Gait based gender identification has received a great attention from researchers in the last decade due to its potential in different applications. This will help a human identification system to focus only on the identified gender related features, which can improve search speed and efficiency of the retrieval system by limiting the subsequent searching space into either a male database or fem...

In this paper, we present a practical identification approach of video fragment for digital video files. Before analyzing the video content, we must decode it based on its encoding format first. In order to effectively identify the format of a fragment, a format classification is performed before the format identification. The methods of format classification and identification are discriminati...

In this paper we present survey on various classification techniques which can be used for plant leaf classification. A classification problem deals with associating a given input pattern with one of the distinct classes. Plant leaf classification is a technique where leaf is classified based on its different morphological features. There are various successful classification techniques like kN...

This paper proposes a new approach of using nonlinear technique, two-dimensional empirical mode decomposition (2DEMD) and PCA plus LDA for facial emotion recognition. The EMD is a non-parametric data-driven analysis tools which decomposes any nonlinear and non-stationary signals into a number of intrinsic mode functions (IMFs). In this work we used the 2DEMD which is the extension of one dimens...

This paper highlights the significance of classification in data mining and knowledge discovery. In this paper we investigate the performance of various data mining classification algorithms viz. Rnd Tree, Quinlan decision tree algorithm (C4.5), KNearest Neighbor algorithm etc., on a large dataset from the „Wisconsin Breast tissue dataset‟ (derived from the UCI Machine Learning Repository) that...

Automatic Digital signal type classification (ADSTC) has many important applications in both of the civilian and military domains. Most of the proposed classifiers can only recognize a few types of digital signals. This paper presents a novel technique that deals with the classification of multi-user chirp modulation signals. In this paper, the peak of the bispectrum and its bi-frequencies are ...

Data Mining is used for various purposes in many applications like industries, medical etc. This is used for extracting the useful information from the huge amount of data set. Health monitoring is also used the data mining concept for predict the diagnosis of the diseases. In health monitoring diabetes is the common health problem nowadays, which affects peoples. There are various data mining ...

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for knearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, discriminant analysis via support vectors (SVDA), is proposed. First, the SVM is employed to compute an optimal direction to discriminant each two classes. Then, the criteria of class separability is constructed...

Protein phosphorylation is a crucial regulatory mechanism in various organisms. With recent improvements in mass spectrometry, phosphorylation site data are rapidly accumulating. Despite this wealth of data, computational prediction of phosphorylation sites remains a challenging task. This is particularly true in plants, due to the limited information on substrate specificities of protein kinas...

Recent technological advances in sensors, low-power microelectronics and miniaturization and wireless networking have enabled the design and proliferation of wireless body sensor networks capable of autonomously monitoring and controlling environments. One of the most promising problems existing in this network is efficient data transmission with optimized resource utilization. This paper handl...