• International Journal of Advanced Culture Technology
• /
• v.9 no.3
• /
• pp.100-105
• /
• 2021

This study examines the effectiveness of the study through a case of PBL(problem-based-learning) class conducted in a balanced culture course called at 00- University in the second semester of 2020. The effects of learning are as follows: First, PBL(problem-based-learning) has sufficient active interaction between the teacher and the learner. In the face of prolonged non-face-to-face learning, the PBL teaching method has sufficient interaction between the professors-learner and the learner. Second, PBL learning can actively utilize various problems that fit the characteristics of the subject and actively utilize the process of role sharing and collaboration. By presenting various problem situations suitable for the subject, students will be able to share roles individually or as a team, and fully experience the process of collaboration and discussion in the process of investigating the data. Third, critical perceptions of problem situations can be extended. In modern times, a variety of problem situations arise and critical perceptions of them must be fully learned. In a mass production and mass consumption society, students should develop the ability to blindly recognize and distinguish between real and fake information in a flood of information. The limitations identified in this class case are, first, the nature of the subject, "Understanding Culture and Philosophy," which makes it possible to discuss the global cultural phenomenon, but it should be discussed in terms of philosophy. Second, it is not easy to work as a team on non-face-to-face online. Nevertheless, PBL is a very effective method of learning in which active interactions and learning activities take place between professors and students, whether face-to-face or face-to-face online learning.

• Journal of Practical Engineering Education
• /
• v.14 no.1
• /
• pp.91-97
• /
• 2022

Recently, as per a representative education method to develop core capabilities (such as critical thinking, communication, collaboration, and creativity) problem based learning (PBL) has been widely adopted in universities. Two important features of PBL are 'collaboration between team members' and 'participation based self-directed learning'. These two features should be satisfied in online education, although it is difficult due to the limitation on space and time in the COVID-19 pandemic. This paper presents a new design of PBL class in Metaverse, based on improving the online PBL class operated in the previous semesters in the H university. In the proposed PBL class, students are able to display materials (e.g., image, pdf, video files) in 3D virtual space, that are related to problem solving. The 3D virtual space is called gallery in this paper. The concept of gallery allows for active participation of students. In addition, the gallery can be used as a tool for collaborative meeting or for final presentation. If possible, the new design of PBL class will be applied and its effectiveness will be analyzed.

• Journal of the Korea Convergence Society
• /
• v.11 no.8
• /
• pp.139-145
• /
• 2020

Due to the rapid development of computer technology, online learning using ICT technology is already quickly settling in our lives. Music education was conducted mainly in an offline-based environment, but research is being conducted to switch to online because there is no time and space constraint of online education and interactive education led by learners is possible. In this study, we propose design and implement an adaptive learning system to enable adaptive learning online among music education. This system has the following advantages. First, by providing an LMS-based platform, one can solve the social education problem corresponding to economic and geographical factors. Second, both objective learning feedback provided automatically by the online adaptive harmony learning system and teaching feedback. Third, learners can be provided with recommended answers to given harmony exercises. The adaptive online learning system of harmony will lead professors and learners to effectively teach and study.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.3
• /
• pp.145-152
• /
• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.

• Journal of Service Research and Studies
• /
• v.13 no.3
• /
• pp.105-126
• /
• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.2
• /
• pp.49-58
• /
• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.

• Journal of Information Technology Services
• /
• v.17 no.2
• /
• pp.165-177
• /
• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Journal of Engineering Education Research
• /
• v.26 no.4
• /
• pp.36-46
• /
• 2023

This paper presents a case study and online-offline (hybrid) course structure for project-oriented community-based service learning in order to solve real-world problems for society. It examines social issues and conduct student projects to develop solutions that can generate sustainable value. This course helps students to use their major knowledge to assess and solve the problems faced by the local community. The outcomes of this course conducted via online lectures and offline project activities are discussed. The operation of this blended type of social problem-solving course is also stated.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.330-333
• /
• 2005

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.305-318
• /
• 2022

Abusive behaviors have become a common issue in many online social media platforms. Profanity is common form of abusive behavior in online. Social media platforms operate the filtering system using popular profanity words lists, but this method has drawbacks that it can be bypassed using an altered form and it can detect normal sentences as profanity. Especially in Korean language, the syllable is composed of graphemes and words are composed of multiple syllables, it can be decomposed into graphemes without impairing the transmission of meaning, and the form of a profane word can be seen as a different meaning in a sentence. This work focuses on the problem of filtering system mis-detecting normal phrases with profane phrases. For that, we proposed the deep learning-based framework including grapheme and syllable separation-based word embedding and appropriate CNN structure. The proposed model was evaluated on the chatting contents from the one of the famous online games in South Korea and generated 90.4% accuracy.