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arXiv 2023年

作者： Liu, Wenjie Gao, PeiPei Wang, Yuxiang Yu, Wenbin Zhang, Maojun Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China College of Computer Science and Information Technology Guangxi Normal University Guilin China

In order to solve the problem of non-ideal training sets (i.e., the less-complete or over-complete sets) and implement one-iteration learning, a novel efficient quantum perceptron algorithm based on unitary weights is proposed, where the singular value decomposition of the total weight matrix from the training set is calculated to make the weight matrix to be unitary. The example validation of quantum gates {H, S, T, CNOT, Toffoli, Fredkin} shows that our algorithm can accurately implement arbitrary quantum gates within one iteration. The performance comparison between our algorithm and other quantum perceptron algorithms demonstrates the advantages of our algorithm in terms of applicability, accuracy, and availability. For further validating the applicability of our algorithm, a quantum composite gate which consists of several basic quantum gates is also illustrated. © 2023, CC BY.

关键词： Singular value decomposition

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A Robust Watermarking Scheme Based on ROI and IWT for Remote Consultation of COVID-19

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computers, Materials & Continua 2020年第9期64卷 1435-1452页

作者： Xiaorui Zhang Wenfang Zhang Wei Sun Tong Xu Sunil Kumar Jha Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow100031Poland

In the current dire situation of the corona virus COVID-19,remote consultations were proposed to avoid cross-infection and regional differences in medical ***,the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical *** ensure the integrity and security of medical images,this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest(ROI)and integer wavelet transform(IWT).First,the medical image is divided into two different parts,regions of interest and non-interest *** the integrity of ROI is verified using the hash algorithm,and the recovery data of the ROI region is calculated at the same ***,binary images with the basic information of patients are processed by logistic chaotic map encryption,and then the synthetic watermark is embedded in the medical carrier image using IWT *** performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the *** results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image *** maximum peak signal to noise ratio(PSNR)value of 51.24 has been achieved,which proves that the watermark is invisible and has strong robustness against noise,compression,and filtering attacks.

关键词： Digital watermarking logistic hash algorithm ROI IWT

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Soft Tissue Deformation Model Based on Marquardt Algorithm and Enrichment Function

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computer Modeling in engineering & Sciences 2020年第9期124卷 1131-1147页

作者： Xiaorui Zhang Xuefeng Yu Wei Sun Aiguo Song Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China

In order to solve the problem of high computing cost and low simulation accuracy caused by discontinuity of incision in traditional meshless model,this paper proposes a soft tissue deformation model based on the Marquardt algorithm and enrichment *** model is based on the element-free Galerkin method,in which Kelvin viscoelastic model and adjustment function are *** algorithm is applied to fit the relation between force and displacement caused by surface deformation,and the enrichment function is applied to deal with the discontinuity in the meshless *** verify the validity of the model,the Sensable Phantom Omni force tactile interactive device is used to simulate the deformations of stomach and *** results show that the proposed model improves the real-time performance and accuracy of soft tissue deformation simulation,which provides a new perspective for the application of the meshless method in virtual surgery.

关键词： Virtual surgery meshless model Marquardt algorithm enrichment function soft tissue simulation

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Impact Force Magnitude and Location Recognition of Composite Materials

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computers, Materials & Continua 2020年第9期64卷 1647-1656页

作者： Yajie Sun Yanqing Yuan Qi Wang Sai Ji Lihua Wang Shao’en Wu Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Science Ball State UniversityMuncieUSA

In order to identify the location and magnitude of the impact force accurately,determine the damage range of the structure and accelerate the health monitoring of key components of the composite,this paper studies the location and magnitude of the impact force of composite plates by an inverse ***,a PZT sensor mounted on the material plate is used to collect the response signal generated by the impact force,which is from several impact locations,and establish transfer functions between the impact location and the PZT ***,this paper applies several forces to any location on the material plate,and collects the corresponding response signals,and reconstructs the impact force of several locations in ***,according to the reconstruction result of each location,the correct impact location is ***,an improved regularization method is used to optimize the reconstructed impact force and accurate the magnitude of the impact *** comparison experiments prove that the recognition error of this method is smaller.

关键词： Impact force identification transfer function regularization

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Weak Fault Diagnosis of Rolling Bearing Based on Improved Stochastic Resonance

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computers, Materials & Continua 2020年第7期64卷 571-587页

作者： Xiaoping Zhao Yifei Wang Yonghong Zhang Jiaxin Wu Yunging Shi School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Automation Nanjing University of Information Science and TechnologyNanjing210044China Electrical and Computer Engineering New Jersey Institute of TechnologyNewark07102USA Network Monitoring Center of Jiangsu Province Nanjing University of Information Science and TechnologyNanjing210044China

Stochastic resonance can use noise to enhance weak signals,effectively reducing the effect of noise signals on feature *** order to improve the early fault recognition rate of rolling bearings,and to overcome the shortcomings of lack of interaction in the selection of SR(Stochastic Resonance)method parameters and the lack of validation of the extracted features,an adaptive genetic random resonance early fault diagnosis method for rolling bearings was *** with the existing methods,the AGSR(Adaptive Genetic Stochastic Resonance)method uses genetic algorithms to optimize the system parameters,and further optimizes the parameters while considering the interaction between the *** method can effectively extract the weak fault features of the *** order to verify the effect of feature extraction,the feature signal extracted by AGSR method was input into the Fully connected neural network for fault *** practicality of the algorithm is verified by simulation data and rolling bearing experimental *** results show that the proposed method can effectively detect the early weak features of rolling bearings,and the fault diagnosis effect is better than the existing methods.

关键词： Rolling bearing weak fault stochastic resonance genetic algorithm neural network

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Cubic convolutional neural network for hyperspectral image classification 6th

Cubic convolutional neural network for hyperspectral image c...

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Sun, Le Song, Xiangbo Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789811581007

In recent years, the framework of convolutional neural network based on deep learning (DL) has made good progress in the field of hyperspectral image (HSI) classification. In order to improve the classification accuracy and reduce the time complexity of the model, we proposed an end-to-end cubic convolution neural network (C-CNN) framework for the classification of HSI. C-CNN uses one-dimensional convolution and principal component analysis (PCA) operation respectively to reduce the dimension of the original HSI, and merges the processed data. Then through convolving the data cube from the spatial domain and the spatial-spectral domain respectively, deep features of HSI are obtained. Batch normalization and dropout layers are used to prevent overfitting. The proposed C-CNN framework can achieve the optimal results within 80 epochs. Experimental results with widely used hyperspectral image datasets show that the proposed method surpasses the existing state-of-the-art methods based on DL. © Springer Nature Singapore Pte Ltd 2020.

关键词： Convolution

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An Improvement of Coherent Semantic Attention for Image Inpainting 1

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Wang, Weiqing Gu, Enming Fang, Wei School of Computer & Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Jiangsu Key Laboratory of Computer Information Process Technology SooChow University Suzhou China

ISBN: (数字)9789811580833

ISBN: (纸本)9789811580826

In some image restoration algorithms of the past, they often do not consider the continuity between pixels, and the internal features of the hole region. The mapping to the image semantically does not take into account the continuity of the feature, resulting in the color of the fault. Or the deformation of the edge contour of the image. In some of the current popular algorithms and models, we can clearly see the color faults and artificial repair traces from their repair results. These discontinuities are mainly because these methods ignore the semantic relevance and feature continuity of the hole region. Therefore, if we want to get a better image repair effect. We have to improve on semantic relevance and feature continuity. We validated the effectiveness of our proposed method in image restoration tasks on the CelebA and Places2 datasets, and our results yielded a better visual experience in some images than existing methods. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Semantics

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The Numerical Results of Binary Coherent-State Signal’s Quantum Detection in the Presence of Noise 6th

The Numerical Results of Binary Coherent-State Signal’s Qua...

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6th International Conference on Artificial Intelligence and Security, ICAIS 2020

作者： Yu, Wenbin Xiong, Zijia Dong, Zangqiang Xu, Yinsong Liu, Wenjie Qu, Zhiguo Liu, Alex X. Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China The Department of Computer Science and Application Zhengzhou Institute of Aeronautical Industry Management ZhengzhouHenan450015 China Department of Computer Science and Engineering Michigan State University East LansingMI48824-1226 United States

ISBN: (纸本)9783030578831

In the optical frequency level communication, quantum effect becomes the source of significant communication errors. One alternative to classical detection is orthogonal projection measurement. In this paper, based on the coherent state’s quantum measurement and discrimination, the quantum optimal detection of binary coherent state signal in the presence of thermal noise was studied. Our numerical results showed the error probabilities of quantum detection under the OOK and BPSK modulation, and verified the performance of these two modulation methods in the thermal noise field background. © 2020, Springer Nature Switzerland AG.

关键词： Optical communication

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Semi-supervised stacked autoencoder-based deep hierarchical semantic feature for real-time fingerprint liveness detection

Semi-supervised stacked autoencoder-based deep hierarchical ...

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作者： Yuan, Chengsheng Chen, Xianyi Yu, Peipeng Meng, Ruohan Cheng, Weijin Wu, Q. M. Jonathan Sun, Xingming School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing210044 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada

The popularity of biometric authentication technology benefits from the rapid development of smart mobile devices in recent years, and fingerprints, which are inherent human traits and neither easily revealed nor deciphered, can be used for real-time individual authentication systems. However, the main security issue of real-time fingerprint authentication systems is that most fingerprint scanners are vulnerable to presentation attacks by artificial replicas, made from plastic clay, gelatin, silicon, wood glue, etc. One anti-spoofing attack scheme, called real-time fingerprint liveness detection (RFLD), has been proposed to discriminate live or fake fingerprints. Currently, to resolve the presentation attacks, most RFLD solutions all relied on handcrafted feature extraction and selection. The features extracted by manual method are shallow features of the samples;however, autoencoder can automatically learn deep hierarchical semantic features representation of the samples, thus replacing the operations extracted with hand-designed features. In this paper, we apply stacked autoencoder to RFLD to significantly lower the work-force burden of the feature extraction engineering, and our model consists of two parts: parameter pre-training based on unsupervised learning and FLD based on supervised learning. The performance has been verified on two public fingerprint datasets: LivDet 2011 and 2013, and the experimental results indicate that our proposed approach works well for RFLD as well as the detection performance is satisfactory. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Feature extraction

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Quantum Searchable Encryption for Cloud Data Based on Delegating Quantum Computing 9th

Quantum Searchable Encryption for Cloud Data Based on Delega...

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9th EAI International Conference on Cloud Computing, CloudComp 2019 and the 4th EAI International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019

作者： Xu, Yinsong Liu, Wenjie Chen, Junxiu Tong, Lian School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Information Engineering Jiangsu Maritime Institute Nanjing211100 China

ISBN: (纸本)9783030485122

Based on delegating quantum computing (DQC), a DQC model that adapts to multi-qubit and composite quantum circuits is given firstly. In this model, the single client with limited quantum ability can give her encrypted data to a powerful but untrusted quantum data server and let the data server computes over the encrypted data without decryption, where the computation is a quantum circuit composed of multiple quantum gates. Then, the client generates the decryption key to decrypt the computing result according to the circuit of computation. However, this model cannot meet the situation of multi-client accessing or computing encrypted cloud data in the cloud environment. To solve this problem, we let the client outsource key generation to a trusted key server, which composes the quantum cloud center with the data server. The clients only perform X and Z operation according to the encryption or decryption key. Then, combined with Grover algorithm, a quantum searchable encryption scheme for cloud data based on delegating quantum computing is proposed in this paper. The data server mainly uses Grover algorithm to perform search computation on the encrypted data. Moreover, a concrete example of our scheme is discussed next, where the data server searches for 2 target items from 8 items of the encrypted data. Finally, security of our proposed scheme is analysed, which can protect the security of the data. © 2020, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Trusted computing

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