• Journal of Distribution Science
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• v.18 no.3
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• pp.25-36
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• 2020

Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.29-39
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• 2002

The transaction tables of the existing association algorithms have two column attributes : It is composed of transaction identifier (Transaction_id) and an item identifier (item). In this kind of structure, as the volume of data becomes larger, the performance for the SQL query statements came applicable decreases. Therefore, we propose advanced association rules algorithm of n-items which can transact multiple items (Transaction_id, Item 1, Item 2…, Item n). In this structure, performance hours can be contracted more than the single item structures, because count can be computed by query of the input transaction tables. Our experimental results indicate that performance of the n items structure is up to 2 times better than the single item. As a result of this paper, the proposed algorithm can be applied to internet shopping, searching engine and etc.

• Journal of Korea Game Society
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• v.12 no.6
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• pp.59-70
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• 2012

There are many methods to buy and sell online items. But A lot of people use item trade sites when they want to sell or buy their items. This article analyzes the price structure of item trade, and finds why gamers use item trade sites in spite of the brokerage. We analyze the difference of item prices between in the market of item trade sites and in the market of other trade methods. And we find that the prices of item trade sites is higher than those of other markets. Buyers pay about 6% higher prices to seller. The higher prices are for the safe trading what item trade sites supply. And sellers take about 0.7% higher prices than in other markets. There is a sufficient motive when gamers use item trade sites in spite of their high prices.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• Proceedings of the CALSEC Conference
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• 1997.11a
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• pp.443-461
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• 1997

ㆍProSTEP, PDES, Inc., and JSTEP announce agreement on PDM Schema ㆍ November 4, 1997 ㆍInteroperable with STEP AP203, AP2l0, AP214, and AP232 ㆍNeutral specification allows for the exchange of the following types - item master data (part identification, approval of part version) - item structure - item classification - item property (mass, costs) - document management (identification, revision… ) - work management (engineering change request, EC order, project) ㆍVendors of PDM systems are asked to join ProSTEP's PDM Round Table and PDES, Inc.'s PDMnet.(omitted)

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• The Pure and Applied Mathematics
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• v.3 no.2
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• pp.141-154
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• 1996

A data-driven index of dimensionality for an educational or psychological test - DETECT, short for Dimensionality Evaluation To Enumerate Contributing Traits, is proposed in this paper. It is based on estimated conditional covariances of item pairs, given score on remaining test items. Its purpose is to detect whatever multidimensionality structure exists, especially in the case of approximate simple structure. It does so by assigning items to relatively dimensionally homogeneous clusters via attempted maximization of the DETECT over all possible item cluster partitions. The performance of DETECT is studied through real and simulated data analyses.

• The Journal of Korean Physical Therapy
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• v.21 no.3
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• pp.1-8
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• 2009

Purpose: The purpose of this study was to examine the functional category, the item structure and the model-data fit of the neck disability index (NDI) of neck pain subjects by performing a Rasch rating scale analysis. Methods: The data was obtained from the assessments of 71 college students (males: 27, females: 44) with neck pain. The data of the NDI was applied to the Rasch's rating scale model to estimate the difficulty of items, the goodness-of-fit of each item, the separation reliability and index, and the rating scale. Results: The 'sleep' item showed misfit and nine items were founds to be fits for self-reporting of disability due to neck pain. The most difficult item of the remaining 9 items was 'work' and the easiest item was 'headache'. The transformation formula score=(logit score+7.10)/(7.10+0.11)$\times$100. The 6 response levels of the NDI were validated according to the structure of the rating scale. The item and subject reliability of the separation reliability was 0.97 and 0.85, respectively. Conclusion: We proved that the NDI for self-reporting of disability of daily activities due to mild neck pain was valid and reliable. This study suggests that individuals with mild neck pain may be assessed by using the modified NDI that does not include the 'sleep' item in the 10 items of NDI.

• Journal of Preventive Medicine and Public Health
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• v.38 no.1
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• pp.61-70
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• 2005

Objectives : To develop a tool for multidimensional measurement of the quality of life, which was psychometrically sound, short, and easy to administer for patients with hypertension. Methods : A sample of 1,115 hypertensive patients aged 20 or above in Cheong-Song County was studied from June 1997 to October 1998. In the development of the instrumental stage, the authors first conceptualized the quality of life. Item generation, item reduction, and questionnaire formatting were followed. Item-level (item descriptive, missing%, item internal consistency, item discriminant validity) analysis, scale-level (scale descriptive, floor and ceiling effect) analysis, and other tests(Cronbach's alpha, inter-dimension correlations, factor analysis, clinical validity) were performed to evaluate the validity and reliability of the new measurement scale. After 1 year, responsiveness and confirmatory factor analysis were performed. Results : The results of both item-level and scale-level analyses were acceptable. An acceptable degree of internal consistency was observed for each of the dimensions (Cronbach's alpha was 0.60 or higher). Inter-dimension correlations were below 0.50 and the factor analysis result was the same as the intended dimension structure. Correlation coefficients between perceived health status, stress and dimensions were proven to be acceptable. The result of comparing dimensional score means among ADL and MMSE-K groups above 60 years was statistically significant(p<0.05). The result of confirmatory factor analysis concluded that the dimensional structure model was well fitted. However, the result of responsiveness test using sensitivity and specificity was unsatisfactory. Conclusions : The newly developed measurement scale is psychometrically reliable and valid instrument for measuring quality of life in hypertensive patients.