Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Profiling engineered data with robust mining methods continues attracting attention in knowledge engineering systems. The purpose of this article is to propose a simple technique that deals with non-linear multi-factorial multi-characteristic screening suitable for knowledge discovery studies. The method is designed to proactively seek and quantify significant information content in engineered mini-datasets. This is achieved by deploying replicated fractional-factorial sampling schemes. Compiled multi-response data are converted to a single master-response effectuated by a series of distribution-free transformations and multi-compressed data fusions. The resulting amalgamated master response is deciphered by non-linear multi-factorial stealth stochastics intended for saturated schemes. The stealth properties of our method target processing datasets which might be overwhelmed by a lack of knowledge about the nature of reference distributions at play. Stealth features are triggered to overcome restrictions regarding the data normality conformance, the effect sparsity assumption and the inherent collapse of the ‘unexplainable error’ connotation in saturated arrays. The technique is showcased by profiling four ordinary controlling factors that influence webpage content performance by collecting data from a commercial browser monitoring service on a large scale web host. The examined effects are: (1) the number of Cascading Style Sheets files, (2) the number of JavaScript files, (3) the number of Image files, and (4) the Domain Name System Aliasing. The webpage performance level was screened against three popular characteristics: (1) the time to first visual, (2) the total loading time, and (3) the customer satisfaction. Our robust multi-response data mining technique is elucidated for a ten-replicate run study dictated by an L₉(3⁴) orthogonal array scheme where any uncontrolled noise embedded contribution has not been necessarily excluded.     

Characteristics of black carbon aerosol in Jiaxing,China during autumn 2013

We conducted measurements of black carbon（BC） aerosol in Jiaxing,China during autumn from September 26 to November 30,2013.We investigated temporal and diurnal variations of BC,and its correlations with meteorological parameters and other major pollutants.Results showed that hourly mass concentrations of BC ranged from 0.2 to 22.0 μg/m³,with an average of 5.1 μg/m³.The diurnai variation of BC exhibited a bimodal distribution,with peaks at 07:00 and 18:00.The morning peak was larger than the evening peak.The mass percentages of BC in PM_2.5 and PM₁₀ were 7.1%and 4.8%,respectively.The absorption coefficient of BC was calculated to be 44.4 Mm^-1,which accounted for 11.1%of the total aerosol extinction.BC was mainly emitted from local sources in southwestern Jiaxing where BC concentrations were generally greater than 11 μg/m³ during the measurement period.Correlation analysis indicated that the main sources of BC were motor vehicle exhaust,and domestic and industrial combustion.