Sr2+–Mg2+-Doped SiAlON Ceramics

In the present work, multi-cation-doped (Sr²⁺–Mg²⁺) SiAlON ceramics were investigated. MgO and SrO were used in 100:0 and 50:50 molar ratios. The mixture was sintered at 1800° and 1830°C for 1 h in a gas pressure-sintering furnace. The results showed that sintered samples were composed of mainly α- and β-SiAlON phases and small amounts of some Sr-containing phases and SiAlON polytypes. According to Rietveld analysis of X-ray diffraction patterns, Mg is incorporated into the α-SiAlON structure. However, the incorporation of Sr is limited.     

Flexural behavior of stratified reinforced concrete: construction,testing, analysis,and design

Stratified concrete poses a promising alternative for construction. Its fresh and hardened properties have been studied at the material level; however, structural behavior in steel reinforced specimens has not been studied. This paper focuses on the flexural behavior of eight stratified reinforced concrete (SRC) specimens representing slices from a slab or non-bearing wall. Specimens with two stratified concrete designs and three steel ratios were tested and compared to estimates from a fiber element numerical model and rectangular stress-block design methods from ACI 318 and Eurocode 2. The results suggest that SRC has similar damage modes as ordinary reinforced concrete (ORC). The fiber element model accurately estimated the measured behavior, while ACI 318 and Eurocode 2 differed from the experimental results by <25%. These prediction accuracies are similar to those for ORC. Therefore, the flexural design of SRC can be done using both fiber element and rectangular stress-block approaches.     

An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

Wear behaviour of α- and α/β-SiAlON ceramics stabilized with Nd2O3 and Y2O3

α- and α/β-SiAlON compositions, doped with Y₂O₃ or Nd₂O₃, were densified by gas pressure sintering (GPS). The wear and mechanical properties of the materials were investigated and compared to β-Si₃N₄ materials. Microstructure evolution and its change with composition as well as the influence of the microstructural changes on the mechanical and tribological properties were reported. Wear tests were performed using a tribometer with ball-on-plate geometry in reciprocating sliding contact under dry condition. It was observed that α/β-SiAlON compositions, doped with Y₂O₃, have better wear properties in comparison to α-SiAlON and β-Si₃N₄ samples. Field emission scanning electron microscopy (FESEM) was used to analyse the worn surfaces after wear tests. The results showed that α/β-SiAlON and β-Si₃N₄ materials have different wear behaviour.     

Automatic segmentation of corpus collasum using Gaussian mixture modeling and Fuzzy C means methods

This paper presents a comparative study of the success and performance of the Gaussian mixture modeling and Fuzzy C means methods to determine the volume and cross-sectionals areas of the corpus callosum (CC) using simulated and real MR brain images. The Gaussian mixture model (GMM) utilizes weighted sum of Gaussian distributions by applying statistical decision procedures to define image classes. In the Fuzzy C means (FCM), the image classes are represented by certain membership function according to fuzziness information expressing the distance from the cluster centers. In this study, automatic segmentation for midsagittal section of the CC was achieved from simulated and real brain images. The volume of CC was obtained using sagittal sections areas. To compare the success of the methods, segmentation accuracy, Jaccard similarity and time consuming for segmentation were calculated. The results show that the GMM method resulted by a small margin in more accurate segmentation (midsagittal section segmentation accuracy 98.3% and 97.01% for GMM and FCM); however the FCM method resulted in faster segmentation than GMM. With this study, an accurate and automatic segmentation system that allows opportunity for quantitative comparison to doctors in the planning of treatment and the diagnosis of diseases affecting the size of the CC was developed. This study can be adapted to perform segmentation on other regions of the brain, thus, it can be operated as practical use in the clinic.     

Two approaches for solving the buffer allocation problem in unreliable production lines

This paper presents an integrated approach to solve the buffer allocation problem in unreliable production lines so as to maximize the throughput rate of the line with minimum total buffer size. The proposed integrated approach has two control loops; the inner loop and the outer loop. While the inner loop control includes an adaptive tabu search algorithm proposed by Demir et al. [8], binary search and tabu search are proposed for the outer loop. These nested loops aim at minimizing the total buffer size to achieve the desired throughput level. To improve the efficiency of the proposed tabu search, alternative neighborhood generation mechanisms are developed. The performances of the proposed algorithms are evaluated by extensive computational experimentation, and the results are reported.     

The effects of immunological castration against GnRH with recombinant OL protein (Ovalbumin-LHRH-7) on carcass and meat quality characteristics,histological appearance of testes and pituitary gland in Kıvırcık male lambs

The aims of the study were to investigate the effects of immunization against GnRH using OL protein (Ovalbumin-LHRH-7) on feedlot performance, carcass, meat quality and some reproductive traits in K?v?rc?k ram lambs. Ram lambs in the immunization (I, n = 7) group were immunized against GnRH using OL protein and boosted 2 weeks later. Control (C, n = 7) group was not treated. The animals were kept at pasture for 6 weeks after the first immunization, subjected to a 70 day fattening program, and then slaughtered. Growth performance, various carcass and meat quality characteristics were not affected from the immunization. GnRH immunization induced GnRH antibody production, suppressed testosterone production and testicular growth (P < 0.01). Testicular structure was negatively affected from the immunization, but not pituitary. These results suggest that immunization against GnRH with OL could be an alternative castration technique in ram lambs without negatively affecting carcass and meat quality characteristics.     

Dehydration,Water Vapor Adsorption and Desorption Behavior of Zn[B3O3(OH)5] · H2O and Zn[B3O4(OH)3]

The dehydration behaviors of two different hydrated zinc borate species, Zn[B₃O₃(OH)₅] · H₂O and Zn[B₃O₄(OH)₃], which are industrially important flame retardants, were studied by thermal gravimetric(TG) analysis and in situ diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. Dehydration onset temperatures of Zn[B₃O₃(OH)₅] · H₂O and Zn[B₃O₄(OH)₃] were 129 and 320°C, respectively, at a 10°C/min ramp rate. A very small amount of boric acid was volatilized in addition to water vapor when both samples were heated at 250°C. A significant amount of water vapor was adsorbed by Zn[B₃O₃(OH)₅] · H₂O from air at 25°C. However, Zn[B₃O₄(OH)₃] adsorbed a very small amount of water under the same conditions. Both zinc borates did not have a tendency to cake during storage.     

The production of β-SiAlON ceramics with low amounts of additive,at low sintering temperature

In the present work nano-sized powder of β-SiAlON was produced using a wet milling process. Different milling times and mediums (methyl ethyl keton, ethanol and toluene as solvents, polyethyleneglicol, oleic acid, sodium tripolyphosphate and polyvinylpyrrolidon as dispersants) were performed for the determination of the most efficient milling system. The powders were produced using a conventional process (the ball to powder ratio was 1:1.5, at 300 rpm, for 1.5 h) having a few hundred nanometer particle size, and these were used as standard powders in this study. The nano-sized β-SiAlON starting powders (<100 nm) were sintered at lower temperatures than that of the conventional powders. The amount of Y₂O₃ in powders (～130 nm), produced by high energy milling process, was fewer than conventional powders (5 wt.%). The results of the powder size, sintering behavior and mechanical properties of this sample were compared to those of the standard powder and its sintered sample. This sample, produced using the nano-powder, was investigated, and densified at 150 °C lower than that of the standard sample. Even though the amount of Y₂O₃ was decreased, the hardness of the samples was better than that of the standard sample.