• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.145-166
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• 2021

M-learning is one of the most important modern learning environments in developed countries, especially in the context of the COVID-19 pandemic. According to the Ministry of Education policies in Saudi Arabia, gender segregation in education reflects the country's religious values, which are a part of the national policy. Thus, it will help many in the target audience to accept online learning more easily in Saudi society. The literature review indicates the importance to use the UTAUT conceptual framework to study the level of acceptance through adding a new construct to the model which is Mobile Application Quality. The study focuses on the end user's requirements to use M-learning applications. It is conducted with a qualitative method to find out the students' and companies' opinions who working in the M-learning field to determine the requirements for the development of M-learning applications that are compatible with the aspirations of conservative societies.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.41-50
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• 2011

In this study, we developed mobile contents and mobile learning system for learning of english presentation based on Android platform. First, the application including contents transfer system which enables contents run on Android platform was developed for learning of English presentation. Second, presentation contents which will be applied on the application were manufactured. The contents developed in this study are for learning English presentations. The contents are classified into two parts; Part 1 is for basic English presentations, and Part 2 is for advanced English presentations. Each part is made up with 9 units, and each unit is composed differently by topics. The number of whole chapter for both parts is 51. We analyzed the questionnaire responses with respect to UI satisfaction and satisfaction of the learning experience. The UI satisfaction results showed that 85% of the participants were satisfied at an ordinary or higher level with our system. And The satisfaction of the learning experience results showed that 95% of the participants were satisfied at the ordinary or higher level with our system.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.402-409
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• 2007

Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.426-431
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• 2009

Recently, the application of E-learning is changing the method that is able to process the learning to learner more efficiently and conveniently. For this purpose, the application research of U-learning that is able to support the learning using mobile device such as PDA, NetBook, Tablet PC and so on is actively processing. But lots of U-learning framework is only considering the change to fit the exist learning contents the mobile device without SCORM that is able to support to make and process the learning contents by regular forms. In this paper, we proposed the learning contents interconnection of U-learning framework considering SCORM. For this purpose, we have to construct the learning by learning object and asset within SCORM. And this method can support learning information that was reconstructed it by learning contents to fit the mobile device as used the mobile device meta-data.

• School Mathematics
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• v.19 no.3
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• pp.593-615
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• 2017

The purpose of this study is to develop a mobile-based math learning application and explore its application. In order to develop a learning application, the present study included literature review on math education involving mobile learning, investigation of literature related to mathematics education conducted in a digital environment, and method of use and implementation environment of existing math learning applications by type. Based on these preliminary investigation and analysis, an android version application, 'Mathematics Classroom for Middle School 3rd Graders' was developed. This application can be used for learning units such as Quadratic Functions and Graphs, Representative Value, and Variance and Standard Deviation. For the unit on Quadratic Functions and Graphs, the application was constructed so that students can draw various graphs by using the graphic mode and discuss their work with other students in the chatting room. For the unit on Representative Value, the application was constructed with the mathematical concept of representative value explained through animation along with activities of grouping data acquired after playing archery games by points or arranging them according to size so that students can study when and how to use median value, mode, and average. The application for Variance and Standard Deviation unit was also constructed in a way that allowed students to study the concept of variance and standard deviation and solve the problems on their own. The results of this study can be used as teaching & learning materials customized for individual student in math classes and will provide anyone the opportunity to engage in an interesting self-directed learning of math at anytime. Developed in the format of real life study, the application will contribute to helping students develop a positive attitude about math.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.133-138
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• 2011

This study investigates the usefulness of cellular and 'feature' phones in assisting students with self-motivated study at school and at home. It involves developing educational applications which can be used on these devices which, once developed, would be extended to students. Furthermore, this study seeks to investigate the merits of these mobile applications in assisting learners to study. It is my hope that this study can be used to develop the software to make these applications a reality. This study' ultimate purpose is to contribute to vitalizing and energizing mobile education.

• Journal of the Korean School Mathematics Society
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• v.25 no.1
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• pp.39-60
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• 2022

In this study, in order to support the expression of group creativity of high school students, we developed mathematics learning contents linked with mobile and online/offline that obtain the maximum and minimum values of the function within a limited range. This learning content was developed in connection with the 'environment', a cross-curricular learning topic. We explored the concept of group creativity in school mathematics. Its manifestation process, elements of group creativity expression process, and mobile and on/offline implementation functions were also explored. Then, we developed a hybrid app, 'Making the Best Box that Thinks of the Earth', which can express group creativity through mobile and online/offline-linked cooperative learning. A learning management system (LMS) and a teaching and learning guidance plan were also developed to efficiently operate mobile and online/offline-linked math learning using the app in schools. Our study found that the hybrid app, 'Creating the Best Box that Thinks of the Earth', was suitable for promoting collective fluency and collective sophistication based on complementary-metacognitive interaction.

• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.1-9
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• 2024

Communication with others plays an important role in human social interaction and information exchange in modern society. However, some individuals have difficulty in communicating due to dysarthria. Therefore, it is necessary to develop effective diagnostic techniques for early treatment of the dysarthria. In the present study, we propose a mobile device-based methodology that enables to automatically classify dysarthria type. The light-weight CNN model was trained by using the open audio dataset of Korean patients with dysarthria. The trained CNN model can successfully classify dysarthria into related subtype disease with 78.8%~96.6% accuracy. In addition, the user-friendly mobile application was also developed based on the trained CNN model. Users can easily record their voices according to the selected inspection type (e.g. word, sentence, paragraph, and semi-free speech) and evaluate the recorded voice data through their mobile device and the developed mobile application. This proposed technique would be helpful for personal management of dysarthria and decision making in clinic.

• Journal of IKEEE
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• v.24 no.4
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• pp.991-997
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• 2020

Reinforcement learning has been applied mainly in sequential decision-making problems. Especially in recent years, reinforcement learning combined with neural networks has brought successful results in previously unsolved fields. However, reinforcement learning using deep neural networks has the disadvantage that it is too complex for immediate use in the field. In this paper, we implemented path planning algorithm for mobile robots using Q-learning, one of the easy-to-learn reinforcement learning algorithms. We used real-time Q-learning to update the Q-table in real-time since the Q-learning method of generating Q-tables in advance has obvious limitations. By adjusting the exploration strategy, we were able to obtain the learning speed required for real-time Q-learning. Finally, we compared the performance of real-time Q-learning and DQN.