Experimental Study of the Extraction of Copper(II) from Sulphuric Acid by Means of Sodium Diethyldithiocarbamate (SDDT)

The present work presents the extraction of copper(II) from sulphuric acid solutions with Sodium diethyldithiocarbamate (SDDT), and six different organic diluents: Dichloromethane, Chloroform, Carbon tetrachloride, Toluene, xylene and Cyclohexane, were tested. The pair SDDT/Chloroform showed to be the most selective in removing the copper cations, and hence was considered throughout the experimental study. The effects of operating parameters such as the initial concentration of the extracting agent, the agitation time, the agitation speed and the acid concentration were considered. For an initial concentration of Cu (II) of 63 ppm in a 0.5 M sulphuric acid solution, both with a mass of the extracting agent of 20 mg, an extraction percentage of about 97.8 % and a distribution coefficient of 44.42 were obtained, respectively, confirming the performance of the SDDT-Chloroform pair.

A Hydro-Mechanical Model for Unsaturated Soils

The hydro-mechanical model for unsaturated soils has been presented based on the effective stress principle taking into account effects of drying-wetting process. The elasto-plastic constitutive equations for stress-strain relations of the soil skeleton have been established. A plasticity model is modified from modified Cam-Clay model. The hardening rule has been established by considering the isotropic consolidation paths. The effect of dryingwetting process is introduced through the ¤ç parameter. All model coefficients are identified in terms of measurable parameters. The simulations from the proposed model are compared with the experimental results. The model calibration was performed to extract the model parameter from the experimental results. Good agreement between the results predicted using proposed model and the experimental results was obtained.

Preconditioned Jacobi Method for Fuzzy Linear Systems

A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.

Fast Algorithm of Shot Cut Detection

In this paper we present a novel method, which reduces the computational complexity of abrupt cut detection. We have proposed fast algorithm, where the similarity of frames within defined step is evaluated instead of comparing successive frames. Based on the results of simulation on large video collection, the proposed fast algorithm is able to achieve 80% reduction of needed frames comparisons compared to actually used methods without the shot cut detection accuracy degradation.

Vibration Analysis of the Gas Turbine Considering Dependency of Stiffness and Damping on Frequency

In this paper the complete rotor system including elastic shaft with distributed mass, allowing for the effects of oil film in bearings. Also, flexibility of foundation is modeled. As a whole this article is a relatively complete research in modeling and vibration analysis of rotor considering gyroscopic effect, damping, dependency of stiffness and damping coefficients on frequency and solving the vibration equations including these parameters. On the basis of finite element method and utilizing four element types including element of shaft, disk, bearing and foundation and using MATLAB, a computer program is written. So the responses in several cases and considering different effects are obtained. Then the results are compared with each other, with exact solutions and results of other papers.

Effects of Annealing Treatment on Optical Properties of Anatase TiO2 Thin Films

In this investigation, anatase TiO2 thin films were grown by radio frequency magnetron sputtering on glass substrates at a high sputtering pressure and room temperature. The anatase films were then annealed at 300-600 °C in air for a period of 1 hour. To examine the structure and morphology of the films, X-ray diffraction (XRD) and atomic force microscopy (AFM) methods were used respectively. From X-ray diffraction patterns of the TiO2 films, it was found that the as-deposited film showed some differences compared with the annealed films and the intensities of the peaks of the crystalline phase increased with the increase of annealing temperature. From AFM images, the distinct variations in the morphology of the thin films were also observed. The optical constants were characterized using the transmission spectra of the films obtained by UV-VIS-IR spectrophotometer. Besides, optical thickness of the film deposited at room temperature was calculated and cross-checked by taking a cross-sectional image through SEM. The optical band gaps were evaluated through Tauc model. It was observed that TiO2 films produced at room temperatures exhibited high visible transmittance and transmittance decreased slightly with the increase of annealing temperatures. The films were found to be crystalline having anatase phase. The refractive index of the films was found from 2.31-2.35 in the visible range. The extinction coefficient was nearly zero in the visible range and was found to increase with annealing temperature. The allowed indirect optical band gap of the films was estimated to be in the range from 3.39 to 3.42 eV which showed a small variation. The allowed direct band gap was found to increase from 3.67 to 3.72 eV. The porosity was also found to decrease at a higher annealing temperature making the film compact and dense.

EML-Estimation of Multivariate t Copulas with Heuristic Optimization

In recent years, copulas have become very popular in financial research and actuarial science as they are more flexible in modelling the co-movements and relationships of risk factors as compared to the conventional linear correlation coefficient by Pearson. However, a precise estimation of the copula parameters is vital in order to correctly capture the (possibly nonlinear) dependence structure and joint tail events. In this study, we employ two optimization heuristics, namely Differential Evolution and Threshold Accepting to tackle the parameter estimation of multivariate t distribution models in the EML approach. Since the evolutionary optimizer does not rely on gradient search, the EML approach can be applied to estimation of more complicated copula models such as high-dimensional copulas. Our experimental study shows that the proposed method provides more robust and more accurate estimates as compared to the IFM approach.

Hydrodynamic Characteristics of Weis–Fogh Type Ship-s Propulsion Mechanism Having Elastic Wing

This experiment was conducted in attempt of improving hydrodynamic efficiency of the propulsion mechanism by installing a spring to the wing so that the opening angle of the wing in one stroke can be changed automatically, compared to the existing method of fixed maximum opening angle in Weis-Fogh type ship propulsion mechanism. Average thrust coefficient was almost fixed with all velocity ratio with the prototype, but with the spring type, thrust coefficient increased sharply as velocity ratio increased. Average propulsive efficiency was larger with bigger opening angle in the prototype, but in the spring type, the one with smaller spring coefficient had larger value. In the range over 1.0 in velocity ratio where big thrust can be generated, spring type had more than twice of propulsive efficiency increase compared to the prototype.

Spatial Correlation Analysis between Climate Factors and Plant Production in Asia

Using 1km grid datasets representing monthly mean precipitation, monthly mean temperature, and dry matter production (DMP), we considered the regional plant production ability in Southeast and South Asia, and also employed pixel-by-pixel correlation analysis to assess the intensity of relation between climate factors and plant production. While annual DMP in South Asia was approximately less than 2,000kg, the one in most part of Southeast Asia exceeded 2,500 - 3,000kg. It suggested that plant production in Southeast Asia was superior to South Asia, however, Rain-Use Efficiency (RUE) representing dry matter production per 1mm precipitation showed that inland of Indochina Peninsula and India were higher than islands in Southeast Asia. By the results of correlation analysis between climate factors and DMP, while the area in most parts of Indochina Peninsula indicated negative correlation coefficients between DMP and precipitation or temperature, the area in Malay Peninsula and islands showed negative correlation to precipitation and positive one to temperature, and most part of India dominating South Asia showed positive to precipitation and negative to temperature. In addition, the areas where the correlation coefficients exceeded |0.8| were regarded as “susceptible" to climate factors, and the areas smaller than |0.2| were “insusceptible". By following the discrimination, the map implying expected impacts by climate change was provided.

A Robust Watermarking using Blind Source Separation

In this paper, we present a robust and secure algorithm for watermarking, the watermark is first transformed into the frequency domain using the discrete wavelet transform (DWT). Then the entire DWT coefficient except the LL (Band) discarded, these coefficients are permuted and encrypted by specific mixing. The encrypted coefficients are inserted into the most significant spectral components of the stego-image using a chaotic system. This technique makes our watermark non-vulnerable to the attack (like compression, and geometric distortion) of an active intruder, or due to noise in the transmission link.

Cost Based Warranty Optimisation Using Genetic Algorithm

Warranty is a powerful marketing tool for the manufacturer and a good protection for both the manufacturer and the customer. However, warranty always involves additional costs to the manufacturer, which depend on product reliability characteristics and warranty parameters. This paper presents an approach to optimisation of warranty parameters for known product failure distribution to reduce the warranty costs to the manufacturer while retaining the promotional function of the warranty. Combination free replacement and pro-rata warranty policy is chosen as a model and the length of free replacement period and pro-rata policy period are varied, as well as the coefficients that define the pro-rata cost function. Multiparametric warranty optimisation is done by using genetic algorithm. Obtained results are guideline for the manufacturer to choose the warranty policy that minimises the costs and maximises the profit.

Estimation of Time -Varying Linear Regression with Unknown Time -Volatility via Continuous Generalization of the Akaike Information Criterion

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

A Novel Machining Signal Filtering Technique: Z-notch Filter

A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Application of CFD for Air Flow Analysis underneath Natural Ventilation with Forced Convection in Roof Attic

In research on natural ventilation, and passive cooling with forced convection, is essential to know how heat flows in a solid object and the pattern of temperature distribution on their surfaces, and eventually how air flows through and convects heat from the surfaces of steel under roof. This paper presents some results from running the computational fluid dynamic program (CFD) by comparison between natural ventilation and forced convection within roof attic that is received directly from solar radiation. The CFD program for modeling air flow inside roof attic has been modified to allow as two cases. First case, the analysis under natural ventilation, is closed area in roof attic and second case, the analysis under forced convection, is opened area in roof attic. These extend of all cases to available predictions of variations such as temperature, pressure, and mass flow rate distributions in each case within roof attic. The comparison shows that this CFD program is an effective model for predicting air flow of temperature and heat transfer coefficient distribution within roof attic. The result shows that forced convection can help to reduce heat transfer through roof attic and an around area of steel core has temperature inner zone lower than natural ventilation type. The different temperature on the steel core of roof attic of two cases was 10-15 oK.

Hybrid Method Using Wavelets and Predictive Method for Compression of Speech Signal

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

Approximate Range-Sum Queries over Data Cubes Using Cosine Transform

In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells- values. The cosine transform is known to have a good energy compaction property and thus can approximate data distribution functions easily with small number of coefficients. The derived estimator is accurate and easy to update. We perform experiments to compare its performance with a well-known technique - the (Haar) wavelet. The experimental results show that the cosine transform performs much better than the wavelet in estimation accuracy, speed, space efficiency, and update easiness.

Increasing The Speed of Convergence of an Artificial Neural Network based ARMA Coefficients Determination Technique

In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination.

Studding of Number of Dataset on Precision of Estimated Saturated Hydraulic Conductivity

Saturated hydraulic conductivity of Soil is an important property in processes involving water and solute flow in soils. Saturated hydraulic conductivity of soil is difficult to measure and can be highly variable, requiring a large number of replicate samples. In this study, 60 sets of soil samples were collected at Saqhez region of Kurdistan province-IRAN. The statistics such as Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Bias Error (MBE) and Mean Absolute Error (MAE) were used to evaluation the multiple linear regression models varied with number of dataset. In this study the multiple linear regression models were evaluated when only percentage of sand, silt, and clay content (SSC) were used as inputs, and when SSC and bulk density, Bd, (SSC+Bd) were used as inputs. The R, RMSE, MBE and MAE values of the 50 dataset for method (SSC), were calculated 0.925, 15.29, -1.03 and 12.51 and for method (SSC+Bd), were calculated 0.927, 15.28,-1.11 and 12.92, respectively, for relationship obtained from multiple linear regressions on data. Also the R, RMSE, MBE and MAE values of the 10 dataset for method (SSC), were calculated 0.725, 19.62, - 9.87 and 18.91 and for method (SSC+Bd), were calculated 0.618, 24.69, -17.37 and 22.16, respectively, which shows when number of dataset increase, precision of estimated saturated hydraulic conductivity, increases.

Spectral Analysis of Speech: A New Technique

ICA which is generally used for blind source separation problem has been tested for feature extraction in Speech recognition system to replace the phoneme based approach of MFCC. Applying the Cepstral coefficients generated to ICA as preprocessing has developed a new signal processing approach. This gives much better results against MFCC and ICA separately, both for word and speaker recognition. The mixing matrix A is different before and after MFCC as expected. As Mel is a nonlinear scale. However, cepstrals generated from Linear Predictive Coefficient being independent prove to be the right candidate for ICA. Matlab is the tool used for all comparisons. The database used is samples of ISOLET.

Flexural Strength and Ductility Improvement of NSC beams

In order to calculate the flexural strength of normal-strength concrete (NSC) beams, the nonlinear actual concrete stress distribution within the compression zone is normally replaced by an equivalent rectangular stress block, with two coefficients of α and β to regulate the intensity and depth of the equivalent stress respectively. For NSC beams design, α and β are usually assumed constant as 0.85 and 0.80 in reinforced concrete (RC) codes. From an earlier investigation of the authors, α is not a constant but significantly affected by flexural strain gradient, and increases with the increasing of strain gradient till a maximum value. It indicates that larger concrete stress can be developed in flexure than that stipulated by design codes. As an extension and application of the authors- previous study, the modified equivalent concrete stress block is used here to produce a series of design charts showing the maximum design limits of flexural strength and ductility of singly- and doubly- NSC beams, through which both strength and ductility design limits are improved by taking into account strain gradient effect.