• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.853-861
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• 2010

Experimental conditions are set with environmental factors which can affect ship navigation. In FTS simulation, infinite simulation can be theoretically tested with no time constraint but the simulated result with the same experimental condition is repeated due to mathematical model. RTS simulation can give more resonable results but costs at lest 30 minutes for only experimental time. The mixture of two simulation methods using probability density function has been proposed: some of experimental conditions in which ship-handling is most difficult are selected with FTS and are tested in RTS. It has drawback that it does not consider the navigation route but aggregated track index. In this paper, anomaly detection approach is suggested to select some experimental conditions of FTS simulation which are most difficult in ship-handling during the navigation route. An empirical result has been shown.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.684-691
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• 2001

In this paper, we design and implement a system which recognizes and tracks a human head on a sequence of images. In this paper, the color of the skin and ellipse modeling is used as feature vectors to recognize the human head. And the modified time-varying edge detection method and the vertical projection method is used to acquire regions of the motion from images with very complex backgrounds. To select the head from the acquired candidate regions, the process for thresholding on the basis of the I-component of YIQ color information and mapping with ellipse modeling is used. The designed system shows an excellent performance in the cases of the rotated heads, occluded heads, and tilted heads as well as in the case of the normal up-right heads. And in this paper, the combinational technique of motion-based tracking and recognition-based tracking is used to track the human head exactly even though the human head moves fast.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.3
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• pp.65-73
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• 2004

The bolier systems of coal fired power plants are large, non-linear systems with numerous interactions between its component parts. In the analysis of such complex systems, dynamic simulation is recognized as a powerful method of keeping track of the myriad of interactions. The boiler system consists of air/gas system and water/steam system. Due to recent reinforcement of environmental regulation on pollutant discharge and requirements of design validation on properites of boiler, the commercial programs are used for the analysis of boiler system. This paper addressed to the development of model using MMS(Modular Modeling System) developed by EPRI(Electric Power Research Institute) as the simulation tool. The developed model using MMS is tested for the design and local data on boiler combustion system of korea standard coal fired power plant boiler. The simulation results show that the developed model well reproduces responses of the combustion system with less than ${\pm}$5% error under steady state and transient state conditions. The developed model for analysis of the combustion system in this paper is general and applicable to any type of coal fired power plant.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.723-730
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• 2013

The speed-limit regulation on a turnout is the main factor inhibiting the speed-up of conventional lines. The specified speed for a train moving through a turnout system is lower than that for a train traveling over the general track. This is done to ensure the running safety of a railway vehicle moving through a turnout. In this study, the shape change example of the guard rail component of a turnout in the Daegu Metropolitan Transit Corporation (DTRO) system was studied. A theoretical examination of the geometrical interaction formula according to wheel/rail shape at the turnout was conducted. Running safety analysis by changing the length of the guard rail on the F10/F12 turnout using the developed analysis techniques (by VI-Rail) was achieved, and the effect on railway safety was examined accordingly.

• Journal of Welding and Joining
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• v.34 no.2
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• pp.59-66
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• 2016

The Gas Metal Arc(GMA) welding, called Metal Inert Gas(MIG) welding, has been an important component in manufacturing industries. A key technology for robotic welding processes is seam tracking system, which is critical to improve the welding quality and welding capacities. The objectives of this study were to develop the intelligent and cost-effective algorithms for image processing in GMA welding which based on the laser vision sensor. Welding images were captured from the CCD camera and then processed by the proposed algorithm to track the weld joint location. The proposed algorithms that commonly used at the present stage were verified and compared to obtain the optimal one for each step in image processing. Finally, validity of the proposed algorithms was examined by using weld seam images obtained with different welding environments for image processing. The results proved that the proposed algorithm was quite excellent in getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and could be employed for general industrial application.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.489-497
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• 2016

The rail fastening system, which provides a structural connection between the rail and the sleepers, is a main track component that plays an important role in retaining the rail gauge within acceptable tolerances, as well as in passing the train load to the roadbed through the sleepers. In this paper, a modal test was first performed to evaluate the dynamic characteristics (e.g., natural frequency) of the clips of the railway fastening system under the condition of rail corrugation in urban railway operation. The corrugation-induced passing frequency was then compared with the natural frequency of the clips to investigate any resonance effect during train passage. Furthermore, a field test under train passage was conducted to measure the accelerations on the rail and the rail fastening clips as well as the strains on the rail fastening clips in the rail corrugation condition. The field measurements indicated that the accelerations on the rail and the rail fastening clips have a close relationship with the rail corrugation, but they had a minimal effect on the strains of the rail fastening clips.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.1
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• pp.44-54
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• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• The Korean Journal of Air & Space Law and Policy
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• v.21 no.1
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• pp.169-189
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• 2006

In 2007, KSLV(Korea Small Launching Vehicle) that we made at Goheung National Space Center is going to launch and promotes of our space exploration systematically and 'Space Exploration Promotion Act' was enter into force. 'Space Exploration Promotion Act' article 3, section 1, as is prescribing "Korean government keeps the space treaties contracted with other countries and international organizations and pursues after peaceful uses of outer space." The representative international treaties are Outer Space Treaty (1967) and Liability Convention (1972) etc. In Liability convention article 2, "A launching State shall be absolutely liable to pay compensation for damage caused by its space object on the surface of the earth or to aircraft in flight. The important content of the art. 2 is the responsible entity is the 'State' not the 'Company'. According by Korean Space Exploration Act art. 14, person who launches space objects according to art. 8 and art. 11 must bear the liability for damages owing to space accidents of the space objects. Could Korean government apply the Products Liability Act which is enter into force from July 1, 2002 to space launching person? And what is the contact type between Korea Aerospace Research Institute(KARl) and Russia manufacturer. Is that a Co-Development contract or Licence Product contract? And there is no exemption clause to waive the Russia manufacturer's liability which we could find it from other similar contract condition. If there is no exemption clause to the Russia manufacturer, could we apply the Korean Products Liability Act to Russia one? The most important legal point is whether we could apply the Korean Products Liability Act to the main component company. According by the art. 17 of the contract between KARl and the company, KARl already apply the Products Liability Act to the main component company. For reference, we need to examine the Appalachian Insurance co. v. McDonnell Douglas case, this case is that long distance electricity communication satellite of Western Union Telegraph company possessions fails on track entry. In Western Union's insurance company supplied to Western Union with insurance of $ 105 millions, which has the satellite regard as entirely damage. Five insurance companies -Appalachian insurance company, Commonwealth insurance company, Industrial Indemnity, Mutual Marine Office, Northbrook Excess & Surplus insurance company- went to court against McDonnell Douglases, Morton Thiokol and Hitco company to inquire for fault and strict liability of product. By the Appalachian Insurance co. v. McDonnell Douglas case, KARl should waiver the main component's product liability burden. And we could study the possibility of the adapt 'Government Contractor Defense' theory to the main component company.