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.

Eliminating language barriers online at European prisons (ELBEP): A case-study

Abstract: ELBEP (Eliminating Language Barriers in European Prisons Through Open and Distance Education Technology) is a multilateral project funded by the European Union (EU) Lifelong Learning, Grundtvig (Adult Education) Programme. It aims to overcome language/communication problems between prison staff and foreign inmates at European prisons via online language teaching programs for the staff. This paper discusses the rationale and application of the project with an eye to the related literature and theoretical background. The project outcomes and findings can serve as an example for similar research studies.

Sosyal Yenilikçilik: Bir Ölçek Geliştirme Çalışması

Abstract: Ozellikle 1990’dan sonra bilimsel calismalarin yogunlastigi sosyal yenilikcilik kavrami insanlarin hayat standartlarini ve refahlarini yukseltebilmek, daha once karsilanmamis ihtiyaclara cozum onerileri ya da yeni fikirler sunabilmek olarak tanimlanmaktadir. Bu calismanin amaci, Turk kulturune uygun, birey duzeyinde gecerli ve guvenilir bir sosyal yenilikcilik olceginin gelistirilerek ozellikle Yonetim yazinina kazandirilmasidir. Bu dogrultuda, anket yonteminin kullanildigi, farkli cografi ve sosyo-ekonomik bolgelerden universitelerin farkli fakultelerinden son sinif ogrencilerinin katildigi bir saha calismasi tasarlanmistir. Yapilan analizler sonucu tek boyutlu, sekiz maddeden olusan gecerli ve guvenilir bireysel sosyal yenilikcilik egilimini olcen bir olcek gelistirilmistir.

Multiwavelet feature sets for ECG beat classification

Abstract: In this study, heart beats are classified as normal, right branch block, left branch block, and paced rhythm using electro cardiographic (ECG) signals obtained from the MIT-BIH cardiac arrhythmia database. Average, standard deviation, energy and entropy of discrete wavelet transform (DWT) coefficients are proposed as the features for the classification. The classification was performed by selecting the appropriate train function of artificial neural network. It has been observed that the combined use of two different feature sets from two wavelet families with the appropriate train function of neural network is better than use of individual wavelets features.

The Stance Logistics: An Attempt to Adapt Logistics Principles on Human and Inter-human Movement Behaviors

Abstract: The broad span of Logistics Management encompasses control of time, place, movement, energy (efforts, labor), as well as the positioning, stance and movement of products, materials, commodities, and people. This study coins the term Stance Logistics to focus on the stance and movement of people within the range of Logistics principles. The philosophy behind this is to enhance the required sensitivity with respect to management and control of time, place, movement, motion, stance and energy in material and nonmaterial exchanges and in all types of human encounters. Stance Logistics includes not only the “on foot” (pedestrian) or “in-vehicle” (automated) movements and public behaviour in stopping, standing, and positioning, but also individual predisposition of physical and mental response, and awareness (aesthesia). This essay describes the application of the scientific principles of Logistics to the personal experiences of people. Current Logistics literature includes mostly models developed on pedestrian and evacuation movement behaviour. To the author’s knowledge, however, there is nothing documented on the issue of personal individual Logistics Stance. Behaviours, especially that of blocking other people’s ways and passages, intervening, rudeness and queue-jumping in various environmental settings have not been extensively studied, if at all, whether during walking, pausing, stopping, face-to-face encounters, standing or waiting in lines and lanes or waiting for an elevator or metro train door to open. This study seeks underlying clues to increase sensitivity and awareness of people’s movement particularly in public areas by shedding light on Logistics behaviours of people. When combined with applicable models of pedestrian movements and integrated with the general principles of Logistics, Stance Logistics can serve as an important guide to facilitate the daily activities of many people. It is believed that, this exploratory study will pave the way for further research to produce promising results on the aspects of this new concept of Stance Logistics

Structure Learning of Bayesian Networks Using Elephant Swarm Water Search Algorithm

Abstract: Bayesian networks are useful analytical models for designing the structure of knowledge in machine learning. Bayesian networks can represent probabilistic dependency relationships among the variables. One strategy of Bayesian Networks structure learning is the score and search technique. The authors present the Elephant Swarm Water Search Algorithm (ESWSA) as a novel approach to Bayesian network structure learning. In the algorithm; Deleting, Reversing, Inserting, and Moving are used to make the ESWSA for reaching the optimal structure solution. Mainly, water search strategy of elephants during drought periods is used in the ESWSA algorithm. The proposed method is compared with simulated annealing and greedy search using BDe score function. The authors have also investigated the confusion matrix performances of these techniques utilizing various benchmark data sets. As presented by the results of the evaluations, the proposed algorithm has better performance than the other algorithms and produces better scores and accuracy values. KEyWoRdS Bayesian Network, Elephant Swarm, Global Search, Local Search, Search and Score Structure Learning, Water Search