Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive information.The main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement techniques.The QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding phase.This innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely implemented.Unlike existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation process.To assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud platform.The results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind signatures.Furthermore,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.

A Blockchain-Based Proxy Re-Encryption Scheme with Conditional Privacy Protection and Auditability

With the development of Internet of Things technology,intelligent door lock devices are widely used in the field of house leasing.In the traditional housing leasing scenario,problems of door lock information disclosure,tenant privacy disclosure and rental contract disputes frequently occur,and the security,fairness and auditability of the housing leasing transaction cannot be guaranteed.To solve the above problems,a blockchain-based proxy re-encryption scheme with conditional privacy protection and auditability is proposed.The scheme implements fine-grained access control of door lock data based on attribute encryption technology with policy hiding,and uses proxy re-encryption technology to achieve auditable supervision of door lock information transactions.Homomorphic encryption technology and zero-knowledge proof technology are introduced to ensure the confidentiality of housing rent information and the fairness of rent payment.To construct a decentralized housing lease transaction architecture,the scheme realizes the efficient collaboration between the door lock data ciphertext stored under the chain and the key information ciphertext on the chain based on the blockchain and InterPlanetary File System.Finally,the security proof and computing performance analysis of the proposed scheme are carried out.The results show that the scheme can resist the chosen plaintext attack and has low computational cost.

Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

Quantum-Resistant Multi-Feature Attribute-Based Proxy Re-Encryption Scheme for Cloud Services

Cloud-based services have powerful storage functions and can provide accurate computation.However,the question of how to guarantee cloud-based services access control and achieve data sharing security has always been a research highlight.Although the attribute-based proxy re-encryption(ABPRE)schemes based on number theory can solve this problem,it is still difficult to resist quantum attacks and have limited expression capabilities.To address these issues,we present a novel linear secret sharing schemes(LSSS)matrix-based ABPRE scheme with the fine-grained policy on the lattice in the research.Additionally,to detect the activities of illegal proxies,homomorphic signature(HS)technology is introduced to realize the verifiability of re-encryption.Moreover,the non-interactivity,unidirectionality,proxy transparency,multi-use,and anti-quantum attack characteristics of our system are all advantageous.Besides,it can efficiently prevent the loss of processing power brought on by repetitive authorisation and can enable precise and safe data sharing in the cloud.Furthermore,under the standard model,the proposed learning with errors(LWE)-based scheme was proven to be IND-sCPA secure.

An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.

Construction of a Multi-Level Strategic System for Cultivating Cultural Industry Management Talents in Colleges and Universities

Through SWOT(strengths,weaknesses,opportunities,and threats)and PEST(political,economic,social,and technological)analysis,this study discusses the construction of a multi-level strategic system for the cultivation of cultural industry management talents in colleges and universities.First of all,based on SWOT analysis,it is found that colleges and universities have rich educational resources and policy support,but they face challenges such as insufficient practical teaching and intensified international competition.External opportunities come from the rapid development of the cultivation of cultural industry management talents and policy promotion,while threats come from global market competition and talent flow.Secondly,PEST analysis reveals the key factors in the macro-environment:at the political level,the state vigorously supports the cultivation of cultural industry management talents;at the economic level,the market demand for cultural industries is strong;at the social level,the public cultural consumption is upgraded;at the technological level,digital transformation promotes industry innovation.On this basis,this paper puts forward a multi-level strategic system covering theoretical education,practical skill improvement,interdisciplinary integration,and international vision training.The system aims to solve the problems existing in talent training in colleges and universities and cultivate high-quality cultural industry management talents with theoretical knowledge,practical skills,and global vision,so as to adapt to the increasingly complex and diversified cultural industry management talents market demand and promote the long-term development of the industry.

基于Proxy的网络计费系统的设计与实现

讨论在校园网环境下的网络计费，对基于Proxy的网络计费与管理进行了详细设计，给出了巨量数据的处理方法。

一种基于Proxy的Web应用安全漏洞检测方法及实现

指出了Web应用中存在的各种安全漏洞,在分析并总结Web应用安全漏洞特点的基础上,设计了一种基于Proxy的Web应用安全漏洞检测方法,该方法可以用来检测一些常见的Web应用安全漏洞,如参数篡改、跨站点脚本漏洞等.给出了利用该方法检测SQL代码插入、跨站点脚本算法的JAVA语言实现.

基于MS Proxy Server的网络计费系统的实现

文中介绍了代理服务器的计费方式,阐述了基于MSProxyServer的网络计费系统的设计与实现。

基于策略DNS和HTTP Proxy的多宿主网络服务部署的研究

针对目前常用的多宿主网络服务部署方法中存在的由于ISP网络地址集的变化或DNS配置等因素会造成服务访问路由不可达的不足,提出了一种基于策略DNS与HTTP Proxy在多宿主网络中服务的部署策略,在各ISP出口安装HTTP Proxy服务器,配合策略DNS服务进行联合部署。从理论上对该策略进行了分析,并对部署方法进行了详细阐述。通过实例分析及效果测量,证实了在不改变网络拓扑、基本不增加投入的情况下,通过该策略可大幅度提高校园网或企业网信息资源服务的互联网用户访问速度和访问质量,并解决了传统方式中路由不可达的问题。

基于PROXY服务器的网络计费系统原理与实现

网络计费是网络管理中重要的一部分 ,一个有效而合理的计费系统是校园网络正常运行的保证 .文章研究了代理机制 ,分析了基于 PROXY服务器的网络计费系统原理 ,提出了网络计费系统的一个开发模型 ,并对模型中的数据采集、计费信息处理、数据查询等主要模块的设计作了较详细的阐述 .

基于NAT-PT和PROXY的HTTP过渡方案的研究与改进

NAT-PT技术和PROXY技术是HTTP服务从IPv4向IPv6过渡的两种主要技术,文章讨论了基于这两种技术的过渡方案的实现与改进。论文从原理上分析现有方案,提出现有实现方案存在的问题,如NAT-PT中的动态映射地址对过期而导致的访问出错的问题,以及PROXY方案中IPv4端不能通过IPv6地址直接访问的问题。针对上述问题提出了改进方案,并通过实验证明了改进方案的可行性和有效性。

基于Proxy服务器的计费系统

本文主要论述网络管理中计费系统的开发方法，探讨代理服务器的主要功能和工作流程，提出了基于Ｐｒｏｘｙ服务器计费系统的系统结构和流程，最后给出了基于Ｐｒｏｘｙ服务器计费系统的逻辑结构和系统功能。

采用SNMP Proxy技术的集群系统的单IP管理

在互联网IP地址日益紧张的情况下,尽可能占用最少的IP地址对集群系统进行管理,将大大节约互联网IP地址资源。该文通过对比RFC1631和RFC2663中提出的NAT、NAPT技术实现原理,提出了SNMPPROXY技术,可以在不改造路由器的情况下,实现集群系统的单IP地址SNMP管理。

基于HTTP和Proxy防毒过滤网关的研究

随着Internet的飞速发展和广泛应用,大量的网络病毒已将Internet作为其一种主要的传播途径。网络病毒传播的方式很多,如通过访问网页、电子邮件以及FTP文件传输等等。为了使Web病毒(通过Web传播的网络病毒)的查杀工作对用户及Web服务器透明化,同时降低Web服务器的风险,提高病毒查杀效率。我们采用了KPSG(KILLProxy Shield Gateway,代理过滤网关)的方式提供对Web病毒(如NIMDA)和蠕虫的查杀。

基于Full Proxy的NAT/Firewall的穿越

VoIP语音视频流对NAT/F irewall的穿越已经成为语音数据业务开展过程中最大的障碍。Fu ll Proxy提供了一种NAT/F irewall穿越的有效途径,具有很强的适应性和透明性。深入讨论了Fu ll Proxy的实现原理和基于Fu ll Proxy的整个呼叫流程,最后在一个嵌入式双CPU系统的基础上实现了一个Fu ll Proxy。

网格门户下基于GSI的MyProxy Login实现

Globus项目通过网格安全基础设施GSI(GridSecurityInfrastructure)来提供网格计算环境中的安全认证和安全通信能力,该文通过基于GSI的安全技术分析和对Gridport下MyProxylogin实现原理的研究,并与普通登录方式进行比较,说明Gridportlogin利用MyProxy解决用户代理问题将更安全、高效。

分布网络管理体系结构中若干术语的辨析——Agent、Delegator、Broker和Proxy

Internet的普及,使网络管理已经成为计算机网络不可缺少的个重要部分.网络管理作为一种特殊的应用领域,研究其体系结构可以使设计人员在较高的抽象层次分析管理功能,有着重要的理论和实践意义,而且对于管理协议和服务的设计有一定的指导意义.

EPON系统中IGMP Proxy技术实现方案

提出了一种基于VLAN的EPON系统组播实现方案,满足当前宽带接入网中有效传输组播业务的需求。该方案充分利用ONU端的IGMPProxy技术,大大降低了IGMP控制报文在EPON系统、上端核心网中的流量。仿真显示了该方案在IGMP控制报文网络流量上的性能大幅提高和优越性。