• 한국군사과학기술학회지
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• 제25권1호
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• pp.9-22
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• 2022

A fighter performing a reconnaissance mission is equipped with a pod that drives optical/infrared sensors for acquiring and identifying target information on the lower part of the fuselage. Due to the nature of the reconnaissance mission, the fighter performs high speed evasive maneuvers, and the resulting load should be considered importantly for the development of the pod. This paper concerns a numerical investigation into the inertial and aerodynamic loads of the airborne pod of high performance aircrafts. For the aerodynamic load analysis, the pylon and pod shapes are added to the fighter 3D model, and the commercial software was used for static and dynamic analysis. Considering the practical mission conditions, the common/extreme conditions were established respectively in the static and dynamic situations of pods and the driving torque could be tripled under dynamic conditions. In the analysis of inertia load, a 3-DOF model considering roll and turning maneuvers was derived by the Lagrangian method, and then the numerical integration method was applied to the analysis. As a results, it was conformed that the inertia load was generally induced at a low level compared to the aerodynamic load, but depending on the unbalance mass condition of the pod, the inertia load cannot be negligible.

• 한국음향학회지
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• 제40권6호
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• pp.571-577
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• 2021

본 연구는 기존의 엔진 없이 전기로 운행되는 자동차에 가상의 엔진소리를 구현해주는 반도체 에 관한 연구로, 운전자의 욕구 및 보행자의 안전을 지키기 위해 Adaptive Difference PCM(ADPCM) 방식과 Frequency modulation 방식을 조합하여 생생한 엔진음을 구현하였다. 또한 미디를 응용하는 전자음 합성 알고리즘을 제안하여 엔진음 합성방법, 엔진음 발생 시스템의 구성 모델을 제시한다. 본 연구는 운전자와 보행자를 모두 만족시키기 위해 캔 통신을 이용하여 운전자의 운전 습관에 따라 전해지는 엔진회전량, 차량 속도, 가속 페달 눌림 량, 토크 등의 정보를 받은 후, 미리 설정된 적절한 파라미터에 따라 주파수 변조를 위한 인터폴레이션, 정보량 축소를 위하 ADPCM 알고리즘, 엔진음을 쉽게 만들기 위한 미디 포맷을 이용하여 시스템과 운전자의 의도를 정확히 반영할 수 있는 인터렉션 알고리즘을 구현하였다.

• 전기전자학회논문지
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• 제26권3호
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• pp.401-407
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• 2022

최근 자율주행 자동차를 구현하기 위해 카메라 영상을 통해 객체 및 차선을 인식하여 자율주행하는 영상처리 기술이 연구되고 있다. 안개는 카메라 촬영 영상의 가시성을 떨어뜨리기 때문에 자율주행 자동차 오작동의 원인이 된다. 이를 해결하기 위해 카메라에 실시간 처리가 가능한 안개 제거 기능을 적용하는 것이 필요하다. 따라서 본 논문에서는 성능이 우수한 Sim의 안개 제거방법을 실시간 처리가 가능한 하드웨어로 구현한다. 제안하는 하드웨어는 Verilog HDL을 사용하여 설계하였고, Xilinx사의 xc7z045-2ffg900을 Target device로 설정하여 FPGA 구현하였다. Xilinx Vivado 프로그램을 이용한 논리합성 결과 4K(4096×2160) 고해상도 환경에서 최대 동작 주파수 276.932MHz, 최대 처리 속도 31.279fps를 가짐으로써 실시간 처리 기준을 만족한다.

• 한국산업융합학회 논문집
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• 제25권4_2호
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• pp.655-662
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• 2022

Recently, with the increase in the use of UAV(unmanned aerial vehicles), research on horizontal maintenance stations that can take off and land in various environments has been actively conducted. These stations can safely land UAV through multiple DOF(degrees of freedom) or at least 2-DOF-based actuator actuation. Among them, many researchers are dealing with the multi-DOF stewart platform due to its high safety. However, the stewart platform requires high-precision control technology because it requires a lot of torque to actuate according to the load action. Therefore, in this paper, to solve the mentioned problem, a bevel gear-based 2-DOF horizontal maintenance station system is proposed. The proposed system is configured to prevent damage due to air resistance when maintaining ships and to install it in a small space. Also, in terms of system configuration, the bevel gear-based horizontal maintenance system has the main advantage of being able to take off and land UAVs of various sizes through the replacement of station pads. The driving of the system consists of a simple form that can control the motor by adjusting the rotation speed of the motor according to the sea waveform.

• International journal of advanced smart convergence
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• 제11권3호
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• pp.222-228
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• 2022

As a means to cope with the climate change crisis caused by global warming, automobile manufacturers continue to make efforts to use the driving energy of vehicles as electricity. As a result, parts industry such as battery, motor, and controller are attracting attention. China is often seen in large cities, with electric vehicles such as electric bicycles, electric motorcycles, and small electric vehicles popularized and commercialized, mainly in large cities. However, small electric vehicles are not popular in Korea, which is why the country's topography is high in hills. In order to drive the hilly domestic roads, power performance including vehicle climbing ability should be improved. In order to improve the power performance and the climbing capacity of small electric vehicles, the capacity of the motor should be increased. However, when the performance of the motor is improved, the weight of the motor becomes heavy and the price competitiveness is likely to decrease. In addition, in order to operate a high-performance motor, the power consumption of the battery is rapidly increased, so various problems must be solved. In order to commercialize a small electric vehicle for one or two people who do not emit harmful exhaust gas to the human body in a hilly domestic terrain, it is effective to have a separate transmission system. In this study, we were conducted dynamometer test to produce a continuously variable transmission(CVT) system prototype using a spring that can be applied to a small electric vehicle and to install a CVT system prototype manufactured in a small electric vehicle. The dynamometer test results showed that the maximum speed performance, acceleration performance, and climbing performance were improved.

• 산업융합연구
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• 제20권8호
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• pp.69-75
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• 2022

초등학교 주변에는 교통약자인 어린이 교통사고를 예방하기 위하여 어린이 보호구역내 스쿨존(school zone)을 지정하여 이 구역내에서는 차량 운행속도를 30km/h 미만으로 운행함에 따라 주·정차가 금지되어 있다. 하지만 우리나라는 OECD 국가 중 어린이 교통사고 사망률이 1위라는 불명예를 안고 있다. 이와 같은 배경하에 본 연구는 어린이 보호구역에서의 다양한 도로여건에 따라 불법 주·정차 차량으로 인한 운전자 시야확보 및 주행차량에 대한 인지의 어려움 등이 상존하고 있어, 이에 어린이 보호구역 내에 불법 주·정차방지 시스템을 구축함으로써 교통약자인 어린이들에 대해 교통사고방지와 운전자 안전운전에 대한 경각심 증진에 기여하기 위함에 연구의 목적을 두었다. 연구 방법으로는 주요선행연구와 문헌조사 및 분석을 바탕으로 주·정차방지시스템에 대한 구축방안을 제시하였다. 구축방안을 통해 교통사고 방지, 스마트한 운전자의 안전운행 유도, 보행자 안전의식 강화, 운전자의 안전의식 경각심 유도 등 효과를 기대할 수 있다.

• 드라이브 ㆍ 컨트롤
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• 제20권3호
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• pp.15-24
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• 2023

The aim of this study was to measure and evaluate the exhaust emission factors of agricultural tractors. Engine characteristics and three exhaust emissions (CO, NO_x, PM) were collected under actual agricultural operating conditions. Experiments were performed on idling, driving, plow tillage, and rotary tillage. The load factor (LF) was calculated using the collected engine data, and the emission factor was analyzed using the LF and exhaust emissions. The engine characteristics and exhaust emissions were significantly different for each working condition, and in particular, the LF was significantly different from the currently applied 0.48 LF. The data distribution of exhaust emissions was different depending on the engine speed. In some conditions, the emission factor was higher than the exhaust emission standards. However, since most emission limit standards are values calculated using an engine dynamometer, even if the emission factor measured under actual working conditions is higher, it cannot be regarded as wrong. It is expected that the results of this study can be used for the inventory construction of a calculation for domestic agricultural machinery emissions in the future.

• 대한원격탐사학회지
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• 제39권4호
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• pp.441-458
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• 2023

Tropical cyclones frequently occur in the Southwest Pacific Ocean and are considered one of the driving forces for coastal alterations. Therefore, this study investigates the frequency and intensity of tropical cyclonesfrom 2000 to 2021 and their influence on the surface winds and wave conditions around the atoll nation Tuvalu. Cyclone best-track and ERA5 single-level reanalysis data are utilized to analyze the condition of the surface winds, significant wave heights, mean wave direction, and mean wave period. Additionally, the scatterometer-derived wind information was employed to compare wind conditions with the ERA5 data. On average, nine cyclones per year originated here, and the frequency increased to 11 cyclones during the last three years while the intensity decreased by 25 m/s (maximum sustained wind speed). Besides, a total of 14 cyclones were observed around Tuvalu during the period from 2015 to 2021, which showed an increase of 3 cyclones compared to the preceding period of 2001 to 2007. During cyclones, the significant wave height reached the highest 4.8 m near Tuvalu, and the waves propagated in the east-southeast direction during most of the cyclone events (52%). In addition, prolonged swells with a mean wave period of 7 to 11 seconds were generated in the vicinity of Tuvalu, for which coastal alteration can occur. After this preliminary analysis, it was found that the waves generated by cyclones have a crucial impact in altering the coastal area of Tuvalu. In the future, remotely sensed high-resolution satellite data with this wave information will be used to find out the degree of alterations that happened in the coastal area of Tuvalu before and after the cyclone events.

• 한국전자통신학회논문지
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• 제18권4호
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• pp.723-730
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• 2023

본 논문에서는 Personal Mobility에 사용되는 스마트헬멧의 안전성 보강을 제안한다. 주요 내용은 헬멧이 안전 신호를 보낼 수 있도록 아두이노를 베이스로 사용하여 초음파 센서를 활용한 거리별, 각도별 변화에 따라 센서의 값을 설정하여 오차를 최소화하여 원활한 인식이 되도록 하였다. 또한, 자이로센서를 활용하여 각 기울기에 따른 방향지시등이 점등되도록 하였다. CDS 센서를 이용하여 야간에 150 lux 이하로 내려갈 시 LED가 점등되도록 설계하였다. 최종적으로 5cm 이내에서 헬멧 착용 여부를 확인할 수 있으며, 평균속도 주행 시 10도에서 방향지시등이 점등되며, 150lux 이하에서 LED가 점등됨을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.