• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.138-145
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• 2018

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5744-5764
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• 2018

In Wireless Sensor Networks (WSNs) for Internet of Things (IoT) environment, fault tolerance is a most fundamental issue due to strict energy constraint of sensor node. In this paper, a robust energy saving data dissemination protocol for IoT-WSNs is proposed. Minimized energy consumption and dissemination delay time based on signal strength play an important role in our scheme. The representative dissemination protocol SPIN (Sensor Protocols for Information via Negotiation) overcomes overlapped data problem of the classical Flooding scheme. However, SPIN never considers distance between nodes, thus the issue of dissemination energy consumption is becoming more important problem. In order to minimize the energy consumption, the shortest path between sensors should be considered to disseminate the data through the entire IoT-WSNs. SPMS (Shortest Path Mined SPIN) scheme creates routing tables using Bellman Ford method and forwards data through a multi-hop manner to optimize power consumption and delay time. Due to these properties, it is very hard to avoid heavy traffic when routing information is updated. Additionally, a node failure of SPMS would be caused by frequently using some sensors on the shortest path, thus network lifetime might be shortened quickly. In contrast, our scheme is resilient to these failures because it employs energy aware concept. The dissemination delay time of the proposed protocol without a routing table is similar to that of shortest path-based SPMS. In addition, our protocol does not require routing table, which needs a lot of control packets, thus it prevents excessive control message generation. Finally, the proposed scheme outperforms previous schemes in terms of data transmission success ratio, therefore our protocol could be appropriate for IoT-WSNs environment.

• Nutrition Research and Practice
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• v.15 no.1
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• pp.95-105
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• 2021

BACKGROUND/OBJECTIVES: The measurement of body composition, including muscle and fat mass, remains challenging in large epidemiological studies due to time constraint and cost when using accurate modalities. Therefore, this study aimed to develop and validate prediction equations according to sex to measure lean body mass (LBM), appendicular skeletal muscle mass (ASM), and body fat mass (BFM) using anthropometric measurement, serum creatinine level, and lifestyle factors as independent variables and dual-energy X-ray absorptiometry as the reference method. SUBJECTS/METHODS: A sample of the Korean general adult population (men: 7,599; women: 10,009) from the Korean National Health and Nutrition Examination Survey 2008-2011 was included in this study. The participants were divided into the derivation and validation groups via a random number generator (with a ratio of 70:30). The prediction equations were developed using a series of multivariable linear regressions and validated using the Bland-Altman plot and intraclass correlation coefficient (ICC). RESULTS: The initial and practical equations that included age, height, weight, and waist circumference had a different predictive ability for LBM (men: R2 = 0.85, standard error of estimate [SEE] = 2.7 kg; women: R2 = 0.78, SEE = 2.2 kg), ASM (men: R2 = 0.81, SEE = 1.6 kg; women: R2 = 0.71, SEE = 1.2 kg), and BFM (men: R2 = 0.74, SEE = 2.7 kg; women: R2 = 0.83, SEE = 2.2 kg) according to sex. Compared with the first prediction equation, the addition of other factors, including serum creatinine level, physical activity, smoking status, and alcohol use, resulted in an R2 that is higher by 0.01 and SEE that is lower by 0.1. CONCLUSIONS: All equations had low bias, moderate agreement based on the Bland-Altman plot, and high ICC, and this result showed that these equations can be further applied to other epidemiologic studies.

• Journal of the Korean Geotechnical Society
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• v.22 no.10
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• pp.173-181
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• 2006

A Two Mobilized-Plane Model is proposed for monotonic and cyclic soil response including liquefaction. This model is based on two mobilized planes: a plane of maximum shear stress, which rotates, and a horizontal plane which is spatially fixed. By controlling two mobilized planes, the model can simulate the principal stress rotation effect associated with simple shear from different $K_0$ states. The proposed model gives a similar skeleton behaviour for soils having the same mean stress, regardless of $K_0$ conditions as observed in laboratory tests. The soil skeleton behaviour observed in cyclic drained simple shear tests, including compaction during unloading and dilation at large strain is captured in the model. Undrained monotonic and cyclic response is predicted by imposing the volumetric constraint of the water on the drained or skeleton behaviour. This constitutive model is incorporated into the dynamic coupled stress-flow finite difference program of FLAC (Fast Lagrangian Analysis of Continua). The model was first calibrated with drained simple shear tests on Fraser River sand, and verified by comparing predicted and measured undrained behaviour of Fraser River sand using the same input parameters.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.4
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• pp.495-506
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• 2024

In this study, we propose the terrain following algorithm using model predictive control and nonlinear disturbance observer-based backstepping sliding mode controller for an aircraft system. Terrain following is important for military missions because it helps the aircraft avoid detection by the enemy radar. The model predictive control is used to replace the generating trajectory and guidance with the flight path angle constraint. In addition, the aircraft is affected to the parameter uncertainty and unknown disturbance such as wind near the mountainous terrain. Therefore, we suggest the nonlinear disturbance-based backstepping sliding mode control method for the aircraft that has highly nonlinearity to enhance flight path angle tracking performance. Through the numerical simulation, the proposed method showed the better tracking performance than the traditional backstepping method. Furthermore, the proposed method presented the terrain following maneuver maintaining the desired altitude.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.41-54
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• 2024

Efforts to reduce on-site safety incidents have expanded, leading to active research in this domain. However, a systematic analysis to improve the utility of technology is lacking. In this study, we conducted a survey on the various institutional and technical improvement measures to promote the application of smart construction safety technology over three years after the implementation of the "Smart Safety Equipment Support Project." The results showed that financial constraint was the primary obstacle in the adoption of this innovation. Fostering a flexible environment in the utilization of management fees and financial support of projects was determined to aid in the extensive application of the technology. Ensuring cost efficiency and user-friendliness were principally necessary for technical enhancements in the smart construction safety technology. Technologies, such as VR/AR safety education, real-time location tracking, wearable devices, and innovation on streamlining safety-related work efficiency, had been anticipated to contribute to on-site safety. Operating a smart safety control center was expected to be beneficial in the systematic securing of data and reduction of safety blind spots. Effective methods had been suggested to overcome the barriers that hindered the development and application of smart construction safety technology. This study facilitates in the technological improvements in this field.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.123-131
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• 2024

Electron paramagnetic resonance (EPR) dosimetry for a tooth from an individual exposed is well known as retrospective dosimetry in radiological accidents. A major constraint of the conventional X-band tooth-EPR dosimetry is the necessity to extract the tooth of the exposed patient for dose assessment. In this study, to conduct the dose assessments of exposed patients through part-extraction of tooth enamel, the minimum detectable dose (MDD) of the tooth enamel was evaluated based on the amount of mass. Further, a field test was conducted via intercomparison using various dose assessment methods to verify the feasibility of X-band tooth-EPR dosimetry using the minimum mass of tooth enamel. The intercomparison results demonstrated that effective dose determination via X-band tooth-EPR dosimetry is reliable. Consequently, it was determined that the minimum mass of tooth enamel required to evaluate an absorbed dose above 0.5 Gy is 15 mg. Thus, EPR dosimetry using 15 mg of tooth enamel can be applied in the triage and initial medical response stages for patients exposed during radiological accidents. This approach represents an advancement in managing radiological accidents by offering a more efficient and less invasive method of dose assessment.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Atmosphere
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• v.23 no.1
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• pp.93-102
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• 2013

Atmospheric transport pathway of an air mass is an important constraint controlling the chemical properties of the air mass observed at a designated location. Such information could be utilized for understanding observed temporal variabilities in atmospheric concentrations of long-lived chemical compounds, of which sinks and/or sources are related particularly with natural and/or anthropogenic processes in the surface, and as well as for performing inversions to constrain the fluxes of such compounds. The Lagrangian particle dispersion model FLEXPART provides a useful tool for estimating detailed particle dispersion during atmospheric transport, a significant improvement over traditional "single-line" trajectory models that have been widely used. However, those without a modeling background seeking to create simple back-trajectory maps may find it challenging to optimize FLEXPART for their needs. In this study, we explain how to set up, operate, and optimize FLEXPART for back-trajectory analysis, and also provide automatization programs based on the open-source R language. Discussions include setting up an "AVAILABLE" file (directory of input meteorological fields stored on the computer), creating C-shell scripts for initiating FLEXPART runs and storing the output in directories designated by date, as wells as processing the FLEXPART output to create figures for a back-trajectory "footprint" (potential emission sensitivity within the boundary layer). Step by step instructions are explained for an example case of calculating back trajectories derived for Anmyeon-do, Korea for January 2011. One application is also demonstrated in interpreting observed variabilities in atmospheric $CO_2$ concentration at Anmyeon-do during this period. Back-trajectory modeling information introduced in this study should facilitate the creation and automation of most common back-trajectory calculation needs in atmospheric research.

• Korean Journal of Food Science and Technology
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• v.21 no.5
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• pp.676-685
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• 1989

Optimal operating conditions of on-farm red pepper dryer were searched by using the simulation-optimization algorithm combining the drying and quality deterioration models of red pepper with Box's complex method. Determination of control variables such as air temperature, air recycle ratio and air flow rate was based on a criterion of minimizing energy consumption under the constrainst conditions that satisfied the specified color retention of carotenoids. As quality constraint was stricter, energy consumption increased and total drying time decreased with lower recycle ratio and higher air flow rate Product mixing during drying was found to be able to improve the energy efficiency and product quality. Currently used air flow rate was assessed to be increased for the optimal operation. Two stage drying at the fixed optimal air flow rate was proven to be useful means for further saying of energy consumption. In the optimal bistaged drying, the second stage began at about one third of the total drying time and low air temperature in the first stage Increased to a high value and air recycle ratio increased slightly in the second stage. Optimal control variable scheme could be explained by the dryer performance and the carotenoids destruction kinetics in red pepper drying.