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Public health is one of the major concerns at the world level. Toxicology is an extremely challenging issue regarding that toxic substances are harmful to human health. In fact, toxicology studies are indispensable to evaluate the toxic effects on humans. Currently, a new evaluation technique based on the analysis of dendritic cells in vitro has been found by researchers. This analysis that remains...
Eye gaze patterns or scanpaths of subjects looking at art while answering questions related to the art have been used to decode those tasks with the use of certain classifiers and machine learning techniques. Some of these techniques require the artwork to be divided into several Areas or Regions of Interest. In this paper, two ways of clustering the static visual stimuli - k-means and the density...
Data Mining is the technique used to visualize and scrutinize the data and drive some useful information from that data so that information can be used to perform any useful work. So clustering is the one of the technique that has been proposed to be used in the area of data mining The notion behind clustering is to assigning objects to cluster based upon some customary characteristics such that object...
Epilepsy is a neurological disorder which affects persons of all age. The brain waves are studied for epilepsy detection. The Electroencephalogram (EEG) is the simplest diagnostic technique available for brain wave analysis. In this paper, we investigate the performance of KNN classifier and K-means clustering for the classification of epilepsy risk level from EEG signals. To identify the non linearity...
The corpus callosum is one of the most important structures in human brain. Most of the neurological disorders reflect directly or indirectly on the morphological features of Corpus Callosum. The mid-sagittal brain Magnetic Resonance images fully describe the anatomical structure of corpus callosum. Often considered challenging task of segmenting Corpus Callosum from Magnetic Resonance images has...
In this paper, we process the image of Chinese characters, and assess the regular of Chinese characters in the image. Images of Chinese handwritten characters is processed to remove the irrelevant information such as background color, background noise. After processing and Hough transforming the image, we can get the information of strokes and angle through the outline of the image. After Hough transforming,...
Clustering is a technique that alleviates network congestion and increase the energy efficiency of the Wireless sensor network. Hierarchical clustering and k-means clustering are well established clustering algorithms. The convergence of hierarchical clustering is only based on the inconsistency criterion while the k-means clustering requires the number of clusters (k) which are user defined. It is...
This paper presents an innovative idea for the classification of individual drivers. The classification is based on each driver's driving features like, ratio of indicators to turns, number of brakes, number of time horn used, average gear, average speed, maximum speed and gear. K-means and hierarchical clustering is used to separate out the slow, normal and fast driving styles based on recorded data...
Wide availability of electronic data has led to the vast interest in text analysis, information retrieval and text categorization methods. To provide a better service, there is a need for non-English based document analysis and categorizing systems, as is currently available for English text documents. This study is mainly focused on categorizing Indic language documents. The main techniques examined...
This paper proposes a method to cluster documents of variable length. The main idea is to apply (a) automatic identification of 1, 2, and 3 grams (To reduce the dependency on huge background vocabulary support or learning or complex probabilistic approach), (b) order them by some measure of relevance, which is developed with the help of Tf-Idf and Term-Weighting approach, and finally (c) use them...
The methods to select supply chain partners for a corporation is very important, especially for the complicated supply chain network with hundreds of members and multilevel structure , and the increasingly developing of evaluation criteria. According to the situation, we propose RVPK algorithm based on PSO (particle swarm optimization) and k-means clustering. The method is applied on clustering of...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
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