In today's World; the speed of access for information is increased global competition in the business world as in the case of many areas. So, it becomes more difficult to find constant and regular business for employers. For Countries to compete on international markets; it is only possible with well-trained workforce professional and technical competence. The global financial crisis which occurred over eight years ago, in 2008, the number of unemployed people still could not land on pre-crisis period. On the other hand, the demand of qualified labor-intensive businesses is not decline despite of the open job positions. On the one hand; the continuous increasing in the number of unemployment is occurred, on the other hand; demand for qualified labour force is increased. This status shows that there is a problem between vocational training and labour market. In this study; our country's vocational education and employment issues can be determined by examining the relationship between them. Also, the problem and the solutions for the field will be examined.

Keywords: Employment, Vocational Education, Aircraft Maintenance.

Özet

Günümüz dünyasında bilgiye erişim hızının artması; birçok alanda olduğu gibi iş dünyasında da küresel rekabeti artırmış,  ülke nüfusunun sürekli ve düzenli iş bulmasını güçleştirmiştir. Ülkelerin uluslararası piyasalarda rekabet edebilmesi; çok iyi yetişmiş mesleki ve teknik yeterliliğe sahip işgücüyle mümkün olabilmektedir. Küresel piyasalarda 2008 krizinin üzerinden sekiz yıl geçmesine rağmen işsiz insan sayısı hala kriz öncesi döneme inememiştir. Diğer taraftan ise işletmeler nitelikli işgücüne yoğun bir talep göstermesine rağmen açık iş pozisyonunda bir düşüş olmamaktadır. Bir yandan işsiz sayısının devamlı artması, öte yandan nitelikli işgücüne artan talep; mesleki eğitim ile işgücü piyasası arasında eşgüdüm sorununun olduğunu ortaya koymaktadır. Bu çalışmada; bilgi toplumu olma yolunda çaba sarf etmesi gereken ülkemizin mesleki eğitim ve istihdam konuları incelenerek aralarındaki ilişki ifade edilecek, sorun sahalarına ilişkin çözüm yolları irdelenecektir.

Anahtar Kelimeler: Mesleki eğitim, İstihdam, İşgücü.

Individuals should possess problem solving skills to reach the desired aims in their life. Because of this, this skill is believed as a critical item of education. The purpose of the present study was to examine if there is a meaningful relationship between the high school students’ problem solving skills according to their gender, the types of high school, departments, and classes. This study was conducted during 2016-2017 academic year with the participation of 181 female and 193 male students studying at Zubeyde Hanim Vocational and Technical Anatolian High School and Gazi Industrial Vocational High School. The information about the ability to study was gathered through a questionnaire developed by Heppner and Peterson (1982) and adapted in Turkish by Sahin, Sahin and Heppner (1993). Data were analysed using One-Way ANOVA, t-test, and the Scheffe’s test. According to ANOVA results, it was seen that the department differentiation influenced their problem solving skills, while class differentiation did not have any effect on their problem solving skills. Also, T-test results indicated that their high schools and gender are significant variables on students’ problem solving skills. 

The two-layer network structure has been widely adopted in wireless sensor networks (WSNs) for managing sensor nodes. In such a structure, the low layer nodes communicate with their cluster head, followed by the cluster-head nodes communicating with the base station operating in either a one hop or a multi-hop manner. The main focus of node-clustering algorithms is minimizing energy consumption due to strictly limited resources in WSNs. Also, WSNs are data intensive networks with the capability of providing users with accurate data. Unfortunately, data missing is common in WSNs. In this paper, we propose a novel joint design of sensor nodes clustering and data recovery, where the WSNs is organized in a two-layer manner with our developed clustering algorithm, and then the missing data is recovered based on this two-layer structure. Furthermore, in the proposed clustering algorithm, we take both the energy-efficiency and data forecasting accuracy into consideration and investigate the tradeoff between them. This is based on the key observation that the high energy-efficiency of the network can be achieved by reducing the distances among the nodes in a cluster, while the accuracy of the forecasting results can be improved by increasing the correlation of the data stream among the nodes in a cluster. Simulation results demonstrate that our joint design outperforms the existing algorithms in terms of energy consumption and forecasting accuracy.