Comparing of Welfare indicators between Turkey and European Union Member States

This study considered pre-selected socio-economic indicators of the first 15 members of the European Union, subsequent 9 countries from East and Central Europe and Turkey, analyzing the situations of countries and variables according to one another and betraying the possible commonalities and disparities between them. Aiming at finding possible similarities and disparities between them selected social economic indicators from EUROSTAT (2005 data were used) is acquired and by using related variables the multidimensional scaling analysis is applied. As a result of the multidimensional scaling analysis the obtained stress value for the two-dimensional configuration was 0,18. The k=2 dimension the stress value explains the data in the rate of 0,85387. It is important to look at the inflation rate and gini coefficient first, when the objective is to investigate the development and welfare indicators of a country. According to distances between Countries, higher welfare and development level was demonstrated in the first 15 members of the European Union. In the second dimension, the distances between the countries of East-Central Europe that subsequently joined the Union and Turkey show that they have similar welfare and development level.Multidimensional Scaling, Social Economics Indicators, EUROSTAT

Commonalities and Disparities among the EU Candidate

One of the important challenges of the European Union (EU) at the beginning of the 21st century is its enlargement. After the integration of the 12 countries in 2005 and 2007, the EU continues its strategy for stability, security and prosperity in Europe. The new candidate countries, at different levels of development, are Western Balkan countries and Turkey. The objective of the paper is to investigate the differences among the EU candidate countries according to the current measures of welfare/sustainability and to find their similarities and differences. This analysis of the differences and the similitude between candidate countries is done by using multidimensional scaling method (MDS) and hierarchical cluster analysis of sustainability, which takes into account, at the same time, economic, health, standard of living, people and environmental variables, as part of the multivariate statistical analysis technique - one of the basic methods of multidimensional scaling. Furthermore, MDS method allows a standardized (transformed) analysis of the data collected in different scales. This study is based on the data standardized by means of Z score transformation. The main conclusions of the analysis light up the differences between candidate countries and could be an important tool for the policy makers to focus their efforts on the difficult goal to join the European Union.multidimensional scaling, hierarchical cluster analysis, statistical analysis

Research of Industry 4.0 Awareness: A Case Study of Turkey

Rapid development of technology, particularly in the field of artificial intelligence, has fuelled the concept of Industry 4.0 among all types of businesses across the globe. This has driven sustainable growth for those businesses as well as promoted economic prosperity in the countries where they operate in. In view of this information, it is of absolute importance that the entire business landscape in Turkey avails itself to greater awareness and education about the benefits of embracing a comprehensive Industry 4.0 philosophy. It is also important to shed the light on the problems these businesses may face in transition from the old industrial philosophies to the new philosophy of Industry 4.0. Therefore, the aim of this study is to measure the level of Industry 4.0 awareness among businesses in Turkey. The research also seeks to determine how targeted Industry 4.0 educational programs and policies vary in relation to the demographic characteristics among some business operators in Turkey. A multiple case study design governed this entire research. Thus, views and in-depth data from 32 companies based in Turkey were collected by questionnaire and subsequently analysed in a detailed format. At the end of the study, the findings revealed that Industry 4.0 awareness differed depending on the employees’ levels of education. The researchers also discovered that the status or extent of relationships these companies had with foreign partners abroad has a significant impact on the awareness levels of Industry 4.0

The Statistical Analysis of finding Optium Ratio between Real Aircraft and Simulator Flights: an application to army aviation

Flight training is a very complicated process. Including the full flight simulators makes this much more complicated, indeed supposed to make it easy. Flight simulators are very important devices, eliminating difficulties, cost and risks likely to be encountered in flight training. It is essential that simulators shall be used to decrease the cost and increase efficiency of trainings. However, flight simulator is not a unique solution, itself. For several reasons, real aircraft shall also be used, at this point, a hyhbrid solution must be established and an optimum training ratio between real aircraft and flight simulators is essential for decisive curriculum. The aim of the work is to find optimum usage ratio between real aircraft (helicopter is considered in this study) and flight simulators in Army Aviation training system. Hence, a field study questionnaire was developed and delivered to 145 experienced army helicopter pilots. The questionnaire consists of three parts. First, the demographic features, including flight qualifications and experiences of the pilots were figured out. In the second part, importance of simulators, their effectiveness, characteristics and pilots’ expectations were researched. Finally, optimum usage ratio between real aircraft and flight simulators was asked. The study population was established from different pilotage status and experience levels in order to set up the homogeneity. Data collected from the study population and subordinate topics in the questionnaire were delineated with factor analysis, ANOVA, reliability tests, Tukey’s test of additivity, Chi-square and some other statistical analysis in SPSS 11.0.data analyzing, factor analysis, flight ratio, training, simulator, statistical procedures

Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

The Artificial Bee Colony (ABC) algorithm is widely used to achieve optimum solution in a short time in integer-based optimization problems. However, the complexity of integer-based problems such as Knapsack Problems (KP) requires robust algorithms to avoid excessive solution search time. ABC algorithm that provides both the exploitation and the exploration approach is used as an alternative approach for various KP problems in the literature. However, it is rarely used for the Single Container Loading problem (SCLP) which is an important part of the transportation systems. In this study, the exploitation and exploration aspects of the ABC algorithm are improved by using memory mechanisms and genetic operators to develop three different hybrid ABC algorithms. The developed algorithms and the basic ABC algorithm are applied to a SCLP dataset from the literature to observe the effects of the memory mechanism and the genetic operators separately. Besides, a joint hybrid ABC algorithm using both reinforcement approaches is proposed to solve the SCLP. The results show that the joint hybrid ABC algorithm has emerged as a promising approach to solving SCLP with an average performance, and the genetic operators are more effective than the memory mechanism to develop a hybrid ABC algorithm. (C) 2021 Elsevier B.V. All rights reserved

The Reliability and Validity of the Turkish Version of the Survey of Activities and Fear of Falling in the Elderly

Background and Purpose

The Reliability and Validity of the Turkish Version of the Survey of Activities and Fear of Falling in the Elderly

Background and Purpose

Polymeric amylase nanoparticles as a new semi-synthetic enzyme system for hydrolysis of starch

WOS: 000317528700009PubMed ID: 23498211alpha-Amylase (EC 3.2.1.1; alpha-D-1,4,glucan glucanohydrolase) catalyzes the hydrolysis of alpha-D-(1,4)-glucosidic linkages in starch, glycogen, and various malto-oligosaccharides, by releasing alpha-anomeric products. In this study, a novel method has been developed to prepare nanoprotein particles that carry alpha-amylase as a monomer by using a photosensitive microemulsion polymerization process. The nanostructured alpha-amylase with photosensitive features have been characterized by fluorescence spectroscopy, transmission electron microscopy (TEM) and Zeta Sizer. The fluorescence intensity of amylase nanoparticles was determined to be 658 a.u. at 610 nm and the average particle size of nanoamylase was found to be about 71.8 nm. Both free alpha-amylase and nanoparticles were used in the hydrolysis of starch under varying reaction conditions such as pH and temperature that affect enzyme activity and the results were compared to each other. Km values were 026 and 0.87 mM and V-max values were 0.36 IU mg(-1) and 22.32 IU mg(-1) for nanoenzyme and free enzyme, respectively. Then, thermal stability, storage stability and reusability were investigated and according to the results, activity was preserved 60% at 60 degrees C; 20% at 70-80 degrees C temperature values and 80% after 105 days storage. Finally after 10 cycles, the activity was preserved 90% and this novel enzymatic polymeric amylase nanoparticle has showed considerable potential as reusable catalyst. (C) 2012 Elsevier B.V. All rights reserved