• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2484-2496
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• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.517-523
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• 2002

In this paper, we propose system that apply VIBL method to add speech recognition to LIBL method based on human s studying method to use natural language to steering system of ship, MERCS and winch appliances and use VIBL method to alternate process that linguistic instruction such as officer s steering instruction is achieved via ableman and control steering gear, MERCS and winch appliances. By specific method of study, ableman s suitable steering manufacturing model embodies intelligent steering gear controlling system that embody and language direction base studying method to present proper meaning element and evaluation rule to steering system of ship apply and respond more efficiently on voice instruction of commander using fuzzy inference rule. Also we embody system that recognize voice direction of commander and control MERCS and winch appliances. We embodied steering manufacturing model based on ableman s experience and presented rudder angle for intelligent steering system, compass bearing arrival time, evaluation rule to propose meaning element of stationary state and correct steerman manufacturing model rule using technique to recognize voice instruction of commander and change to text and fuzzy inference. Also we apply VIBL method to speech recognition ship control simulator and confirmed the effectiveness.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.231-243
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• 2016

This study presents the applicability of two-dimensional (2D) flood inundation model by applying to real irrigation reservoir failure with limited available data. The study area is Sandae Reservoir placed in Gyeongju and downstream area of it and the reservoir was failured by piping in 2013. The breach hydrograph was estimated from one-dimensional (1D) hydrodynamic model and the discharge was employed for upstream boundary of 2D flood inundation model. Topography of study area was generated by integrating digital contour map and satellite data, and Cartesian grids with 3m resolution to consider geometry of building, road and public stadium were used for 2D flood inundation analysis. The model validation was carried out by comparing predictions with field survey data including reservoir breach outflow, flood extent, flood height and arrival time, and identifying rational ranges with allowed error. In addition, the applicability of 2D model is examined using different simulation conditions involving grid size, building and roughness coefficient. This study is expected to contributed to analysis of irrigation reservoirs were at risk of a failure and setting up Emergency Action Plan (EAP) against irrigation reservoir failure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.91-99
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• 2019

Existing node-to-node based optimal path searching is built on the assumption that all destination nodes can be arrived at from an origin node. However, the recent appearance of the adaptive path search algorithm has meant that the optimal path solution cannot be derived in node-to-node path search. In order to reflect transportation data at the links in real-time, the necessity of the node-to-link (or link-to-node; NL) problem is being recognized. This research assumes existence of a network with link-label and non-additive path costs as a solution to the node-to-link optimal path problem. At the intersections in which the link-label has a turn penalty, the network retains its shape. Non-additive path cost requires that M-similar paths be enumerated so that the ideal path can be ascertained. In this, the research proposes direction deletion and turn restriction so that regulation of the loop in the link-label entry-link-based network transformation method will ensure that an optimal solution is derived up until the final link. Using this method on a case study shows that the proposed method derives the optimal solution through learning. The research concludes by bringing to light the necessity of verification in large-scale networks.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.23-32
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• 2019

In this paper, we proposed a multi-chain Time of Arrival (ToA) positioning method to estimate positions using all received Loran-C signals from multiple chains without constraining to a single chain. Conventionally, we have to choose only one chain among several available chains for position estimation using Loran-C. Therefore, the number of signals to be used for positioning is limited to three to five. In general, if more signals are used for positioning estimation, its performance tends to be improved in terms of accuracy and availability. To validate the proposed method for multi-chain Loran-C, we firstly carried out a static positioning test in land. By analyzing the test results, we confirmed that the proposed method works well under a multi-chain Loran-C scenario. Subsequently, another mobile positioning test was conducted on board a vessel under a practical application scenario. From this second test, we successfully demonstrated that the multi-chain ToA positioning method even in situations where the conventional single-chain Loran-C approach fails for positioning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.569-575
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• 2010

The occupancy based O/D is essential for measuring efficiency of various transportation policies like HOV/HOT lane, ramp metering, and public parking station. There has been many studies on occupancy survey methodology and O/D estimation using TCS (Toll Collection System) data separately. The occupancy O/D estimation methodology using TCS data has not been attempted thus far. An overall process from data collection stage to the occupancy O/D estimation stage has been suggested. Field survey was performed at the northbound Seoul toll station of Gyeongbu Expressway by each 2 hours of AM peak, PM non-peak, PM peak, midnight periods on a day. The process of matching the TCS data and field survey data classified by tollbooth ID, car type/mode, and arrival time was also performed. One typical output of the results showed that the ratio of single occupancy vehicles bounding for Seoul during the AM peak amounted to 60%. With the key output of this study and the specific O/D estimation methodology suggested, the whole centroid-to-centroid occupancy O/D of the country could be available, and then various applications in which the occupancy information is required could be possible.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.125-130
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• 2006

Both surface seismic and far-offset VSP data were recorded alongtwo mutually perpendicular profiles in the Pungam basin. The first-arrival times were simultaneously inverted using the tomography method. For the surface data, seismic energy was generated by a 5-kg sledgehammer at 48 stations and detected by 21 surface geophones at 3 m intervals and one 3-component geophone in test borehole for the purpose of static corrections. For the VSP data, seismic waves generated by the sledgehammer on the ground were detected by a 3-component borehole geophone in a depth range of $9{\sim}99\;m$. Delay times of the hammer data were corrected using the seisgun data before the inversion to yield velocity tomograms. The tomograms indicates that the soil layer with velocities less than 750 m/s averages 1.8 m thick. The velocity varies from 5353 m/s at the depth range of $31{\sim}40\;m$ to 4262 m/s at the depth range of $65{\sim}73\;m$. Compared with core samples, the relatively large variation in velocity may due to lithology changes and fracture effects with depth.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.61-70
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• 2004

This paper treats optimal route assessment system at seaway based on weather forecasting and wave measurement through observation. Since early times. captain & officer have been sailing to select the optimum route considering the weather ana ship status condition empirically. However. it is rare to find digitalized onboard route support system whereas weather fax or wave and swell chart are utilized for the officer. based on officer's experience. In this paper, optimal route assessment system which is composed of voyage efficiency and safety component is introduced. Optimum route minimized ETA (estimated time of arrival) ana fuel consumption is evaluated for efficient voyage considering speed loss and power increase based on wave added resistance of ship. In the view point of safety, seakeeping prediction is performed based on 3 dimensional panel method. Basically. the weather forecast is assumed to be prepared previously in order to operate this system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.384-390
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• 2020

Purpose: Organophosphate insecticide poisoning can have clinically fatal results. This study aimed to evaluate the relationship between the neutrophil/lymphocyte ratio (NLR) and the occurrence of death in patients with organophosphate insecticide poisoning. Methods: For this retrospective study, data on patients with organophosphate insecticide poisoning who visited the emergency room between January 2008 and November 2018 were collected. The NLR was measured at the time of arrival in the emergency room. The patients were divided into survival and death groups. Results: Overall, 150 patients were enrolled: 15 (10%) in the death group and 135 (90%) in the survival group. In the univariate analysis, the following variables were significantly different between the two groups: age, white blood cell count, amylase level, creatinine level, Acute Physiology And Chronic Health Evaluation (APACHE) II score, and NLR. In the logistic regression analysis of variables with significant differences in the univariate analysis, there were significant differences between the two groups with respect to age, APACHE II score, and NLR. The NLR was significantly higher in the death group than in the survival group (20.83 ± 22.24 vs. 7.38 ± 6.06, p=0.036). Conclusion: High NLR in patients with organophosphate insecticide poisoning may be useful in predicting mortality.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.