• Title/Summary/Keyword: Result Analysis and Evaluation

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Evaluation of MODIS-derived Evapotranspiration According to the Water Budget Analysis (물 수지 분석에 의한 MODIS 위성 기반의 증발산량 평가)

  • Lee, Yeongil;Lee, Junghun;Choi, Minha;Jung, Sungwon
    • Journal of Korea Water Resources Association
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    • v.48 no.10
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    • pp.831-843
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    • 2015
  • This study estimates MODIS-derived evapotranspiration data quality by revised RS-PM algorithm in Seolmacheon test basin. We used latent flux with eddy covariance method to evaluate MODIS-derived spatial evapotranspiration and gap-filled these data by three methods (FAO-PM, MDV and Kalman Filter) and to quantify daily evapotranspiration. Gap-filled daily evapotranspiration data was used to evaluate evapotranspiration computed by revised RS-PM algorithm derived MODIS satellite images. For the water budget analysis, we used soil moisture content that is quantified to average individual soil moisture rate observed by TDR (Time Domain Reflectometry) sensor at soil depth. The soil moisture variation is calculated in consideration from initial to final soil moisture content. According to the result of this study, evapotranspiration computed by revised RS-PM algorithm is very larger than eddy covariance data gap-filled by three methods. Also, water budget characteristics is not closed. We could analysis that MODIS-derived spatial evapotranspiration does not represent actual evapotranspiration in Seolmacheon.

Research on Index Configuration of Urban Growth Management -31 cities and Counties in Gyeonggi Province, Korea- (도시성장관리 지표설정에 관한 연구 -경기도 31개 시 군을 평가 대상으로-)

  • Jo, Jae-Kyung;Lee, Dae-Jong;An, Jae-Hong;Lee, Myeohg-Hum
    • The Journal of the Korea Contents Association
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    • v.14 no.10
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    • pp.754-775
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    • 2014
  • At the point of growth management, weighted values for the each index have been calculated by applying AHP method based on the interview. With calculated weighted values, an example assessment had been performed on Gyunggi area, a typical place where urban growth management is needed urgently, and intended to provide applicable implications by analyzing them when establishing the means of the urban growth management plans. The result of this research is presented in order of the weight values highest to lowest as below: 'preventing disordered urban sprawl', 'protecting taxpayers', 'promoting efficient urban development' and 'improving the quality of life'. When applied to Gyunggi area, the results are in similar patterns: 'preventing disordered urban sprawl (11 cities)', 'protecting taxpayers (11 cities)', 'improving the quality of life (5 cities)' and 'promoting efficient urban development (4 cities)'. To build the well-balanced urban growth management plans, two factors must be in consideration as well as with others, 'Improving quality of the life' and 'promoting efficient urban development'. Furthermore, the result of the index in this research can provide a guidance to local governments of provinces and cities to build their urban growth management plans in the future.

Evaluation of Information Representation Goodness-of-fit According to Protein Visualization Pattern (단백질 가시화 형태에 따른 정보표현적합도 평가)

  • Byeon, Jaehee;Choi, Yoo-Joo;Suh, Jung-Keun
    • Journal of Internet Computing and Services
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    • v.16 no.2
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    • pp.117-125
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    • 2015
  • The information about protein structure gives the clues for the function of protein. It is needed for the improvement for the efficacy and fast development of protein drugs. So, the studies visualizing the structure of protein effectively increase. Most studies of visualization focus on the structural prediction for protein or the improvement on the rendering speed. However, studies of information delivery depending on the form of protein visualization are very limited. The major objective of this study is to analyze the information representation goodness-of-fit for the patterns of the hybrid visualization with primary and secondary structures of protein. Those hybrid visualizations included the patterns which updated current representative visualization services, Chimera, PDB and Cn3D. Information factor to analyze information representation goodness-of-fit is assorted by protein primary structure, secondary protein structure, the location of amino acid and ratio information about protein secondary structure, based on the result of subject-analysis. Subject is the group of experts who are involved in protein drug development over 5 years. The result of this study shows the meaningful difference in the information representation goodness-of-fit by the patterns of hybrid visualization and proves the difference in the information by the pattern of visualization.

Empirical Leisure Environment Satisfaction Evaluation of Public Institution Employees in Innocity (혁신도시 이전 공공기관 종사자의 여가활동 만족도에 영향을 미치는 요인 분석 -광주·전남 공동혁신도시를 중심으로-)

  • Baek, Min;An, Hyung-Soon
    • The Journal of the Korea Contents Association
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    • v.19 no.2
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    • pp.368-378
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    • 2019
  • With respect to the growth and development of innocity from improvements in leisure environments, this research examines the factors that affect the level of satisfaction of innocity leisure environments to propose political implications. In order to do so, 43 leisure activities were chosen, and the level of importance of those activities to the residents prior to moving to the innocity was compared to the level of satisfaction the residents felt regarding the activities after moving. As a result, 13 activities, including literature attendance, had greater levels of satisfaction after moving than the levels of importance prior to moving. The rest (30) activities showed the opposite results. We deduced the factors that affect the level of satisfaction by performing logistic regression analysis on 3 dependent variables. As a result, the static and passive leisure activities had higher satisfactory levels, whereas the dynamic and active had lower satisfactory levels. Thus, innocity must develop culture facilities quickly, expand exercise facilities to support sports activties, and promote tourism by improving and networking with tourist attractions in order to improve future satisfactory levels of leisure activities.

The Effects of Reminiscence Therapy Using Mind Map to Improve Cognitive Function, Depression Index, Quality of Life for Elderly Women Suspected Of Dementia. (마인드맵을 활용한 회상치료가 여성 치매 의심 노인의 인지기능, 우울 지수 및 삶의 질에 미치는 영향)

  • Jang, Woo-hyuk;Son, Hyo-seong;Seo, Ye-ji;Youn, Su-jeong;Kim, Hyun-ji
    • Journal of Society of Occupational Therapy for the Aged and Dementia
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    • v.12 no.2
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    • pp.97-106
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    • 2018
  • Objective : The purpose of this study was to investigate the effects of reminiscence therapy using mind map to improve cognitive function, depression index, quality of life for old woman with dementia. Method : The study were 14 patients who were diagnosed with a woman suspected of dementia. They were randomly assigned to Study group(N=7) and control group(N=7). All patients received only to Study groups. reminiscence therapy using mind map was composed to 10 sessions, 40 minutes per sessions, 2 times a week, for 5 weeks. For result analysis, descriptive statistic, Wilcoxon signed rank test, and Mann-Whitney U test were used. The evaluation tools were Mini-Mental State Examination Korean Version (MMSE-K), Korean Version of Beck Depression Inventory (K-BDI), Korean Version of the World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). Result : There was a significant difference in cognitive function, depression index, and quality of life in the within group after intervention, and there was a significant difference in cognitive function in the between group comparison. Conclusion : According to the results of study, an easing effect was confirmed regarding reminiscence therapy using mind map for an old woman with dementia. using reminiscence therapy using mind map when applied to the improvement of cognitive function, depression index, quality of life.

Modified Pyramid Scene Parsing Network with Deep Learning based Multi Scale Attention (딥러닝 기반의 Multi Scale Attention을 적용한 개선된 Pyramid Scene Parsing Network)

  • Kim, Jun-Hyeok;Lee, Sang-Hun;Han, Hyun-Ho
    • Journal of the Korea Convergence Society
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    • v.12 no.11
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    • pp.45-51
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    • 2021
  • With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

Recommender Systems using Structural Hole and Collaborative Filtering (구조적 공백과 협업필터링을 이용한 추천시스템)

  • Kim, Mingun;Kim, Kyoung-Jae
    • Journal of Intelligence and Information Systems
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    • v.20 no.4
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    • pp.107-120
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    • 2014
  • This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

Evaluation of Green House Gases by Transportation Using Traffic Census Results from Changwon City (창원시 실제 교통량 자료를 이용한 도로수송부문 온실가스 배출량 평가)

  • Oh, Il-Hwan;Lee, Seung-Hoon;Cheong, Jang-Pyo;Kim, Tae-Hyeung;Seo, Jeoung-Yoon
    • Journal of Environmental Science International
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    • v.18 no.7
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    • pp.747-754
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    • 2009
  • In this study, which aims to estimate the volume of greenhouse gas emitted by road transportation vehicles in Changwon City, the emission rate was calculated on the basis of the actual traffic volume measured at major crossroads and compared with the results obtained from the methodology used to estimate the greenhouse gas emissions of road transportation provided in the IPCC 2006 GL guidelines (Tier 1, Tier 3). Analysis of the results of the comparison showed that the Tier 1 methodology, which was applied in the estimation of the rate of greenhouse gas emissions, carries a high probability of underestimation, while the Tier 3 methodology carries a relatively high probability of overestimation. Therefore, when considering the assignment of permissible rates of emission to local governments, the application of the methodology, i.e. whether one uses Tier 1 or Tier 3, may result in a large difference in the rate of allowable emissions. It is suggested that a method based on the actual volume of traffic would be the most reasonable one with regard to the development of a realistic plan.

Study on Unwed Mothers' Experiences of Participation in a Crisis Support Program (양육미혼모의 위기지원 프로그램 참여경험에 관한 질적연구)

  • Jung, Deok-Jin
    • The Journal of the Korea Contents Association
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    • v.19 no.4
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    • pp.241-255
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    • 2019
  • This purpose of this study was to explore the implication of the social work practice through the experiences of the users who participated in the crisis support program. To do this, In-depth interviews were carried out with 12 research participants. The data was analyzed by general qualitative research methods. As a result of analysis, prior to participating in the Triangle Project, users lost their will to live in a vicious cycle of life crisis. Through the participation of the service, they were able to receive the integrated support of 'pregnancy - childbirth - rearing'. These experiences ultimately led to the regeneration of the will to live. Based on the results of this study, we suggest practical and policy implications that can complement the limitation of Korean unwed mothers' support system.

Study on the Design Computing Model for SpO Extraction Algorithm on Pulse Oximetry (펄스 옥시메터의 산소포화도 추출 알고리즘을 위한 계산모델 설계에 관한 연구)

  • Kim, Yun-Yeong;Kim, Do-Cheol;Lee, Yun-Seon
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.25-32
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    • 1998
  • This paper is based on the design and analysis computing model of oxygen saturation with the pulse oximeter using the integral ratio of pulsating components. In our proposed algorithm. we modeled the transmitted optical signal in fingertip or earlobe to DC component $A_{dc}$ pulsating component $A_a\;Sinwt$, noise component $A_{noise}$ and etc.. To separate the pulsating components and DC components efficiently, we defined the signal average to DC components. Also we presented the way to eliminate the noise using integral ratio. To acquire a linearity of correlation graph for pulsating components ratios and non invasive oxygen saturation. we intensively observed on the oxygen saturations in the range of 75-100% in consideration of the error range of simulator. Also, for real time processing we experimented on changing the period of area calculating cycle from 1 to 6. The functional evaluation of the algorithm is compared with the method using the amplitude ratio of pulsating components frequently seen with pulse oximeter. The result was that our algorithm with 4 cycles of area calculating cycle which considered to be best fit by 1% to the existing method. Moreover r , the decision coefficient showing the correlation of regression graph with real data, proved better result of 0.985 than 0.970.

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