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.

Evolutionary computation for architectural design of restaurant layouts

Abstract: This paper presents the results obtained by NSGA-II and DE on a restaurant layout optimization problem, trying to maximize total profit while minimizing investment. The problem entails the configuration of restaurant functions, the decisions regarding the restaurant shell composition (fraction and position of windows, dimensions), and how to shape and place the kitchen and service areas. The NSGA-II and DE algorithms are implemented in a Parametric Design Environment that is familiar in the architectural practice. We demonstrate that the DE algorithm achieves slightly better performance in terms of hypervolume calculation, and achieve promising results when the Pareto front approximation is examined. To the best of our knowledge, this is the first application of multi-objective approach for restaurant design.

Addressing the high-rise form finding problem by evolutionary computation

Abstract: This paper aims to examine the application of evolutionary algorithms to the form finding problem of high-rise buildings. In the light of mentioned purpose, this study concentrates on the conceptual phase of the design process due to the importance of early design decisions. In this respect, multiobjective real-parameter constrained optimization is considered as the method of this study in order to solve high-rise design problem. From the point of evolutionary computation, we compare two evolutionary algorithms (NSGA-II and DE) focusing on their computational performance and architectural features of the resulting alternatives. Two objective functions are formulated that specifically focus on structural displacement minimization and construction cost per square meter minimization, which are clearly conflicting. As a conclusion, we discuss in the context of the high-rise design problem, the solutions identified by the NSGA-II and DE algorithms.

Feature Selection and Classification of EEG Finger Movement Based on Genetic Algorithm

Abstract: Electroencephalography (EEG) classification for mental tasks is the crucial part of the braincomputer interface. Many studies try to extract discriminative features from EEG signals. In this study, feature selection algorithm based on genetic algorithm (GA) was implemented to find the best features that describe EEG signal. The best features are searched among ten statistical features calculated from the cross-correlation of effective channel with relevant EEG channels in the proposed study. A comparison was made after and before feature selection in two major viewpoints: classification accuracy and computation time. Multi-Layer Perceptron Neural Network (MLP) and Support Vector Machine (SVM) are used to classify left and right finger movements of 13 subjects. The overall classification performance is enhanced about 1% for both classifiers after feature selection. Computation time has reduced about 34% in SVM classifier and there is huge reduction about 84 % in MLP.

The effects of mass customisation on productivity

Abstract: In the last two decades, demanding customers put manufacturing industries under the pressure of customised product orders. This market condition forced manufacturers to follow and adopt a customer-oriented philosophy. Therefore, some manufacturing industries began to change their business processes accordingly to actualise mass customisation systems. It can be inferred from this that such a big technical change must have a great impact on productivity. Therefore, this study aims to analyse the effects of the Mass Customisation (MC) concept on productivity. To measure the productivity change in the manufacturing industries of Turkey, the Two-Deflator Growth Accounting Approach is applied. In this frame, MC and Mass Production (MP) industries were compared according to their value-added, capital contribution, labour contribution and productivity. The findings contradict the current literature and imply that the price of customised products is higher. In this frame, to enhance productivity and lessen the price, some suggestions that are related to human quality upgrades and technical changes are provided.

Do Changes in Threat Salience Predict the Moral Content of Sermons? The Case of Friday Khutbas in Turkey

Abstract: Moral Foundations Theory (MFT; Haidt, 2007) has introduced a par‐ adigmatic change in the field of moral psychology by defining ethics around five different foundations. MFT criticizes pre‐existing theo‐ ries for having a Western and liberal bias and argues that morality is not only about individual rights and duties; rather, ingroup‐related moral foundations are also at the heart of moral judgments. The value given to these specific “core” moral foundations is affected by a number of contextual variables. The most important of these is the perception of threat. Although there are many studies in the literature investigating the relationship between threat perception and moral foundations (e.g., Van Leeuwen & Park, 2009), to our knowledge, there is a dearth of empirical studies on whether the theory has predictive power over the applied field data of long‐term fluctuations (cf. Van de Vyver, Houston, Abrams, & Vasiljevic, 2015). This study examines whether the level of perceived threat across the country would lead to the increased endorsement of binding moral foundations in societal‐level data. We used the content of “Friday Khutbas” delivered in Turkish mosques between January 2001 and June 2018 and investigated whether the emphasis on the binding foundations in the khutbas would increase with the societal‐level threats.