Application of principal component-artificial neural network models for simultaneous determination of phenolic compounds by a kinetic spectrophotometric method

A multicomponent analysis method based on principal component analysis-artificial neural network models (PC-ANN) is proposed for the determination of phenolic compounds. The method relies on the oxidative coupling of phenols (phenol, 2 chlorophenol, 3-chlorophenol and 4-chlorophenol) to N,N-diethyl-p-phenylenediamine in the presence of hexacyanoferrate(III). The reaction monitored at analytical wavelength 680 nm of the dye formed. Phenols can be determined individually over the concentration range 0.1-7.0 microg ml(-1). Differences in the kinetic behavior of the four species were exploited by using PC-ANN, to resolve mixtures of phenol. After reducing the number of kinetic data using principal component analysis, an artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. The optimized ANN allows the simultaneous quantitation of four analytes in mixtures with relative standard errors of prediction in the region of 5% for four species. The results show that PC-ANN is an efficient method for prediction of the four analytes.     

A parameter-varying filtered PID strategy for air–fuel ratio control of spark ignition engines

In this paper, a new synthesis method is presented to control air–fuel ratio (AFR) in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The major challenge in the control of AFR is the time-varying delay in the control loop which restricts the application of conventional control techniques. In this paper, the time-varying delay in the system dynamics is first approximated by Padé approximation to render the system dynamics into non-minimum phase characteristics with time-varying parameters. Application of parameter-varying dynamic compensators is invoked to retrieve unstable internal dynamics. The associated error dynamics is then utilized to construct a filtered PID controller combined with a parameter-varying dynamic compensator to track the desired AFR command using the feedback from the universal exhaust gas oxygen sensor. The proposed method achieves desired dynamic properties independent of the matched disturbances. It also accommodates the unmatched perturbations due to the dynamic compensator features. The results of applying the proposed method to experimental numerical data demonstrate the closed-loop system stability and performance against time-varying delay, canister purge disturbances and measurement noise for both port fuel injection engines and lean-burn engines.     

Influence of ultrasonic parameters on degradation of acrylic acid/acrylamide copolymer based superabsorbent hydrogels cross-linked with NMBA

Continuous exposure to high-energy ultrasonic waves depolymerizes macromolecules in solutions and produces a permanent reduction in viscosity. Different factors affect the efficiency of this process. In this study, ultrasonic degradation of one commercially important hydrogel based on acrylic acid and acrylamide cross-linked with N,N-methylenebisacrylamide (NMBA) was carried out in aqueous solution at room temperature (25?°C). The purpose of this study was to present new experimental data for this ultrasonic degradation. In this respect, the effect of sonication parameters (power and pulse) on the rate of degradation was investigated. Granule disintegration was determined using a method to measure the swelling power of hydrogel. A method of viscometry was used to study the degradation behavior of the hydrogel and a first-order kinetic equation was employed to calculate the degradation rate constants. The experimental results indicated that the rate of ultrasonic degradation increased with increasing ultrasonic power and pulse. FTIR and UV spectrometry measurements confirmed that the degradation proceeded by mechanical forces. A detailed degradation mechanism has been proposed including chain scission. The present study has enabled us to understand the role of the ultrasonic parameters in deciding the extent of viscosity reduction in hydrogel systems.     

Multi-Objective Optimization of aluminum hollow tubes for vehicle crash energy absorption using a genetic algorithm and neural networks

A numerical study of the crushing of thin-walled circular aluminum tubes has been carried out to investigate their behaviors under axial impact loading. These kinds of tubes are usually used in automobile and train structures to absorb the impact energy. A Multi-Objective Optimization of circular aluminum tubes undergoing axial compressive loading for vehicle crash energy absorption is performed for five crushing parameters using the weighted summation method. To improve the accuracy of the optimization process, artificial neural networks are used to reproduce the behavior of the crushing parameters in crush dynamics conditions. An explicit finite element method (FEM) is used to model and analyzed the behavior. A series of aluminum cylindrical tubes are simulated under axial impact condition for the experimental validation of the numerical solutions. A finite element code, capable of evaluating parameters crush, is prepared of which the outputs are used for training and testing the developed neural networks. In order to find the optimal solution, a genetic algorithm is implemented. With the purpose of illustrating optimum dimensional ratios, numerical results are presented for thin-walled circular aluminum AA6060-T5 and AA6060-T4 tubes. Multi-Objective Optimization of circular aluminum tubes has been performed in the basis of different priorities to create the ability for designer to select the optimum dimension ratio. Also, crush parameters of two aluminum alloys has been compared.     

A multi-purpose digital image watermarking using fractal block coding

In this paper, a new multi-purpose watermarking technique is presented which satisfies both verification and authentication purposes simultaneously by embedding a binary watermark into the image. The proposed method uses a special type of fractal block coding with a local search region with contrast scaling and mean of range block as its parameters. It also utilizes Fuzzy C-Mean clustering to specify the watermark bits. To overcome the high computational complexity of fractal coding, a new simple coding method is also presented which improves the robustness of the watermarking and decreases the run time of fractal block coding in the watermarking procedure. To measure the fragility and robustness of the method to signal distortions such as JPEG compression, median filter, and additive noise, some experiments were employed. The experimental results showed that the proposed method has provided a sensitive authentication and a reliable verification.     

PONTO—An instrument for imaging with polarized neutrons

An imaging instrument dedicated to radiography and tomography with polarized cold neutrons was installed and successfully tested at the BER II reactor at Helmholtz Zentrum Berlin. The spatial resolution for un-polarized neutrons was less than 85 μm for a point-to-detector distance of 5 mm, in the case of polarized neutrons it was less than 300 μm. With these resolutions, details of magnetic fields in different lead samples below the critical temperature being in the Meissner phase and magnetic flux pinning could be imaged.     

Lateral resistance of joints made with various screws in commercial wood plastic composites

In this study, the effects of screw diameter, pilot hole diameter, end distance, thickness of side and main members, loading speed and screw type on the lateral resistance of screw joints in commercial wood plastic composites were investigated and also compared with those calculated using the European Yield Model (EYM). The results have shown that for a given diameter of screw, increase in end distance, thickness of joint members, pilot hole diameter and loading speed, increases lateral resistance of the joint. Comparing screw effect it was found that lateral resistances of joints made with various screws did not have significant differences. The results have also shown that the accuracy of EYM prediction of lateral resistance for the joints fractured in mode I_s is better than those fractured in modes III_s or V.     

Internal structure of the electrodeposited nanocrystalline Al–Mg alloy dendrites

Porous nanocrystalline supersaturated face centered cubic (fcc)-Al(Mg) dendrites with globular morphology were produced via electrodeposition. The cross-section of the globules revealed compact–disperse–compact structure along the growth direction. Initially compact globules formed due to high potential (or current density) which decreased eventually resulting in disperse-entity growth. Overlapping spherical diffusion zone formation over the disperse-entities was attributed as a reason for the compact growth at later stages. The internal structure of the globules was explained by the global potential (E)–time curve and the estimated local current densities ahead of deposit front. A growth mechanism for globular morphology was proposed using the results presented.