• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.137-143
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• 2018

This study is an interaction design study which can improve the usability of random item boxes that are used as in - game contents in Korean mobile games. Currently, Korean mobile game sales continue to rise. Sales of random item boxes are the main reason for the increase in sales. Problems with the use of random item boxes have been continuously raised, and legal regulations are currently in place. When using random item boxes, the user can not know the exact percentage information. There is a concern that this expresses gambling. In this context, we have studied interaction design to improve the usability of random item boxes, and conducted user online surveys and in - depth interviews to provide users with a better game experience. As a result, it is shown that providing percentage information intuitively when using random item boxes can enhance user experience. Through this study, it is expected that interaction design research will be actively conducted to provide a better user experience when using random item boxes.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.439-452
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• 2022

This study aimed to explore the relationships between random item usage and gaming disorder tendency. A total of 413 adults participated and demographic and psychosocial variables were collected using Cloninger's Temperament and Character Inventory, Cognitive Emotion Regulation Questionnaire, and Daily Hassles Scale for Korean Worker. The results are as follows. First, two-third of gamers used the random item games and women are more engaged than men in random item games. Second, there were significant differences of gaming disorder tendency, game use time, and game use money (both for general and random item) depending on the item use type. Third, predictors of gaming disorder tendency were found as game use money (general), game use time, maladaptive emotion regulation, stress, novelty seeking, and stress using multiple regression analysis. Proper intervention for gaming disorder tendency and the need of further research were discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.194-200
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• 2005

A stochastic dynamic lot sizing problem for multi-item is suggested in the case that the distribution of the cumulative demand is known over finite planning horizons and all unsatisfied demand is fully backlogged. Each item is produced simultaneously at a variable ratio of input resources employed whenever setup is incurred. A dynamic programming algorithm is proposed to find the optimal production policy, which resembles the Wagner-Whitin algorithm for the deterministic case problem but with some additional feasibility constraints.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.421-431
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• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.129-132
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• 1987

Multi-item inventory problems can be well characterized by the nature of interaction of the quantities and timing. This interaction may be due to the effect of certain combination of orders. It is that the set-up cost of ordering individual items can be saved by jointly ordering at a time. This study finds a decision criteria of optimum inventory policy through the comparisons of individual multi-item order policy(IMP), joint multi-item order policy(JMP), augmented multi-item order policy(AMP) in cost ratio. Subsequently we assume that there exists a unique optimum order level corresponding to an optimum reorder range for the augmented multi-item order, at which a cost saying is maximum.

• Advances in aircraft and spacecraft science
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• v.2 no.2
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• pp.217-232
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• 2015

To prevent over-testing of the test-item during random vibration testing Scharton proposed and discussed the force limited random vibration testing (FLVT) in a number of publications. Besides the random vibration specification, the total mass and the turn-over frequency of the load (test item), $C^2$ is a very important parameter for FLVT. A number of computational methods to estimate $C^2$ are described in the literature, i.e., the simple and the complex two degrees of freedom system, STDFS and CTDFS, respectively. The motivation of this work is to evaluate the method for the computation of a realistic value of $C^2$ to perform a representative random vibration test based on force limitation, when the adjacent structure (source) description is more or less unknown. Marchand discussed the formal description of getting $C^2$, using the maximum PSD of the acceleration and maximum PSD of the force, both at the interface between load and source. Stevens presented the coupled systems modal approach (CSMA), where simplified asparagus patch models (parallel-oscillator representation) of load and source are connected, consisting of modal effective masses and the spring stiffness's associated with the natural frequencies. When the random acceleration vibration specification is given the CSMA method is suitable to compute the value of the parameter $C^2$. When no mathematical model of the source can be made available, estimations of the value $C^2$ can be find in literature. In this paper a probabilistic mathematical representation of the unknown source is proposed, such that the asparagus patch model of the source can be approximated. The chosen probabilistic design parameters have a uniform distribution. The computation of the value $C^2$ can be done in conjunction with the CSMA method, knowing the apparent mass of the load and the random acceleration specification at the interface between load and source, respectively. Data of two cases available from literature have been analyzed and discussed to get more knowledge about the applicability of the probabilistic method.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.43-48
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• 1986

In this paper, the one period multi-item inventory model is considered in which it is required to determine the production quantity and selling price of each item which maximize the probability of realizing predetermined level of profit. The objective function of this model is the sum of weighted probabilities which represent the possibility of obtaining the predetermined level of profit for each item. Budget constraint, inventory site constraint and constraints of price are considered. Finally this paper shows a numerical example in which random demand of each item has exponential distribution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.427-431
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• 1994

The objective of this paper is to provide an inventory control policy for the system that carries a single item with a multiple demand classes, when the demand is Poisson distributed random variable. The inventory control process includes the process of determining the reorder point, and the process of inventory control during the lead time. The goal of the optimization process is to achieve the service level of each demand class as well as the system-wide total service level at a preset desired service level while sustaining a minimum average inventory.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.241-246
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• 2000

A simple random sample is taken from a population and a particular survey item is subject to nonresponse that corresponds to random subsampling of the sampled values within adjustment cells. Our object is to estimate Bayesian probability interval of the population mean.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.319-332
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• 1997

The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.