Precise interferometric length and phase-change measurement of gauge blocks based on reproducible wringing

A modern fringe-pattern-analyzing interferometer with a resolution of 1 x 10(-9) and without exclusion of systematic uncertainties owing to optic effects of less than 1 nm was used to test a new method of interferometric length measurement based on a combination of the reproducible wringing and slave-block techniques. Measurements without excessive wringing film error are demonstrated for blocks with nominal lengths of 2-6 mm and with high surface flatness. The uncertainty achieved for these blocks is less than 1 nm. Deformations of steel gauge blocks and reference platens, caused by wringing forces, are investigated, and the necessary conditions for reproducible wringing are outlined. A subnanometer uncertainty level in phase-change-correction measurements has been achieved for gauge blocks as long as 100 mm. Limitations on the accuracy standard method of interferometric length measurements and shortcomings of the present definition of the length of the material artifact are emphasized.     

Coping with production time variability via dynamic lead-time quotation

In this paper, we propose two dynamic lead-time quotation policies in an M/GI/1 type make-to-stock queueing system serving lead-time sensitive customers with a single type of product. Incorporating non-exponential service times in an exact method for make-to-stock queues is usually deemed difficult. Our analysis of the proposed policies is exact and requires the numerical inversion of the Laplace transform of the sojourn time of an order to be placed. The first policy assures that the long-run probability of delivering the product within the quoted lead-time is the same for all backlogged customers. The second policy is a refinement of the first which improves the profitability if customers are oversensitive to even short delays in delivery. Numerical results show that both policies perform close to the optimal policy that was characterized only for exponential service times. The new insight gained is that the worsening impact of the production time variability, which is felt significantly in systems accepting all customers by quoting zero lead times, decreases when dynamic lead-time quotation policies are employed.     

Investigation of nickel(II) biosorption on Enteromorpha prolifera: optimization using response surface analysis

In this study, the biosorption of nickel(II) ions on Enteromorpha prolifera, a green algae, was investigated in a batch system. The single and combined effects of operating parameters such as initial pH, temperature, initial metal ion concentration and biosorbent concentration on the biosorption of nickel(II) ions on E. prolifera were analyzed using response surface methodology (RSM). The optimum biosorption conditions were determined as initial pH 4.3, temperature 27 degrees C, biosorbent concentration 1.2 g/L and initial nickel(II) ion concentration 100 mg/L. At optimum biosorption conditions, the biosorption capacity of E. prolifera for nickel(II) ions was found to be 36.8 mg/g after 120 min biosorption. The Langmuir and Freundlich isotherm models were applied to the equilibrium data and defined very well both isotherm models. The monolayer coverage capacity of E. prolifera for nickel(II) ions was found as 65.7 mg/g. In order to examine the rate limiting step of nickel(II) biosorption, such as the mass transfer and chemical reaction kinetics, the intraparticle diffusion model, external diffusion model and the pseudo second order kinetic model were tested with the experimental data. It was found that for both contributes to the actual biosorption process. The pseudo second order kinetic model described the nickel(II) biosorption process with a good fitting.     

Transition metal cations extraction by ester and ketone derivatives of chromogenic azocalix[4]arenes

The molecule of azocalix[n]arene is a macrocyclic used effectively in the complexation of the heavy metal pollutants (like silver and mercury). In this work, our main aim is to prepare new chromogenic azocalix[n]arene molecules to elaborate an extractant with high extractant selectivity for metal ions able to detect this type of pollutant. The solvent extraction properties of four acetyls, four methyl ketones and four benzoyls derivatives from azocalix[4]arenes which were prepared by linking 4-ethyl, 4-n-butyl, 4-acetamid anilin and 2-aminothiazol to calix[4]arene through a diazo-coupling reaction, the alkaline earth (Sr2+) and the transition (Ag+, Hg2+, Co2+, Ni2+, Cu2+, Zn2+, Cd2+, Cr3+) metal cations have been determined by extraction studies with metal picrates. Both ketones are better extractants than esters, and show a strong preference for Ag+, while Cu2+ and Cr3+ are the most extracted cation with the esters. Both acetyl and benzoyl esters are good carriers for Ag+ and Hg2+.     

Electrochemical treatment of deproteinated whey wastewater and optimization of treatment conditions with response surface methodology

Electrochemical treatment of deproteinated whey wastewater produced during cheese manufacture was studied as an alternative treatment method for the first time in literature. Through the preliminary batch runs, appropriate electrode material was determined as iron due to high removal efficiency of chemical oxygen demand (COD), and turbidity. The electrochemical treatment conditions were optimized through response surface methodology (RSM), where applied voltage was kept in the range, electrolyte concentration was minimized, waste concentration and COD removal percent were maximized at 25 degrees C. Optimum conditions at 25 degrees C were estimated through RSM as 11.29 V applied voltage, 100% waste concentration (containing 40 g/L lactose) and 19.87 g/L electrolyte concentration to achieve 29.27% COD removal. However, highest COD removal through the set of runs was found as 53.32% within 8h. These results reveal the applicability of electrochemical treatment to the deproteinated whey wastewater as an alternative advanced wastewater treatment method.     

Magnetocaloric effect of polycrystalline La0.5Sm0.2Sr0.3Mn1-xCrxO3 (0 ≤ x ≤ 0.20) compound prepared by glycine-nitrate process

Journal of Materials Science: Materials in Electronics - This paper reports the effect of chromium’s substitution in magnetic oxides with perovskite structure La0.5Sm0.2Sr0.3Mn1-xCrxO3...     

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to find reliable methods for the estimation of construction material prices. Material prices have a time dependent nature. In order to increase the foreseeability of the costs of construction materials, this study focuses on estimation of construction material indices through time series analysis. Two different types of analysis are implemented for estimation of the future values of construction material indices. The first method implemented was Autoregressive Integrated Moving Average (ARIMA), which is known to be successful in estimation of time series having a linear nature. The second method implemented was Non-Linear Autoregressive Neural Network (NARNET) which is known to be successful in modeling and estimating of series with non-linear components. The results have shown that depending on the nature of the series, both these methods can successfully and accurately estimate the future values of the indices. In addition, we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.     

Permeability properties of concretes with high reactivity metakaolin and calcined impure kaolin

This study reports the findings of an experimental study carried out on transport properties of the concretes modified with different calcined non purified kaolins (CK) and commercially available high reactivity metakaolin (MK). CK used in this study were obtained by calcining impure ground kaolins from four different quarries located on kaolin beds of different morphological and geological formations in Turkey. However, commercially available MK produced by thermal treatment of high purity kaolin from Czech Republic was used as reference material. In concrete mix design, the cement was replaced with 5, 10, 15, and 20 % by weight of CK or MK. The gas permeability, water permeability, water sorptivity, and chloride permeability tests were performed at the end of 28 and 90 days of curing periods. The results indicated that the concretes incorporated with different types of calcined kaolins had comparable performance in permeability with MK modified concrete, depending mainly on the type and amount of the mineral admixture used. Moreover, all of the concretes incorporation MK or CK had considerably better permeability than plain concrete regardless of the replacement level.     

Synthesis of compositionally different multicomponent metal-oxide films (SnO2) x (ZnO)1 − x (x = 1–0.5)

The study is concerned with high-purity SnO₂ and ZnO powders produced from salt solutions of corresponding metals by low-temperature hydrothermal synthesis. Fragments of SnO₂ and ZnO ceramic targets formed as 1 × 8 cm bars are fabricated by dry pressing. The bars are used to form composite targets for ion-beam sputtering and the fabrication of compositionally different (SnO₂) _x (ZnO)_{1 ? x} (x = 1–0.5) films appropriate for the production of gas sensors or transparent electronic devices. The optical and electrical parameters of the films with different compositions are studied.     

Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems

The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.