Temporal scatterplots

Computational Visual Media - Visualizing high-dimensional data on a 2D canvas is generally challenging. It becomes significantly more difficult when multiple time-steps are to be presented, as the...     

Density in scatterplots and the estimation of correlation

The construction of a graphical presentation involves the representation of information by means of visual symbols. The acquisition of information from the resultant graph is a perceptual process that involves the decoding and interpretation of the visual symbols. Hence good design decisions will be based on an understanding of the information acquisition process and in particular graphical perception. This study examines the perception of bivariate normal data presented in a scatter diagram, and creates a model that successfully explains how individuals perceive the information contained in scatterplots

Subjects were shown a series of scatter diagrams on the CRT of a microcomputer and were asked to estimate correlation. Several variables were examined that explain estimated correlation including regression slope, dispersion, number of points displayed, and the size of the CRT screen. All of these factors were found to significantly affect subjects' estimates of correlation.     

User interaction with scatterplots on small screens--A comparative evaluation of geometric-semantic zoom and fisheye distortion

Existing information-visualization techniques that target small screens are usually limited to exploring a few hundred items. In this article we present a scatterplot tool for Personal Digital Assistants that allows the handling of many thousands of items. The application's scalability is achieved by incorporating two alternative interaction techniques: a geometric-semantic zoom that provides smooth transition between overview and detail, and a fisheye distortion that displays the focus and context regions of the scatterplot in a single view. A user study with 24 participants was conducted to compare the usability and efficiency of both techniques when searching a book database containing 7500 items. The study was run on a pen-driven Wacom board simulating a PDA interface. While the results showed no significant difference in task-completion times, a clear majority of 20 users preferred the fisheye view over the zoom interaction. In addition, other dependent variables such as user satisfaction and subjective rating of orientation and navigation support revealed a preference for the fisheye distortion. These findings partly contradict related research and indicate that, when using a small screen, users place higher value on the ability to preserve navigational context than they do on the ease of use of a simplistic, metaphor-based interaction style.     

Continuous design

The rising popularity of refactoring, tools such as JUnit, and agile methodologies such as extreme programming (XP) has brought a new style of design into view. Continuous design is the process of using refactoring to continuously improve a program's design. Continuous design is also known as evolutionary or emergent design. It emphasizes the core of the process: continuously taking advantage of opportunities to improve our design. Continuous design's focus on simplicity and continuous improvement has made the code better and more maintainable over time, rather than less.     

Continuous case-based reasoning

Case-based reasoning systems have traditionally been used to perform high-level reasoning in problem domains that can be adequately described using discrete, symbolic representations. However, many real-world problem domains, such as autonomous robotic navigation, are better characterized using continuous representations. Such problem domains also require continuous performance, such as on-line sensorimotor interaction with the environment, and continuous adaptation and learning during the performance task. This article introduces a new method for continuous case-based reasoning, and discusses its application to the dynamic selection, modification, and acquisition of robot behaviors in an autonomous navigation system, SINS (self-improving navigation system). The computer program and the underlying method are systematically evaluated through statistical analysis of results from several empirical studies. The article concludes with a general discussion of case-based reasoning issues addressed by this research.     

连铸中间包钢水连续测温

在介绍了连铸中间包钢水连续测温系统应用及发展的基础上，探讨了实体型抗氧化钨体热电偶、保护管的腐蚀行为与对策、测温点的选择与深度、响应速度等连测技术中的有关问题。     

Continuous Model-Driven Engineering

CMDE has been successfully applied in several industrial projects, including telecommunication services, supply-chain management, bioinformatics, logistics, and healthcare. In all these cases, agility at the customer, user, and application level proved key to aligning and linking business and IT. We now expect an additional boost when integrating this approach into a processor project-management environment that oversees development and evolution. This environment will include deadline management and progress reports, automatically informing all relevant parties when certain actions are required, managing different versions and product lines, and automatically steering the build and quality-management process. Perhaps not surprisingly, the development of this management environment proved to be a prime application of CMDE.     

A Creativity Model for the Analysis of Continuous Improvement Programmes: A Suggestion to Make Continuous Improvement Continuous

Continuous improvement programmes constitute an area in which creativity seems to play a vital role. This paper shows how continuous improvement may be studied more effectively in a framework which reveals relationships between the four facets of creativity: products, processes, people, and the press or environment. It is suggested that such a systematic analysis can enhance continuous improvement efforts by indicating how momentum is maintained as the company develops self-reflective (‘learning’) skills.     

Template-Based Continuous Speech Recognition

Despite their known weaknesses, hidden Markov models (HMMs) have been the dominant technique for acoustic modeling in speech recognition for over two decades. Still, the advances in the HMM framework have not solved its key problems: it discards information about time dependencies and is prone to overgeneralization. In this paper, we attempt to overcome these problems by relying on straightforward template matching. The basis for the recognizer is the well-known DTW algorithm. However, classical DTW continuous speech recognition results in an explosion of the search space. The traditional top-down search is therefore complemented with a data-driven selection of candidates for DTW alignment. We also extend the DTW framework with a flexible subword unit mechanism and a class sensitive distance measure-two components suggested by state-of-the-art HMM systems. The added flexibility of the unit selection in the template-based framework leads to new approaches to speaker and environment adaptation. The template matching system reaches a performance somewhat worse than the best published HMM results for the Resource Management benchmark, but thanks to complementarity of errors between the HMM and DTW systems, the combination of both leads to a decrease in word error rate with 17% compared to the HMM results     

Continuous operations on languages

Most of the operations of interest in language theory arecontinuous in a certain technical sense. For such operations, there always exist infinite sets of languages that areindependent in the sense that no language in such a set can be generated from the other languages in the set by the operations in question.     

Continuous space language models

This paper describes the use of a neural network language model for large vocabulary continuous speech recognition. The underlying idea of this approach is to attack the data sparseness problem by performing the language model probability estimation in a continuous space. Highly efficient learning algorithms are described that enable the use of training corpora of several hundred million words. It is also shown that this approach can be incorporated into a large vocabulary continuous speech recognizer using a lattice rescoring framework at a very low additional processing time. The neural network language model was thoroughly evaluated in a state-of-the-art large vocabulary continuous speech recognizer for several international benchmark tasks, in particular the Nist evaluations on broadcast news and conversational speech recognition. The new approach is compared to four-gram back-off language models trained with modified Kneser–Ney smoothing which has often been reported to be the best known smoothing method. Usually the neural network language model is interpolated with the back-off language model. In that way, consistent word error rate reductions for all considered tasks and languages were achieved, ranging from 0.4% to almost 1% absolute.     

Continuous Generalized Procrustes analysis

Two-dimensional shape models have been successfully applied to solve many problems in computer vision, such as object tracking, recognition, and segmentation. Typically, 2D shape models are learned from a discrete set of image landmarks (corresponding to projection of 3D points of an object), after applying Generalized Procustes Analysis (GPA) to remove 2D rigid transformations. However, the standard GPA process suffers from three main limitations. Firstly, the 2D training samples do not necessarily cover a uniform sampling of all the 3D transformations of an object. This can bias the estimate of the shape model. Secondly, it can be computationally expensive to learn the shape model by sampling 3D transformations. Thirdly, standard GPA methods use only one reference shape, which can might be insufficient to capture large structural variability of some objects.To address these drawbacks, this paper proposes continuous generalized Procrustes analysis (CGPA). CGPA uses a continuous formulation that avoids the need to generate 2D projections from all the rigid 3D transformations. It builds an efficient (in space and time) non-biased 2D shape model from a set of 3D model of objects. A major challenge in CGPA is the need to integrate over the space of 3D rotations, especially when the rotations are parameterized with Euler angles. To address this problem, we introduce the use of the Haar measure. Finally, we extended CGPA to incorporate several reference shapes. Experimental results on synthetic and real experiments show the benefits of CGPA over GPA.     

Continuous monoids and semirings

Different kinds of monoids and semirings have been defined in the literature, all of them named “continuous”. We show their relations. The main technical tools are suitable topologies, among others a variant of the well-known Scott topology for complete partial orders.     

相关扰动下连续系统的连续时间最小二乘辨识的数值实现

基于数值积分和常微分方程数值解的欧拉法和龙格－－库塔法，给出随机连续系统的连续时间最小二乘辨识的两种数值实现方法，仿真结果表明了该方法的有效性。     

Universal Continuous Routing Strategies

We analyze universal routing protocols, that is, protocols that can be used for any communication pattern in any network, under a stochastic model of continuous message generation. In particular, we present two universal protocols, a store-and-forward and a wormhole routing protocol, and characterize their performance by the following three parameters: the maximum message generation rate for which the protocol is stable, the expected delay of a message from generation to service, and the time the protocol needs to recover from worst-case scenarios. Both protocols yield significant performance improvements over all previously known continuous routing protocols. In addition, we present adaptations of our protocols to continuous routing in node-symmetric networks, butterflies, and meshes. Received October 1996, and in final form April 1997.     

Continuous input nonlocal games

We present a family of nonlocal games in which the inputs the players receive are continuous. We study three representative members of the family. For the first two a team sharing quantum correlations (entanglement) has an advantage over any team restricted to classical correlations. We conjecture that this is true for the third member of the family as well.     

持续审计(CA)研究综述

持续审计(Continuous Auditing,CA)是目前计算机辅助审计领域中的一个研究前沿问题.本文对CA的研究进行了分析、比较和展望.首先分析了CA的内涵.然后,对CA的相关研究进行了分类:(1)技术实现方法,分成嵌入式和分离式两种;(2)理论分析;(3)应用于CA的关键技术,并根据该分类对CA的研究分别进行了分析.最后,总结了本文的工作,并对将来CA的研究做了展望.     

基于连续多版本的可审计文件系统

随着越来越多的法律法规要求将电子数据纳入审计监督范围,电子数据安全审计变得愈来愈重要.电子数据审计要求为数据的更改生成可验证的审计跟踪记录.现有的针对电子数据审计的系统因为不能防止内部人员的攻击以保证审计跟踪记录的安全可信,无法很好地满足用户需求.设计并实现了一个基于连续多版本的可审计文件系统CV-AFS,通过连续多版本技术连续捕获和保存文件系统数据变化,引入了一个可信的审计代理负责生成相应的审计跟踪记录,事后审计机构可根据审计跟踪记录来对数据进行审计,从而防止了内部人员的攻击.通过使用增量Hash算法,降低了生成审计跟踪记录的开销.作者在Linux上基于多版本文件系统ext3cow实现了CV-AFS的原型系统并进行了性能测试.Postmark的测试结果表明,CV-AFS的总时间开销要比使用传统完全Hash算法的开销降低43.5%.