检索结果-南通市图书馆

Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 231-250页

作者： Tajmal Hussain Jongwon Seok Department of information and Communication engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product *** light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing *** this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual *** evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different *** ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted *** evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and *** analysis with recent studies also showed the superior performance of our methodology.

关键词： Smart manufacturing CNN steel defects ensemble models

Quantum public-key crypto via EPR pairs

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 58-63页

作者： Xiang-Qun Fu Hong-Wei Li Jian-Hong Shi Tan Li Wan-Su Bao Henan Key Laboratory of Quantum information and Cryptography Information Engineering University Synergetic Innovation Center of Quantum information and Quantum Physics University of Science and Technology of China

With the development of quantum computing technology, quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key cryptography. This paper designs a quantum trapdoor one-way function via EPR pairs and quantum measurements. Based on this, a new quantum public-key cryptosystem is presented, which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext attack. Compared with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition, which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs

Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril Department of Computer Science and engineering College of Engineering GuindyAnna UniversityChennai600025India Department of information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

Unraveling post-growth mechanisms of monolayer CsPbBr3 nanocubes:Laser-enhanced transformations and cathodoluminescence-electron microscopy correlations

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 146-156页

作者： Mingxing Li Xiaoge Wang Xiaofan Cao Zhiqun He Chunjun Liang Mingxing Chen Jing Ju Fangtian You Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic Technology Beijing Jiaotong University Beijing National Laboratory for Molecular Sciences (BNLMS) College of Chemistry and Molecular Engineering Peking University

Lead-halide perovskite nanoparticles（LHP NPs） are highly promising materials for next-generation displays and solid-state lighting due to their exceptional optical properties. However, their inherent instability presents a significant challenge. Recent advances have demonstrated that optoelectronic devices based on monolayer nanoparticle films exhibit both high luminescence efficiency and long-term *** research demonstrates that mobility limitations and anisotropic alignments in CsPbBr3nanocube monolayer films are key to their stabilization, hindering spontaneous growth through face-to-face fusion and resulting in the formation of connecting necks in a diagonal direction. Introducing laser irradiation confirmed this by significantly accelerating nanocubes growth, increasing mobility, and enhancing local structural ordering, leading to larger and more regularly shaped nanosheets. Fourier transform infrared spectroscopy and energy dispersive spectroscopy line-scan analyses indicated that laser irradiation did not disrupt the ligand structure. Transmission electron microscopy and correlative cathodoluminescence electron microscopy revealed the effects of post-growth and heterogeneous structures, including enhanced luminescence and inhomogeneous intensity in the nanosheets. These findings deepen the understanding of the post-growth mechanism of monolayer nanoparticles and the structure-emission correlation and highlight the unique role of laser irradiation in directing the formation of well-defined and regular nanostructures.

关键词： Post-growth mechanism Heterogeneous structure Single-particle spectroscopy Laser irradiation

A mechanical reinforced and antifreezing polyacrylate hydrogel electrolyte for high-performance zinc-ion batteries

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2025年第1期18卷 341-350页

作者： Zili Zhang Ruolin Wang Hongfei Lu Di Zhang Yu Zhao Jing Xu Bin Sun Zhi-Min Dang Yang Jin School of Electrical and information engineering Zheng Zhou UniversityZhengzhou 450001China State Key Lab of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

The operation of aqueous zinc-ion batteries in flexible energy storage field is plagued by the uncontrollable growth of Zn-dendrite and inevitable freeze of water below 0 ℃.Therefore,it is necessary to design a hydrogel electrolyte with good mechanical property and freezing resistance to uniform the Zn-deposition and resist flexibility loss at low *** find that the mechanical property(strength and toughness)of hydrogel electrolyte has a significant impact on the suppression of dendrite growth and the uniform deposition of zinc ***,a polyacrylate hydrogel is prepared in one step by ultraviolet(UV)curing method with Zn(CF_(3)SO_(3))_(2)salt and polyvinyl alcohol(PVA)addition to increase the antifreezing ability and mechanical *** adsorption of water molecules by 2-hydroxyethyl acrylate(HEA)and PVA reduces the freezing point of the hydrogel,which is beneficial for enhancing the electrochemical stability at low *** this basis,the Zn-symmetrical battery with hydrogel electrolyte has a long lifespan of 4710 h at 0.5 mA·cm^(-2)and 0.5 mAh·cm^(-2)at room ***,the hydrogel electrolyte exhibits an outstanding stability at low temperature of^(-2)0 ℃,the lifespan of symmetrical battery reaches to 4000 h at 0.5 mA·cm^(-2)and 0.5 mAh·cm^(-2).The assembled full cell with NaV3O8·1.5H_(2)O(NVO)cathode and hydrogel electrolyte possesses a high capacity retention ratio of 77%after 10,000 cycles at^(-2)0 ℃.The flexible cell can power light-emitting diode(LED)lamp under bending,warping and cutting without liquid leakage and an electronic watch at the operating temperature of^(-2)0 ℃.

关键词： zinc ion battery hydrogel electrolyte mechanical enhancement freezing resistance

A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea School of Electrical and Computer engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical engineering of Southern Medical university(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Performance of cumulant-based rank reduction estimator in presence of unexpected modeling errors

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Central South university 2015年第3期22卷 992-1001页

作者：王鼎 Institute of information System engineering PLA Information Engineering University

Compared with the rank reduction estimator(RARE) based on second-order statistics(called SOS-RARE), the RARE based on fourth-order cumulants(referred to as FOC-RARE) can handle more sources and restrain the negative impacts of the Gaussian colored noise. However, the unexpected modeling errors appearing in practice are known to significantly degrade the performance of the RARE. Therefore, the direction-of-arrival(DOA) estimation performance of the FOC-RARE is quantitatively derived. The explicit expression for direction-finding(DF) error is derived via the first-order perturbation analysis, and then the theoretical formula for the mean square error(MSE) is given. Simulation results demonstrate the validation of the theoretical analysis and reveal that the FOC-RARE is more robust to the unexpected modeling errors than the SOS-RARE.

关键词： fourth-order cumulants(FOC) rank reduction estimator(RARE) modeling error mean square error(MSE)

维普期刊数据库

Research on the Security Criterion of S-Boxes Against Division Property

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2021年第1期30卷 85-91页

作者： WANG Senpeng HU Bin GUAN Jie SHI Tairong ZHANG Kai pla SSF information engineering university

As a generalized integral property, division property was proposed by Todo at EUROCRYPT *** propose a new security criterion of S-boxes against division property and prove that it is invariant under permutation-xor equivalence. Based on the criterion, the division properties of some important 4-bit S-boxes are showed. Then, we apply it to improve the resistance of ciphers against division-property-based integral attacks while keeping the same security level against other ***, the resistance of the cipher PRESENT against division-property-based integral attack is improved by 2 rounds, and the resistance of the cipher LBlock against division-property-based integral attack is improved by 1 round.

关键词： cryptography permutation-xor equivalence division-property-based integral attack division property PRESENT cipher security criterion S-boxes LBlock cipher generalized integral property