• Title/Summary/Keyword: Behavior Tree

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Analysis of the Characteristics of the Older Adults with Depression Using Data Mining Decision Tree Analysis (의사결정나무 분석법을 활용한 우울 노인의 특성 분석)

  • Park, Myonghwa;Choi, Sora;Shin, A Mi;Koo, Chul Hoi
    • Journal of Korean Academy of Nursing
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    • v.43 no.1
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    • pp.1-10
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    • 2013
  • Purpose: The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. Methods: A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. Results: The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. Conclusion: The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

Prediction Models of Conflict and Intimacy in Teacher-Child Relationships: Investigation of Child Variables Based on Decision Tree Analysis (교사-유아 관계의 갈등 및 친밀감에 대한 예측 모형: 의사결정나무분석을 적용한 유아변인의 탐색)

  • Shin, Yoolim
    • Korean Journal of Childcare and Education
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    • v.16 no.5
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    • pp.69-86
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    • 2020
  • Objective: The purpose of this research was to examine the prediction models of conflict and intimacy in teacher-child relationships based on decision tree analysis. Methods: The participants were 297 preschool children from ages three to five including 166 boys and 131 girls. Teacher-child relationships were measured by the Student-Teacher Relationship Scale(STRS). Physical aggression, relational aggression, social withdrawal, and prosocial behaviors were measured by teacher ratings. Moreover, ADHD-RS(Attentive Deficit Hyperactivity Disorder Rating Scale) was used to measure ADHD. The data was analyzed with decision tree analysis. Results: According to the prediction model for teacher-child conflict, the significant predictors were physical aggression and social withdrawal. According to the prediction model for teacher-child intimacy, the significant predictors were prosocial behaviors and relational aggression. However, children's age, gender and ADHD were not significant predictors. Conclusion/Implications: The findings suggest that social behaviors may be closely related with teacher-child relationships for preschool children. Based on the results of this study, intervention suggestions were made.

Natural Education Programs for Personalization of Environment : - Cases of Michigan 4-H Children's Garden, Binder Park Zoo, and Natural Education Programs of National Parks in the United States (자기환경화를 가능하게 하는 자연교육 프로그램 - 미국의 미시건 4-H 어린이 정원, 바인더 파크 동물원 및 국립공원 사례를 중심으로)

  • 이선경;김상윤;윤여창
    • Hwankyungkyoyuk
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    • v.11 no.2
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    • pp.102-117
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    • 1998
  • Responsible environmental behavior of Youths who will live in the 21C needs the ‘Personalization of Environment’, which means the process or the result of awareness to the non-personal environment as the personal environment to show the responsible environmental behaviors through the intended physical and psychological contacts to environment. This study intended to analyze various programs of national parks, zoo, children's garden and Project Learning Tree in the United States and to discuss the possibility of ‘personalization of environment’ and implication for environmental education of Korea. Literature review, field trips, personal interviews and internet searches were used to collect information and data. Programs of North Cascade National Park, Mt. Rainier National Park and 4-H Children's Garden in Michigan State University showed the cases of direct personalization of environment focusing on the direct contact with nature. The programs of Binder Park Zoo in Battle Creek and Project Learning Tree showed the possibilities of indirect personalization of environment forming meaningful relationships with nature through various indirect activities. It is suggested that various natural education programs in Unites States make nature and places meaningful for the people and it needs to be applied for the environmental education programs in Korea.

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Protection Switching Methods for Point-to-Multipoint Connections in Packet Transport Networks

  • Kim, Dae-Ub;Ryoo, Jeong-dong;Lee, Jong Hyun;Kim, Byung Chul;Lee, Jae Yong
    • ETRI Journal
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    • v.38 no.1
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    • pp.18-29
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    • 2016
  • In this paper, we discuss the issues of providing protection for point-to-multipoint connections in both Ethernet and MPLS-TP-based packet transport networks. We introduce two types of per-leaf protection-linear and ring. Neither of the two types requires that modifications to existing standards be made. Their performances can be improved by a collective signal fail mechanism proposed in this paper. In addition, two schemes - tree protection and hybrid protection - are newly proposed to reduce the service recovery time when a single failure leads to multiple signal fail events, which in turn places a significant amount of processing burden upon a root node. The behavior of the tree protection protocol is designed with minimal modifications to existing standards. The hybrid protection scheme is devised to maximize the benefits of per-leaf protection and tree protection. To observe how well each scheme achieves an efficient traffic recovery, we evaluate their performances using a test bed as well as computer simulation based on the formulae found in this paper.

Risk factors of alcohol use disorder in Korean adults based on the decision tree analysis (의사결정나무분석을 이용한 성인의 알코올사용장애 위험요인)

  • Mi Young Kwon;Ji In Kim
    • The Journal of Korean Society for School & Community Health Education
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    • v.24 no.1
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    • pp.47-59
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    • 2023
  • Objectives: The aim of this study was to identify risk factors of alcohol use disorder among Korean adults. Methods: Cross-sectional exploratory study based on data collected from Data from the 6th Korea National Health and Nutrition Examination Survey in 2015 were performed in this study. There were 3,248 participants who were 2,558 normal drinkers while 690 had alcohol use disorder. Decision tree analysis were used to exam socio-demographic and health-related factors to predict alcohol use disorder. Results: As a result of decision tree analysis, the predictive model for factors related to alcohol use disorder in Korean adults presented with 8 pathways. The significant predictors of alcohol use disorder were age, gender, smoking, marital status, and house income. Male smokers whose household income is 'high' or 'low' are most vulnerable to alcohol use disorders. Conclusions: This study indicates that need to consider health behavior and house income when we practice prevention policies and health education of alcohol use disorder.

A automatic construction technique of Robust Behavior Plan (강인 행동 계획의 자동 생성 방법)

  • Lee, Sang-Hyoung;Cha, Byung-Gun;Lee, Sang-Hoon;Suh, Il-Hong
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.929-930
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    • 2006
  • In this paper, we propose a planning algorithm which automatically generates robust behavior plans for service robots in the dynamically changing environments. The proposed method searches for paths to perform the given tasks in the physical space and the configuration space where tasks are described. And then, the characteristics of paths for successfully performed task are abstracted and generalized to build an ordered-tree structure. The resulting robust behavior plans guarantee that the given tasks are successfully performed. The validity of our method is tested by simulation work for a pushing-box task.

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A Study on the Insider Behavior Analysis Using Machine Learning for Detecting Information Leakage (정보 유출 탐지를 위한 머신 러닝 기반 내부자 행위 분석 연구)

  • Kauh, Janghyuk;Lee, Dongho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.2
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    • pp.1-11
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    • 2017
  • In this paper, we design and implement PADIL(Prediction And Detection of Information Leakage) system that predicts and detect information leakage behavior of insider by analyzing network traffic and applying a variety of machine learning methods. we defined the five-level information leakage model(Reconnaissance, Scanning, Access and Escalation, Exfiltration, Obfuscation) by referring to the cyber kill-chain model. In order to perform the machine learning for detecting information leakage, PADIL system extracts various features by analyzing the network traffic and extracts the behavioral features by comparing it with the personal profile information and extracts information leakage level features. We tested various machine learning methods and as a result, the DecisionTree algorithm showed excellent performance in information leakage detection and we showed that performance can be further improved by fine feature selection.

Scheduling Management Agent using Bayesian Network based on Location Awareness (베이지안 네트워크를 이용한 위치인식 기반 일정관리 에이전트)

  • Yeon, Sun-Jung;Hwang, Hye-Jeong;Lee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.712-717
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    • 2011
  • Recently, diverse schedule management agents are being researched for the efficient schedule management of smart devices users, but they remain at a confirmatory level. In order to efficiently manage user's schedules, execution of planned schedules should be monitored to help users properly execute their schedules, or feedback must be given so that when setting up new schedules, users can plan their schedule according to their schedule establishment patterns. This research proposes a schedule management agent that infers the user's behaviors by using acquired user context, and provides schedule related feedback depending on the user's behavior patterns, when users are executing their schedules or planning new schedules. For this, collected user context information is preprocessed and user's behavior is inferred by Bayesian network. Also, in order to provide feedbacks necessary for confirming the user's schedule execution and new schedule establishment, a context tree pattern matching method for the user's schedule, location and time contexts was applied, then verified with 6 weeks of user simulation in a mobile environment.

Cyclic testing of weak-axis steel moment connections

  • Lee, Kangmin;Li, Rui;Jung, Heetaek;Chen, Liuyi;Oh, Kyunghwan
    • Steel and Composite Structures
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    • v.15 no.5
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    • pp.507-518
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    • 2013
  • The seismic performance of six types of weak-axis steel moment connections was investigated through cyclic testing of six full-scale specimens. These weak-axis moment connections were the column-tree type, WUF-B type, FF-W type, WFP type, BFP-B type and DST type weak-axis connections. The testing results showed that each of these weak-axis connection types achieved excellent seismic performance, except the WFP and the WUF-B types. The WFP and WUF-B connections displayed poor seismic performance because a fracture appeared prematurely at the weld joint due to stress concentrations. The column-tree type connection showed the best seismic behavior such that the story drift ratio could reach 5%.

A Study on Phenomena of Watertree and Dielectric Breakdown in XLPE (XLPE의 수트리와 절연파괴 현상에 관한 연구)

  • Lee, Sung-Il;Ryu, Sung-Lim;Park, Il-Kyu;Lee, Ho-Sik
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2001.11b
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    • pp.262-265
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    • 2001
  • In order to investigate the water tree degradation behavior on XLPE cable, direct voltage of 200 to 800V has been applied to the material at $50^{\circ}C\sim100^{\circ}C$. and the water tree property has been correlated with voltage and temperature in this study. The leakage current was shown to increase as temperature increased and the Ohm's law was generally satisfied in this experiment though some experimental errors were found. The leakage current was shown to decrease and reach to the stable state with time. It was also shown that the time for the stabilization of leakage current was lessened as voltage increased

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