• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.490-492
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• 2000

기존의 인터넷 라우터는 Drop tail 방식으로 패킷을 관리한다. 따라서 네트워크 트래픽의 지수적인 증가로 인한 혼잡 상황으로 발생하는 패킷 손실을 해결할 수 없다. 이 문제를 해결하기 위해 IETF(Internet Engineering Task Force)에서는 RED(Random Early Detection)와 같은 능동적인 큐 관리 알고리즘을 제시하였다. 하지만 RED는 동적으로 변화하는 인터넷 트래픽에 대하여 단지 큐 크기의 변화 정보를 얻어 혼잡 상황을 제어하기 때문에 성능에 있어는 매우 비효율적이다. 본 논문에서는 기존의 RED를 개선한 MRED를 제안했다. MRED는 RED에 비하여 휴리스틱한 방법을 이용하여 폐기 확률 값을 계산하고, 이를 실험을 통하여 MRED의 성능을 검증하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.995-999
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• 2010

Every year, traffic accidents and traffic congestion have been rapidly increasing, Although the roadway design and signal system have been improved to relieve traffic accidents, traffic casualties and property damage do not decrease. This paper develops a real-time traffic accident detection and analysis system (RTADAS): In the proposed system, we aim to precisely detect traffic accidents at different design and flow of intersections, However, because the data collected from intersections have uncertainty and complicated causal dependency between them, we construct probability-based networks for correct accident detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.57-66
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• 2007

Scanning worms increase network traffic load because they randomly scan network addresses to find hosts that are susceptible to infection. Since propagation speed is faster than human reaction, scanning worms cause severe network congestion. So we need to build an early detection system which can automatically detect and quarantine such attacks. We propose algorithms to detect scanning worms using network traffic characteristics such as variance, variance to mean ratio(VMR) and correlation coefficient. The proposed algorithm have been verified by computer simulation. Compared to existing algorithm, the proposed algorithm not only reduced computational complexity but also improved detection accuracy.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• Journal of Oral Medicine and Pain
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• v.9 no.1
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• pp.147-156
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• 1984

In spite of the radical increase of chemical poisoning cases caused by prevalent of oranic chlorine like endosulfan, the study of detection of chemical poisoning has seldom been attempted; the study of poisoning in teeth, which is more secure physiochemically, and in all the oral tissues has been even less attempted. The author has administered endosulfan into the month of a rabbit, causing its death, and tried to detect endosulfan in the teeth, jaws, and oral tissues through forensic chemical and histopathological tests. The result obtained is as follows : 1. By thin layer chromatography, endosulfan was detected in the jews, dental hard tissues, dental pulp, blood, and the liver. 2. By gas chromatography, it was also detected in the jaws, dental hard tissues, dental pulp, blood, and the liver. 3. The congestion and hemorrhage in buccal mucosa, palatal mucosa, and dental pulp was detected.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.329-336
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• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.13-22
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• 2009

Recently, DSRC technology is used in the various fields such as parking system, BIS, ETC, etc. This paper suggests a traffic information system using this DSRC technology. The traffic information processing based on point detection using existing vehicle detection equipment is the system in which a collection and a service are operated separately while the traffic information system based on the link detection using DSRC is able to collect and provide the traffic information through the communication between RSE and OBU. The speed of a traffic congestion is high on the process converted from a point passing speed to a link average speed because the vehicle detection equipment makes the link traffic information into the point information. When the condition of traffic is deteriorated, traffic speed of the vehicle detection equipment becomes higher than DSRC. Especially, in this system, deflection by data of the traffic speed of the traffic information system is much decreased, and the unexpected condition detection and traffic condition are provided promptly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9B
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• pp.823-833
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• 2003

To satisfy the requirements of the real-time Internet services, queue management and scheduling schemes should be enhanced to accommodate the delay and jitter characteristic of them. Although the existing queue management schemes can address the congestion problems of TCP flows, they have some problems in supporting real-time services. That is, they show performance degradation when burst traffics are continuously going into the system after the queue is occupied at a predefined threshold level. In addition, under the congestion state, they show large jitter, which is not a desirable phenomenon for real-time transmissions. To resolve these problems, we propose a SDRED (State Dependent Random Early Detection) and dynamic scheduling scheme that can improve delay and jitter performances by adjusting RED parameters such as ma $x_{th}$ and $w_{q}$ according to the queue status. The SDRED is designed to adapt to the current traffic situation by adjusting the max,$_{th}$ and $w_{q}$ to four different levels. From the simulation results, we show that the SDRED decreases packet delays in a queue and has more stable jitter characteristics than the existing RED, BLUE, ARED and DSRED schemes.mes.mes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.178-202
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• 2012

In this paper, we first survey cross-layer architectures for Wireless Sensor Networks (WSNs) and Wireless Multimedia Sensor Networks (WMSNs). Afterwards, we propose a novel cross-layer architecture for QoS provisioning in clustered and multi-hop based WMSNs. The proposed architecture provides support for multiple network-based applications on a single sensor node. For supporting multiple applications on a single node, an area in memory is reserved where each application can store its network protocols settings. Furthermore, the proposed cross-layer architecture supports heterogeneous flows by classifying WMSN traffic into six traffic classes. The architecture incorporates a service differentiation module for QoS provisioning in WMSNs. The service differentiation module defines the forwarding behavior corresponding to each traffic class. The forwarding behavior is primarily determined by the priority of the traffic class, moreover the service differentiation module allocates bandwidth to each traffic class with goals to maximize network utilization and avoid starvation of low priority flows. The proposal incorporates the congestion detection and control algorithm. Upon detection of congestion, the congested node makes an estimate of the data rate that should be used by the node itself and its one-hop away upstream nodes. While estimating the data rate, the congested node considers the characteristics of different traffic classes along with their total bandwidth usage. The architecture uses a shared database to enable cross-layer interactions. Application's network protocol settings and the interaction with the shared database is done through a cross-layer optimization middleware.