• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.125-136
• /
• 2021

The development of systems that can generate automatically instructional material is a challenging goal for the e-learning community. These systems pave the way towards large scale e-learning deployment as they produce instruction on-demand for users requesting to learn about any topic, anywhere and anytime. However, realizing such systems is possible with the availability of vast repositories of web information in different formats that can be searched, reused and integrated into information-rich environments for interactive learning. This paradigm of learning relieves instructors from the tedious authoring task, making them focusing more on the design and quality of instruction. This paper presents a mobile learning system (Mole) that supports the generation of instructional material in M-Learning (Mobile Learning) contexts, by reusing and integrating heterogeneous hypermedia web resources. Mole uses open hypermedia repositories to build a Learning Web and to generate learning objects including various hypermedia resources that are adapted to the user context. Learning is delivered through a nice graphical user interface allowing the user to navigate conveniently while building their own learning path. A test case scenario illustrating Mole is presented along with a system evaluation which shows that in 90% of the cases Mole was able to generate learning objects that are related to the user query.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.2
• /
• pp.282-287
• /
• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• The Journal of the Korea Contents Association
• /
• v.20 no.3
• /
• pp.452-461
• /
• 2020

The purpose of this study is to identify how learners perceive mobile technology-based learning materials. For this purpose, two methods were utilized. Using multi-dimensional scale(MDS), it was identified that how learners perceive each type of learning materials using mobile technology. Through semantic differential scale(SDS), learners' perception of the difference between mobile learning materials and existing traditional learning materials was analyzed. As a result, learning materials using mobile technology were classified into as follows : the dimension of interaction with the content; the sense of presence. Learners perceived that mobile learning materials had characteristics of 'active', 'learner-centric', 'multi-sensory', and 'stimulating interest'. The significance of this study was to empirically and comprehensively investigate learners' perception for the characteristics of various mobile learning materials.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.6
• /
• pp.1369-1380
• /
• 2011

Most existing mobile distance learning systems are asynchronous ones that allow students to download lecture video and presentation material. However, there are a few synchronous real-time mobile distance learning systems that support slide, annotation, feedback from student, and lecture video and audio at the same time. These live mobile distance learning systems have an advantage of supporting real-time interaction between students and a lecturer thereby making students understand the lecture better. But, they also have a disadvantage in the sense that they don't allow students to experience the past lecture. This problem can be solved by recording and replaying lecture session. So far, there are few mobile distance learning systems that support session recording and replay. This paper presents a synchronous mobile distance learning system that supports video and audio, slide with annotation, and real-time feedback from students, as well as session recording and replay, which is not supported by the existing mobile distance learning systems. The evaluation of the system among students shows that 61.3% of them were satisfied while 3.2% weren't.

• Journal of Information Processing Systems
• /
• v.20 no.4
• /
• pp.558-573
• /
• 2024

Considering factors such as illumination, camera quality variations, and background-specific variations, identifying a face using a smartphone-based facial image capture application is challenging. Face Image Quality Assessment refers to the process of taking a face image as input and producing some form of "quality" estimate as an output. Typically, quality assessment techniques use deep learning methods to categorize images. The models used in deep learning are shown as black boxes. This raises the question of the trustworthiness of the models. Several explainability techniques have gained importance in building this trust. Explainability techniques provide visual evidence of the active regions within an image on which the deep learning model makes a prediction. Here, we developed a technique for reliable prediction of facial images before medical analysis and security operations. A combination of gradient-weighted class activation mapping and local interpretable model-agnostic explanations were used to explain the model. This approach has been implemented in the preselection of facial images for skin feature extraction, which is important in critical medical science applications. We demonstrate that the use of combined explanations provides better visual explanations for the model, where both the saliency map and perturbation-based explainability techniques verify predictions.

• Journal of Drive and Control
• /
• v.19 no.4
• /
• pp.62-69
• /
• 2022

Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

• The Journal of the Korea Contents Association
• /
• v.19 no.2
• /
• pp.88-98
• /
• 2019

As the 2015 revised curriculum is being implemented from 2018, efforts are being made to cultivate scientific literacy among students in the field of science. Scientific experiments help students to develop their interest in Science and their scientific attitudes. Learning through experimentation rather than learning scientific facts increases learners' understanding, and can be remembered longer. Therefore, experiments in Science subject are very important. However, in middle schools, scientific experiments are not performed due to the lack of time, budget and experimental material. In this research, we analyze middle school science textbooks, conduct questionnaires for students of science pre-service teachers, select the most important science experiments, and develop a mobile App to simulate and experience scientific experiments with the App. The proposed App is developed in a game format using quest-based learning methods to gain learning enhancement. It is also made using Unity. In this paper, after developing the app, we propose the direction of STEAM contents development through analyzing the difference from existing apps and the feedback from users.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.7
• /
• pp.29-36
• /
• 2021

In this paper, we classify ECG signal data for mobile devices using deep learning models. To classify abnormal heartbeats with high accuracy, three factors of the deep learning model are selected, and the classification accuracy is compared according to the changes in the conditions of the factors. We apply a CNN model that can self-extract features of ECG data and compare the performance of a total of 48 combinations by combining conditions of the depth of model, optimization method, and activation functions that compose the model. Deriving the combination of conditions with the highest accuracy, we obtained the highest classification accuracy of 97.88% when we applied 19 convolutional layers, an optimization method SGD, and an activation function Mish. In this experiment, we confirmed the suitability of feature extraction and abnormal beat detection of 1-channel ECG signals using CNN.

• International Journal of Contents
• /
• v.18 no.2
• /
• pp.47-57
• /
• 2022

e-Learning content can be defined as digital content to achieve educational goals. Since it is an educational material that can be distributed in offline, online, and mobile environments, it is important to create content that meets the learner's education environment and educational goals. In particular, if the learner is a public official, the vision, philosophy, and characteristics of each local government must reflect. As non-face-to-face online education expands further due to the COVID-19 pandemic, local governments that have relied on onsite education in the past urgently require developing strong basic competency education and special task competency content that reflect regional characteristics. Such e-learning content, however, hardly exists and the ability to independently develop them is also insufficient. In this circumstance, this case study describes the process of self-production of e-learning content suitable for Busan's characteristics by the Human Resource Development (HRD) Institute of Busan City, a local government. The field of instructional design and instructional technology is always evolving and growing by blending technological innovation into instructional platform design and adapting to the changes in society. Busan HRD Institute (BHI), therefore, tried to implement blended learning by developing content that reflected the recent trend of micro-learning in e-learning through a detailed analysis. For this, an e-learning content developer with certain requirements was selected and contracted, and the process of developing content through a collaboration between the client and developer was described in this study according to the ADDIE model of Instructional Systems Development (ISD).

• Research in Mathematical Education
• /
• v.4 no.1
• /
• pp.45-55
• /
• 2000

The rapid proliferation of wireless networks provides a ubiquitous channel for delivering instructional materials at the convenience of the user. By delivering content through portable devices linked to the Internet, the full spectrum of multimedia capabilities is available for engaging the user's interest. This capability encompasses not only text but images, video, speech generation and voice recognition. Moreover, the incorporation of machine learning capabilities at the source provides the ability to tailor the material to the general level of expertise of the user as well as the immediate needs of the moment: for instance, a request for information regarding a particular city might be covered by a leisurely presentation if solicited from the home, but more tersely if the user happens to be driving a car. This paper presents system architecture to support mobile instruction in conjunction with knowledge-based tutoring capabilities. For concreteress, the general concepts are examined in the context of a system for mathematics education on the Web.