• 한국융합학회논문지
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• 제9권2호
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• pp.137-143
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• 2018

본 연구는 한국 모바일 게임에서 게임 내 콘텐츠로 활용하고 있는 확률형 아이템의 사용성을 개선할 수 있는 인터랙션 디자인 연구이다. 현재 국내 모바일 게임은 지속적인 매출의 상승을 이어가고 있다. 하지만 그 중심에는 확률형 아이템 판매라는 모바일 게임의 대표적인 수익 모델이 있다. 확률형 아이템 사용의 문제점은 지속해서 제기되어 왔고, 현재 법적인 규제안까지 상정 되어있는 상태다. 확률형 아이템은 현재 모바일 게임 이용자가 아이템 사용 시 정확한 확률을 알 수 없으며 한탕주의와 같은 사행성을 표방한다는 우려도 있었다. 이러한 상황에서 확률형 아이템 사용성을 개선하기 위한 인터랙션 디자인을 연구하여 모바일 게임 이용자들에게 더 나은 게임 사용 경험을 제공하기 위해 사용자 온라인 설문과 심층 면접 조사를 시행했다. 연구 결과 확률형 아이템 사용 시 확률 정보를 직관적으로 제공하는 것이 사용자 경험을 높일 수 있다는 결과가 나타났다. 본 연구를 통해 확률형 아이템 사용 시 더 나은 사용자 경험을 제공하기 위한 인터랙션 디자인 연구가 더욱 활발히 이루어질 것으로 기대한다.

• 한국콘텐츠학회논문지
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• 제22권6호
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• pp.439-452
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• 2022

본 연구에서는 확률형 아이템과 게임 과몰입과의 관련성을 살펴보기 위해, 확률형 아이템을 성능 확률형과 치장 확률형, 그리고 비확률형 아이템을 사용하는 세 집단으로 구분 후, 집단간 게임 과몰입을 포함한 변인들의 차이를 살펴보고, 게임 과몰입에 영향을 미치는 인구통계학적, 심리사회적 변인이 무엇인지 탐색하고자 하였다. 이를 위해 게임 이용률이 가장 높은 20대를 대상(N=413)으로 인구통계학적 변인(연령, 성별), 게임 과몰입, 게임시간, 게임이용비용, 확률형아이템이용비용(이하 확률형이용비용)을 측정하고, 심리사회적 변인은 기질 및 성격, 인지정서조절, 스트레스를 Cloninger의 기질 및 성격 검사, 인지적 정서조절전략 척도, 일상생활 스트레스 척도를 사용하여 각각 측정하였다. 연구 결과, 첫째, 게이머의 2/3가 확률형 아이템 게임을 즐기는 것으로 나타났으며, 여자의 비율이 남자의 비율보다 높은 것으로 나타났다. 둘째, 아이템 유형에 따라 구분한 세 집단 간에는 게임 과몰입, 게임시간, 게임이용비용, 확률형이용비용에서 유의미한 차이가 관찰되었다. 셋째, 게임 과몰입에 영향을 미치는 변인은 게임이용비용, 게임시간, 부적응적 인지정서조절, 스트레스, 자극추구 기질과 연대감 성격으로 나타났다. 게임 과몰입을 위한 적절한 개입으로서, 게임시간, 지출비용, 정서조절과 스트레스 관리의 중요성을 확인하였고, 본 연구 결과의 일반화를 위한 후속 연구에 대해 논의하였다.

• 대한산업공학회지
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• 제31권3호
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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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• 제13권4호
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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.

• 산업경영시스템학회지
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• 제10권16호
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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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• 제2권2호
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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.

• 대한산업공학회지
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• 제12권1호
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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.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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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.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2000년도 추계학술발표회 논문집
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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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• 제26권3호
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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.