Spatial bound whale optimization algorithm: an efficient high-dimensional feature selection approach

Neural Computing and Applications - Selecting a subset of candidate features is one of the important steps in the data mining process. The ultimate goal of feature selection is to select an optimal...     

Investigation of Heat‐Induced Degradation of Virgin Olive Oil Using Front Face Fluorescence Spectroscopy and Chemometric Analysis

A simple setup using a 365‐nm light‐emitting diode coupled to a USB spectrometer through an optical fiber, in a front‐face fluorescence configuration, was used to investigate the heat‐induced deterioration of virgin olive oil at different heating temperatures and times. The samples were heated for 30, 60, 120 and 180 min for every temperature setting of 140, 160 and 180 °C, respectively. Two important results are reported in this article. First, a neo‐formed compound around 665 nm due to the degradation of chlorophyll was observed. This new peak was attributed to pyropheophytins. The second result showed an important rise of the peak around 489 nm, which corresponded to the oxidation products. The correlation obtained between the peroxide value and the 489 nm peak using principal component analysis revealed the mechanism of the oxidation process. It further showed that the peak around 489 nm is a direct consequence of the degradation of hydroperoxide.     

Camera localization for a human-pose in 3D space using a single 2D human-pose image with landmarks: a multimedia social network emerging demand

Recovering a 3D human-pose in the form of an abstracted skeleton from a 2D image suffers from loss of depth information. Assuming the projected human-pose is represented by a set of 2D landmarks capturing the human-pose limbs, recovering back the original 3D locations is an ill posed problem. To recover a 3D configuration, camera localization in 3D space plays a major role, an inaccurate camera localization might mislead the recovery process. In this paper, we propose a 3D camera localization model using only human-pose appearance in a 2D image (i.e., the set of 2D landmarks). We apply a supervised multi-class logistic regression to assign the camera location in 3D space. In the learning process, we assume a set of predefined labeled camera locations. The features we train consist of relative length of limbs and 2D shape context. The goal is to build a relation between these projected landmarks and the camera location in 3D space. This kind of analysis allows us to reconstruct 3D human-poses based on the 2D projection only without any predefined camera parameters. Also, makes real-time multimedia exchange more reliable specially for human-pose related tasks. We test our model on a set of real images showing a variety of camera locations.

     

Modeling heterogeneous photocatalytic inactivation of E. coli using suspended and immobilized TiO2 reactors

A study was carried out to develop a kinetic model of the photocatalytic inactivation of Escherichia coli using different TiO₂ catalysts. The model developed is based on a reaction scheme that involves effectively coupling mass‐transfer fluxes between bacteria and catalyst surface on one hand and bacterial degradation reaction on the other. The photocatalytic results were derived from experiments led in a batch reactor under both dark and Ultra Violet (UV) irradiation conditions. Using a reference catalyst, the robustness of the developed model was tested under solar conditions. The experimental data validated the model as successfully able to reproduce evolutions in the viable bacteria concentration in the range of parameters studied without any further adjustment of the kinetic parameters. The model was used to simulate the bacterial degradation kinetics under different working conditions to describe the partitioning of both bacterial adhesion and photocatalytic reaction in the solution to be treated © 2015 American Institute of Chemical Engineers AIChE J, 61: 2532–2542, 2015     

Folksonomy link prediction based on a tripartite graph for tag recommendation

Nowadays social tagging has become a popular way to annotate, search, navigate and discover online resources, in turn leading to the sheer amount of user-generated metadata. This paper addresses the problem of recommending suitable tags during folksonomy development from a graph-based perspective. The proposed approach adapts the Katz measure, a path-ensemble based proximity measure, for the use in social tagging systems. We model a folksonomy as a weighted, undirected tripartite graph. We then apply the Katz measure to this graph, and exploit it to provide tag recommendations for individual users. We evaluate our method on two real-world folksonomies collected from CiteULike and Last.fm. The experimental results demonstrate that the proposed method improves the recommendation performance and is effective for both active taggers and cold-start taggers compared to existing algorithms.     

Oil fouling in double‐pipe heat exchanger under liquid‐liquid dispersion and the influence of copper oxide nanofluid

Dispersions of oil in water are encountered in a variety of industrial processes leading to a reduction in the performance of the heat exchangers when thermally treating such two phase fluids. This reduction is mainly due to changes in the thermal and hydrodynamical behavior of the two phase fluid. In the present work, an experimental investigation was performed to study the effects of light oil fouling on the heat transfer coefficient in a double‐pipe heat exchanger under turbulent flow conditions. The effects of different operating conditions on the fouling rate were investigated including: hot fluid Reynolds number (the dispersion), cold fluid Reynolds number, and time. The oil fouling rate was analyzed by determining the growth of fouling resistance with time and through pressure drop measurements. The influence of copper oxide (CuO) nanofluid on the fouling rate in the dispersion was also determined. It was found that the presence of dispersed oil causes a reduction in heat transfer coefficient by percentages depending on the Reynolds number of both cold and hot fluids and the concentration of oil. In addition, the time history of fouling resistance exhibited different trends with the flow rates of both fluids and its trend was influenced appreciably by the presence of CuO nanofluid.     

Effect of Cryogenic Cooling on the Heat Transfer during Turning of AZ31C Magnesium Alloy

ABSTRACT

A combined analytical and experimental study was carried out to analyze the effects of cryogenic cooling on temperature during turning of AZ31C magnesium alloy. Finite element method was employed to model and simulating the cryogenic and dry turning. Results obtained from the model were found to be in good agreement with the experimental observations. For the maximum temperature at the turned surface, the difference in the experimental and predicted value observed during dry and cryogenic turning was only 4 and 8% respectively. A significant reduction in the maximum temperature on the chip surface (around 35%) and tool surface (around 29%) was observed during the cryogenic turning compared to dry turning. This reduction in temperature was an attribute of liquid nitrogen, which produces intense cooling effect around the vicinity cutting zone where heat generation takes place hence enhancing the heat transfer. The isothermal region belonging to the highest temperature on the tool surface was also reduced by about 42%. The reduction in temperature during cryogenic conditions were found to be beneficial for the machining of magnesium alloys under safe conditions, reducing the risk of ignition and explosions, and also increases the sustainability of the process.