Large Fabrication Tolerance for VCSELs Using High-Contrast Grating

We report the experimental demonstration of a large fabrication tolerance for a single-layer, highly reflective high-index-contrast subwavelength grating (HCG) mirror. HCG vertical-cavity surface-emitting lasers (VCSELs) are demonstrated with plusmn20% variation in the HCG critical dimension. Emission wavelength of the HCG-VCSEL shifts only 2 nm with 40% change in grating spacing and 8% change in grating period.     

A Method for Detecting Wide-scale Network Traffic Anomalies

Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.     

一种互联网宏观流量异常检测方法

网络流量异常指网络中流量不规则地显著变化。网络短暂拥塞、分布式拒绝服务攻击、大范围扫描等本地事件或者网络路由异常等全局事件都能够引起网络的异常。网络异常的检测和分析对于网络安全应急响应部门非常重要,但是宏观流量异常检测需要从大量高维的富含噪声的数据中提取和解释异常模式,因此变得很困难。文章提出一种分析网络异常的通用方法,该方法运用主成分分析手段将高维空间划分为对应正常和异常网络行为的子空间,并将流量向量影射在正常子空间中,使用基于距离的度量来检测宏观网络流量异常事件。     

Statistical Techniques for Detecting Traffic Anomalies Through Packet Header Data

This paper proposes a traffic anomaly detector, operated in postmortem and in real-time, by passively monitoring packet headers of traffic. The frequent attacks on network infrastructure, using various forms of denial of service attacks, have led to an increased need for developing techniques for analyzing network traffic. If efficient analysis tools were available, it could become possible to detect the attacks, anomalies and to take action to contain the attacks appropriately before they have had time to propagate across the network. In this paper, we suggest a technique for traffic anomaly detection based on analyzing correlation of destination IP addresses in outgoing traffic at an egress router. This address correlation data are transformed using discrete wavelet transform for effective detection of anomalies through statistical analysis. Results from trace-driven evaluation suggest that proposed approach could provide an effective means of detecting anomalies close to the source. We also present a multidimensional indicator using the correlation of port numbers and the number of flows as a means of detecting anomalies.     

A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI

A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.     

基于条件规则库的流量异常检测系统设计

流量异常检测,作为一种网络入侵检测的方法,存在着如何建立正常行为模型的难题。提出了扩大属性检测的范围,采用异常值计算,并由此建立条件规则库作为正常模型的想法,在此基础上用不精确推理方法进行流量异常检测,最后给出了综合系统的设计。     

无线Mesh 网络中基于人工免疫 系统的异常检测

This paper focuses on investigating immunological principles in designing a multi agent security architecture for intrusion detection and response in wireless mesh networks. In this approach, the immunity based agents monitor the situation in the network. These agents can take appropriate actions according to the underlying security policies. Specifically, their activities are coordinated in a hierarchical fashion while sensing, communicating, determining and generating responses. Such an agent can learn about and adapt to its environment dynamically and can detect both known and unknown intrusions. The proposed intrusion detection architecture is designed to be flexible, extendible, and adaptable so that it can perform real time monitoring. This paper provides the conceptual view and a general framework of the proposed system. In the end, the architecture is illustrated by an example and by simulation to show it can prevent attacks efficiently.     

Decision-Theoretic Approach for Classification of Ricker Wavelets and Detection of Seismic Anomalies

Decision-theoretic pattern recognition methods are applied to classifying Ricker wavelets and to detecting waveform anomalies in seismograms. The methods include Bayes decision rule and linear and quadratic classifications. Envelope and instantaneous frequency are extracted as the two features of a seismic trace used as input into the classification schemes. A modified fixed-increment training procedure is employed to solve the decision boundary. The classification schemes successfully distinguish zero-phase Ricker wavelets of different peak frequencies from each other and from random noise.     

双氟二苯乙炔类液晶的高对比度垂面取向

通过在SiO2无机层上蒸镀长链醇的取向方法以及摩擦聚酰亚胺层的取向方法，证明了高双折射率、负介电各向异性双氟二苯乙炔液晶具有优良的垂面取向特性。添加5～10％的异硫氰基二苯乙炔不但改善了对比度，而且提高了质量因数。缺点是使阈值电压升高。     

Detecting Circles Using a Two-Stage Approach

We propose a two-stage method for detecting circular objects in this paper. In the first stage, curves are divided as linear segments or nonlinear segments. A least square estimator is used to find the estimated centers and radii of the nonlinear segments in the second stage. The found centers and radii are then evaluated to see if there exist circles in the nonlinear segments. Both of the broken and occluded circular objects are evaluated for the proposed method. From the experimental results, it is seen that the proposed method is efficient.     

使用时空相关性分析检测加密僵尸网络流量

In this paper, we propose a novel method to detect encrypted botnet traffic. During the traffic preprocessing stage, the proposed payload extraction method can identify a large amount of encrypted applications traffic. It can filter out a large amount of non-malicious traffic, greatly improving the detection efficiency. A Sequential Probability Ratio Test (SPRT)-based method can find spatial-temporal correlations in suspicious botnet traffic and make an accurate judgment. Experimental results show that the false positive and false negative rates can be controlled within a certain range.     

Detecting the Presence of Speech Using ADPCM Coding

When speech is coded using a differential pulse-code modulation system with an adaptive quantizer, the digital code words exhibit considerable variation among all quantization levels during both voiced and unvoiced speech intervals. However, because of limits on the range of step sizes, during silent intervals the code words vary only slightly among the smallest quantization steps. Based on this principle, a simple algorithm for locating the beginning and end of a speech utterance has been developed. This algorithm has been tested in computer simulations and has been constructed with standard integrated circuit technology.     

嵌入式编码在图像检测系统中的应用研究

利用自然图像的低通频谱特性和小波系数整体上随分辨率的减低而增大这一事实,结合图像检测系统中目标识别算法更关注整体信息的特点,将嵌入式编码算法SPIHT应用于红外图像检测系统,通过对系统探测距离和SPIHT编解码参数的匹配,在保证目标正确识别的同时取得了良好的压缩效果.     

Detecting Streaming of Twitter Spam Using Hybrid Method

Twitter, the social network which evolving faster and regular usage by millions of people and who become addicted to it. So spam playing a major role for Twitter users to distract them and grab their attention over them. Spammers actually detailed like who send unwanted and irrelevant messages or websites and promote them to several users. To overcome the problem many researchers proposed some ideas using some machine learning algorithms to detect the spammers. In this research work, a new hybrid approach is proposed to detect the streaming of Twitter spam in a real-time using the combination of a Decision tree, Particle Swarm Optimization and Genetic algorithm. Twitter has given access to the researchers to get tweets from its Twitter-API for real-time streaming of tweet data which they can get direct access to public tweets. Here 600 million tweets are created by using URL based security tool and further some features are extracted for representation of tweets in real-time detection of spam. In addition, our research results are compared with other hybrid algorithms which a better detection rate is given by our proposed work.     

利用激光探测水下声信号的研究

对激光探测水下声信号可行性进行了研究.水下声信号造成的水表面微扰导致了反射的激光光通量的变化,探测器接收到的光通量的变化频率与水下声信号的频率相同,并给出了探测器位置与接收光通量的关系.     

用液晶检测绝缘薄膜的缺陷

本文介绍一种检测绝缘薄膜缺陷的简易而有效的方法——液晶测量法,并针对交流薄膜电致发光(ACTFEL)器件中常用的几种绝缘薄膜作检测与分析。     

无保温层屋面渗漏的红外热像检测方法

模拟了无保温层的单层屋面渗漏情况,探索了其红外热像检测方法.结果表明能准确测定渗漏的位置,同时对影响屋面温差变化的材料热容、导热系数和屋面太阳照射吸收率进行了分析,并通过对实际工程的检测,进一步证明了红外热像技术在建筑物屋面渗漏中应用的可行性.     

使用数字万用表巡检功能对基站电信号进行监测

引言在当今的电子产品中,随着器件的精密度和准确性提升,其电气特性的要求也更加严格,电信号值的一点偏差都会导致很严重的问题。所以不管是设计过程还是使用过程,电信号值都应该处于监测状态,这样我们就能够预防很多相关问题的发生,即使在发生问题后也有更多的参考信息。在万用表中实施巡检功能正是基于减少设备成本,只     

基于贝叶斯模型的高效主动探测算法(英文)

Fault diagnosis on large-scale and complex networks is a challenging task, as it requires efficient and accurate inference from huge data volumes. Active probing is a cost-efficient tool for fault diagnosis. However almost all existing probing-based techniques face the following problems: 1) performing inaccurately in noisy networks; 2) generating additional traffic to the network; 3) high cost computation. To address these problems, we propose an efficient probe selection algorithm for fault diagnosis base...