• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5541-5554
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• 2018

A voice is one of the most significant non-verbal elements for communication. Disorders in vocal organs, or habitual muscular setting for articulatory cause vocal disorders. Therefore, by analyzing the vocal disorders, it is possible to predicate vocal diseases. In this paper, a method of predicting vocal disorders using the jitter, shimmer, and harmonics-to-noise ratio (HNR) extracted from vocal records is proposed. In order to extract jitter, shimmer, and HNR, one-second's voice signals are recorded in 44.1khz. In an experiment, 151 voice records are collected. The collected data set is clustered using cobweb clustering method. 21 classes with 12 leaves are resulted from the data set. According to the semantics of jitter, shimmer, and HNR, the class whose centroid has lowest jitter and shimmer, and highest HNR becomes the normal vocal group. The risk of vocal disorders can be predicted by measuring the distance and direction between the centroids.

• The Korean Journal of Archival Studies
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• no.5
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• pp.3-37
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• 2002

Today the market of EDMS is esteemed more than 100 billions won. It signifies a comming of age of electronic records. The traditional archival theories which are based on the paper records are confronted with a new challenge. In some leading countries of archival studies reorientation of archives management has been tried by a number of distinguished specialists such as Bearman and Hedstrom since 10 years. As a consequence new paradigm of archival theories has been developed. Also in Korea this new paradigm has been introduced by some expert such as Lee, Sang-Min, Sul, Moon-won, Lee, Seung-Eok. However their arguments are too general to offer a concrete clue for new paradigm. Faced by new age of electronic records, it's important to start a discussion for the reasonable methods of electronic records management at once. The most drastically changed part of record management by the electronic technique is the life-cycle of records. The commonly practiced three-stage life-cycle is to be reduced to the two-stage life-cycle, and the concept of the spatial movement of records is to be changed. It can be also pointed that the public emerges as user from the early creating stage of records beyond time and space. Thus is can be said that the method of the management features dynamic and cohesive. The method of appraisal must be also changed and reproduced, so that it can reflect the various levels considering dynamics of the electronic records. Supposedly it will be a core factor that causes the change of methodology in records management with the change of life-cycle theory. It must be noted that various subjects would be involved in the work of classification and description over time and space and that feedback between them is of important. Description also tends to be made at the crating stage of records and structured dynamically. It results from the change of life-cycle and the introduction of the concept of continuum. Such trend allows us to start discussions on the assumption that description of both creator and archival professionals act together an important role. Of course, it is linked with the methodology in which most descriptions are made automatically at the early drafting stage of the structure. The meat date is formed on the assumption that there should be feedback between areas of automatic description, description of creators and archival professionals. The most important thing in description is to develop a suitable way how it is structured. An alternative must be offered for managing data set. As iweb that is being operated by Myongji university shows, records created in daily business are managed not as electronic records but as date base. This is because they exist outside the repository in the EDMS system. Since data set often has various sources, an alternative for classification needs to be developed. It is now likely that database is filed according to the created year to be transferred automatically to the repository. Over a long-term the total management of database, electronic records and electronic information will be a topic. A right direction of new paradigm will be found for both iweb and E-government, when practice and studies of theories are combined and interacted.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.9
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• pp.1349-1354
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• 2019

Objective: The objective of this study was to determine the best approach for handling missing records of first to successful insemination (FS) in Japanese Black heifers. Methods: Of a total of 2,367 records of heifers born between 2003 and 2015 used, 206 (8.7%) of open heifers were missing. Four penalty methods based on the number of inseminations were set as follows: C1, FS average according to the number of inseminations; C2, constant number of days, 359; C3, maximum number of FS days to each insemination; and C4, average of FS at the last insemination and FS of C2. C5 was generated by adding a constant number (21 d) to the highest number of FS days in each contemporary group. The bootstrap method was used to compare among the 5 methods in terms of bias, mean squared error (MSE) and coefficient of correlation between estimated breeding value (EBV) of non-censored data and censored data. Three percentages (5%, 10%, and 15%) were investigated using the random censoring scheme. The univariate animal model was used to conduct genetic analysis. Results: Heritability of FS in non-censored data was $0.012{\pm}0.016$, slightly lower than the average estimate from the five penalty methods. C1, C2, and C3 showed lower standard errors of estimated heritability but demonstrated inconsistent results for different percentages of missing records. C4 showed moderate standard errors but more stable ones for all percentages of the missing records, whereas C5 showed the highest standard errors compared with noncensored data. The MSE in C4 heritability was $0.633{\times}10^{-4}$, $0.879{\times}10^{-4}$, $0.876{\times}10^{-4}$ and $0.866{\times}10^{-4}$ for 5%, 8.7%, 10%, and 15%, respectively, of the missing records. Thus, C4 showed the lowest and the most stable MSE of heritability; the coefficient of correlation for EBV was 0.88; 0.93 and 0.90 for heifer, sire and dam, respectively. Conclusion: C4 demonstrated the highest positive correlation with the non-censored data set and was consistent within different percentages of the missing records. We concluded that C4 was the best penalty method for missing records due to the stable value of estimated parameters and the highest coefficient of correlation.

• Journal of Korean Society of Archives and Records Management
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• v.14 no.3
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• pp.7-32
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• 2014

The objective of this research is to seek a preservation method against the set of data. To achieve this purpose, this study analyzed the MIDAS RASIS RI/ RG of the Nuclear Safety and Security Commission, and then followed it with the under analysis of the MIDAS RASIS, thus presenting the transfer process. This was conducted for the records management of the MIDAS RASIS-designed records management modules DB. For the records management of MADIS RASIS, the records management module DB was thus planned, which presented the transfers through the standard records management system.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.204-210
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• 2019

Mobile Crowd Computing is one of the most efficient and effective way to collect the Electronic health records and they are very intelligent in processing them. Mobile Crowd Computing can handle, analyze and process the huge volumes of Electronic Health Records (EHR) from the high-performance Cloud Environment. Electronic Health Records are very sensitive, so they need to be secured, authenticated and processed efficiently. However, security, privacy and authentication of Electronic health records(EHR) and Patient health records(PHR) in the Mobile Crowd Computing Environment have become a critical issue that restricts many healthcare services from using Crowd Computing services .Our proposed Efficient Multi-layer Encryption Framework(MLEF) applies a set of multiple security Algorithms to provide access control over integrity, confidentiality, privacy and authentication with cost efficient to the Electronic health records(HER)and Patient health records(PHR). Our system provides the efficient way to create an environment that is capable of capturing, storing, searching, sharing, analyzing and authenticating electronic healthcare records efficiently to provide right intervention to the right patient at the right time in the Mobile Crowd Computing Environment.

• The Korean Journal of Archival Studies
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• no.10
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• pp.3-26
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• 2004

ISO 15489:2001 addresses the principles and requirements with which organizations, both public and private, should comply on the management of their records to ensure that adequate records are created, captured and managed. The standard defines the characteristics that a record should have through records management system as follows: authenticity, reliability, integrity, and usability. Authenticity means that records can be proven to be what it purports to be, to have been created or sent by the person purported to have created or sent it, and to have been created or sent at the time purported. Reliability means that the contents of the records can be trusted as a full and accurate representation of the transactions, activities or facts to which they attest and can be depended upon in the course of subsequent transactions or activities. Integrity refers to ensuring that a record is complete and unaltered. Usability means that records can be located, retrieved, presented and interpreted. In order to have these characteristics, a record should be persistently linked to the metadata necessary to document a transaction. Metadata is "data describing context, content and structure of records and their management through time." Metadata ensure the creation and maintenance of authentic, reliable and usable records and the protection of the integrity of those records. It could be implemented by creating and capturing records management metadata in systems that create and manage records. There have been some projects and standard initiatives to identify a core set of records management metadata. Included are the Australian Recordkeeping Metadata Standard and the British Metadata Standard which is part of the Requirements for Electronic Records Management System. Recently ISO/TS 23081-1 is published to implement metadata requirements within the framework of ISO 15489. Public records management system in Korea is ruled by the Act on the Management of Archives by Public Agencies and Administrative Records Management Regulation. This article evaluates records and their descriptive elements captured and maintained by the records management system in Korea on the basis of the international metadata standards.

• Journal of Korean Society of Archives and Records Management
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• v.8 no.2
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• pp.153-179
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• 2008

Museum Records is both a resource for the administration and for researchers. And It is necessary for the day-to-day operation of the museum's activity and it serves researchers of all kinds. This study is aimed to grasp the present condition of museum records management in a National Museum of Korea and 11 local national museums in Korea as a case study. To this end, two methods were used to collect the essential data. First, a comprehensive literature survey was conducted to investigate foreign successful museum records management system. Second, interview and questionnaire survey were conducted to collect the data of actual state of National Museum. The results show that National Museum should be a wholly responsible for the department and disposition of professional staffs and set up the comprehensive registration system, the standard of classification considering the museum's feature and the regular estimation system. And also National Museum should expand and improve the facilities according to "Archives and Records Management of Public Agencies Act".

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.105-120
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• 2015

A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• Journal of Korean Library and Information Science Society
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• v.46 no.1
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• pp.1-23
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• 2015

The purpose of this paper is to development an algorithm for FRBR implementation(functional requirements for bibliographic records), analyzing KORMARC bibliographic records by work types. For this purpose, it was utilized analyzing home and foreign case studies including OCLC and LC's algorithm. Analyzing the experimental data from the Korean National Library's bibliographic records, it was extracted from identifying elements by FRBR's four bibliographic entities. To cluster a related works by work-set, the algorithm was designed to construct the authorized access points as a combination of an author name and a title from the record. I suggested that it should be wholly improved a quality of existing bibliographic records and level of data input to development a FRBR algorithm in Korean libraries.