Utku Kose

An Augmented Reality Based Mobile Software to Support Learning Experiences in Computer Science Courses

Objective of this study is to improve educational processes in abstract or technical courses, by providing a mobile Augmented Reality (AR) tool. This tool is a mobile software system aiming to provide a supportive, e-learning material for students. By using the tool, students can view 3D animations, and special-made videos to have more idea about a course subject, or have a chance to improve their knowledge on the related course content. In order to achieve this, students are enabled to use mobile device camera interface on special signs placed in course books or any other supportive, physical materials that are given by course lecturers. Additionally, it is also possible to watch course materials after focusing on some physical objects in the real-life. Consequently, the software tool has aimed to ensure an effective learning experience by employing advantages of mobile devices and forming interactive sessions between virtual and real environment.

INTELLIGENT LEARNING ENVIRONMENTS WITHIN BLENDED LEARNING FOR ENSURING EFFECTIVE C PROGRAMMING COURSE

This paper describes a blended learning implementation and experience supported with intelligent learning environments included in a learning management system (LMS) called @KU-UZEM. The blended learning model is realized as a combination of face to face education and e-learning. The intelligent learning environments consist of two applications named CTutor, ITest. In addition to standard e-learning tools, students can use CTutor to resolve C programming exercises. CTutor is a problem-solving environment, which diagnoses students’ knowledge level but also gives feedbacks and tips to help them to understand the course subject, overcome their misconceptions and reinforce learnt concepts. ITest provides an assessment environment in which students can take quizzes that were prepared according to their learning levels. The realized model was used for two terms in the “C Programming” course given at Afyon Kocatepe University. A survey was conducted at the end of the course to find out to what extent the students were accepting the blended learning model supported with @KU-UZEM and to discover students’ attitude towards intelligent learning environments. Additionally, an experiment formed with an experimental group who took an active part in the realized model and a control group who only took the face to face education was performed during the first term of the course. According to the results, students were satisfied with intelligent learning environments and the realized learning model. Furthermore, the use of intelligent learning environments improved the students’ knowledge about C programming.

Optimization of self-learning in Computer Engineering courses: An intelligent software system supported by Artificial Neural Network and Vortex Optimization Algorithm

Self‐learning process is an important factor that enables learners to improve their own educational experiences when they are away of face‐to‐face interactions with the teacher. A well‐designed self‐learning activity process supports both learners and teachers to achieve educational objectives rapidly. Because of this, there has always been a remarkable trend on developing alternative self‐learning approaches. In this context, this study is based on two essential objectives. Firstly, it aims to introduce an intelligent software system, which optimizes and improves computer engineering students’ self‐learning processes. Secondly, it aims to improve computer engineering students’ self‐learning during the courses. As general, the software system introduced here evaluates students’ intelligence levels according to the Theory of Multiple Intelligences and supports their learning via accurately chosen materials provided over the software interface. The evaluation mechanism of the system is based on a hybrid Artificial Intelligence approach formed by an Artificial Neural Network, and an optimization algorithm called as Vortex Optimization Algorithm (VOA). The system is usable for especially technical courses taught at computer engineering departments of universities and makes it easier to teach abstract subjects. For having idea about success of the system, it has been tested with students and positive results on optimizing and improving self‐learning have been obtained. Additionally, also a technical evaluation has been done previously, in order to see if the VOA is a good choice to be used in the system. It can be said that the whole obtained results encourage the authors to continue to future works.

Educational material development model for teaching computer network and system management

Computer network and system management education is often structured based on theoretical information and it is not considered effective and efficient due to various reasons such as inadequacy of available materials and hardware. In addition, investors are reluctant to make investments on the provision of educational materials due to relatively high cost specific to this field. However, recent developments in virtualization technologies have led to the emergence of new trends in computer network and system management education. This paper provides information about the use of virtualization technology in computer network education, the utilization of real network devices, and defines a new generation network training platform. The aim of the study is to offer a new model using virtualization technology for network‐based computer education. The topology additionally proposed here involves the use of real hardware instead of virtual ones, which distinguishes it from the similar topologies. This model is expected to guide future network and system managers to develop and use a real network and system management training platform that is far more effective than simulation programs.

Underwater image enhancement based on contrast adjustment via differential evolution algorithm

Due to the absorption and scattering of light in underwater environment, underwater images have poor contrast and resolution. This situation generally causes to a color, which became more dominant than the other ones. Because of that, analyzing underwater images effectively and identifying any object under the water has become a difficult task. In this paper, an underwater enhancement approach by using differential evolution algorithm was proposed. In the approach, a contrast enhancement in the RGB space is done. By using the approach, both scattering and absorption effects are reduced.

Artificial Intelligence Applications in Distance Education

As a result of the rise of modern knowledge society, it has been highly required to have newer approaches and innovations in the sense of educational processes. Because of this, different methods and technologies have appeared to make the expressed requirements real. At this point, information and communication technologies have had a great role in remarkable improvements. From this perspective, the Distance Education approach and its related techniques like ELearning, M-Learning...etc. are popular and strong elements for today’s world. In addition to the related effectiveness of the E-Learning, researchers also perform more scientific studies to support E-Learning or improve its functions and features to provide better conditions within the learning and teaching process. Today, one of the most remarkable improvement ways is using Artificial Intelligence techniques to support classical Distance Education approaches-techniques or develop newer ones to continue development of the subject area.

Diabetes determination via vortex optimization algorithm based support vector machines

Approaches performed based on computer supported systems within the medical field gain more popularity day by day. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics. Diabetes is one of these diseases. In this study, a diabetes diagnosis system based on Support Vector Machines has been proposed. Along training of SVM, Vortex Optimization Algorithm was used for determining the sigma parameter of the Gauss (RBF) kernel function, and a classification process has been done over the diabetes data set related to Pima Indians.

Design and Development of a Chaos-Based Image Encryption System

In the context of cryptography applications, using Chaos-based approaches, methods and techniques for image-based data have become an efficient and important way to design and develop strong security solutions, in especially recent years. At this point, many different scientific research studies are performed in or-der to provide newer cryptographic systems and ensure effective directions for obtaining more secure data storing and sharing. In parallel, this study introduces a basic, simple Chaos-based image encryption system, which employs chaotic systems to form a mathematical and algorithmic infrastructure for data security.

On the State of Free and Open Source E-Learning 2.0 Software

Objective of this article is to provide a brief view on current state of free and open source E-Learning 2.0 software, and discuss about future in the context of free and open source software oriented E-Learning solutions. E-Learning 2.0 is a term, which is used to define E-Learning solutions combining the usage of Web 2.0 technologies, and the related E-Learning aspects, which are widely employed in educational processes. Because it is a current form of E-Learning activities, E-Learning 2.0 and leading free and open source software have been examined briefly under this work; in order to have idea about literature, and the latest developments. Furthermore, some ideas on future of free and open source E-Learning software are also expressed by thinking about potential versions of E-Learning such as E-Learning 3.0, and E-Learning 4.0.

A Novel Underwater Image Enhancement Approach with Wavelet Transform Supported by Differential Evolution Algorithm

In this paper, a novel underwater image enhancement approach was proposed. This approach includes use of a method formed by the wavelet transform and the differential evolution algorithm. In the method, the contrast adjustment function was applied to the original underwater image first. Then, the homomorphic filtering technique was used to normalize the brightness in the image. After these steps, the underwater image was separated into its R, G, and B components. Then wavelet transform function was performed on each of the R, G, and B channels with Haar wavelet decomposition. Thus, detailed images were obtained for each of the color channels by wavelet transform low-pass approximation (cA), horizontal (cH), vertical (cV) and diagonal (cD) coefficients. Four parameters of weights (w) of each component cA, cH, cV, and cD situated in the R, G, and B color channels were optimized using differential evolution algorithm. In the proposed method, differential evolution algorithm was employed to find the optimum w parameters for Entropy and PSNR in separate approaches. Finally, unsharp mask filter was used to enhance the edges in the image. As an evaluation approach, performance of the proposed method was tested by using the criteria of entropy, PSNR, and MSE. The obtained results showed that the effectiveness of the proposed method was better than the existing techniques. Likewise, the visual quality of the image was also improved more thanks to the proposed method.