The fast developments in the computer technology and the internet becoming common in every part of our lives especially in recent years have become indispensable in the teaching and learning field of students and instructors. Web-based studies have brought innovations also in the education field and in this field, various applications have become common. This study covers the technical and functional features of the online exam system carried out and being used in Selcuk University Higher School of Vocational and Technical Sciences. The automation was set up on a database system and the administrator, academician and students can access the system over the web server. The software which is dynamical structure and application simplicity working on the web server (in the web environment) can be applied on the exams of the students who take different courses in the higher school. The Online Exam System (OES) that was created enables instructors to make question banks with the choices of using shapes, multiple choice and multiple answers and to evaluate the applied exams instantaneously. OES, instant evaluation of examinations and gives students the opportunity to watch the performance. Via OES, positive contributions are provided for both the instructors and the students in terms of particularly place and time in the education field.
In the present paper, loxodromes, which cut all meridians and parallels of twisted surfaces (that can be considered as a generalization of rotational surfaces) at a constant angle, have been studied in Euclidean 3-space and some examples have been constructed to visualize and support our theory.
Compressive strength of concrete is one of the most important elements for an existing building and a new structure to be built. While obtaining the desired compressive strength of concrete with an appropriate mix and curing conditions for a new structure, with nondestructive testing methods for an existing structure or by taking core samples the concrete compressive strength are determined. One of the most important factors that affects the concrete compressive strength is age of concrete. In this study, it is attempted to estimate compressive strength, modelling Artificial Neural Networks (ANN) and using different mixture ratios and compressive strength of concrete samples at different ages. In accordance with obtained data's in the estimation of concrete compressive strength, ANN could be used safely.
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