• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.6
• /
• pp.134-140
• /
• 2008

Preceding vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based preceded vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an preceded vehicle detection system is developed using stereo vision sensors. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the preceded vehicles including a leading vehicle. Then, the position parameters of the preceded vehicles or leading vehicles can be obtained. The proposed preceded vehicle detection system is implemented on a passenger car and its performances is verified experimentally.

• Structural Engineering and Mechanics
• /
• v.80 no.5
• /
• pp.563-583
• /
• 2021

Composite materials, composed of multiple constituent materials with dissimilar properties, are actively adopted in a wide range of industrial sectors due to their remarkable strength-to-weight and stiffness-to-weight ratio. Nevertheless, the failure mechanism of composite materials is highly complicated due to their sophisticated microstructure, making it much harder to predict their residual material lives in real life applications. A promising solution for this safety issue is structural damage detection. In the present paper, damage detection of composite material via electrical resistance-based technique and infrared thermography is reviewed. The operating principles of the two damage detection methodologies are introduced, and some research advances of each techniques are covered. The advancement of IR thermography-based non-destructive technique (NDT) including optical thermography, laser thermography and eddy current thermography will be reported, as well as the electrical impedance tomography (EIT) which is a technology increasingly drawing attentions in the field of electrical resistance-based damage detection. A brief comparison of the two methodologies based on each of their strengths and limitations is carried out, and a recent research update regarding the coupling of the two techniques for improved damage detection in composite materials will be discussed.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.881-891
• /
• 2023

Recently, various studies on malicious URL detection using artificial intelligence have been conducted, and most of the research have shown great detection performance. However, not only does classical machine learning require a process of analyzing features, but the detection performance of a trained model also depends on the data analyst's ability. In this paper, we propose a DL-ML Fusion Hybrid Model for malicious web site URL detection based on URL lexical features. the propose model combines the automatic feature extraction layer of deep learning and classical machine learning to improve the feature engineering issue. 60,000 malicious and normal URLs were collected for the experiment and the results showed 23.98%p performance improvement in maximum. In addition, it was possible to train a model in an efficient way with the automation of feature engineering.

• Journal of the Korean Society of Safety
• /
• v.31 no.6
• /
• pp.121-128
• /
• 2016

Social Media transformed the mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, in regards to disaster management, the necessity for public participation policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for purposes of implementing social media disaster management. Social Big Board collects a daily average of 36 million tweets in Korean in real time and automatically filters disaster safety related tweets. The filtered tweets are then automatically categorized into 71 disaster safety types. This real time tweet monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relations to disaster management. It is a first step towards disaster management that communicates with the people that allows us to hear the voice of the people concerning disaster issues and also understand their emotions at the same time. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is key algorithms, will be described. Disaster issues are divided into two categories: potential issues, which refers to abnormal signs prior to disaster events, and occurrence issues, which is a notification of disaster events. The detection models of these two categories are defined and the performance of the models are compared and evaluated.

• Structural Engineering and Mechanics
• /
• v.86 no.6
• /
• pp.715-730
• /
• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.20 no.1
• /
• pp.109-118
• /
• 2024

Recently, a social issue has arisen involving RDDoS attacks following the sending of threatening emails to security administrators of companies and institutions. According to a report published by the Korea Internet & Security Agency and the Ministry of Science and ICT, survey results indicate that DDoS attacks are increasing. However, the top response in the survey highlighted the difficulty in countering DDoS attacks due to issues related to security personnel and costs. In responding to DDoS attacks, administrators typically detect anomalies through traffic monitoring, utilizing security equipment and programs to identify and block attacks. They also respond by employing DDoS mitigation solutions offered by external security firms. However, a challenge arises from the initial failure in early response to DDoS attacks, leading to frequent use of detection and mitigation measures. This issue, compounded by increased costs, poses a problem in effectively countering DDoS attacks. In this paper, we propose a system that creates detection rules, periodically collects traffic using mail detection and IDS, notifies administrators when rules match, and Based on predefined threshold, we use IPS to block traffic or DDoS mitigation. In the absence of DDoS mitigation, the system sends urgent notifications to administrators and suggests that you apply for and use of a cyber shelter or DDoS mitigation. Based on this, the implementation showed that network traffic was reduced from 400 Mbps to 100 Mbps, enabling DDoS response. Additionally, due to the time and expense involved in modifying detection and blocking rules, it is anticipated that future research could address cost-saving through reduced usage of DDoS mitigation by utilizing artificial intelligence for rule creation and modification, or by generating rules in new ways.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.2
• /
• pp.11-22
• /
• 2015

The almost of Web page has been gathered the personal information(Korean resident registration number, name, cell-phone number, home telephone number, E-mail address, home address, etc.) using the membership and log-in. The all most user of Web page are concerned for gathering of the personal information. I-pin is the alternative means of resident registration number and has been used during the last ten-year period in the internet. The accident of I-pin mass illegal issue was happened by hacker at February, 2015. In this paper, we analysis the problems of I-pin system about I-pin mass illegal issue accident and propose a improvement method of it. First, I-pin issue must be processed by the off-line of face certification in spite of user's inconvenience. Second, I-pin use must be made up through second certification of password or OTP. The third, the notification of I-pin use must be sent to the user by the text messaging service of cell-phone or the E-mail. The forth, I-pin must be used an alternative means of Korean resident registration number in Internet. The methods can reduce the problems of I-pin system.

• The Bulletin of The Korean Astronomical Society
• /
• v.39 no.1
• /
• pp.79.1-79.1
• /
• 2014

GRBs are the most energetic and very frequent electromagnetic events among known astronomical phenomena in the universe. The progenitor of GRBs is believed as one of most promising sources of gravitational waves. Thus, detection of gravitational wave signals associated with GRBs will be a fascinating issue. In this presentation, we describe how we search gravitational waves related to GRBs by using LIGO and Virgo data.

• Communications of the Korean Institute of Information Scientists and Engineers
• /
• v.30 no.6
• /
• pp.47-58
• /
• 2012

• Journal of Microbiology and Biotechnology
• /
• v.24 no.3
• /
• pp.297-312
• /
• 2014

Food safety is increasingly becoming an important public health issue, as foodborne diseases present a widespread and growing public health problem in both developed and developing countries. The rapid and precise monitoring and detection of foodborne pathogens are some of the most effective ways to control and prevent human foodborne infections. Traditional microbiological detection and identification methods for foodborne pathogens are well known to be time consuming and laborious as they are increasingly being perceived as insufficient to meet the demands of rapid food testing. Recently, various kinds of rapid detection, identification, and monitoring methods have been developed for foodborne pathogens, including nucleic-acid-based methods, immunological methods, and biosensor-based methods, etc. This article reviews the principles, characteristics, and applications of recent rapid detection methods for foodborne pathogens.