• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.999-1011
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• 1994

Driving maneuvers in car-following are affected not only by the factors related to road and traffic conditions, but also by factors related to drivers' cognition to them. This paper attempts to analyse drivers' car-following distance tests on road characteristics. Driving maneuvers are directly observed by video recorder sets in the vehicle. At the same time drivers are interviewed about their cognitive degree of car-following distance according to a given level of cognitive language. As a result, linguistical cognition of car-following distance is well fitted in with Weber-Fechner's law. This paper suggests a modeling method that takes into account the driver's cognition for acquiring traffic visible information on driving maneuver.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.82-89
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• 2005

This study deals with the development of the extended Kalman filter(EKF) algorithm for the localization of underwater mining vehicles. Both simulation and experimental studies in a test bed are carried out. For the experiments, a scale dawn tracked vehicle is run in a soil bin containing cohesive soil of bentonite-water mixture. To develop the EKF algorithm, we use a kinematic model including the inner/outer track slips and the slip angle for the vehicle. The measurements include the inner and outer wheel speeds from encoders, the heading angle from a compass sensor and a fiber optic rate gyro, and x and y coordinate position values from a vision system. The vision sensor replaces the LBL(Long Base Line) sonar system used in the real underwater positioning situations. Artificial noise signals mimicking the real LBL noise signal are added to the vision sensor information. To know the mean slip values of the tracks in both straight and cornering maneuver, several trial running experiments are executed before applying the EKF algorithm. Experimental results show the effectiveness of the EKF algorithm in rejecting the sensor measurements noise. Also, the simulation and experimental results show close correlations.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.58-65
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• 2016

Lately, tugboats are widely used to maneuver vessels by pushing or towing them where tugboats use rope. In order to correctly control the motion of tugboat and towed vessel, the dynamics of the towline would be well identified. In real application environment, the towing rope length changes and the towing load is not constant due to the various sizes of towed vessel. And there are many ropes made by many types of materials. It means that it is not easy to obtain rope dynamics, such that it is too difficult to satisfy the given control purpose by designing control system. Thus real time identification or adaptive control system design method may be a solution. However it is necessary to secure sufficient information about rope dynamics to obtain desirable control performance. In this paper, the authors try to have several rope dynamic models by changing the rope length to consider real application conditions. Among them, a representative model is selected and the others are considered as uncertain models which are considered in control system design. The authors design a robust control to cope with strong uncertain and nonlinear property included in the real plant. The designed control system based on robust control framework is evaluated by simulation.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.31-34
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• 2021

The article considers the possibilities of increasing the accuracy of estimates of the parameters of the trajectory of the target with the provision of a given probability of stable support of the air object, in particular, during its maneuver. The aim of the work is to develop a filtration algorithm that provides a given probability of stable tracking of the air object by determining the regular components of filtration errors, in particular, when maneuvering the air object, and their compensation with appropriate correction of filter parameters and estimates of air object trajectory parameters.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.178-184
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• 2016

The motor power of the industry to use the electric energy is gradually increased. The electric motor generates a voltage drop in the starting current during startup. The starting current is started it is difficult to have an adverse effect on neighboring power systems with large motor starting when the voltage drop across the power grid. In addition to that the motor torque according to the load depending on the size of the rotation speed is changed to a motor start-up speed is important. However, the distance to the emergency generator transformers or motors from the motor capacity is smaller but short and difficult to maneuver the theory and practice of the operating characteristics of the starting characteristics of the motor used a lot of large industrial plants were measured and analyzed. Therefore, this study investigated the motor starting Analysis and interpretation for the relationship with the large motor starting torque and speed during motor starting.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.23-31
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• 2004

This paper focuses on a boundary surface based ray casting. In general the boundary surface based ray casting is processed in two stages. The first stage finds boundary surfaces and stores them into buffers. The second stage calculates a distance from a viewpoint to the voxels of the interested area by projecting boundary surfaces on the view plane, and then starts to traverse a volume data space with the distance. Our approach differs from the general boundary surface based ray casting in processing the first stage of it. Contrast to the typical boundary surface based ray casting where all boundary surfaces of volume data are stored into buffers, they are projected on the planes aligned to the axis of volume data coordinates and these projected data are stored into 6 buffers. Such maneuver shortens time for ray casting, and reduces memory usage because it can be carried out independently from the amount of the volume data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.206-212
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• 2017

Induction motor torque is the reactive power is needed which corresponds to the exciting current to generate the magnetic flux as the product of current and flux. For use in the method of supplying the required reactive power to the induction motor power factor correction apparatus using a lot of ways to supply in place of the power supply side, when using a power factor compensation device can reduce the apparent power, the power factor can be improved. However, the distance to the emergency generator transformers or motors from the motor capacity is smaller but short and difficult to maneuver the theory and practice of the operating characteristics of the starting characteristics of the motor used a lot of large industrial plants were measured and analyzed. Therefore, this study investigated the motor starting Analysis and interpretation for the relationship with the large motor starting torque and speed during motor starting.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.271-278
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• 2011

Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.151-155
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• 2019

The purpose of this study is to investigate the knowledge and performance ability of cardiopulmonary resuscitation (CPR) of physical therapist. A total of 105 physical therapists participated in this study. All participants were responded a self-administered method questionnaire to investigate the knowledge of CPR, and measured on their performance ability of CPR by Braden Pro application. We identified the performance ability of CPR and compared between educated and uneducated group. Among the 7 items on the knowledge of CPR questionnaire, educated group scored higher than uneducated group in Sequence of CPR, Ratio of compression and ventilation, Position of hands for chest compressions, Compression rate of chest and Ventilation volume. However, Depth of chest compressions and Airway maneuver were scored higher in uneducated group. The performance ability of CPR was not significantly different between two groups. However, Compression rate of chest was higher than guideline of CPR in both groups. There were inconsistent results between the knowledge and performance ability of CPR whether educated or not. This study suggests that it needs to provide repeated educations that improve knowledge and performance ability of CPR in physical therapists.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.79-88
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• 2019

This study analyzes the influential factors and patterns associated with death from aircraft accidents and incidents using data mining techniques. To this end, we used two datasets for aircraft accidents and incidents, one from the National Transportation Safety Board (NTSB) and the other from the Federal Aviation Administration (FAA). We developed our prediction models using the decision tree classifier to predict death from aircraft accidents or aircraft incidents and thereby derive the main cause factors and patterns that can cause death based on these prediction models. In the NTSB data, deaths occurred frequently when the aircraft was destroyed or people were performing dangerous missions or maneuver. In the FAA data, deaths were mainly caused by pilots who were less skilled or less qualified when their aircraft were partially destroyed. Several death-related patterns were also found for parachute jumping and aircraft ascending and descending phases. Using the derived patterns, we proposed helpful strategies to prevent death from the aircraft accidents or incidents.