• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.1-14
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• 2015

The purpose of this paper is to reveal two problems in the existing inventory systems in retail market, and to suggest a Two-Bin System under Automatic Ordering System considering only base-stock. Large retailers already have a sophisticated inventory system based on an automatic ordering principle. However, why does the out-of-stock (OOS) happen in large discount stores in spite of having a good inventory system? This paper suggests two systems after finding the root causes concerning the previous question. For evaluating the performance of each system, the random 200 data set in each sample group was generated from MINITAB 16 and obeyed the Poisson distribution. The existing inventory system in retail market cannot help generating OOS due to indwelling contradiction in itself. The reasons are the ordering deadline and the relationship between ordering quantity and base stock. This paper also demonstrates that these previous studies on inventory fall into the closed loop. Also the paper shows that the performance of the replenishment policy was better than traditional methods dealing with ordering quantity and base stock.

• Journal of Applied Reliability
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• v.10 no.2
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• pp.93-105
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• 2010

The following thesis provides an explanation for the definition of the MIL-HDBK-2155 : Failure Reporting, Analysis and Corrective Action System (FRACAS), which systemizes the collection and analysis of failure data and the feedback process of the results. It also presents a plan based on MIL-HDBK-2155 for the collection and analysis of operating specifications on weapon systems. The collection and analysis of failure data and the feedback process utilizing FRACAS contributes to identifying improvement requirements during equipment operation as well as finding and eliminating the root cause of the failures. The objective of applying FRACAS to weapon systems is to receive source data feedback for reliability enhancements and performance improvements during operation. This is done by recognizing weaknesses in the design or operation by identifying the type of failures that might occur, and by performing Failure Modes, Effects and Criticality Analysis(FMECA) and Failure Tree Analysis(FTA).

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.637-642
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• 2007

The sum of each work duration are entire period in construction project. Each work occurs to be late, the total period of construction project will delays. Therefore, the total period of construction project will not be delayed if probability of working progress makes higher. Finding each work's constraints performs constraints analysis in process of construction for checking probability of working progress. Grasp work's constraints through the constraints analysis and removes. This research will show preventing delay of consruction project, through constraints analysis process.

• Journal of the Korean Home Economics Association
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• v.40 no.10
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• pp.33-48
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• 2002

The purpose of this study guides them to the needs of leave preparation and material methods for self- examination and social adaptation so that they may live their remaining time in residental care better, and that execute preliminary training to improve their qualities for healthy family lives in the future. The program of this study was tested on 8 adolescents at their high school ages selected from an orphanage in Seoul. The effect of the program was determined by the quantity evaluation with a statistical analysis(ANCOVA) and also by the quality evaluation that requires interviews. Here is the summary of the result of leave preparation program; Firstly, the leave preparation program was effective on finding self-identity, psychological welfare and personal relationship. Secondly, The program helped them recognize that their own personalities, growing-up circumstances and family in root influenced on their self-understanding and growth. Most of the subjects said they accepted these factors in an affirmative way. Thirdly, the program gave a positive effect on their views of social adaptation and family formation after leave.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.1-9
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• 2021

This study aimed to investigate the existence of the Feldstein-Horioka (1980) puzzle in international macroeconomics by applying the conditional Autoregressive Distributed Lag (ARDL) model to examine the long-run relationship between national savings and investments in Thailand and China. The input of this study relied on annual national savings and investments as a fraction of GDP during 1980-2019 which was collected from China National Bureau of Statistics (NBS) and Thailand National Economic and Social Development Council (NESDC). Hypothetically, Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests were applied to test the stationary properties and to investigate the integration level of selected time series. The empirical results, confirmed by cumulative sum (CUSUM) and cumulative sum square (CUSUMSQ), maintained no serial correlation and structural break problems. The finding of this study suggested that the Feldstein-Horioka puzzle in Thailand did not exist significantly. Thailand's national savings and investments nexus was independent, following the classic economic idea that financial liberalization, or perfect capital mobility, allowed national savings and investments to flow freely to countries with better interest rates. Whereas, a strong significant correlation was found in the case of China during the fixed exchange rate regime switching in 1994 and post WTO participation after 2001-2019.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1664-1673
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• 2022

Achieving sustainable development requires an increasing share of green technologies. World energy demand is expected to rise significantly especially in developing economies. The increasing energy demands will be entertained with conventional energy sources at the cost of higher emissions unless eco-friendly technologies are used. This study examines the asymmetric effects of nuclear energy on carbon emissions for Pakistan from 1974 to 2019. Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) unit root tests suggest that variables are integrated of order one and bound test of Autoregressive Distributed Lag (ARDL) and nonlinear ARDL confirm a long-run relationship among selected variables. The ARDL, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS) results show that the coefficient of nuclear energy has a negative and significant impact on emissions in both short and long run. Further, the NARDL finding shows that there exists an asymmetric long-run association between nuclear energy and CO₂ emissions. The vector error correction method (VECM) results indicate that there exists a bidirectional causal relationship between nuclear energy and carbon emissions in both the short and long run. Additionally, the impact of nuclear energy on ecological footprint has been examined and our findings remain robust.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.57-68
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• 1995

A general procedure for the numerical solution of coupled, nonlinear, differential two-point boundary-value problems, solutions of which are crucial to the controller design, has been developed and demonstrated. A fixed-end-points, free-terminal-time, optimal-control problem, which is derived from Pontryagin's Maximum Principle, is solved by an extension of Davidenko's method, a differential form of Newton's method, for algebraic root finding. By a discretization process like finite differences, the differential equations are converted to a nonlinear algebraic system. Davidenko's method reconverts this into a pseudo-time-dependent set of implicitly coupled ODEs suitable for solution by modern, high-performance solvers. Another important advantage of Davidenko's method related to the time-optimal problem is that the terminal time can be computed by treating this unkown as an additional variable and sup- plying the Hamiltonian at the terminal time as an additional equation. Davidenko's method uas used to produce optimal trajectories of a single-degree-of-freedom problem. This numerical method provides switching times for open-loop control, minimized terminal time and optimal input torque sequences. This numerical technique could easily be adapted to the multi-point boundary-value problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.136-136
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• 2022

This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

• Steel and Composite Structures
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• v.44 no.6
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• pp.867-882
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• 2022

Predicting the compressive strength of concrete (CSoC) is of high significance in civil engineering. The CSoC is a highly dependent and non-linear parameter that requires powerful models for its simulation. In this work, two novel optimization techniques, namely evaporation rate-based water cycle algorithm (ER-WCA) and equilibrium optimizer (EO) are employed for optimally finding the parameters of a multi-layer perceptron (MLP) neural processor. The efficiency of these techniques is examined by comparing the results of the ensembles to a conventionally trained MLP. It was observed that the ER-WCA and EO optimizers can enhance the training accuracy of the MLP by 11.18 and 3.12% (in terms of reducing the root mean square error), respectively. Also, the correlation of the testing results climbed from 78.80% to 82.59 and 80.71%. From there, it can be deduced that both ER-WCA-MLP and EO-MLP can be promising alternatives to the traditional approaches. Moreover, although the ER-WCA enjoys a larger accuracy, the EO was more efficient in terms of complexity, and consequently, time-effectiveness.

• Resources Recycling
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• v.31 no.4
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• pp.56-65
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• 2022

Copper is one of the non-ferrous metals used in the electrical/electronic manufacturing industries due to its superior properties particularly the high conductivity and less resistivity. The effluent generated from the surface finishing process of these industries contains higher copper content which gets discharged in to water bodies directly or indirectly. This causes severe environmental pollution and also results in loss of an important valuable metal. To overcome this issue, continuous R & D activities are going on across the globe in adsorption area with the purpose of finding an efficient, low cost and ecofriendly adsorbent. In view of the above, present investigation was made to compare the performance of a plant root (Datura root powder) as a bio-adsorbent to that of the synthetic one (Tulsion T-42) for copper adsorption from such effluent. Experiments were carried out in batch studies to optimize parameters such as adsorbent dose, contact time, pH, feed concentration, etc. Results of the batch experiments indicate that 0.2 g of Datura root powder and 0.1 g of Tulsion T-42 showed 95% copper adsorption from an initial feed/solution of 100 ppm Cu at pH 4 in contact time of 15 and 30 min, respectively. Adsorption data for both the adsorbents were fitted well to the Freundlich isotherm. Experimental results were also validated with the kinetic model, which showed that the adsorption of copper followed pseudo-second order rate expression for the both adsorbents. Overall result demonstrates that the bio-adsorbent tested has a potential applicability for metal recovery from the waste solutions/effluents of metal finishing units. In view of the requirements of commercial viability and minimal environmental damage there from, Datura root powder being an effective material for metal uptake, may prove to be a feasible adsorbent for copper recovery after the necessary scale-up studies.