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Utilization of machine learning and neural networks to optimize the enclosure angle, magnetic field, and radiation parameter for mixed convection of hybrid nanofluid flow next to assess environmental impact

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engineering Analysis with Boundary Elements 2023年 146卷 252-262页

作者： Tao Hai Hayder A. Dhahad Masood Ashraf Ali Vishal Goyal Sattam Fahad Almojil Abdulaziz Ibrahim Almohana Abdulrhman Fahmi Alali Khaled Twfiq Almoalimi Farah Qasim Ahmed Alyousuf School of Computer and Information Qiannan Normal University for Nationalities Duyun Guizhou 558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun Guizhou 558000 China Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Shah Alam Selangor 40450 Malaysia Mechanical Engineering Department University of Technology Baghdad Iraq Department of Industrial Engineering College of Engineering Prince Sattam bin Abdulaziz University Alkharj 16273 Saudi Arabia Department of Electronics and Communication Engineering GLA University Mathura India Department of Civil Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Information Technology College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq

This paper examines the mixed convective heat transfer (HTR) of nanofluid (NFD) flow in a rectangular enclosure with the upper moving wall numerically. The lower wall has a high temperature and a number of semi-circular obstacles with the same temperature are installed on it. The upper moving wall has a low temperature and the other two walls are insulated. The enclosure can change from horizontal to vertical. Radiation HTR is considered in the enclosure and there is a magnetic field (MGF) that can change the angle from horizontal to vertical affecting the NFD. This study is carried out for different angles of the enclosure and MGF from horizontal to vertical for radiation parameters (RDP) of 0 to 3 and a constant MGF with Hartmann number of 20 and Richardson number of 10. The aim is to estimate the Nusselt number (Nu), entropy generation (ETG), and Bejan number (Be). The SIMPLE algorithm is utilized using FORTRAN software, and optimization is done using artificial intelligence to find the maximum and minimum output values. The results demonstrate that the maximum value of Nu and Bes corresponds to the MGF angle and enclosure angle of 90°. The minimum value of the Nu and the maximum amount of ETG corresponds to the horizontal MGF and horizontal enclosure when the RDP is 1.5. An increment in the RDP enhances the amount of Nu. The maximum amount of ETG, i.e. 12.87, corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. It was also found that most environmental impacts, and hence values for different environmental factors, arise from the production of nanoparticles; thus, it is a significant contributor to environmental impacts.

关键词： Machine learning Entropy generation Numerical calculations Convection Nanofluid

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Semiconductive and Ferromagnetic Lanthanide MXenes Derived from Carbon Intercalated Two-dimensional Halides

arXiv

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arXiv 2024年

作者： Fang, Qian Wang, Liming Chang, Kai Yang, Hongxin Yan, Pu Cao, Kecheng Li, Mian Chai, Zhifang Huang, Qing Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Key Laboratory of Special Energy Materials and Chemistry Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China University of Chinese Academy of Sciences Beijing100049 China Qianwan Institute of CNiTECH Ningbo315336 China Center for Quantum Matter School of Physics Zhejiang University Hangzhou31008 China School of Physical Science and Technology Shanghai Key Laboratory of High-resolution Electron Microscopy ShanghaiTech University Shanghai201210 China

Two-dimensional (2D) magnetic semiconductors are a key focus in developing next-generation information storage technologies1,2. MXenes, as emerging 2D early transition metal carbides and nitrides, offer versatile compositions and tunable chemical structures3. Incorporating lanthanide metals, with their unique role of 4f-electrons in engineering physical properties4, into MXenes holds potential for advancing technological applications. However, the scarcity of lanthanide-containing ternary MAX phase precursors and the propensity of lanthanides to oxidize pose significant challenges to obtain lanthanide MXenes (Ln2CT2) via the ‘top-down’ etching method5. Here, we propose a general ‘bottom-up’ methodology for lanthanide MXenes, that derive from carbon intercalated van der Waals building blocks of 2D halides. Compared to conventional MXenes conductors, the synthesized Ln2CT2 exhibit tunable band gaps spanning 0.32 eV to 1.22 eV that cover typical semiconductors such as Si (1.12 eV) and Ge (0.67 eV). Additionally, the presence of unpaired f-electrons endows Ln2CT2 with intrinsic ferromagnetism, with Curie temperatures ranging between 36 K and 60 K. Theoretical calculations reveal that, in contrast to traditional MXenes, the number of delectrons states around the Fermi level are largely diminishes in bare Ln2C MXenes, and the halogen terminals can further exhaust these electrons to open band gaps. Meanwhile, the Ln-4f electrons in Ln2CT2 are highly localized and stay away from the Fermi level, contributing to the spin splitting for the observed ferromagnetic behavior. Lanthanide MXenes hold immense promise for revolutionizing future applications in spintronic devices. © 2024, CC BY.

关键词： Nitrides

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Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-grained Student Ensemble

arXiv

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arXiv 2022年

作者： Qu, Xiaoye Zeng, Jun Liu, Daizong Wang, Zhefeng Huai, Baoxing Zhou, Pan Huawei Cloud China School of Software Engineering Huazhong University of Science and Technology China Peking University China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China

Distantly-Supervised Named Entity Recognition (DS-NER) effectively alleviates the data scarcity problem in NER by automatically generating training samples. Unfortunately, the distant supervision may induce noisy labels, thus undermining the robustness of the learned models and restricting the practical application. To relieve this problem, recent works adopt self-training teacher-student frameworks to gradually refine the training labels and improve the generalization ability of NER models. However, we argue that the performance of the current self-training frameworks for DS-NER is severely underestimated by their plain designs, including both inadequate student learning and coarse-grained teacher updating. Therefore, in this paper, we make the first attempt to alleviate these issues by proposing: (1) adaptive teacher learning comprised of joint training of two teacher-student networks and considering both consistent and inconsistent predictions between two teachers, thus promoting comprehensive student learning. (2) fine-grained student ensemble that updates each fragment of the teacher model with a temporal moving average of the corresponding fragment of the student, which enhances consistent predictions on each model fragment against noise. To verify the effectiveness of our proposed method, we conduct experiments on four DS-NER datasets. The experimental results demonstrate that our method significantly surpasses previous SOTA methods. The code is available at https://***/zenhjunpro/ATSEN. © 2022, CC BY.

关键词： Students

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Ultra-High Energy Storage Performance in Mg Modified Batio3 Films with Paraelectric Behavior

SSRN

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SSRN 2022年

作者： Ye, Yaosen Li, Fadong Guo, Kaixin Cui, Ruirui Zhang, Min Zhang, Jun Deng, Chaoyong School of Electronics and Information Engineering Guiyang University Guiyang550005 China Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang550025 China College of Computer and Information Engineering Guizhou University of Commerce Guiyang550014 China

Barium titanate (BTO) based materials have excellent application prospects in modern power electronic and electric power systems. Herein, BTO films doped with different concentrations of Mg (BM x T, x = 0, 0.06, 0.12, 0.18, 0.24) were fabricated on Pt/Ti/SiO2/Si substrates via a sol-gel and spin-coated method. A high energy storage density of 63.7 J/cm3 and excellent energy storage efficiency of 94.9% are simultaneously achieved in BM0.18T film. At the same time, the film still possesses excellent energy storage performances after 106 times of charge-discharge cycles, resulting high fatigue resistance. These outstanding properties are based on the paraelectric properties of Mg-doped amorphous thin films. This work provides a new method for preparing thin films with high energy storage density and efficiency in the future. © 2022, The Authors. All rights reserved.

关键词： Energy storage

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SFNS: Spatial-frequency image noise suppression for low-power industrial cone-beam computed tomography

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Applied Intelligence 2025年第11期55卷 1-15页

作者： Zhu, Yimin Wu, Xing Yao, Junfeng Qian, Quan Song, Jun Gao, Shouwei School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China Wuxi Zhongdun Technology Co. Ltd Changzhou China CSSC Seago System Technology Co. Ltd Ningbo China Key Laboratory of Silicate Cultural Relics Conservation (Shanghai University) Ministry of Education Shanghai China Department of Geography Hong Kong Baptist University Hong Kong China School of Mechanical and Electrical Engineering and Automation Shanghai University Shanghai China

With the widespread use of industrial computed tomography (CT) in semiconductor manufacturing, the noise in tomographic images from low-power radiation sources has become an increasingly prominent issue, which severely impacts the detection and processing tasks. In this paper, a spatial-frequency image noise suppression model (SFNS) is proposed to suppress noise while maintaining structural details in the image. A hybrid loss with spatial-frequency dual-domain information is designed to resolve spatial-domain limitations in optimization through complex-discrepancy-based spherical region separation criterion. To address the coupled noise characteristics in low-power CT systems, a stochastic noise degradation training strategy is designed to dynamically emulate fluctuations in real noise environments, and the network architecture integrates checkerboard sampling with cascaded residual stacks to enhance detail perception and reduce computational overhead. Experimental results demonstrate that SFNS achieves PSNR 32.14dB and SSIM 0.8896. Both quantitative metrics and qualitative evaluations validate the effectiveness of the proposed method in balancing structural fidelity and noise suppression.

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Cooperative guidance strategy for multiple hypersonic gliding vehicles system

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Chinese Journal of Aeronautics 2020年第3期33卷 990-1005页

作者： Jianglong YU Xiwang DONG Qingdong LI Zhang REN Jinhu LV School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100083China Shananxi Key Laboratory of Integrated and Intelligent Navigation Xi’an 710068China

Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is *** paper mainly cares about the coordination of the entry glide flight phase and driving-down *** from the existing results,both the attack time and the attack angle constraints are considered ***, for the entry glide flight phase, a two-stage method is proposed to achieve the rapid cooperative trajectories planning, where the control signal corridors are designed based on the quasi-equilibrium gliding *** the first stage, the bank angle curve is optimized to achieve the attack angle *** the second stage, the angle of attack curve is optimized to achieve the attack time *** optimized parameters can be obtained by the secant ***, for the driving-down phase, the cooperative terminal guidance law is designed where the terminal attack time and attack angle are *** guidance law is then transformed into the bank angle and angle of attack *** cooperative guidance strategy is summarized as an ***, a numerical simulation example with three hypersonic gliding vehicles is provided for revealing the effectiveness of the acquired strategy and algorithm.

关键词： Attack angle constraints Attack time constraints Cooperative guidance Cooperative path planning Entry guidance Hypersonic vehicles

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data mining accelerated the design strategy of high-entropy alloys with the largest hardness based on genetic algorithm optimization

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Materials Genome engineering Advances 2024年第2期2卷 108-125页

作者： Xianzhe Jin Hong Luo Xuefei Wang Hongxu Cheng Chunhui Fan Xiaogang Li Xiongbo Yan Key Laboratory for Corrosion and Protection of The Ministry of Education(MOE) Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijingChina

This article proposed a design strategy that integrated machine learning models based on random forest and genetic algorithm(GA)for the rapid screening of hardness in the AlCoCrCuFeMoNiTi high-entropy alloys *** feature engineering and modeling,valence electron concentration,atomic size difference(δr),Pauling electronegativity difference(Δχ),geometric parameters(Λ),and the Cr content were identified as the five key features in the *** GAwas employed to search for alloys with superior hardness and guided *** three itera-tions,the HEA Al_(18)Co_(21)Cr_(23)Fe_(23)Mo_(15)exhibiting the highest predicted hardness(868.8 HV)was *** alloy was predominantly composed of BCC,ordered B2,andσphases,with an experimental hardness of 899.8±9.9 HV,which as approximately 5.38%greater than the maximum hardness observed in the original *** design strategy can also solve other regression problems and pave the way for optimizing material performance in various engineering applications.

关键词： AlCoCrCuFeMoNiTi genetic algorithm hardness high-entropy alloys machine learning

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Predicting astrometric microlensing events from intermediate-mass stars (3 M⊙

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Monthly Notices of the Royal Astronomical Society 2025年第4期540卷 3421–3430页

作者： Su, Jie Wang, Jiancheng Zhang, Yigong Cheng, Xiangming Zhang, Zhenjun Yunnan Agricultural University College of Big Data Kunming 650201 China Yunnan Observatories Chinese Academy of Sciences Kunming 650216 China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of Sciences Kunming 650216 China Center for Astronomical Mega-Science Chinese Academy of Sciences Beijing 100012 China University of Chinese Academy of Sciences Beijing 100049 China College of Information Engineering Kunming University Kunming 650214 China School of Computer Science and Information Engineering Anyang Institute of Technology Anyang 455000 China

Astrometric microlensing provides a powerful tool for determining the masses of isolated stars. Current predictions for astrometric microlensing events lack the coverage of lens stars with estimated masses between3and5M⊙⁠, even though intermediate-mass stars occupy a critical phase in stellar evolution. In this study, we utilize Gaia DR3 data to search for predicted astrometric microlensing events caused by intermediate-mass stars (⁠3M⊙

关键词： gravitational lensing: micro methods: data analysis astrometry

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Dadm: Enhancing Eeg Artifact Removal by Fusing Artifact Representation into the Time-Frequency Domain

SSRN

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SSRN 2024年

作者： Li, Haoran Feng, Fan Kang, Jiarong Zhang, Jin Gong, Xiaoli Lu, Tingjuan Sun, Zhe Solé-Casals, Jordi College of Computer Science Nankai University Tianjin China Department of Biomedical Engineering School of Medicine Tsinghua University Beijing China Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China State Key Laboratory of High-end Server and Storage Technology China 903rd Hospital of PLA China Faculty of Medicine Faculty of Health Data Science Juntendo University Japan Data and Signal Processing Group University of Vic Central University of Catalonia Catalonia Vic08500 Spain

The electroencephalogram (EEG) provides essential data for analyzing brain activities. However, artifacts such as electrooculography (EOG) and electromyography (EMG) often interleave with the EEG signals, significantly affecting the quality of EEG signal analysis. The heterogeneous distribution of these artifacts in the time-frequency domain makes it challenging to remove multiple artifacts using a unified model. In this paper, we propose an Artifact-Aware EEG Denoising Model, referred to as DADM, to effectively remove various types of artifacts in a unified manner. We first obtain an artifact representation that indicates the type of artifact from a pre-trained artifact classification model. This artifact representation is then used as prior knowledge, which is fused into the denoising model in the frequency-time domain. This enables the model to become aware of the artifact type and precisely remove artifacts based on their type. Due to the heterogeneous distributions of artifacts in the frequency domain, we introduce a frequency enhancement module that can identify specific types of artifacts based on their representation and remove them using a hard attention mechanism. Additionally, we design a time-domain compensation module to enhance the denoising capability of DADM by compensating for potential losses of global information. Comprehensive experiments demonstrate that DADM significantly outperforms the Novel CNN in denoising EEG signals, showing a notable 7.77% improvement in correlation coefficient (CC) metrics. © 2024, The Authors. All rights reserved.

关键词： Electroencephalography

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Optical IRS for Visible Light Communication: Modeling, Design, and Open Issues

arXiv

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arXiv 2024年

作者： Sun, Shiyuan Yang, Fang Mei, Weidong Song, Jian Han, Zhu Zhang, Rui The Department of Electronic Engineering Tsinghua University Beijing100084 China The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China The Shenzhen International Graduate School Tsinghua University Shenzhen518055 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Optical intelligent reflecting surface (OIRS) offers a new and effective approach to resolving the line-of-sight blockage issue in visible light communication (VLC) by enabling redirection of light to bypass obstacles, thereby dramatically enhancing indoor VLC coverage and reliability. This article provides a comprehensive overview of OIRS for VLC, including channel modeling, design techniques, and open issues. First, we present the characteristics of OIRS-reflected channels and introduce two practical models, namely, optics model and association model, which are then compared in terms of applicable conditions, configuration methods, and channel parameters. Next, under the more practically appealing association model, we discuss the main design techniques for OIRS-aided VLC systems, including beam alignment, channel estimation, and OIRS reflection optimization. Finally, open issues are identified to stimulate future research in this area. Copyright © 2024, The Authors. All rights reserved.

关键词： Visible light communication

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