• Title/Summary/Keyword: walking machine

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A Study on Infra-Technology of RCP Interaction System

  • Kim, Seung-Woo;Choe, Jae-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1121-1125
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    • 2004
  • The RT(Robot Technology) has been developed as the next generation of a future technology. According to the 2002 technical report from Mitsubishi R&D center, IT(Information Technology) and RT(Robotic Technology) fusion system will grow five times larger than the current IT market at the year 2015. Moreover, a recent IEEE report predicts that most people will have a robot in the next ten years. RCP(Robotic Cellular Phone), CP(Cellular Phone) having personal robot services, will be an intermediate hi-tech personal machine between one CP a person and one robot a person generations. RCP infra consists of $RCP^{Mobility}$, $RCP^{Interaction}$, $RCP^{Integration}$ technologies. For $RCP^{Mobility}$, human-friendly motion automation and personal service with walking and arming ability are developed. $RCP^{Interaction}$ ability is achieved by modeling an emotion-generating engine and $RCP^{Integration}$ that recognizes environmental and self conditions is developed. By joining intelligent algorithms and CP communication network with the three base modules, a RCP system is constructed. Especially, the RCP interaction system is really focused in this paper. The $RCP^{interaction}$(Robotic Cellular Phone for Interaction) is to be developed as an emotional model CP as shown in figure 1. $RCP^{interaction}$ refers to the sensitivity expression and the link technology of communication of the CP. It is interface technology between human and CP through various emotional models. The interactive emotion functions are designed through differing patterns of vibrator beat frequencies and a feeling system created by a smell injection switching control. As the music influences a person, one can feel a variety of emotion from the vibrator's beats, by converting musical chord frequencies into vibrator beat frequencies. So, this paper presents the definition, the basic theory and experiment results of the RCP interaction system. We confirm a good performance of the RCP interaction system through the experiment results.

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Present Condition and Preferences on Well-being Elements in Apartments (아파트의 웰빙요소 도입현황과 선호도)

  • Choi, Yoon-Jung
    • Journal of the Korean housing association
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    • v.18 no.1
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    • pp.61-72
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    • 2007
  • The purposes of this study were to summarize the concept of well-being and well-being apartment, to grasp the present condition of apartments which were introduced with well-being elements, and to find out the consumer preferences on well-being elements for apartment planning. Library and internet surveys were performed to summarize the concept of well-being and well-being apartment and to grasp the present condition of apartments which were introduced with well-being elements. Questionnaire survey was carried out from 2nd to 22nd of June 2005, to investigate the preferences on well-being elements for apartment planning. The respondents were 250 residents who are from thirties to fifties and living in urban area. As results, respondents think that 'living for health of body and mind' about concept of well-being and 'certificated apartments by green building rating system' or 'apartments introduced ecological factor' about concept of well-being apartment. They answered that 'yes' about 'Do you have intention to buy well-being apartment?'. The elements in aspect of complex planning having the preference were revealed that promenade for complex design, ecological garden or walking space for landscape design, outdoor exercise space for outdoor design, and security system for foundation equipment. The elements having the preference in aspect of public facilities were fitness room for sports & health facility and study room for cultural facility. The preferred elements in aspect of building and unit design were roof garden for building design, multi-functional room for unit floor plan, natural surface material for interior surface, ventilation system for indoor environment, control system for home automation, and food waste machine for home electronics.

Assessment of Physical Activity Pattern, Activity Coefficient, Basal Metabolic Rate and Daily Energy Expenditure in Female University Students (일부 여대생의 활동에너지 소비패턴, 활동계수, 기초대사량 및 에너지 소비량 평가)

  • Park, Yoonji;Kim, Jung Hee
    • Korean Journal of Community Nutrition
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    • v.18 no.1
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    • pp.45-54
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    • 2013
  • This study was conducted to investigate the physical activity pattern, activity coefficient, basal metabolic rate and energy expenditure of female university students. One-day activity diaries were collected from 95 female university students in Seoul. Body composition was measured by Inbody 720. Subjects spent 7 hr 8min on sleeping, 6 hr 31min on studying, 2 hr 50min on physiological activity, 2 hr 3min on leisure, 2 hr 2min on walking and jogging, 1 hr 58 min on commuting and 22min on house chores. The activity coefficient of these subjects was 1.58. The comparison of body composition of subjects according to PAL showed that body weight, body fat mass, arm circumference and arm muscle circumference of physically active group were significantly higher than those of the sedentary group. BMR calculated by Harris-Benedict (H-B) formula and DRI formula and BMR measured by Inbody 720 was 1375 kcal, 1306 kcal and 1209 kcal, respectively. Total energy expenditure (TEE) examined by one-day activity diaries and calculated by H-B formula and estimated energy requirement (EER) formula in DRI was 2102.1 kcal, 2184.4 kcal, and 2164.5 kcal, respectively. The Pearson correlation coefficient between TEE examined by one-day activity diaries and H-B TEE was 0.795 (p < 0.001) while that between TEE examined and DRI EER was 0.604 (p < 0.001). Overall data indicated that female university students seemed to be less active. Therefore it is recommended that universities develop good exercise programs for their students. Further studies are needed to generate more meaningful results with a larger sample size and using machine attached to the body, which are able to detect physical activity more accurately.

Accuracy evaluation of threshold rainfall impacting pedestrian using ROC (ROC를 이용한 보행에 영향을 미치는 한계강우량의 정확도 평가)

  • Choo, Kyungsu;Kang, Dongho;Kim, Byungsik
    • Journal of Korea Water Resources Association
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    • v.53 no.12
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    • pp.1173-1181
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    • 2020
  • Recently, as local heavy rains occur frequently in a short period of time, economic and social impacts are increasing beyond the simple primary damage. In advanced meteorologically advanced countries, realistic and reliable impact forecasts are conducted by analyzing socio-economic impacts, not information transmission as simple weather forecasts. In this paper, the degree of flooding was derived using the Spatial Runoff Assessment Tool (S-RAT) and FLO-2D models to calculate the threshold rainfall that can affect human walking, and the threshold rainfall of the concept of Grid to Grid (G2G) was calculated. In addition, although it was used a lot in the medical field in the past, a quantitative accuracy analysis was performed through the ROC analysis technique, which is widely used in natural phenomena such as drought or flood and machine learning. As a result of the analysis, the results of the time period similar to that of the actual and simulated immersion were obtained, and as a result of the ROC (Receiver Operating Characteristic) curve, the adequacy of the fair stage was secured with more than 0.7.

Application of Decision Tree to Classify Fall Risk Using Inertial Measurement Unit Sensor Data and Clinical Measurements

  • Junwoo Park;Jongwon Choi;Seyoung Lee;Kitaek Lim;Woochol Joseph Choi
    • Physical Therapy Korea
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    • v.30 no.2
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    • pp.102-109
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    • 2023
  • Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model's performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.

Development of a water quality prediction model for mineral springs in the metropolitan area using machine learning (머신러닝을 활용한 수도권 약수터 수질 예측 모델 개발)

  • Yeong-Woo Lim;Ji-Yeon Eom;Kee-Young Kwahk
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.307-325
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    • 2023
  • Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.