• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.33 no.4
• /
• pp.139-157
• /
• 2022

Finding and selecting proper reviewers is a burden on the publisher of the journal. In order to solve this problem, the online submission system started to recommend appropriate reviewers automatically. It includes a variety of new features, from recommending authors in the references of submitted papers as reviewers to finding similar papers by searching the citation index and suggesting reviewer candidates extensively. This study investigated how the online submission system provides functions such as recommendation of reviewers. As a result of examining major online submission systems, ScholarOne and Editorial Manager were recommending reviewer candidates by commercial citation index and review history platform. On the other hand, JAMS, a domestic online submission system, did not have any advanced functions such as recommendation of candidates for reviewers. Sooner or later, in Korea, it seems that more efforts should be made to improve the function of online submission system, such as recommending suitable reviewers for papers.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1187-1194
• /
• 2020

We presented a method of deep quiz cropping for automatic construction of quiz pool in online quiz systems. The method detects question boxes and sunda boxes in images captured from test papers by a deep learning-based object detector, and makes pairs of question box and sunda box by the box coupling. We applied the deep quiz cropping to images captured from test papers and achieved successful results.

• Journal of information and communication convergence engineering
• /
• v.21 no.3
• /
• pp.239-243
• /
• 2023

Owing to the environment in which it has become difficult to face people, on-tact communication has been activated, and online video conferencing platforms have become indispensable collaboration tools. Although costs have dropped and productivity has improved, communication remains poor. Recently, various companies, including existing online videoconferencing companies, have attempted to solve communication problems by establishing a videoconferencing platform within the virtual reality (Virtual Reality) space. Although the VR videoconference platform has only improved upon the benefits of existing video conferences, the problem of manually summarizing minutes because there is no function to summarize minute documents still remains. Therefore, this study proposes a method for establishing a meeting minute summary system without applying cases to a VR videoconference platform. This study aims to solve the problem of communication difficulties by combining VR, a metaverse technology, with an existing online video conferencing platform.

• Journal of Navigation and Port Research
• /
• v.31 no.7
• /
• pp.563-568
• /
• 2007

In this paper, an adaptive neural network controller and its application to automatic berthing control of ship is presented. The neural network controller is trained online using adaptive interaction technique without any teaching data and off-line training phase. Firstly, the neural networks used to control rudder and propeller during automatic berthing process are presented. Secondly, computer simulations of automatic ship berthing are carried out in Pusan bay to verify the proposed controller under the influence of wind disturbance and measurement noise. The results of simulation show good performance of the developed berthing control system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1531-1536
• /
• 2011

We propose an automatic swearword filter system for online game chatting by using Support Vector Machines(SVM). We collected chatting sentences from online games and tagged them as normal sentences or swearword included sentences. We use n-gram syllables and lexical-part of speech (POS) tags of a word as features and select useful features by chi square statistics. Each selected feature is represented as binary weight and used in training SVM. SVM classifies each chatting sentence as swearword included one or not. In experiment, we acquired overall 90.4% of F1 accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.499-501
• /
• 2021

Recently, artificial intelligence and SW have occupied an important position worldwide as the foundation technology of the era of the 4th industrial revolution, and web browser-based programming learning systems are becoming common due to changes in the learning environment caused by COVID-19. In accordance with this trend, this paper proposes a functionally scalable microservice-based system structure for an online evaluation system as a tool for learning algorithms that are the basis of artificial intelligence and SW. In addition, a functional structure for applying machine learning to automatic evaluation functions under the proposed system structure is also proposed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.519-524
• /
• 2003

In this report, a longitudinal adaptive flight control law is presented for the automatic landing system of a Japanese automatic landing flight experiment vehicle (ALFLEX). The longitudinal adaptive flight control law is designed to track an output of the vehicle to a guidance signal from the guidance portion of the automatic landing system. The proposed adaptive control law in the attitude control portion adjusts the controller gains continuously online as flight conditions change, in spite of the existence of unmodeled dynamics. The number of the controller gains to be adjusted is decreased to 1/2 from the previous studies. Computer simulation involving six-degree-of-freedom (DOF) nonlinear flight dynamics is performed to examine the effectiveness of the proposed adaptive control law. In order to verify the influence of the dispersion of the initial conditions, the Monte Carlo simulation is also applied. The initial conditions are more widely dispersed than the previous studies. As a result, except under the unsuitable initial conditions, the ALFLEX successfully landed on the runway.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.5
• /
• pp.1092-1097
• /
• 2007

Ontology construction has need of many time and cost. This is why it is difficult to build a commercial semantic web. To solve the problem, we must automatically construct ontology. In this paper, we propose an automatic ontology generation system from web documents containing important informations of the web. The proposed system has two steps. One is simplification process which generates simple sentences from all sentences in the documents. Another is ontology generation process with transfer rules. Our system is very useful fur application domains in which many documents are updated or inserted frequently such as online shopping malls.

• Journal of the Korean Data and Information Science Society
• /
• v.11 no.1
• /
• pp.19-30
• /
• 2000

As the number of online documents increases enormously with the expansion of information technology, the importance of automatic document classification is greatly enlarged. In this paper, an automatic document classification method is investigated and applied to UseNet 20 newsgroup articles to test its efficacy. The classification system uses Naive Bayes classification algorithm and the experimental result shows that a randomly selected newsgroup arcicle can be classified into its own category over 77% accuracy.

• Journal of Broadcast Engineering
• /
• v.21 no.4
• /
• pp.525-537
• /
• 2016

In this paper, we develop an online video mash-up system which use automatic scene elements composition scheme using a storyboard. There are two conventional online video production schemes. Video collage method is simple and easy, but it was difficult to reflect narrative or story. Another way is a template based method which usually select a template and it replaces resources such as photos or videos in the template. However, if the related templates do not exist, there are limitations that cannot create the desired output. In addition, the quality and atmosphere of the output is too dependent on the template. To solve these problems, we propose a video mash-up scheme using storyboard and we also implement a classification and recommendation scheme based on topic modeling.