Locational analysis for regionalization of Turkish Red Crescent blood services

After a series of earthquakes in 1999, Turkish Red Crescent (TRC) has engaged in a restructuring for all of its activities, including the blood services. Our study on the blood management system had been started as part of this initiative to restructure the blood services and improve both their effectiveness and efficiency. In the current system of TRC, not much consideration has been given to how the locational decisions affect the performance of blood centers, stations and mobile units. In recent years, however, there has been much discussion regarding the regionalization of the blood management system in Turkey. In this study, we develop several mathematical models to solve the location–allocation decision problems in regionalization of blood services. We report our computational results, obtained by using real data, for TRC blood services.     

An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System,Support Vector Machine and Artificial Neural Network Models

Sediment transport in streams and rivers takes two forms as suspended load and bed load. Suspended load comprises sand + silt + clay-sized particles that are held in suspension due to the turbulence and will only settle when the stream velocity decreases, such as when the streambed becomes flatter, or the streamflow into a pond or lake. The sources of the suspended sediments are the sediments transported from the river basin by runoff or wind and the eroded sediments of the river bed and banks. Suspended-sediment load is a key indicator for assessing the effect of land use changes, water quality studies and engineering practices in watercourses. Measuring suspended sediment in streams is real sampling and the collection process is both complex and expensive. In recent years, artificial intelligence methods have been used as a predictor for hydrological phenomenon namely to estimate the amount of suspended sediment. In this paper the abilities of Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and Adaptive Network Based Fuzzy Inference System (ANFIS) models among the artificial intelligence methods have been investigated to estimate the suspended sediment load (SSL) in Ispir Bridge gauging station on Coruh River (station number: 2316). Coruh River is located in the northern east part of Turkey and it is one of the world”s the fastest, the deepest and the largest rivers of the Coruh Basin. In this study, in order to estimate the suspended sediment load, different combinations of the streamflow and the SSL were used as the model inputs. Its results accuracy was compared with the results of conventional correlation coefficient analysis between input and output variables and the best combination was identified. Finally, in order to predict SSL, the SVM, ANFIS and various ANNs models were used. The reliability of SVM, ANFIS and ANN models were determined based on performance criteria such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Efficiency Coefficient (EC) and Determination Coefficient (R²).     

Extraction of voltage harmonics using multi-layer perceptron neural network

This paper presents a harmonic extraction algorithm using artificial neural networks for Dynamic Voltage Restorers (DVRs). The suggested algorithm employs a feed forward Multi Layer Perceptron (MLP) Neural Network with error back propagation learning to effectively track and extract the 3rd and 5th voltage harmonics. For this purpose, two different MLP neural network structures are constructed and their performances compared. The effects of hidden layer, supervisors and learning rate are also presented. The proposed MLP Neural Network algorithm is trained and tested in MATLAB program environment. The results show that MLP neural network enable to extract each harmonic effectively.     

Parallel-machine rescheduling with machine disruptions

In this study we consider a rescheduling problem on identical parallel machines. The rescheduling is undertaken because of a period of unavailability on one of the machines. We consider the total flow time as an efficiency measure and stability is gauged in terms of the number of jobs processed on different machines in the original and new schedules. We show that all efficient schedules with respect to efficiency and stability measures can be generated in polynomial time.     

Preparation and characterization of conductive polypyrrole/kaolinite composites

Conductive polypyrrole (PPy)/kaolinite clay composites were prepared by in situ chemical polymerization of pyrrole in the presence of kaolinite using FeCl₃ as oxidant. The PPy content and conductivity of the composites reached 32.8% and 8.3×10^?2 S/cm at HCl concentrations of 1.5 M and 0.5 M, respectively. The microhardness of the composites containing different amounts of PPy was higher than that of the PPy and kaolinite components. The highest microhardness observed was 30.17 kg/mm² for the composite containing 9.6% PPy. The electrical resistance of the composites was monitored during heating–cooling cycles over the range 5–120 °C. The change in resistance with temperature was more repeatable for the composite than for PPy. The composites were characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The humidity-sensing properties were also examined.     

Current and voltage transfer function filters using a single active device

In this study, current and voltage transfer function filters using single active component, namely, current backward transconductance amplifier (CBTA) are presented. The proposed structures are a single-input three outputs (SITO) current-transfer function filter, a single-input four-output (SIFO) voltage transfer function filter and three-input single-output (TISO) voltage transfer function filter. The proposed filters have low active and passive sensitivities and use canonical number of electronics components. The validity of the proposed circuits is demonstrated by PSPICE simulations and experimental results. Operation range of the CBTA and its parasitic effects are also discussed.     

Treatment of olive mill wastewater by different physicochemical methods and utilization of their liquid effluents for biological hydrogen production

In this study various two-stage processes were investigated for biological hydrogen production from olive mill wastewater (OMW) by Rhodobacter sphaeroides O.U.001. Two-stage processes consist of physicochemical pretreatment of OMW followed by photofermentation for hydrogen production. Explored pretreatment methods were chemical oxidation with ozone and Fenton's reagent, photodegradation by UV radiation, and adsorption with clay or zeolite. Among these different two-stage processes, strong chemical oxidants like ozone and Fenton's reagent have the highest color removal (90%). However, their effluents were observed to be unsuitable for both hydrogen production and bacterial growth. On the other hand, clay treatment method was selected as the optimum process that allows fast and low-cost treatment as well as its effluent found to have the highest hydrogen production potential (31.5 m³ m^?3). Spent-clay regeneration was also investigated on the grounds that solid waste minimization is important for the overall efficiency of this process.     

Determination of photoinitiated polymerization of multifunctional acrylates with acetic acid derivatives of thioxanthone by RT-FTIR

Photopolymerization of multifunctional acrylates with 2-thioxanthone-thioacetic acid (TXSCH₂COOH) and 2-(carboxymethoxy) thioxanthone (TXOCH₂COOH) as the one-component photoinitiator has been investigated by real-time Fourier transform infrared (RT-FTIR) spectroscopy. The photobleaching of these one-component nature initiators was performed in air. The irradiation time for total bleaching was 240 s for TXSCH₂COOH and 540 s for TXOCH₂COOH.