• The Transactions of the Korea Information Processing Society
• /
• v.6 no.5
• /
• pp.1177-1188
• /
• 1999

Continuing advance in computers and MIDI devices has accelerated research on the computerized music technology, Realization of high speed computer communication networks facilitated on-line computer music systems, which needs to send a volume of multimedia data. This paper presents the design and implementation of the Remote Concert Education System which helps users practice ensemble without gathering in a room. The system maintains the music database, identifies tones and measures of the melody played with different instruments, check the correctness on-line, and finally provides the analysed results of the ensemble. The developed system can be used as a supporting system for music education if high speed communication network is available.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.12
• /
• pp.3416-3435
• /
• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• Journal of Practical Engineering Education
• /
• v.16 no.5_spc
• /
• pp.643-651
• /
• 2024

This study aims to design and implement an AI mock interview system for Computer Science (CS) interview preparation using LLM (Large Language Model) based ChatGPT. The system utilizes AI's natural language processing and speech recognition capabilities to analyze and provide real-time feedback on interview responses, helping users improve their weaknesses during the preparation process. According to a survey, 90% of users reported that the real-time feedback function provided substantial assistance in their interview preparation. Key features include GPT prompt generation and Speech-to-Text functionality, which converts voice data into text. The system received positive evaluations for its response time and feedback accuracy. Future research will explore expanding the range of question types and applying the system to various industries.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.5
• /
• pp.1412-1422
• /
• 2016

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.99-102
• /
• 2021

The article considers one of the areas of development of artificial intelligence where there is the development of computer intelligent systems capable of performing functions traditionally considered intelligent - language comprehension, inference, use of accumulated knowledge, learning, pattern recognition, as well as learn and explain their decisions. It is found that informational intellectual systems are promising in their development. The article is devoted to intelligent information systems and technologies in educational activities, ie issues of organization, design, development and application of systems designed for information processing, which are based on the use of artificial intelligence methods.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.11-19
• /
• 2024

Web programming courses are often included in university Computer Science programs as introductory and foundational computer programming courses. However, amateur programmers often have difficulty learning how to integrate HTML, CSS, JavaScript, and various preprocessors or libraries to create websites. Additionally, many web programming mistakes do not produce visible output in the browser. Therefore, in recent years, Front-End Code Playground (FECP) tools that incorporate HTML, CSS, and JavaScript into a single, online web-based application have become popular. These tools allow web coding to happen directly in the browser and provide immediate visual feedback to users. Such immediate visual feedback can be particularly beneficial for amateur coders to learn and practice with. Therefore, this study gathers data on various FECP tools, compares their differences, and provides an analysis of how such tools benefit students. This study concludes with an outline of the application of FECP to web programming courses to enhance the learning experience.

• Computers and Concrete
• /
• v.3 no.1
• /
• pp.29-42
• /
• 2006

In this study, a novel education system for inspection of concrete bridges is presented. The new education approach uses virtual reality (VR) and three-dimensional computer graphics (3DCG) in training engineers to become bridge inspection specialists. The slow time-dependent deterioration of concrete bridges can be reproduced on the computer screen in any chosen time frame, thus providing the trainees with illustrative and educative insight into the deterioration problem. In the proposed VR/3DCG approach a three-dimensional model of concrete bridge, including surfaces, viewpoints and walkthrough paths is created. With the help of this virtual bridge model, an experienced bridge inspection specialist teaches the different deterioration phenomena of concrete bridges to the trainees. The new system was tested, and the inspection results from the case bridge showed that in comparison with the traditional Japanese bridge inspection education system, the new system gives better results. In addition to the improvement of quality of bridge inspections, the new VR/3DCG system-based education brings along some other, more intangible benefits.

• Journal of information and communication convergence engineering
• /
• v.20 no.4
• /
• pp.288-294
• /
• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• Journal of Engineering Education Research
• /
• v.26 no.1
• /
• pp.12-19
• /
• 2023

With the introduction of the accreditation of engineering programs in Korea, universities affiliated with the programs have opened introductory engineering design courses for first- or second-year students. Since these courses mainly aim at cultivating problem-solving skills through team projects, this type of classes has opened as face-to-face classes. However, from the beginning of 2020, online teaching was recommended or forced on universities due to the COVID-19 pandemic. Thus, effective design of online courses on introductory engineering design was inevitable during the period. In this paper, we introduce a case study of the course in the Department of Computer Science at S University in Fall 2021. Through concrete suggestions on project areas, selection of team members considering grade levels and interest, several systems for prevention of free riding, and carefully designed open-book exams, the course resulted in both high achievements and high satisfaction.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.7
• /
• pp.621-626
• /
• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.