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A neural network is employed to analyze axial piston pump of hydrostatic circular recessed bearing. Owing to complexity of the system, the neural network is used to predict the bearing parameters of the experimental system. The system mainly consists of cylinder block, piston, slipper, ball‐joint and swash plate. The neural model of the system has three layers, which are input layer with one neuron, hidden layer with ten neurons and output layer with three neurons. It can be outlined from the results for both approaches neural network could be modeled bearing systems in real time applications.

The purpose of this paper is to improve the application of neural networks on vehicle engine systems for fault detecting and analysing engine oils.

Three types of neural networks are employed to find exact neural network predictor of vehicle engine oil performance and quality. Nevertheless, two oil types are analysed for predicting performance in the engine. These oils are used and unused oils. In experimental work, two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases.

The results of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases.

The results of the proposed neural network analyser follow the desired results of the vehicle engine's vibration variation. However, this kind of neural network scheme can be used to analyse oil quality of the car in experimental applications.

As theoretical and practical studies are evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area.

This paper is an original contribution on vehicle oil quality analysis using a proposed artificial neural network and it should be helpful for industrial applications of vehicle oil quality analysis and fault detection.

To improve the application neural networks predictors on bearing systems and to investigate the exact neural model of the ball‐bearing system.

A feed forward neural network is designed to model‐bearing system. Two results are compared for finding the exact model of the system.

The results of the proposed neural network predictor gives superior performance for analysing the behaviour of ball bearing undergoing loading deformation.

The results of the proposed neural network exactly follows desired results of the system. Neural network predictor can be employed in practical applications.

As theoretical and practical study is evaluated together, it is hoped that ball‐bearing designers and researchers will obtain significant results in this area.

This paper fulfils an identified research results need and offers practical investigation for an academic career and research. Also, It should be very helpful for industrial application of ball‐bearing systems.

This paper aims to explore pro-environmental behavior (PEB) in Azerbaijan. Therefore, the authors used value-belief-norm (VBN) theory, extended by the construct of social norms (SN), as a basis.

Data were collected by establishing a link within various social media platforms. The final sample consisted of 407 respondents. The authors analyzed four dimensions of PEB using higher-order structural equations. The authors also examined both direct and (serial) indirect effects for cross-cultural validation of the extended VBN theory.

The authors were able to confirm the VBN theory in its entirety. However, SN, which are influential in collectivistic and Sunni-majority states, do not contribute significantly to explaining PEB in predominantly Shiite Azerbaijan.

The authors could not establish a direct effect of SN on PEB within this study. However, the authors observed an indirect “values-beliefs-norms-behavior” effect. The different (partly abbreviated) effect channels of the four tested value antecedents provide interesting insights for marketing research.

Based on the results, it seems crucial to make Muslim consumers aware of the negative outcomes of their consumption behavior and to emphasize individual responsibility. However, SN may not need to be addressed depending on cultural and/or religious values.

The authors examined PEB in Azerbaijan by testing the serial mediation effects in the VBN model. Further, the authors tested the influence of SN within the framework of the original VBN theory, contributing to a better understanding of the possibility of integrating components of the theory of planned behavior.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The major aim of study was to determine the chicken meat producer's optimal selling times.

The method used for this purpose was Wald, Benefit and Regret criterions of Game Theory. The transformed Wald, Benefit and Regret linear programming models were solved to find the optimal solution. The data consisted of monthly chicken meat prices received by producers between 2000‐2007, which were obtained from the Poultry Meat Producers and Breeders Association.

The optimal solutions of Wald and Benefit criteria showed that June was the best selling month for chicken meat producers in Turkey. August was found to be the optimal selling month according to the Minimum regret criterion. In light of the Maximum criterion it was concluded that the producers would be at highest regret positions with 98.28 percent in event of selling in November.

The results found in this study could be an indicator for individual chicken producers for a more competitive bargaining power when they make a contract with chicken meat production and marketing firms.

The purpose of this paper is to perform a comparative assessment of the urban and rural households’ preferences of fresh mutton meat consumption in Hakkari, Turkey.

The sample size consisted of 95 rural and 95 urban households. The data were collected from November 2007 until May 2008 intermittently. Probity and Heckman Models were used in the study.

Price elasticity of mutton meat demand was calculated as –0.242, which reveals the mutton meat is a compulsory good in the research area. Income elasticity of mutton meat was found as 0.39, which shows relatively satisfactory amount of mutton meat is consumed. However, there existed great differences in terms of mutton meat consumption per capita among the income groups.

The findings in the study may contribute to the mutton meat producers and marketers in the region when planning their production and marketing strategies.

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.

The major purpose of this study was to compare the fresh chicken meat consumption structure of urban and rural households of different income levels in Van province, Turkey.

The sample size of 96 urban and 95 households were selected randomly using sampling selection method where the population is limited. The data were collected by personnel interviewing from the households in eight districts and eight villages of Van province, Turkey between 15 November 2004 and 5 March 2005. The households were classified as the lowest, medium, upper medium and the highest income groups. Independent‐samples t‐students, one‐way ANOVA, chi‐square and linear regression statistical tests were used.

The average yearly fresh chicken meat consumption per head was 19.1 and 14.6 kg for urban and rural households, respectively. According to regression test results $1,000 increase in yearly income will raise the yearly chicken meat consumption of urban and rural households by 3.8 and 8.7 kg, respectively. The income was effective on both the consumption level and behavior of households. The urban households attached more attention to habit and nutrition value variables, while the cheapness was the major factor affecting the rural households' preference of chicken meat.

The article analyzes the differences/similarities of urban and rural households in terms of consumption expenditures and consumers' behaviors towards fresh chicken meat. The paper is an original research subject as regards its potential contributions of the nutritional measures to be taken and marketing strategies to be developed in the region.

The purpose of this paper is to investigate the relative influences of technical and functional quality levels of service quality and patient satisfaction. In this context, the healthcare service quality and the factors affecting customer satisfaction were evaluated using the grey relational analysis (GRA) method.

This is a survey-based study which involves 15 patients in a dialysis center, so the GRA is applied to clarify the uncertainty on service quality level with a limited number of patients without any statistical distribution. In order to reveal whether service quality and customer satisfaction are two different structures, a GRA model is built with ten different quality factors.

Results show that each quality factor has a different effect on the quality of service. Another important finding is that service quality and customer satisfaction are different structures for customers.

The results enable healthcare managers to understand the importance of patient care and the importance of service quality if they want to facilitate their use of their expectations in related factors.

The study is the first in terms of the application of GRA models in a private health institution operating in Turkey. Successful implementation of the GRA method allows a reasonable decision to be made with a limited number of data at hand. It is considered that the method can be used successfully in other health institutions in the Turkish Health System.