• Title/Summary/Keyword: Multi-Level Model

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The Effect of Settlement Inclusivity on Older People's Mental Health (정주환경 포용성이 고령층의 정신건강에 미치는 효과)

  • Lee, Sae Rom;Park, In Kwon
    • Journal of the Korean Regional Science Association
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    • v.36 no.4
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    • pp.3-23
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    • 2020
  • This study aims to conceptualize the settlement inclusivity for overcoming social exclusion and the decline in quality of life of older people and to examine its effects on their mental health. The concept of the settlement inclusivity for older people focuses on the immediate environment around the place where they live. We proposed two domains for the conceptual framework; social domain that provides opportunities for community cohesion; spatial domain that provides security of residential area and access to basic services within walking distance. The social domain was represented by participation and interdependence, while the spatial domain by security and accessibility in the settlement inclusivity. Zero-inflated negative binomial regression model was constructed with 2017 National Survey of Older Koreans data to analyze the factors influencing depressive symptoms of older adults. The empirical results demonstrate that increased level of neighborhood network and social participation is associated with a decrease in the number of depressive symptoms. In addition, higher satisfaction in neighborhood environment and good accessibility to public transport/stores are associated with fewer depressive symptoms. Finally, housing condition and home ownership have a moderating effect on the relationship between social network/participation and depressive symptoms level, whereas they have no direct effects on depressive symptoms. This study demonstrates multi-dimensionally and mutually significant associations between settlement inclusivity and depressive symptoms for older people providing implications for urban planning and policies to improve mental well-being of older population.

A Comparison of Pan-sharpening Algorithms for GK-2A Satellite Imagery (천리안위성 2A호 위성영상을 위한 영상융합기법의 비교평가)

  • Lee, Soobong;Choi, Jaewan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.4
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    • pp.275-292
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    • 2022
  • In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

The Moderating Effect of Gender in the Relationship between Physical Education and Adolescents' Internalizing and Externalizing Problem Behaviors: Using Multi-level Growth Modeling (체육시간과 청소년의 외현화·내재화 문제와의 관계에서 성별의 조절효과: 다층성장모형의 적용)

  • Taekho Lee;Seokyoung Lee;Yoonsun Han
    • Korean Journal of Culture and Social Issue
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    • v.21 no.2
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    • pp.131-158
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    • 2015
  • This study examined the relationship between physical education and externalizing(aggression) and internalizing(depression, social withdrawal) problem behaviors among adolescents. The moderating role of gender and time in the association between physical education and problem behavior was also identified. This study used data from the second, third, and fourth waves of the middle school student cohort (N=2,133, N=2,151, N=1,979) of the Korean Children-Youth Panel Survey(KCYPS). Main analyses involved multilevel growth model with interaction terms. The dependent variables were aggression, depression, and social withdrawal. The independent variables were gender and physical education (exercise hours) at school. The control variables were abuse, school-adjustment, annual household income and parents' highest level of education. The major longitudinal findings of this study are as follows: First, there was significant change according to the passage of time only in aggression among externalizing and internalizing problems. Second, gender differences exist in aggression and depression. Third, exercise hours of physical education had a negative relationship with internalizing problems. Fourth, there were no gender differences over time in both externalizing and internalizing problems. Fifth, the interaction between exercise hours of physical education and time was statistically significant for social withdrawal. Sixth, the interaction between exercise hours of physical education and gender was statistically significant for depression. The results of this study may become an academic basis for suggesting policy directions that promote increased exercise hours in physical education classes at school.

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Application of Machine Learning Algorithm and Remote-sensed Data to Estimate Forest Gross Primary Production at Multi-sites Level (산림 총일차생산량 예측의 공간적 확장을 위한 인공위성 자료와 기계학습 알고리즘의 활용)

  • Lee, Bora;Kim, Eunsook;Lim, Jong-Hwan;Kang, Minseok;Kim, Joon
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1117-1132
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    • 2019
  • Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

Genetic and Economic Analysis for the Relationship between Udder Health and Milk Production Traits in Friesian Cows

  • El-Awady, H.G.;Oudah, E.Z.M.
    • Asian-Australasian Journal of Animal Sciences
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    • v.24 no.11
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    • pp.1514-1524
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    • 2011
  • A total of 4,752 monthly lactation records of Friesian cows during the period from 2000 to 2005 were used to estimate genetic parameters and to determine the effect of udder health on milk production traits. Three milk production traits were studied: 305-day milk yield (305-dMY), 305-day fat yield (305-dFY) and 305-day protein yield (305-dPY). Four udder health traits were studied: somatic cell count (SCC), mastitis (MAST), udder health status (UDHS) with 10 categories and udder quarter infection (UDQI) with 7 categories. Mixed model least square analysis was used to estimate the fixed effects of month and year of calving and parity (P) on different studied traits. Sire and dam within sire were included in the model as random effects. Data were analyzed using Multi-trait Derivative Free Restricted Maximum Likelihood methodology (MTDFREML) to estimate genetic parameters. Unadjusted means of 305-dMY, 305-dFY, 305-dPY and SCC were 3,936, 121, 90 kg and 453,000 cells/ml, respectively. Increasing SCC from 300,000 to 2,000,000 cells/ml increased UDQI from 5.51 to 23.2%. Losses in monthly and lactationally milk yields per cow ranged from 17 to 93 and from 135 to 991 kg, respectively. The corresponding losses in monthly and lactationally milk yields return per cow at the same level of SCC ranged from 29.8 to 163 and from 236 to 1,734 Egyptian pounds, respectively. Heritability estimates of 305-dMY, 305-dFY, 305-dPY, SCC, MAST, UDHS, UDQI were 0.31${\pm}$0.4, 0.33${\pm}$0.03, 0.35${\pm}$0.05, 0.23${\pm}$0.02, 0.14${\pm}$0.02, 0.13${\pm}$0.03, and 0.09${\pm}$0.01, respectively. All milk production traits showed slightly unfavorable negative phenotypic and genetic correlations with SCC, MAST, UDHS and UDQI. There were positive and high genetic correlations between SCC and each of MAST (0.85${\pm}$0.7), UDHS (0.87${\pm}$0.10) and UDQI (0.77${\pm}$0.06) and between MAST and each of UDHS (0.91${\pm}$0.11) and UDQI (0.83${\pm}$0.07). It could be concluded that the economic losses from mastitis and high SCC are considerable. The high genetic correlation between SCC and clinical mastitis (CM) suggest that the selection for lower SCC would help to reduce or eliminate the undesirable correlated responses of clinical mastitis associated with selection for increasing milk yield. Additionally, it is recommended also that if direct information on under health traits is not available, measures of SCC can be inclusion in a selection criteria to improve the income from dairy cows.

The Effects of Management Consulting Quality and Consultant Capability on Entrepreneurial Firms' Performance (창업기업의 경영성과에 있어서 컨설팅품질과 컨설턴트역량의 영향에 대한 연구: 흡수능력과 자원역량의 매개효과를 중심으로)

  • Yoon, Ki-Chang
    • Journal of Distribution Science
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    • v.14 no.5
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    • pp.81-89
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    • 2016
  • Purpose - Prior researches have empirically focused on the effect of management consulting quality and consultant capability on entrepreneurial firms' performance. This study, however, focused on investigating the moderating role of absorptive capacity and resource capability between management consulting and entrepreneurial firms' performance. So, this study investigated the relationship among consulting quality, consultant capability, absorptive capacity, resource capability, and entrepreneurial firms' performance from the resource based view (RBV). Especially, this study focused on the mediating role of absorptive and resource capability in relational structure of entrepreneurial firms' dimensions. Research design, data, and methodology - In this study, research hypotheses and model are established by the prior researches from the fields of strategic management and entrepreneurial behavior. Concretely, H1~H4 are the relationship between consulting (consulting quality, consultant capability) and innovation (absorptive capacity, resource capability); H5 is the relationship between absorptive capacity and resource capability; and H6~H7 are the relationship between innovation (absorptive capacity, resource capability) and management performance. The data was collected 207 copies from entrepreneurial firms in South Korea. These firms were established in January 2014 and maintained by November 2015 in high-tech industry. The questionnaire was consisted of five dimensions; consulting quality, consultant capability, absorptive capacity, resource capability, and management performance. Each dimension measured multi items on a 5-point Likert scale. The hypotheses and research model are analyzed using structural equation modeling (SEM) with AMOS 22. Results - The results of this study are as follows. 1) Consulting quality significantly influenced on the absorptive capacity of entrepreneurial firms. 2) But, consultant capability did not influence on the absorptive capacity of entrepreneurial firms. 3) Consulting quality and consultant capability significantly influenced on the resource capability of entrepreneurial firms. 4) Absorptive capacity significantly influenced on the resource capability of entrepreneurial firms; 5) Absorptive capacity did not significantly influence on the management performance of entrepreneurial firms. 6) Resource capability, however, significantly influenced on the management performance of entrepreneurial firms. By these results, absorptive capacity of entrepreneurial firms had a mediating role partly among consulting quality, consultant capability, and management capability. The resource capability of entrepreneurial firms had a mediating role among consulting quality, consultant capability, and management capability, perfectly. Conclusions - According to this study, the high level of consulting quality and consultant capability may enforce the resource capability of entrepreneurial firms. It means, practically, that external knowledge is a driver for innovation, and then the innovation effects on the management performance of entrepreneurial firms. So, at the initial stage, the management consulting programs are very important to entrepreneurial firms and should be conceived as an essential element. This study may contribute to the advancement of academic in field of new start business, small business, or venture business based on resources, especially the role of absorptive capacity and resource capability between consulting programs and management performance. However, this study has some limitations. They are the measurement of consulting quality's items, cross-sectional research, and the limitation of concept and industry.

Design of Conveyor Structure for Integrated Post-Process in Multi-Injection Molding Machine Environments (다중 사출설비 환경에서 후가공 공정의 통합운영을 위한 컨베이어 구조 설계에 관한 연구)

  • Kim, Ki Bum
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.5
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    • pp.22-27
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    • 2020
  • In this paper, we study the methodology to improve productivity and transportation efficiency simultaneously in the manufacturing environment of injection plants which has multiple injection machines arranged in parallel. In general, the post-processes such as finishing are continuously arranged in the injection machine located in the lower level of the injection plants, and one or two workers in charge of post-processing are always arranged. Therefore injection plants have low productivity due to post-processing and the front of the injection machine is very crowded due to various logistics flows. In this paper, we propose the designing methodology of conveyor structure for integrating the post-processes arranged at each injection machine and transporting the injection products to the integrated post-process automatically. Specifically, we propose the models for computing the number of conveyor units into the integrated processes, and for finding the optimal combinations to connect each machines and the conveyors. The proposed model is for the total productivity improvement, which are productivity and transportation efficiency. By applying the proposed model to companies that produce injection parts used for the home appliances, we verify the applicability and the effect of improving productivity and transportation efficiency, which more than 40%.

Search of Characteristic for Dose Distribution Presented by Multi­isocentric Stereotactic Radiosurgical Plan Using Linear Accelerator (선형 가속기를 이용한 정위적 방사선 수술시 병소내 선량분포의 특성조사)

  • 최경식;오승종;이형구;최보영;전흥재;서태석
    • Progress in Medical Physics
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    • v.14 no.4
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    • pp.225-233
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    • 2003
  • The goal of a radiation treatment plan is to deliver a homogeneous dose to a target with minimal irradiation of the adjacent normal tissues. Dose uniformity is especially important for stereotactic radiosurgery using a linear accelerator. The dose uniformity and high dose delivery of a single spherical dose distribution exceed 70%. This also results with a similar stereotactic radiosurgical plan using a Gamma Knife. The dose distribution produced in a stereotactic radiosurgical plan using a Gamma Knife and Linear accelerator is spherical, and the application of the sphere packing arrangement in a real radiosurgical plan requires much time and skill. In this study, we found a characteristic of dose distribution with transformation of beam parameters that must be considered in a radiosurgical plan for effective radiosurgery. First, we assumed a cylinder type tumor model and a cube type tumor model. Secondly, the results of the tumor models were compared and analyzed with dose profiles and DVH_(Dose Volume Histogram) representative dose distribution. We found the optimal composition of beam parameters_(i.e. collimator size, number of isocenter, gap of isocenters etc.), which allowed the tumor models to be involved in the isodose curve at a high level. In conclusion, the characteristics found in this study are helpful for improving the effectiveness and speed of a radiosurgical plan for stereotactic radiosurgery.

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Assessing the Impact of Climate Change on Water Resources: Waimea Plains, New Zealand Case Example

  • Zemansky, Gil;Hong, Yoon-Seeok Timothy;Rose, Jennifer;Song, Sung-Ho;Thomas, Joseph
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.18-18
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    • 2011
  • Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

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Relationship between Delirium and Clinical Prognosis among Older Patients underwent Femur Fracture Surgery (대퇴부골절 후 수술환자의 섬망과 임상예후와의 관계)

  • Shim, Jae-Lan;Hwang, Seon-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.2
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    • pp.649-656
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    • 2016
  • This study was a retrospective examination to identify the association of postoperative delirium of the prognosis on following femur fracture surgery in elderly patients. Data was collected from the medical records of elderly patients (aged 65 years or older), who underwent femur fracture surgery from July 2010 to January 2014, following on 3-years in one university hospital. A total of 68 patients were involved. There were 31 cases (45.6%) with delirium and 37 cases (54.4%) without delirium. The participant's average age was 80.8 (patients with delirium), and 81.8 (delirium without patients) years of age, respectively, and most of them were female. There was no significant difference between the two groups. Taking five or more medications, serum creatinine level, and the total medical costs were significantly different in the delirium group and non-delirium group. In addition, the proportional hazard model of Cox to determine the predictors for the major clinical outcome occurring after surgery revealed delirium, five or more multi-drug use, and an experience of transfusion to be significant predictors. In conclusion, postoperative delirium in the elderly undergoing femur fracture surgery can have a negative clinical outcome in patients and caregivers. Therefore, a preoperative evaluation and management of the risk factors will be necessary.