Essentially, motive behind using control system is to generate suitable control signal for yielding desired response of a physical process. Control of synchronous generator has always remained very critical in power system operation and control. For certain well known reasons power generators are normally operated well below their steady state stability limit. This raises demand for efficient a...

Reliability of software counts on its fault-prone modules. This means that the less software consists of fault-prone units the more we may trust it. Therefore, if we are able to predict the number of fault-prone modules of software, it will be possible to judge the software reliability. In predicting software fault-prone modules, one of the contributing features is software metric by which one ...

This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, t...

this paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. this system can be used in multiple places. for example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver from falling asleep. this system is composed of three parts: (1) mechanical, (2) electrical and (3) image processing system. a...

with the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. one of the major problems in text classification relates to the high dimensional feature spaces. therefore, the main goal of text classification is to reduce the dimensionality of features space. there are many feature selection methods. however...

bivariate features, obtained from multichannel electroencephalogram (eeg) recordings, quantify the relation between different brain regions. studies based on bivariate features have shown optimistic results for tackling epileptic seizure prediction problem in patients suffering from refractory epilepsy. a new bivariate approach using univariate features is proposed here. differences and ratios ...

Multidimensional data is often feature space heterogeneous so that individual features have unequal importance in different sub areas of the feature space. This motivates to search for a technique that provides a strategic splitting of the instance space being able to identify the best subset of features for each instance to be classified. Our technique applies the wrapper approach where a clas...

High dimensionality and class imbalance are two main problems that affect the quality of training datasets in software defect prediction, resulting in inefficient classification models. Feature selection and data sampling are often used to overcome these problems. Feature selection is a process of choosing the most important attributes from the original data set. Data sampling alters the data s...

Sungtak Kim et al. 89 We consider the feature recombination technique in a multiband approach to speaker identification and verification. To overcome the ineffectiveness of conventional feature recombination in broadband noisy environments, we propose a new subband feature recombination which uses subband likelihoods and a subband reliable-feature selection technique with an adaptive noise mode...

Feature selection is an important technique for dimension reduction in machine learning and pattern recognition communities. Feature evaluation functions play essential roles in constructing feature selection algorithms. This paper introduces a new notion of knowledge granularity, called conditional knowledge granularity, reflecting relationship between conditional attributes and decision attri...