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    The evaluation of dream anxiety and sleep quality in hemodialysis patients
    (Kure Iletisim Grubu A.S., 2017) Selvi Y.; Ozdemir P.G.; Soyoral Y.; Tasdemir M.; Aslan M.
    Sleep problems are prevalent in hemodialysis patients. Although several studies have investigated the sleep quality and its causes in hemodialysis patients, there is no report available on dream anxiety in hemodialysis patients. The aim of this study was to evaluate the sleep quality and dream anxiety in hemodialysis patients. We also investigated related factors which influence sleep quality and dream anxiety. Fifty-Two hemodialysis patients and 38 healthy individuals were included in the present study. The sleep quality and dream anxiety were assessed with Pittsburgh Sleep Quality Index (PSQI) and Van Dream Anxiety Scale (VDAS); respectively. The majority of hemodialysis patients had poor sleep quality (%92.3) in our study. Hemodialysis patients had significantly longer sleep latency, higher sleep disturbances and daytime dysfunction than healthy individuals. Hemodialysis patients had higher global dream anxiety scores than healthy individuals. There was a negative relationship between hemoglobin levels and Global VDAS score. Global PSQI score was negative correlated with serum creatinine and phosphorus levels, while positive correlated with C-reactive protein levels. Our results suggest that hemodialysis patients had poor sleep quality, higher sleep disturbances and daytime dysfunction compared with healthy subjects. Moreover, we demonstrated that dream anxiety was significantly higher in hemodialysis patients.
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    An improved tree seed algorithm for optimization problems
    (International Association of Computer Science and Information Technology, 2018) Aslan M.; Beskirli M.; Kodaz H.; Kiran M.S.
    Various heuristic algorithms have been proposed in the literature for solving optimization problems. Tree-seed algorithm (TSA) is inspired from relation between trees and seeds that a population-based evolutionary algorithm. when create process of a seed occur in TSA, the position updating of each dimension of the seed is calculated separately. In scope this study, Some changes have been implemented to original TSA. A new operator was added to the position update equation of original TSA when create a seed from tree. This operator is calculated by dynamically according to the dimension of the problem. As the dimension of the problem increases, the value of the this operator decreases. In addition, we determined an upper and a lower bound for the update process of the seed. The Improved Tree Seed Algorithm (ITSA) proposed in this study and the TSA have been tested on some benchmark functions in the literature. As a result, when the experimental results are taken into consideration, it is understood that the proposed algorithm ITSA is obtained more effective results for benchmark functions than TSA. Moreover, it is observed that ITSA found quite successful results compared with TSA for large-scale benchmark problems. © 2018 International Association of Computer Science and Information Technology.