一种高效无线传感器网络认证及密钥协商方案

随着无线传感器网络在社会各个领域的渗透,其安全机制的研究一直是无线传感器网络的研究热点。在分析了无线传感器网络中认证及密钥协商方案设计时应满足条件的基础上,基于单向HASH函数和对称密码算法,设计了无线传感器网络中传感器节点间一种高效的认证及密钥协商方案。并从互认证、会话密钥、可抵御攻击等方面对该方案的安全性进行了分析,说明了该方案的安全性能较好,可有效抵御典型攻击行为;详细比较该方案和现有类似方案的运行性能,结果表明,该方案在存储容量需求、计算复杂性和通信带宽需求方面均优于现有方案。     

One-Component Artificial Gustatory System Based on Hydrogen-Bond Organic Framework for Discrimination of Versatile Analytes

Hydrogen-bond organic frameworks (HOFs) with excellent structural and luminescent properties have emerged as a promising material for the construction of fluorescence sensors. However, designing a facile, universal and high throughput sensor with multiplex detection capacity still remains challenging. Herein, a one-component sensor array is constructed that mimics natural gustatory system for accurate and high-throughput discrimination and identification of versatile analytes. HOF as a single sensing element greatly simplifies the probe preparation in sensor array and detection procedure. Metal ions, proteins and bacteria as the model targets are rapid and accurately discriminated, presenting the universality of the system. Particularly, the system is successfully used for the classification of antibiotic mechanisms. The study expands the application scope of HOFs and provides a facile and universal system for sensing applications.     

Recent Development of Jumping Motions Based on Soft Actuators

Drawing inspiration from the jumping motions of living creatures in nature, jumping robots have emerged as a promising research field over the past few decades due to great application potential in interstellar exploration, military reconnaissance, and life rescue missions. Early reviews mainly focused on jumping robots made of lightweight and rigid materials with mechanical components, concentrating on jumping control and stability. Herein, attention is paid to the jumping mechanisms of soft actuators assembled from various soft smarting materials and powered by different stimulus sources. The challenges and prospects of soft jumping actuators are also discussed. It is hoped that this review will contribute to the further development of soft jumping actuators and broaden their practical applications.     

Relaxation-Induced Significant Room-Temperature Dielectric Pulsing Effects

Thermo-responsive dielectric materials are in urgent demand owing to the rapid development of smart electronic/electrical systems. Although different types and structures of thermally responsive dielectric materials have been continuously reported, their dielectric response behaviors all originate from thermodynamic phase transitions. Herein, it is demonstrated that structural relaxation in poly(vinylidene fluoride) (PVDF), a non-thermodynamic phase transition, can induce a significant thermal dielectric pulse at room temperature. The dielectric pulse strength of up to 6.3 × 10⁵ at 20 Hz, with a dielectric pulsing temperature of 24 °C, is achieved from polyethylene glycol (PEG)-PVDF coaxial nanofibrous films (PVDF@PEG), fabricated via a continuous blow spinning method. Moreover, the films exhibit excellent flexibility, adjustable strength and toughness, switchable hydrophilicity/hydrophobicity, and effective thermal management capability. The relaxation-induced dielectric pulsing effect, outstanding multifunctionality, and simple preparation combine to promote further scalability and prospects of PVDF@PEG. In particular, the work contributes to the discovery of the relaxation-induced dielectric response mechanism, which provides a new strategy for the generation of thermo-responsive dielectric materials.     

Ultra-Damping Composites Enhanced by Yolk–Shell Piezoelectric Damping Mechanism

High-performance damping materials are significant toward reducing vibration and maintaining stability for industrial applications. Herein, a yolk–shell piezoelectric damping mechanism is reported, which can enhance mechanical energy dissipation and improve damping capability. With the addition of yolk–shell particles and carbon nanotube (CNT) conductive network, damping properties of various resin matrices are enhanced with the energy dissipation path of mechanical to electrical to heat energy. Particularly, the peak loss factor of epoxy composites reaches 1.91 and tan δ area increases by 25.72% at 20 °C. The results prove the general applicability of yolk–shell piezoelectric damping mechanism. Besides, the novel damping materials also exhibit excellent flexibility, stretchability, and resilience, offering a promising application toward damping coating, indicating broad scope of application in transportation and sophisticated electronics, etc.     

Electrocapacitive Deionization: Mechanisms,Electrodes, and Cell Designs

Capacitive deionization (CDI) is an emerging water desalination technology for removing different ionic species from water, which is based on electric charge compensation by these charged species. CDI is becoming popular because it is more energy-efficient and cost-effective than other technologies, such as reverse osmosis and distillation, specifically in dealing with brackish water having low or moderate salt concentrations. Over the past decade, the CDI research field has witnessed significant advances in the used electrode materials, cell architectures, and associated mechanisms for desalination applications. This review article first discusses ion storage/removal mechanisms in carbon and Faradaic materials aided by advanced in situ analysis techniques and computations. It then summarizes research progress toward electrode materials in terms of structure, surface chemistry, and composition. More still, it discusses CDI cell architectures by highlighting their different cell design concepts. Finally, current challenges and future research directions are summarized to provide guidelines for future CDI research.     

RTDNet：面向高分辨率卫星影像的赤潮探测网络

目的 赤潮是一种常见的海洋生态灾害,严重威胁海洋生态系统安全。及时准确获取赤潮的发生和分布信息可以为赤潮的预警和防治提供有力支撑。然而,受混合像元和水环境要素影响,赤潮分布精细探测仍是挑战。针对赤潮边缘探测的难点,结合赤潮边缘高频特征学习与位置语义,提出了一种计算量小、精度高的网络模型RTD-Net （red tide detection network）。方法 针对赤潮边缘探测不准确的问题,设计了基于RIR （residual-in-residual）结构的网络,以提取赤潮边缘水体的高频特征;利用多感受野结构和坐标注意力机制捕获赤潮水体的位置语义信息,增强赤潮边缘水体的细节信息并抑制无用的特征。结果 在GF1-WFV （Gaofen1 wide field of view）赤潮数据集上的实验结果表明,所提出的RTDNet模型赤潮探测效果不仅优于支持向量机（support vector machine,SVM）、U-Net、Deep-Labv3+及HRNet （high-resolution network）等通用机器学习和深度学习模型,而且也优于赤潮指数法GF1_RI （Gaofen1 red tide index ）以及赤潮探测专用深度学习模型RDU-Net （red tide detection U-Net）,赤潮误提取、漏提取现象明显减少,F1分数在两幅测试图像上分别达到了0.905和0.898,相较于性能第2的模型DeepLabv3+提升了2%以上。而且,所提出的模型参数量小,仅有2.65 MB,约为DeepLabv3+的13%。结论 面向赤潮探测提出一种基于RIR结构的赤潮深度学习探测模型,通过融合多感受野结构和注意力机制提升了赤潮边缘探测的精度和稳定性,同时有效降低了计算量。本文方法展现了较好的应用效果,可适用于不同高分辨率卫星影像的赤潮探测。     

基于改进深度学习的风机油污识别

针对风机设备油液渗漏影响风机正常运行亟需解决的对风机设备油污的识别问题,提出了一种基于改进深度学习的风机油污检测方法。基于深度学习在目标检测中的应用特点,对目标检测网络YOLOv5n（You Only Look Once v5n）进行改进,将原网络中的非极大抑制（Non Maximum Suppression,NMS）替换为Soft-NMS,降低了网络的误检率,添加CA (Coordinate Attention)注意力机制,增强了模型对目标的定位能力,改进原网络损失函数为α-IoU（Alpha- Intersection over Union）损失函数,提高了边界框检测的准确度。实验结果表明:模型平均精度提升了8.1%,查全率提高了19.1%,网络推理速度提高了28.6%。改进后的模型能准确检测风机油污,有效解决了风机实际运行中油液渗漏所带来的问题。     

Advanced Authentication Mechanisms for Identity and Access Management in Cloud Computing

Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security strategies and models to overcome these issues. Another major concern in IAM services is the excessive or the lack of access level to different users with previously granted authorizations. This paper proposes a comprehensive review of security services and threats. Based on the presented services and threats, advanced frameworks for IAM that provide authentication mechanisms in public and private cloud platforms. A threat model has been applied to validate the proposed authentication frameworks with different security threats. The proposed models proved high efficiency in protecting cloud platforms from insider attacks, single sign-on failure, brute force attacks, denial of service, user privacy threats, and data privacy threats.