The Influence of Surfactant on the Surface Characterization of Celestite in Spherical Oil Agglomeration

This study investigates the relationship between the critical surface tension of wetting of celestite and agglomeration recovery as well as the zeta potential in dependence of pH and amount of collector (Na‐Oleate). For this purpose, effects of pH and collector amount on the agglomeration recovery are investigated and zeta potential measurements and Fourier Transform Infrared Spectrophotometer (FTIR) analyses are carried out to determine the adsorption type of Na‐Oleate on celestite surface. The sessile drop technique is used for the measurement of contact angle and determination of the critical surface tension of wetting (Y_C) of celestite. The maximum agglomeration recovery is obtained at pH 7. The critical surface tension of wetting of celestite is very close to the surface tension of kerosene, which is 25.95 mN/m. Furthermore, at the optimum Na‐Oleate amount of 10 kg/ton, the critical surface tension of wetting of celestite is approximately equal to the surface tension of kerosene.     

A combo technology of autotrophic and heterotrophic denitrification processes for groundwater treatment

In this study,a sequential process (heterotrophic up-flow column and completely mixed membrane bioreactors) was proposed combining advantages of the both processes.The system was operated for 249 days with simulated and real groundwater for nitrate removal at concentrations varying from 25 to 145 mg·L-1 NO3-N.The contribution of heterotrophic process to total nitrate removal in the system was controlled by dozing the ethanol considering the nitrate concentration.By this way,sulfur based autotrophic denitrification rate was decreased and the effluent sulfate concentrations were controlled.The alkalinity requirement in the autotrophic process was produced in the heterotrophic reactor,and the system was operated without alkalinity supplementation.Throughout the study,the chemical oxygen demand in the heterotrophic reactor effluent was (23.7 ± 22) mg·L-1 and it was further decreased to(7.5 ± 7.2) mg·L-1 in the system effluent,corresponding to a 70％ reduction.In the last period of the study,the real groundwater containing 145 mg·L-1 NO3-N was completely removed.Membrane was operated without chemical washing in the first 114 days.Between days 115-249 weekly chemical washing was required.     

Investigation of kinetics of agglomerate growth in oil agglomeration process

In this study, the kinetics of agglomerate growth in a batch oil agglomeration process has been studied using bituminous coal. The effect of operating variables such as kerosene concentration, pulp density and speed of agitation on the agglomeration process was investigated. It has been found that the second-order kinetic equation describes the growth of agglomerates adequately. The growth of the agglomerates in the oil agglomeration process shows a self-preserving growth. Using this, a characteristic curve has been developed. For the prediction of the size distribution of the agglomerates, the d₅₀ values of the agglomerates must be known. Therefore, a model has been developed by using the kinetic equation for estimation of d₅₀ values of agglomerates for this coal. It was shown that the size distribution of the agglomerates for any levels of the process variables studied can be predicted using the equation of characteristic curve and d₅₀ values. Knowledge obtained from this study will be helpful for technological advancement of this kind of study.     

Application of the Box-Wilson experimental design method for the spherical oil agglomeration of coal

In this study, the Box-Wilson statistical experimental design method was employed to evaluate the effects of important variables such as bridging liquid (oil) concentration, salt (CaCl₂·2H₂O) concentration and stirring speed on the agglomeration of bituminous coal. Response function coefficients were determined by the regression analysis of experimental data and the predictions were found to be in good agreement with the experimental results. The optimum kerosene concentration, CaCl₂·2H₂O concentration and stirring speed were determined as 30 wt%, 1 M and 1683 rpm, respectively, when considering combustible recovery and ash content.In addition, contact angle and solution surface tension measurements were carried out to evaluate of agglomeration success with the contact angle values and surface tension values. The surface tension of CaCl₂ 2H₂O solutions and the average contact angle increased with increasing CaCl₂·2H₂O concentration.     

Removal of Cd(II), Hg(II), and Pb(II) ions from aqueous solution using p(HEMA/chitosan) membranes

An interpenetration network (IPN) was synthesized from 2‐hydroxyethyl methacrylate (HEMA) and chitosan, p(HEMA/chitosan) via UV‐initiated photo‐polymerization. The selectivity to different heavy metal ions viz Cd(II), Pb(II), and Hg(II) to the IPN membrane has been investigated from aqueous solution using bare pHEMA membrane as a control system. Removal efficiency of metal ions from aqueous solution using the IPN membranes increased with increasing chitosan content and initial metal ions concentrations, and the equilibrium time was reached within 60 min. Adsorption of all the tested heavy metal ions on the IPN membranes was found to be pH dependent and maximum adsorption was obtained at pH 5.0. The maximum adsorption capacities of the IPN membrane for Cd(II), Pb(II), and Hg(II) were 0.063, 0.179, and 0.197 mmol/g membrane, respectively. The adsorption of the Cd(II), Hg(II), and Pb(II) metal ions on the bare pHEMA membrane was not significant. When the heavy metal ions were in competition, the amounts of adsorbed metal ions were found to be 0.035 mmol/g for Cd(II), 0.074 mmol/g for Hg(II), and 0.153 mmol/g for Pb(II), the IPN membrane is significantly selective for Pb(II) ions. The stability constants of IPN membrane–metal ions complexes were calculated by the method of Ruzic. The results obtained from the kinetics and isotherm studies showed that the experimental data for the removal of heavy metal ions were well described with the second‐order kinetic equations and the Langmuir isotherm model. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange

Prediction of stock price index movement is regarded as a challenging task of financial time series prediction. An accurate prediction of stock price movement may yield profits for investors. Due to the complexity of stock market data, development of efficient models for predicting is very difficult. This study attempted to develop two efficient models and compared their performances in predicting the direction of movement in the daily Istanbul Stock Exchange (ISE) National 100 Index. The models are based on two classification techniques, artificial neural networks (ANN) and support vector machines (SVM). Ten technical indicators were selected as inputs of the proposed models. Two comprehensive parameter setting experiments for both models were performed to improve their prediction performances. Experimental results showed that average performance of ANN model (75.74%) was found significantly better than that of SVM model (71.52%).     

Feature tracking and matching in video using programmable graphics hardware

This paper describes novel implementations of the KLT feature tracking and SIFT feature extraction algorithms that run on the graphics processing unit (GPU) and is suitable for video analysis in real-time vision systems. While significant acceleration over standard CPU implementations is obtained by exploiting parallelism provided by modern programmable graphics hardware, the CPU is freed up to run other computations in parallel. Our GPU-based KLT implementation tracks about a thousand features in real-time at 30 Hz on 1,024 × 768 resolution video which is a 20 times improvement over the CPU. The GPU-based SIFT implementation extracts about 800 features from 640 × 480 video at 10 Hz which is approximately 10 times faster than an optimized CPU implementation.     

Uncertainty Analysis of Four-Terminal-Pair Capacitance Characterization up 30 MHz

The Impedance Group Laboratories of National Metrology Institute of Turkey previously developed a new method for the characterization of Agilent 16380A-type four-terminal-pair air dielectric capacitance standards ranged from 1 to 1,000 pF up to 30 MHz. This method is based on obtaining all resonance frequencies of standard capacitors using a vector network analyzer in order to calculate inductive residual parameters of the standards. As a continuation of the study, this paper gives a detailed uncertainty analysis for the method.     

Prioritization methodology of dangerous substances for water quality monitoring with scarce data

Monitoring and control of dangerous substances discharged into receiving waters have attracted more attention lately. Since it is not possible to analyze every single substance, a prioritization methodology is needed for the selection of those to be monitored. Existing well-developed models require significant amount of data for reliable outcomes. This paper presents a methodology to prioritize the dangerous substances having adverse effects on freshwaters in Turkey, where data are scarce. Such a methodology will also serve as a solid model for other countries with limited background data. The adopted methodology enabled the elimination of chemicals to generate a candidate list composed of 608 substances among more than 5000 substances. Further screening and prioritization were conducted using different assessment methods (i.e., Total Hazard Value, Total Impact Value, Combined Monitoring-based, and Modelling-based Priority Setting) to obtain a proposed Final Candidate Specific Pollutants List of 150 dangerous substances. The proposed Candidate National Pollutant List of Turkey was established by combining 45 priority pollutants of the European Union with a list of candidate specific pollutants. According to the outcomes of this study, monitoring and controlling of 195 dangerous substances in freshwaters are recommended. Further detailed studies should be conducted in order to observe the actual levels of these dangerous substances in freshwaters followed by a review of the monitoring list accordingly. Moreover, further revisions might be required in the proposed list due to some possible versatile conditions in terms of sampling points (i.e., change in the location of industries).