构建网络安全防护体系

随着计算机技术和通信技术的发展,计算机网络将日益成为工业、农业和国防等方面的重要信息交换手段,渗透到社会生活的各个领域.网络安全问题日益突出,为了提高网络的整体安全水平必须全方位的构建网络安全防护体系,本文介绍网络安全防护体系的构建过程,并描述网络安全防护体系结构.     

A color image segmentation method as used in the study of ancient monument decay

In the cultural heritage area, it is of fundamental importance to characterize and classify the conservation state of the materials constituting ancient monuments, in order to study and monitor their decay. Generally, the decay diagnosis is provided by “naked eye” analysis done by expert scientists “walking around” the artifact and recording the conservation state of each individual element they observe. In this paper, a color image segmentation approach, based on histogram threshold and edge detection techniques is presented, to extract degradation regions, characterized by holes or cavities, from color images of stone-materials. The goal is to provide an aid to the decay diagnosis by segmenting degraded regions from color images, computing quantitative data, such as the area and perimeter of the extracted zones, and processing qualitative information, such as various levels of depth detected into the same zones. Since color is a powerful tool in the distinction between objects, a segmentation technique based on color, instead of intensity only, has been used to provide a clearer discrimination between regions. The study case concerns the impressive remains of the Roman Theatre in the city of Aosta (Italy). In particular, we have processed and analyzed some color images of the theatre puddingstones, acquired by a camera.     

金属焊接质量的红外成像检测

介绍一种基于红外成像技术的金属焊接质量的无损检测方法.首先介绍了检测的基本原理和检测装置,然后详细给出了以边缘检测为基础的缺陷检测方法及检测结果.最后通过比较说明,利用红外成像技术对金属焊接质量进行无损检测是一种很有效的方法.     

基于双目点云的三维物体检测准确性分析

双目相机虽然能通过算法生成密集的深度数据,但其在精度上与激光雷达生成的深度数据有着较大的差距,特别是在纹理不明显的区域。针对这种现象,尝试使用激光雷达的精确点云来排除由双目相机产生的pseudo-LiDAR数据中与之差别较大的部分点,然后将优化后的pseudo-LiDAR用以进行三维物体检测。实验结果显示,将pseudo-LiDAR数据中的不准确点（坏点）排除,有助于提高检测准确率,最多可提高21.02%。因此,如何不依赖激光雷达数据来排除pseudo-LiDAR点云中的坏点是进一步提高双目相机系统检测准确率的关键。     

A Framework for Policies and Practices to Improve Test Security Programs: Prevention,Detection, Investigation,and Resolution (PDIR)

Test security is not an end in itself; it is important because we want to be able to make valid interpretations from test scores. In this article, I propose a framework for comprehensive test security systems: prevention, detection, investigation, and resolution. The article discusses threats to test security, roles and responsibilities, rigorous training for everyone involved in testing, and an evaluation of current practices in test security. I call on everyone responsible for testing programs—the Association of Test Publishers, Council of Chief State School Officers, National Council on Measurement in Education, U.S. Department of Education, and state assessment program managers, their vendors, and the research community—to collaborate on guidelines and practices for security violation prevention, detection, investigation, and resolution.     

长江口深水航道船舶超宽交会通航效率分析

为提高长江口深水航道通过能力,减少由船舶交会宽度限制产生的延误,通过分析船舶超宽交会现状,建立仿真逻辑模型,运用Arena进行离散仿真试验。采集长江口深水航道交通流数据,设置不同的船舶交会宽度限制,对大型船舶进出港过程进行仿真,分析不同交会宽度限制对船舶通航的影响,获得被延误船舶比例、被延误船舶数量和延误时间,进而提出提升通过能力的建议。试验表明,采用Arena进行离散仿真能够量化分析超宽交会对通航效率的影响,可为航道拓宽和交通管理提供科学依据。     

低重复率稿件中的学术不端行为检测与防范

重复率低却存在抄袭的稿件,其原因可能为单一的检测系统存在漏洞,新发表的论文上传数据库存在时间差,作者对稿件的有意识“修饰”,以及网络时代造假手段多样化.为此,文中提出以下措施:使用多种数据库进行文字检测,从查重报告中发现问题,建立有效的审稿专家数据库、网站教育和警示,充分利用网络资源,加快稿件处理进程,增强编辑的责任意识等,以利于更好地防范学术不端行为.     

A learning-based method to detect and segment text from scene images

This paper proposes a learning-based method for text detection and text segmentation in natural scene images. First, the input image is decomposed into multiple connected-components (CCs) by Niblack clustering algorithm. Then all the CCs including text CCs and non-text CCs are verified on their text features by a 2-stage classification module, where most non-text CCs are discarded by an attentional cascade classifier and remaining CCs are further verified by an SVM. All the accepted CCs are output to result in text only binary image. Experiments with many images in different scenes showed satisfactory performance of our proposed method.     

Predictive value of ventilatory inflection points determined under field conditions

The aim of this study was to evaluate the predictive potential provided by two ventilatory inflection points (VIP₁ and VIP₂) examined in field without using gas analysis systems and uncomfortable facemasks. A calibrated respiratory inductance plethysmograph (RIP) and a computerised routine were utilised, respectively, to derive ventilation and to detect VIP₁ and VIP₂ during a standardised field ramp test on a 400 m running track on 81 participants. In addition, average running speed of a competitive 1000 m run (S_1k) was observed as criterion. The predictive value of running speed at VIP₁ (S_VIP1) and the speed range between VIP₁ and VIP₂ in relation to VIP₂ (VIP_SPAN) was analysed via regression analysis. VIP_SPAN rather than running speed at VIP₂ (S_VIP2) was operationalised as a predictor to consider the covariance between S_VIP1 and S_VIP2. S_VIP1 and VIP_SPAN, respectively, provided 58.9% and 22.9% of explained variance in regard to S_1k. Considering covariance, the timing of two ventilatory inflection points provides predictive value in regard to a competitive 1000 m run. This is the first study to apply computerised detection of ventilatory inflection points in a field setting independent on measurements of the respiratory gas exchange and without using any facemasks.     

人工神经网络在火灾探测中的应用

火灾的早期探测是较为复杂且具有重要意义的研究课题。针对传统火灾探测方法存在的不足,提出了一种基于人工神经网络技术的火灾自动探测系统,即采用黄金分割优选法对网络隐含层节点数进行优选,采用优于BP算法的LM算法进行网络学习训练。实验结果表明不仅这种系统具有拟合精度高和运算速度快等优点,且探测效率良好。