Theoretically-Efficient and Practical Parallel DBSCAN

The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for DBSCAN in Euclidean space that take $O(n\log n)$ work for two dimensions, sub-quadratic work for three or more dimensions, and can be computed approximately in linear work for any constant number of dimensions. However, existing parallel DBSCAN algorithms require quadratic work in the worst case, making them inefficient for large datasets. This paper bridges the gap between theory and practice of parallel DBSCAN by presenting new parallel algorithms for Euclidean exact DBSCAN and approximate DBSCAN that match the work bounds of their sequential counterparts, and are highly parallel (polylogarithmic depth). We present implementations of our algorithms along with optimizations that improve their practical performance. We perform a comprehensive experimental evaluation of our algorithms on a variety of datasets and parameter settings. Our experiments on a 36-core machine with hyper-threading show that we outperform existing parallel DBSCAN implementations by up to several orders of magnitude, and achieve speedups by up to 33x over the best sequential algorithms

Preconcentration of some trace elements via using multiwalled carbon nanotubes as solid phase extraction adsorbent

in present study preconcentration followed by solid phase extraction of heavy metal ions, Cu(II), Co(B), Ni(II) and Pb(II) using a multiwalled carbon nanotubes (MWNTs) and complexing reagent o-cresolphthalein complexone were investigated. The effects of parameters, including pH of the solutions, amounts of complexing reagent, eluent type, sample volume, flow rates of solution, and matrix ions, were examined for the optimum recoveries of the analyte ions. The preconcentration factor was 40. Detection limit (3s) obtained for the investigated metals in the optimal conditions were observed in the range of 1.64-5.68 mu g l(-1). The validation of the presented method was obtained by the analysis of certified reference material HR 1 (Humber river sediment), the obtained results were agreed with certified values. The optimum experimental conditions that ensure the efficiency of the procedure have been investigated and have been successfully applied to the determination of trace elements in environmental samples with satisfactory results. (C) 2009 Elsevier B.V. All rights reserved

Accelerating Hepatitis C virus elimination in Egypt by 2030: A national survey of communication for behavioral development as a modelling study.

Aim of the workThis study aimed at assessing the dominance of risk practices associated with HCV endemicity in Egypt and detecting the behavioral development level concerning different aspects of HCV risk behaviors with respect to age and gender. The survey highlights the most cost-effective strategies that could accelerate HCV elimination in Egypt.Subjects and methodsA national household survey targeted 3780 individuals (age range: 10-85 years). The sample was a systematic probability proportionate to size from 6 governorates representing the six major subdivisions of Egypt. The indicators used for assessing the behavioral development level towards HCV included six domains: awareness (7 indicators), perceived risk (5 indicators), motivation with the intention to change (4 and 5 indicators for males and females respectively), trial, rejection or adoption (6 and 5 indicators for males and females respectively).ResultsThe study revealed that along the continuum of behavior development, the percentage of the participants who acquired half of the scores was as follows: 73.1% aware, 69.8% developed perceived risk, 80.6% motivated with only 28.9% adopting the recommended behaviors, 32% rejected them, 2.3% were in the trial stage versus 35.8% who did not try any. Adolescents had significantly lower levels of development for almost all domains when compared to adults. Statistical higher significance was detected in favor of adults, employees, married, Lower Egypt governorates, and university-educated participants (pConclusionEgypt would be closer to HCV elimination when cost-effective strategies are directed not towards creating awareness, perceived risk or motivation to change- (at an acceptable level)- but towards motivating adopting risk-reduction behaviors for HCV, tackling misconceptions and reinforcement of social support

A robust fuzzy k-means clustering model for interval valued data

Fuzzy k-means, Robust clustering, Interval valued data, Noise center, Noise radius, Noise cluster,