detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (wsns). to address the problem of outlier detection in wireless sensor networks, in this paper we present a pca-based centralized approach and a dpca-based distributed energy-efficient approach for detecting outliers in sensed data in a wsn. the outliers in sensed data can be ca...

linseed is an important oilseed and fibre crop predominantly grown in india. the aim of the present research was to evaluate genetic diversity and patterns of relationships among the 58 genotypes through 10 morphological traits and 12 polymorphic microsatellite (ssr) markers. euclidean analysis of agro-morphological traits grouped the 58 genotypes into four clusters of which cluster i was the l...

Face recognition is a significant area of pattern and computer vision research. Illumination in face obvious yet challenging task matching. Recent researchers introduced machine learning algorithms to solve illumination problems both indoor outdoor scenarios. The major challenge the lack classification accuracy. Thus, novel Optimized Neural Network Algorithm (ONNA) used aforementioned drawback....

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, intuitive accessible manner, basic principles underlying PCA its applications. Next, present a systematic, though no exclusive, survey some representative works illustrating poten...

selecting within local pomegranate accessions is the main method used to identify new cultivars. total of 76 pomegranate accessions from hatay, turkey, were collected and their morpho-pomological and chemical characteristics were determined. the results showed that there was significant diversity among the accessions in terms of fruit quality parameters. several accessions were notable for thei...

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently re...

Synchrophasor measurements can significantly enhance the monitorability of the power grid by revealing the dynamics of grid operation. However, due to high-rate samples collected in large volume, big data challenges emerge to efficiently process the data. The present work advocates robust subspace approaches including robust principal component analysis and subspace clustering, to identify low-...

The performance of principal component analysis (PCA) suffers badly in the presence of outliers. This paper proposes two novel approaches for robust PCA based on semidefinite programming. The first method, maximum mean absolute deviation rounding (MDR), seeks directions of large spread in the data while damping the effect of outliers. The second method produces a low-leverage decomposition (LLD...

background: fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. by early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. objective: here, we extract fetal ecg from maternal abdominal recordings and detect r-peaks in order to recognize fetal heart rate. on the next step, we find a b...