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A Comparative Study of Predictive Factors for Passing the National Physical Therapy Examination using Logistic Regression Analysis and Decision Tree Analysis

  • Kim, So Hyun;Cho, Sung Hyoun
    • Physical Therapy Rehabilitation Science
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    • v.11 no.3
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    • pp.285-295
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    • 2022
  • Objective: The purpose of this study is to use logistic regression and decision tree analysis to identify the factors that affect the success or failurein the national physical therapy examination; and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 76,727 subjects from the physical therapy national examination data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was pass or fail, and the input variables were gender, age, graduation status, and examination area. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In the logistic regression analysis, subjects in their 20s (Odds ratio, OR=1, reference), expected to graduate (OR=13.616, p<0.001) and from the examination area of Jeju-do (OR=3.135, p<0.001), had a high probability of passing. In the decision tree, the predictive factors for passing result had the greatest influence in the order of graduation status (x2=12366.843, p<0.001) and examination area (x2=312.446, p<0.001). Logistic regression analysis showed a specificity of 39.6% and sensitivity of 95.5%; while decision tree analysis showed a specificity of 45.8% and sensitivity of 94.7%. In classification accuracy, logistic regression and decision tree analysis showed 87.6% and 88.0% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. Additionally, whether actual test takers passed the national physical therapy examination could be determined, by applying the constructed prediction model and prediction rate.

Estimation of Carbon Stock in the Chir Pine (Pinus roxburghii Sarg.) Plantation Forest of Kathmandu Valley, Central Nepal

  • Sharma, Krishna Prasad;Bhatta, Suresh Prashad;Khatri, Ganga Bahadur;Pajiyar, Avinash;Joshi, Daya Krishna
    • Journal of Forest and Environmental Science
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    • v.36 no.1
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    • pp.37-46
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    • 2020
  • Vegetation carbon sequestration and regeneration are the two major parameters of forest research. In this study, we analyzed the vegetation carbon stock and regeneration of community-managed pine plantation of Kathmandu, central Nepal. Vegetation data were collected from 40 circular plots of 10 m radius (for the tree) and 1m radius (for seedling) applying a stratified random sampling and nested quadrat method. The carbon stock was estimated by Chave allometric model and estimated carbon stock was converted into CO2 equivalents. Density-diameter (d-d) curve was also prepared to check the regeneration status and stability of the plantation. A d-d curve indicates the good regeneration status of the forest with a stable population in each size class. Diversity of trees was very low, only two tree species Pinus roxburghii and Eucalyptus citriodora occurred in the sample plots. Pine was the dominant tree in terms of density, basal area, biomass, carbon stock and CO2 stock than the eucalyptus. The basal area, carbon stock and CO2 stock of forest was 33±1.0 ㎡ ha-1, 108±5.0 Mg ha-1 and 394±18 Mg ha-1, respectively. Seedling and tree density of the plantation was 4,965 ha-1 and 339 ha-1 respectively. The forest carbon stock showed a positive relationship with biomass, tree diameter, height and basal area but no relationship with tree density. Canopy cover and tree diameter have a negative effect on seedling density and regeneration. In conclusion, the community forest has a stable population in each size class, sequestering a significant amount of carbon and CO2 emitted from densely populated Kathmandu metro city as the forest biomass hence have a potentiality to mitigate the global climate change.

Decision Tree with Optimal Feature Selection for Bearing Fault Detection

  • Nguyen, Ngoc-Tu;Lee, Hong-Hee
    • Journal of Power Electronics
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    • v.8 no.1
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    • pp.101-107
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    • 2008
  • In this paper, the features extracted from vibration time signals are used to detect the bearing fault condition. The decision tree is applied to diagnose the bearing status, which has the benefits of being an expert system that is based on knowledge history and is simple to understand. This paper also suggests a genetic algorithm (GA) as a method to reduce the number of features. In order to show the potentials of this method in both aspects of accuracy and simplicity, the reduced-feature decision tree is compared with the non reduced-feature decision tree and the PCA-based decision tree.

A Study on the Distribution of Pinus densiflora in DMZ area (DMZ에서의 소나무 분포에 관한 연구)

  • 이일구
    • Journal of Plant Biology
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    • v.11 no.4
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    • pp.21-29
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    • 1968
  • It may be fully known that Korea is the main producing country of pine tree form the pan-Asian viewpoint of the geographical distribution of the pine tree. Through the study on the reason why the pine tree became a tree of the maximum cover degree in Korea and the observation of natural preservation status of all sorts of trees in the DMZ area for nearly 20 years after the Korean Armistice, it has come to know that almost all of the pine tree were banished. This phenomenon has been resulted by the ecological characteristics of the pine tree itself which has no sprouting power at all, war disasters, deforestation and incendiary fire that have been steadily occurred until now since the time of Armistice.

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Zero-tree Packetization without Additional Memory using BFS (BFS를 이용한 추가 메모리를 요구하지 않는 제로트리 압축기법)

  • 김충길;정기동
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.5_6
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    • pp.321-327
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    • 2004
  • SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

A customer credit Prediction Researched to Improve Credit Stability based on Artificial Intelligence

  • MUN, Ji-Hui;JUNG, Sang Woo
    • Korean Journal of Artificial Intelligence
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    • v.9 no.1
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    • pp.21-27
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    • 2021
  • In this Paper, Since the 1990s, Korea's credit card industry has steadily developed. As a result, various problems have arisen, such as careless customer information management and loans to low-credit customers. This, in turn, had a high delinquency rate across the card industry and a negative impact on the economy. Therefore, in this paper, based on Azure, we analyze and predict the delinquency and delinquency periods of credit loans according to gender, own car, property, number of children, education level, marital status, and employment status through linear regression analysis and enhanced decision tree algorithm. These predictions can consequently reduce the likelihood of reckless credit lending and issuance of credit cards, reducing the number of bad creditors and reducing the risk of banks. In addition, after classifying and dividing the customer base based on the predicted result, it can be used as a basis for reducing the risk of credit loans by developing a credit product suitable for each customer. The predicted result through Azure showed that when predicting with Linear Regression and Boosted Decision Tree algorithm, the Boosted Decision Tree algorithm made more accurate prediction. In addition, we intend to increase the accuracy of the analysis by assigning a number to each data in the future and predicting again.

A Study of Evaluating Streetscape Green Environments to Improve Urban Street Green Spaces - A Case Study of Jeonju City - (도시가로녹지의 개선을 위한 녹화환경평가 연구 -전주시를 대상으로-)

  • Jeong, Moon-Sun;Lim, Hyun-Jeong
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.22 no.3
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    • pp.55-71
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    • 2019
  • The purpose of this study is to propose an evaluation method to assess green environments of streetscapes to improve urban street green spaces in Jeonju City. Through a rapid assessment of urban street green spaces, we suggest an objective basis for expanding street green space as well as for adopting sustainable maintenance and improvement measures. We choose 12 sections of streetscapes (roads and sidewalks) to investigate existing street conditions which have more than four lanes and function as major road axes. Six large roads and six medium roads of Jeonju City center area are investigated as pilot assessment study sites. Site inventory checklists consist of environmental characteristics of streetscape, street tree status, and planting condition evaluation. Environmental characteristics of streetscapes are composed of physical and neighborhood factors. For instance, items for physical factors are types and width of road/sidewalks, paving materials, tree protection materials, and green strip. And surrounding landuse is a neighborhood factor. Assessment items for street tree status are street plant names (tree/shrubs/ground cover), size, and planting intervals. Planting condition evaluation items are tree shape, damage, canopy density, and planting types with existence of adjacent green space. Evaluation results are classified into three levels such as A(maintain or repair), B(greening enhancement), and C(structural improvement). In case of grade A, streetscapes have enough sidewalk width for maintaining green strip and a multi-layered planting(in large road only) with fairly good growing conditions of street trees. For grade B and C, streetscapes have a moderate level of sidewalk width with a single street tree planting. In addition, street tree growing conditions are appeared poor so that green enhancement or maintenance measures are needed. For median, only grade B and C are found as its planting growing foundations are very limited in space. As a result, acquiring enough sidewalk space is essential to enhance ecological quality of urban street green. Especially, it is necessary to have green strip with reasonable widths for plant growing conditions in sidewalks. In addition, we need to consider native species with multi-layer plant compositions while designing street green.

Current Status of Tree Height Estimation from Airborne LiDAR Data

  • Hwang, Se-Ran;Lee, Im-Pyeong
    • Korean Journal of Remote Sensing
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    • v.27 no.3
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    • pp.389-401
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    • 2011
  • Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.

Configuration of ACK Trees for Multicast Transport Protocols

  • Koh, Seok-Joo;Kim, Eun-Sook;Park, Ju-Young;Kang, Shin-Gak;Park, Ki-Shik;Park, Chee-Hang
    • ETRI Journal
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    • v.23 no.3
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    • pp.111-120
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    • 2001
  • For scalable multicast transport, one of the promising approaches is to employ a control tree known as acknowledgement (ACK) tree which can be used to convey information on reliability and session status from receivers to a root sender. The existing tree configuration has focused on a 'bottom-up' scheme in which ACK trees grow from leaf receivers toward a root sender. This paper proposes an alternative 'top-down' configuration where an ACK tree begins at the root sender and gradually expands by including non-tree nodes into the tree in a stepwise manner. The proposed scheme is simple and practical to implement along with multicast transport protocols. It is also employed as a tree configuration in the Enhanced Communications Transport Protocol, which has been standardized in the ITU-T and ISO/IEC JTC1. From experimental simulations, we see that the top-down scheme provides advantages over the existing bottom-up one in terms of the number of control messages required for tree configuration and the number of tree levels.

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A Comparison Study on the Survival Characteristics of Big Old Sophora japonica and Zelkova serrata Called 'Goe'

  • Rho, Jae-Hyun;Han, Sang Yup;Kim, Sang Beom
    • Journal of People, Plants, and Environment
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    • v.23 no.1
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    • pp.115-123
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    • 2020
  • With the aim of accumulating data that can be used to infer the basis for the acculturation of trees called 'Goe,' this study aims to identify the survival status of the pagoda and zelkova trees known as 'Goe' trees by comparing and analyzing the status of pagoda trees (Sophora japonica) and zelkova tree (Zelkova serrata) designated as a protected tree in Korea. The results of this study are as follows; Zelkova serrata designated as a protected tree grows the most, with 2,147 trees (29.4%) in Cheonnam, followed by Chungnam (16.5%) and Gyeongbuk (14.4%). However, Sophora japonica showed a different result from zelkova Serrata as the total number of 210 Sophora japonica (55.7%) in Gyeongbuk and Daegu is much larger than that of zelkova Serrata. As a result, in the Yeongnam region, where the Confucianism of Yeongnam was actively practiced, the existence of Sophora japonica is much larger than that of the Zelkova Serrata, which is not a coincidence, and it is difficult to determine it only based on their flora and planting distribution. Results of comparing protected trees of Sophora japonica and Zelkova Serrata showed that the average age of Zelkova Serrata wass 289 years, while that of Sophora japonica was 302 years, and that the average height of Zelkova Serrata wass 18 m, which is higher than the height of 16 m of Sophora japonica. The average diameter at breast height of Zelkova Serrata was 398 cm and that of Sophora japonica was 314 cm, which indicates that Zelkova Serrata is relatively big. Therefore, it can be assumed that Zelkova Serrata has a larger growth potential than Sophora japonica, and the possibility of growth as a big tree is also high, but it seems that the explanation that "they are relatively long-lived" is not clearly determined.