• Speech Sciences
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• v.13 no.3
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• pp.35-48
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• 2006

The present study examined whether words with higher frequency have more exposure to the lenition process such as intervocalic stop voicing or /h/ reduction in the production of the Korean speakers. Experiment 1 and Experiment 2 tested if word-internal intervocalic voicing and /h/ reduction occur more often in the words with higher frequency than less frequent words respectively. Results showed that the rate of voicing was not significantly different between the high frequency group and the low frequency group; rather both high and low frequency words were shown to be fully voiced in this prosodic position. However, intervocalic /h/s were deleted more in high frequency words than in low frequency words. Low frequency words showed that other phonetic variants such as [h] and [w] were found more often than in high frequency group. Thus the results of the present study are indefinitive as to the relationship between the word frequency and lenition with the data at hand.

• Journal of Microbiology
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• v.41 no.4
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• pp.335-339
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• 2003

Many genetic variants of ${\alpha}_1$-antitrypsin have been associated with early onset emphysema and liver cirrhosis. However, the detailed structural basis of pathogenic ${\alpha}_1$-antitrypsin molecules is rarely known. Here we found that a recombinant $M_{malton}$ variant (Phe52-deleted) lost inhibitory activity by spontaneous conformational conversion into a more stable, inactive form under physiological conditions. Biochemical and spectroscopic data suggested that the variant converts into a reactive center loop-inserted conformation, resembling the latent form of plasminogen activator inhibitor-1.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.97-101
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• 1992

This paper proposes a new procedures for assessing the influence of individual or groups of cases when any regressors are included. At first, various influence measures pickout influential cases when one regress-or is deleted. Next find influential subsets by using heuristic approach and perform group deletion. Retaining or removing any regressors may depend on the presence or absence of one or few cases. Then, we can identify the interrelationships that exist among regressors and cases and examine their impact on the fitted regression equation. We conclude with an example using fuel consumption data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.31-37
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• 1989

The recursive residuals are obtained by the iterative processes as descrbed in section 2. They may require more efforts and time to compute and may face difficultie in ordering of data. But we can investigate each case to be deleted and gather more informations on each case. The recursive residuals are much more effective with conjecture of cusum technique. We suggest to use the predicted residual for the construction of recursive residuals in nonlinear regression models. The assessment of influence and leverage by the connection with recursive residuals will be necessary.

• Convergence Security Journal
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• v.18 no.2
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• pp.25-32
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• 2018

As the use of smartphones become more common, the communication via instant messenger becomes natural. However, it is important to secure the relevant information promptly since the chat room between participants can be used as a space for a criminal conspiracy, and crime-related contents can be stored and deleted easily on smartphones. Therefore, this study aims to identify the available data and to use it as proof by comparing and analyzing the instant messengers with high usage rate.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.75-88
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• 2021

Automobile credit business has developed rapidly in recent years, and corresponding default phenomena occur frequently. Credit default will bring great losses to automobile financial institutions. Therefore, the successful prediction of automobile credit default is of great significance. Firstly, the missing values are deleted, then the random forest is used for feature selection, and then the sample data are randomly grouped. Finally, six prediction models of support vector machine (SVM), random forest and k-nearest neighbor (KNN), logistic, decision tree, and artificial neural network (ANN) are constructed. The results show that these six machine learning models can be used to predict the default of automobile credit. Among these six models, the accuracy of decision tree is 0.79, which is the highest, but the comprehensive performance of SVM is the best. And random grouping can improve the efficiency of model operation to a certain extent, especially SVM.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.689-697
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• 2004

Rapid advances in mobile computing and the availability of wireless communications will soon provide mobile users with the ability to access data regardless of the location of the user or of the data. SRA(Static Replica Allocation) that is traditional scheme has been used for the replication method on the server. This replicates the data on the replica server after a moving host has been transferred to the cell. This strategy is simple and can easily relocate data. However, if a mobile user does not exist in the cell, the replicated data can be deleted in order to maintain data consistency. In addition to, if the mobile host leaves from replicated cell, it is difficult to access data in terms of replication route. Therefore, this paper proposes a new method of relocation based on data consistency strategy called USRAC(User Selection Replica Allocation based on Consistency) and also analyzes access cost according to the moving rate of mobile users, according to the access rate of mobile hosts, and according to the number of cells of mobile users and mobile hosts.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.43-51
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• 2010

It is meaningful to investigate data in unallocated space because we can investigate the deleted data. Consecutively complete file recovery using the File Carving is possible in unallocated area, but noncontiguous or incomplete data recovery is impossible. Typically, the analysis of the data fragments are needed because they should contain large amounts of information. Microsoft Word, Excel, PowerPoint and PDF document file's text are stored using compression or specific document format. If the part of aforementioned document file was stored in unallocated data fragment, text extraction is possible using specific document format. In this paper, we suggest the method of extracting a particular document file text in unallocated data fragment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.4
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• pp.593-600
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• 2009

Purpose: This study was to examine the relation of nurses' job stress and knowledge, attitude and care behavior for elderly patient in hospitals. Method: One hundred ninety one nurses caring the elderly patients in hospitals in Ilsan, Busan and Gyeongsangnam-do were subjects. The data was collected between Sept. 21 and 31, 2009. Data was analyzed using t-test, ANOVA, Pearson correlation with SPSS/Win 17.0 and the fitness of pathway models with AMOS 5.0. Results: The mean scores of job stress and knowledge were in middle range, and attitude and care behavior were in a little higher range. The fitness of hypothetical model was excellent. Job stress had direct effects on attitude and care behavior, knowledge had direct effect on attitude and attitude had direct effect on care behavior. But the pathways related to job stress and attitude and job stress and care behavior were not significant. In modified model deleted the pathway between job stress and attitude, the pathway related to job stress and behavior also was not significant. Conclusion: Education related to the elderly for nurses to improve care behavior is needed continuously.