• Title/Summary/Keyword: Model Improvement

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Analysis of English Ability Improvement Effect through a Hybrid Model using Online Contents and Video Conferencing (온라인 컨텐츠 및 화상회의를 활용한 하이브리드 모델을 통한 영어 능력 향상 효과 분석)

  • Song, JaeShin;Jung, SungMoo;Lee, JaeMu;Kim, JaMee;Cha, HyunJin
    • The Journal of Korean Association of Computer Education
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    • v.12 no.3
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    • pp.31-40
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    • 2009
  • English education taken with native English speakers is very effective, but it is hard to obtain English education with native English speakers in rural schools. In this study, therefore, we supported English education with on-line content and video conferencing with native English speakers. This study worked with one hundred fifty students from six elementary and middle schools equally distributed by city size over three months. This study performed experimental research by T-test comparing of pre- and post-tests of the hybrid model. In our results, the upper group showed greater improvement in understanding while the lower group showed more improvement in writing. In addition, the lower group showed more improvement than the upper group in overall English accomplishment.

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Use of the Extended Kalman Filter for the Real-Time Quality Improvement of Runoff Data: 1. Algorithm Construction and Application to One Station (확장 칼만 필터를 이용한 유량자료의 실시간 품질향상: 1. 알고리즘 구축 및 단일지점에의 적용)

  • Yoo, Chul-Sang;Hwang, Jung-Ho;Kim, Jung-Ho
    • Journal of Korea Water Resources Association
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    • v.45 no.7
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    • pp.697-711
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    • 2012
  • This study applied the extended Kalman Filter, a data assimilation method, for the real-time quality improvement of runoff measurements. The state-space model of the extended Kalman Filter was composed of a rainfall-runoff model and the runoff measurement. This study divided the purpose of quality improvement of runoff measurements into two; one is to suppress the abnormally high variation of dam inflow data, and the other to amend the missing or erroneous measurements. For each case, a proper model of extended Kalman Filter was proposed, and the main difference between two models is whether only the variation is considered or both the bias and variation are considered in the estimation of covariance function. This study was applied to the Chungju Dam Basin to confirm the proposed models were effectively worked to improve the quality of both the dam inflow data and the runoff measurements with some missing and erroneous part.

A Study on the Improvement of Maritime Traffic Safety Assessment Scheme by applying Metaevaluation Model (메타평가 모형 적용을 통한 해상교통안전진단제도 개선방안에 관한 연구)

  • Cho, Ik-Soon;Cho, Kyung-Min
    • Journal of Navigation and Port Research
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    • v.37 no.4
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    • pp.383-390
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    • 2013
  • After forming a institutional framework with specified in Maritime Safety Law(ex. Maritime Traffic Safety Law) on May 27th, 2009, The efforts for improving 'Maritime Traffic Safety Assessment Scheme(MTSA scheme)' have continued to the present. But there's no review with the comprehensive and systematic approach for proceeding acceleration step of MTSA scheme. At this point, this study analyzed current status and derived improvement measures using by 'PIP'OU model' which was designed for the comprehensive analysis in accordance with metaevaluation theory, like as question investigation and etc. Consequently, it mainly needs to improve 'Assessment Plan' domain and minimized the difference in views between concerned parties. This study is expected to be used to develop systematic maritime policy by proposing the order of priority in improvement matters.

Portfolio Decision Model based on the Strategic Adjustment Capacity: A Bionic Perspective on Bird Predation and Firm Competition

  • Mao, Chao;Chen, Shou;Liu, Duan
    • Journal of Distribution Science
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    • v.13 no.1
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    • pp.7-18
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    • 2015
  • Purpose - This study integrates a corporate competition system with a bird predation system to examine how organizational strategic adjustment capacity influences firm performance. By proving the prominent effects on performance, a financial vector is constructed to represent corporate strategic adjustment results, and an operation capacity vector is constructed, which can be categorized as a parameter for locating birds. All these works help us to propose a new method of investment, the portfolio decision model based on the strategic adjustment capacity. Research design, data, and methodology - Strategic adjustment capacity can be decomposed into three aspects: the organizational learning capacity from the top firms, the extent to which firms maintainor rely on the best operational capacity vector in history, and the ability to eliminate the disadvantages or retain the advantages of the operation capacity vector from the previous year. The method of solving cyclic equations is designed to evaluate strategic adjustment. Firms manufacturing specialized equipment are chosen to test the effects of the strategic adjustment capacity on three aspects of firm performance. Results - There is a positive correlation between the capacity to learn from the best firms and performance improvement. The relationship between the dependence or maintenance of a firm's advantages and performance improvement is a U-shape curve, and there is no significant effect of inertial control on performance improvement. Conclusions - A firm's competition system is a sophisticated adaptation, and competitive advantage and performance can be investigated based on the principles of competition in nature.

Research on Deep Learning Performance Improvement for Similar Image Classification (유사 이미지 분류를 위한 딥 러닝 성능 향상 기법 연구)

  • Lim, Dong-Jin;Kim, Taehong
    • The Journal of the Korea Contents Association
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    • v.21 no.8
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    • pp.1-9
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    • 2021
  • Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

Abstraction of Models with State Projections In Model Checking (모델 체킹에서 상태 투영을 이용한 모델의 추상화)

  • Kwon, Gi-Hwon
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1295-1300
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    • 2004
  • Although model checking has gained its popularity as one of the most effective approaches to the formal verification, it has to deal with the state explosion problem to be widely used in industry. In order to mitigate the problem, this paper proposes an ion technique to obtain a reduced model M' from a given original model M. Our technique Identifies the set of necessary variables for model checking and projects the state space onto them. The model M' is smaller in both size and behavior than the original model M, written M'$\leq$M. Since the result of reachability analysis with M' is preserved in M, we can do reachability analysis with model checking using M' instead of M. The abstraction technique is applied to Push Push games, and two model checkers - Cadence SMV and NuSMV - are used to solve the games. As a result, most of unsolved games with the usual model checking are solved with the ion technique. In addition, ion shows that there is much of time and space improvement. With Cadence SMV, there is 87% time improvement and 79% space one. And there is 83% time improvement and 56% space one with NuSMV.

The Effects of Personalized Residential Environment Improvement on Occupational Performance Satisfaction and Activities of Daily Living : Case Studies in Stroke Patients (개인맞춤형 주거환경개선이 작업수행만족도 및 일상생활활동에 미치는 효과 : 뇌졸중 환자를 대상으로 한 사례연구)

  • Kim, Minho;Park, Sungho
    • Journal of The Korean Society of Integrative Medicine
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    • v.3 no.1
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    • pp.41-51
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    • 2015
  • Purpose: The purpose of this study was to investigate the effects of personalized residential environment improvement on occupational performance satisfaction and activities of daily living(ADL) in stroke patients, and desire to use as the basis for presenting an effective method for improving the residential environment of the disabled patients. Method: This study has been carried out with 3 stroke patients undergoing therapy for rehabilitation at the S hospital from August 2014 to January 2015. Residential environment improvement was conducted based on the desired space. Occupational performance, satisfaction and ADL assessed by modified COPM, K-MBI. Intervention has provided grab bar and aids fit to the environment of each person. Result: After residential environment improvement, ADL score was improved, but improved scores for specific items only. In occupational performance and satisfaction, there was a significant difference. Conclusion: The results of this study were to find out that there is a positive effect of personalized residential environment improvement on occupational performance satisfaction and activities of daily living in stroke patients, could be used as a basis for presenting an effective way to residential environment improvement of the disabled patients.

Improving the Performance of Risk-adjusted Mortality Modeling for Colorectal Cancer Surgery by Combining Claims Data and Clinical Data

  • Jang, Won Mo;Park, Jae-Hyun;Park, Jong-Hyock;Oh, Jae Hwan;Kim, Yoon
    • Journal of Preventive Medicine and Public Health
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    • v.46 no.2
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    • pp.74-81
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    • 2013
  • Objectives: The objective of this study was to evaluate the performance of risk-adjusted mortality models for colorectal cancer surgery. Methods: We investigated patients (n=652) who had undergone colorectal cancer surgery (colectomy, colectomy of the rectum and sigmoid colon, total colectomy, total proctectomy) at five teaching hospitals during 2008. Mortality was defined as 30-day or in-hospital surgical mortality. Risk-adjusted mortality models were constructed using claims data (basic model) with the addition of TNM staging (TNM model), physiological data (physiological model), surgical data (surgical model), or all clinical data (composite model). Multiple logistic regression analysis was performed to develop the risk-adjustment models. To compare the performance of the models, both c-statistics using Hanley-McNeil pair-wise testing and the ratio of the observed to the expected mortality within quartiles of mortality risk were evaluated to assess the abilities of discrimination and calibration. Results: The physiological model (c=0.92), surgical model (c=0.92), and composite model (c=0.93) displayed a similar improvement in discrimination, whereas the TNM model (c=0.87) displayed little improvement over the basic model (c=0.86). The discriminatory power of the models did not differ by the Hanley-McNeil test (p>0.05). Within each quartile of mortality, the composite and surgical models displayed an expected mortality ratio close to 1. Conclusions: The addition of clinical data to claims data efficiently enhances the performance of the risk-adjusted postoperative mortality models in colorectal cancer surgery. We recommended that the performance of models should be evaluated through both discrimination and calibration.

Development and Evaluation of Urban Canopy Model Based on Unified Model Input Data Using Urban Building Information Data in Seoul (서울 건물정보 자료를 활용한 UM 기반의 도시캐노피 모델 입력자료 구축 및 평가)

  • Kim, Do-Hyoung;Hong, Seon-Ok;Byon, Jae-Yong;Park, HyangSuk;Ha, Jong-Chul
    • Atmosphere
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    • v.29 no.4
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    • pp.417-427
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    • 2019
  • The purpose of this study is to build urban canopy model (Met Office Reading Urban Surface Exchange Scheme, MORUSES) based to Unified Model (UM) by using urban building information data in Seoul, and then to compare the improving urban canopy model simulation result with that of Seoul Automatic Weather Station (AWS) observation site data. UM-MORUSES is based on building information database in London, we performed a sensitivity experiment of UM-MOURSES model using urban building information database in Seoul. Geographic Information System (GIS) analysis of 1.5 km resolution Seoul building data is applied instead of London building information data. Frontal-area index and planar-area index of Seoul are used to calculate building height. The height of the highest building in Seoul is 40m, showing high in Yeoido-gu, Gangnam-gu and Jamsil-gu areas. The street aspect ratio is high in Gangnam-gu, and the repetition rate of buildings is lower in Eunpyeong-gu and Gangbuk-gu. UM-MORUSES model is improved to consider the building geometry parameter in Seoul. It is noticed that the Root Mean Square Error (RMSE) of wind speed is decreases from 0.8 to 0.6 m s-1 by 25 number AWS in Seoul. The surface air temperature forecast tends to underestimate in pre-improvement model, while it is improved at night time by UM-MORUSES model. This study shows that the post-improvement UM-MORUSES model can provide detailed Seoul building information data and accurate surface air temperature and wind speed in urban region.

Set-Up model for the silicon steel cold rolling mill

  • Kim, Sang-Kyun;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1323-1326
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    • 2003
  • In this paper, we propose set-up model of silicon steel cold rolling mill. Until now, the working of Silicon Steel is operated using the look-up table value of roll force which a field operator finds by making good use of his experience. Therefore, the standardization of data and an improvement of the quality on product are very difficult. So we establish neural model using field data of various kinds of coil at each pass.

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