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An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization

computer Modeling in engineering & sciences 2023年第5期135卷 1571-1587页

作者： Jun Liu Geng Yuan Changdi Yang Houbing Song Liang Luo Robotics Institute School of Computer ScienceCarnegie Mellon UniversityPittsburghPA15217USA Department of Electrical&Computer Engineering College of EngineeringNortheastern UniversityBostonMA02115USA Security and Optimization for Networked Globe Laboratory(SONG Lab) Embry-Riddle Aeronautical UniversityDaytona BeachFL32114USA School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu610054China

The interpretability of deep learning models has emerged as a compelling area in artificial intelligence *** safety criteria for medical imaging are highly stringent,and models are required for an ***,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and ***,the interpretability of CNNs has come into the *** medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning ***,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these *** this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac *** enhanced GPU training system implemented interpretable global average pooling for graphics using deep *** deep learning tasks were *** included data management,neural network architecture,and *** system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment *** results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning *** model is lightweight and more convenient to deploy on mobile devices than transfer learning models.

关键词： Interpretable graphics training visualization image segmentation left ventricle CNNs global average pooling

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Reversible Data Hiding With Secret Encrypted Image Sharing and Adaptive Coding

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IEEE Internet of Things Journal 2025年第13期12卷 23933-23945页

作者： Fang, Guangtian Wang, Feng Zhao, Chenbin Qin, Chuan Chang, Ching-Chun Chang, Chin-Chen Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Fujian University of Technology College of Computer Science and Mathematics Key Laboratory of Big Data Mining and Applications Fuzhou350118 China Monash University Faculty of IT Department of Software Systems and Cybersecurity VIC3800 Australia Ministry of Education School of Cyber Science and Engineering Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan430072 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Feng Chia University Information and Communication Security Research Center Taichuang 40724 Taiwan Feng Chia University Department of Information Engineering and Computer Science Taichung40724 Taiwan

To ensure the security of image information and facilitate efficient management in the cloud, the utilization of reversible data hiding in encrypted images (RDHEI) has emerged as pivotal. However, most existing RDHEI schemes suffer from lower security and limited embedding capacity. To tackle these challenges, we propose a reversible data hiding with secret encrypted image sharing and adaptive coding scheme. Specifically, in the encryption phase, we introduce an improved secret sharing (SS) encryption method based on the chinese remainder theorem for polynomials (CRTP). This method not only improves the security of encrypted images but also vacates a larger room for embedding. In the embedding phase, we introduce an adaptive coding embedding approach using XOR preservation (XORP) and huffman coding, which provides high embedding capacity. Experimental results and security analysis demonstrate that our proposed encryption method achieves optimal values in security indicators for encrypted images, such as information entropy, histograms, NPCR and UACI. The proposed embedding method is superior to some state-of-the-art schemes in terms of embedding capacity. Furthermore, in datasets BOSSBase and BOWS2, the average embedding rates of the proposed embedding approach can reach 2.1745 bpp and 2.0656 bpp, respectively. © 2025 IEEE.

关键词： Cryptography Encryption Security Data mining Adaptive coding Correlation Cloud computing Polynomials Image coding Streaming media

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Arbitrary acoustic orbital angular momentum detection using dual-layer metasurfaces

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science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 106-112页

作者： Zhanlei Hao Haojie Chen Yuhang Yin Shan Zhu Yadong Xu Cheng-Wei Qiu Huanyang Chen Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China School of Physical Science and Technology and Jiangsu Key Laboratory of Thin Films Soochow UniversitySuzhou 215006China

Orbital angular momentum(OAM),with its unique physical properties and vast application prospects,has attracted widespread attention in various ***,the development of valid and practical acoustic OAM detection methods continues to be a challenging *** this paper,we propose a novel construction method of dual-layer metasurfaces to achieve a doubleconversion process for the waveform reshaping and differentiated focusing of two-dimensional vortex sources with different ***,by utilizing a concise formula,a one-to-one correspondence is established between the OAM of incident vortex waves and different imaging *** fundamental principle of this special conversion relationship is rigorously constrained by the directional compensation of phase and the material parameters of dual-layer metasurfaces with different quadratic phase *** importantly,the highly consistent results between numerical demonstrations and acoustic experiments further confirm the feasibility and effectiveness of the proposed OAM detection *** work provides a new perspective on the precise manipulation for the phase of vortex fields,holding potential applications in super-resolution imaging and the design of acoustic OAM-based devices.

关键词： arbitrary acoustic OAM detection vortex waves dual-layer metasurfaces waveform reshaping differentiated focusing acoustic experiments

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Schottky barrier modulation of bottom contact SnO_(2) thin-film transistors via chloride-based combustion synthesis

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Journal of Materials science & Technology 2023年第17期148卷 199-208页

作者： Bongho Jang Junhee Lee Hongki Kang Jaewon Jang Hyuk-Jun Kwon Department of Electrical Engineering and Computer Science DGISTDaegu 42988South Korea School of Electronic and Electrical Engineering Kyungpook National UniversityDaegu 41566South Korea School of Electronics Engineering Kyungpook National UniversityDaegu 41566South Korea Convergence Research Advanced Centre for Olfaction DGISTDaegu 42988South Korea

The enhanced carrier flow at the interface between Au and SnO_(2)semiconductors,which initially form Schottky contacts,is realized using chloride-based combustion ***-based combustion sys-tems can achieve chlorine(Cl)doping effects as well as conversion to crystalline SnO_(2)films at clearly lower temperatures(∼250℃)than conventional *** to the Cl doping effect,the high carrier concentration can induce thin potential barriers at the metal/semiconductor(MS)junctions,resulting in carrier injection by *** a result,compared to conventional SnO_(2)thin-film transistors,the de-vices fabricated by combustion synthesis exhibit significantly improved electrical performance with field-effect mobility of 6.52 cm 2/Vs(∼13 times),subthreshold swing of 0.74 V/dec,and on/offratio of∼10^(7)below 300℃.Furthermore,because of the enhanced tunneling carriers induced by the narrowed barrier width,the Schottky barriers are significantly reduced from 0.83 to 0.29 eV(65%decrease)at 250℃and from 0.42 to 0.17 eV(60%decrease)at 400℃.Therefore,chloride-based combustion synthesis can con-tribute to developing SnO_(2)-based electronics and flexible devices by achieving both high-quality oxide films and improved current flow at the MS interface with low-temperature annealing.

关键词： SnO_(2) Combustion Sol-gel Schottky contact Thin-film transistors

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Unpaired remote sensing image super-resolution with content-preserving weak supervision neural network

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science China(Information sciences) 2023年第1期66卷 324-325页

作者： Jie WU Runmin CONG Leyuan FANG Chunle GUO Bob ZHANG Pedram GHAMISI College of Electrical and Information Engineering Hunan University Institute of Information Science Beijing Jiaotong University College of Computer Science Nankai University Department of Computer and Information Science University of Macau Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology Institute of Advanced Research in Artificial Intelligence (IARAI)

Dear editor,Image super-resolution(SR) uses image processing methods to increase the resolution of the image without increasing any hardware cost. Remote sensing images with high spatial resolution contain rich imagery information, which can be utilized for object detection, building segmentation, building extraction, change detection, and so on.

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Dark Forest Algorithm:A Novel Metaheuristic Algorithm for Global Optimization Problems

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computers, Materials & Continua 2023年第5期75卷 2775-2803页

作者： Dongyang Li Shiyu Du Yiming Zhang Meiting Zhao Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo315000China Engineering Laboratory of Advanced Energy Materials Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo315000China School of Material and Chemical Engineering Ningbo UniversityNingbo315000China

Metaheuristic algorithms,as effective methods for solving optimization problems,have recently attracted considerable attention in science and engineering *** are popular and have broad applications owing to their high efficiency and low *** algorithms are generally based on the behaviors observed in nature,physical sciences,or *** study proposes a novel metaheuristic algorithm called dark forest algorithm(DFA),which can yield improved optimization results for global optimization *** DFA,the population is divided into four groups:highest civilization,advanced civilization,normal civilization,and low *** civilization has a unique way of *** verify DFA’s capability,the performance of DFA on 35 well-known benchmark functions is compared with that of six other metaheuristic algorithms,including artificial bee colony algorithm,firefly algorithm,grey wolf optimizer,harmony search algorithm,grasshopper optimization algorithm,and whale optimization *** results show that DFA provides solutions with improved efficiency for problems with low dimensions and outperforms most other algorithms when solving high dimensional *** applied to five engineering projects to demonstrate its *** results show that the performance of DFA is competitive to that of current well-known metaheuristic ***,potential upgrading routes for DFA are proposed as possible future developments.

关键词： Metaheuristic algorithm global optimization

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Control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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Functional plastic films:nano-engineered composite based flexible microwave antennas with near-unity relative visible transmittance

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Light(advanced Manufacturing) 2024年第2期5卷 95-105页

作者： Cheng Zhang Liang Zhu Chengang Ji Zhilu Ye Nabeel Alsaab Minye Yang Yuhui Hu Pai-Yen Chen L.Jay Guo School of Optical and Electronic Information&Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicagoIL 60607USA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA

Microwave antennas are essential elements for various applications,such as telecommunication,radar,sensing,and wireless power *** antennas are conventionally manufactured on rigid substrates using opaque materials,such as metal strips,metallic tapes,or epoxy pastes;thus,prohibiting their use in flexible and wearable devices,and simultaneously limiting their integration into existing optoelectronic ***,we demonstrate that mechanically flexible and optically transparent microwave antennas with high operational efficiencies can be readily fabricated using composite nanolayers deposited on common plastic *** composite nanolayer structure consists of an ultra-thin copper-doped silver film sandwiched between two dielectric films of tantalum pentoxide and aluminum *** material and thickness of each constituent layer are judiciously selected such that the whole structure exhibits an experimentally measured averaged visible transmittance as high as 98.94%compared to a bare plastic substrate,and simultaneously,a sheet resistance as low as 12.5Ω/*** representative types of microwave antennas are implemented:an omnidirectional dipole antenna,unidirectional Yagi-Uda antenna,low-profile patch antenna,and Fabry-Pérot cavity *** devices exhibit great mechanical flexibility with bending angle over 70°,high gain of up to 13.6 dBi,and large radiation efficiency of up to 84.5%.The proposed nano-engineered composites can be easily prepared over large areas on various types of substrates and simultaneously overcome the limitations of poor mechanical flexibility,low electrical conductivity,and reduced optical transparency usually faced by other constituent materials for flexible transparent microwave *** demonstrated flexible microwave antennas have various applications ranging from fifth-generation and vehicular communication systems to bio-signal monitors and wearable electronics.

关键词： Optically transparent antenna Flexible microwave antenna Transparent conductor Ultra-thin silver Doped silver Wearable optoelectronics

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Continuous-Time Prediction of Industrial Paste Thickener System With Differential ODE-Net

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 686-698页

作者： Zhaolin Yuan Xiaorui Li Di Wu Xiaojuan Ban Nai-Qi Wu Hong-Ning Dai Hao Wang the Beijing Advanced Innovation Center for Materials Genome Engineering Institute of Artificial IntelligenceBeijing Key Laboratory of Knowledge Engineering for Materials ScienceSchool of Computer and Communication EngineeringUniversity of Science and Technology Beijing the Department of ICT and Natural Science Norwegian University of Science and Technology IEEE the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and Technology the Department of Computing and Decision Sciences Lingnan University the Department of Computer Science Norwegian University of Science and Technology

It is crucial to predict the outputs of a thickening system,including the underflow concentration(UC)and mud pressure,for optimal control of the *** proliferation of industrial sensors and the availability of thickening-system data make this ***,the unique properties of thickening systems,such as the non-linearities,long-time delays,partially observed data,and continuous time evolution pose challenges on building data-driven predictive *** address the above challenges,we establish an integrated,deep-learning,continuous time network structure that consists of a sequential encoder,a state decoder,and a derivative module to learn the deterministic state space model from thickening *** a case study,we examine our methods with a tailing thickener manufactured by the FLSmidth installed with massive sensors and obtain extensive experimental *** results demonstrate that the proposed continuous-time model with the sequential encoder achieves better prediction performances than the existing discrete-time models and reduces the negative effects from long time delays by extracting features from historical system *** proposed method also demonstrates outstanding performances for both short and long term prediction tasks with the two proposed derivative types.

关键词： Industrial 24 paste thickener ordinary differential equation(ODE)-net recurrent neural network time series prediction

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A machine learning scheme to assess the radio propagation conditions on wireless communication networks

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Journal of Ambient Intelligence and Humanized Computing 2025年 1-14页

作者： Galvan-Tejada, Giselle M. Martinez-Enriquez, Ana Maria Department of Electrical Engineering Center for Research and Advanced Studies of IPN Av. IPN 2508 Mexico City San Pedro Zacatenco07360 Mexico Department of Computer Science Center for Research and Advanced Studies of IPN Av. IPN 2508 Mexico City San Pedro Zacatenco07360 Mexico

Wireless communication has become the primary means of electronic communication around the world. Particularly, we focus on the radio propagation conditions of a wireless sensor network (WSN), our case study, where common methods exist for measurements of WSN’s performance. However, these methods are expensive and not fully automated, and therefore they have severe drawbacks and limitations. Thus, this paper describes an automatic, simple, and fast-answer system for solving practical radio-communication problems by resorting to two branches of artificial intelligence: machine learning and knowledge-based systems (KBS). The non-incremental unsupervised learning module classifies a dataset into clusters that are then computed in order to induce concepts, which are specific features shared by every dataset within a cluster. These concepts serve to construct implication rules being the knowledge used by the KBS in charge of answering queries about WSN in radio propagation conditions. Furthermore, given that WSN is a dynamic environment, our system also incorporates an incremental supervised learning module in order to process a new received reduced dataset, and potentially to induce new concepts and update the knowledge base of implication rules. Such process is performed unchanging the inference engine module of our KBS. Finally, we provide illustrating examples of our approach’s abilities for query-answering, highlighting that its response time fulfills restricted real-world conditions thanks to the conception of polynomial-complexity algorithms on which our system runs, and which are among our contributions. © The Author(s) 2025.

关键词： Unsupervised learning

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