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Seeks to present a theoretical analysis on the general behaviour of a thrust bearing.

The model programme using a method adaptation of finite differences was developed to solve the Reynolds equation for lubrication. The model in the theoretical analysis uses a single one‐dimensional grid. The altering of total lubrication load obtained as a result of under‐cutting in the thrust bearing has been determined together with the parameters such as oil film thickness and pressure. Parameters such as the pressure and thickness of the oil film were determined. The hydrodynamic behaviour of thrust bearing was analysed by considering different dimensionless system pressure, speed and geometry of the bearing. The effect of the elastic load due to elastic deflection is taken into account as the load‐bearing characteristics are included. Also, a proposed neural network predictor is utilised to analyse the general behaviour of thrust bearing.

The results of the proposed neural network predictor give superior performance for analysing of the behaviour of a thrust bearing undergoing in elastic deformation.

This continuation of theoretical and practical study evaluation should be of benefit to thrust bearing designers and researchers, who hopefully will make significant progress as a result.

To analyse a self‐acting parallel surface thrust bearing using a proposed feedforward neural network.

Firstly, a one‐piece hydrodynamic thrust bearing with an initially flat surface is analysed, designed and tested. Analysis of the configuration used is particularly simple and gives good agreement with experimental results. Secondly, some artificial neural network types are designed to analyse minimum film thickness for specified load of thrust bearing system.

A more efficient film shape might result if the length of the cantilever did not increase with radius, since with the configuration used, the deflection of the outer corner was almost three times greater than the deflection of the inner corner, although this effect only becomes acute with regard to film thickness at fairly high loads. The design analysis of an asymmetric cantilever would be more lengthy and less easy to apply. Extrapolation of results for the plain bearing shows that high loads could be carried, but under severe conditions of temperature and clearance.

Owing to finance problems, it was not easy to setup system in real time applications. This approach would be given usefulness elsewhere.

In future, this technique will be implemented for designing experimental neural network predictor on thrust bearing system. Also, this kind of neural predictor will be suitable for complex bearing systems.

A new type of neural network is used to investigate film thickness of thrust bearing system. Quick propagation neural network has given superior performance for designing of model of thrust bearing system. As described and shown in figures and tables, this kind of neural predictor could be employed for analysing such systems in practical analyses.

This paper presents an investigation for analyzing the efficiency of axial piston pumps in a variety conditions using a proposed neural network. Since slippers affect the performance of the system considerably, the effects of surface roughness on lubrication have been studied in slippers with varying hydrostatic bearing areas and surface roughness. The neural network structure is very suitable for this kind of system. The network is capable of predicting the leakage oil quantity of the experimental system. The network has parallel structure and fast learning capacity. It is also easy to see from the experimental results that the leakage oil quantity was caused by surface roughness, orifice diameter and the size of hydrostatic bearing area, loading pressure and the number of rotations. It can be outlined from the results for both approaches, neural network could be modeled slipper bearing systems in real time applications.

The author considers an invariant lightlike submanifold M, whose transversal bundle tr(TM) is flat, in an indefinite Sasakian manifold M¯(c) of constant φ¯-sectional curvature c. Under some geometric conditions, the author demonstrates that c=1, that is, M¯ is a space of constant curvature 1. Moreover, M and any leaf M′ of its screen distribution S(TM) are, also, spaces of constant curvature 1.

The author has employed the techniques developed by K. L. Duggal and A. Bejancu of reference number 7.

The author has discovered that any totally umbilic invariant ligtlike submanifold, whose transversal bundle is flat, in an indefinite Sasakian space form is, in fact, a space of constant curvature 1 (see Theorem 4.4).

To the best of the author’s findings, at the time of submission of this paper, the results reported are new and interesting as far as lightlike geometry is concerned.

Turkish Ministry of Health (MoH) has Health Transformation Program (HTP). The purpose of this program has been to modify the structure of the current system in order to enhance health system productivity, quality, and access in the Turkish health system. The paper aims to discuss these issues.

To measure the productivity, a data envelopment analysis-based Malmquist index approach was employed.

Results showed that the overall HTP have had a considerable positive impact on the productivity of general hospitals.

The limitation is the availability of some data that might not be collected or reported to the MoH in Turkey.

This research’s findings will have an impact on reforming the health care system in Turkey to be competitive and efficient as possible.

The research will have implication on reducing cost and provide value to the Turkish population.

This is one of the very few articles that targeted the efficiency of hospital system in Turkey.

The purpose of this paper is to evaluate if sudden retail price increases for beef products have affected consumers purchasing behaviors. Little research has been conducted that integrates retail price volatility with subdued food consumption motivations. Prior research about consumers’ meat-purchasing habits and systemic concerns linked to sustainability and animal welfare is limited or de-contextualized. This study also attempts to assess if retail price increases have triggered a change in perception of the meat industry, by looking at specific values related to animal protein production and consumption.

This study is based on an inductive, quantitative analysis of primary data obtained from a survey on beef consumption. For convenience and validity, all respondents had to be living in Canada for 12 months, and were at least 18 years old. The choice of country is not trivial. First, access to data were convenient for this study. Second, and most importantly, Canada has supply managed commodities that include poultry and chicken. In effect, Canada produces the amount of chicken it needs. Beef production is vulnerable to market volatility. As a result, demand-focussed market conditions for one often influence conditions for the other.

Findings indicate that higher prices have compelled 37.9 percent of the sample to reduce or to stop beef consumption altogether in the last 12 months. Beyond the issue of price, sustainability, food safety and health appear to be significant factors, more so than ethics (animal welfare). Results also show that education can be considered as a determinant for sustainable aspects of beef production when prices increase. Age and gender had no statistical significance on survey results. Some limitations are presented and future research paths are suggested.

Since the sample in this study was mainly composed of consumers based in Canada, the generalizations of the findings should be approached with some caution. The same research should be conducted with consumers from other parts of the Western world to verify if the results can be generalized.

This survey help the authors to understand some aspects of beef consumption at retail. Findings of this empirical study have implications for future communications to consumers, in that greater emphasis should be given to the connection consumers have with other nutritional alternatives. Since meat consumption in the Western world is intrinsically linked to culinary traditions, behaviors can be challenging to change.

The economic implications of a rapid adoption of a plant-based diet for the agricultural economy would be significant. However, the reality is that according to many studies of consumer behavior, customers still place a higher value on buying and eating meat than on any other food group. Canada’s relationship with animal proteins has deep cultural roots, particularly during holidays and summertime.

The present study has given important insights into the determinants of meat consumption reduction, a behavior which could both have long-term economic implications for the cattle and beef industries. This paper provides a deeper insight into some socio-economic factors that contribute to slow erosion of meat consumption reduction, and the effects of higher prices at retail. This is, as far as the authors know, likely the first study of its kind.

The main purpose of this study is to measure financial literacy of individual pension system customers in Ankara and to find out factors affecting financial literacy while acquiring additional information on financial decisions of individual pension system customers. The results show that the self-financial knowledge evaluation of individual pension system customers and their financial literacy are not compatible. Besides, the financial literacy levels of the customers who make their investment themselves and customers who leave investment decision to the individual pension system company are found not to be statistically significant although self-investors believe they have higher financial knowledge. In addition to this, the effects of financial literacy level in terms of renewable energy investments are also evaluated. Individuals with an increasing level of financial literacy may turn to renewable energy sources and investments because of their low-cost and high-return potential.

The purpose of this paper is to introduce a novel approach based on the high-order matrix derivative of the Bernstein basis and collocation method and its employment to solve an interesting and ill-posed model in the heat conduction problems, homogeneous backward heat conduction problem (BHCP).

By using the properties of the Bernstein polynomials the problems are reduced to an ill-conditioned linear system of equations. To overcome the unstability of the standard methods for solving the system of equations an efficient technique based on the Tikhonov regularization technique with GCV function method is used for solving the ill-condition system.

The presented numerical results through table and figures demonstrate the validity and applicability and accuracy of the technique.

A novel method based on the high-order matrix derivative of the Bernstein basis and collocation method is developed and well-used to obtain the numerical solutions of an interesting and ill-posed model in heat conduction problems, homogeneous BHCP with high accuracy.

This chapter presents innovative approaches to active learning that were introduced into the teaching of preservice teachers at the Faculty of Education of University of West Bohemia, Pilsen, in the Czech Republic. Over the last three years, the Technology-Enhanced Learning course has seen substantial innovations in both the content and use of teaching strategies designed to prepare the students for their professional lives. The whole update of the course was implemented using the results of action research – all individual changes were rigorously tracked and analyzed. The state of the art in the active learning domain in education of preservice teachers is presented in this chapter.

There is a description of the procedure to update the course, based on the reflections of teachers and feedback from students, gathered during action research. Detailed evaluations of particular methods of active learning that have been proven in teaching are provided.

Besides practical activities with tablets and smartphones, during which students familiarize themselves with various types of applications and reflect on their use in teaching, the course was extended by the use of practical aids for the efficient inclusion of mobile technologies for teaching – the Czech version of Allan Carrington’s Padagogy Wheel. This aid is derived from the revised Bloom’s taxonomy and SAMR model and helps the systematic reflection of preservice teachers when preparing for technology-enhanced teaching.

A significant part of the teaching consists of cooperative projects between preservice teachers and pupils of elementary schools – for example, the preservice teachers help elementary school pupils discover possibilities of virtual reality during Google Cardboard activities, or preservice teachers in teams with elementary school pupils create digital stories together on the topic of Internet safety.

The innovative approach to active teaching in the Technology-Enhanced Learning course is apparent even during the exam. In the course of the exam, students process, present, and defend a lesson plan for the implementation of an activity using digital technologies.

Throughout the learning, as well as at the end, preservice teachers are encouraged to reflect on the teaching in the Technology-Enhanced Learning subject.

This study aims to optimize autonomous performance (i.e. both longitudinal and lateral) and endurance of the quadrotor type aerial vehicle simultaneously depending on the autopilot gain coefficients and battery weight.

Quadrotor design processes are critical to performance. Unmanned aerial vehicle durability is an important performance parameter. One of the factors affecting durability is the battery. Battery weight, energy capacity and discharge rate are important design parameters of the battery. In this study, proper autopilot gain coefficients and battery weight are obtained by using a stochastic optimization method named as simultaneous perturbation stochastic approximation (SPSA). Because there is no direct correlation between battery weight and battery energy density, artificial neural network (ANN) is benefited to obtain battery energy density corresponding to resulted battery weight found from SPSA algorithm. By using the SPSA algorithm optimum performance index is obtained, then obtained data is used for longitudinal and lateral autonomous flight simulations.

With SPSA, the best proportional integrator and derivative (PID) coefficients and battery weight, energy efficiency and endurance were obtained in case of morphing.

It takes a long time to find the most suitable battery values depending on quadrotor endurance. However, this situation can be overcome with the proposed SPSA.

It is very useful to determine quadrotor endurance, PID coefficients and morphing rate using the optimization method.

Determining quadrotor endurance, PID coefficients and morphing rate using the optimization method provides advantages in terms of time, cost and practicality.

The proposed method improves quadrotor endurance. In addition, with the SPSA optimization method and ANN, the parameters required for endurance will be obtained faster and more securely. In addition, the energy density according to the battery weight also contributes to the clean environment and energy efficiency.