检索结果-南通市图书馆

维普期刊数据库

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第6期79卷 4825-4844页

作者： Ahmed H.Alhadethi Ikram Smaoui Ahmed Fakhfakh Saad M.Darwish Computer Science and school of electronics and telecommunications University of SfaxSfax3029Tunisia LETI Laboratory University of SfaxSfax3029Tunisia Digital Research Center of sfax Technopark of SfaxSfax3029Tunisia Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandriaEgypt

The act of transmitting photos via the Internet has become a routine and significant *** the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further *** study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous *** main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image *** paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during *** employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious ***,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been *** applications involving the transmission and sharing of images across a *** suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture *** effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of *** scheme ensures a large reduction in computational and energy requirements while minimizing image quality *** approach employs multi-scale characteristics to improve the resistance of signatures against image *** proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

关键词： Image transmission image compression text hiding Bezier curve Histogram of Oriented Gradients(HOG) LSTM image enhancement Gaussian noise rotation

FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of electronics 2024年第1期33卷 58-71页

作者： Zeyi LI Pan WANG Zixuan WANG school of Computer Science Nanjing University of Posts and Telecommunications school of Modern Posts Nanjing University of Posts and Telecommunications school of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Deep learning Machine learning algorithms Computational modeling Network intrusion detection Imaging Telecommunication traffic Generative adversarial networks

Road map for, and technical challenges of, carbon-nanotube integrated circuit technology

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

national Science Review 2024年第3期11卷 14-16页

作者： Jia Si Panpan Zhang Zhiyong Zhang Key Laboratory for the Physics and Chemistry of Nanodevices and Center for Carbon-based electronics School of Electronics Peking University State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications

The past decade has witnessed an explosion of research on carbon-nanotube(CNT) electronics due to their outstanding properties, including an ultrathin body, a high carrier mobility and a high saturation velocity.

关键词： TRANSISTORS

FSCIL-EACA: Few-Shot Class-Incremental Learning Network Based on Embedding Augmentation and Classifier Adaptation for Image Classification

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of electronics 2024年第1期33卷 139-152页

作者： Ruru ZHANG Haihong E Meina SONG school of Computer Science Beijing University of Posts and Telecommunications Education Department Information Network Engineering Research Center Beijing University of Posts and Telecommunications

The ability to learn incrementally is critical to the long-term operation of AI systems. Benefiting from the power of few-shot class-incremental learning(FSCIL), deep learning models can continuously recognize new classes with only a few samples. The difficulty is that limited instances of new classes will lead to overfitting and exacerbate the catastrophic forgetting of the old classes. Most previous works alleviate the above problems by imposing strong constraints on the model structure or parameters, but ignoring embedding network transferability and classifier adaptation(CA), failing to guarantee the efficient utilization of visual features and establishing relationships between old and new classes. In this paper, we propose a simple and novel approach from two perspectives: embedding bias and classifier bias. The method learns an embedding augmented(EA) network with cross-class transfer and class-specific discriminative abilities based on self-supervised learning and modulated attention to alleviate embedding bias. Based on the adaptive incremental classifier learning scheme to realize incremental learning capability,guiding the adaptive update of prototypes and feature embeddings to alleviate classifier bias. We conduct extensive experiments on two popular natural image datasets and two medical datasets. The experiments show that our method is significantly better than the baseline and achieves state-of-the-art results.

关键词： Training Adaptation models Visualization Image recognition Prototypes Self-supervised learning Power capacitors

Polyimide covalent organic frameworks as efficient solid-state Li^(+) electrolytes

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China Chemistry 2024年第5期67卷 1647-1652页

作者： Xu Liu Shi Wang Siqi Liu Chengfang Liu Xiangchun Li Jian Wu Dazhi Li Shihao Xu Chongyang Liu Wen-Yong Lai State Key Laboratory of Organic electronics and Information Displays(SKLOEID) Institute of Advanced Materials(IAM)School of Chemistry and Life SciencesNanjing University of Posts&TelecommunicationsNanjing 210023China

Covalent organic frameworks(COFs) are attractive porous crystalline materials with extremely high stability, easy functionalization, and open channels, which are expected to be unique ion conductors/transporters in lithium ion batteries(LIBs). Despite recent advances, low ion conductivity and low transference number, resulting in low charging/discharging rate, low energy density, and short battery life, are the main issues that limit their direct application as solid electrolytes in LIBs. Here, we designed and synthesized a novel polyimide COF, namely, TAPA-PDI-COF, with abundant C=O groups, which has been successfully employed as high-performance solid electrolytes by doping TAPA-PDI-COF and succinonitrile(SN). Both the well-defined nanochannels of COFs and SN confined in the well-aligned channels restricted the free migration of anions, while C=O on COFs and CN groups of SN enhanced Li^(+) transport, thus achieving a high ion conductivity of 0.102 m S cm^(-1)at 80 °C and a high lithium-ion transference number of 0.855 at room temperature. According to density functional theory(DFT)calculations, Li-ion migration mainly adopted in-plane transport rather than the axial pathway, which may be due to the shorter hopping distances in the planar pathway. The results suggest an effective strategy for the design and development of all-solidstate ionic conductors for achieving high-performance LIBs.

关键词： lithium ion batteries(LIBs) covalent organic frameworks(COFs) solid-state ion conductors solid-state electrolytes ion conductivity

维普期刊数据库

Optimizing Optical Fiber Faults Detection:A Comparative Analysis of Advanced Machine Learning Approaches

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第5期79卷 2697-2721页

作者： Kamlesh Kumar Soothar Yuanxiang Chen Arif Hussain Magsi Cong Hu Hussain Shah school of electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an710071China State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)*** emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of *** existingliterature witnessed various partial or inadequate *** the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and *** traditional fault managementsystems,this research has three-fold ***,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC ***,this paper assesses the classificationdelay of each classification ***,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults *** work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various *** addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid *** findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 *** the other hand,EL techniques improved the accuracy in detecting fiberoptic ***,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.

关键词： Fiber optics fault detection multiclassification machine learning ensemble learning

Single-Component Color-Tunable Smart Organic Emitters with Simultaneous Multistage Stimuli-Responsiveness and Multimode Emissions

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Research 2024年第2期2023卷 719-728页

作者： Yu Yan Chengfang Liu Jianzhong Fan Yusheng Li Huanling Liu Qian Wang Xiangchun Lil Junfeng Li Wen-Yong Lai State Key Laboratory of Organic electronics and Information Displays(SKLOEID) Institute of Advanced Materials(IAM)School of Chemistry and Life SciencesNanjing University of Posts&Telecommunications9 Wenyuan RoadNanjng 210023China Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

Achieving color-tunable emission in single-component organic emitters with multistage stimuli-responsiveness is of vital significance for intelligent optoelectronic applications,but remains enormously ***,we present an unprecedented example of a color-tunable single-component smart organic emitter(DDOP)that simultaneously exhibits multistage stimuli-responsiveness and multimode *** based on a highly twisted amide-bridged donor-tcceptor-donor structure has been found to facilitate intersystem crossing,form multimode emissions,and generate multiple emissive species with multistage *** pristine crystalline powders exhibit abnormal excitation-dependent emissions from a monomer-dominated blue emission centered at 470 nm to a dimer-dominated yellow emission centered at 550 nm through decreasing the ultraviolet(UV)excitation wavelengths,whereas DDOP single crystals show a wide emission band with a main emission peak at 585 nm when excited at different *** emission behaviors of pristine crystalline powders and single crystals are different,demonstrating emission features that are closely related to the aggregation *** work has developed color-tunable single-component organic emitters with simultaneous multistage stimuli-responsiveness and multimode emissions,which is vital for expanding intelligent optoelectronic applications,including multilevel information encryption,multicolor emissive patterns,and visual monitoring of UV wavelengths.

关键词： donor excitation Smart

Multi-UAV Collaborative Edge Computing Algorithm for Joint Task Offloading and Channel Resource Allocation

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 Communications and Information Networks 2024年第2期9卷 137-150页

作者： Yuting Wei Sheng Wu Zhe Ji Zhigang Yu Chunxiao Jiang Linling Kuang school of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China China Academy of electronics and Information Technology Beijing 100041China Beijing national Research Center for Information Science and Technology Tsinghua Space CenterTsinghua UniversityBeijing 100084China

Unmanned aerial vehicle (UAV)-based edge computing is an emerging technology that provides fast task processing for a wider area. To address the issues of limited computation resource of a single UAV and finite communication resource in multi-UAV networks, this paper joints consideration of task offloading and wireless channel allocation on a collaborative multi-UAV computing network, where a high altitude platform station (HAPS)is adopted as the relay device for communication between UAV clusters consisting of UAV cluster heads (ch-UAVs) and mission UAVs (m-UAVs). We propose an algorithm, jointing task offloading and wireless channel allocation to maximize the average service success rate (ASSR)of a period time. In particular,the simulated annealing(SA)algorithm with random perturbations is used for optimal channel allocation,aiming to reduce interference and minimize transmission delay.A multi-agent deep deterministic policy gradient (MADDPG) is proposed to get the best task offloading strategy. Simulation results demonstrate the effectiveness of the SA algorithm in channel allocation. Meanwhile,when jointly considering computation and channel resources,the proposed scheme effectively enhances the ASSR in comparison to other benchmark algorithms.

关键词： UAV-based edge computing multi-UAV collaboration joint task offloading and wireless channel allocation simulated annealing(SA)algorithm multi-agent deep deterministic policy gradient(MADDPG)

Experimental demonstration of a quantum downstream access network in continuous variable quantum key distribution with a local local oscillator

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Photonics Research 2024年第6期12卷 1262-1273页

作者： DENGKE QI XIANGYU WANG ZHENGHUA LI JIAYU MA ZIYANG CHEN YUEMING LU SONG YU State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service(MoE) Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronicsand Center for Quantum Information TechnologyPeking UniversityBeijing 100871China

Quantum networks provide opportunities and challenges across a range of intellectual and technical frontiers,including quantum computation,communication,and *** traditional communication networks,quantum networks utilize quantum bits rather than classical bits to store and transmit *** key distribution(QKD)relying on the principles of quantum mechanics is a key component in quantum networks and enables two parties to produce a shared random secret key,thereby ensuring the security of data *** this work,we propose a cost-effective quantum downstream access network structure in which each user can get their corresponding key information through terminal *** on this structure,we demonstrate the first four-end-users quantum downstream access network in continuous variable QKD with a local local *** contrast to point-to-point continuous variable QKD,the network architecture reevaluates the security of each user and accounts for it accordingly,and each user has a lower tolerance for excess noise as the overall network expands with more ***,the feasibility of the experiment is based on the analysis of the theoretical model,noise analysis,and multiple techniques such as the particle filter and adaptive equalization algorithm used to suppress excess *** results show that each user can get a low level of excess noise and can achieve secret key rates of 546 kbps,535 kbps,522.5 kbps,and 512.5 kbps under a transmission distance of 10 km,respectively,with the finite-size block of 1×10^(8).This not only verifies the good performance but also provides the foundation for the future multi-user quantum downstream access networks.

关键词： quantum oscillator local