Republic of Korea Army

About: Republic of Korea Army is a government organization based out in Daejeon, South Korea. It is known for research contribution in the topics: Crisis communication & Mental health. The organization has 67 authors who have published 74 publications receiving 513 citations. The organization is also known as: ROKA & ROK Army.

Seroprevalence of malaria infections in Korean troops on a peacekeeping mission in East Timor from 2001 to 2002.

Abstract: Eun-Ah Chang, MD, PhD, and Chae Seung Lim, MD, PhD: Department of Laboratory Medicine, Korea University, Ansan Hospital, Ansan City; Inil Park, MD: Captain, Army doctor, 1987 Troops, Republic of Korea Army; Jin Yong Kim, MD, PhD: Division of Gastroenterology, Internal Medicine Department, Korea University, Guro Hospital, Seoul; In Bum Suh, MD, PhD: Department of Laboratory Medicine, Kangwon National University Hospital, Chuncheon; Seong Soo A. An, PhD: Department of Research and Development, PeopleBio Inc., Yonsei Engineering Center, Seoul; Young Kee Kim, MD, PhD: Department of Laboratory Medicine, Korea University, Anam Hospital, Seoul; Kap No Lee, MD, PhD: Department of Laboratory Medicine, Korea University, Guro Hospital, Seoul, Republic of Korea.

Association between insulin resistance and lung function trajectory over 4 years in South Korea: community-based prospective cohort

Abstract: Hyperglycemic conditions are associated with respiratory dysfunction Although several studies have reported that insulin resistance (IR) is related to decreased lung function, the association between IR and change in lung function has been rarely studied This study aimed to investigate the potential association of IR on annual change in lung function using a community-based prospective cohort in Korea We selected 4827 Korean participants whose serial lung functions were assessed over 4 years using 1:3 propensity score matching Exposure was baseline IR estimated with homeostatic model assessment (HOMA-IR), and outcomes were annual changes in lung function determined by calculating the regression coefficient using least-square linear regression analysis In the multivariate linear regression, per one unit increased log transformed HOMA-IR was associated with decline in FEV1%-predicted (β: − 023, 95% CI: − 036 to − 011) and FVC %-predicted (β: − 020, 95% CI: − 033 to − 008), respectively In the generalized additive model plot, HOMA-IR showed a negative linear association with annual changes in FEV1%-predicted and FVC %-predicted The suggested threshold of HOMA-IR for decline in lung function was 10 unit for annual change in FEV1%-predicted and 22 unit for annual change in FVC %-predicted Age showed statistically significant effect modification on the relationship between HOMA-IR and annual change in FEV1%-predicted Increased HOMA-IR was associated with the decreased annual change in FEV1%-predicted, particularly in older people In South Korea, increased HOMA-IR was associated with decline in lung function Since IR was related to decline in FEV1%-predicted, particularly in older people, tailored approaches are needed in these populations The potential pulmonary hazard of IR needs to be confirmed in future studies

An Optimization Approach to Minimize the Expected Loss of Demand Considering Drone Failures in Drone Delivery Scheduling

Abstract: This study proposes a drone-based delivery schedul- ing method considering drone failures to minimize the expected loss of demand (ELOD). An optimization model (DDS-F) is developed to determine the assignment of each drone to a subset of customers and the corresponding delivery sequence. Because solving the optimization model is computationally challenging, a Simulated Annealing (SA) heuristic algorithm is developed to reduce the computational time. The proposed SA features a fast initial solution generation based on the Petal algorithm, a binary integer programming model for path selection, and a local neigh- borhood search algorithm to find better solutions. Numerical results showed that the proposed approach outperformed the well-known Makespan problem in reducing the ELOD by 23.6% on a test case. Several case studies are conducted to illustrate the impact of the failure distribution function on the optimal flight schedules. Furthermore, the proposed approach was able to obtain the exact solutions for the test cases studied in this paper. Numerical results also showed the efficiency of the proposed algorithm in reducing the computational time by 44.35%, on average, compared with the exact algorithm.

Joint use of DEA and constrained canonical correlation analysis for efficiency valuations involving categorical variables

Abstract: The research on efficiency valuations has used two distinct approaches. One is the nonparametric approach known as data envelopment analysis (DEA), the other is the parametric approach based on regression analysis or its extension such as constrained canonical correlation analysis (CCCA). Interestingly, a recent study has employed a hybrid approach that cross-fertilizes DEA and CCCA to compensate for the drawbacks of the two methods and capture their positive aspects. This approach first applies DEA to select efficient units and then utilizes CCCA to identify a smooth efficient frontier with the selected efficient units only. We extend it to incorporate a categorical variable that reflects an environmental effect on efficiency performance. The need for considering a categorical variable arises in practice for an equitable efficiency valuation, as illustrated by managerial performance evaluation of the branches of a fast-food company, where the location of branches such as commercial or noncommercial area significantly affects their performance. We demonstrate various possible ways to handle such a categorical variable in the framework of a hybrid approach and characterize each of the methods. Based on this study, we suggest one method that simultaneously utilizes an extension of DEA, referred to as DEA with categorical variable, and CCCA employing a dummy variable, as in multiple regressions with dummy variables. Through an application to the branches of a fast-food company, we show the efficacy of the suggested method in terms of penalizing the advantageous location effect and compensating for the disadvantageous location effect. We also provide some discussions on the limitations underlying the hybrid approach in order to guide a proper use of this approach to the other potential applications.

A Real-Time Rerouting Method for Drone Flights Under Uncertain Flight Time

Abstract: This paper proposes a method for real-time rerouting drone flights under uncertain flight times. The battery runtime that remains of a drone in real-time may be insufficient to complete its flight mission. This may be due to external factors, such as unexpected severe weather or obstacles that move into the drone’s flight path. Under unexpected situations, such as these, the drone cannot safely return to its depot, as planned. To ensure that the drone makes a safe return and that the flight mission is a success, there must be a real-time rerouting process for a drone’s flight path in response to unforeseeable circumstances. Hence, this paper proposes a real-time rerouting process consisting of two optimization models that generate an optimal alternative flight path for a drone that has insufficient remaining battery runtime. The first model is used to find an optimal flight path to visit all remaining target waypoints. If the first model fails to obtain a feasible solution, the second model is implemented to find an optimal flight path to minimize the number of unvisited waypoints. To confine the total flight (travel) time to the insufficient battery runtime, both models include the constraint associated with uncertain flight (travel) times between waypoints. To capture this uncertainty, this paper proposes a chance constrained programming (CCP) approach under the assumption of a known mean, variance, and flight time intervals. Numerical examples show how the proposed rerouting process works, and the CCP method results in more conservative solutions as compared to the deterministic approach.