• Proceedings of the Plant Resources Society of Korea Conference
• /
• 2020.08a
• /
• pp.96-96
• /
• 2020

Soybean seeds are important sources of non-nutritive health promoting metabolites. The contents of these metabolites are affected by both genetic and environmental factors. In the present study, the contents of five common isoflavones including daidzin, genistin, glycitin, malonyldaidzin, and malonylgenistin were analyzed in 72 soybeans of different seed coat colors, diversity, and of different origins including China (22), Japan (9), USA (12), India (4), and Korea (25). The average total isoflavone content (TIC) was maximum in Indian soybeans (3302.36 ㎍/g) and minimum in Chinese landraces (1214.95 ㎍/g). The Korean landraces had higher average TIC (2148.05 ㎍/g) than the USA genetic materials (1580.23 ㎍/g) and Japanese landraces (1485.99 ㎍/g). The content of malonylgenistin was in the range of 54.31 - 2385.68 ㎍/g in the entire population, and was the most abundant isoflavone irrespective of origin although there was content variation among individual soybeans. Besides, glycitin was the least concentrated isoflavone, and its content ranged from 0.00 to 79.79 ㎍/g. With respect to seed coat color, green soybeans from all countries displayed the maximum malonylgenistin and TIC contents. Exceptions were those of Korean and Indian origins where black and yellowish-green soybeans presented the highest malonylgenistin and TIC contents, respectively. In multivariate analysis, 92.72% of the variance was explained by the first two principal components, and the soybeans were grouped in to three clusters based on isoflavone contents. Overall, our findings signify the importance of seed coat color and origin as discriminant parameters, and provide wide spectrum of routes for breeding soybean cultivars.

• Journal of Advanced Navigation Technology
• /
• v.25 no.6
• /
• pp.476-483
• /
• 2021

In order to maintain the safety of the airspace with ever increasing traffic volume, it is necessary to thoroughly analyze the collision risk with the current data. In this study, collision risk analysis was conducted using Detect and Avoid (DAA) Well-Clear (DWC) metrics, risk induces developed for the DAA systems of unmanned aerial vehicles. All flights in year 2019 that flew within the Incheon Flight Information Region (FIR) boundary were analyzed using the recorded Automatic Dependent Surveillance-Broadcast(ADS-B) data. High risk regions as well as trends by airports and seasons were identified. The results indicate that the risk is higher around the congested area near Incheon International Airport and Gimpo International Airport. Seasonally, the risk was highest in August that coincides with the Summer vacation period. The result will be useful for the baseline data for various aviation safety enhancement activities such as revision of routes and procedures and training of the field specialists.

• Journal of Soil and Groundwater Environment
• /
• v.28 no.6
• /
• pp.33-44
• /
• 2023

A risk assessment on the heavy metals including arsenic (As), cupper (Cu), lead (Pb), and zinc (Zn) was investigated by setting exposure routes in agricultural fields. Moreover, the factors requiring improvement in risk assessment were also discussed through a review of the dermal absorption slope factor (SF_abs) and total amount of suspended particles (TSP) in the current risk assessment guidelines. Assessment results show that the total cancer risk (TCR) of As through crop and soil ingestion was 1.51E-03 in adults and 6.37E-4 in children, which indicated a carcinogenic risk (exceeding 1E-05). On the other side, the harzard index (HI) was 3.37 in adults and 1.41 in children, which was evaluated as having a non-carcinogenic risk (>1). The carcinogenic purification targets for As were calculated to be 6.84 mg/kg in adults and 6.86 mg/kg in children, while the non-carcinogenic purification targets were calculated to be 13.43 mg/kg for adults and 22.54 mg/kg for children. When applying SF_abs 61 of the current guidelines, it appears that there is a carcinogenic risk even though the As exposure concentration is below the area of concern 1 standard (25 mg/kg), which suggestes that additional research on this factor is required for the risk assessment. In order to apply the measured suspended particle concentration to risk assessment, TSP should be derived from PM10 using an appropriate correlation equation. As a result, it is suggested to improve the risk assessment guidelines so that the mesured PM10 value measured in the field can be used directly.

• Journal of Aerospace System Engineering
• /
• v.17 no.6
• /
• pp.46-53
• /
• 2023

As urban traffic congestion and environmental pollution are becoming significant issues in major cities, Urban Air Mobility (UAM) is gaining attention as an efficient solution. In this study, we conducted a geographic information system (GIS)-based spatial analysis and clustering algorithm considering the actual data of the terrain and infrastructure in the Busan area, through which we were able to select the location of vertiports and corridors (flight routes) for the UAM operation. Based on the Gimhae International Airport, which is expected to be the center of the UAM infrastructure system in the Busan region, we judged that three vertiport locations in the target area were suitable. Subsequently, we used the A^* (A-star) algorithm considering Ground Risk to select a flight path that minimized both risk and distance. Through this, we confirmed a risk reduction effect of 80.168% compared to the minimum distance route.

• Korea Trade Review
• /
• v.45 no.3
• /
• pp.35-54
• /
• 2020

China's 'One Belt One Road' initiative has had a profound impact on China's relationship with Central Asia, which shares borders at North-western region. Central Asia plays an important role in securing the export market of Chinese products, supply of raw materials, and transportation route to Europe. The inland port is of significance to facilitate the development of logistics, trade and industry in the surrounding areas by enabling the distribution and import and export clearance in the region by performing the role of the seaport on the hinterland. The purpose of this study is to analyze the effect of the development of inland ports in central and western China on the geopolitical relationship between China and Central Asia. To this end, we analyze the status of inland port development in China's Midwest by employing the SWOT-PEST analysis method to analyze the current status as well as prospects of trade, investment and transportation routes with Central Asia in terms of geopolitics. As a result of the analysis, the relations between China and Central Asian Countries are becoming more politically and economically close, but it has brought about serious challenges by domestic and foreign environmental changes. Therefore, the development of the inland ports in central and western China are determined by the geopolitical relations under 'One Belt One Road' initiative between China and Central Asia, while the development of the inland port is also expected to serve as a catalyst for the development of both regions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.11a
• /
• pp.23-26
• /
• 2023

In the past, in observing the sea fog on the major sea route and providing real-time information for the safe operation of ships, a visibility sensor or a fog detector with similar operating principles was installed to observe local fog near the place where it was installed. However, it was somewhat unreasonable to immediately provide sea fog observation information to ships and users because the reliability of real-time observation information was somewhat low due to pollution caused by dust, salt, and pollen, or malfunctions of detection sensors by organisms such as spider webs. From 2019 to 2022, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries collaborated to build a more reliable real-time image-based sea fog observation system in 100 regions of the Lighthouse on major sea routes across the country to collect reliable sea fog observation information every 10 minutes and perform real-time public service(webpage).

• Journal of Navigation and Port Research
• /
• v.47 no.6
• /
• pp.386-393
• /
• 2023

Recently, the demand for autonomous navigation technology has increased, and related research is also increasing. Autonomous ships generally follow the planned route, calculate the avoidance route according to the risk situation while sailing, and follow a calculated route. In general, an automatic steering device is used to follow the route, and among the operational automatic steering device methods, the route control mode is the most appropriate method to apply to autonomous ships. Therefore, in this study, we developed a route-tracking algorithm to apply an avoidance route using the navigation control mode of an automatic steering device. The algorithm was developed by dividing the straight and turning sections. A performance test was conducted to satisfy the performance suggested by IEC 62065, the relevant international standard, using simulator equipment that had acquired international certification to verify its performance. The results of the performance verification confirmed that the cross-track error, which represents the straight distance between the ship and the route, satisfied the performance standards suggested by IEC 62065 when the ship followed the route.

• Geomechanics and Engineering
• /
• v.37 no.3
• /
• pp.223-241
• /
• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.1-16
• /
• 2023

Accurate traffic information prediction is considered to be one of the most important aspects of intelligent transport systems(ITS), as it can be used to guide users of transportation facilities to avoid congested routes. Various deep learning models have been developed for accurate traffic prediction. Recently, ensemble techniques have been utilized to combine the strengths and weaknesses of various models in various ways to improve prediction accuracy and stability. Therefore, in this study, we developed and evaluated a traffic information prediction model using various deep learning models, and evaluated the performance of the developed deep learning models as a stacking ensemble. The individual models showed error rates within 10% for traffic volume prediction and 3% for speed prediction. The ensemble model showed higher accuracy compared to other models when no cross-validation was performed, and when cross-validation was performed, it showed a uniform error rate in long-term forecasting.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.49-65
• /
• 2023

In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.