基于模糊逻辑的彩色图像增强

彩色图像的对比度增强具有较强的工程应用价值,提出了一种简单高效的彩色图像增强算法。该算法基于模糊逻辑理论,配合使用RGB和HSI彩色模型,并依据使对比度变换误差最小的原则,调整灰度变换系数。实验结果表明,该方法的增强效果优于传统的直方图均衡,运行效率高,具有实用价值。     

基于模糊逻辑的无人机定位系统设计

针对无人机定位精度问题,硬件设计采用模块化设计思想,以STM32系列的微控制器为核心,以微机械传感器和GPS 模块为基础,组成无人机组合导航系统;软件提出了基于“模糊逻辑”的加速度区间自适应算法,修正惯导定位误差随时间快速积累、GPS发射信号受阻,造成的连续定位能力和精度较差的问题,保证了系统定位精度,为小型自主起降固定翼无人机、多旋翼无人机定位奠定基础。     

可编程光学并行模糊逻辑门

提出了可级联的光学并行模糊逻辑门系统，十六种模糊逻辑运算可通过编程偏振半波片的状态而得到实现，语言中给出了实验结果。     

引人注目的模糊逻辑技术

 在当今科学技术的成果中,模糊逻辑技术宛如科技百花园中一枝争奇斗艳的奇葩,在自动控制、智能信息系统中日益显示出新颖超凡的魅力。     

光学并行实现模糊逻辑图像处理

提出和验证一种基于偏振－空间编码方案和多重成像技术的光学方法来实现模糊逻辑图像处理,系统中,模糊变量和它们的补被编码为空间正交分布的两个偏振状态。通过对透镜阵列状态的编程,可以实现两个模糊图像间的模糊逻辑操作。本系统中,两个输入图像被偏振编码为8个编码图像作为输入图像,系统是空不变系统,不需要取阈装置和解码过程,通过引进取阈装置,可以在一层系统中实现两个图像间更为复杂的模糊逻辑操作,并给出了实验结果。     

基于前馈模糊逻辑的微波功率控制设计与分析

描述和设计了一类生产陶瓷载体的大型微波干燥控制系统;针对微波干燥过程中微波功率控制不准确、产品缺陷率高的问题, 分析了过程变量与控制变量之间的关系特点,并在现有算法基础上,设计了一种基于前馈模糊逻辑的微波功率控制模型;最后对此控制模型设计算法,并应用于实际进行实验分析,得出了很好的效果。     

一种嵌入式软件逻辑覆盖测试方法研究

针对嵌入式软件测试覆盖率低的问题,本文提出了基于软件故障注入的逻辑覆盖测试方法,首先就嵌入式系统常用传感器建立故障模式库,设计了嵌入式软件故障注入系统;其次选取中间层作为故障注入点,研究基于VxWorks653嵌入式操作系统的故障注入实现方式,并通过分析故障信号在软件系统中的传播,提出优化测试用例的方法;最后通过实验验证了该方法可有效提高容错设计功能、冗余设计功能、故障检测功能测试的逻辑覆盖率;有助于提高嵌入式软件的可靠性。     

一种基于模糊成像机理的QR码图像快速盲复原方法

提出了一种基于模糊成像机理的QR码图像快速盲复原方法.在对模糊成像弥散光斑质心不变性研究的基础上,设计圆形寻像图形,在成像模糊时能通过连通域等方法快速检测到图形质心以及QR码符号位置,再结合阶跃边缘特性、梯度强度特性、边缘检测技术以及光学成像机理快速准确估计出模糊QR码图像离焦半径大小,应用维纳滤波算法快速且有效复原Q...     

基于Cisco路由器防火墙的局域网访问控制

许多局域网采用Cisco路由器与因特网连接,如何充分利用Cisco路由器提供的防火墙功能,构筑一个实用的防火墙呢？一般来说,一个完整的防火墙系统不仅要防外侵,而且要防止内部人员对外的非法访问。局域网外面来的访问,网络边界是确定的,内部对外的访问,边界则是动态的,这就需要确定哪个访问是非法的,并且动态、自动地禁止非法对外访问。因此需要采取某种方法,既能保证对内对外的自由访问,又能保证网络上的资源足够安全。这就是本文所要解决的问题。     

基于云存储的电力系统访问控制方案设计

电力系统是一个由多个子系统构成的综合性系统,作为一个能够实现海量数据处理同时具有高实时性、高可靠性的管理控制平台,需要电力系统能够实现对所辖多个子系统进行复杂、细密、大范围的访问控制,这些条件要求能够设计出合理有效的访问控制模型。为了实现安全、可靠、高效的电力系统访问控制提出了将传统电力系统同云存储平台相结合的访问控制方案,通过云存储平台对数据进行存取可以达到大数据量、均衡负载、安全可靠的目的;通过添加可信度因子构建访问控制模型,根据不同用户的可行度计算值分配给以不同的权限,匹配其可操作的资源,实现了对于用户操作对象的细化识别。     

Hyperledger Fabric Access Control System for Internet of Things Layer in Blockchain-Based Applications

Blockchain-based applications are gaining traction in various application fields, including supply chain management, health care, and finance. The Internet of Things (IoT) is a critical component of these applications since it allows for data collection from the environment. In this work, we integrate the Hyperledger Fabric blockchain and IoT devices to demonstrate the access control and establish the root of trust for IoT devices. The Hyperledger Fabric is designed to be secure against unwanted access and use through encryption protocols, access restrictions, and cryptography algorithms. An attribute-based access control (ABAC) mechanism was created using Hyperledger Fabric components only to gain access to the IoT device. Single board computers based on the ARM architecture are becoming increasingly powerful and popular in automation applications. In this study, the Raspberry Pi 4 Model B based on ARM64 architecture is used as the IoT device. Because the ARM64 architecture is not supported by default, we build executable binaries and Docker images for the ARM64 architecture, using the Hyperledger Fabric source code. On an IoT device, we run the fabric node in native mode to evaluate the executable binaries generated for the ARM64 architecture. Through effective chaincode execution and testing, we successfully assess the Hyperledger fabric blockchain implementation and access control mechanism on the ARM64 architecture.     

基于OFDM-PON的媒质接入控制协议设计

在以太网无源光网络帧结构的基础上,针对正交频分复用无源光网络的特点,提出了一种适用于正交频分复用无源光网络的媒质接入控制协议.对多点控制协议、控制消息的结构、业务优先级等进行了设计,提出了一种提供服务质量保障的特殊情况下区别用户服务等级的动态带宽分配算法.该算法引入两级调度的机制,将带宽资源的分配分为不同优先级业务的调度和同类型业务下不同等级的光网络单元调度.文章对提出协议的时延、丢包率、吞吐量等方面的性能进行了仿真,仿真结果显示提出的媒质接入控制协议很好地实现了对各业务的服务质量保障,符合多业务接入对服务质量等的需求.     

Dual adaption based evolutionary algorithm for optimized the smart healthcare communication service of the Internet of Things in smart city

The Internet of Things (IoT) is a revolutionary technique of sharing data for smart devices that generates huge amounts of data from smart healthcare systems. Therefore, healthcare systems utilize the convergence power and traffic analysis of sensors that cannot be satisfactorily handled by the IoT. In this article, a novel mutation operator is devised and incorporated with the differential evolution (DE) algorithm. Two tests have been conducted in the validation process. Firstly, the newly dual adaption-based operators incorporated with the differential evolution algorithm are being proposed. The proposed approach provides sufficient diversity and enhances the search speed of nature’s local and global search environments in the problem. The proposed method incorporates the application of IoT-based smart healthcare. Second, an application-based test has been conducted, in which the proposed approach is applied to the application in the smart healthcare system. Therefore, IoT sensor deployment is an optimization problem to minimize service time, delay, and energy loss by considering the communication constraint between sensors(objects). The proposed algorithm is applied in this article to solve this optimization problem. Further, in the experimentation and comparative study, the proposed method is superior to the standard evolutionary algorithms in IoT applications concerning the minimum number of function evaluations and minimization of traffic services. The proposed approach also achieves efficiency in the minimum loss of energy in each service and reduces load and delay.     

光通信技术在物联网中的应用

介绍了物联网的定义及结构;从感知层和网络层角度,探讨了光通信技术(光纤通信和无线通信)在物联网中的应用现状和前景.光纤通信、近距离无线通信、移动通信是物联网开发的基础,制定物联网各个层面上统一的、标准化协议和技术标准是物联网未来发展必须解决的关键和难点.     

DDKA-QKDN: Dynamic On-Demand Key Allocation Scheme for Quantum Internet of Things Secured by QKD Network

In the era of the interconnection of all things, the security of the Internet of Things (IoT) has become a new challenge. The theoretical basis of unconditional security can be guaranteed by using quantum keys, which can form a QKD network-based security protection system of quantum Internet of Things (Q-IoT). However, due to the low generation rate of the quantum keys, the lack of a reasonable key allocation scheme can reduce the overall service quality. Therefore, this paper proposes a dynamic on-demand key allocation scheme, named DDKA-QKDN, to better meet the requirements of lightweight in the application scenario of Q-IoT and make efficient use of quantum key resources. Taking the two processes of the quantum key pool (QKP) key allocation and the QKP key supplement into account, the scheme dynamically allocates quantum keys and supplements the QKP on demand, which quantitatively weighs the quantum key quantity and security requirements of key requests in proportion. The simulation results show that the system efficiency and the ability of QKP to provide key request services are significantly improved by this scheme.     

Lightweight authentication scheme for massive MIMO on Internet of Things connectivity

Massive MIMO is an essential technology in developing 5G networks and a concept that may be applied to other wireless systems. However, the advantages of adopting massive MIMO for broadband communication are well-established. Recently researcher has been devoted to building communication systems sustaining high communication rates with security. While massive MIMO for Internet-of-Things (IoT) connectivity is still a developing issue, IoT connectivity has requirements and limitations that differ significantly from broadband connections. Although IoT makes people’s lives easier by allowing physical devices to flow through, the interaction of open wireless channels such as Bluetooth, ZigBee, LoRa, Narrowband-Internet of Things (NBIoT), and WiFi, has produced various security and privacy difficulties. Identity authentication is one of the effective solutions for addressing the Internet of Things security and privacy concerns. The typical point-to-point authentication technique ignores the internet of things’ massive number of nodes and limited node resources. Group authentication is an authentication method that simultaneously confirms the identity of a group of members, offering a novel approach to identity identification for the internet of things nodes. However, existing group authentication systems appropriate for the internet of things scenarios pose security issues. They cannot withstand malicious attacks such as forging and replay and cannot prevent group managers from fooling group members. Most existing group authentication schemes are computationally expensive and cannot be applied to resource-constrained IoT scenarios. At the same time, existing systems based on secret-sharing technology cannot resist forgery attacks and replay attacks. The attacker can forge a legal token by modifying the Lagrangian coefficient in the authentication token to pass the group authentication. This work employs verifiable secret sharing technology to create a lightweight verifiable group authentication method (L-IoT-GS) suitable for Internet of Things situations to resist group managers’ deceptive group behavior. Nodes in the Internet of Things scenario can frequently join and leave the network. Because of this, this article proposes a critical update link based on a verified group authentication system for updating group Member rights. According to security analysis, the suggested L-IoT-GS scheme meets accuracy and confidentiality requirements and can withstand malicious attacks such as replay, forgery, and impersonation. Furthermore, performance study and experimental simulation reveal that the L-IoT-GS technique minimizes group members’ computing costs compared to existing standard IoT group authentication schemes.     

Edge Based Priority-Aware Dynamic Resource Allocation for Internet of Things Networks

The exponential growth of the edge-based Internet-of-Things (IoT) services and its ecosystems has recently led to a new type of communication network, the Low Power Wide Area Network (LPWAN). This standard enables low-power, long-range, and low-data-rate communications. Long Range Wide Area Network (LoRaWAN) is a recent standard of LPWAN that incorporates LoRa wireless into a networked infrastructure. Consequently, the consumption of smart End Devices (EDs) is a major challenge due to the highly dense network environment characterised by limited battery life, spectrum coverage, and data collisions. Intelligent and efficient service provisioning is an urgent need of a network to streamline the networks and solve these problems. This paper proposes a Dynamic Reinforcement Learning Resource Allocation (DRLRA) approach to allocate efficient resources such as channel, Spreading Factor (SF), and Transmit Power (Tp) to EDs that ultimately improve the performance in terms of consumption and reliability. The proposed model is extensively simulated and evaluated with the currently implemented algorithms such as Adaptive Data Rate (ADR) and Adaptive Priority-aware Resource Allocation (APRA) using standard and advanced evaluation metrics. The proposed work is properly cross validated to show completely unbiased results.