• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.186-188
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• 2014

In recent years, domestic as well as LTE wireless network of Wi-Fi and most used. In addition, mobile-intensive services that used mainly in our society makes it easier, SNS, application (APP), and file downloads. As such, the amount of data requested, while living at the time of mobile users will want to be safe from the earliest. And the wireless network communications mortality (3G, 4G (LTE), LTE-A) and Wi-Fi (802.11 n-2.4 G H z z H a c-5, 802.11 G), and users are mainly used in the death 4G (LTE), communication Wi-Fi, 802.11 n-2.4 GHz are used most frequently. As above, use the wireless network in order to safely and quickly developed the technology of the Li-Fi. Li-Fi light (visible light) technology to communicate with, and Wi-Fi (802.11 n-2.4 G z H) 100 times faster, LTE-A 66 times faster. However, the current Li-Fi to commercialise the big issue exists. In this paper, there are a lot of existing problems in the commercialization of Li-Fi being used in Wi-Fi, and a comparative analysis.

• Korean Journal of Materials Research
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• v.28 no.11
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• pp.663-670
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• 2018

H13 tool steels are widely used as metallic mold materials due to their high hardness and thermal stability. Recently, many studies are undertaken to satisfy the demands for manufacturing the complex shape of the mold using a 3D printing technique. It is reported that the mechanical properties of 3D printed materials are lower than those of commercial forged alloys owing to micropores. In this study, we investigate the effect of microstructures and defects on mechanical properties in the 3D printed H13 tool steels. H13 tool steel is fabricated using a selective laser melting(SLM) process with a scan speed of 200 mm/s and a layer thickness of $25{\mu}m$. Microstructures are observed and porosities are measured by optical and scanning electron microscopy in the X-, Y-, and Z-directions with various the build heights. Tiny keyhole type pores are observed with a porosity of 0.4 %, which shows the lowest porosity in the center region. The measured Vickers hardness is around 550 HV and the yield and tensile strength are 1400 and 1700 MPa, respectively. The tensile properties are predicted using two empirical equations through the measured values of the Vickers hardness. The prediction of tensile strength has high accuracy with the experimental data of the 3D printed H13 tool steel. The effects of porosities and unmelted powders on mechanical properties are also elucidated by the metallic fractography analysis to understand tensile and fracture behavior.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.783-791
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• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.1
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• pp.76-82
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• 2019

This study was investigate the characteristics of GHGs ($CO_2$, $CH_4$, and $N_2O$) emissions of diesel medium duty trucks according to their various driving modes. GHGs emissions decreased as vehicle speed increased, and emissions increased after 64.7 km/h. The 4.5 ton trucks show higher values of $CO_2$, $CH_4$, $N_2O$, 35%, 25%, and 57%, respectively, comparing of the 2.5 ton trucks. Also, $CO_2$ emissions under WHVC mode were 20% lower than those under the NEDC mode. In the case of cold start condition, $CO_2$ emissions were 12-13% higher than those for hot start condition. In the future, the result of present study will provide basic data to set up GHGs emission standards for medium and heavy duty vehicles.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.930-938
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• 2018

Underwater noise radiated from submarines is directly related to the probability of being detected by the sonar of an enemy vessel. Therefore, minimizing the noise of a submarine is essential for improving survival outcomes. For modern submarines, as the speed and size of a submarine increase and noise reduction technology is developed, interest in flow noise around the hull has been increasing. In this study, a noise analysis technique was developed to predict flow noise generated around a submarine shape considering the free surface effect. When a submarine is operated near a free surface, turbulence-induced noise due to the turbulence of the flow and bubble noise from breaking waves arise. First, to analyze the flow around a submarine, VOF-based incompressible two-phase flow analysis was performed to derive flow field data and the shape of the free surface around the submarine. Turbulence-induced noise was analyzed by applying permeable FW-H, which is an acoustic analogy technique. Bubble noise was derived through a noise model for breaking waves based on the turbulent kinetic energy distribution results obtained from the CFD results. The analysis method developed was verified by comparison with experimental results for a submarine model measured in a Large Cavitation Tunnel (LCT).

• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Atmosphere
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• v.29 no.3
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• pp.325-342
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• 2019

Precipitation and no-precipitation events under the influence of the Siberian high pressure system in Yeondong region, were analysed and classified as four types [obvious precipitation event (OP) type, obvious no-precipitation event (ON) type, ambiguous precipitation event (AP) type and ambiguous no-precipitation event (AN) type], according to the easiness in determining whether to have precipitation or not in Yeongdong region, to help in improving the forecast skill. Concerning the synoptic pressure pattern, for OP type, the ridge of Siberian high extends from Lake Baikal toward Northeast China, and there is a northerly wind upstream of the northern mountain complex (located near the Korean-Chinese border). On the other hand, for ON type, the ridge of Siberian high extends southeastward from Lake Baikal, and there is a westerly wind upstream of the northern mountain complex. The pressure pattern of AP type was similar to the OP type and that of AN type was also similar to ON type. Thus it was difficult to differentiate AP type and OP type and AN type and ON type based on the synoptic pressure pattern only. The four types were determined by U (wind speed normal to the Taebaek mountains) and Froude number (FN). That is, for OP type, average FN and U at Yeongdong coast are ~2.0 and ${\sim}6m\;s^{-1}$, and those at Yeongseo region are 0.0 and $0.1m\;s^{-1}$, respectively. On the contrary, for ON type, average FN and U at Yeongdong coast are 0.0 and $0.2m\;s^{-1}$, and those at Yeongseo region are ~1.0 and ${\sim}4m\;s^{-1}$, respectively. For AP type, average FN and U at Yeongdong coast are ~1.0 and ${\sim}4m\;s^{-1}$, and those at Yeongseo region are 0.0 and $0.2m\;s^{-1}$, whereas for AN type, average FN and U at Yeongdong coast are 0.1 and $0.6m\;s^{-1}$ and those at Yeongseo region are ~1.0 and ${\sim}3m\;s^{-1}$, respectively. Based on the result, a schematic diagram for each type was suggested.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.495-505
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• 2019

Typical algorithms of deep learning include CNN(Convolutional Neural Networks), which are mainly used for image recognition, and RNN(Recurrent Neural Networks), which are used mainly for speech recognition and natural language processing. Among them, CNN is able to learn from filters that generate feature maps with algorithms that automatically learn features from data, making it mainstream with excellent performance in image recognition. Since then, various algorithms such as R-CNN and others have appeared in object detection to improve performance of CNN, and algorithms such as YOLO(You Only Look Once) and SSD(Single Shot Multi-box Detector) have been proposed recently. However, since these deep learning-based detection algorithms determine the success of the detection in the still images, stable object tracking and detection in the video requires separate tracking capabilities. Therefore, this paper proposes a method of combining Kalman filters into deep learning-based detection networks for improved object tracking and detection performance in the video. The detection network used YOLO v2, which is capable of real-time processing, and the proposed method resulted in 7.7% IoU performance improvement over the existing YOLO v2 network and 20 fps processing speed in FHD images.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.30-38
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• 2019

In recent years, researches on various communication methods have been conducted, particularly on OFDM (Orthogonal Frequency Division Multiplexing) and CDMA (Code Division Multiple Access) methods, as the use of underwater communication increases. While OFDM is, in general, advantageous in that it is resistant to Doppler in the water and it enables a high-speed communication, CDMA is resistant to frequency selective fading in the water and it can reduce energy consumption. Therefore, in this paper, we performed experiments in the shallow water in Western Sea of Korea to analyze the performance of OFDM and CDMA communication systems in the underwater channel environment. The maximum delay spread and Doppler spread were drawn by using the data obtained from the real sea area in order to analyze the underwater channel environment characteristics of the shallow water in Western Sea of Korea. The communication performances of OFDM and CDMA are shown as coded BER (Bit Error Rate) according to the variation of the maximum delay spread and the Doppler spread, respectively. The result of the analysis show that the OFDM method has more resistant performances to the underwater channel environment changes than the CDMA method.