No abstract

Dimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization problems have been solved for high stiffness and low coefficients of thermal and moisture expansion. Some of the results based on efficient global optimization solution have been verified by genetic algorithm, simulated annealing, and generalized pattern search solutions from the previous studies. The proposed optimization algorithm is also validated experimentally. After completing the design and optimization process, failure analysis of the optimized composites has been performed based on Tsai-Hill, Tsai-Wu, Hoffman, and Hashin-Rotem criteria.

Predictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn't only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural network (DNN) architecture proposed in this study intends to bring a different approach to the predictive maintenance domain.There is an input layer in this architecture, a Long-Short term memory (LSTM) layer, a dropout layer (DO) followed by an LSTM layer, a hidden layer, and an output layer. The number of epochs used in the architecture and the batch size was determined using the Genetic Algorithm (GA). The activation function used after the output layer, DO ratio, and optimization algorithm optimizes loss function determined by using grid search (GS). This approach brings a different perspective to the literature for finding optimum parameters of LSTM. The neural network and hyperparameter optimization approach proposed in this study performs much better than existent studies regarding LSTM network usage for predictive maintenance purposes

Öz: Türkiye'de sosyo-kültürel nedenlerle yaşam gidişindeki önemli olaylardan birisi evliliktir ve bu olay bireylerin göç davranışını tetiklemektedir. Türkiye'de 1995Türkiye'de -2000

In recent years, one of the hottest debates on Turkish economy is the conflict on resource allocation between real estate and industry sectors. The debate was so intense that ex-minister of Economy Mr. Ali Babacan declared his opinions. Mr. Babacan's statements about the creation of fixed capital by the private sector is not promising, and private sector fixed capital expenditures are not in the desired level. This situation is due to the limited economic growth and future economic growth. In this study, we have investigated whether Mr. Babacan's statement is right or not. We have discussed the reliability of the measurement of real estate output as Gruneberg and Folwell did in 2013 and Ruddock did in 2002. That could be concluded that we agree with ex-minister of Economy Mr. Babacan's comments regarding to imbalances among sectors are threatening Turkish economy's stability. The imbalances are favoring residential real estate investments and consequently the country is exposed to currency risk.