• Title/Summary/Keyword: Quantitative Data

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The Analysis Method of Integrated Logistic System using Evolution Strategies and Data Envelopment Analysis (진화전략과 DEA를 이용한 통합 물류 시스템 분석 방법)

  • Um In-Sup;Lee Hong-Chul;Kang Jeong-Yun
    • Journal of the Korea Society for Simulation
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    • v.13 no.4
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    • pp.17-29
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    • 2004
  • The focus of this study is to represent a methodology of analysis for integrated logistic system by means of the Evolution Strategies and Data Envelopment Analysis(DEA). The integrated logistic system is composed of AS/RS (Automated Storages and Retrieval System), AGVs(Automated Guided Vehicle System) and Conveyor System. We design the simulation alternatives with choosing the qualitative critical factors for the each subsystem. Evolution Strategies is used to optimize the quantitative critical factors and responses of each alternative. DEA is applied to measure the efficiency of the alternatives in order to select the optimal operation efficiency scheme. The method of analysis which combines Evolution Strategies with DEA can be used to analyze the qualitative and quantitative critical factors in the integrated logistic systems.

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Feature Analysis of Industrial Accidents in Manufacturing Business Using QUEST Algorithm (QUEST 알고리즘을 이용한 제조업에서의 산업재해 특성 분석)

  • Leem Young-Moon;Hwang Young-Seob
    • Journal of the Korea Safety Management & Science
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    • v.8 no.2
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    • pp.51-59
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    • 2006
  • So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.

Classification and Regression Tree Analysis for Molecular Descriptor Selection and Binding Affinities Prediction of Imidazobenzodiazepines in Quantitative Structure-Activity Relationship Studies

  • Atabati, Morteza;Zarei, Kobra;Abdinasab, Esmaeil
    • Bulletin of the Korean Chemical Society
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    • v.30 no.11
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    • pp.2717-2722
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    • 2009
  • The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

Orofacial Thermal Quantitative Sensory Testing (QST): A Study of Healthy Korean Women and Sex Difference

  • Ahn, Sung-Woo;Kim, Ki-Suk
    • Journal of Oral Medicine and Pain
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    • v.40 no.3
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    • pp.96-101
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    • 2015
  • Purpose: Thermal sensory test as an essential part of quantitative sensory testing (QST) has been recognized as a useful tool in the evaluation of the trigeminal nerve function. Normative data in the orofacial region have been reported but the data on differences in the test site, sex and ethnicity are still insufficient. Thus, this study aimed to investigate the normal range of orofacial thermal QST data in the healthy Korean women, and assess sex difference of thermal perception in the orofacial regions. Methods: Thermal QST was conducted on 20 healthy women participants (mean age, 26.4 years; range, 21 to 34 years). The thermal thresholds (cold detection threshold, CDT; warm detection threshold, WDT; cold pain threshold, CPT; and heat pain threshold, HPT) were measured bilaterally at the 5 trigeminal sites (the forehead, cheek, mentum, lower lip and tongue tip). The normative thermal thresholds of women in the orofacial region were evaluated using one-way ANOVA and compared with the previously reported data from age- and site-matched 30 healthy men (mean age, 26.1 years; range, 23 to 32 years) using two-way ANOVA. One experienced operator performed the tests of both sexes and all tests were done in the same condition except the time variability. Results: Women showed significant site differences for the CDT (p<0.001), WDT (p<0.001), and HPT (p=0.047) in the orofacial region. The CDT (p<0.001) and the CPT (p=0.007) presented significant sex difference unlike the WDT and the HPT. Conclusions: The thermal sensory evaluation in the orofacial region should be considered in the context of site and sex and the normative data in this study could be useful for assessment of the sensory abnormalities in the clinical setting.

Conditions and potentials of Korean history research based on 'big data' analysis: the beginning of 'digital history' ('빅데이터' 분석 기반 한국사 연구의 현황과 가능성: 디지털 역사학의 시작)

  • Lee, Sangkuk
    • The Korean Journal of Applied Statistics
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    • v.29 no.6
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    • pp.1007-1023
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    • 2016
  • This paper explores the conditions and potential of newly designed and tried methodology of big data analysis that apply to Korean history subject matter. In order to advance them, we need to pay more attention to quantitative analysis methodologies over pre-existing qualitative analysis. To obtain our new challenge, I propose 'digital history' methods along with associated disciplines such as linguistics and computer science, data science and statistics, and visualization techniques. As one example, I apply interdisciplinary convergence approaches to the principle and mechanism of elite reproduction during the Korean medieval age. I propose how to compensate for a lack of historical material by applying a semi-supervised learning method, how to create a database that utilizes text-mining techniques, how to analyze quantitative data with statistical methods, and how to indicate analytical outcomes with intuitive visualization.

Development of Day Fog Detection Algorithm Based on the Optical and Textural Characteristics Using Himawari-8 Data

  • Han, Ji-Hye;Suh, Myoung-Seok;Kim, So-Hyeong
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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    • pp.117-136
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    • 2019
  • In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).

A Study on the Quantitative Evaluation Method of Small-Scale Environmental Impact Assessment

  • Dong-Myung CHO;Ju-Yeon LEE;Woo-Taeg KWON
    • Journal of Wellbeing Management and Applied Psychology
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    • v.6 no.2
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    • pp.39-46
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    • 2023
  • Purpose: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Research design, data and methodology: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Results: As a result of the analysis of qualitative and quantitative factors, the arithmetic sum of the qualitative factors of the total six projects is 160, accounting for 80% of the total number of reduction measures, and the quantitative factors are 40, accounting for 20%. Among them, the number of qualitative reduction measures reached 97.4% for animal and plant items, and more than 90% for air quality, noise and vibration, and eco-friendly resource circulation items. Conclusions: Therefore, it is necessary to avoid establishing qualitative reduction measures and set quantitative measures as the basis, but to specify the specifications, size, and installation location related to the reduction measures, and to calculate the numerical reduction efficiency.

Quantitative Assessment of Input and Integrated Information in GIS-based Multi-source Spatial Data Integration: A Case Study for Mineral Potential Mapping

  • Kwon, Byung-Doo;Chi, Kwang-Hoon;Lee, Ki-Won;Park, No-Wook
    • Journal of the Korean earth science society
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    • v.25 no.1
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    • pp.10-21
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    • 2004
  • Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.

A Data Mining Approach for a Dynamic Development of an Ontology-Based Statistical Information System

  • Mohamed Hachem Kermani;Zizette Boufaida;Amel Lina Bensabbane;Besma Bourezg
    • Journal of Information Science Theory and Practice
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    • v.11 no.2
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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.