• Advances in nano research
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• 제14권3호
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Journal of Information Science Theory and Practice
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• 제11권2호
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• 응용통계연구
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• 제23권6호
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• pp.1245-1253
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• 2010

There are two main approaches for estimating the discontinuous regression function nonparametrically. One is the direct approach, the other is the indirect approach. The major goal of the two approaches are different. The direct approach focuses on the overall good estimation of the regression function itself, whereas the indirect approach focuses on the good estimation of jump locations. Apparently, the two approaches are quite different in nature. Gijbels et al. (2007) argue that the comparison of two approaches does not make much sense and that it is even difficult to choose an appropriate criterion for comparisons. However, it is obvious that the indirect approach also has the regression curve estimate as the subsidiary result. Therefore it is necessary to verify the appropriateness of the indirect approach as the estimator of the discontinuous regression function itself. Park (2009a) compared the performance of two approaches through a simulation study. In this paper, we consider a more general case and draw some useful conclusions.

• Journal of Preventive Medicine and Public Health
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• 제28권3호
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• pp.623-639
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• 1995

We have never seen any method to cope basically with complicated situation and problems around medical reimbursement rates here in Korea since 1977 witnessed by the beginning of medical insurance. By the way researchers concerned are beginning to propose some kinds of innovative and detailed ideas to government these days. They are Diagnosis-related group(DRG) and Resource-based .elative value scale(RBRVS). In the light of this situation it is so encouraging that our government can come up with that and move. In case of RBRVS research we have already been reaching even to the level of reviewing and revising methodology for its further development after naive pilot study on internal medicine and general surgery last year. However there might be something different conditions between USA and Korea to apply the same Dr. Hsiao's method and it must be vital to check so called' total work approach' compared with 'intra-service work approach' before expanding to the whole medical fields. According to the' Intra-service approach', the physician's work is supposed to be divided into three sub-works by the name of intraservice work, pre, and post service work. These sub-works, again should be merged together to be the pre-postwork subset through some statistical methods of the estimation process applied by Dr. Hsiao's methodology in RBRVS development later on. But in this paper that estimation process was not taken because we could have real values for all of those surveyed items related to just one specialty, OB & GY. Instead, We used some statistical comparison procedures relevant to demographic characteristics, reliability & validity and correlation analysis with American RVU(Relative value unit) between the total work and merged total work from intraservice work approach. The unit of analysis was individual physicians of OB & GY and 300 physicians were selected for each approach through statistical sampling method based on national population of OB & GY physicians in Korea. And also with the thankful help of Advisory Committee under Korean Association of OB & GY, questionnaires were made and mailed to the subjects, two times. As a result there were not any statistically significant differences in demographic characteristics between the two approaches except for the variable 'Response time for the questionnaires', but in other sections of comparisons, response rate, representative values, reliability & validity test, correlation analysis with American RVU, all showed 'Total approach' was not only more rational and statistically meaningful than 'Intra-service approach' but also had considerable merits. But we are not absolutely sure about this paper's robustness. Because of some limitations, we'd rather like to suggest further researches should be followed. In that sense the first thing would be a research for the influence of doctor's characteristics, especially 'frequency' on the rating of work and the way to define total work more clearly.

• 아동학회지
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• 제37권5호
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• pp.129-144
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• 2016

Objective: This study's purpose was to develop a teaching competency scale for character education for early childhood teachers and to examine its reliability. Methods: The study procedure was as follows: First, scale items were generated by reviewing the literature as a deductive approach and focused interviews with 8 field experts in an inductive approach. Second, face validation was assessed by 7 academic experts, and statistical validation processes were done twice. The data used in the final statistical analyses included 206 questionnaires for early childhood teachers. Statistical validation included item response analysis, item discrimination analysis, exploratory factor analysis, confirmatory factor analysis, and reliability analysis. Results: The 3 factors identified were as follows: Communicate teaching competence, practical teaching competence, and instrumental teaching competence. The validity and reliability of the Teaching Competency Scale for Character Education in Early Childhood Teachers were acceptable. Conclusion: This new scale will be a useful tool to better support character education for early childhood teachers and contribute to providing a basis for developing more sophisticated tools.

• 한국가스학회지
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• 제1권1호
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• pp.14-20
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• 1997

배관망의 해석은 유체역학을 필요로 하며 관내의 유체의 거동과 운전상태에 따른 유동 해석을 위해 여러 식들이 사용되어왔다. 본 연구에서는 정상상태의 유량방정식을 사용해 경인지역가스 배관망에 대한 수학적 모델을 만들고 모사 및 분석을 수행하였다. 개발된 수학적 모델에서 얻어진 데이터에 통계학적인 방법을 도입해 통계학적 모델을 만듦으로써 통계학적 모델을 이용한 배관망 해석의 가능성에 대해 검토하였다.

• 소음진동
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• 제11권2호
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• pp.257-264
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• 2001

In this research, piezoelectric smart structures are applied for SEA(Statistical Energy Analysis), which is well known approach for high frequency analysis. A new input power measurement based on piezoelectric electrical power measurement is proposed and compared with the conventional method in SEA. As an example, a simple aluminum beam on which piezoelectric actuator is attached is considered. By measuring the electrical impedance and electrical current of the piezoelectric actuator, the electrical power given on the actuator is found and this is In turn converted into the mechanical energy. From the measured value of the stored energy of the beam, the Internal loss factor is calculated and this value shows a good agreement with that given by the conventional method as well as the theoretical value. To compare the coupling loss factor, L-shape beam system which consists of a aluminum beam subsystem and a steel beam subsystem coupled by three pin is taken as second example. The input power and stored energy of each subsystem are found by the proposed approach. The coupling loss factor found by the electrical input power obtained from the piezoelectric actuator exhibits similar trend to the value found by the conventional method as well as the theoretical value. In conclusion, the use of SEA for high frequency application of piezoelectric smart structures is Possible. Especially, the input power that is essential for SEA can be found accurately by measuring the electrical input power of the piezoelectric actuator.

• Smart Structures and Systems
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• 제14권3호
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• pp.377-395
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• 2014

Vibration-based fault detection and condition monitoring of rotating machinery, using statistical process control (SPC) combined with statistical pattern recognition methodology, has been widely investigated by many researchers. In particular, the discrete wavelet transform (DWT) is considered as a powerful tool for feature extraction in detecting fault on rotating machinery. Although DWT significantly reduces the dimensionality of the data, the number of retained wavelet features can still be significantly large. Then, the use of standard multivariate SPC techniques is not advised, because the sample covariance matrix is likely to be singular, so that the common multivariate statistics cannot be calculated. Even though many feature-based SPC methods have been introduced to tackle this deficiency, most methods require a parametric distributional assumption that restricts their feasibility to specific problems of process control, and thus limit their application. This study proposes a nonparametric multivariate control chart method, based on multiscale wavelet scalogram (MWS) features, that overcomes the limitation posed by the parametric assumption in existing SPC methods. The presented approach takes advantage of multi-resolution analysis using DWT, and obtains MWS features with significantly low dimensionality. We calculate Hotelling's $T^2$-type monitoring statistic using MWS, which has enough damage-discrimination ability. A bootstrap approach is used to determine the upper control limit of the monitoring statistic, without any distributional assumption. Numerical simulations demonstrate the performance of the proposed control charting method, under various damage-level scenarios for a bearing system.

• Journal of Communications and Networks
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• 제15권5호
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• pp.469-475
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• 2013

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cells if the required average user throughput is not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.107-116
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• 2004

The advent of microarray technologies gives an opportunity to moni tor the expression of ten thousands of genes, simultaneously. Such microarray data can be deteriorated by experimental errors and image artifacts, which generate non-negligible outliers that are estimated by 15% of typical microarray data. Thus, it is an important issue to detect and correct the se faulty probes prior to high-level data analysis such as classification or clustering. In this paper, we propose a systematic procedure for the detection of faulty probes and its proper correction in Genechip array based on multivariate statistical approaches. Principal component analysis (PCA), one of the most widely used multivariate statistical approaches, has been applied to construct a statistical correlation model with 20 pairs of probes for each gene. And, the faulty probes are identified by inspecting the squared prediction error (SPE) of each probe from the PCA model. Then, the outlying probes are reconstructed by the iterative optimization approach minimizing SPE. We used the public data presented from the gene chip project of human fibroblast cell. Through the application study, the proposed approach showed good performance for probe correction without removing faulty probes, which may be desirable in the viewpoint of the maximum use of data information.