学习困难儿童智力结构及其与心理语言、视动能力关系的研究

IQ Structure, Psycholinguistic and Visual-motor Abilities Study on Children Learning Disability TONG Fang Directed by professor Zhu Liqi (Developmental and educational psychology) ABSTRACT Objective To comprehensive analyze the IQ structures, and relationships among IQ, psychometric characteristics and visual-motor integration on children disability. At same time, to probe into the family factors that influenced IQ, psycholinguistic abilities and behavior of LD children. Method (1) Downloading the papers on children learning disability from www.cqvip.com and www.wanfangdata.com, in which, the articles were collected by key words from 1985 to 2005. To conduct meta-analysis on IQ construction, compare the case group and the control group, including full IQ, verbal and practice IQ. (2) Designed with model compared and self-compared, 59 diagnosed learning disability children, tested themes with WISC, ITPA and Berry’s VMI. WISC included 10 items, 5 of which subtotal to verbal and practice IQ respectively. IPTA included 10 items, too, 5 process of which subtotal to auditory and visual perception. The first 3 items shared representation level, the other 2 of that shared automatic level.VMI had one score. Analyzed factors and levels with description and Pearson Correlation. To probe to linguistic internal alternately functions of LD children, and compare the scores of groups in different IQ. (3) Analyzed the perspective questionnaire filled by parents. Early development facts compared with model groups. Factors relationships analyzed with Kendall correlation, KOM and Bartlett’s test of sphericity, Promax Rotation. Results: (1) There have been 319 papers related with LD, in which 36 with IQ and 14 valid reports have been analyzed by Meta. FIQ’s 95%CI (confidence interval) is 2.418 ~ 0.172, VIQ between the difficulty and non- difficulty group. C-WISC-R reports were 10 papers, of which, 95%CI of FIQ is 2.424 ~ 0.676, of VIQ is 2.314 ~ 1.196, of PIQ is 2.176 ~ 0.176. The VIQ comparing the PIQ, 95%CI is 1.1 ~ -0.07 in difficulty group and 0.5 ~ -0.0046 in non-difficult group. Nevertheless, in the other 4 tests, FIQ’s 95%CI is 2.00 ~ -0.818 between LD and NLD. (2) Children psycholinguistic abilities had strong relation with Berry’s VMI test excluding auditory reception, and with perceptive factor of intelligence excluding verbal expression. Auditory reception and visual closure had strong relation with FIQ and PIQ. Grammatic closure, visual association and manual expression had strong relation with concept factor. The representational and automatic levels are depended on integration of auditory and visual procession. Lower verbal expression (VE) let to lower expression process and low scores on representational level. Lower visual sequential memory (VSM) let to lower memory process and influenced automatic level. Groups compared by IQ 90 show that LD children with under IQ 90 had lower scores on items of IPTA than with up IQ 90 excluded verbal expression. It was proved that IQ administrated the linguistic ability. Nevertheless, general abilities deficiency didn’t show influencing on the types of the perceptive delay. There was mutual function among linguistic ability on LD children. Auditory and visual level are overlapped each other. Not only show higher Decoding and lower Encoding on Auditory perception, lower Decoding and higher Encoding on Visual perception, in representation, but also higher Sequential remember, lower Closure on Audition, and lower Sequential member, higher Closure on Vision, in Automation. Nevertheless, there was no different between Representational and Automatic level, which may be the relationship of parallel or evolution. (3) Major family factors were father’s education, occupation. Lower auditory perception related to unconcerned, lower visual perception related to premature delivery and written slowly. Threatened–abortion, childbirth-suffocated were known as influencing children’s IQ and later linguistic abilities. It wasn’t shown that dosage relationship with the types of perceptive delay. Conclusion: (1) The FIQ, VIQ and PIQ of Children with LD is lower than that of NLD group. There is no significantly different between VIQ and PIQ in LD and NLD groups. (2) The objectives of ITPA and WISC tests are differently. The psycholinguistic abilities had strong relation with perceptive factor and VMI. Some facts of IPTA related with FIQ. IQ had strong administration on linguistic abilities. There was mutual function among linguistic internal abilities. (3) Family facts on IQ and psycholinguistic abilities were Father’s education, abnormal pregnant and abortion. It would be pre-show development delay in early period.

Feature Matching for Object Localization in the Presence of Uncertainty

We consider the problem of matching model and sensory data features in the presence of geometric uncertainty, for the purpose of object localization and identification. The problem is to construct sets of model feature and sensory data feature pairs that are geometrically consistent given that there is uncertainty in the geometry of the sensory data features. If there is no geometric uncertainty, polynomial-time algorithms are possible for feature matching, yet these approaches can fail when there is uncertainty in the geometry of data features. Existing matching and recognition techniques which account for the geometric uncertainty in features either cannot guarantee finding a correct solution, or can construct geometrically consistent sets of feature pairs yet have worst case exponential complexity in terms of the number of features. The major new contribution of this work is to demonstrate a polynomial-time algorithm for constructing sets of geometrically consistent feature pairs given uncertainty in the geometry of the data features. We show that under a certain model of geometric uncertainty the feature matching problem in the presence of uncertainty is of polynomial complexity. This has important theoretical implications by demonstrating an upper bound on the complexity of the matching problem, an by offering insight into the nature of the matching problem itself. These insights prove useful in the solution to the matching problem in higher dimensional cases as well, such as matching three-dimensional models to either two or three-dimensional sensory data. The approach is based on an analysis of the space of feasible transformation parameters. This paper outlines the mathematical basis for the method, and describes the implementation of an algorithm for the procedure. Experiments demonstrating the method are reported.

A Self-Organizing Multiple-View Representation of 3D Objects

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Analytical Representation of Contours

The interpretation and recognition of noisy contours, such as silhouettes, have proven to be difficult. One obstacle to the solution of these problems has been the lack of a robust representation for contours. The contour is represented by a set of pairwise tangent circular arcs. The advantage of such an approach is that mathematical properties such as orientation and curvature are explicityly represented. We introduce a smoothing criterion for the contour tht optimizes the tradeoff between the complexity of the contour and proximity of the data points. The complexity measure is the number of extrema of curvature present in the contour. The smoothing criterion leads us to a true scale-space for contours. We describe the computation of the contour representation as well as the computation of relevant properties of the contour. We consider the potential application of the representation, the smoothing paradigm, and the scale-space to contour interpretation and recognition.

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Most reinforcement learning methods operate on propositional representations of the world state. Such representations are often intractably large and generalize poorly. Using a deictic representation is believed to be a viable alternative: they promise generalization while allowing the use of existing reinforcement-learning methods. Yet, there are few experiments on learning with deictic representations reported in the literature. In this paper we explore the effectiveness of two forms of deictic representation and a naive propositional representation in a simple blocks-world domain. We find, empirically, that the deictic representations actually worsen performance. We conclude with a discussion of possible causes of these results and strategies for more effective learning in domains with objects.

Tense, Aspect and the Cognitive Representation of Time

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Context-Based Vision System for Place and Object Recognition

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Activity Zones for Context-Aware Computing

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Toward a Theory of Representation Design

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The Role of Knowledge in Visual Shape Representation

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TYPICAL: A Knowledge Representation System for Automated Discovery and Inference

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