• Journal of KIISE:Databases
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• v.37 no.3
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• pp.171-175
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• 2010

This paper analyzes the tag data inconsistency problem caused by incomplete execution of the tag access operation to the RFID tag's memory and proposes a protocol to control consistent tag data accesses with finalizing the incomplete operation. Passive RFID tag cannot guarantee complete execution of the tag access operations because of uncertainty and unexpected disconnection of RF communications. This leads to the tag data inconsistency problem. To handle this, we propose a concurrency control protocol which defines incomplete tag operations as continuous queries and monitors the tags're-observation continuously. The protocol finalizes the incomplete operation when the tag is re-observed while it blocks inconsistent data accesses from other operations. We justify the proposed protocol by analyzing the completeness and consistency. The experiments show that the protocol shows better performance than the traditional lock-based concurrency control protocol.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.113-143
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• 1997

Most of the conflict problems between 2 persons can be represented as a bi-matrix game, because player's utilities, in general, are non-zero sum and change according to the progress of game. In the bi-matrix game the equilibrium point set which satisfies the Pareto optimality can be a good bargaining or coordination solution. Under the condition of incomplete information about the risk attitudes of the players, the bargaining or coordination solution depends on additional elements, namely, the players' methods of making inferences when they reach a node in the extensive form of the game that is off the equilibrium path. So the investigation about the players' inference type and its effects on the solution is essential. In addition to that, the effect of an individual's aversion to risk on various solutions in conflict problems, as expressed in his (her) utility function, must be considered. Those kinds of incomplete information make decision maker Bayesian, since it is often impossible to get correct information for building a decision making model. In Baysian point of view, this paper represents an analytic frame for guessing and learning opponent's attitude to risk for getting better reward. As an example for that analytic frame. 2 persons'bi-matrix game is considered. This example explains that a bi-matrix game can be transformed into a kind of matrix game through the players' implicitly cooperative attitude and the need of arbitration.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.1
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• pp.27-42
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• 2003

The purpose of this study is to evaluate the quality of the Serials Union Catalog(UCAT) of KISTI. In examining both MARC records and bibliographic display records of 172 Japanese serials, AACR2R and KORMARC formats were used as the standard rules. Those records were described in the minimum or incomplete level ; but had repeated errors in various data fields, which included the incorrect choice of main headings, parallel titles and other titles, the improper use of language codes and related data fields, and the provision of incomplete information, etc. To improve the overall quality of bibliographic database, thorough comprehension and application of cataloging rules and MARC formats are strongly required.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.97-100
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• 2008

This study estimated the error involved in the areal average rainfall derived incomplete radar information due to radar partial coverage of a basin or sub-basin. This study considers the Han River Basin as an application example for the rainfall observation using the Ganghwa rain radar. Among the total of 24 mid-sized sub-basins of the Han River Basin evaluated in this study, only five sub-basins are fully covered by the radar and three are totally uncovered. Remaining 16 sub-basins are partially covered by the radar leading incomplete radar information available. When only partial radar information is available, the sampling error decreases proportional to the size of the radar coverage, which also varies depending on the number of clusters. It is general that smaller sampling error can be expected when the number of clusters increases if the total area coverage remains the same. This study estimated the sampling error of the areal average rainfall of partially-covered mid-sized sub-basins of the Han River Basin, and the results show that the sampling error could be at least several % to maximum tens % depending on the relative coverage area.

• Survey Research
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• v.9 no.2
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• pp.1-27
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• 2008

Problems of incomplete data are pervasive in statistical analysis. In particular, incomplete data have been an important challenge in repeated measures studies. The objective of this study is to give a brief introduction to missing data mechanisms and conventional/recent missing data methods and to assess the performance of various missing data methods under ignorable and non-ignorable missingness mechanisms. Given the inadequate attention to longitudinal studies with missing data, this study applied recent advances in missing data methods to repeated measures models and investigated the performance of various missing data methods, such as FIML (Full Information Maximum Likelihood Estimation) and MICE(Multivariate Imputation by Chained Equations), under MCAR, MAR, and MNAR mechanisms. Overall, the results showed that listwise deletion and mean imputation performed poorly compared to other recommended missing data procedures. The better performance of EM, FIML, and MICE was more noticeable under MAR compared to MCAR. With the non-ignorable missing data, this study showed that missing data methods did not perform well. In particular, this problem was noticeable in slope-related estimates. Therefore, this study suggests that if missing data are suspected to be non-ignorable, developmental research may underestimate true rates of change over the life course. This study also suggests that bias from non-ignorable missing data can be substantially reduced by considering rich information from variables related to missingness.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.327-336
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• 2014

Recurrent event data occurs when a subject experiences same type of event repeatedly and is found in various areas such as the social sciences, Economics, medicine and public health. To analyze recurrent event data either a total time or a gap time is adopted according to research interest. In this paper, we analyze recurrent event data with incomplete observation gap using a gap time scale. That is, some subjects leave temporarily from a study and return after a while. But it is not available when the observation gaps terminate. We adopt an interval censoring mechanism for estimating the termination time. Furthermore, to model the association among gap times of a subject, a frailty effect is incorporated into a model. Programs included in Survival package of R program are implemented to estimate the covariate effect as well as the variance of frailty effect. YTOP (Young Traffic Offenders Program) data is analyzed with both proportional hazard model and a weibull regression model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3B
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• pp.183-198
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• 2006

We define the incomplete medium sharing system as a multi-channel shared medium communication system where constraints are imposed to the set of channels that may be allocated to some transmitter-receiver node pairs. To derive a centralized MAC scheme of a incomplete medium sharing system, we address the problem of optimal channel allocation The optimal channel allocation problem is then translated into a max-flow problem in a multi-commodity flow graph, and it is shown that the optimal solution can then be obtained by solving a linear programming problem. In addition, two suboptimal channel allocation schemes are proposed to bring down the computational complexity to a practical/feasible level; (1) one is a modified iSLIP channel allocation scheme, (2) the other is sequential channel allocation scheme. From the results of a extensive set of numerical experiments, it is found that the suboptimal schemes evaluate channel utilization close to that of the optimal schemes while requiring much less amount of computation than the optimal scheme. In particular, the sequential channel allocation scheme is shown to achieve higher channel utilization with less computational complexity than . the modified iSLIP channel allocation scheme.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.1-6
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• 2019

The proposed model is developed to minimize the loss of information in incomplete data including missing data. The first step is to transform the learning data to compensate for the loss information using the data extension technique. In this conversion process, the attribute values of the data are filled with binary or probability values in one-hot encoding. Next, this conversion data is input to the deep learning model, where the number of entries is not constant depending on the cardinality of each attribute. Then, the entry values of each attribute are assigned to the respective input nodes, and learning proceeds. This is different from existing learning models, and has an unusual structure in which arbitrary attribute values are distributedly input to multiple nodes in the input layer. In order to evaluate the learning performance of the proposed model, various experiments are performed on the missing data and it shows that it is superior in terms of performance. The proposed model will be useful as an algorithm to minimize the loss in the ubiquitous environment.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.103-108
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• 2009

This paper proposes a method for building a transliteration dictionary, which is based on pronouncing information extracted from two kinds of existing dictionaries. Also, it proposes a method for transforming the pronouncing information into Korean translitered words. To express the pronouncing information, we define Phoman code system. In order to avoid phonetic estimation process of English words which is the most important problem, the proposed method uses the pronouncing information extracted from the existing dictionaries. Therefore, unlike previous approaches, the proposed method does not need any incomplete phonetic estimation process so that it can produce accurate transliteration results. The proposed method has been fully implemented.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.368-378
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• 2002

As more companies are equipped with data aquisition systems for their products, huge amount of field warranty data has been accumulated. We focus on the case when the field data for a given product comprise with the number of sales and the number of the first failures for each period. The number of censored items and their ages are assumed to be given. This type of data are incomplete in the sense that the age of a failed item is unknown. We construct a model for this type of data and propose an algorithm for nonparametric maximum likelihood estimation of the product reliability. Unlike the nonhomogeneous Poisson process(NHPP) model, our method can handle the data with censored items as well as those with small population. A few examples are investigated to characterize our model, and a real field warranty data set is analyzed by the method.