Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

The role of childhood emotional maltreatment and body image dissatisfaction in problematic smartphone use among adolescents.

Abstract: Growing empirical evidence has identified specific psychological and contextual risk factors associated with problematic smartphone use (PSU). However, the potential direct and indirect impact of childhood emotional maltreatment (CEM) on PSU remains largely unexplored, despite the established role of CEM in the onset of other excessive, problematic, and addictive behaviors. Consequently, the purpose of the present study was to test the direct and indirect relationships of emotional abuse and neglect (two facets of CEM) with PSU via specific mediational pathways including body image dissatisfaction (BID), social anxiety, and depression. The sample comprised 443 adolescents who completed a questionnaire that included assessment tools of aforementioned variables. Multiple mediation model results indicated that CEM was directly and indirectly associated with PSU via BID, depression, BID-related depression, and BID-related social anxiety. Results suggested that emotionally traumatic experiences were associated with PSU in adolescents and that this relationship may partially be explained by BID and psychosocial risk factors. The present study draws caution to the amplifying roles of CEM and BID on increased PSU. The results of the study have important clinical and public health implications, but additional research is needed before interventions can be developed and implemented on the basis of present results.

Classification of EEG Recordings by Using Fast Independent Component Analysis and Artificial Neural Network

Abstract: Since there is no definite decisive factor evaluated by the experts, visual analysis of EEG signals in time domain may be inadequate. Routine clinical diagnosis requests to analysis of EEG signals. Therefore, a number of automation and computer techniques have been used for this aim. In this study we aim at designing a MLPNN classifier based on the Fast ICA that accurately identifies whether the associated subject is normal or epileptic. By analyzing a data set consisting of 100 normal and 100 epileptic EEG time series, we have found that the MLPNN classifier based on the Fast ICA achieved and sensitivity rate of 98%, and specificity rate of 90.5%. The results demonstrate that the testing performance of the neural network diagnostic system is found to be satisfactory and we think that this system can be used in clinical studies. Since the time series analysis of EEG signals is unsatisfactory and requires specialist clinicians to evaluate, this application brings objectivity to the evaluation of EEG signals.

A differential evolution algorithm for the no-idle flowshop scheduling problem with total tardiness criterion

Abstract: In this paper, we investigate the use of a continuous algorithm for the no-idle permutation flowshop scheduling (NIPFS) problem with tardiness criterion. For this purpose, a differential evolution algorithm with variable parameter search (vpsDE) is developed to be compared to a well-known random key genetic algorithm (RKGA) from the literature. The motivation is due to the fact that a continuous DE can be very competitive for the problems where RKGAs are well suited. As an application area, we choose the NIPFS problem with the total tardiness criterion in which there is no literature on it to the best of our knowledge. The NIPFS problem is a variant of the well-known permutation flowshop (PFSP) scheduling problem where idle time is not allowed on machines. In other words, the start time of processing the first job on a given machine must be delayed in order to satisfy the no-idle constraint. The paper presents the following contributions. First of all, a continuous optimisation algorithm is used to solve ...