The impact of the Hebbian learning rule on research in behavioural neuroscience.

Hebb's principal theoretical propositions, the cell assembly and the nature of synaptic change, were generated at a time when the focus of work in behavioural neuroscience was directed at understanding issues such as the principles governing the behaviour of animals in neuropsychological studies of learning and memory and the role of drives in the control of behaviours like sex and feeding and drinking. It was not until attention shifted to understanding the neural underpinnings of learning and memory that Hebb's propositions had an impact on behavioural neuroscience as they provided a simple, and testable, mechanism for synaptic plasticity observed both in learning and in other forms of experience-dependent neural change. But much of the field remains interested in other issues such as sensation and perception, motivation, attention, and so on, and to date, Hebb's propositions have had little impact. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A multi-criterion interaction-oriented model with proportional rule for designing supply chain networks

Supply chain management has offered a way to improve the industrial environment becomes more competitive. While, the commonly seen methodologies may be effective in solving the production–distribution problem only from supplier- or customer-oriented consideration, those cannot present the interactive relationship between upstream and downstream enterprises. In the competitive semiconductor industry environment, considering the viewpoints of the supplier and consumer simultaneously is particularly required, because multiple manufacturing and demanding steps are performed at separate situations, concurrently. In this paper, we propose an interaction-oriented approach, which bases on the analytic hierarchy process (AHP) methodology and proportional rule, to solve the semiconductor distribution problem with multiple quantitative and qualitative criteria. The developed approach gives an expected satisfaction for the all participators of the whole chain while the cooperative information is shared perfectly and effectively. Analysis results demonstrate the proposed methodology is efficient and effective through a real world case study.     

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.     

上马水库地裂缝成因及工程处理措施探讨

文中着重阐述了上马水库库坝区的地裂缝产生的原因及发育规律,分析了地裂缝对水库的直接危害,为水库除险加固设计提供了指导,并提出了切实可行的工程处理措施建议。     

缺陷交互作用对陶瓷半导体导电性能的影响

本文借助于缺陷化学反应过程，分析了陶瓷半导体内缺陷间的交互作用，得到了陶瓷半导体实验研究的三个重要启示：（1）强还原（或氧化）或施主（或受主）掺杂对同一样品不能同时起到最佳效果；（2）本征原子空位对施主或受主的补偿导致电导率的非线性增长；（3）缺陷的缔合降低了半导化杂质的有效浓度，从而使电导性能发生异常变化。     

用面向对象编程实现问题求解自动化

本文从面向对象方法基本原理和面向对象编程的技术特征出发，阐明所建应用软件系统中的对象，类及相应类层次结构和类组合结构，使系统具有很强的表现真空世界复杂系统结构的能力，系统通过消息传递在程序执行中实现对操作的调用机制，使之在面向用户问题选择和执行求解策略方面有很强的适应性，这一点对于强调人－机交互和解题协作的智能决策支持系统设计至关重要，文章给出了用Ｃ＋＋实现的模型对象系统及消息传递机制。     

逻辑与数据库技术概论

本文对二十余年来人们在逻辑与数据库相结合领域所作的工作进行了归纳总结,并把它们区分为三类:理论和完全关系结构方法,纯理论方法以及理论和不完全关系结构方法。本文简要介绍了这三种方法的基本思想和关键技术,并讨论了它们各自的特点和适用范围。     

基于间接关联规则的数据挖掘算法研究

简单数据集可以通过关联规则得到在数据间的相互关系;相当多的情况下,由于不能从关联规则得到隐藏在数据间的相互关系,需要按间接关联规则分析出数据项集在交易集合中出现的频度,挖掘隐藏在数据间的相互关系。文中通过使用概念分层和基于近邻的方法,探讨利用FP树产生的频繁项集,对候选关联检验其是否满足项对支持度条件,并利用这个频繁项集挖掘事务的间接关联,找到挖掘事务的间接关联的内在规律,构造出不依赖中介条件的间接关联挖掘算法。     

A new DSmT combination rule in open frame of discernment and its application

A new combination rule based on Dezert-Smarandache theory (DSmT) is proposed to deal with the conflict evidence resulting from the non-exhaustivity of the discernment frame. A two-dimensional measure factor in Dempster-Shafer theory (DST) is extended to DSmT to judge the conflict degree between evidence. The original DSmT combination rule or new DSmT combination rule can be selected for fusion according to this degree. Finally, some examples in simultaneous fault diagnosis of motor rotor are given to illustrate the effectiveness of the proposed combination rule.     

最小支持度在教学质量评价系统中的数据挖掘应用

以当前的高职高专院校教育教学为平台,研究分析最小支持度关联规则挖掘技术与教学质量评价相结合的问题,针对教学质量评价结果中的盲目性、不易把握等问题,提出利用最小支持度来分析质量评价体系,获取以影响因素为条件,以评价分析为结论的关联规则来解决目前教学质量评价中的不合理性,使教学质量评价公平、公正、合理、高效,并给教学管理人员提供决策分析资料。