A Statistical Model of <Emphasis Type="Italic">I</Emphasis><Subscript><Emphasis Type="Italic">c</Emphasis></Subscript> Changes for Bending Bi-2223 Tapes

Bi-2223 tape was one of the high-temperature superconductors with commercial applications. One of the applications was bending and winding Bi-2223 tape into solenoids to produce high magnetic fields. To study bending properties, three multifilamentary of Bi-2223 tapes sheathed with silver alloys were manufactured. Bending experiments for the tapes were performed, and critical currents I _c of tapes with definite bending radius were measured. And, current transferring mechanisms in filaments were analyzed, as well. Experimental results showed that silver alloy sheathed tapes had better bending properties than pure silver-sheathed one. On the contrary, to describe bending radius dependence of I _c , a statistical model was suggested. The model expected that bending radius dependence of I _c was following an exponential law that was quantitatively expressed by mathematic expressions. Bending dependence of I _c could be calculated from the expression and calculated results agreed with experimental data very well. Therefore, the suggested model has successfully explained the experimental results.     

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.     

The selection of technology forecasting method using a multi-criteria interval-valued intuitionistic fuzzy group decision making approach

Technological forecasting is a tool for organizations to develop their technology strategies. The quality of forecasting is extremely important for the accuracy of the results and in turn company future. Therefore a proper selection methodology of forecasting technique that considers the characteristics of technology and resources needed such as cost, time is essential. On the other hand, although many forecasting techniques are available, there is a high uncertainty in choosing the most appropriate technique among a set of available techniques. In this paper interval valued intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is proposed for the solution of technological forecasting technique selection problem. The proposed method includes seven selection criteria and twelve forecasting technique alternatives. The methodology is applied for 3D TV technology. The results revealed that Fisher Pry method is found as the most appropriate method for forecasting since it has the highest closeness coefficient.     

Development of a decision support system for robot selection

With the availability of more different robot types and models along with their separate specifications, selecting the most appropriate robot is becoming more difficult and complicated for companies. Furthermore, a common set of robot selection criteria is not available for the decision makers. In this study, a two-phase robot selection decision support system, namely ROBSEL, is developed to help the decision makers in their robot selection decisions. In development of ROBSEL, an independent set of criteria is obtained first and arranged in the Fuzzy Analytical Hierarchy Process (FAHP) decision hierarchy. In the first elimination phase of the decision support system, the user obtains the feasible set of robots by providing limited values for the 15 requirements. ROBSEL, then, uses FAHP decision hierarchy to rank the feasible robots in the second phase. ROBSEL is illustrated and tested and several critical issues in its practical usage are explored in the paper. The applications of ROBSEL show that ROBSEL is a useful, practical and easy to use robot selection tool and improves robot selection decisions in the companies.     

The effects of temperature,radiation, and illumination on current–voltage characteristics of Au/PVA(Co,Zn-doped)/n-Si Schottky diodes

Polyvinyl alcohol (PVA)/(Co-Ni) nanofiber film was fabricated on silicon wafer using electrospinning technique. The topography of the produced PVA/(Co-Ni) nanofiber film was examined by scanning electron microscopy (SEM). The Au/Poly (vinyl alcohol) (Co, Ni-doped)/n-Si Schottky diode (SD) was thermally formed in evaporating system after the spinning process. At first, the current–voltage (I–V) characteristics of Au/PVA (Co, Zn-doped)/n-Si SD was measured at the room temperature (300 K). For the investigating the effect of temperature, illumination and radiation on Au/PVA (Co, Zn-doped)/n-Si SD comparatively, the measurement was performed under the illumination intensity of 200 W, at 380K, and finally the radiation dose of 22 kGy respectively. The diode characteristics such as the zero-bias barrier height (ϕ_Bo), ideality factor (n) and series resistance (R_s) were calculated at room temperature and under the condition of high temperature, illumination, and radiation. It was found that these characteristics were affected by the illumination and radiation as well as the temperature. The density of interface states (N_ss) distribution profiles as a function of (E_c - E_ss) extracted from the forward I–V measurements were also affected by illumination and radiation even if just a bit. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Mechanical and microstructural properties of low-carbon steel-plate-reinforced gray cast iron

In the present experimental study, strengthening of gray cast iron by reinforcing with steel plates was investigated in the as-cast and normalized conditions. Normalizing heat treatments were applied to the specimens at temperatures of 800 °C and 850 °C. Three-point bend specimens were manufactured from gray cast iron and also from gray cast iron with reinforced steel plates. Flexural strengths of the steel-plate-reinforced cast iron were calculated for four distinct volume fractions (V_r = 0.04, 0.08, 0.12, and 0.16). The current study shows that the steel-plate-reinforced gray cast iron has higher flexural strength and flexural modulus than the cast iron without reinforcement. The flexural strength considerably increases with slight increase in normalization temperature. Optical and scanning electron microscopy analyses were used to examine flake morphology and microstructures of gray cast iron and steel-plate-reinforced gray cast iron. It is noted that carbon diffuses from the gray cast iron to the steel plates. A transition region containing partially dissolved graphite and having high hardness was observed due to the carbon diffusion.     

Influence of gender,program of study and PC experience on unethical computer using behaviors of Turkish undergraduate students

This study administered the unethical computer using behavior scale (UECUBS) developed by [Namlu, A.G., & Odabasi, F. (2007). Unethical computer using behavior scale: A study of reliability and validity on Turkish university students. Computers and Education, 48, 205–215.] to investigate whether gender, program of study and PC experience have an impact on ethical judgments of undergraduate students regarding information and communication technologies (ICTs). The sample consisted of 559 undergraduates from the Education Faculty of the most populated state university in Turkey. The results of 5 (program of study) × 2 (gender) × 2 (PC experience) between-groups analysis of variance (ANOVA) indicated no significant differences among different programs of study and between high and low experienced PC users. The analysis showed significant differences between males and females. A significant interaction between the program of study and gender was found, which indicated that the difference between males and females did not follow a similar pattern across different programs of study. More specifically, females’ ethical judgments were consistent across different fields while males’ judgments varied according to the field of study.     

Determination of important biochemical properties of honey to discriminate pure and adulterated honey with sucrose (Saccharum officinarum L.) syrup

The aims of the present study were to determine biochemical properties of honey samples and to discriminate pure and adulterated honey produced by the standard bee feeding method (control honey), the shaking method (pure blossom honey), and overfeeding (100 kg/colony syrup) with sucrose syrup (adulterated honey). The biochemical properties evaluated were moisture, ash, acidity, hydroxymethylfurfural (HMF), specific sugars (i.e. fructose, glucose, fructose–glucose, sucrose, and maltose), diastase activity, δ¹³C value (honey), δ¹³C value (protein), electrical conductivity, potassium, vitamin C, and proline. Fifteen honey samples were analyzed by discriminant analysis stepwise method. Proline, electrical conductivity and sucrose were found as discriminative characters of samples. Based on these three properties 100% of original group cases (samples) correctly classified in their real group. We found that the honey produced by feeding with 100 kg sucrose syrup per colony contained the sucrose as low as pure blossom honey. Therefore, the sugar (sucrose, fructose and glucose) content of honey cannot be used to distinguish between adulterated (sucrose syrup) and pure blossom honey.