Multi-layer architecture for adaptive fuzzy inference system with a large number of input features

The Sugeno adaptive fuzzy neural network using training data is a good approximation to model different systems. The large number of adaptive neuro-fuzzy inference system (ANFIS) input features is a major challenge in using ANFIS and is not applicable with increased parameters. We present a solution for many input features solving modular problems; we created a multi-layer architecture of SUB-ANFIS (MLA-ANFIS) for this purpose. Different topologies were created with various combinations of multiple input features, and an error indicator was calculated for each combination of topologies. Finally, the best topology was chosen among the states with the highest possible performance. We implemented a multi-layered approach based on 365-day concrete compressive strength data with eight input features and the optimized MLA-ANFIS topology (5-3-1) for this purpose from different ANFIS topologies and neural networks. Finally, the results from five other datasets prove the impact of the proposed MLA-ANFIS approach compared to the neural network method.     

Category clustering calculator for free recall

The free recall measure is one of the most popular measures in memory research. Using this measure, researchers can assess not only the amount of recall but also the strategy participants used to recall the material. Category clustering is a strategy participants often use when the input list is categorized. Unfortunately, computing category clustering measures is laborious. The present paper introduces a calculator that computes these measures for each participant using a platform that is accessible to most researchers in an attempt to make these measures more user-friendly.     

Resource-origins of Nonmonotonicity

Formal nonmonotonic systems try to model the phenomenon that common sense reasoners are able to “jump” in their reasoning from assumptions Δ to conclusions C without their being any deductive chain from Δ to C. Such jumps are done by various mechanisms which are strongly dependent on context and knowledge of how the actual world functions. Our aim is to motivate these jump rules as inference rules designed to optimise survival in an environment with scant resources of effort and time. We begin with a general discussion and quickly move to Section 3 where we introduce five resource principles. We show that these principles lead to some well known nonmonotonic systems such as Nute’s defeasible logic. We also give several examples of practical reasoning situations to illustrate our principles. Edited by Hannes Leitgeb     

MV-Algebras and Quantum Computation

We introduce a generalization of MV algebras motivated by the investigations into the structure of quantum logical gates. After laying down the foundations of the structure theory for such quasi-MV algebras, we show that every quasi-MV algebra is embeddable into the direct product of an MV algebra and a “flat” quasi-MV algebra, and prove a completeness result w.r.t. a standard quasi-MV algebra over the complex numbers. Presented by Heinrich Wansing     

Interference by process, not content, determines semantic auditory distraction

Distraction by irrelevant background sound of visually-based cognitive tasks illustrates the vulnerability of attentional selectivity across modalities. Four experiments centred on auditory distraction during tests of memory for visually-presented semantic information. Meaningful irrelevant speech disrupted the free recall of semantic category-exemplars more than meaningless irrelevant sound (Experiment 1). This effect was exacerbated when the irrelevant speech was semantically related to the to-be-remembered material (Experiment 2). Importantly, however, these effects of meaningfulness and semantic relatedness were shown to arise only when instructions emphasized recall by category rather than by serial order (Experiments 3 and 4). The results favor a process-oriented, rather than a structural, approach to the breakdown of attentional selectivity and forgetting: performance is impaired by the similarity of process brought to bear on the relevant and irrelevant material, not the similarity in item content.     

网络旗帜广告的记忆效果

由于人们对网络旗帜广告效果的质疑,在网络广告的计费方式上也出现了两种计价模式,分别为按照浏览率和点击率来计量广告效果。其本质问题在于单纯浏览是否能够产生广告效果,以及浏览和点击各自所能带来的广告效果差异有多大。本研究利用模糊测量及相应统计方法,就上网者对网络旗帜广告的记忆效果进行测量。结果显示,在单纯浏览的情况下,上网者对网络旗帜广告已经留有印象,但这种记忆效果并不随着浏览次数的增加而显著改善;点击所能带来的广告记忆效果约为单纯浏览对应效果的1.4~1.5倍     

Extended similarity trees

Proximity data can be represented by an extended tree, which generalizes traditional trees by including marked segments that correspond to overlapping clusters. An extended tree is a graphical representation of the distinctive features model. A computer program (EXTREE) that constructs extended trees is described and applied to several sets of conceptual and perceptual proximity data.This research was supported in part by a National Science Foundation Pre-doctoral Fellowship to the first author.A magnetic tape containing both the EXTREE program described in the article and ADDTREE/P program for fitting additive trees can also be obtained from the above address. Requests for the program should be accompanied by a check for $25 made out to Teachers College, to cover the costs of the tape and postage.     

Relevance and argumentation: How bald can you get

This paper is concerned with vagueness in language, its relation to logico-philosophical questions on the one hand, and to so-called syncategorematic terms and their linguistic use on the other hand. It attempts to show that it is not language itself which is vague but rather the way we use it.