A novel fuzzy clustering algorithm for the analysis of axillary lymph node tissue sections

Recently Fourier Transform Infrared (FTIR) spectroscopic imaging has been used as a tool to detect the changes in cellular composition that may reflect the onset of a disease. This approach has been investigated as a mean of monitoring the change of the biochemical composition of cells and providing a diagnostic tool for various human cancers and other diseases. The discrimination between different types of tissue based upon spectroscopic data is often achieved using various multivariate clustering techniques. However, the number of clusters is a common unknown feature for the clustering methods, such as hierarchical cluster analysis, k-means and fuzzy c-means. In this study, we apply a FCM based clustering algorithm to obtain the best number of clusters as given by the minimum validity index value. This often results in an excessive number of clusters being created due to the complexity of this biochemical system. A novel method to automatically merge clusters was developed to try to address this problem. Three lymph node tissue sections were examined to evaluate our new method. These results showed that this approach can merge the clusters which have similar biochemistry. Consequently, the overall algorithm automatically identifies clusters that accurately match the main tissue types that are independently determined by the clinician.     

Hybrid Approach for Addressing Uncertainty in Risk Assessments

Parameter uncertainty is a major aspect of the model-based estimation of the risk of human exposure to pollutants. The Monte Carlo method, which applies probability theory to address model parameter uncertainty, relies on a statistical representation of available information. In recent years, other uncertainty theories have been proposed as alternative approaches to address model parameter uncertainty in situations where available information is insufficient to identify statistically representative probability distributions, due in particular to data scarcity. The simplest such theory is possibility theory, which uses so-called fuzzy numbers to represent model parameter uncertainty. In practice, it may occur that certain model parameters can be reasonably represented by probability distributions, because there are sufficient data available to substantiate such distributions by statistical analysis, while others are better represented by fuzzy numbers (due to data scarcity). The question then arises as to how these two modes of representation of model parameter uncertainty can be combined for the purpose of estimating the risk of exposure. This paper proposes an approach (termed a hybrid approach) which combines Monte Carlo random sampling of probability distribution functions with fuzzy calculus. The approach is applied to a real case of estimation of human exposure, via vegetable consumption, to cadmium present in the surficial soils of an industrial site located in the north of France. The application illustrates the potential of the proposed approach, which allows the uncertainty affecting model parameters to be represented in a way that is consistent with the information at hand. Also, because the hybrid approach takes advantage of the “rich” information provided by probability distributions, while retaining the conservative character of fuzzy calculus, it is believed to hold value in terms of a “reasonable” application of the precautionary principle.     

Global Level Path Planning for Mobile Robots in Dynamic Environments

This paper presents a self-adapting approach to global level path planning in dynamic environments. The aim of this work is to minimize risk and delays in possible applications of mobile robots (e.g., in industrial processes). We introduce a hybrid system that uses case-based reasoning as well as grid-based maps for decision-making. Maps are used to suggest several alternative paths between specific start and goal point. The casebase stores these solutions and remembers their characteristics. Environment representation and casebase design are discussed. To solve the problem of exploration vs. exploitation, a decision-making strategy is proposed that is based on the irreversibility of decisions. Forgetting strategies are discussed and evaluated in the context of case-based maintenance. The adaptability of the system is evaluated in a domain based on real sensor data with simulated occupancy probabilities. Forgetting strategies and decision-making strategies are evaluated in simulated environments. Experiments show that a robot is able to adapt in dynamic environments and can learn to use paths that are less risky to follow.     

SECANT-FUZZY LINEAR REGRESSION METHOD FOR HARMONIC COMPONENTS ESTIMATION IN A POWER SYSTEM

In order to avoid unnecessary damage of electrical equipments and installations,high quality power should be delivered to the end user and strict control on frequency should be made, Therefore, it is important to estimate the power system's harmonic components with higher accuracy. This paper presents a new approach for estimating harmonic component in a power system using secant - fuzzy linear regression method. In this approach the non - sinusoidal voltage or current waveform is written as I linear function. The coefficient of this function is assumed to be fuzzy number with a membership function that has center and spread value. The time dependent quantity is written as Taylor series with two different time dependent quantities. The objective is to use the sample obtained from the transmission line to find the power system harmonic components and frequencies. We used an experimental voltage signal from a sub power station as a numerical test.     

Biases in Social Comparative Judgments: The Role of Nonmotivated Factors in Above-Average and Comparative-Optimism Effects.

Biases in social comparative judgments, such as those illustrated by above-average and comparative-optimism effects, are often regarded as products of motivated reasoning (e.g., self-enhancement). These effects, however, can also be produced by information-processing limitations or aspects of judgment processes that are not necessarily biased by motivational factors. In this article, the authors briefly review motivational accounts of biased comparative judgments, introduce a 3-stage model for understanding how people make comparative judgments, and then describe how various nonmotivational factors can influence the 3 stages of the comparative judgment process. Finally, the authors discuss several unresolved issues highlighted by their analysis, such as the interrelation between motivated and nonmotivated sources of bias and the influence of nonmotivated sources of bias on behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Bluetooth Routing Protocol Using Evolving Fuzzy Neural Networks

In this paper, a routing protocol which utilizes the characteristics of Bluetooth technology is proposed for Bluetooth-based mobile ad hoc networks. The routing tables are maintained in the master devices and the routing zone radius for each table is adjusted dynamically by using evolving fuzzy neural networks. Observing there exists some useless routing packets which are helpless to build the routing path and increase the network loads in the existing ad hoc routing protocols, we selectively use multiple unicasts or one broadcast when the destination device is out of the routing zone radius coverage of the routing table. The simulation results show that the dynamic adjustment of the routing table size in each master device results in much less reply time of routing request, fewer request packets and useless packets compared with two representative protocols, Zone Routing Protocol and Dynamic Source Routing.     

Reasoning, Integration, Inference Alteration, and Text Comprehension.

This paper reports how the study of formal logical reasoning provides insight into more everyday types of reasoning, such as that involved in language comprehension. Both of these types of cognition are thought to involve the use of mental models, and so it is reasonable to think that the cognitive operations needed for formal logical reasoning would be involved in everyday reasoning as well. We focused on three aspects of formal reasoning: (a) the integration of information into a common mental model, (b) the drawing of inferences, and (c) the coordination of alternative possibilities. We were able to show that the integration and inference components were related to narrative comprehension processes, but the coordination of alternative models was not. Thus, there is evidence for some overlap in the mental processes used in formal and everyday reasoning. This further justifies the study of formal logical reasoning as a window into certain types of everyday reasoning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The effects of case libraries on problem solving

Abstract The purpose of the study was to investigate the effects of providing access to a case library of related stories while undergraduates solved ill-structured problems. While solving complex food product development problems, the experimental group accessed experts' stories of similar, previously solved problems; the comparable group accessed fact sheets (expository representation of stories' content); and the control group accessed text selected at random from a textbook dealing with issues unrelated to the stories. On multiple-choice questions assessing processes related to problem solving (prediction, inferences, explanations, etc.), experimental students out-performed the comparable and control groups. Performance on short-answer questions also assessing problem-related skills was not significantly different, in part because of test fatigue. Analysis of interviews identified a number of factors that students used in deciding how to apply their study strategies, including causal factors, grounding phenomenon, grounding in context, and outcomes.     

Hemispheric contributions to nonverbal abstract reasoning and problem solving.

Hemispheric involvement in reasoning abilities has been debated for some time, and it remains unclear whether the right hemisphere's involvement in problem solving is modality specific or dependent on the type of spatial reasoning required. In the current study, 2 types of nonverbal reasoning abilities were examined, spatial reasoning and proportional reasoning, in 109 patients with cerebrovascular disease that was confined to either the right or the left hemisphere or was diffuse in nature. Results indicated that no lateralizing effects were present based on type of spatial reasoning. Findings are consistent with the suggestion that higher order cognitive processes involved in nonverbal abstraction and problem solving are not strongly lateralized to the right hemisphere but rather are more generally distributed throughout the cortex. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

激光微焊接质量的模糊识别技术研究

讨论了激光微焊点焊接质量的模糊识别的概念，数学模型及其应用方法，并介绍了系统的硬件组成。