• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.89-101
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• 2014

Recently, as domestic air traffic dramatically increases, the need of ATC(air traffic control) systems has grown for safe and efficient ATM(air traffic management). Especially, for smooth ATC, it is far more important that performance of display system which should show all air traffic situation in FIR(Flight Information Region) without additional latency is guaranteed. In this paper, we design a ASTERIX(All purpose STructured Eurocontrol suRveillance Information eXchange) parsing module to promote stable ATC by minimizing system loads, which is connected with reducing overheads arisen when we parse ASTERIX message. Our ASTERIX parsing module based on pattern matching creates patterns by analyzing received ASTERIX data, and handles following received ASTERIX data using pre-defined procedure through patterns. This module minimizes display errors by rapidly extracting only necessary information for display different from existing parsing module containing unnecessary parsing procedure. Therefore, this designed module is to enable controllers to operate stable ATC. The comparison with existing general bit level ASTERIX parsing module shows that ASTERIX parsing module based on pattern matching has shorter processing delay, higher throughput, and lower CPU usage.

• Journal of the Korea Computer Industry Society
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• v.2 no.4
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• pp.443-454
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• 2001

Software design patterns are reusable solutions to recurring problems that occur during software development. As programmers gain experience, they recognize the similarity of new problems to problems they have solved before. With even more experience, they recognize that solutions for similar problems follow recurring patterns. In this paper, as one of these reusable design-patterns, the Intermediator pattern for the efficient communication between business component is designed and implemented. Existent business components were way that follow Facade pattern. But Facade pattern is almost like the existing Interface pattern in that the communication of all the object outside the set is done by only one representative object, and this causes the traffic system to be overloaded. Therefore, the Intermediator pattern supplements the traffic overloads by improving the inefficient system of business components' communication through multi-interface, and make all communication behavior between objects done by Intermediator object which controls all actual behavior by way of Intermediator method implementation. Consequently, the Intermediator pattern is designed and implemented in this paper can bring down the level of coupling and raise the cohesion among objects, and refer to many of other object flexibly through several interfaces.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.212-219
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• 2023

Vessel Traffic Service (VTS) area presents a complex traffic pattern due to ships entering or leaving the port to utilize port facilities, as well as ships passing through the coastal area. To ensure safe and efficient management of maritime traffic, VTS operators continuously monitor and control vessels in real time. However, during periods of high traffic congestion, the workload of VTS operators increases, which can result in delayed or inadequate VTS services. Therefore, it would be beneficial to predict traffic congestion and congested areas to enable more efficient traffic control. Currently, such prediction relies on the experience of VTS operators. In this paper, we defined vessel traffic congestion from the perspective of a VTS operator. We proposed a method to generate traffic networks using historical navigational data and predict traffic congestion and congested areas. Experiments were performed to compare prediction results with real maritime data (Daesan port VTS) and examine whether the proposed method could support VTS operators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3635-3654
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• 2015

With the rapid development of smart devices and mobile Internet, the video application plays an increasingly important role on mobile devices. Understanding user behavior patterns is critical for optimized operation of mobile live streaming systems. On the other hand, volume based billing models on cloud services make it easier for video service providers to scale their services as well as to reduce the waste from oversized service capacities. In this paper, the watching behaviors of a commercial mobile live streaming system are studied in a content-centric manner. Our analysis captures the intrinsic correlation existing between popularity and watching intensity of programs due to the synchronized watching behaviors with program schedule. The watching pattern is further used to estimate traffic volume generated by the program, which is useful on data volume capacity reservation and billing strategy selection in cloud services. The traffic range of programs is estimated based on a naive popularity prediction. In cross validation, the traffic ranges of around 94% of programs are successfully estimated. In high popularity programs (>20000 viewers), the overestimated traffic is less than 15% of real happened traffic when using upper bound to estimate program traffic.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.127-134
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• 2013

While there are many services that can check current traffic condition and application program such as bus arrival alarm are developed, since it only provide simple alarm and check level of information, it is still insufficient in many senses. Therefore, the program that try to develop in this study is the system that predict arrival time to destination and inform the bus passengers by applying real time traffic information. The system developed related to this study is still very inadequate. In the system developed in this thesis, when the user input the current bus number and destination using smart-phone, relevant server acquire the bus route information from bus information DB, and analyze real time traffic information based on the information from traffic information DB, and inform customer of expected arrival time to destination. In this thesis, traffic congestion can be eased off and regular operation of public transportation can be improved with reliable destination arrival alarm. Also, it is considered that pattern of bus users can be analyzed by using these information, and analyzing average transport speed and time of public transportation, travel time depending on various situation can give a boost to study related to transportation information and its development.

• Journal of Oriental Neuropsychiatry
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• v.32 no.1
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• pp.1-11
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• 2021

Objectives: To investigate the prevalence of acute stress disorder (ASD) and post-traumatic stress disorder (PTSD) in patients with traffic injuries. In addition, PTSD patients was classified using 'pattern identification for jing ji and zheng chong'. Methods: Questionnaires such as the primary care PTSD screen for DSM-5(PC-PTSD-5), Korean version of PTSD checklist-5 (PCL-5-K), and the instrument of pattern identification for jing ji and zheng chong were conducted on 195 patients within 3 days to 1 year after traffic accidents. Patients were recruited from six medical institutions. Collected data were used to determine the prevalence of acute stress disorder and post-traumatic stress disorder. Results: On PC-PTSD-5, the prevalence was 39.1% for ASD and 50% for PTSD. On PCL-5-K, the prevalence was 20.4% for ASD and 29.3% for PTSD. Satisfying both PC-PTSD-5 and PCL-5-K, the prevalence was 18.2% for ASD and 25.8% for PTSD. As a result of pattern identification for jing ji and zheng chong, 'weakness of heart and gall bladder type' accounted for the highest proportions in both ASD and PTSD groups. Conclusions: In this study, the prevalence was 39.1% for ASD and 50% for PTSD by PC-PTSD-5. Satisfying both PC-PTSD-5 and PCL-5-K, the prevalence was 18.2% for ASD and 25.8% for PTSD. Further large-scale prospective studies are needed to analyze the prevalence of ASD and PTSD, the rate of progression from ASD to PTSD, and the type of pattern identification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.29-40
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• 2021

Risk factors that threaten public safety such as crime, fire, and traffic accidents have spatial characteristics. Since each region has different dangerous environments, it is necessary to analyze the spatial pattern of risk factors for each sector such as traffic accident, fire, crime, and living safety. The purpose of this study is to analyze the spatial distribution pattern of local safety level index, which act as an index that rates the safety level of each sector (traffic accident, fire, crime, living safety, suicide, and infectious disease) for basic local governments across the nation. The following analysis tools were used to analyze the spatial autocorrelation of local safety level index : Global Moran's I, Local Moran's I, and Getis-Ord's G⁎i. The result of the analysis shows that the distribution of safety level on traffic accidents, fire, and suicide tends to be more clustered spatially compared to the safety level on crime, living safety, and infectious disease. As a result of analyzing significant spatial correlations between different regions, it was found that the Seoul metropolitan areas are relatively safe compared to other cities based on the integrated index of local safety. In addition, hot spot analysis using statistical values from Getis-Ord's G⁎i derived three hot spots(Samchuck, Cheongsong-gun, and Gimje) in which safety-vulnerable areas are clustered and 15 cold spots which are clusters of areas with high safety levels. These research findings can be used as basic data when the government is making policies to improve the safety level by identifying the spatial distribution and the spatial pattern in areas with vulnerable safety levels.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.1
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• pp.9-16
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• 2017

As a preliminary study of enter or leaving traffic patterns of the Korea main port, port Management Information System (Port-MIS) data was used to check the volume of vessels entering and leaving the port of Busan, and three consecutive days from each seasons were selected for study. Selected 12-day General Information Center on Maritime Safety & Security (GICOMS) data was also used to analyze the traffic pattern in the main traffic lane of Busan port for dangerous goods carrier. Also, the distance between dangerous goods carriers and Oryukdo breakwater of east breakwater in the main traffic lane was analyzed. Collision probability was estimated using the cumulative probability distribution function of the normal distribution for the maritime traffic safety audit scheme based on the assumption that a ship's trajectory has a normal distribution for a section of the route. However, in case of entry or leaving thorough the Oryukdo breakwater and entry thorough the east breakwater, ship's sailing trajectories were revealed not to follow a normal distribution via regularity testing using a KS-test and SW-test. Especially in the north port, the tendency of the right side of the ship to pass was remarkable. It is desirable to develop a traffic model suitable for the characteristics of the port rather than to apply general traffic theories, and to apply this model to a maritime traffic safety diagnosis, so further research is needed.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.21-28
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• 2012

Recently, the necessity for good techniques of detecting network traffic attack has increased. In this paper, we suggest a new method of detecting abnormal patterns of network traffic data by visualizing their IP and port information into two dimensional images. The proposed approach first generates four 2D images from IP data of transmitters and receivers, and makes one 2D image from port data. Analyzing those images, it then extracts their major features such as linear patterns or high intensity values, and determines if traffic data contain DDoS or DoS Attacks. To comparatively evaluate the performance of the proposed algorithm, we show that our abnormal pattern detection method outperforms the existing algorithm in terms of accuracy and speed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.91-102
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• 2024

This study aimed to investigate the sleep-wake patterns, social jetlag (SJL), and daytime sleepiness (DS) among air traffic controllers (ATCs) with rotating shifts. A total of 133 shift-rotating ATCs participated by completing self-report questionnaires regarding their sleep-wake patterns and DS. SJL, indicating the mid-sleep difference between workdays (W) and free days (F), was calculated for each shift. Night-shift workdays had the shortest sleep duration (SD) (5.28 hours), whereas free days following day shifts had the longest SD (6.66 hours). SJL for day and night shifts was 2.73 and 2.71 hours, respectively. The average DS score was 7.92 out of 24, with a 28.6% prevalence of DS. There was a negative correlation between SD following day shifts and SJL for the day shifts. Given these findings, it is recommended to implement effective interventions and work schedules to maintain consistent sleep patterns and minimize social jetlag to address sleep issues for shift-working ATCs.