate insights from a bunch of data, develop the technology, and algorithm to solve the complicated problems analytically. Today, data science plays a massive role in our life, and researchers realise how it is essential. Numerous research studies on data science have been published in recent years, but each focus on specific issues, such as data science and its impact on business, manufacturing, academia, and healthcare. This paper will present a roadmap of data science to benefit the readers to know about this field and realise how it is essential in several areas. In addition, it clarifies the mechanism of how data science work and what are the capabilities of the data scientist to be able to work in this field. It also shows the trends and future work of data science. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Big data

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The development of online trust among construction teams in Finland

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Electronic Journal of Information technology in Construction 2007年 12卷 305-321页

作者： Uden, Lorna Naaranoja, Marja Faculty of Computing Engineering and Technology Staffordshire University United Kingdom Vaasan Ammattikorkeakoulu University of Applied Sciences Finland

Construction is a complex process involving many different stakeholders. It is important that information among these stakeholders flows smoothly. A crucial aspect of the success of a project depends on the effective sharing of knowledge among the different people. Trust is important for knowledge transfer especially for online applications. There are different types of trust that have implications for knowledge sharing among the construction teams. This paper describes the importance of trust that we have identified during knowledge sharing among four construction projects in Finland. It begins with identification of the needs of online technology among construction teams. It is followed by a brief review of the different types of online trust. Section Three describes the case study methodology. In Section Four the implications of the online trust among construction teams are then discussed. Section Five concludes with suggestions for promoting trust among construction teams for knowledge sharing.

关键词： Online systems

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A Comprehensive Review on Lithium-Ion Battery Lifetime Prediction and Aging Mechanism Analysis

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Batteries 2025年第4期11卷 127-127页

作者： Madani, Seyed Saeed Shabeer, Yasmin Allard, François Fowler, Michael Ziebert, Carlos Wang, Zuolu Panchal, Satyam Chaoui, Hicham Mekhilef, Saad Dou, Shi Xue See, Khay Khalilpour, Kaveh Department of Chemical Engineering University of Waterloo WaterlooONN2L 3G1 Canada Varennes QCJ3X 1P7 Canada Institute of Applied Materials-Applied Materials Physics Karlsruhe Institute of Technology Karlsruhe76131 Germany Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom Department of Electronics Carleton University OttawaONK1S 5B6 Canada School of Science Computing and Engineering Technologies Swinburne University of Technology MelbourneVIC3122 Australia University of Wollongong WollongongNSW2500 Australia Institute of Energy Materials Science University of Shanghai for Science and Technology Shanghai200093 China Faculty of Engineering and IT University of Technology Sydney UltimoNSW2007 Australia

Lithium-ion batteries experience degradation with each cycle, and while aging-related deterioration cannot be entirely prevented, understanding its underlying mechanisms is crucial to slowing it down. The aging processes in these batteries are complex and influenced by factors such as battery chemistry, electrochemical reactions, and operational conditions. Key stressors including depth of discharge, charge/discharge rates, cycle count, and temperature fluctuations or extreme temperature conditions play a significant role in accelerating degradation, making them central to aging analysis. Battery aging directly impacts power, energy density, and reliability, presenting a substantial challenge to extending battery lifespan across diverse applications. This paper provides a comprehensive review of methods for modeling and analyzing battery aging, focusing on essential indicators for assessing the health status of lithium-ion batteries. It examines the principles of battery lifespan modeling, which are vital for applications such as portable electronics, electric vehicles, and grid energy storage systems. This work aims to advance battery technology and promote sustainable resource use by understanding the variables influencing battery durability. Synthesizing a wide array of studies on battery aging, the review identifies gaps in current methodologies and highlights innovative approaches for accurate remaining useful life (RUL) estimation. It introduces emerging strategies that leverage advanced algorithms to improve predictive model precision, ultimately driving enhancements in battery performance and supporting their integration into various systems, from electric vehicles to renewable energy infrastructures. © 2025 by the authors.

关键词： Lithium-ion batteries

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Learning-Based Design of LQG Controllers in Quantum Coherent Feedback

arXiv

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arXiv 2025年

作者： Song, Chunxiang Liu, Yanan Zhang, Guofeng Mo, Huadong Dong, Daoyi School of Engineering and Technology University of New South Wales CanberraACT2600 Australia School of Engineering University of Newcastle NewcastleNSW2308 Australia University of Duisburg-Essen Duisburg47057 Germany Department of Applied Mathematics The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Shenzhen Research Institute The Hong Kong Polytechnic University Shenzhen518057 China School of Systems and Computing University of New South Wales CanberraACT2600 Australia Australian Artificial Intelligence Institute Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia

In this paper, we propose a differential evolution (DE) algorithm specifically tailored for the design of Linear-Quadratic-Gaussian (LQG) controllers in quantum systems. Building upon the foundational DE framework, the algorithm incorporates specialized modules, including relaxed feasibility rules, a scheduled penalty function, adaptive search range adjustment, and the "bet-and-run" initialization strategy. These enhancements improve the algorithm’s exploration and exploitation capabilities while addressing the unique physical realizability requirements of quantum systems. The proposed method is applied to a quantum optical system, where three distinct controllers with varying configurations relative to the plant are designed. The resulting controllers demonstrate superior performance, achieving lower LQG performance indices compared to existing approaches. Additionally, the algorithm ensures that the designs comply with physical realizability constraints, guaranteeing compatibility with practical quantum platforms. The proposed approach holds significant potential for application to other linear quantum systems in performance optimization tasks subject to physically feasible constraints. Copyright © 2025, The Authors. All rights reserved.

关键词： Quantum optics

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Analysis of different phase change materials (PCMs) and wall material in a nano-circular space thermal energy storage (TES) system: A molecular dynamics approach

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International Journal of Thermal Sciences 2025年 215卷

作者： Cao, Cheng Ali, Ali B.M. Hussein, Zahraa Abed Sawaran Singh, Narinderjit Singh Abdullaeva, Barno Zubair, Ahmad Salahshour, Soheil Baghaei, Sh School of Mechanical Engineering Changshu Institute of Technology Jiangsu Changshu215500 China Air Conditioning Engineering Department College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Al-Manara College for Medical Sciences Amarah Maysan Iraq Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nila71800 Malaysia Department of Mathematics and Information Technologies Vice-Rector for Scientific Affairs Tashkent State Pedagogical University Tashkent Uzbekistan Central Labs King Khalid University AlQura'a Abha P.O. Box 960 Saudi Arabia Applied College Mahala Campus King Khalid University Abha P.O. Box 9004 61413 Saudi Arabia Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Research Center of Applied Mathematics Khazar University Baku Azerbaijan Fast Computing Center Shabihsazan Ati Pars Tehran Iran

Thermal energy storage (TES) play a vital role in overcoming the fluctuating nature of solar thermal energy. To study and understand the performance of these systems, using new techniques such as computer simulations can be useful. In this article, a specific circular nanochannel containing a phase change material (PCM) is introduced and its thermal and mass performance are investigated. By using two types of PCM and three wall metals (platinum, copper, and aluminum) the effects of changing several geometric and thermodynamic parameters are evaluated. In general, two different plans are proposed and parameters such as thermal conductivity, heat flux, charging, and discharging time are defined and evaluated. The obtained results show that the use of paraffin reduces the phase change time from 1.36 ns to 1.21 ns. Geometrical investigations also show that increasing the diameter ratio leads to a decrease in heat flux. Increasing the velocity of argon atoms in the inner tube also leads to an increase in the mobility of atoms and as a result improves the heat transfer rate. Using copper, the thermal conductivity is 54.3 % and 13.5 % higher than platinum and aluminum. The maximum heat flux for the two proposed cases is about 1500 and 1285 W/m2, respectively. Increasing the velocity of argon atoms from 0.01 Å/fs to 0.05 Å/fs leads to a decrease in the phase change time from 1.12 ns to 1.15 ns. Regarding the type of PCM, paraffin performs better than the combination of water-hydrocarbon. © 2025 Elsevier Masson SAS

关键词： Copper

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Time-Dependent Variational Approach to Ground-State Phase Transition and Phonon Dispersion Relation of the Quantum Double-Well Model

引用

Chinese Physics Letters 2008年第8期25卷 2758-2761页

作者：钟红伟徐海清黄乒花 Department of Information and Computing Science Guangxi University of Technology Liuzhou 545006 Faculty of Applied Technology Hunan Institute of Engineering Xiangtan 411101 School of Physical Electronics University of Electronic Science and Technology of China Chengdu 610054

The ground-state phase transition and the phonon dispersion relation of the quantum double-well model are studied by means of the time-dependent variational approach combined with a Hartree-type many-body trial wavefunction. The single-particle state is taken to be a frozen Jackiw-Kerman wavefunction. Under the condition of minimum uncertainty relation, we obtain an effective classical Hamiltonian for the system and equations of motion for the particle＇s expectation values. It is shown that the effective substrate potential transits from a symmetric double-well potential to a symmetric single-well potential, and the ground state exhibits a transition from a broken symmetry phase to a restored symmetry phase as increasing the strength of quantum fluctuations. We also obtain the phonon dispersion relations and the phonon gaps at the two phases.

关键词： FIELD-THEORY POLYACETYLENE DYNAMICS SOLITONS APPROXIMATION FLUCTUATIONS PRESSURE CHAINS ICE

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