Industrial Plant for Olive Mill Wastewater from Two-Phase Treatment by Chemical Oxidation

Olive-oil production generates high and variable amounts of wastewaters from the olives and olive-oil washing (OMW), resulting to great environmental impact. These waters are normally stored in large holding ponds for evaporation during the summer. The present study examines the chemical-oxidation process using ferric chloride catalyst for the activation of H2O2 (Fenton reaction). Tests have been made on an industrial scale. The final average value of chemical oxygen demand (COD) was close to 371?mg?O2?L?1 (%CODremoval = 86%, CODinitial = 2684?mg?O2?L?1), and the water produced can be used for irrigation or can be discharged directly into the municipal wastewater system for tertiary treatment.     

A Study of Structure Evolution in Pearlitic Steel Wire at Increasing Plastic Deformation

In this work was studied the influence of the plastic deformation's intensity under deep drawing on microstructures of a pearlitic steel containing 0.8% C. Varying the levels of deformation causes diverse dislocation movements as well as modified structural states in the individual phases of the pearlitic eutectoid steel. It is shown that in the course of plastic deformation there is a reduction of interlamellar distance in a pearlite and increase in dislocation density. In some parts partial spheroidisation cementite plates is observed. The bands formed in dislocation structure are found out. The analysis of failure mechanisms of steel with pearlite structure after plastic deformation is carried out. During the deformation of pearlite, the increase in stress at the phase boundary, owing to the elastic strain incompatibility between the ferrite and cementite phases, resembles the stress concentration at grain boundaries. Pores form at the interface between the surface of the ferritic matrix and the spheroidised carbide particles. Such micro pores occur by means of plastic deformation of the ferrite's interstices around the stronger cementite owing to the reduction of the ferritic interstices and their subsequent cracking.     

Hybrid recommendations for mobile commerce based on mobile phone features

Mobile data communications have evolved as the number of third generation (3G) subscribers has increased. The evolution has triggered an increase in the use of mobile devices, such as mobile phones, to conduct mobile commerce and mobile shopping on the mobile web. There are fewer products to browse on the mobile web; hence, one‐to‐one marketing with product recommendations is important. Typical collaborative filtering (CF) recommendation systems make recommendations to potential customers based on the purchase behaviour of customers with similar preferences. However, this method may suffer from the so‐called sparsity problem, which means there may not be sufficient similar users because the user‐item rating matrix is sparse. In mobile shopping environments, the features of users' mobile phones provide different functionalities for using mobile services; thus, the features may be used to identify users with similar purchase behaviour. In this paper, we propose a mobile phone feature (MPF)‐based hybrid method to resolve the sparsity issue of the typical CF method in mobile environments. We use the features of mobile phones to identify users' characteristics and then cluster users into groups with similar interests. The hybrid method combines the MPF‐based method and a preference‐based method that uses association rule mining to extract recommendation rules from user groups and make recommendations. Our experiment results show that the proposed hybrid method performs better than other recommendation methods.     

Procedural Synthesis using Vortex Particle Method for Fluid Simulation

We propose a fast and effective technique to improve sub‐grid visual details of the grid based fluid simulation. Our method procedurally synthesizes the flow fields coming from the incompressible Navier‐Stokes solver and the vorticity fields generated by vortex particle method for sub‐grid turbulence. We are able to efficiently animate smoke which is highly turbulent and swirling with small scale details. Since this technique does not solve the linear system in high‐resolution grids, it can perform fluid simulation more rapidly. We can easily estimate the influence of turbulent and swirling effect to the fluid flow.     

Multitask bilateral learning for real‐time image enhancement

Nowadays, deep neural networks (DNNs) for image processing are becoming more complex; thus, reducing computational cost is increasingly important. This study highlights the construction of a DNN for real‐time image processing, training various image processing operators efficiently through multitask learning. For real‐time image processing, the proposed algorithm takes a joint upsampling approach through bilateral guided upsampling. For multitask learning, the overall network is based on an encoder‐decoder architecture, which consists of encoding, processing, and decoding components, in which the encoding and decoding components are shared by all the image processing operators. In the processing component, a semantic guidance map, which contains processing information for each image processing operator, is estimated using simple linear shifts of the shared deep features. Through these components, the proposed algorithm requires an increase of only 5% in the number of parameters to add another image processing operator and achieves faster and higher performance than that of deep‐learning‐based joint upsampling methods in local image processing as well as global image processing.