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BRAINovations
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Authors:
Manoj
Kumar Jain
Abstract:
Quite often the variables used in system analysis are qualitative in nature. They cannot be defined precisely, whereas software development for system analysis needs a mathematical framework with precise computations. It is not trivial to capture the uncertainty in the system.
Fuzzy sets provide us the facility to capture the uncertainty in the system. In normal crisp set where the membership of an element is always certain in a sense that it would be member or not of the given set. In contrast to this a membership functions or possibility (ranging from 0 to 1, including both values) is assigned with each member. System analysis is done through system dynamics which is not very efficient. We present an efficient technique to generate expert system using fuzzy set. In our proposed approach five linguistic qualifiers are used for each variable, namely, Very Low (VL), Low (L), Medium (M), High (H), and Very High
(VH). We capture the influence or feedback in the system with the help of if then else rules and matrices are generated for them which are used for analysis. Complete methodology and its applicability are presented here.
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Authors:
M.
Anitha
, P.
Tamije Selvy
Abstract:
Settings White Matter lesions (WMLs) are small areas of dead cells found in parts of the brain. In general, it is difficult for medical experts to accurately quantify the WMLs due to decreased contrast between White Matter (WM) and Grey Matter (GM). The aim of this paper is to
automatically detect the White Matter Lesions which is present in the brains of elderly people. WML detection process includes the following stages: 1. Image preprocessing, 2. Clustering (Fuzzy c-means clustering, Geostatistical Possibilistic clustering and Geostatistical Fuzzy clustering) and 3.Optimization using Particle Swarm Optimization (PSO). The proposed system is tested on a database of 208 MRI images. GFCM yields high sensitivity of 89%, specificity of 94% and overall accuracy of 93% over FCM and GPC. The clustered brain images are then subjected to Particle Swarm Optimization (PSO). The optimized result obtained from GFCM-PSO provides sensitivity of 90%, specificity of 94% and accuracy of 95%. The detection results reveals that GFCM and GFCMPSO better localizes the large regions of lesions and gives less false positive rate when compared to GPC and GPC-PSO which captures the largest loads of WMLs only in the upper ventral horns of the brain.
BRAINStorming
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Authors:
Doru
Anastasiu Popescu
, Maria
Catrinel Dănăuță
Abstract:
In this paper, we are trying to introduce a method of selection of some web pages from a web application, which will be verified by using different validating mechanisms. The number of selected web pages cannot be higher than a previously established constant. The method of selection of these web pages must assure the highest possible quality of the verification of the entire application. The error detection of these web pages will automatically lead to the error detection in other pages. This fact will be realised by using an equivalence relation among the web pages of the web application.
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Authors:
Laleh
Fakhraee Faruji
Abstract:
Memory is not a single faculty but is a combination of multiple distinct abilities (Schacter, 1987). The declarative-procedural distinction is used both with regard to knowledge and memory that stores this knowledge. Ellis (2008) used the terms explicit/implicit, and declarative/procedural interchangeably. In this article the researcher aims at identifying the different aspects of declarative/procedural memory, interaction between these two types of memory, and the role they may play in second language acquisition.
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Authors:
Parviz
Birjandi
, Somayyeh
Sabah
Abstract:
In recent times, there has been a growing interest in analyzing the relationship between language and thought from a variety of points of view to explore whether language comes before thought or thought precedes language. Accordingly, the present paper attempts at mulling over the current debates on this issue, including Chomsky’s (1975, 1983) Independent Theory, the Sapir-Whorf hypothesis (1956), Piaget’s Cognitive Determinism (1952, as cited in, Chaput, 2001), Vygotsky’s (1978, 1986) Theory of Interchanging Roles, O’brien and Opie’s (2002) Radical Connectionism, and Slobin’s (1987, 1991, 2003) Thinking for Speaking Hypothesis, which recently have received a great amount of attention, among other positions. Then the pedagogical implications of the Thinking for Speaking Hypothesis for Second Language Acquisition (SLA) are presented.
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Authors:
Sumit
Goyal
, Gyanendra
Kumar Goyal
Abstract:
This paper presents the capability of Time–delay artificial neural network models for predicting shelf life of processed cheese. Datasets were divided into two subsets (30 for training and 6 for validation). Models with single and multi layers were developed and compared with each other. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash -
Sutcliffo Coefficient were used as performance evaluators, Time- delay model predicted the shelf life of processed cheese as 28.25 days, which is very close to experimental shelf life of 30 days.
Lecture BRAINotes
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Authors:
Angel
Garrido
Abstract:
The problems of uncertainty, imprecision and vagueness have been discussed for many years. These problems have been major topics in philosophical circles with much debate, in particular, about the nature of vagueness and the ability of traditional Boolean logic to cope with concepts and perceptions that are imprecise or vague. The Fuzzy Logic (which is usually translated into Castilian by “Lógica Borrosa”, or “Lógica Difusa”, but also by “Lógica Heurística”) can be considered a bypass-valued logics (Multi-valued Logic, MVL, its acronym in English). It is founded on, and is closely related to-Fuzzy Sets Theory, and successfully applied on Fuzzy Systems. You might think that fuzzy logic is quite recent and what has worked for a short time, but its origins date back at least to the Greek philosophers and especially Plato (428-347 B.C.). It even seems plausible
to trace their origins in China and India. Because it seems that they were the first to consider that all things need not be of a certain type or quit, but there are a stopover between. That is, be the pioneers in considering that there may be varying degrees of truth and falsehood. In case of colors, for example, between white and black there is a whole infinite scale: the shades of gray. Some recent theorems show that in principle fuzzy logic can be used to model any continuous system, be it based
in AI, or physics, or biology, or economics, etc. Investigators in many fields may find that fuzzy, commonsense models are more useful, and many more accurate than are standard mathematical ones. We analyze here the history and development of this problem: Fuzziness, or “Borrosidad” (in Castilian), essential to work with Uncertainty.
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