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Indirect immunofluorescence (IIF) with HEp-2 cells has been used to detect antinuclear auto-antibodies (ANA) for diagnosing systemic autoimmune diseases. The aim of this study is to develop an automatic scheme to identify the fluorescence pattern of HEp-2 cell in the IIF images. By using the previously proposed two-staged segmentation method, the similarity-based watershed algorithm with marker techniques...
Monitoring driver fatigue, inattention, drowsiness and alertness is very important in order to prevent vehicular accidents. The system detecting and monitoring should be noninvasive type and non-distracting to the driver. The physiological parameters such as skin conductance, oximetry pulse, respiration, SPO2 and BVP can lead to the acceptable solution to the problem. The author is working on the...
MicroRNAs (miRNAs) have been found in diverse organisms and play critical role in gene expression regulations of many essential cellular processes. Discovery of miRNAs and identification of their target genes are fundamental to the study of such regulatory circuits. To distinguish the real pre-miRNA from other stem loop hairpins with similar stem loop (pseudo pre-miRNA) is an important task in molecular...
Though DNA microarray technology simultaneously measures the expression levels of thousands of genes, only a few underlying gene features may account for significant data variation in gene classification problems. Selection of features from huge data set is difficult and so dimension reduction of gene expression data set is essential in order to determining important features, which play key role...
The land use or land cover map depicts the physical coverage of the Earth's terrestrial surface according to its use (viz. vegetation, habitation, water body, bare soil, artificial structures etc.). Land use map generation from remotely sensed images is one of the challenging task of remote sensing technology. In this article, motivated from group forming behaviour of real ants, we have proposed two...
In the last years, the area of Multicriteria Decision Analysis (MCDA) has brought about new methods to cope with classification problems, among which those based on the concept of prototypes. These refer to specific alternatives (samples) of the training dataset that are good representatives of the groups they fit in. In this paper, experiments are conducted over two prototype selection (PS) techniques...
Combining classifiers are nowadays one of the most promising direction in pattern recognition. There are many methods of decision making which could be used by the ensemble of classifiers. The most popular are methods that have their origin in voting, where the decision of the common classifier is a combination of individual classifiers' outputs, i.e. classifiers' responses (class numbers) or values...
Extracting classification rules from data is an important task of data mining and is gaining considerable attention in recent years. This paper comprises classification of different types of rule extraction algorithm and their comparative study by considering their advantages separately. These Ant Colony based algorithms called as Ant_Miner have been successfully implemented in various fields such...
This work proposes characterization of single-length cycle cellular automata (CA) attractors with the target to model this class of CA for designing efficient pattern recognizer. Identification of essential properties of a CA while forming multi-length cycles provides the basis of such characterization. A scheme has been developed that synthesizes the single-length cycle attractor CA, avoiding multi-length...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
Early work has demonstrated that conserve self pattern recognition algorithm (CSPRA) produces promising performance in the field of anomaly detection. This paper further extends the applications of CSPRA to Fisher's Iris data, Indian Telugu data and Wisconsin breast cancer data. A formal description of the differences between the two detection strategies (classical CSPRA and selective CSPRA) is given...
In this paper we propose a simple scalable genetic programming multi-class ensemble classifier of higher accuracy. A formula is derived to obtain the maximum number of nodes permitted in a GP classifier. A wrapper approach for feature selection mechanism based on GP classifier is adopted in our work.
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
Packet classification is one of the most critical techniques in many network devices such as firewall, IDS and IPS, etc. In order to meet the performance requirement for high speed Internet (even higher than 10 Gbps), practical algorithms must keep better spatial and temporal performance. Moreover, as the size of rule set is increasing to tens of thousands, novel packet classification algorithms must...
All sections of the society need to benefit from the strides in Information Technology, more so the differently enabled. This paper presents a Novel solution for a text read out OCR system adapted for the visually challenged. A paper of text from Malayalam magazines, newspapers, books or journals placed on a flatbed scanner would be recognized and read out as text. Selected text could also be printed...
When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing. Grid applications such as astronomy, chemistry,...
Three term backpropagation (BP) network as proposed by Zweiri in 2003 has outperformed standard two term backpropagation. However, further studies on three term backpropagation in 2007 indicated that this network only surpassed standard BP for small scale datasets but not for medium and large scale datasets. It has also been observed that by using mean square error (MSE) as a cost function in three...
Data classification is a prime task in data mining. Accurate and simple data classification task can help the clustering of large dataset appropriately. In this paper we have experimented and suggested a simple ANN based classification models called as minimal ANN (MANN) for different classification problems. The GA is used for optimally finding out the number of neurons in the single hidden layered...
In this paper, we propose a framework of multi-genre movie recommender system based on neuro-fuzzy decision tree (NFDT) methodology. The system is capable of recommending list of movies in descending order of preference in response to user queries and profiles. The system also takes care of attempt to vote stuffing using novel application of fuzzy c-means clustering algorithm. Typical user query and...
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