• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.116-122
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• 2020

Human and material resource planning is one representative example of Operations Research. Resource planning is important not only in civilian settings but also in military ones. In the Air Force, flight scheduling is one of the primary issues that must be addressed by the personnel who are connected to flight missions. However, although the topic is of great importance, relatively few studies have attempted to resolve the problem on a scientific basis. Each flight squadron has its own scheduling officers who manually draw up the flight schedules each day. While mistakes may not occur while drafting schedules, officers may experience difficulties in systematically adjusting to them. To increase efficiency in this context, this study proposes a mathematical model based on a binary variable. This model automatically drafts flight schedules considering pilot's mission efficiency. Furthermore, it also recommends that schedules be drawn up monthly and updated weekly, rather than being drafted from scratch each day. This will enable easier control when taking the various relevant factors into account. The model incorporates several parameters, such as matching of the main pilots and co-pilots, turn around time, availability of pilots and aircraft, monthly requirements of each flight mission, and maximum/minimum number of sorties that would be flown per week. The optimal solution to this model demonstrated an average improvement of nearly 47% compared with other feasible solutions.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.1-9
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• 2020

Large-scale industrial facility structures continue to deteriorate due to the effects of operating and environmental conditions. The problems of these industrial facilities are potentially causing economic losses, environmental pollution, casualties, and national losses. Accordingly, in order to prevent disaster accidents of large structures in advance, the necessity of diagnosing structures using non-destructive inspection techniques is being highlighted. The defect occurrence, location and defect type of the structure are important parameters for predicting the remaining life of the structure, so continuous defect observation is very important. Recently, many researchers have been actively researching real-time monitoring technology to solve these problems. Structure Health Monitoring Inspection is a technology that can identify and respond to the occurrence of defects in real time, but there is a limit to check the degree of defects and the direction of growth of defects. In order to compensate for the shortcomings of these technologies, the importance of defect imaging techniques is emerging, and in order to find defects in large structures, a method of inspecting a wide range using guided ultrasonic is effective. The work presented here introduces a calculation for the shape factor for evaluation of the damaged area, as well as a variable β parameter technique to correct a damaged shape. Also, we perform research in modeling simulation and an experiment for comparison with a suggested inspection method and verify its validity. The curved structure image obtained by the advanced RAPID algorithm showed a good match between the defect area and the shape.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.179-196
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• 2021

Experimental investigations on the seismic behaviors of the PVC-FRP Confined Reinforced Concrete (PFCRC) columns under low cyclic loading are carried out and two variable parameters including CFRP strips spacing and axial compression ratio are considered. The PFCRC column finally fails by bending and is characterized by the crushing of concrete and yielding of the longitudinal reinforcement, and the column with a high axial compression ratio is also accompanied by the cracking of the PVC tube and the fracture of CFRP strips. The hysteretic curves and skeleton curves of the columns are obtained from the experimental data. With the increase of axial compression ratio, the stiffness degradation rate accelerates and the ductility decreases. With the decrease of CFRP strips spacing, the unloading sections of the skeleton curves become steep and the ductility reduces significantly. On the basis of fiber model method, a numerical analysis approach for predicting the skeleton curves of the PFCRC columns is developed. Additionally, a simplified skeleton curve including the elastic stage, strengthening stage and unloading stage is suggested depending on the geometric drawing method. Moreover, the loading and unloading rules of the PFCRC columns are revealed by analyzing the features of the skeleton curves. The quantitative expressions that are used to predict the unloading stiffness of the specimens in each stage are proposed. Eventually, an analytical model for the PFCRC columns under low cyclic loading is established and it agrees well with test data.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.92-97
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• 2021

The importance of processes in cryogenic environments is increasing in a way to address problems such as critical dimension (CD) narrow and bottlenecks in micro-processing. Accordingly, in this paper, we proceed with the design and analysis of Electrostatic Chuck(ESC) and Coolant in cryogenic environments, and present optimal model conditions to provide the temperature distribution analysis of ESC in these environments and the appropriate optimal design. The wafer temperature uniformity was selected as the reference model that the operating conditions of the refrigerant of the liquid nitrogen in the doubled aluminum path were excellent. Design of simulation (DOS) was carried out based on the wheel settings within the selected reference model and the classification of three mass flow and diameter case, respectively. The comparison between factors with p-value less than 0.05 indicates that the optimal design point is when five turns of coolant have a flow rate of 0.3 kg/s and a diameter of 12 mm. ANOVA determines the interactions between the above factor, indicating that mass flow is the most significant among the parameters of interests. In variable selection procedure, Case 2 was also determined to be superior through the two-Sample T-Test of the mean and variance values by dividing five coolant wheels into two (Case 1 : 2+3, Case 2: 3+2). Finally, heat transfer analysis processes such as final difference method (FDM) and heat transfer were also performed to demonstrate the feasibility and adequacy of the analysis process.

• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.268-273
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• 2020

We analyze the characteristics of the coherent beam combination of lasers by monitoring the speckle pattern of the beam reflected from a scattering medium. Three collimated laser sources with high coherence are focused on a scattering target using a lens, and we then examine the speckle pattern of the returned beam in the Fourier domain. We observe that the size of the speckle pattern changes, depending on the focused-beam size or degree of spatial overlap of the three beams. Furthermore, through Fourier-domain analysis of the speckle pattern we obtain the monitoring variable to qualify the efficiency of the coherent beam combination.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.4
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• pp.125-131
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• 2020

Purpose : Lower extremity orthoses have been used as conservative methods to recover gait of the stroke patients. The purpose of this study is to examine how newly designed pelvic belt orthosis can improve gait ability and dynamic balance of adults with Hemiparesis after stroke. Methods : 22 patients who had hemiparesis after stroke participated in this study. Two groups were randomly created by assigning 10 subjects to the experimental group and the rest of the 12 subjects to the control group. The control group was treated by conventional physical therapy and occupational therapy. Identical therapy protocols were used to treat the experimental group who were assigned to wear the pelvic belt orthosis during post measurement. This study has a group of independent variables including group, gender, age, height, MAS, lesion side, cause and a group of dependent variables including gait speed, cadence, step length, stride length, and dynamic balance. The GAITRite system was used to measure spatial-temporal gain parameters and the balance system SD to measure dynamic balance. The data was analyzed using R version 3.3.1. Random forest, boosting algorithm, and MANOVA test were conducted to determine the effects of independent variables on dependent variables. Results : This study has a group of independent variables including group, gender, age, height, MAS, lesion side, cause and a group of dependent variables including gait speed, cadence, step length, stride length, and dynamic balance. The independent variable "group" has the most important value, which is approximately 25.42 (%IncMSE) representing a value three times greater than the second important predictor "height." Conclusion : As a result of this research, the hypothesis is validated with conclusion that Pelvic Belt orthosis could be effectively used for improving gait ability and balance of the patients with post-stroke hemiparesis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.121-129
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• 2022

With the recent increase in international trade volume the trade volume through ships is also continuously increasing. The treatment of ballast water goes through the following five steps, samples are taken and analyzed at each step, and samples are obtained using a suction pump. These suction pumps have low efficiency and thus need to be improved. In this study, it is to optimize the form of the impeller which affects directly improvements of performance to determine the capacity of suction pump and to fulfill the purpose of this research. To do it, we have carried out parametric design as an input variable, geometric form for the impeller. By conducting the flow analysis for the optimum form, it has confirmed the value of improved results and achieved the purpose to study in this paper. It has selected the necessary parameter for optimizing the form of the pump impeller and analyzed the property using experiment design. And it can reduce the factor of parameter for local optimization from findings to analyze the property of form parameter. To perform MOGA(Multi-Objective Genetic Algorithm) it has generated response surface using parameters for local optimization and conducts the optimization using multi-objective genetic algorithm. with created experiment cases, it has performed the computational fluid dynamics with model applying the optimized impeller form and checked that the capacity of the pump was improved. It could verify the validity concerning the improvement of pump efficiency, via optimization of pump impeller form which is suggested in this study.

• Steel and Composite Structures
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• v.42 no.4
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• pp.501-511
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• 2022

Earthquake Resistant Design Philosophy seeks (a) no damage, (b) no significant structural damage, and (c) significant structural damage but no collapse of normal buildings, under minor, moderate and severe levels of earthquake shaking, respectively. A procedure is proposed for seismic design of low-rise reinforced concrete special moment frame buildings, which is consistent with this philosophy; buildings are designed to be ductile through appropriate sizing and reinforcement detailing, such that they resist severe level of earthquake shaking without collapse. Nonlinear analyses of study buildings are used to determine quantitatively (a) ranges of design parameters required to assure the required deformability in normal buildings to resist the severe level of earthquake shaking, (b) four specific limit states that represent the start of different structural damage states, and (c) levels of minor and moderate earthquake shakings stated in the philosophy along with an extreme level of earthquake shaking associated with the structural damage state of no collapse. The four limits of structural damage states and the three levels of earthquake shaking identified are shown to be consistent with the performance-based design guidelines available in literature. Finally, nonlinear analyses results are used to confirm the efficacy of the proposed procedure.

• Animal Bioscience
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• v.34 no.10
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• pp.1623-1631
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• 2021

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW^0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R² = 0.39) than the NRC equation (R² = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.