Failures of retrieval and comparison constrain change detection in natural scenes.

In a change detection paradigm, a target object in a natural scene either rotated in depth, was replaced by another object token, or remained the same. Change detection performance was reliably higher when a target postcue allowed participants to restrict retrieval and comparison processes to the target object (Experiment 1). Change detection performance remained excellent when the target object was not attended at change (Experiment 2) and when a concurrent verbal working memory load minimized the possibility of verbal encoding. (Experiment 3). Together, these data demonstrate that visual representations accumulate in memory from attended objects as the eyes and attention are oriented within a scene and that change blindness derives, at least in part, from retrieval and comparison failure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Perceptually Grounded Language Learning: Part 2—DETE: A Neural/Procedural Model

In Part 1 of this two-part series, we introduced Katamic memory—a neural network architecture capable of robust sequence learning and recognition. In Part 2, we introduce the Blobs World taskjdomain for language learning and describe the DETE language learning system, which is composed of over 50 Katamic memory modules. DETE currently learns small subsets of English and Spanish via association with perceptual! motor inputs. In addition to Kaiamic memory, DETE employs several other novel features: (1) use of feature planes, to encode visual shapes, spatial relationships and the motions of objects, (2) phase-locking of neural firing, in order to represent focus of atention and to bind objects across multiple feature planes, and (3) a method for encoding temporal relationships, so that DETE can learn utterances involving the immediate past and future. We compare DETE to related models and discuss the implications of this approach for language-learning research.     

动态过程监视的最佳显示方式研究

文中讨论了人机界面的视学工效问题，通过实验评价了用于动态过程监视与控制的三种ＣＲＴ显示方式的工效，并由此得出人类视学系统反应对图形方式更优于对数字方式，图形与数字的复合方式。     

Radiosity with Well Distributed Ray Sets

In this paper we present a new radiosity algorithm, based on the notion of a well distributed ray set (WDRS). A WDRS is a set of rays, connecting mutually visible points and patches, that forms an approximate representation of the radiosity operator and the radiosity distribution. We propose an algorithm that constructs an optimal WDRS for a given accuracy and mesh. The construction is based on discrete importance sampling as in previously proposed stochastic radiosity algorithms, and on quasi Monte Carlo sampling. Quasi Monte Carlo sampling leads to faster convergence rates and the fact that the sampling is deterministic makes it possible to represent the well distributed ray set very efficiently in computer memory. Like previously proposed stochastic radiosity algorithms, the new algorithm is well suited for computing the radiance distribution in very complex diffuse scenes, when it is not feasible to explicitly compute and store form factors as in classical radiosity algorithms. Experiments show that the new algorithm is often more efficient than previously proposed Monte Carlo radiosity algorithms by half an order of magnitude and more.     

Automated Support for Building and Extending Expert Models

Building a knowledge-based system is like developing a scientific theory. Although a knowledge base does not constitute a theory of some natural phenomenon, it does represent a theory of how a class of professionals approaches an application task. As when scientists develop a natural theory, builders of expert systems first must formulate a model of the behavior that they wish to understand and then must corroborate and extend that model with the aid of specific examples. Thus there are two interrelated phases of knowledge-base construction: (1) model building and (2) model extension. Computer-based tools can assist developers with both phases of the knowledge-acquisition process. Workers in the area of knowledge acquisition have developed computer-based tools that emphasize either the building of new models or the extension of existing models. The PROTÉGÉ knowledge-acquisition system addresses these two activities individually and facilitates the construction of expert systems when the same general model can be applied to a variety of application tasks.     

An alternate method for using a visual discrimination model (VDM) to optimize soft-copy display image quality

Researchers have developed visual discrimination models (VDMs) that can predict a human observer's ability to detect a target object superposed on an image. These models incorporate sophisticated knowledge of the properties of the human visual system. In the predictive approach, termed conventional VDM usage, two input images with and without a target are analyzed by an algorithm that calculates a just-noticeable-difference (JND) index, which is a taken as a measure of the detectability of the target. A new method of using the VDM is described, termed channelized VDM, which involves finding the linear combination of the VDM-generated channels (which are not used in conventional VDM analysis) that has optimal classification ability between normal and abnormal images. The classification ability can be measured using receiver operating characteristic (ROC) or two alternative forced choice (2AFC) experiments, and in special cases they can also be predicted by signal detection theory (SDT) based model-observer methods. In this study simulated background and nodule containing regions were used to validate the new method. It was found that the channelized VDM predictions were in excellent qualitative agreement with human-observer validated SDT predictions. Either VDM method (conventional or channelized) has potential applicability to soft-copy display optimization. An advantage of any VDM-based approach is that complex effects, such as visual masking, are automatically accounted for, which effects are usually not included in SDT-based methods.     

Using formalized temporal message-flow diagrams

Temporal message-flow diagrams (TMFDs), alternatively called sequence charts, interaction diagrams, event traces, or actor diagrams, are illustrations of a system's global message-passing activity over time, and a pictorial aid to understanding the system's behavior. They are widely used for requirements and documentation for network protocols and object-oriented applications. We present a general formalism for TMFDs, describe a suite of tools we have designed that employs this formalism, and present our experiences with these tools. The formalism and tools described serve to support and broaden the use of TMFDs in developing communicating systems.     

公安110报警指挥系统组网设计

１１０是电话网中的匪警特服号，现代信息化社会的发展要求１１０接警响应迅速而准确，本文介绍了公安１１０报警指挥系统的组成原理，给出了该系统与公共市话网和公安专网的组网实现方法，并对工程设计中的系统可靠性问题进行了详细的讨论，该系统也可用于１１９报警等其待服业务。     

基于．NET气门尺寸检测系统软件架构设计

光学非接触检测是随着机械制造技术、计算机视觉技术、图像处理技术等发展而出现的新兴检测技术。传统人工手段对气门尺寸的检测往往存在效率低、可靠性差、检测精度不高、成本高、容易出错等弊端,采用光学非接触检测技术不仅可以提高检测的效率、精度和可靠性,同时可以降低成本和出错率。文中在阐述了系统的硬件结构和基本工作原理的基础上,通过分析实际生产需求,结合．NET技术框架,提出了符合实际需求的检测系统总体架构,并开发了汽车发动机气门尺寸自动检测系统,实现了系统各个功能模块并合理地解决了模块之间的联系,通过高精度算法检测出零件参数。该系统已应用于实际生产中,取得不错的效果。