Category Representation for Classification and Feature Inference.

This research's purpose was to contrast the representations resulting from learning of the same categories by either classifying instances or inferring instance features. Prior inference learning research, particularly T. Yamauchi and A. B. Markman (1998), has suggested that feature inference learning fosters prototype representation, whereas classification learning encourages exemplar representation. Experiment 1 supported this hypothesis. Averaged and individual participant data from transfer after inference training were better fit by a prototype than by an exemplar model. However, Experiment 2, with contrasting inference learning conditions, indicated that the prototype model was mimicking a set of label-based bidirectional rules, as determined by the inference learning task demands in Experiment 1. Only the set of rules model accounted for all the inference learning conditions in these experiments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The “Median” Method for the Reduction of Noise and Trigger Jitter on Waveform Data

The “median” method for the reduction of the effect of noise and trigger jitter on waveform data is described. The effectiveness of this method was examined using simulations and experiments and, for typical jitter and noise observed in electrical pulse metrology, is shown to provide reconstructed waveforms with transition durations that accurately match those of the input signal. Also, for aberrations, an upper bound on the error in the amplitude of the aberration is provided.     

基于网站结构挖掘的Web文档自动分类

对Web文档进行人工分类可以达到准确的分类效果，但需要大量的时间和人力的投入。传统的基于特征向量的分类方法准确性较低，文中提出把挖掘网站的拓扑结构和现有的文档分类方法相结合，并根据扩展网页的特征提取，挖掘出单个网站的分类模式，再将多个网站的分类模式进行综合，生成搜索引擎的分类模式。     

防爆起重机的进一步完善

随着化工及军工企业的扩建，防爆起重机作为一种特殊用途的起重机需求量与日俱增，寻求设计出更为先进实用的产品来满足生产的需要已成为起重机生产厂的目标。目前在防爆起重机的变频调速不很成熟的前提下，对双速电机的控制方案作进一步改进已成为必要。     

砼耐久性专家系统总体结构设计

对国内外有关混凝土耐久性的研究成果进行系统分析，重点解决了混凝土耐久性中的众多影响因素、程度的确定及其量化表示等问题，利用神经网络技术解决了知识表示及其推理技术中的复杂性和不确定性问题，设计了推理机，建立了知识库，建立了考虑耐久性破坏因素的碱集料反应、冻性、钢筋锈蚀、硫酸盐侵蚀的混凝土耐久性专家系统。     

Comparison of Operant Escape and Innate Reflex Responses to Nociceptive Skin Temperatures Produced by Heat and Cold Stimulation of Rats.

In behavioral tests, rats performed learned escape responses to thermal stimulation of the paws by 44.0. 47.0. or 0.3 degrees C. Licking, guarding, and jumping reflexes were evaluated at these temperatures. The frequency, latency, and duration of escape and reflex responses were compared and were related to hind-paw skin temperatures measured during stimulation of awake and anesthetized rats. The duration and latency of escape from heat were appropriately related to stimulus intensity. Escape occurred reliably for each intensity. Reflexes occurred unreliably and at long latency to 44.0 or 0.3 degrees C and were not appropriately related to heat intensity. The reflexes were relatively insensitive to thermal nociceptive stimulation other than heating of the skin at a high rate. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Identification of Tone Duration, Line Length, and Letter Position: An Experimental Approach to Timing and Working Memory Deficits in Schizophrenia.

Patients with schizophrenia display numerous cognitive deficits, including problems in working memory, time estimation, and absolute identification of stimuli. Research in these fields has traditionally been conducted independently. We examined these cognitive processes using tasks that are structurally similar and that yield rich error data. Relative to healthy control participants (n = 20), patients with schizophrenia (n = 20) were impaired on a duration identification task and a probed-recall memory task but not on a line-length identification task. These findings do not support the notion of a global impairment in absolute identification in schizophrenia. However, the authors suggest that some aspect of temporal information processing is indeed disturbed in schizophrenia. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Control of Variation by Reward Probability.

Two bar-press experiments with rats tested the rule that reducing expectation of reward increases the variation from which reward selects. Experiment 1 used a discrete-trial random-interval schedule, with trials signaled by light or sound. One signal always ended with reward; the other signal ended with reward less often. The 2 signals were randomly mixed. Bar-press duration (how long the bar was held down) varied more during the signal with the lower probability of reward. Experiment 2 closely resembled Experiment 1 but used a random-ratio schedule rather than a random-interval schedule. Again, bar-press duration varied more during the signal with the lower probability of reward. The results support the rule--the first well-controlled comparisons to do so. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Category Learning in Rhesus Monkeys: A Study of the Shepard, Hovland, and Jenkins (1961) Tasks.

In influential research, R. N. Shepard, C. I. Hovland, and H. M. Jenkins (1961) surveyed humans' categorization abilities using tasks based in rules, exclusive-or (XOR) relations, and exemplar memorization. Humans' performance was poorly predicted by cue-conditioning or stimulus-generalization theories, causing Shepard et al. to describe it in terms of hypothesis selection and rule application that were possibly supported by verbal mediation. The authors of the current article surveyed monkeys' categorization abilities similarly. Monkeys, like humans, found category tasks with a single relevant dimension the easiest and perceptually chaotic tasks requiring exemplar memorization the most difficult. Monkeys, unlike humans, found tasks based in XOR relations very difficult. The authors discuss the character and basis of the species difference in categorization and consider whether monkeys are the generalization-based cognitive system that humans are not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Evaluation of Passage-Based Text Categorization

Researches in text categorization have been confined to whole-document-level classification, probably due to lack of full-text test collections. However, full-length documents available today in large quantities pose renewed interests in text classification. A document is usually written in an organized structure to present its main topic(s). This structure can be expressed as a sequence of subtopic text blocks, or passages. In order to reflect the subtopic structure of a document, we propose a new passage-level or passage-based text categorization model, which segments a test document into several passages, assigns categories to each passage, and merges the passage categories to the document categories. Compared with traditional document-level categorization, two additional steps, passage splitting and category merging, are required in this model. Using four subsets of the Reuters text categorization test collection and a full-text test collection of which documents are varying from tens of kilobytes to hundreds, we evaluate the proposed model, especially the effectiveness of various passage types and the importance of passage location in category merging. Our results show simple windows are best for all test collections tested in these experiments. We also found that passages have different degrees of contribution to the main topic(s), depending on their location in the test document.