• Journal of Digital Convergence
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• v.17 no.7
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• pp.59-71
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• 2019

The distribution logistics center has its own inventory, so designing an efficient storage area is very important. The purpose of this study is to present the optimal storage area calculation method for distribution logistics center considering the use of standard pallet unit load, and the results of this study are as follows. First, standard rack modules for storing T-11 and T-12 type pallet, which is generally used in Korea, were defined. Second, a variety of pallet transport equipments were investigated and analyzed to define the standard transport equipment's work passageway by type. Finally, it has great implications in terms of suggesting measures to minimize unused space that may occur during placement of pallet rack modules within storage space, as well as the easy and optimal calculation of the storage area for the distribution logistics center. Future research require a study on the layout of the entire distribution logistics center, which reflects the latest logistics technologies, such as standard rack modules for Mini-Load and GTP picking system.

• Journal of agriculture & life science
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• v.53 no.6
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• pp.23-33
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• 2019

In accordance with a change in the management information system containing the management record and planning for the entire national forest in South Korea by an amendment of the relevant law (The national forest management planning and methods, Korea Forest Service), in this study, average, the maximum, and the minimum values for DBH were presented while only average values were required before the amendment. In this regard, there is a need for an estimation algorithm by which all the existing values for DBH established before the revision can be converted to the highest and the lowest ones. The purpose of this study is to develop an estimation equation to automatically show the minimum and the maximum values for DBH for 12 main tree species from the data in the national forest management information system. In order to develop the estimation equation for the minimum and the maximum values for DBH, there was exploited the 6,858 fixed sample plots of the fifth and the sixth national forest inventory between in 2006 and 2015. Two estimation models were applied for DBH-tree age and DHB-tree height using such growth variables as DBH, tree age, and height, to draw the estimation equation for the maximum and the minimum values for DBH. The findings showed that the most suitable model to estimate the minimum and the maximum values for DBH was Dmin=a+bD+cH, Dmax=a+bD+cH with the variables of DBH and height. Based on these optimal models, the estimation equation was devised for the minimum and the maximum values for DBH for the 12 main tree species.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.24-35
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• 2021

Due to increasing awareness on the treatment of end-of-use/life products, disassembly has been a fast-growing research area of interest for many researchers over recent decades. This paper introduces a novel lot-sizing problem that has not been studied in the literature, which is the service-parts lot-sizing with disassembly option. The disassembly option implies that the demands of service parts can be fulfilled by newly manufactured parts, but also by disassembled parts. The disassembled parts are the ones recovered after the disassembly of end-of-use/life products. The objective of the considered problem is to maximize the total profit, i.e., the revenue of selling the service parts minus the total cost of the fixed setup, production, disassembly, inventory holding, and disposal over a planning horizon. This paper proves that the single-period version of the considered problem is NP-hard and suggests a heuristic by combining a simulated annealing algorithm and a linear-programming relaxation. Computational experiment results show that the heuristic generates near-optimal solutions within reasonable computation time, which implies that the heuristic is a viable optimization tool for the service parts inventory management. In addition, sensitivity analyses indicate that deciding an appropriate price of disassembled parts and an appropriate collection amount of EOLs are very important for sustainable service parts systems.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.125-134
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• 2014

Supply Chain Management(SCM) is getting important, because size of the company is getting bigger and the kinds of product are various. In the case of manufacturing corporation, for the optimization of SCM, we have to make production and distribution plan by considering the various fluctuation in the aspect of integration. In this paper, first, It proposed the reasonable operational way of the SCM about when the customer's demanding is various and demanding expectation fluctuates in capacity standardization of producer stage. Second, the paper proposed the management way for demanding by considering confirmed demanding information, related inventory expense and demanding shortage expense when we make production and distribution plan. The paper applied the genetic algorithm proved for current usefulness. it proposed the optimal operational way for SCM by dividing into 2 ways for dealing with the duration of confirmed demanding information and various fluctuation.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.51-57
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• 2010

Cycling that transform human energy into mechanical energy is one of the man-machine systems out of sports fields. Benchmarking means "improving ourselves by learning from others', therefore benchmarking toward dominant cyclist is necessary on field. The goals of this study were to provide important factors on multi-disciplines (kinematics, physiology, power, psychology) for a tailored-training program that is suitable to individual characteristics. Two cyclists participated in this study and gave consent to the experimental procedure. One was dominant cyclist (years: 21 yrs, height: 177 cm, mass: 70 kg), and the other was non-dominant cyclist (years: 21, height: 176, mass: 70). Kinematic data were recorded using six infrared cameras (240Hz) and QTM (software). Physiological data (VO2max, AT) were acquired according to graded exercising test with cycle ergometer and power with Wingate test used by Bar-Or et. al (1977) and to evaluate muscle function with Cybex. Psychological data were collected with competitive state anxiety inventory (CSAI-2) that was devised by Martens et. al (1990) and athletes' self-management questionnaire (ASMQ) of Huh (2003). It appears that the dominant's CV of ankle joint angle was higher than non-dominant's CV and dominant's pedaling pattern was consistent in biomechanics domain, which the dominant's values for all factors ware higher than non-dominant's values in physical, and physiological domain, and their values between cognitive anxiety and somatic anxiety were contrary to each other in psychology. Further research on multi-disciplines may lead to the development of tailored-optimal training programs applicable with key factors to enhance athletic performance by means of research including athlete, coach and parents.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.91-103
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• 2006

Given a bill of materials (BOM) tree T labeled by the breadth first search (BFS) order from node 0 to node n and a general network ${\Im}=(V,A)$, where V={1,2,...,m} is the set of production facilities and A is the set of arcs representing transportation links between any of two facilities, we assume that each node of T stands for not only a component. but also a production stage which is a possible stocking point and operates under a periodic review base-stock policy, We also assume that the random demand which can be achieved by a suitable service level only occurs at the root node 0 of T and has a normal distribution $N({\mu},{\sigma}^2)$. Then our integrated model of facility location problems and safety stock optimization problem (FLP&SSOP) is to identify both the facility locations at which partitioned subtrees of T are produced and the optimal assignment of safety stocks so that the sum of production cost, inventory holding cost, and transportation cost is minimized while meeting the pre-specified service level for the final product. In this paper, we first formulate (FLP&SSOP) as a nonlinear integer programming model and show that it can be reformulated as a 0-1 linear integer programming model with an exponential number of decision variables. We then show that the linear programming relaxation of the reformulated model has an integrality property which guarantees that it can be optimally solved by a column generation method.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• The Journal of Information Systems
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• v.30 no.2
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.15-24
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• 2009

Cycling that transform human energy into mechanical energy is one of the man-machine systems out of sports fields. Benchmarking means " improving ourselves by learning from others ", therefore benchmarking toward dominant cyclist is necessary on field. the goals of this study were to provide important factors on multi-disciplines (kinematics, physiology, power, psychology) for a tailored-training program that is suitable to individual characteristics. Two cyclist participated in this study and gave consent to the experimental procedure. one was dominant cyclist (years:21 yrs, height:177 cm, mass:70 kg), and the other was non-dominant cyclist(years:21, height:176, mass:70). Kinematic data were recorded using six infrared cameras (240Hz) and QTM (software). Physiological data (VO2max, AT) were acquired according to graded exercising test with cycle ergometer and power with Wingate test used by Bar-Or et. al ( 1977) and to evaluate muscle function with Cybex. Psychological data were collected with competitive state anxiety inventory (CSAI-2) that were devised by Martens et. al (1990) and with athletes' self-management questionnaire (ASMQ) of Huh (2003). It appears that the dominant's CV(coefficient of variability) was higher than non-dominant's CV in Sports Biomechanics domain, that the dominant's values for all factors ware higher than non-dominant's values in physical, and physiological domain, and their values between cognitive anxiety and somatic anxiety were contrary to each other in psychology. Further research on multi-disciplines may lead to the development of tailored-optimal training programs applicable with key factors to enhance athletic performance by means of research including athlete, coach and parents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.611-616
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• 2018

RFID-based Smart cabinets can make a recognition error owing to the electromagnetic wave interference. This paper proposes and implements a smart cabinet system for inventory management using RFID, especially which can be applied to biological laboratories. We calculate the optimal value of partition distance for the higher recognition rate between RFID tags and the reader, and the optimal partition thickness for electromagnetic wave absorption to achieve the higher recognition rate, in which two kinds of the partitions have been tested, a pure steel partition with various thickness and a thin steel partition attached with electromagnetic waves absorber. The experimental results show that the most recommended partition structure for the smart cabinets is one with the partition distance of 30cm and the partition thickness of 1mm attached with the electromagnetic wave absorption tapes.