Hierarchical intelligent control with flexible AC transmission systems application

A novel hierarchical intelligent controller configuration is proposed using an artificial neural network as a control-mode classifier in the supervisory level and a set of pre-designed controllers in the lower level. Controller outputs are modified nonlinearly by the classifying signals in a structure resembling one artificial neuron with adaptively changed weights. The lower-level local controllers are implemented using neural networks. An illustrative example of this approach is based on the transient stabilization of a single-machine infinite-bus system studied in Flexible AC Transmission Systems (FACTS) research.     

Distinguished Scientific Awards for an Early Career Contribution to Psychology.

The Early Career Awards recognize the large number of excellent young psychologists. Recipients of this award may not have held a PhD for more than nine years. The areas considered in 1991 were animal learning and behavior, developmental, and personality. The winners for 1991 were Kent C. Berridge, Susan A. Gelman, and Randy J. Larsen. For each winner a citation, biography, and selected bibliography of their works are presented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Neural Network Feedback Control: Work at UTA’s Automation and Robotics Research Institute

This is an outline of research in neural networks for feedback control done since the mid 1990s at the Automation and Robotics Research Institute (ARRI) of The University of Texas at Arlington (UTA). It shows how the developments of Intelligent Control Systems based on neural networks have followed three main generations. This statement provides a short, broad-brush perspective on the development of intelligent neural feedback controllers.     

A Genetic Dissociation of Learning and Recall in Caenorhabditis elegans.

A learning event can be dissociated into 3 components: acquisition, storage, and recall. When the laboratory wild-type strain of Caenorhabditis elegans (N2 strain) is exposed to benzaldehyde in the absence of food, the worms display a reduction of their attractive response to this volatile odorant. This results from the association between benzaldehyde and a nutrient-deficient environment. Another wild-type isolate, the CB4856 strain, fails to display this decreased response to benzaldehyde after exposure to benzaldehyde in the absence of food. However, like the N2 strain, when tested to isoamyl alcohol after benzaldehyde conditioning, the CB4856 strain displays a decreased isoamyl alcohol response. Therefore, the CB4856 strain does not have an acquisition deficit, but it suffers from a recall deficit specific to benzaldehyde. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Pure perceptual-based sequence learning.

Learning a sequence of target locations when the sequence is uncorrelated with a sequence of responses and target location is not the response dimension (pure perceptual-based sequence learning) was examined. Using probabilistic sequences of target locations, the author shows that such learning can be implicit, is unaffected by distance between target locations, and is mostly limited to first-order transition probabilities. Moreover, the mechanism underlying learning affords processing of information at anticipated target locations and appears to be attention based. Implications for hypotheses of implicit sequence learning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

垦东地区上第三系馆陶组上段成藏规律研究

通过对山东垦东地区构造特征，地层特征和储层特征的研究，从油气运聚，储盖组合，油藏类型及分布和油气控制因素等方面对馆陶组上段成藏规律进行了综合分析，研究表明，研究区的储层主要为曲流河沉积砂体，原油来源于周边的4个生油凹陷，通过不整合曲，储集层以及断层运移到垦东地区后聚集成藏。     

Vero细胞在微载体上迁移和多层生长现象

本文通过对电子显微镜观察了Ｖｅｒｏ细胞有微载体增减过程中的迁移民政部发现在不同增减阶段，Ｖｒｏ细胞迁移方式不同；在分泌形成的细胞外基质，上，Ｖｅｒｏ细胞迁移是通过 层粘连蛋白介导进行的，被层粘连蛋白抗体抑制；这种迁移导致Ｖｅｒｏ细胞在微载体上形成多层生长现象。     

Learning and Revising User Profiles: The Identification of Interesting Web Sites

We discuss algorithms for learning and revising user profiles that can determine which World Wide Web sites on a given topic would be interesting to a user. We describe the use of a naive Bayesian classifier for this task, and demonstrate that it can incrementally learn profiles from user feedback on the interestingness of Web sites. Furthermore, the Bayesian classifier may easily be extended to revise user provided profiles. In an experimental evaluation we compare the Bayesian classifier to computationally more intensive alternatives, and show that it performs at least as well as these approaches throughout a range of different domains. In addition, we empirically analyze the effects of providing the classifier with background knowledge in form of user defined profiles and examine the use of lexical knowledge for feature selection. We find that both approaches can substantially increase the prediction accuracy.     

Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system

This paper describes how SWoRD (scaffolded writing and rewriting in the discipline), a web-based reciprocal peer review system, supports writing practice, particularly for large content courses in which writing is considered critical but not feasibly included. To help students gain content knowledge as well as writing and reviewing skills, SWoRD supports the whole cycle of writing, reviews, back-reviews, and rewriting by scaffolding the journal publication process as its authentic practice model. In addition, SWoRD includes algorithms that compute individual reviewer’s review accuracy, which is in turn used to support the various drawbacks of reciprocal peer reviews (e.g., variation in motivation or ability of reviewers). Finally, this paper describes an empirical evaluation showing that the SWoRD approach is effective in improving writing quality in content classes.