Multi-response optimization of process parameters for remediation of tetrachloroethylene pools by surfactants: Application of Taguchi design of experiment and Artificial Neural Network

Within the scope of the study, the effectiveness of the experimental conditions was tested by performing a multi-response Taguchi experimental design for the optimization of the minimum cost remediation performance with Tween 80, Methyl beta cyclodextrine (MCD) and Sodium dodecyl sulfate (SDS) from tetrachloroethylene (PCE) contaminated porous media. Tween 80, MCD and SDS were extensively used in cosmetic industry as emulsifier. Both time of remediation and cost of remediation were studied as two separate response variables in three replicate experiments conducted according to the Taguchi L9 orthogonal experimental design. In the multi-response Taguchi analysis, the sensitivity analysis was performed by systematically changing the weights determined for two separate response variables in the calculation of total loss of quality (TNQLj). Optimum experimental conditions were determined with the help of the calculated multi-response signal/noise (S/N) ratios (MRSN). The results show that the type of Flushing Agent is the most important factor in optimizing the remediation time and remediation cost for the removal of dense non-aqueous phase liquid (DNAPL) PCE mass. Flushing rate is considered to be the least contributing factor. Furthermore, the results of the analysis of variance (ANOVA) showed that all parameters used in the system had a significant effect on the experimental results and the Taguchi method could explain 97.15% of the Remediation Time and 92.03% of the Remediation Cost. Afterwards, the data obtained from the experiments performed according to the experimental design were modelled using Artificial Neural Network (ANN) to estimate the remediation performance and remediation cost without performing new experiments.     

Optimization of electrochemical treatment of industrial paint wastewater with response surface methodology

The electrochemical oxidation of water-based paint wastewater was investigated batch-wise in the presence of NaCl electrolyte with carbon electrodes for the first time in literature. The electrochemical treatment conditions were optimized using response surface methodology where potential difference, reaction temperature and electrolyte concentration were to be minimized while chemical oxygen demand (COD), color and turbidity removal percents and initial COD removal rate were maximized at 100% pollution load. The optimum conditions were satisfied at 35 g/L external electrolyte concentration, 30 degrees C reaction temperature and 8 V potential difference (64.37 mA/cm(2) current density) realizing 51.8% COD and complete color and turbidity removals, and 3010.74 mg/Lh initial COD removal rate. According to these results, the electrochemical method could be a strong alterative to conventional physicochemical methods for the treatment of water-based paint wastewater.     

Application of neural networks to heuristic scheduling algorithms

This paper considers the use of artificial neural networks (ANNs) to model six different heuristic algorithms applied to the n job, m machine real flowshop scheduling problem with the objective of minimizing makespan. The objective is to obtain six ANN models to be used for the prediction of the completion times for each job processed on each machine and to introduce the fuzziness of scheduling information into flowshop scheduling. Fuzzy membership functions are generated for completion, job waiting and machine idle times. Different methods are proposed to obtain the fuzzy parameters. To model the functional relation between the input and output variables, multilayered feedforward networks (MFNs) trained with error backpropagation learning rule are used. The trained network is able to apply the learnt relationship to new problems. In this paper, an implementation alternative to the existing heuristic algorithms is provided. Once the network is trained adequately, it can provide an outcome (solution) faster than conventional iterative methods by its generalizing property. The results obtained from the study can be extended to solve the scheduling problems in the area of manufacturing.     

Automatic Feature Selection of Hardware Layout: A Step toward Robust Hardware Trojan Detection

Recently, the problem of hardware Trojan detection has gained a tangible significance in academia and industry. That problem, by its nature, is complex, time consuming and error prone due to design and fabrication outsourcing of hardware circuits to external untrusted foundries. Researchers have proposed different approaches, either destructive or non-destructive, to overcome that problem. The destructive approach depends on reverse engineering via decapsulation, delayering and layout identification. This paper presents a first trial of a new approach that can afford an automatic and robust solution for the step of layout identification. The proposed technique takes the underlying digital circuit as input, and automatically determines its basic features using Haar feature extractor. Based on that features, a decision tree is trained to act as a weak classifier, which is later boosted, by making use of AdaBoost learning algorithm, to produce a strong classifier in a chain of cascaded classifiers. Accordingly, a classification model is built up to provide an automatic hardware Trojan location and detection tool. To evaluate the proposed model, ISCAS89 benchmark dataset was used for training and testing. The hardware dataset has been altered deliberately to show different Trojan examples –namely, Trojan insertion, Trojan deletion and Trojan parametric- inside hardware circuits. By investigating the underlying experimental results, the capabilities of the proposed model are evaluated, and the evaluation shows that the approach can detect different hardware Trojan types in different circuit layouts, with high accuracy rate. The proposed approach is not only automatic, but also robust and promising.     

DC Magnetic Properties of the Ho doped ZnO Compounds

In this work, we report on the DC magnetic properties of Ho doped ZnO, Zn_0.8?4x Ho _x O _y (0.05≤x≤0.10), polycrystalline samples prepared by the so-called solid state reaction method. Magnetic measurements, M–H and M–T, done by using a PPMS magnetometer, show a paramagnetic behavior including indirect antiferromagnetic coupling between some Ho³⁺ magnetic moments. In other words, the negative values of the Curie–Weiss temperatures, θ, for the polycrystalline samples with six different Ho concentrations indicate that there is an effective antiferromagnetic coupling among the magnetic moments of Ho³⁺ ions. However, the decrease in the magnitude of θ with increasing x indicates that this coupling decreases with increasing amount of Ho in the compounds. Furthermore, the effective magnetic moments, μ _eff, per Ho atom calculated from the 1/χ?T curves gradually increase with increasing concentration. Therefore, the trends of the magnitudes of θ, and μ _eff values clearly indicate that apart from the antiferromagnetic coupling there is also an increasing contribution of a ferromagnetic coupling with increasing x. Hence, one may also conclude that the compounds studied seem to have a kind of spin-glass behavior.     

The influence of polyaniline (PANI) coating on corrosion behaviour of zinc–cobalt coated carbon steel electrode

Zinc–cobalt alloy plating (ZnCo) was successfully deposited on carbon steel (CS) applying current of 2 mA with galvanostatic technique. Polyaniline film (PANI) was synthesized with cyclic voltammetry technique from 0.20 M aniline containing 0.20 M sodium tartrate solution on zinc–cobalt plated carbon steel (CS/ZnCo) electrode. PANI film characterized by scanning electron microscopy (SEM), was covered with a dark green-brown homopolymer film of strongly adherent homogeneous characteristic while the other one was plated with a porous light ZnCo one. The corrosion behaviour of zinc–cobalt deposited carbon steel electrodes with and without polyaniline (PANI) film in 3.5% NaCl solution was investigated with AC impedance spectroscopy (EIS) technique and anodic polarization curves. The results showed that PANI coating led to decrease of the permeability of metallic plating. The PANI homopolymer film provided an effective barrier property on zinc–cobalt coating and a remarkable anodic protection to substrate for longer exposure time.     

Empyema thoracis--a series of 230 cases

A retrospective analysis of 230 cases of empyema thoracis which occurred in our clinic during the last 14 years have been presented. The causes, the pathogen organism, treatment with antibiotic are enumerated. The surgical treatment carried in resistant cases have been described Ten patients (4.34 percent) died due to respiratory failure and septic shock. Importance of early and appropriate treatment has been stressed.     

Electrochemical treatment of Baker's yeast wastewater containing melanoidin: optimization through response surface methodology

Effluents from Baker's yeast production plant contain a high percentage of color and a large amount of organic load. In the present study, Baker's yeast wastewater (BYW) is treated with the electrocoagulation (EC) process using Al electrodes. Operating parameters (pH, current density, color intensity and operating time) are optimized by response surface methodology (RSM). Quadratic models are developed for the responses which are removal efficiencies of color, chemical oxygen demand (COD) and total organic carbon (TOC) and operating cost (OC). Optimum operating parameters and responses are determined as initial pH 5.2, current density of 61.3 A/m(2) and operation time of 33 min, and 71% of color, 24% of COD, 24% of TOC removal efficiencies and OC of 0.869 €/m(3), respectively. The quadratic model fits for all responses very well with R(2) (>0.95). This paper clearly shows that RSM is able to optimize the operating parameters to maximize the color, COD and TOC removal efficiencies and minimize the OC.     

Super-resolution reconstruction of faces by enhanced global models of shape and texture

We present a computationally efficient method for the super-resolution reconstruction of face images from their low-resolution versions. It is based on generative models and utilizes both the shape and texture components together. The main idea is that the image details can be synthesized by global modeling of accurately aligned local image regions. In order to achieve sufficient accuracy in alignment, shape reconstruction is considered as a separate problem and solved together with texture reconstruction in a coordinated manner. Meanwhile, the statistical dependency between the shape and texture components is also considered. Moreover, different from traditional model-based super-resolution methods, we use a corrected form of the degradation operator with the aligned images. We show that when the degradation is used with the aligned texture components as is, it causes bias in the reconstructions. To overcome this problem, we reflect the same processing performed in alignment onto the degradation operator and use this corrected version in texture reconstruction. Experimental results show that the proposed solution provides superior image reconstructions (both qualitatively and quantitatively) in a faster way.     

Continuous electrochemical treatment of phenolic wastewater in a tubular reactor

The electrochemical treatment of phenolic wastewater in a continuous tubular reactor, constructed from a stainless steel tube with a cylindrical carbon anode at the centre, was investigated in this study, being first in literature. The effects of residence time on phenol removal was studied at 25 degrees C, 120 g l(-1) electrolyte concentration for 450 and 3100 mg l(-1) phenol feed concentrations with 61.4 and 54.7 mA cm(-2) current densities, respectively. The change in phenol concentration and pH of the reaction medium was monitored in every run and GC/MS analyses were performed to determine the fate of intermediate products formed during the electrochemical reaction in a specified batch run. During the electrolysis mono, di- and tri-substituted chlorinated phenol products were initially formed and consumed along with phenol thereafter mainly by polymerization mechanism. For 10 and 20 min of residence time phenol removal was 56% and 78%, respectively, with 450 mg l(-1) phenol feed concentration and above 40 min of residence time all phenol was consumed within the column. For 1, 1.5, 2 and 3h of residence time, phenol removal achieved was 42%, 71%, 81% and 98%, respectively, at 3100 mg l(-1) phenol feed concentration. It is noteworthy that more than 95% of the initial phenol was converted into a non-passivating polymer without hazardous end products in a comparatively fast and energy-efficient process, being a safe treatment.