A functional theory of the McCollough effect.

Pattern-contingent color aftereffects, or McCollough effects (MEs), are used to probe the visual brain's operations psychophysically. Their neural substrate is unknown, however, and theories about them are weak. Our theory proposes a strong functional role for MEs and a neuropsychological basis that accounts for "top-down" (global) constraints ignored by other theories. The functional aspect of the theory is based on the concept of contingent adaptation level, following H. Helson (1964), and on the "error-correcting device" of D. P. Andrews (1964), which tracks and adjusts internal representation to external-world contingencies. The neuropsychological part of the theory postulates that global properties are the result of MEs being generated not at the individual detector level but in the vectorfields of which the detectors are elements. It is an implementation of Lie transformation group theory (W. C. Hoffman, 1966). Evidence for this model is assessed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Probing unconscious visual processing with the McCollough effect

The McCollough effect, an orientation-contingent color aftereffect, has been known for over 30 years and, like other aftereffects, has been taken as a means of probing the brain's operations psychophysically. In this paper, we review psychophysical, neuropsychological, and neuroimaging studies of the McCollough effect. Much of the evidence suggests that the McCollough effect depends on neural mechanisms that are located early in the cortical visual pathways, probably in V1. We also review evidence showing that the aftereffect can be induced without conscious perception of the induction patterns. Based on these two lines of evidence, it is argued that our conscious visual experience of the world arises in the cortical visual system beyond V1.     

基于BP神经网络的供应链突发风险评价模型

为评价供应链突发风险的影响,从供应链的组成和运作要素角度定义了5种类型的供应链突发风险,并建立了一套基于风险类型的供应链突发风险评价指标体系.在此基础上,以风险评价指标为输入,风险类型和风险等级为输出,建立了基于BP神经网络的供应链突发风险评价模型.该模型使用BP网络作为经验知识的学习机制来学习突发风险评价指标与突发风险类型及等级之间的映射关系,然后通过BP网络的知识记忆和泛化推理能力实现对供应链突发风险的自动识别和评价.提出的模型在一个供应链风险样本集上进行了验证,验证结果表明了模型的有效性.     

Steel annealing furnace robust neural network model

Abstract

In this day and age, galvanised coated steel is an essential product in several key manufacturing sectors because of its anticorrosive properties. The increase in demand has led managers to improve the different phases in their production chains. Among the efforts needed to accomplish this task, process modelling can be identified as the one with the most powerful outputs in spite of its non-trivial development. In many fields, such as industrial modelling, multilayer feedforward neural networks are often proposed as universal function approximators. These supervised neural networks are commonly trained by the traditional, back-propagation learning format, which minimises the mean squared error (mse) of the training data. However, in the presence of corrupted or extremely deviated samples (outliers), this training scheme may produce incorrect models, and it is well known that industrial data sets frequently contain outliers. The process modelled is a steel coil annealing furnace in a galvanising line, which shares characteristics with most of the furnaces used in galvanised lines all over the world. This paper reports the effectiveness of robust learning algorithms compared to the classical mse-based learning algorithm for the modelling of a real industry process. From this model an adequate line velocity (the velocity set point) for a coil, depending on its characteristics and the furnace condition to receive this coil (temperature set points), can be obtained. With this set point generation model the operator could set strategies to manage the line, i.e. set the order of the coil to be treated or preview the line's speed conditions for the transitory situations.     

基于BP神经网络的钢水温度预定模型

针对目前钢水温度预定方法存在不足,在分析钢水温度预定原理的基础上,在邯钢邯宝炼钢厂建立了基于BP神经网络的精炼终点目标温度和转炉终点目标温度的动态预定模型。利用邯宝炼钢厂的历史生产数据对模型进行了训练和测试,并进行了现场应用试验。结果表明,预定模型对转炉和精炼终点目标温度进行了优化,应用预定模型后,LF开始温度命中率提高到75%,中间包温度命中率提高到96.7%。     

McCollough effect to "form": A local phenomenon.

S. Siegel et al (see record 1992-22207-001) recently reported a McCollough effect (ME) to "form" using a square and a tic-tac-toe grid. It is possible that the effect they reported could be the result of local adaptation to colored contours presented to different retinal areas, rather than a color aftereffect contingent on form. Three induction conditions (with the same 6 Ss) tested this hypothesis. In Condition 1, Ss fixated on the center of the pattern during testing and induction. In Condition 2, Ss fixated on a corner of the pattern during testing and in the center of the pattern during induction. The Ss fixated on the 4 corners of the pattern during induction in Condition 3. An ME was observed in Condition 1 but not in the other conditions. These results support the hypothesis that the ME to form is a product of local color and contour pairing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于BP神经网络的VD过程温降预报模型

建立了基于BP神经网络的VD过程温降预报模型,利用五数总括值法和聚类分析法进行了BP神经网络输入数据的预处理,采用MINITAB软件确定了影响VD过程温降的主要因素为抽真空时间、保压时间、吹氩时间、非真空时间和钢水进VD过热度。利用245罐数据作为训练数据、50罐作为验证数据对模型进行了验证,结果表明:模型计算偏差在±5℃范围内的比例达到88%。     

A neural network based model of sinter quality and sinter plant performance indices

Abstract

A prerequisite of a smooth operation of the ironmaking blast furnace is that the quality of the burden is stable. In blast furnaces where sinter is used as the (main) iron bearing material, its quality plays a crucial role in productivity and fuel economy. Simultaneously the corresponding factors must be considered for the sinter plant. The present paper studies the influence of three variables characterising the bedding piles and five sinter plant operation variables on sinter quality, sinter plant productivity, specific fuel consumption and share of cold return fines. Daily mean values for a period of five years of operation were used in the data driven modelling based on feedforward neural networks. The resulting models were found to describe the major changes in the outputs well. The input–output relations captured by the models were analysed by perturbing one input variable of the networks at a time and analysing the predicted behaviour of the outputs.     

Learning and homeostasis: drug addiction and the McCollough effect

Increasing evidence suggests that the immune cytokine interferon-gamma (IFN-gamma) plays a deleterious role in immune-mediated demyelinating disorders. To further understand the effects of IFN-gamma on oligodendrocytes, we have compared and quantitated the response of developing and mature oligodendrocytes in vitro to IFN-gamma and have observed several differences. Morphological changes and cell death occurred in developing cultures after 2 days in IFN-gamma, and in mature oligodendrocytes after 4-7 days. Developing oligodendrocytes underwent significantly increased apoptotic cell death in the presence of IFN-gamma, but mature oligodendrocytes exposed to IFN-gamma died of necrosis. Prior to morphological changes or cell death in mature oligodendrocytes exposed to IFN-gamma, steady-state levels of myelin-specific mRNAs and proteins were reduced. Thus, these results indicate that the sensitivity of oligodendrocytes to IFN-gamma is related to the developmental state of the cell. Such information is crucial for understanding the response of oligodendrocytes in immune-mediated demyelinating disorders and during remyelination in these diseases.     

Motion deblurring in a neural network model of retino-cortical dynamics

Simulations of a neural network model of retino-cortical dynamics (O?men H, Neural Netw 6 (1993) 245-273) are presented. The temporal-step response of the model to a single dot (spatial impulse) consists of three post-retinal phases: reset, feed-forward dominant and feedback dominant. In response to a single moving dot, the model predicts the perception of extensive blur. This extensive blur is proposed to be due to the relative spatial and temporal offsets between transient and sustained signals conveyed from retina to post-retinal levels. In response to a pair of horizontally separated dots moving in the horizontal direction, the model predicts extensive blur for the trailing dot irrespective of dot-to-dot separation. For the leading dot, the model predicts a decrease in perceived blur for long exposure durations when dot-to-dot separations are small. The reduction of perceived blur at long exposure durations for small dot-to-dot separations is proposed to stem from the spatio-temporal overlap between the transient activity generated by the trailing dot and the sustained activity generated by the leading dot. The model also predicts that targets moving at higher speeds generate more blur even when blur is normalized with respect to speed. The mechanism in the model generating this effect is a slow inhibition within the sustained channel. These predictions are compared with recent psychophysical data (Chen S, Bedell HE, O?men H, Vis Res 35 (1995) 2315-2328) and are found to be in excellent agreement. The model is used to offer a coherent explanation for several controversial findings published in the literature. This computational study shows that a model without any motion-compensation mechanism can give a good account of motion deblurring phenomenon and supplements our recent experimental study which provided evidence against motion-compensation type models in explaining the motion deblurring phenomenon (Chen S, Bedell HE, O?men H, Vis Res 35 (1995) 2315-2328).     

An anatomically constrained neural network model of fear conditioning.

Conditioning of fear reactions to an auditory conditioned stimulus (CS) paired with a footshock unconditioned stimulus/stimuli (UCS) involves CS transmission to the amygdala from the auditory thalamus, the auditory cortex, or both. This article presents a simple neural network model of this neural system. The model consists of modules of mutually inhibitory nonlinear units representing the different relevant anatomical structures of the thalamo-amygdala and thalamo-cortico-amygdala circuitry. Frequency-specific changes produced by fear conditioning were studied at the behavioral level (stimulus generalization) and the single-unit level (receptive fields). The findings mirror effects observed in conditioning studies of animals. This computational model provides an initial grounding for explorations of how emotional information and behavior are related to anatomical and physiological observations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Faces, vases, subjective contours, and the McCollough effect

A version of the face-vase pattern was constructed with the use of subject contours. The McCollough effect was viewed on this pattern and it was found that perceptual alteration (face to vase) does not weaken the strength of the effect's hues while a complete perceptual rearrangement (faces/vases to concentric rectangles) does.     

The indirect McCollough effect: an examination of an associative account

The interaction between macrophages and oxidatively modified low density lipoprotein (Ox-LDL) appears to play a central role in the development of atherosclerosis, not only through foam cell formation but also via the induction of numerous cytokines and growth factors. The current study demonstrated that Ox-LDL upregulated vascular endothelial growth factor (VEGF) mRNA expression in RAW 264 cells, a monocytic cell line, in a time- and concentration-dependent manner and that Ox-LDL stimulated VEGF protein secretion from the cells. Lysophosphatidylcholine, a component of Ox-LDL, also enhanced VEGF mRNA expression in RAW 264 cells and VEGF secretion from RAW 264 cells, with a maximal effect at a concentration of 10 micromol/L lysophosphatidylcholine. Immunohistochemical studies showed that human early atherosclerotic lesions exhibited intense VEGF immunoreactivity in subendothelial macrophage-rich regions of the thickened intima. In atherosclerotic plaques, VEGF staining was also observed in foam cell-rich regions adjacent to the lipid core or the neovascularized basal regions of plaque consisting predominantly of smooth muscle cells. High-power-field observation revealed that VEGF was localized in the extracellular space as well as at the macrophage cell surface. These observations suggest the possible involvement of Ox-LDL in the development of human atherosclerosis through VEGF induction in macrophages.     

神经网络控制系统的研究概况

本文介绍了神经网络控制系统的类型和研究概况，并对其存在的问题和发展趋势作了讨论。     

基于GA-PSO-BP神经网络的LF终点温度预测

针对LF冶炼特点和现有钢水温度预报方法存在的不足,提出了一种新的预测LF终点温度的BP神经网络模型。用遗传算法(GA)和粒子群算法(PSO)混合优化BP神经网络的权值和阈值,提高BP神经网络的预测精度。混合模型既克服了传统机理模型难以准确实现的困难,也弥补了传统BP算法的不足,结合了2种算法的优点,改善了预测模型的收敛性能。开发了基于Java语言的现场应用软件。仿真结果表明,该算法可以提高预测精度和速度,预测误差在5℃以内的炉次达到了88%。     

应用改进的神经网络模型预报转炉冶炼终点

准确预报转炉冶炼终点的钢水温度与碳含量对提高转炉终点命中率具有重要意义。针对现有多层前馈网络学习算法的不足,基于BP模型提出一种改进算法,建立了复吹转炉冶炼终点的预报模型,并与BP模型的预测结果进行了统计比较。研究表明,改进后的模型能够对冶炼终点进行良好的预报。采用单节点输出模型对终点钢水碳含量与温度分别进行预报,预测误差w(Δ[C])<±0.03%的命中率达97.22%,Δt<±12℃的命中率为94.44%。还建立了神经网络双节点输出模型对转炉终点钢水碳含量及温度同时进行预报,误差Δt<±15℃、w(Δ[C])<0.03%的双命中率为76.92%。