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Hyperspectral image super resolution using deep internal and self-supervised learning

CAAI Transactions on Intelligence technology 2024年第1期9卷 128-141页

作者： Zhe Liu Xian-Hua Han graduate school of science and technology for Innovation Yamaguchi UniversityYamaguchiJapan graduate school of Artificial Intelligence and science Rikkyo UniversityTokyoJapan

By automatically learning the priors embedded in images with powerful modelling ca-pabilities,deep learning-based algorithms have recently made considerable progress in reconstructing the high-resolution hyperspectral(HR-HS)*** previously collected large-amount of external data,these methods are intuitively realised under the full supervision of the ground-truth ***,the database construction in merging the low-resolution(LR)HS(LR-HS)and HR multispectral(MS)or RGB image research paradigm,commonly named as HSI SR,requires collecting corresponding training triplets:HR-MS(RGB),LR-HS and HR-HS image simultaneously,and often faces dif-ficulties in *** learned models with the training datasets collected simultaneously under controlled conditions may significantly degrade the HSI super-resolved perfor-mance to the real images captured under diverse *** handle the above-mentioned limitations,the authors propose to leverage the deep internal and self-supervised learning to solve the HSI SR *** authors advocate that it is possible to train a specific CNN model at test time,called as deep internal learning(DIL),by on-line preparing the training triplet samples from the observed LR-HS/HR-MS(or RGB)images and the down-sampled LR-HS ***,the number of the training triplets extracted solely from the transformed data of the observation itself is extremely few particularly for the HSI SR tasks with large spatial upscale factors,which would result in limited reconstruction *** solve this problem,the authors further exploit deep self-supervised learning(DSL)by considering the observations as the unlabelled training ***,the degradation modules inside the network were elaborated to realise the spatial and spectral down-sampling procedures for transforming the generated HR-HS estimation to the high-resolution RGB/LR-HS approximation,and then the reconstruction errors of the observations were formulated for mea

关键词： computer vision deep learning deep neural networks hyperspectral image enhancement

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Programmable directional color dynamics using plasmonics

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Microsystems & Nanoengineering 2024年第1期10卷 325-334页

作者： Gyurin Kim Doeun Kim Soeun Ko Jang-Hwan Han Juhwan Kim Joo Hwan Ko Young Min Song Hyeon-Ho Jeong school of Electrical Engineering and Computer science Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Department of Semiconductor Engineering Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Artificial Intelligence(AI)graduate school Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea

Adaptive multicolor filters have emerged as key components for ensuring color accuracy and resolution in outdoor visual ***,the current state of this technology is still in its infancy and largely reliant on liquid crystal devices that require high voltage and bulky structural ***,we present a multicolor nanofilter consisting of multilayered‘active’plasmonic nanocomposites,wherein metallic nanoparticles are embedded within a conductive polymer *** nanocomposites are fabricated with a total thickness below 100 nm using a‘lithography-free’method at the wafer level,and they inherently exhibit three prominent optical modes,accompanying scattering phenomena that produce distinct dichroic reflection and transmission ***,a pivotal achievement is that all these colors are electrically manipulated with an applied external voltage of less than 1 V with 3.5 s of switching speed,encompassing the entire visible ***,this electrically programmable multicolor function enables the effective and dynamic modulation of the color temperature of white light across the warm-to-cool spectrum(3250 K-6250 K).This transformative capability is exceptionally valuable for enhancing the performance of outdoor optical devices that are independent of factors such as the sun’s elevation and prevailing weather conditions.

关键词： directional prevailing exceptional

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Modifying Lyapunov exponent of chaotic map by self-cascading

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science China(Technological sciences) 2024年第7期67卷 2203-2214页

作者： YI ChenLong LI ChunBiao LI YongXin XIA Ming HUA ZhongYun school of Electronic and Information Engineering Nanjing University of Information Science&TechnologyNanjing 210044China school of Artificial Intelligence Nanjing University of Information Science&TechnologyNanjing 210044China school of Computer science and technology Harbin Institute of Technology Shenzhen Graduate SchoolShenzhen 518055China

The self-cascade(SC) method is an effective technique for chaos enhancement and complexity increasing in chaos ***, the controllable self-cascade(CSC) method allows for more accurate control of Lyapunov exponents of the discrete map. In this work, the SC and CSC systems of the original map are derived, which enhance the chaotic performance while preserving the fundamental dynamical characteristics of the original map. Higher Lyapunov exponent of chaotic sequences corresponding to higher frequency are obtained in SC and CSC systems. Meanwhile, the Lyapunov exponent could be linearly controlled with greater flexibility in the CSC system. The verification of the numerical simulation and theoretical analysis is carried out based on the platform of CH32.

关键词： self-cascade controllable self-cascade chaos enhancement chaos control

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Efficient flexible perovskite solar cells and modules using a stable SnO_(2)-nanocrystal isopropanol dispersion

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Nano Research 2024年第4期17卷 2704-2711页

作者： Zhiwei Su Jing Li Ruixuan Jiang Shujie Zhang Chengkai Jin Feng Ye Bingcan Ke Mengjun Zhou Jinhui Tong Hyesung Park Fuzhi Huang Yi-Bing Cheng Tongle Bu State Key Laboratory of Advanced technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China school of Material science and Engineering Wuhan University of TechnologyWuhan 430070China Department of Materials science and Engineering Graduate School of Semiconductor Materials and Devices EngineeringGraduate School of Carbon NeutralityLow Dimensional Carbon Materials CenterUlsan National Institute of Science and TechnologyUlsan 44919Republic of Korea Xianhu Laboratory of the Advanced Energy science and technology Guangdong Laboratory Foshan 528200China

The outstanding advantages of lightweight and flexibility enable flexible perovskite solar cells(PSCs)to have great application potential in mobile energy *** to the low cost,low-temperature processibility,and high electron mobility,SnO_(2) nanocrystals have been widely employed as the electron transport layer in flexible *** prepare high-quality SnO_(2) layers,a monodispersed nanocrystal solution is normally ***,the SnO_(2) nanocrystals can easily aggregate,especially after long periods of ***,we develop a green and cost-effective strategy for the synthesis of high-quality SnO_(2) nanocrystals at low temperatures by introducing small molecules of glycerol,obtaining a stable and well-dispersed SnO_(2)-nanocrystal isopropanol dispersion *** to the enhanced dispersity and super wettability of this alcohol-based SnO_(2)-nanocrystal solution,large-area smooth and dense SnO_(2) films are easily deposited on the plastic conductive ***,this contributes to effective charge transfer and suppressed non-radiative recombination at the interface between the SnO_(2) and perovskite *** a result,a greatly enhanced power conversion efficiency(PCE)of 21.8%from 19.2%is achieved for small-area flexible PSCs.A large-area 5 cm×5 cm flexible perovskite solar mini-module with a champion PCE of 16.5%and good stability is also demonstrated via this glycerol-modified SnO_(2)-nanocrystal isopropanol dispersion approach.

关键词： tin oxide isopropanol dispersion colloid stability flexible perovskite solar cells

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Enhancing SAEAs with unevaluated solutions:a case study of relation model for expensive optimization

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science China(Information sciences) 2024年第2期67卷 41-58页

作者： Hao HAO Xiaoqun ZHANG Aimin ZHOU Institute of natural sciences Shanghai Jiao Tong University Shanghai Frontiers science Center of Molecule Intelligent Syntheses school of Computer science and technology East China Normal University

Surrogate-assisted evolutionary algorithms(SAEAs) hold significant importance in resolving expensive optimization problems. Extensive efforts have been devoted to improving the efficiency of SAEAs through the development of proficient model-assisted solution selection methods, which, however, first requires generating high-quality solutions. The fundamental paradigm of evaluating a limited number of solutions in each generation within SAEAs reduces the variance of adjacent populations, thereby affecting the quality of offspring solutions. This is a frequently encountered issue yet receives little attention. To address the issue, this paper presents a framework using unevaluated solutions to enhance the efficiency of *** surrogate model is employed to identify high-quality solutions for the direct generation of new solutions without evaluation. To ensure dependable selection, we have introduced two tailored relation models to select the optimal solution and the unevaluated population. A comprehensive experimental analysis is performed on two test suites, which showcases the superiority of the relation model over regression and classification models in the solution selection phase. Furthermore, the surrogate-selected unevaluated solutions with high potential have been shown to enhance the efficiency of the algorithm significantly.

关键词： expensive optimization unevaluated solutions relation model surrogate-assisted evolutionary algorithm

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Numerical insight into heat transfer enhancement by granules inner-migration in a moving bed:A performance comparison between slanted-stick and plow-shaped agitator

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Particuology 2024年第6期89卷 109-116页

作者： Binfan Jiang Hao Pei Dehong Xia Haiyang Wang school of Energy and Environmental Engineering University of Science and Technology BeijingBeijing 100083China Shunde graduate school of University of science and technology Beijing Guangdong 528399China Jianlong Group&USTB Joint Laboratory Beijing 100083China

Waste heat recovery of high-temperature granules is one of the most promising sustainable energy supply and carbon reduction ways for industry.A moving bed indirect heat exchanger(MBIHE)with inner-migration was proposed for granular heat *** migration and the enhanced heat transfer induced by two types of agitators(i.e.,agitator with slanted stick A_(s)and with plow-shaped surface A_(p))in the MBIHE are analyzed based on DEM coupled with *** to the effective agitation,the average heat transfer coefficient in the granule side is enhanced to∼3 times compared to that without *** heat recovery efficiency in the moving bed reached more than 70%with the agitations of either A_(s)or A_(p).The heat efficiency of A_(s)is∼7%higher than that of A_(p),but with at least 60%greater rotational *** ensure reliable agitation,the A_(p)is suggested to be adopted in the MBIHE to induce granule migration.

关键词： Waste heat recovery High-temperature granule Granule migration Heat transfer enhancement Industry energy saving

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Fast Cross-Platform Binary Code Similarity Detection Framework Based on CFGs Taking Advantage of NLP and Inductive GNN

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Chinese Journal of Electronics 2024年第1期33卷 128-138页

作者： Jinxue PENG Yong WANG Jingfeng XUE Zhenyan LIU school of Computer science and technology Beijing Institute of Technology

Cross-platform binary code similarity detection aims at detecting whether two or more pieces of binary code are similar or not. Existing approaches that combine control flow graphs(CFGs)-based function representation and graph convolutional network(GCN)-based similarity analysis are the best-performing ones. Due to a large amount of convolutional computation and the loss of structural information, the use of convolution networks will inevitably bring problems such as high overhead and sometimes inaccuracy. To address these issues, we propose a fast cross-platform binary code similarity detection framework that takes advantage of natural language processing(NLP)and inductive graph neural network(GNN) for basic blocks embedding and function representation respectively by simulating extracting structural features and temporal features. GNN’s node-centric and small batch is a suitable training way for large CFGs, it can greatly reduce computational overhead. Various NLP basic block embedding models and GNNs are evaluated. Experimental results show that the scheme with long short term memory(LSTM)for basic blocks embedding and inductive learning-based Graph SAGE(GAE) for function representation outperforms the state-of-the-art works. In our framework, we can take only 45% overhead. Improve efficiency significantly with a small performance trade-off.

关键词： Training Semantics Process control Binary codes Feature extraction natural language processing Graph neural networks

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Effect of strain on structure and electronic properties of monolayer C_(4)N_(4)

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Chinese Physics B 2024年第5期33卷 595-600页

作者：陈昊徐瑛赵家石周丹 school of Physics Changchun University of Science and TechnologyChangchun 130022China school of Computer science and technology Changchun University of Science and TechnologyChangchun 130022China

The first-principles calculations are performed to examine structural,mechanical,and electronic properties at large strain for a monolayer C_(4)N_(4),which has been predicted as an anchoring promising material to attenuate shuttle effect in Li–S batteries stemming from its large absorption energy and low diffusion energy *** results show that the ideal strengths of C_(4)N_(4)under tension and pure shear deformation conditions reach 13.9 GPa and 12.5 GPa when the strains are 0.07 and 0.28,*** folded five-membered rings and diverse bonding modes between carbon and nitrogen atoms enhance the ability to resist plastic deformation of C_(4)N_(4).The orderly bond-rearranging behaviors under the weak tensile loading path along the[100]direction cause the impressive semiconductor–metal transition and inverse semiconductor–metal *** present results enrich the knowledge of the structure and electronic properties of C_(4)N_(4)under deformations and shed light on exploring other two-dimensional materials under diverse loading conditions.

关键词： two-dimensional materials strain effect structural evolution electronic properties

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Neural network study of the nuclear ground-state spin distribution within a random interaction ensemble

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Nuclear science and Techniques 2024年第3期35卷 216-227页

作者： Deng Liu Alam Noor A Zhen-Zhen Qin Yang Lei school of Mathematics and Physics Southwest University of Science and TechnologyMianyang 621010China school of Nuclear science and technology Southwest University of Science and TechnologyMianyang 621010China

The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output *** quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the ***,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.

关键词： Neural network Two-body random ensemble Spin distribution of nuclear ground state

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Single transition-metal atoms anchored on a novel Diracdispersive π-π conjugated holey graphitic carbon nitride substrate:computational screening toward efficient bifunctional OER/ORR electrocatalysts

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Rare Metals 2024年第8期43卷 3819-3832页

作者： Chun-Yao Fang Xi-Hang Zhang Qiang Zhang Di Liu Xiao-Meng Cui Jing-Cheng Xu Cheng-Long Shi Meng-Yu Yang College of science University of Shanghai for Science and Technology school of Materials and Chemistry University of Shanghai for Science and Technology

Nonprecious-metal-group single-metal-atom catalysts with bifunctional catalytic capabilities toward the oxygen evolution reaction（OER） and oxygen reduction reaction（ORR） are highly sought after in energy-conversion and storage ***,producing renewable and sustainable energy sources remains ***,single-transition metal atoms anchored on π-πconjugated two-dimensional（2D） graphitic carbon nitride substrates form π-d conjugated conductive channels that enhance the overall electrocatalytic ***,firstprinciples calculations were carried out to design and demonstrate a novel macropore graphitic carbon nitride(gC10N3) as a promising 2D electrocatalyst substrate to support single-transition metal（TM,from Sc to Au）.The "donation-acceptance" charge interaction in the TM-N2moiety effectively balances the adsorption strength of oxygenated intermediates in Ni@g-C10N3and Rh@gC10N3,making them effective bifunctional OER/ORR electrocatalysts with IrO2/Pt-beyond overpotentials being as low as 0.39/0.38 V and 0.54/0.44 V,***,they possess high stability and conductivity and are less susceptible to oxidation and corrosion under working *** guarantees high activity under ambient ***,the origin of the OER/ORR activity of TM@g-C10N3is explained using multilevel descriptors:intrinsic(p,Bader charge,integral crystal orbital Hamilton population（ICOHP）,bond length,and d-band center（εd）.In particular,for optimal Ni@g-C10N3,the clear hybridization between the Ni-d orbital and surface O-p orbital causes the paired electrons to occupy the bonding *** enables OH*to be adsorbed on the Ni@g-C10N3,thereby achieving the highest catalytic performance.

关键词： First-principles calculation Oxygen evolution reaction Oxygen reduction reaction Bifunctional electrocatalysts Single-metal-atom electrocatalysts

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