• ETRI Journal
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• v.39 no.4
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• pp.558-569
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• 2017

In this study, a non-preemptive M/G/1 queueing model of a spectrum handoff scheme for cognitive wireless networks is proposed. Because spectrum handoff gives secondary users an opportunity to carry on their transmissions, it is crucially important to determine the actions of primary users. In our queueing model, prioritized data traffic is utilized to meet the requirements of the secondary users. These users' packets are categorized into three different priority classes: urgent, real-time, and non-real time. Urgent data packets have the highest priority, while non-real time data packets have the lowest priority. Riverbed (OPNET) Modeler simulation software was used to simulate both reactive and proactive decision spectrum handoff schemes. The simulation results were consistent with the analytical results obtained under different load and traffic conditions. This study also revealed that the cumulative number of handoffs can be drastically decreased by exploiting priority classes and utilizing a decent spectrum handoff strategy, such as a reactive or proactive decision-based strategy.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.602-610
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• 2000

In communication networks used in safety-critical systems such as control systems in nuclear power plants there exist three types of data traffic : urgent or asynchronous hard real-time data hard real-time periodic data and soft real-time periodic data. it is necessary to allocate a suitable bandwidth to each data traffic in order to meet their real-time constraints. This paper proposes a method to meet the real-time constraints for the three types of data traffic simultaneously under a timer-controlled token bus protocol or the IEEE 802.4 token bus protocol and verifies the validity of the presented method by an example. This paper derives the proper region of the high priority token hold time and the target token rotation time for each station within which the real-time constraints for the three types of data traffic are met, Since the scheduling of the data traffic may reduce the possibility of the abrupt increase of the network load this paper proposes a brief heuristic method to make a scheduling table to satisfy their real-time constraints.

• Korean journal of aerospace and environmental medicine
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• v.31 no.1
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• pp.13-16
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• 2021

The coronavirus disease-19 (COVID-19) vaccine is expected to play an important role in stopping the pandemic. Studies show that COVID-19 vaccines are effective at keeping you from getting COVID-19. Getting a COVID-19 vaccine will also help keep you from getting seriously ill even if you do get COVID-19. Efforts to find an effective vaccine against severe acute respiratory syndrome coronavirus 2 have progressed unprecedentedly through active support from public research grants and private-public partnership programs. Clinical studies have been actively conducted, and some vaccines are being vaccinated with approval for urgent use. The WHO has approved and supplied the Pfizer-BioNTech COVID-19 vaccine and the Oxford-AstraZeneca COVID-19 vaccine. In Korea, the Oxford-AstraZeneca vaccine was approved for urgent use, and vaccination began on February 26, 2021. In this paper, the efficacy and side effects of each vaccines and the effect on pilots and air traffic controllers related to COVID-19 vaccination were investigated in terms of aviation medicine.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.501-509
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• 2004

The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.44-61
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• 2022

With the increase of truck traffic, roads are becoming more congested and the risk of accidents is also increasing. Since the fatality rate of traffic accidents caused by trucks is about 2 to 3 times higher than that of passenger cars and buses, it is urgent to prepare policies for truck traffic safety. While most of the previous studies focused on factor analysis that contributes to traffic accidents, this study presented traffic safety policies (4 major-criteria and 12 sub-criteria) for trucks through driver interviews and previous studies. Then, the priority of the policies was evaluated by using Fuzzy-AHP. As a result, the improvement of truck drivers' working environment was evaluated as the most important criteria, and followed by the improvement of road traffic conditions. In detail, there is an urgent need to improve the freight car fare system, ensure sufficient rest for drivers, and strengthen the crackdown of illegal parking and stopping along roads. This study is expected to be usefully utilized in preparing traffic flow safety policies in preparation for the continuous increase of truck traffic.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1460-1465
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• 2016

In this paper, we propose an energy efficient and multimedia traffic friendly MAC protocol (EEMF-MAC) that controls sender's wakeup period based on the data packet's transmission urgency and the receiver's wakeup periods based on the received data packet traffic loads. The protocol is useful for applications such as object tracking, real time data gathering, in which priority-based packet transmission is required. The basic idea of EEMF-MAC is that it uses the priority concept with transmission urgency of sender's data packet to reduce the transmission delay of the urgent data and it also uses duty cycling technique in order to achieve energy efficiency. EEMF-MAC showed a better performance in energy efficiency and packet transmission delay compared to existing protocols, RI-MAC and EE-RI-MAC.

• Journal of the Korea Safety Management & Science
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• v.18 no.4
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• pp.73-80
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• 2016

This study highlights the main effect of job demand, work shift, work environment and stressors on the railway traffic controller's health, and the moderating effect of work0life balance. The result of empirical analysis based on questionnaires received from 328 traffic controllers working at 10 railway operating companies indicates that job demand, work shift, work environment and stressors have significant effect on their health, among which stressors is a major factor. In the respect of moderating effect, WLB showed no significance except for job demand. This result implies that controller's health can not be enhanced through their individual family or leisure life. Therefore, effective countermeasures and policy to mitigate their health problems and heal their symptoms are urgent.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.70-77
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• 2020

In this study, we estimate the vehicle speed by analyzing the acoustic data recorded in a single microphone of a surveillance camera. The frequency analysis of the acoustic data corrects the Doppler effect, which is a characteristic of the moving sound source, and reflects the geometric relationship according to the location of the sound source and the microphone on the two-dimensional plane. The acoustic data is selected from the horn sound that is mainly observed in an urgent situation among various sound sources that may occur in a traffic accident, and the characteristics of the monotone source are considered. We verified the reliability of the proposed method by time domain acoustic analysis and actual vehicle evaluation. This method is effective and can be used for traffic accident analysis in the blind spot of the camera using a single microphone built into the existing surveillance camera.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.52-60
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• 2024

APT (Advanced Persistent Threat) attack is a dangerous, targeted attack form with clear targets. APT attack campaigns have huge consequences. Therefore, the problem of researching and developing the APT attack detection solution is very urgent and necessary nowadays. On the other hand, no matter how advanced the APT attack, it has clear processes and lifecycles. Taking advantage of this point, security experts recommend that could develop APT attack detection solutions for each of their life cycles and processes. In APT attacks, hackers often use phishing techniques to perform attacks and steal data. If this attack and phishing phase is detected, the entire APT attack campaign will be crash. Therefore, it is necessary to research and deploy technology and solutions that could detect early the APT attack when it is in the stages of attacking and stealing data. This paper proposes an APT attack detection framework based on the Network traffic analysis technique using open-source tools and deep learning models. This research focuses on analyzing Network traffic into different components, then finds ways to extract abnormal behaviors on those components, and finally uses deep learning algorithms to classify Network traffic based on the extracted abnormal behaviors. The abnormal behavior analysis process is presented in detail in section III.A of the paper. The APT attack detection method based on Network traffic is presented in section III.B of this paper. Finally, the experimental process of the proposal is performed in section IV of the paper.