In this paper, the goal is to obtain a dynamic model of a particular system. The system is a combination of a wheeled vehicle(chassis) with a turret rotating in azimuth direction and a gun rotating in a elevation direction. At this time, the motion of the gun according to the shaking of the continuous shot is obtained using the coordinate transformation equation in the azimuth and elevation angle. Also, the dynamic model for the swaying of wheeled vehicle is obtained through the Lagrange’s equation. Through this, we analyze the tumbles of the gun, whiat is the major term, and what dynamics are needed for stabilization control.

Rye, whole-crop barley and Italian Ryegrass are major winter forage species in Korea, and yield monitoring of winter forage species is important to improve forage productivity by precision management of forage. Forage monitoring using Unmanned Aerial Vehicle (UAV) has offered cost effective and real-time applications for site-specific data collection. To monitor forage crop by multispectral camera with UAV, we tested four types of vegetation index (Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI). Field measurements were conducted on paddy field at Naju City, Jeollanam-do, Korea between February to April 2019. Aerial photos were obtained by an UAV system and NDVI, GNDVI, NGRDI and NDREI were calculated from aerial photos. About rye, whole-crop barley and Italian Ryegrass, regression analysis showed that the correlation coefficients between dry matter and NDVI were 0.91∼0.92, GNDVI were 0.92∼0.94, NGRDI were 0.71∼0.85 and NDREI were 0.84∼0.91. Therefore, GNDVI were the best effective vegetation index to predict dry matter of rye, wholecrop barley and Italian Ryegrass by UAV system.

The purpose of this study is to obtain data on the zones formed by the movement of livestock vehicles and to determine if such areas can be used to establish quarantine activities and quarantine policies for livestock epidemics. For this purpose, this study used mobile data on poultry-related livestock vehicles generated in 2019. InfoMap, a community detection method, was used for regional classification, and the results of the analysis were visualized on a map using GIS. The study results confirmed that the zone of the administrative unit can be classified based on the movement of livestock vehicles. In addition, the zones created by the vehicle movement could be seen to change depending on the purpose and timing of the operation of livestock vehicles. Some areas form relatively stable zones, such as Jeolla-do and Gyeongsang-do, while others change depending on the situation, such as Chungcheong-do, Gyeonggi-do, and Gangwon-do. Further, the zones derived for poultry differed from those derived for cattle and pigs in previous studies.

In this study, analyzed the cause of failure of the cardan shaft for water propulsion of an armored wheeled vehicle. During the development test(DT), the vehicle was deflected to the left on the water. As a result of the confirmation, increasing angular displacement and abrasion of SPIDER(Universal joint) occurred. As a result of a structure analysis and torsion fracture test, cause of failure is not insufficient design and strength deficit of each parts. and as a result of a simulation review of the assembly layout of each part, it was confirmed that excessive rotational vibration occurred. In order to solve this problem, improved the assembly layout of the water propulsion system and the worn SPIDER lubrication. Since there has been no occurrence of the same case between military operations so far, it has been confirmed that the improvement plan is appropriate.

The premature failure of the universal joint connecting the drive gear box and the cooling fan caused a deterioration in serviceability and operability. Universal joint is a device that transmits engine power to a cooling fan. Internal pin breakage and shaft separation can cause secondary damage such as cooling fan malfunction and radiator damage caused by component failure. The purpose of this paper is to analyze the damage phenomenon of universal joints caused by bundles in SPVs and to improve them. In order to verify the improvement, a single part test and a system conformance test were conducted, and durability test was conducted to confirm the improvement effect on the improved prototype. Through these, the effects of increasing the durability of the improved product were estimated.

In this study, the failure characteristic of the center floor of a front-wheel drive vehicle was investigated according to material. UHSS, Al6061-T6, CFRP, and CFRP-Al were used as materials. As the analysis condition, a fixed support was applied to the rear surface of the center floor and a forced displacement of 2 mm/sec was applied to the front surface. As the result, when comparing with the equivalent stress and strain energy according to the material, it was found that UHSS, Al6061-T6, CFRP, and CFRP-Al were higher in the order. Also, when comparing with the equivalent strain due to the material, it was shown that the equivalent strain was high in the order of Al6061-T6, UHSS, CFRP and CFRP-Al. As for the damage characteristic of the center floor according to the material, it was found that the highest structural stability was obtained when UHSS was used. However, it was found that it was good to utilize Al6061-T6 in order to acquire the structural stability along with the structure with the lighter weight.

This study examined the spatial autocorrelation of the 2016 foot and mouth disease (FMD) outbreaks in South Chungcheong to determine the association between the disease epidemics and pig farm vehicle movements. Two spatial autocorrelation testing methods were used: Moran’s I and Getis-Ord G statistics. The Moran’s I statistic for the FMD outbreak areas was -0.239, and its p-value was less than 0.007. The median Getis-Ord G statistic for the FMD outbreak areas was -0.323. The results indicated that the geographical distribution of the FMD outbreak areas was not spatially homogeneous. The spatial autocorrelation of the 2016 FMD epidemics was considered by applying a geographical weighted Poisson regression (GWPR) model in the analysis, in which pig farm vehicle movements were used as risk factors for the 2016 FMD epidemics. The number of FMD-infected farms per second-level administrative province (si or gun) was used as a dependent variable. The number of farm vehicle movements within the province (within variable), from one province to other provinces (outbound variable), or from other provinces to one province (inbound variable), were included as independent variables in the GWPR model. The results of the GWPR model were as follows. The estimated median coefficient of the log-transformed within variable, the log-transformed outbound variable, and log-transformed inbound variable were -0.000, 0.010, and -0.009, respectively. The optimal bandwidth for the GWPR model was 80.49, and the AIC score was 89.35. The results showed that the GWPR model would provide an understanding of the relationship between the 2016 FMD epidemics and pig farm vehicle movements

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

본 논문은 버스정류장 미세먼지 저감을 위해 설계된 도로시설물의 성능평가 과정 및 결과를 보고한다. 먼저, 유한요 소해석 프로그램인 LS-DYNA를 이용하여 대상 구조물에 대한 충돌해석이 수행되었다. 해석변수로 차량의 속도와 충돌 위치를 고려한 다양한 조건에서의 구조해석이 진행되었다. 대상 시설물의 성능은 이 결과를 이용하여 구조적 성능과 충돌 후 차량의 안전성능이 평가되었다. 해석결과로부터 충돌속도가 증가하고 충돌위치가 전면으로 갈수록 시설물의 구조성능과 차량의 충돌 후 안전성능이 저하되는 것이 콘크리트의 손상량을 통해 확인되었다. 더불어 충돌 후 차량의 거동에 대한 분석을 통해 시설물에 연속되는 연석이 설치되면 차량의 이탈을 방지해 안전성능을 확보하는 것으로 예측되었다. 최종적으로, 대상 시설물은 설계 시 고려된 목표 충돌속도 25km/h보다 더 큰 40km/h까지 충분한 안전성능을 확보하고 있다는 것이 확인되었다.

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

Since the first HPAI epidemics in 2003, there has been little epidemiological research on the association between HPAI epidemics and vehicle movements around poultry farms. This study examined the relationship between vehicle movements around poultry farms and the 2014/15 HPAI epidemics in the Republic of Korea using two methods: a boosted regression trees (BRT) model and logistic regression of a generalized linear model (GLM). The BRT model considers the non-linearity association between the frequency of vehicle movements around poultry farms and the HPAI outbreak status per province using a machine learning technique. In contrast, a GLM assesses the relationship based on the traditional frequentist method. Among the three types of vehicle movements (outbound, inbound, and within), only the outbound was found to be a risk factor of the 2014/15 HPAI epidemics according to both the BRT model and multivariate logistic regression of GLM. In the BRT model results, the median relative contribution of the log-transformed outbound variable was 53.68 (range: 39.99 – 67.58) in the 2014 epidemics and 49.79 (range: 33.90 – 56.38) in the 2015 epidemics. In the GLM results, the odds ratio of the log-transformed outbound variable was 1.22 for the 2014 HPAI epidemics (p < 0.001) and 2.48 for the 2015 HPAI epidemics (p < 0.001), respectively. The results indicated that intensive disinfection measures on outbound movement were needed to reduce the risk of HPAI spread. The current BRT models are suitable for risk analysis because the median area under the receiver operating characteristic curve was 0.83 (range: 0.74 – 0.91) and 0.85 (range: 0.73 – 0.87) for the 2014 and 2015 epidemics models, respectively. The Akaike information criterion scores for the multivariate logistic regression of GLM were 150.27 and 78.21 for the 2014 and 2015 epidemics models, respectively. These scores were relatively lower than those from the univariate logistic regression of GLM.

MDPS control has been a difficult problem for the past two decades. Though there are many ways to control steering feeling, the MDPS control logic is still being upgraded or developed for steering feel improvement. A new point of view in MDPS is proposed by evolution logic, which is a new driver friendly improvement based on the analysis of driver’s driving pattern. As a result of the application of evolution logic, this paper shows that drivers behaviour effecting factors among MDPS parameters will efficiently lead to customers’ satisfaction.

This study has related to lightweight automobiles due to global warming with the reduction of fossil fuel reserves are rapidly progressing around the automobile industry. This study has revealed the relationship for the mechanical properties via the analyzed microstructure, precipitated phase variation of the wheel hub of a commercial vehicle manufactured using molten forging technology using A356 and A357 alloys, which are high-strength Al-Si-Mg base cast aluminum alloys. Differential scanning calorimetry has performed to analyze the precipitation amount of each alloy that influences the mechanical properties of aluminum alloy. The XRD analysis has measured for the microstructure's crystal phase on A356 and A357 alloys. In this paper has evaluated to compare the properties of the A356 alloy and the A357 alloy for the mechanical properties. The A356 alloy has confirmed that a microstructure is finer than A357 alloy, and a quantity of precipitated material is more than A357 alloy. Therefore, this study confirmed that the A356 alloy has better mechanical properties than the A357 alloy.

본 연구에서는 뇌파와 맥파를 이용한 생체신호 분석을 통해 자율주행차량 사용자에게 안정감을 유발하는 최적의 색온도를 제안하고자 하였다. 이를 위해 3000 K, 4000 K, 5000 K, 6000 K의 색온도를 갖는 조명을 자율주행 환경에 적용하여 제시하였다. 실험은 자동차 그래픽 시뮬레이터가 구비된 실험실에서 진행되었으며, 실험절차는 다음과 같다. 1) 안정기(5분), 2) U-K테스트(3분), 3) 자율주행+조명(3분). 이 과정은 색온도를 변경해가며 총 4회 반복되었다. 수집된 시계열데이터에 대해 주파수 분석을 실시하였고 파워 스펙트럼 분석을 통해 주파수 대역별 power값을 산출하였다. 뇌파는 안정의 지표인 α파와 각성의 지표인 β에 대해 분석을 실시하였으며, 맥파의 경우 교감신경계 활성도에 대해 분석을 실시하였다. 산출된 데이터는 연구대상자 개인 간 편차를 줄이기 위해 정규화하여 통계분석을 실시하였다. 1차 분석 결과, 뇌파의 경우 5000 K의 조명을 제시하였을 때 α파가 가장 높았고, 대부분의 조명 제시 상황에서 β파가 증가하였다. 맥파의 경우 주행 상황에서 SNSA가 증가하였다. β파와 SNSA에 대한 2차 분석 결과, 유의수준 5%에서 색온도 간 유의한 차이가 인정되지 않았다. 결론적으로, α파가 가장 높은 5000 K의 색온도가 안정감을 유발한다고 볼 수 있다. 이러한 결과를 자율주행차량에 적용한다면, 탑승자의 높은 만족도를 유발할 수 있을 것으로 보인다. 나아가, 이와 같은 긍정적인 효과가 자율주행차량의 수용으로 이어질 수 있다.

The goal of the current study was to estimate the contribution of poultry farm vehicle movement frequency to the 2014 highly pathogenic avian influenza (HPAI) epidemic using both global and local regression models. On one hand, the global model did not consider the hypothesis that a relationship between predictors and the outcome variable might vary across the country (spatially homogeneous), while on the other hand, the local model considered that there was spatial heterogeneity within the country. The HPAI outbreak status in each province was used as a dependent variable and the number of poultry farm vehicle movements within each province (within variable), the number of poultry farm vehicle movement from one province to another province (outbound variable), the number of poultry farm vehicle movements from other provinces to one province (inbound variable), and the number of poultry farms in each province were included in the model as independent variables. The results of a global model were as follows: estimated coefficient of the log-transformed within variable was 0.73, that of the log-transformed outbound variable was 2.04, that of the log-transformed inbound variable was 0.74, and that of the number of poultry farms was 1.08. Only the number of poultry farms was a statistically significant variable (p-value < 0.001). The AIC score of the global model was 1397.5. The results of the local model were as follows: estimated median coefficient of the log-transformed within variable was 0.75, that of the log-transformed outbound variable was 2.54, that of the log-transformed inbound variable was 0.60, and that of the number of poultry farms was 0.07. The local model’s AIC score was 1382.2. The results of our study indicate that a local model would provide a better understanding of the relationship between HPAI outbreak status and poultry farm vehicle movements than that provided by a global model.