Eric M. Perloff;Tom J. Crijns;Casey M. O'Connor;David Ring;Patrick G. Marinello;Science of Variation Group
Clinics in Shoulder and Elbow
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v.26
no.2
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pp.156-161
/
2023
Background: We analyzed association between viewing two-dimensional computed tomography (2D CT) images in addition to radiographs with radial head treatment recommendations after accounting for patient and surgeon factors in a survey-based experiment. Methods: One hundred and fifty-four surgeons reviewed 15 patient scenarios with terrible triad fracture dislocations of the elbow. Surgeons were randomized to view either radiographs only or radiographs and 2D CT images. The scenarios randomized patient age, hand dominance, and occupation. For each scenario, surgeons were asked if they would recommend fixation or arthroplasty of the radial head. Multi-level logistic regression analysis identified variables associated with radial head treatment recommendations. Results: Reviewing 2D CT images in addition to radiographs had no statistical association with treatment recommendations. A higher likelihood of recommending prosthetic arthroplasty was associated with older patient age, patient occupation not requiring manual labor, surgeon practice location in the United States, practicing for five years or less, and the subspecialties "trauma" and "shoulder and elbow." Conclusions: The results of this study suggest that in terrible triad injuries, the imaging appearance of radial head fractures has no measurable influence on treatment recommendations. Personal surgeon factors and patient demographic characteristics may have a larger role in surgical decision making. Level of evidence: Level III, therapeutic case-control study.
Kim, Jihye;Kwak, Jihye;Jun, Sang Min;Lee, Sunghack;Kang, Moon Seong
Journal of The Korean Society of Agricultural Engineers
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v.65
no.6
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pp.23-35
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2023
In this study, we developed a method to determine the flood-limited water levels of agricultural reservoirs, considering both their irrigation and flood control functions. Irrigation safety and flood safety indices were defined to be applied to various reservoirs, allowing for a comprehensive assessment of the irrigation and flood control properties. Seasonal flood-limited water level scenarios were established to represent the temporal characteristics of rainfall and agricultural water supply and the safety indices were analyzed according to these scenarios. The optimal scenarios were derived using a schematic solution based on Pareto front analysis. The method was applied to Obong, Yedang, and Myogok reservoirs, and the results showed that the characteristics of each reservoir were well represented in the safety indices. The irrigation safety of Obong reservoir was found to be significantly influenced by the late-stage flood-limited water level, while those of Yedang and Myogok reservoir were primarily affected by the early and mid-stage flood-limited water levels. The values of irrigation safety and flood safety indices for each scenario were plotted as points on the coordinate plane, and the optimal flood-limited water levels were selected from the Pareto front. The storage ratio of the optimal flood-limited water levels for the early, mid, and late stages were 65-70%, 70%, and 75% for Obong reservoir, 75%, 70-75%, and 65-70% for Yedang reservoir, and 75-80%, 70%, and 50% for Myogok reservoir. We expect that the method developed in this study will facilitate efficient reservoir operations.
Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.
Kim, Sang-Wan;Kim, Donghan;Lee, Yoon-Kyung;Lee, Impyeong;Lee, Sangho;Kim, Junghoon;Kim, Keunyong;Ryu, Joo-Hyung
Korean Journal of Remote Sensing
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v.36
no.2_2
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pp.379-399
/
2020
The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.
The East Asian (China, Korea and Japan) summer monsoon precipitation and its variability are examined from the outputs of the 22 coupled climate models performing coordinated experiments leading to the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) following the multi-model ensemble (MME) technique. Results are based on averages of all the available models. The shape of the annual cycle with maximum during the summer monsoon period is simulated by the coupled climate models. However, models fail to simulate the minimum peak in July which is associated with northward shifts of the Meiyu-Changma-Baiu precipitation band. The MME precipitation pattern is able to capture the spatial distribution of rainfall associated with the location of the north Pacific subtropical high and the Meiyu-Changma-Baiu frontal zone. However precipitation over the east coast of China, Korea-Japan peninsular and the adjoining oceanic regions is underestimated. Future projections to the radiative forcing of doubled $CO_2$ scenario are examined. The MME reveals an increase in precipitation varying from 5 to 10 %, with an average of 7.8 % over the East Asian region at the time of $CO_2$ doubling. However the increases are statistically significant only over the Korea-Japan peninsula and the adjoining north China region. The increase in precipitation may be attributed to the projected intensification of the subtropical high, and thus the associated influx of moist air from the Pacific to inland. The projected changes in the amount of precipitation are directly proportional to the changes in the strength of the subtropical high. Further a possible increase in the length of the summer monsoon precipitation period from late spring through early autumn is suggested.
In the Republic of Korea, the LTE-based public safety (PS-LTE) network is being built for the 700 MHz frequency band. However, the same bands are also assigned to the LTE-based high-speed railway (LTE-R) network. Therefore, it is essential to utilize the co-channel interference management schemes for the coexistence of two LTE networks in order to increase the system throughput and to reduce the user outage probability. In this paper, we focus on the downlink (DL) system for the coexistence of PS-LTE and LTE-R networks by considering non radio access network (RAN) sharing and LTE-R RAN sharing by PS-LTE users (UEs) to analyze the UE throughput. Moreover, we also utilize the cooperative communications schemes, such as coordinated multipoint (CoMP) for the coexistence of PS-LTE and LTE-R networks in order to reduce the UE outage probability. We categorize the coexistence of PS-LTE and LTE-R networks into four different scenarios, and evaluate the performance of each scenario by the important performance indexes, such as UE average throughput and UE outage probability.
Kim, Jeongmin;Choi, Seunghyun;Do, Myungsik;Han, Daeseok
International Journal of Highway Engineering
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v.18
no.3
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pp.47-57
/
2016
PURPOSES : This study aims to examine the differences between the existing traffic demand forecasting method and the traffic demand forecasting method considering future regional development plans and new road construction and expansion plans using a four-step traffic demand forecast for a more objective and sophisticated national highway maintenance. This study ultimately aims to present future pavement deterioration and budget forecasting planning based on the examination. METHODS : This study used the latest data offered by the Korea Transport Data Base (KTDB) as the basic data for demand forecast. The analysis scope was set using the Daejeon Metropolitan City's O/D and network data. This study used a traffic demand program called TransCad, and performed a traffic assignment by vehicle type through the application of a user equilibrium-based multi-class assignment technique. This study forecasted future traffic demand by verifying whether or not a realistic traffic pattern was expressed similarly by undertaking a calibration process. This study performed a life cycle cost analysis based on traffic using the forecasted future demand or existing past pattern, or by assuming the constant traffic demand. The maintenance criteria were decided according to equivalent single axle loads (ESAL). The maintenance period in the concerned section was calculated in this study. This study also computed the maintenance costs using a construction method by applying the maintenance criteria considering the ESAL. The road user costs were calculated by using the user cost calculation logic applied to the Korean Pavement Management System, which is the existing study outcome. RESULTS : This study ascertained that the increase and decrease of traffic occurred in the concerned section according to the future development plans. Furthermore, there were differences from demand forecasting that did not consider the development plans. Realistic and accurate demand forecasting supported an optimized decision making that efficiently assigns maintenance costs, and can be used as very important basic information for maintenance decision making. CONCLUSIONS : Therefore, decision making for a more efficient and sophisticated road management than the method assuming future traffic can be expected to be the same as the existing pattern or steady traffic demand. The reflection of a reliable forecasting of the future traffic demand to life cycle cost analysis (LCCA) can be a very vital factor because many studies are generally performed without considering the future traffic demand or with an analysis through setting a scenario upon LCCA within a pavement management system.
Recent droughts make hydroelectric power generation (HPG) decreasing. Due to climate change in the future, the frequency and intensity of drought are expected to increase, which will increase uncertainty of HPG in multi-purpose dams. Therefore, it is necessary to estimate the amount of HPG according to climate change scenarios and analyze the effect of drought on the amount of HPG. This study analyzed the future HPG of the Soyanggang Dam and Chungju Dam according to the SSP2-4.5 and SSP5-8.5 scenarios. Regression equations for HPG were developed based on the observed data of power generation discharge and HPG in the past provided by My Water, and future HPGs were estimated according to the SSP scenarios. The effect of drought on the amount of HPG was investigated based on the drought severity calculated using the standardized precipitation index (SPI). In this study, the future SPIs were calculated using precipitation data based on four GCM models (CanESM5, ACCESS-ESM1-5, INM-CM4-8, IPSL-CM6A) provided through the environmental big data platform. Overall results show that climate change had significant effects on the amount of HPG. In the case of Soyanggang Dam, the amount of HPG decreased in the SSP2-4.5 and SSP5-8.5 scenarios. Under the SSP2-4.5 scenario the CanESM model showed a 65% reduction in 2031, and under the SSP5-8.5 scenario the ACCESS-ESM1-5 model showed a 54% reduction in 2029. In the case of Chungju Dam, under the SSP2-4.5 and SSP5-8.5 scenarios the average monthly HPG compared to the reference period showed a decreasing trend except for INM-CM4 model.
The purpose of the water distribution system is gradually changing to increase the flexibility for responding to various abnormal situations. In addition, it is essential to improve resilience through preparing emergency plans against water supply failure. The most efficient way is emergency interconnections which supply water from interconnected adjacent blocks. To operate successful interconnections, it is essential to evaluate the supply performance in spatial and temporal aspects. The spatial and temporal aspects are dominated by its interconnected pipes and interconnected reservoirs respectively. In this study, an emergency interconnection scenario where problem occurred in reservoir 1 at 0:00hr in A city, Korea. An Advanced-Pressure Driven Analysis model was used to simulate the volume and inflow volume of the interconnected reservoirs. Based on the hydraulic analysis results, a multi-dimensional evaluation of the supply performance was conducted by applying possible water supply range indicator (PWSRI) and possible water supply temporal indicator (PWSTI) which are based on fuzzy membership functions. As a result, it was possible to evaluate the supply performance on the sides of consumers in spatio-temporal aspects and to review whether established plans mitigate the damage as intended. It is expected to be used for decision making on structural and non-structural emergency plan to improve the performance of an emergency interconnection.
As the using rate of an explosive gas has been increased in the industrial site, the regional residents adjacent to the site as well as the site workers have frequently fallen into a dangerous situation. Damage caused by accident in the process using hydrogen gas is not confined only to the relevant process, but also is linked to a large scale of fire or explosion and it bring about heavy casualties. Therefore, personnel in charge should investigate the kinds and causes of the accident, forecast the scale of damage and also, shall establish and manage safety countermeasures. We, in Anti-Calamity Research Center, forecasted the scope of danger if break out a fire or/and explosion in hydrogen gas facilities of MLCC firing process. We selected piping leak accident, which is the most frequent accident case based on an actual analysis of accident data occurred. We select and apply piping leak accident which is the most frequent case based on an actual accident data as a model of damage forecasting scenario caused by accident. A jet fire breaks out if hydrogen gas leaks through pipe size of 10 mm ${\Phi}$ under pressure of 120 bar, and in case of $4kw/m^2$ of radiation level, the radiation heat can produce an effect on up to distance of maximum 12.45 meter. Herein, we are going to recommend safety security and countermeasures for improvement through forecasting of accident damages.
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