Early LOC Estimation of Web Apps Created Using Yii Framework by Nonlinear Regression Models

We have performed early LOC estimation of Web applications (apps) created using the Yii framework by three nonlinear regression models with three predictors based on the normalizing transformations. We used two univariate transformations (the decimal logarithm and the Box-Cox transformation) and the Box-Cox four-variate transformation for constructing nonlinear regression models. The nonlinear regression model constructed by the Box-Cox four-variate transformation has better size prediction results compared to other regression ones based on the univariate transformations.

Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

The authors consider the construction of a nonlinear multiple regression model, its confidence and prediction intervals to evaluate the efforts of mobile application development in the planning phase based on the multivariate normalizing transformation and outlier detection. The constructed model is compared to the linear regression model and nonlinear regression models based on the univariate transformations, such as the decimal logarithm, Box–Cox, and Johnson transformation. This model, in comparison with other regression models, has better prediction accuracy.

Seasonal Variations of the Depletion Factor during Recession Periods in the Senegal, Gambia and Niger Watersheds

The daily depletion factor K describes the discharge decrease of rivers only fed by groundwater in the absence of rainfall. In the Senegal, Gambia and Niger river basins in West Africa, the flow recession can exceed 6 months and the precise knowledge of K thus allows discharge forecasts to be made over several months, and is hence potentially interesting for hydraulic structure managers. Seasonal flow recession observed at 54 gauging stations in these basins from 1950 to 2016 is represented by empirical and usual conceptual models that express K. Compared to conventional conceptual models, an empirical model representing K as a polynomial of the decimal logarithm of discharge Q gives better representations of K and better discharge forecasting at horizons from 1 to 120 days for most stations. The relationship between specific discharge Qs and K, not monotonous, is highly homogeneous in some sub-basins but differs significantly between the Senegal and Gambia basins on the one hand and the Niger basin on the other. The relationship K(Q) evolves slightly between three successive periods, with values of K generally lower (meaning faster discharge decrease) in the intermediate period centered on the years 1970–1980. These climate-related interannual variations are much smaller than the seasonal variations of K.

Evidence of Temporal Postdischarge Decontamination of Bacteria by Gliding Electric Discharges: Application to Hafnia alvei

ABSTRACT This study aimed to characterize the bacterium-destroying properties of a gliding arc plasma device during electric discharges and also under temporal postdischarge conditions (i.e., when the discharge was switched off). This phenomenon was reported for the first time in the literature in the case of the plasma destruction of microorganisms. When cells of a model bacterium, Hafnia alvei, were exposed to electric discharges, followed or not followed by temporal postdischarges, the survival curves exhibited a shoulder and then log-linear decay. These destruction kinetics were modeled using GinaFiT, a freeware tool to assess microbial survival curves, and adjustment parameters were determined. The efficiency of postdischarge treatments was clearly affected by the discharge time (t*); both the shoulder length and the inactivation rate k max were linearly modified as a function of t*. Nevertheless, all conditions tested (t* ranging from 2 to 5 min) made it possible to achieve an abatement of at least 7 decimal logarithm units. Postdischarge treatment was also efficient against bacteria not subjected to direct discharge, and the disinfecting properties of “plasma-activated water” were dependent on the treatment time for the solution. Water treated with plasma for 2 min achieved a 3.7-decimal-logarithm-unit reduction in 20 min after application to cells, and abatement greater than 7 decimal logarithm units resulted from the same contact time with water activated with plasma for 10 min. These disinfecting properties were maintained during storage of activated water for 30 min. After that, they declined as the storage time increased.