Web 2D Graphics File Formats

The earliest Web browsers focussed on the display of textual information. When graphics were added, essentially only image graphics and image file formats were supported. For a significant range of applications, image graphics has severe limitations, for example in terms of file size, download time and inability to interact with and modify the graphics client-side. Vector graphics may be more appropriate in these cases, and this has become possible through the introduction of the WebCGM and Scalable Vector Graphics (SVG) formats, both of which are open standards, the former from ISO/IEC and W3C and the latter from W3C. This paper reviews the background to Web graphics, presents the WebCGM file format, and gives a more detailed exposition of the most recent format, SVG. The paper concludes with reflections on the current state of this area and future prospects.     

Identifying the timing and duration of collecting patient priorities in an orthopedic clinic

The patient‐centered care model supports patients actively engaging in their care. Typically this involves collecting patient‐reported outcomes and priorities that may not be part of the routine practice. There is a research gap related to whether there is time available within the routine orthopedic medical practice to collect patient‐centered data for immediate use without delaying the overall clinical processes or influencing patient clinical experiences. A time study was conducted to quantify the current patient processes at an orthopedic clinic, and a statistical simulation model was used to evaluate potential changes in patients’ clinical process if a patient‐centered survey were to be implemented. The proportion of simulated patients who would experience delays due to the survey, the durations of their delays, and the average duration of the patient process delay were recorded at each step in the clinical process. The results are presented in terms of the relationship between the time devoted to collecting data and the impact on the patient experience for various survey durations at various process points. This study demonstrates an approach to evaluate how introducing a patient priorities survey (for collecting both patient‐reported outcomes and priorities), which could be used in the same patient visit, might impact the clinical process and introduce process delays.     

Using hierarchical statistical analysis and deep neural networks to detect covert timing channels

Covert timing channels provide a mechanism to leak data across different entities. Manipulating the timing between packet arrivals is a well-known example of such approach. The time based property makes the detection of the hidden messages impossible by traditional security protecting mechanisms such as proxies and firewalls. This paper introduces a new generic hierarchical-based model to detect covert timing channels. The detection process consists of the analysis of a set of statistical metrics at consecutive hierarchical levels of the inter-arrival times flows. The statistical metrics considered are: mean, median, standard deviation, entropy, Root of Average Mean Error (RAME). A real statistical metrics timing channel dataset of covert and overt channel instances is created. The generated dataset is set to be either flat where the statistical metrics are calculated on all flows of data or hierarchal (5 levels of hierarchy were considered) where the statistical metrics are computed on sub parts of the flow as well. Following this method, 5 different datasets were generated, and used to train/test a deep neural network based model. Performance results about accuracy and model training time showed that the hierarchical approach outperforms the flat one by 4 to 10 percent (in terms of accuracy) and was able to achieve short model training time (in terms of seconds). When compared to the Support Vector Machine (SVM) classifier, the deep neural network achieved a better accuracy level (about 2.3% to 12% depends on the used kernel) and significantly shorter model training time (few seconds versus few 100’s of seconds). This paper also explores the importance of the used metrics in each level of the detection process.     

Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R

The widely used proportional odds model is developed for correlated repeated ordinal score data, using a modified version of the generalized estimating equation (GEE) method for model fitting for a range of working correlation models. The algorithm developed estimates the correlation parameter, by minimizing the generalized variance of the regression parameters at each step of the fitting algorithm. Methods for parameter estimation are described for the widely used uniform and first-order autoregressive correlation models, for data potentially recorded at irregularly spaced time intervals. A full implementation of the algorithm (repolr) in the R statistical software package, that both tests the assumption of proportional odds and accommodates missing data, is described and applied to a clinical trial of post-operative treatment, after rupture of the Achilles tendon and a study of patient pain response after hip joint resurfacing.     

基于SVG的Web页面动态刷新

文中将SVG图形显示技术和Web页面动态刷新技术相结合,实现了Web复杂图形的实时更新。SVG(ScalableVector Graphics)是由W3C发布的基于XML的二维矢量图形描述语言。Web页面动态刷新是指当服务器端数据发生变化或者事件发生时,可以将信息或数据通知客户端,实现客户端Web页面现实内容的改变。     

VISTO: A new CBIR system for vector images

In this paper, we present the main features of VISTO (Vector Image Search TOol), a new content-based image retrieval (CBIR) system for vector images. Though unsuitable for photo-realistic imagery, vector graphics are continually becoming more advanced and diffused. Vector images are fully scalable, resolution independent, not restricted to rectangular shape, allowing layering and editable/searchable text. Notwithstanding this increasing interest, the research area concerning CBIR systems for vectorial images is quite new, and our research on a vector based CBIR system actually derives from a precise request of vector based application experts that did not find appropriate solutions to their retrieval problems in customary shape-based CBIR system. To the best of our knowledge, VISTO is the first CBIR system for vector images proposed in the literature, and it supports the retrieval of images in SVG (scalable vector graphics) format.     

Performance evaluation of medical expert systems using ROC curves

This paper presents a performance evaluation of the diagnostic accuracy of the medical expert system CADIAG-2/PANCREAS. The study included 47 clinical cases from a university hospital with 51 diagnosis of pancreatic diseases (four patients had two pancreatic diseases). As gold standard, the histologically or clinically confirmed diagnoses were assumed. Performance was studied along three lines: (a) each case was evaluated twice, first, by restricting patient data to history, physical examination, and basic laboratory tests and, second, by utilizing the complete set of data including also special laboratory tests. US. X ray, CT-scan, ECG, and biopsy, if available: (b) considering CADIAG-2's hypotheses generation, each evaluation series was also carried out twice, first, by testing whether the gold standard was the first diagnosis in the ranked list of hypothesis and, second, whether the gold standard was among the hypotheses: (c) receiver operating characteristic (ROC) curves were determined by varying an internal threshold which determined the extent of CADIAG-2's diagnostic hypotheses generation. The evaluation showed that CADIAG-2's initial list of diagnostic hypotheses, based on patient history, physical examination, and basic laboratory tests usually has already included the gold standard diagnosis and thus an application of CADIAG-2 at a very early stage of the diagnostic process seems achievable. Moreover, it turned out that given the complete set of patient's medical data the gold standard is usually ranked at the first place in the list of hypotheses. except for patients with chronic diseases where only unspecific findings are available. The last test series showed that ROC curves do not only allow optimal adjustment of the expert system's internal ad hoc decision criteria such as thresholds, weights, and scores but also provide a basis for better comparing the performance of different medical expert systems.     

基于X文件的数据库管理方法的研究

为了解决虚拟建筑中X格式的图形文件和Oracle数据库的异构问题,对DirectX所绘制的X图形文件格式进行了深入分析,并探索了图形数据库管理方法。利用Oracle数据库存储X文件格式的图形数据,通过OLE DB技术访问图形数据库,实现了对DirectX所绘制图形的可视化操作以及图形文件和Oracle数据库的集成。对X文件参数用数据库进行管理,方便了对图形进行操作,提高了作图效率,增加了软件的可用性。     

Statistical graphics in APL: Structuring a graphical support system for interactive data analysis

The design of an interactive statistical graphics system in APL is described. Called STATGRAPHICS, the system is structured to create an environment in which statistical and graphics functions are integrated under flexible user control. An optional menu control scheme allows inexperienced users to execute functions under system control, while experienced users can access program functions directly. Procedure control functions, which generate fullscreen control pages and execute operations through defined program function keys, enable graphics to become an integral part of the statistical modeling process.     

Automatic and interactive evolution of vector graphics images with genetic algorithms

Vector graphics are popular in illustration and graphic design. Images are composed of discrete geometric shapes, such as circles, squares, and lines. The generation of vector images by evolutionary computation techniques, however, has been given little attention. JNetic is an implementation of a comprehensive evolutionary vector graphics tool. Vector primitives available range from simple geometric shapes (circles, polygons) to spline-based paint strokes. JNetic supports automatic and user-guided evolution, chromosome editing, and high-detail masks. Automatic evolution involves measuring the pixel-by-pixel colour distance between a candidate and target image. Masks can be painted over areas of the target image, which help reproduce the high-detail features within those areas. By creative selection of primitives and colour schemes, stylized interpretations of target images are produced. The system has been successfully used by the authors as a creative tool.     

A Library for Developing PHIGS Programming Tools in a PEX Environment

The merger of three-dimensional graphics with the X Window System has recently been standardized by adapting PHIGS, the Programmer's Hierarchical Interactive Graphics System, to the X Window System with PEX, the PHIGS Extension to X. The standard programming library for PEX has been defined to be identical to PHIGS PLUS allowing PHIGS programs to port directly to the X environment. X uses a client server model to run applications as client processes which communicate with a server to perform graphical display and input. For improved performance, the PEX extension defines new server resources to reduce network traffic and to take advantage of graphics hardware existing on high-end servers. A side effect of this distributed model of computation is a distribution of PHIGS structures leading to a relaxation of the exclusive access which a PHIGS application usually maintains over its Central Structure Store. We exploit the distributed nature of a PEX/PHIGS client's Central Structure Store to provide access to it for other applications besides the originating PEX/PHIGS client. We refer to these other applications as tools since one of our primary goals is to create development tools for PHIGS programmers. Rather than concentrate on particular debugging tools, we focus upon easing the process of actually developing tools. Our goal is to supply a collection of routines which can be used by PHIGS programmers to create custom tools or other programs which require access to the graphics data of remote PHIGS processes. Our Tool Development Library provides the PHIGS programmer a small number of management routines which orchestrate the connection and mapping to the data of one or more remote PHIGS applications. Manipulation of remote PHIGS structures is accomplished just as easily as local operations and is performed using standard PHIGS calls. The remote application being accessed requires no changes to its source code. Obvious uses for the Tool Development Library are in the construction of PHIGS tools such as structure browsers, editors and debugging aids. Less obvious is the potential for developing collections of cooperating graphics applications which share graphics data.     

基于可伸缩矢量图形的手绘几何图形结构分析方法

复杂图形通常是由多个图元按一定几何关系构成,以基本图形的识别为基础,复杂图形识别重点在于图形元素之间的空间关系模式的判定。几何图形的图元构成复杂,难以直接利用启发式规则进行识别;而现有的结构分析方法太复杂,采用传统方法难以进行有效识别。针对手绘几何图形识别中结构分析这一核心技术问题,设计了一种几何图形结构描述模型,该模型通过对图元及其约束关系的形式化描述来表示图形,使用可伸缩矢量图形(SVG)标签存储图元及其约束,通过解析SVG标签来识别几何图形的形状及其内部关系,为图形结构分析提供了统一格式的表示方法。所提方法已经过自主开发的GeoSketch系统的验证,并取得良好效果。实验结果表明:该方法简洁、低维,方便进行图形形状及内部关系的判定。     

Parallel simulation for a fish schooling model on a general‐purpose graphics processing unit

We consider an individual‐based model for fish schooling, which incorporates a tendency for each fish to align its position and orientation with an appropriate average of its neighbors' positions and orientations, in addition to a tendency for each fish to avoid collisions. To accurately determine the statistical properties of the collective motion of fish whose dynamics are described by such a model, many realizations are typically required. This carries a very high computational cost. The current generation of graphics processing units is well suited to this task. We describe our implementation and present computational experiments illustrating the power of this technology for this important and challenging class of problems. Copyright © 2008 John Wiley & Sons, Ltd.     

图形矢量技术在油田集输生产中应用的研究

从实现各种设备图层、设计生产进度和油气产品的处理以及为决策者及时提供第一手的数据三个方面，研究了图形矢量技术在油田集输生产管理系统中所起的重要作用．介绍了MapInfo的矢量化图形管理功能，列举了开发油田集输生产管理系统的一些经验．     

Recurrent non-specific low-back pain in adolescents: the role of exercise

This study evaluated the efficacy of an exercise programme as an intervention for recurrent non-specific low-back pain (NLSBP) in adolescents. A randomized controlled trial was conducted with an experimental group (n = 27, age 14.6 years) who participated in an 8-week exercise programme and a matched control group (n = 27, age 14.6 years) who continued normal daily activities. All participants suffered from recurrent NSLBP. Pre and post intervention measures of NSLBP status (pain severity and consequences) and daily inactivity (time spent sitting, PC time, TV time) were reported in one week diaries. Two-way mixed ANOVA (independent variables: pre/post and experimental/control) was conducted for each dependent variable, significance was set at P < 0.05. Significant interaction effects were identified for the severity of pain, number of occasions missing sport due to NSLBP and amount of sport participated in. In each case the experimental group benefited from the exercise programme. In contrast, no significant interaction effects were observed for physical inactivity, both groups spent a similar amount of time sitting, watching TV and using a PC pre- and post- intervention. It was concluded that an exercise programme acted as an effective short-term treatment strategy for NSLBP in adolescents. Further evaluation is required to assess the long-term effectiveness.     

LS—SVM在混沌时间序列预测中的应用

支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。文中将最小二乘支持向量机算法应用于混沌时间序列预测中，并同BP网络及RBF网络的预测结果进行了比较分析。仿真实验表明，该方法具有很好的泛化能力和一定的噪声容忍能力。     

矢量图形系统的开发

矢量图形系统已经成为图形组态平台中一个不可或缺的重要部分,本文基于Vc＋＋平台,应用面向对象的设计方法来设计程序构成,最终完成了包括文档和视图的实现、鼠标的交互绘图、以及图形的选中、平移、旋转、无极放缩等设计目标,同时也实现了自定义格式的矢量图存储。     

A Bayesian approach for analyzing a cluster-randomized trial with adjustment for risk misclassification

Bayesian hierarchical modelling techniques have some advantages over classic methods for the analysis of cluster-randomized trial. Bayesian approach is also becoming more popular to deal with measurement error and misclassification problems. We propose a Bayesian approach to analyze a cluster-randomized trial with adjusting for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. Both simulated numerical example and real clinical example are given to illustrate the proposed approach. The Bayesian approach has great potential to be used in misclassification problem in generalized linear mixed model (GLMM) since it allow us to fit complex models and identify all the parameters. Our results suggest that Bayesian approach for analyzing cluster-randomized trial and adjusting for misclassification in GLMM is flexible and powerful.