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Recent progress of artificial intelligence for liquid-vapor phase change heat transfer

npj Computational Materials 2024年第1期10卷 2552-2565页

作者： Youngjoon Suh Aparna Chandramowlishwaran Yoonjin Won Department of Mechanical and Aerospace Engineering University of CaliforniaIrvineCAUSA Department of Electrical Engineering and Computer Science University of CaliforniaIrvineCAUSA

Artificial intelligence(AI)is shifting the paradigm of two-phase heat transfer *** innovations in AI and machine learning uniquely offer the potential for collecting new types of physically meaningful features that have not been addressed in the past,for making their insights available to other domains,and for solving for physical quantities based on first principles for phasechange thermofluidic *** review outlines core ideas of current AI technologies connected to thermal energy science to illustrate how they can be used to push the limit of our knowledge boundaries about boiling and condensation *** technologies for meta-analysis,data extraction,and data stream analysis are described with their potential challenges,opportunities,and alternative ***,we offer outlooks and perspectives regarding physics-centered machine learning,sustainable cyberinfrastructures,and multidisciplinary efforts that will help foster the growing trend of AI for phase-change heat and mass transfer.

关键词： transfer meaningful shifting

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Performance Analysis of ZF and RZF in Low-Resolution ADC/DAC Massive MIMO Systems

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China Communications 2024年第8期21卷 115-126页

作者： Talha Younas Shen Jin Muluneh Mekonnen Gao Mingliang Saqib Saleem Sohaib Tahir Mahrukh Liaqat School of Electrical and Electronic Engineering Shandong University of TechnologyZibo 255000China Department of Electrical and Computer Engineering COMSATS University IslamabadSahiwal Campus Department of Electrical and Computer Engineering College of EngineeringDhofar UniversitySalalah 211Oman Department of Electrical and Computer Engineering Addis Ababa Science and Technology UniversityAddis AbabaEthiopia Department of Electrical Engineering College of Electrical and Mechanical EngineeringNUSTIslamabadPakistan

Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power *** power consumption at the receiver radio frequency(RF)circuits can be significantly reduced by the application of analog-to-digital converter(ADC)of low *** this paper we investigate bandwidth efficiency(BE)of massive MIMO with perfect channel state information(CSI)by applying low resolution ADCs with Rician *** start our analysis by deriving the additive quantization noise model,which helps to understand the effects of ADC resolution on BE by keeping the power constraint at the receiver in *** also investigate deeply the effects of using higher bit rates and the number of BS antennas on bandwidth efficiency(BE)of the *** emphasize that good bandwidth efficiency can be achieved by even using low resolution ADC by using regularized zero-forcing(RZF)combining *** also provide a generic analysis of energy efficiency(EE)with different options of bits by calculating the energy efficiencies(EE)using the achievable *** emphasize that satisfactory BE can be achieved by even using low-resolution ADC/DAC in massive MIMO.

关键词： low-bit analog-digital converter massive(multiple-input-multiple-output)MIMO minimum mean square error(MMSE) regularized zero forcing zero forcing

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An Overview of LoRa Localization Technologies

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computers, Materials & Continua 2025年第2期82卷 1645-1680页

作者： Huajiang Ruan Panjun Sun Yuanyuan Dong Hamid Tahaei Zhaoxi Fang Institute of Artificial Intelligence Shaoxing UniversityShaoxing312000China Department of Computer Science and Engineering School of Mechanical and Electrical EngineeringShaoxing UniversityShaoxing312000China

Traditional Global Positioning System(GPS)technology,with its high power consumption and limited perfor-mance in obstructed environments,is unsuitable for many Internet of Things(IoT)*** paper explores LoRa as an alternative localization technology,leveraging its low power consumption,robust indoor penetration,and extensive coverage area,which render it highly suitable for diverse IoT *** comprehensively review several LoRa-based localization techniques,including time of arrival(ToA),time difference of arrival(TDoA),round trip time(RTT),received signal strength indicator(RSSI),and fingerprinting *** this review,we evaluate the strengths and limitations of each technique and investigate hybrid models to potentially improve positioning *** studies in smart cities,agriculture,and logistics exemplify the versatility of LoRa for indoor and outdoor *** findings demonstrate that LoRa technology not only overcomes the limitations of GPS regarding power consumption and coverage but also enhances the scalability and efficiency of IoT deployments in complex environments.

关键词： LoRa localization IoT TDoA RSSI application hybrid models

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New strategy for enhancing the strength and toughness of Ti-Al metallic-intermetallic laminated composites: Constructing multiple heterostructures using Ni foil

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Progress in Natural science:Materials International 2024年第6期34卷 1173-1183页

作者： Pengfei Zhou Meini Yuan Mengye Jia Xin Pei Yang Wang Wei Yang Honglin Wang Yuhong Zhao School of Mechanical and Electrical Engineering North University of China School of Aerospace Engineering North University of China School of Environment and Safety Engineering North University of China Inner Mongolia Metal Material Research Institute School of Materials Science and Engineering North University of China

In order to simultaneously improve the strength and ductility of Ti-Al metallic-intermetallic laminated（TA-MIL）composites, novel Ti-Al-Ni ternary MIL（TAN-TMIL） composites with multiple heterostructures（HS） were fabricated by adding a 0.02 mm Ni foil behind the Ti and Al foils. The results showed that TAN-600 consisted of the same phases（Ti, Al3Ti, and Al） as TA-600 and additionally produced new Ni Al3and Ni2Al3phases due to the Ni-Al reactions. Furthermore, when the hot-pressing temperature was increased to 650°C, Kirkendall voids appeared in the Al3Ti layer（TA-650） and at the Al3Ti/Ni Al3interface（TAN-650）. Compared to TA-MIL composites, the thickness of the Al3Ti layer in the TAN-TMIL composites increased by four times when prepared at 600°C, but decreased by four times when prepared at 650°C. Electron backscatter diffraction（EBSD） and nano-indentation tests revealed that TAN-600 had multiple HS and more high-angle grain boundaries（HAGB）, optimizing the structure of TA-600. Importantly, this structural arrangement enhanced the interface effects and compressive properties of TAN-600. Tensile testing indicated that the crack-free NiAl3/Ni2Al3layer contributed to the strength of TAN-600, ensuring multi-directional fracture in the Al3Ti layer. This research provides insights for improving the strength and toughness of TA-MIL composites.

关键词： Laminated composites Ti-Al-Ni ternary system Multiple heterostructures Microstructure evolution mechanical properties

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Dual-strategy regulation for enhancing hydrogen storage performance of non-activated Mg8Ni-TiO2/MnO2 composites

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Journal of Energy Chemistry 2025年第4期103卷 543-555页

作者： Duode Zhao Xiaojiang Hou Chenlu Wang Danting Li Xinlei Xie Peixuan Zhu Xiaohui Ye Guoquan Suo Guang Yang Guangsheng Xu School of Material Science and Engineering Shaanxi Key Laboratory of Green Preparation and Functionalization for Inorganic Material Shaanxi University of Science and Technology College of Mechanical & Electrical Engineering Shaanxi University of Science and Technology Research Center of High-performance Aerospace Materials and Devices Shaanxi Polytechnic Institute

Magnesium-based materials are considered as among the most promising candidates for hydrogen storage,owing to their high storage capacity,safety,and ***,a passivation layer easily forms on the surface of magnesium,which hinders the dissociation and diffusion of *** dehydrogenation temperature,sluggish kinetics and activation difficulties hinder their commercial ***,dual-strategy regulation through nickel microalloying and surface catalysis of TiO2/MnO2catalysts has been proposed to obtain more active sites and diffusion channels that promote hydrogen dissociation and ***8Ni-X(X=None,TiO2,and TiO2/MnO2) can achieve more than 80% hydrogen absorption without ***8Ni-5 wt% TiO2/MnO2absorbs hydrogen 5.27 wt% in 30 s at 200℃and desorbs 5.15 wt% in 20 min at 325℃.The activation energy（Ea） of hydrogen absorption is 52.04kJ/*** results are significantly better than those of Mg8Ni and MgH2under the same *** NiTi phase is generated in the course of hydrogenation,and the coexistence of multiple phases and multivalent Ti facilitates the transport of electrons and *** dual-strategy regulation means of surface catalysis and microalloying is promising for the design of high-capacity fast hydrogen absorbed and desorbed materials without activation.

关键词： Hydrogen storage Mg8Ni Microalloying Thermodynamics TiO2/MnO2

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LoRA-MedSAM: Efficient Medical Image Segmentation 5th

LoRA-MedSAM: Efficient Medical Image Segmentation

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5th International Conference on Medical Imaging and computer Aided Diagnosis, MICAD 2024

作者： Hu, Jiamin Xu, Xuwei Zou, Zhenmin Department of Mechanical and Aerospace Engineering University of Manchester Manchester United Kingdom School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9789819638628

Medical image segmentation becomes increasingly important for identifying and delineating anatomical structures, diseases, and abnormalities within medical images. However, existing large pre-trained foundation models for medical image segmentation, such as MedSAM, are often limited by their substantial computing resource requirements when fine-tuned for specific tasks. This high computational burden hinders their deployment in real-world clinical scenarios where rapid model adaptation is crucial yet computing resources are typically constrained. To address the challenge, in this paper, we introduce LoRA-MedSAM, a highly efficient method for fine-tuning large pre-trained models on medical image segmentation tasks. In particular, we leverage the Low-Rank Adaptation technique to significantly expedite the fine-tuning process of MedSAM model while maintaining high performance. Extensive experiments on three widely adopted medical image segmentation datasets have demonstrated both the effectiveness and efficiency of our method. Specifically, LoRA-MedSAM drastically reduces the fine-tuning time by 22.7%, 14.8% and 29.4% while outperforming the vanilla MedSAM by 1.1%, 5.5% and 0.5% higher Dice Similarity Coefficient (DSC) on the AMOS, BTCV and MultiTalent datasets, respectively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Medical imaging

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A robust image encryption method based on block diagonal chaotic architecture with CNN performance evaluation metric

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Multimedia Tools and Applications 2025年 1-35页

作者： Mamandi, Vida Ardalani, Nahid Ghalamkari, Behbod Department of Electrical Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Mechanical Electrical and Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In this paper, a new block diagonal chaotic model (BDC) is investigated due to higher necessity of advanced secure data transmission method in wireless medium and considerable limitation on computational storage space. In this model, the image sparse coding using BDC matrix in noisy and Rayleigh fading channels is studied. The structured BDC model is designed with two schemes, including chaotic pseudo inverse matrix (CPI-m) and block diagonal chaotic structured matrix (BDC-m) using two chaotic maps, in which the initial values for generating nonlinear chaotic sequences are used as private key at the receiver side. The simulation results show that the retrieved data measured based on CPI and BDC schemes outperforms the chaotic compressive sensing (CCS) method over AWGN and Rayleigh fading channels by 6% and 22.7%, respectively. Also, the sensitivity of recovered BDC-based image increases to 10(−32) compared to that of 10(−16) for conventional CCS based image. Moreover, the encryption key space increases from 10(37) for standard CCS-based measurements to β×10111 for measured data based on the BDC model, which guarantees that the competitors access no information. Considering datasets from iterative reconstruction process, the image features are extracted using convolutional neural network (CNN) model by ResNet-18 and GoogleNet architectures. The improved performance of data based on CPI and BDC model is validated by retrieved images accuracy over the classifier support vector machine (SVM). © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Fading channels

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Feedback-based safe gradient flow for optimal regulation of virtual power plants 14

Feedback-based safe gradient flow for optimal regulation of ...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Colot, Antonin Cornélusse, Bertrand Cortés, Jorge Dall'Anese, Emiliano Department of Electrical Engineering and Computer Science University of Liège Belgium Department of Mechanical and Aerospace Engineering University of California San Diego United States Department of Electrical and Computer Engineering Boston University United States

ISBN: (纸本)9781837242689

This paper considers the problem of controlling distributed energy resources (DERs) in a distribution network (DN);the paper focuses on the voltage regulation task and on the concept of virtual power plant (VPP). For the latter, we envision an aggregation of DERs as a VPP that tracks power setpoints at the point of common coupling to provide ancillary services to the bulk power system. We propose a feedback-based controller that pursues solutions to a time-varying AC optimal power flow problem. This controller ensures voltage constraints are met in real time, assuming no voltage measurement errors. The feedback from the system mitigates the controller sensitivity to model uncertainties and eliminates the need for measurements of uncontrollable loads at every node. The feedback-based controller is tested on the IEEE37-node system with delta and wye-connected devices in a strongly unbalanced configuration. © The Institution of engineering & Technology 2024.

关键词： Virtual Power Plants

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ASL-OOD:Hierarchical Contextual Feature Fusion with Angle-Sensitive Loss for Oriented Object Detection

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computers, Materials & Continua 2025年第2期82卷 1879-1899页

作者： Kexin Wang Jiancheng Liu Yuqing Lin Tuo Wang Zhipeng Zhang Wanlong Qi Xingye Han Runyuan Wen Northwest Institute of Mechanical and Electrical Engineering Xianyang712099China School of Information Engineering Chang’an UniversityXi’an710064China School of Computer Science and Technology Xidian UniversityXi’an710071China

Detecting oriented targets in remote sensing images amidst complex and heterogeneous backgrounds remains a formidable challenge in the field of object *** frameworks for oriented detection modules are constrained by intrinsic limitations,including excessive computational and memory overheads,discrepancies between predefined anchors and ground truth bounding boxes,intricate training processes,and feature alignment *** overcome these challenges,we present ASL-OOD(Angle-based SIOU Loss for Oriented Object Detection),a novel,efficient,and robust one-stage framework tailored for oriented object *** ASL-OOD framework comprises three core components:the Transformer-based Backbone(TB),the Transformer-based Neck(TN),and the Angle-SIOU(Scylla Intersection over Union)based Decoupled Head(ASDH).By leveraging the Swin Transformer,the TB and TN modules offer several key advantages,such as the capacity to model long-range dependencies,preserve high-resolution feature representations,seamlessly integrate multi-scale features,and enhance parameter *** improvements empower the model to accurately detect objects across varying *** ASDH module further enhances detection performance by incorporating angle-aware optimization based on SIOU,ensuring precise angular consistency and bounding box *** approach effectively harmonizes shape loss and distance loss during the optimization process,thereby significantly boosting detection *** evaluations and ablation studies on standard benchmark datasets such as DOTA with an mAP(mean Average Precision)of 80.16 percent,HRSC2016 with an mAP of 91.07 percent,MAR20 with an mAP of 85.45 percent,and UAVDT with an mAP of 39.7 percent demonstrate the clear superiority of ASL-OOD over state-of-the-art oriented object detection *** findings underscore the model’s efficacy as an advanced solution for challenging remote sensing object detection tasks.

关键词： Oriented object detection transformer deep learning

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Classifying chest x-rays for COVID-19 through transfer learning: a systematic review

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Multimedia Tools and Applications 2025年第2期84卷 689-748页

作者： Mallick, Devanshi Singh, Arshdeep Ng, Eddie Yin-Kwee Arora, Vinay Thapar Institute of Engineering & Technology Punjab Patiala India Wipro Limited Gurugram India School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore Computer Science Engineering Department Thapar Institute of Engineering & Technology Punjab Patiala India

This study makes a comprehensive assessment of the predominant Transfer Learning (TL) techniques employed for the classification of COVID-19 cases in Chest X-rays (CXR) images. The methodologies have been selected on the basis of their merits and demerits, suitability, and possible impact on the development of the region being studied. The study examines the various methods of TL employed in the classification of COVID-19 cases with the objective to gain a deeper understanding about all the aspects of these methodologies. It can be of great significance for the researchers and medical professionals in making well-informed decisions about the implementation of these techniques to improve the precision and effectiveness of COVID-19 diagnosis. The practical consequences of these techniques help in early identification of such cases for having a suitable intervention. As many as 48 studies conducted during the period 2020–2023 have been included in the current research work for having an assessment about the problem under investigation. The study has specifically focused on transfer learning-based models utilized for the identification of COVID-19 through CXR pictures. It highlights the challenges posed by dataset dynamics, methodological variations, and performance metrics of different models. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： COVID-19

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