• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.681-686
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• 2010

Although the height of a ramp is an important design element, it has not been considered in prior studies. Therefore, in this study, the ramp slope and height are considered as independent variables. To analyze the effects of the slope and height, five levels of slope (1:6, 1:8, 1:10, 1:12 and 1:14) and three levels of height (15cm, 30cm and 45cm) are considered. For the dependent variables, the total time, velocity and perceived discomfort were considered as usability measures, pulse rate changes and EMG signals of four related muscles (extensor carpi radialis, triceps brachii, anterior deltoid and posterior deltoid) were considered as physiology measures. As a result, differences among usability and physiological characteristic for the five slopes increased as the height increased. Additionally, slope effects were minor when the height was low (15cm). Almost domestic/international regulations and guidelines related to ramp recommended 1:12 slope for the ramp design, however, there was no significant difference between 1:10 and 1:12 according to result of this study. In addition, slope effects were minor at a low height; thus, a slope of 1:8 can be recommended if the installation space for a gentler ramp is not sufficient.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.94-104
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• 2012

The purpose of this research is to quantify the compliance of on-road emission from a light duty diesel vehicle, based on a comparison to emission regulation standard. $NO_x$, CO and THC emissions were measured using a portable device on a selected real-world driving route with a length of approximately 22 km. On-road measurements were repeated by 10 times on a same route to reflect variability in traffic conditions. A test route was divided into 22 road links with length of 1 km to analyze emission results with higher spatial resolution. The average emissions of $NO_x$, CO and THC over total travel distance, which is approximately 220 km, were quantified to be in compliance with emission regulation standards. Under higher spatial resolution, $NO_x$ concentration exceeded a standard in 92 links out of 220 links. The extended time in stop period and the stop-and-go driving cycle were identified as two important reasons for increased $NO_x$ emissions in observed cases. Heavy traffics showed higher $NO_x$ emissions than free flow. These results indicate that the real-world vehicle emissions might exceed the compliance level associate with traffic conditions. Another interesting observation of this research is that the on-road emission characteristics can be independent to the average speed of road links with higher spatial resolution. Variability in on-road emission might not be fully described by solely relying on an average speed, because variability in traffic conditions and road conditions can influence on real-world vehicle emissions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1005-1018
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• 2017

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver's driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle' fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle's fault and noxious gas emitted to the outside.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.177-182
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• 2022

This study aim to verify the difference in muscle activity due to difference in the direction of the stroking method for the stroke direction of the muscles using a tool made by a 3D printer. The subjects were conducted with 20 healthy adults in their 20s, and IASTM applied the intervention of the perpendicular stroking on the direction of muscle driving and intervention of the pararell stroking on the direction of muscle driving, with 10 each deployed. All subjects measured the muscle activity before intervention, and the muscle activity was measured and compared with the independent T test and the paired T test. The results of this study showed a significant increase in muscle activity in vertical groups, although the muscle activity in horizontal groups decreased. It was that differences in direction are significant in the application of IASTM.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.591-596
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• 2022

Since 4-bar linkage widely used in various industrial fields has a fixed link length, it is inconvenient to add an independent link structure or control device to change the movement of output link. Therefore, this paper proposes a new concept of variable 4-bar linkage mechanism to selectively adjust the movement of the output link to fit desired situations, and applied to the commercial table fans, which is a representative product using a 4-bar linkage system. The optimal rotation angle steps for efficiency are determined experimentally and the appropriate lengths of linkage to fit each step are calculated analytically. Changes in the linkage length are implemented by the rotational motion using a grooved cylindrical cam and the feasibility of the proposed variable linkage mechanism is verified through fabrication and measurement. The presented variable link mechanism is expected to improve the efficiency of industrial robots and fuel valve systems.

• Journal of the Korean Society for Railway
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• v.17 no.1
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• pp.28-34
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• 2014

In this paper, a concept design of a rail type ultra-high-speed train is proposed and its dynamic characteristics are analyzed. Instead of the existing solid axle, a new type bogie system and independently rotating wheels are applied in the proposed train. In order to analyze the dynamic characteristics, a multibody dynamic model of a vehicle is developed and the basic validity is verified by eigenvalue analysis. Also, it is shown that the critical speed is improved in comparison to that of existing high-speed train model HEMU-430X. Finally, through 7000R curved track driving analysis at a speed of 550 km/h, the lateral force of the wheels and the derailment quotient are estimated and the applicability of the new concept railway vehicle is confirmed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.639-645
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• 2018

This paper is intended to develop a decision model that can be applied to autonomous vehicles and autonomous mobile vehicles. The developed module has an independent configuration for application in various driving environments and is based on a platform for organically operating them. Each module is studied for decision making on lane changes and for securing safety through reinforcement learning using a deep learning technique. The autonomous mobile moving body operating to change the driving state has a characteristic where the next operation of the mobile body can be determined only if the definition of the speed determination model (according to its functions) and the lane change decision are correctly preceded. Also, if all the moving bodies traveling on a general road are equipped with an autonomous driving function, it is difficult to consider the factors that may occur between each mobile unit from unexpected environmental changes. Considering these factors, we applied the decision model to the platform and studied the lane change decision system for implementation of the platform. We studied the decision model using a modular learning method to reduce system complexity, to reduce the learning time, and to consider model replacement.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.2
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• pp.251-259
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• 2000

The ionic wind formed in a nonuniform electric field has been recognized to have a significant effect on particle collection in an electrostatic precipitator(ESP). Under normal operating conditions the effect of ionic wind is not pronounced. However, as the flow velocity becomes smaller, the ionic wind becomes pronounced and induces secondary flow, which has a significant influence on the flow field and the particle collecting efficiency. In this paper, experiments for investigating the effect of secondary flow on collection efficiencies were carried out by changing the flow velocities in 0.2-0.7m/s and the applied voltages in 9-11kV/cm. The particle size distributions and concentrations are measured by DMA and CNC. To analyze the experimental results, numerical analysis of electric filed in ESP was carried out. It shows that particle collection is influenced by two independent dimensionless numbers, $Re_{ehd}\;and\;Re_{flow}$ not by $N_{ehd}$ alone. When $Re_{flow}$, decreases for constant $Re_{ehd}$, the secondary flow prohibits the particle collection. But when $Re_{ehd}$ increases for constant $Re_{flow}$, it enhances the particle collection by driving the particles into the collection region.

• Journal of Mechanical Science and Technology
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• v.14 no.9
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• pp.956-967
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• 2000

In this paper, we explore the issues of force display in the cooperative virtual environment shared by multiple users distributed over the network with heterogeneous hardware platforms. The proposed method is to cope with the problem of small time delay and the difference of sampling rate in the distributed configuration. In the proposed approach the interaction forces of the participants are just treated as the independent sources of acceleration. Thus the action of a participant simply changes the acceleration of the virtual object and consequently the states of the virtual object will be updated. When the updated states are reported to all the participants, the information on the time of state changes is delivered, too. Employing the discrete state information updated by the other users, each user modifies his own virtual environment and pseudo-realtime simulation can be realized. Excluding the software interface and the communication technique, it is proposed the simulation method for the operation of respective users and the way of calculating the driving input to the display device. For experimental verification we construct a cooperative virtual environment shared by two remote users and outline the results of experiments.

• Korean Management Science Review
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• v.22 no.1
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• pp.15-26
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• 2005

The bootstrap is a method of computational inference that simulates the creation of new data by resampling from a single data set. We propose a new job for the bootstrap: generating inputs from one historical trace using Threshold Bootstrap. In this regard, the most important quality of bootstrap samples is that they be functionally indistinguishable from independent samples of the same stochastic process. We describe a quantitative measure of difference between two time series, and demonstrate the sensitivity of this measure for discriminating between two data generating processes. Utilizing this distance measure for the task of generating inputs, we show a way of tuning the bootstrap using a single observed trace. This application of the threshold bootstrap will be a powerful tool for Monte Carlo simulation. Monte Carlo simulation analysis relies on built-in input generators. These generators make unrealistic assumptions about independence and marginal distributions. The alternative source of inputs, historical trace data, though realistic by definition, provides only a single input stream for simulation. One benefit of our method would be expanding the number of inputs achieving reality by driving system models with actual historical input series. Another benefit might be the automatic generation of lifelike scenarios for the field of finance.