MALDI-TOF MS: an upcoming tool for rapid detection of antibiotic resistance in microorganisms

MALDI-TOF MS profiling for microorganism detection has already been demonstrated in the 1990s, but has evolved to the first-line identification method in many laboratories just during the past five years. While this application of MALDI-TOF MS has proven its broad applicability, accuracy, robustness, and cost-effectiveness it is of particular interest to expand the capabilities of the mass spectrometric platform. Resistance detection is the most desirable further application of MALDI-TOF MS in microbiology, but maybe also the most challenging. Different approaches have been published regarding diverse antibiotic drugs and distinct microorganism classes. The current review shall give an overview about the developments of the recent years and their potential to get transformed in clinical useful assays in the future.     

无线传感器网络技术在海洋平台结构安全检测领域的应用研究

无线传感器网络能够很好地解决海洋平台结构检测中遇到的很多问题。对无线传感器网络这一无线通信中的热点领域在无线传感器网络体系构架、大规模组网技术及网络管理、环境感知技术、数据采集技术以及信息处理技术等方面进行了应用研究,以期能将该项技术应用于我国海洋平台结构的安全检测中。     

Variance sensitive adaptive threshold-based PCA method for fault detection with experimental application

Principal Component Analysis (PCA) is a statistical process monitoring technique that has been widely used in industrial applications. PCA methods for Fault Detection (FD) use data collected from a steady-state process to monitor T² and Q statistics with a fixed threshold. For the systems where transient values of the processes must be taken into account, the usage of a fixed threshold in PCA method causes false alarms and missing data that significantly compromise the reliability of the monitoring systems. In the present article, a new PCA method based on variance sensitive adaptive threshold (T_vsa) is proposed to overcome false alarms which occur in the transient states according to changing process conditions and the missing data problem. The proposed method is implemented and validated experimentally on an electromechanical system. The method is compared with the conventional monitoring methods. Experimental tests and tabulated results confirm the fact that the proposed method is applicable and effective for both the steady-state and transient operations and gives early warning to operators.     

基于主成分迭代支集检测的多对比度 磁共振快速成像

很多磁共振成像应用(如 T1、T2 参数成像)需要连续采集一系列不同对比度的图像。丰富的对比度机制反映了 人体组织的内在特性,为临床提供了有效的定量诊断手段。然而,由于扫描时间过长,这种方法在临床上的应用受到一 定的限制。近几年兴起的压缩感知理论在磁共振快速成像方面显示了巨大的潜能。其中,学者们提出一种基于主成分分 析的快速磁共振成像方法。该方法从已知的解析物理模型和参数范围中训练主成分,并通过截断的方式利用图像序列的 时域稀疏性。但是,当这种截断先验信息不准确时,上述方法可能会产生模型误差。 本文通过采用迭代支集检测的方法 实现主成分系数支集的适应性估计。文章最后通过两组人体膝盖数据的重建实验,验证了该方法的有效性。     

Coherent microscopy by laser optical feedback imaging (LOFI) technique

The application of the non-conventional imaging technique LOFI (laser optical feedback imaging) to coherent microscopy is presented. This simple and efficient technique using frequency-shifted optical feedback needs the sample to be scanned in order to obtain an image. The effects on magnitude and phase signals such as vignetting and field curvature occasioned by the scanning with galvanometric mirrors are discussed. A simple monitoring method based on phase images is proposed to find the optimal position of the scanner. Finally, some experimental results illustrating this technique are presented.     

浅析网络异常流量分析检测研究与实现

伴随着互联网技术与网络业务的快速发展,网络规模逐渐扩大,网络运用开始逐步朝多元化、多样化以及复杂化的方向发展.现今,网络流量监测已经逐渐发展为计算机网络运用当中一个必不可少的内容与环节.文章将对网络异常流量加以说明,并对网络异常流量检测技术研究与实现进行分析与研究.     

网络蠕虫的检测和防治

随着网络系统应用及其复杂性的增加,网络蠕虫已成为网络安全的主要威胁之一。目前的蠕虫传播速度如此之快使得单纯依靠人工手段已无法抑制蠕虫的爆发。本文首先介绍了蠕虫的相关概念,然后详细介绍了当前蠕虫检测的关键技术,最后给出了蠕虫检测技术的总结和展望。     

基于相似性的僵尸网络检测研究

本文根据同一个僵尸网络中的成员在行为上呈现一定相似性的原理,提出了一个僵尸网络检测模型,该模型能满足对IRC、HTTP、P2P三种僵尸网络的检测要求.     

试析入侵检测技术在计算机网络安全维护中的应用

计算机网络技术在给人们带来方便快捷服务的同时,也面临着一些问题.比如如今网络安全成了人们诟病的话题,也成了我国计算机发展路程上的主要研究对象.本文主要介绍入侵检测技术在计算机网络安全维护中的应用,从入侵检测技术的重要性,以及如何有效的对其利用.     

Key-dependent 3D model hashing for authentication using heat kernel signature

Multimedia-based hashing is considered an important technique for achieving authentication and copy detection in digital contents. However, 3D model hashing has not been as widely used as image or video hashing. In this study, we develop a robust 3D mesh-model hashing scheme based on a heat kernel signature (HKS) that can describe a multi-scale shape curve and is robust against isometric modifications. We further discuss the robustness, uniqueness, security, and spaciousness of the method for 3D model hashing. In the proposed hashing scheme, we calculate the local and global HKS coefficients of vertices through time scales and 2D cell coefficients by clustering HKS coefficients with variable bin sizes based on an estimated L² risk function, and generate the binary hash through binarization of the intermediate hash values by combining the cell values and the random values. In addition, we use two parameters, bin center points and cell amplitudes, which are obtained through an iterative refinement process, to improve the robustness, uniqueness, security, and spaciousness further, and combine them in a hash with a key. By evaluating the robustness, uniqueness, and spaciousness experimentally, and through a security analysis based on the differential entropy, we verify that our hashing scheme outperforms conventional hashing schemes.