密罐技术研究及应用概述

随着网络技术的飞速发展,网络安全问题日益突出。对于网络安全的防护,传统的被动防御已经无法满足人们的需要,蜜罐技术作为一种主动技术弥补了传统防护系统的不足。本文从定义、分类以及原理等方面对蜜罐技术给出一个比较系统的解释,并从四个方面研究了蜜罐技术在网络安全实践中的应用。     

活动轮廓模型在医学图像分割中的应用及发展

图像分割是医学三维重建、医学可视化等的基础,对疾病的诊断和治疗有着重要的临床意义,目前,用于医学图像分割的算法很多,而活动轮廓模型(Active Contour Model)的提出则是这个领域的一个重大突破。介绍活动轮廓模型从参数活动轮廓模型到几何活动轮廓模型的发展过程及发展现状,提出活动轮廓模型的研究和发展方向。     

An Active Disturbance Rejection Based Approach to Vibration Suppression in Two‐Inertia Systems

This study concerns the resonance problems found in motion control, typically described in a two‐inertia system model as compliance between the motor and the load. We reformulate the problem in the framework of active disturbance rejection control (ADRC), where the resonance is assumed to be unknown and treated as disturbance, estimated and mitigated. This allows the closed‐loop bandwidth to go well beyond the resonant frequency, which is quite difficult using existing methods. In addition, such level of performance is achieved with minimum complexity in the controller design and tuning: no parameter estimation or adaptive algorithm is needed, and the controller is tuned by adjusting one parameter, namely, the bandwidth of the control loop. It is also shown that the proposed solution applies to both the velocity and position control problems, and the fact that ADRC offers an effective and practical motion control solution, in the presence of unknown resonant frequency within the bandwidth of the control system. Finally, frequency response analysis is performed where stability margin is obtained before the simulation results are verified in the hardware experiments.     

Using active learning to adapt remote sensing image classifiers

The validity of training samples collected in field campaigns is crucial for the success of land use classification models. However, such samples often suffer from a sample selection bias and do not represent the variability of spectra that can be encountered in the entire image. Therefore, to maximize classification performance, one must perform adaptation of the first model to the new data distribution. In this paper, we propose to perform adaptation by sampling new training examples in unknown areas of the image. Our goal is to select these pixels in an intelligent fashion that minimizes their number and maximizes their information content. Two strategies based on uncertainty and clustering of the data space are considered to perform active selection. Experiments on urban and agricultural images show the great potential of the proposed strategy to perform model adaptation.     

Real-time particle swarm optimization based current harmonic cancellation

As a powerful optimization algorithm, particle swarm optimization (PSO) has been widely applied to power system researches. However, most existing applications of PSO can only be implemented offline. The difficulties of online implementation mainly come from the unavoidable lengthy simulation time to evaluate a candidate solution. Recently, PSO was implemented online that can identify parameters in a motor control systems. In this paper, the real-time PSO (RT-PSO) based identification technique is applied to cancel current harmonics in power systems. By transforming the identification problem to optimization problem, RT-PSO can simultaneously identify four parameters associated with fundamental current from measurement. In this way, there is no need to identify the fundamental frequency separately or construct fundamental signal from identified harmonic information. The identification algorithm can be applied to three-phases independently, even for unbalanced system or single-phase system. The identified fundamental signal is then used as the reference for current harmonics cancellation. The RT-PSO based harmonic cancellation is realized with an active filter and used to compensate harmonic current created by a nonlinear load. Simulation results demonstrate that the RT-PSO algorithm can provide accurate identification of the fundamental current which in turn will result in good harmonic cancellation performance. As a capable online optimization technique, RT-PSO can be extensively applied to many optimization and control problems.     

VisionGo: Towards video retrieval with joint exploration of human and computer

This paper introduces an effective interactive video retrieval system named VisionGo. It jointly explores human and computer to accomplish video retrieval with high effectiveness and efficiency. It assists the interactive video retrieval process in different aspects: (1) it maximizes the interaction efficiency between human and computer by providing a user interface that supports highly effective user annotation and an intuitive visualization of retrieval results; (2) it employs a multiple feedback technique that assists users in choosing proper method to enhance relevance feedback performance; and (3) it facilitates users to assess the retrieval results of motion-related queries by using motion-icons instead of static keyframes. Experimental results based on over 160 h of news video shows demonstrate the effectiveness of the VisionGo system.     

Front detection on satellite images based on wavelet and evidence theory: Application to the sea breeze fronts

This paper is concerned with the detection of fronts in satellite images. We focus on some specific textured patterns of clouds that are visible on Meteosat Second Generation (MSG) images and generated at the so-called “sea breeze front”. This is the limit of the penetration of the sea breeze inland. The sea breeze circulation is a phenomenon that arises when land and sea surface temperatures reveal strong variations. This generates a landward wind that creates a cloud-free area starting from the coast line and ending at the sea breeze front. With the new geostationary meteorological sensors like MSG, this band of cloud-free area can clearly be seen. The automatic analysis of the sea breeze front with such image sensors (instead of using local measurements) is then of great importance. It has the precious advantage to extract huge amount of data and to get rid of the use of local sensors. Unfortunately, from an image processing point of view, this front appears as the limit of a very textured area. It is sometimes disturbed by clouds located in higher layers of the atmosphere. Due to this complexity, conventional detection methods issued from computer vision are not adapted. In this paper we propose an approach that automatically detects fronts in images and we apply this framework to the sea breeze fronts. The methodology is based on the well-known active contour method (or “snake”) issued from the computer vision community. The specific textures involved as well as the transparency phenomena are dealt with some properties of the wavelet decomposition of the images. This decomposition enables to compute several criteria related to the presence or not of a front that are combined using the Dempster-Shafer theory. The validation of our approach is done on synthetic and real data. It is important to outline that the presented theoretical framework is not only devoted to the detection of the sea breeze front but can also be used to detect any others textured patterns.     

基于启发式失效率函数的主动队列管理

研究主动队列管理技术的REI)和REM的丢包率和队长稳定性关系;基于启发式丢包处理方法,提出一种 采用启发式失效率函数计算丢弃概率函数以减小丢包率的拥塞控制算法(HFA)。在轻量级负载情况下,该算法性能 和自适应随机早期检测与随机指数标记相当;而在重量级负载情况下,不仅丢包率的均值和方差小,而且瞬时队长在 设定的目标范围,可以明显地减小队列长度的波动性。在N}2上进行的大量实验结果表明,所提算法具有瞬时队长 控制在预期范围、抖动性小、丢包率及丢包率方差小等优点。     

星载差分吸收气压雷达的系统仿真与性能分析

提出一种工作在65~70 GHz强氧气吸收波段的星载差分吸收气压雷达,用以连续获取全球高时空分辨率的海面气压数据。通过对星载差分吸收气压雷达系统设计需求的分析,利用大气廓线数据和大气吸收系数模型,对海面气压差分吸收的性能进行了仿真及性能分析。仿真结果表明：通过强氧气吸收波段下的海面气压和差分吸收指数之间存在线性关系,星载差分吸收气压雷达在66 GHz与69 GHz的工作频率下晴空时得到的海面气压估计的均方根误差在2.6 mbar,不同云况下得到的海面气压估计的均方根误差在3~4 mbar,为后续雷达系统的设计与工程实现提供了参考与依据。