16주간의 실내조정운동프로그램이 지적장애학생의 신체구성과 건강체력 그리고 적응행동에 미치는 영향

정남규,박경은,한태경 한국스포츠학회 2020 한국스포츠학회지 Vol.18 No.2

본 연구는 D시 소재한 S학교의 지적장애학생을 대상으로 16주간 실내조정운동프로그램이 체신체구성과 체력, 적응행동에 미치는 영향을 규명하고자 하였다. 신체조성 변인 중 키는 신장계를 사용하였고 몸무게, 체질량지수, 체지방률 은 체성분분석기(Inbody 470, Biospace Co, Korea)를 사용하였다. 장애학생 건강체력검사(PAPS-D)를 실시하여 건강체력항목을 측정하였으며, 적응행동설문지(KISE-SAB)는 국립특수교육원에서 개발한 설문지를 사용하여 검사를 실시하였다. 측정은 16주간 실내조정운동프로그램 운동 전과 후를 동일하게 실시하였다. 실내조정운동프로그램은 주 3회 100분간, 중강도로 실시하였다(Borg scale;12∼13). 자료처리는 통계프로그램 SPSS를 이용하여 모든 변인의 평균 과 표준편차를 구하고 반복측정분산분석을 실시하였다. 통계적 유의수준은 a<.05로 설정하였다. 16주간 실내조정운동프 로그램을 실시한 결과, 신체조성변인 중 체지방률에서 시기×집단에 유의한 상호작용효과가 나타났으며(p=.020), 건강 체력변인 중 유연성(p=.001), 순발력(p=.001)에서 시기×집단에 유의한 상호작용효과가 나타났다. 적응행동변인 중 사회적 적응행동(p=.003)과 전체적 적응행동(p=.008)에서 시기×집단에 유의한 상호작용효과가 나타났다. 지적장애 학생들에게 실내조정운동프로그램을 실시한 결과 체력과 적응행동이 향상되어 신체적 능력과 함께 사회․정서적 안정감을 얻고 이로 인하여 일상생활 적응에 긍정적인 영향을 미치는 것을 알 수 있었다. The purpose of this study was to identify the effects of the 16 weeks indoor rowing exercise program on physical fitness and adaptive behavior on students with intellectual disabilities at special schools in D city. Body composition measured height, weight, body mass index, and body fat(Inbody 470, Biospace Co, Korea). Health fitness test(Physical Activity Promotion system for Students-Disability; PAPS-D) was conducted for students with disabilities, and adaptive behavior test used developed by the National Institute of Special Education (Korea Institute of Special Education–Scale of Adaptive Behavior; KISE-SAB). The measurement was conducted in the same way as the pre-and post-inspection of the indoor adjustment exercise program for 16 weeks. The indoor rowing program was conducted three times a week for 100 minutes and the intensity of the exercise was 12-13 using Borg scale. Data processing performed Two-way Repeated Measures ANOVA to obtain the mean and standard deviation of all variables and to analyze interactions using the statistical program. The 16 weeks indoor rowing exercise program showed significant interaction effects with the time × group at body fat percent, flexibility and explosive muscular strength. Significant interaction effects were found in the time × group of people in social and overall adaptive behavior. As a result of conducting an indoor rowing exercise program for students with intellectual disabilities, it was found that physical strength and adaptive behavior were improved to gain social and emotional stability along with their physical abilities, which positively affected their daily life adaptation.

실내에서 관수주기, 상토종류, 배수층의 유$\cdot$무에 따른 자생 가는쇠고사리의 생육반응

주진희,방광자,Ju, Jin-Hee,Bang, Kwang-Ja 한국조경학회 2005 韓國造景學會誌 Vol.32 No.6

본 연구는 실내에서의 관수주기, 상토종류, 배수층의 유$\cdot$무에 따른 가는쇠고사리의 생육을 살펴봄으로써 실내조경용 식물소재로 활용 및 관리 방법에 관한 자료를 제공하고자 수행하였다. 관수주기는 주 2회와 주 7회로 처리하였으며 배수층은 각 관수주기 처리별로 500mm 깊이의 마사토로 처리하였다. 상토는 자연토인 마사토:부엽토=1:1와 인공토인 피트모스:버미큘라이트:펄라이트=1:1:1을 사용하였다. 1. 2가지의 상토의 화학적인 특징을 분석한 결과 토양산도, 치환성 양이온함량은 피트모스:버미큘라이트:펄라이트=1:1:1 처리에서, 전기전도도, 유기물함량, 유효인산, 전질소함량, 양이온치환용량은 마사토:부엽토=1:1 처리에서 높은 수준을 보였다. 2. 관수주기에 있어 주 2회 관수처리가 주 7회 관수처리보다 가는쇠고사리의 생육과 실내 적응성이 높아 양치식물이 높은 수분환경을 선호함에도 불구하고 과도한 관수는 바람직하지 않는 것으로 사료된다. 3. 상토에 다른 가는쇠고사리의 생육과 실내 적응성은 마사토:부엽토=1:1 처리가 피트모스:버미큘라이트:펄라이트=1:1:1 처리에 비해 높았다. 그러나 실내에서는 자연토의 하중문제가 발생될 수 있으므로 추후 이를 대체할 수 있는 경량의 인공토양이 개발되어야 할 것이다. 4. 배추층의 유$\cdot$무에 의한 가는쇠고사리의 생육결과, 주 2회 관수처리에서는 배수층에 유$\cdot$무에 따른 생육적 차이가 크지 않았으나 주 7회 관수처리에서는 배수층이 있는 처리구가 생육과 실내 적응성이 높았다. It was aimed to promote as a material for interior landscape by validating Rumohra aristata, in an indoor environment, especially irrigation interval, medium composition and drainage at indoor. 1. The result of physico-chemical analysis of medium composition showed that porosity, pH and Ex-Ca, Ex-Mg and Ex-K were high with peatmoss: vermiculite: perlite(1:1:1) and water contents, organic matter content, total nitrogen and cation exchange capacity were high with sand: leaf mold(1:1). 2. Growth and indoor adaptability of Rumohra aristata were better with irrigation at 2 interval per week than irrigation at 7 interval per week regardless of drainage. 3. In the case of medium composition, of growth and indoor adaptability were higher with sud: leaf mold (1:1) than peatmoss: vermiculite: perlite(1:1:1). 4. Fronds fresh weight and dry weight decreased when irrigation interval increased and were higher with sand: leaf mold(1:1) than peatmoss: vermiculite: perlite(1:1:1) treatment.

Implementation of adaptive indoor comfort temperature control via embedded system for air-conditioning unit

Thananchai Leephakpreeda 대한기계학회 2012 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.26 No.1

Environmental control strategy via computerized implementation is one of the most efficient approaches to integrate new advanced knowledge in research of human thermal comfort to a mechanical air-conditioning unit. Recently, a new conceptual development in designing air-conditioning systems has indicated that the indoor comfort temperature strongly depends upon changes of the outdoor air temperature rather than to be a conventional fixed temperature set-point. The explanation is due to occupants’ adaptability of thermal comfort to a dynamic environment in terms of their clothing and/or activities while the outdoor temperature can be explicitly used as an ultimate indicator of such changes to empirical function of the indoor comfort temperature. In this paper, the first prototype embedded system is developed to emulate such an adaptive algorithm to numerically determine an indoor comfort temperature for a real-time control in an air-conditioning system. From a theoretical point of view, an adaptive comfort model together with grey prediction model is presented for exploring a practical application of a comfort temperature-based control for a single air-conditioned space, so as to show the viability of the proposed methodology by simulated results. The field studies by interview survey of satisfaction on thermal comfort within an air-conditioned reading room of a library confirm the viability of the proposed real-time computerized implementation of adaptive indoor comfort temperature via the embedded system for a conventional air-conditioning unit in practical uses.

실내 이산화탄소 농도 예측 기반 적응형 환기 제어 알고리즘 개발

최영재,배강우,정용기,문현준,문진우 한국생태환경건축학회 2023 한국생태환경건축학회 논문집 Vol.23 No.2

Purpose: This study aimed to develop an adaptive ventilation control algorithm for occupant-centric control (OCC). The control algorithm utilizes a real-time indoor carbon dioxide concentration prediction model that reflects occupant information and is continuously updated through daily learning. Method: The prediction model was developed using a long short-term memory (LSTM) learning algorithm based on data obtained from a living lab. The indoor CO2 concentration after 5 minutes was predicted through the data of the past 1 hour, and the prediction accuracy was evaluated with the test data. The adaptive ventilation control algorithm, which incorporates the prediction model, was then applied to the living lab for experiments to evaluate its real-time prediction accuracy, adaptability, and control performance. Result: As a result of the performance evaluation of the predictive model, the coefficient of variation of the root mean squared error (CVRMSE) was 1.78% and the R2 was 0.97. The adaptability evaluation over four days presented an improvement in CVRMSE from 1.78% to 1.13%, which is approximately 36.52% improvement from the initial performance. During the experiment with the adaptive ventilation control algorithm, the accuracy decreased slightly with a CVRMSE of 2.90% and R2 of 0.98, likely due to frequent ventilation control leading to large data variations. Despite short period of the indoor carbon dioxide concentration exceeding 1,000 ppm, the control was effective. According to the results, it is expected that providing comfortable indoor air quality at all times can be achieved by improving the optimal control cycle and supplementing data learning for various control modes in future research.

그린 스마트 스쿨을 위한 공간 적응형 자율주행 공기청정 로봇 설계 및 구현

오석주,이채형,이채규 한국인터넷방송통신학회 2022 한국인터넷방송통신학회 논문지 Vol.22 No.1

The effect of indoor air pollution on the human body is greater and more dangerous than outdoor air pollution. In general, a person stays indoors for a long time, and in a closed room, pollutants are continuously accumulated and the polluted air is better delivered to the lungs. Especially in the case of young children, it is very sensitive to indoor air and it is fatal. In addition, methods to reduce indoor air pollution, which cannot be ventilated with more frequent indoor activities and continuously increasing external fine dust due to Covid 19, are becoming more important. In order to improve the problems of the existing autonomous driving air purifying robot, this paper divided the map and Upper Confidence bounds applied to Trees(UCT) based algorithm to solve the problem of the autonomous driving robot not sterilizing a specific area or staying in one space continuously, and the problem of children who are vulnerable to indoor air pollution. We propose a space-adaptive autonomous driving air purifying robot for a green smart school that can be improved. 실내공기오염이 인체에 미치는 영향이 실외공기오염보다 더 크며 위험하다. 일반적으로 사람은 실내에 머무는시간이 길고, 밀폐된 실내는 오염물질이 지속적으로 쌓여 오염된 공기가 폐에 더 잘 전달된다. 특히 어린 아이들의 경우실내공기에 매우 민감하며 치명적이다. 이와 더불어 코로나19로 인한 더 잦은 실내활동과 지속적으로 증가하는 외부미세먼지와 함께 환기를 못하는 현재 실내공기오염을 줄이는 방법은 더욱 중요해지고 있다. 본 논문은 기존 자율주행공기청정 로봇의 문제점을 개선하고자 지도를 분할과 UCT(Upper Confidence bounds applied to Trees) 기반의알고리즘을 통해 자율주행 로봇이 구역을 살균하지 않거나 한곳에 계속 머무르는 문제점과 실내공기오염에 취약한 아이들의 문제를 개선할 수 있는 그린 스마트 스쿨을 위한 공간 적응형 자율주행 공기청정 로봇을 제안한다.

An adaptive hybrid filter for practical WiFi-based positioning systems

박남준,정석훈,한동수 한국통신학회 2015 ICT Express Vol.1 No.2

This paper proposes an adaptive hybrid filter for WiFi-based indoor positioning systems. The hybrid filter adopts the notion of particle filters within the prediction framework of the basic Kalman filter. Restricting the predicts of a moving object to a small number of particles on a way network, and replacing the Kalman gain with a dynamic weighting scheme are the key features of the hybrid filter. The adaptive hybrid filter significantly outperformed the basic Kalman filter, and a particle filter in the performance evaluation at three test places: a Library and N5 building, KAIST, Daejeon, and an E-mart mall, Seoul.

Adaptive neuro-fuzzy inference system based faulty sensor monitoring of indoor air quality in a subway station

유창규,류홍빈,Mingzhi Huang,김정태 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.3

A new faulty sensor monitoring method based on an adaptive neuro-fuzzy inference system (ANFIS) is proposed to improve the monitoring performance of indoor air quality (IAQ) in subway stations. To enhance network performance, a data preprocessing step for detecting outliers and treating missing data is implemented before building the monitoring models. A squared prediction error (SPE) monitoring index based on the ANFIS prediction model is proposed to detect sensor faults, where the confidence limit for the SPE index is determined by using the kernel density estimation method. The proposed monitoring approach is applied to detect four typical kinds of sensor faults that may happen in the indoor space of a subway. The prediction results in the subway system indicate that the prediction accuracy of an ANFIS structure with 15 clusters is superior to that of an appropriate artificial neural network structure. Specifically, when detecting one kind of complete failure fault that happened within the normal range, the detection performance of ANFIS-based SPE outperforms that of a traditional principal component analysis method. The developed sensor monitoring technique could work well for other kinds of sensor faults resulting from a noxious underground environment.

Adaptive Thermal Comfort of Planned Low-income Housing of a Developing Country: Case of Kigali, Rwanda

Amina Irakoze,Lee Young-A,Kim Kee Han 한국태양에너지학회 2021 한국태양에너지학회 논문집 Vol.41 No.3

Global warming is expected to raise the average temperature of the tropical region by up to 3-4°C in the next 70 years. Due to the vulnerable living conditions that are predominant in most developing countries in the region, this will dramatically affect the indoor thermal performance of exclusively, naturally ventilated buildings that form the majority of residential buildings in less-industrialized nations. In addition, the lack of knowledge about the built environment and thermal comfort design guidelines may significantly affect locals’ health and well-being, especially among low-income groups. This study evaluates the thermal performance of low-income housing that were constructed as a governmentsponsored project for urban revitalization in Kigali, Rwanda. Dynamic thermal simulations are carried out through EnergyPlus software using the DesignBuilder program as user interface. Annual discomfort hours and discomfort degree-days are calculated using the ASHRAE 55 adaptive comfort model. The results indicate poor thermal environmental conditions in this planned low-income housing structure. Indoor operative temperature is outside the adaptive comfort range for about 70% of time annually with 955.3 discomfort degree-days. The roof was found to be the key element causing indoor temperature to exceed the upper comfort temperature threshold, while wall material mostly influenced indoor temperature below the lower comfort temperature limit.

Variational Bayesian Adaptive Unscented Kalman Filter for RSSI-based Indoor Localization

Bo Yang,Xinchun Jia,Fuwen Yang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.3

Most existing localization schemes necessitate a priori statistical characteristic of measurement noise, which may be unrealistic in practical applications. This paper investigates the variational Bayesian adaptive unscented Kalman filtering (VBAUKF) for received signal strength indication (RSSI) based indoor localization under inaccurate process and measurement noise covariance matrices. First, an inaccurate and slowly varying measurement noise covariance matrix can be estimated by choosing appropriate conjugate prior distribution for an indoor localization model with inaccurate process and measurement noise covariance matrices. By choosing inverse Wishart priors distribution, the state, predicted error and measurement noise covariance matrices are inferred on each time separately. Second, a parameter optimization algorithm is designed to minimize the localization error of VBAUKF until it less than the threshold set in advance. Finally, experimental validation is presented to demonstrate the accuracy and effectiveness of the proposed filtering method for indoor localizaion.

Faulty Sensor Detection, Identification and Reconstruction of Indoor Air Quality Measurements in a Subway Station

Hongbin Liu,Mingzhi Huang,Iman Janghorban,Payam Ghorbannezhad,ChangKyoo Yoo 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

Indoor air quality (IAQ) is important in subway stations because it can influence the health and comfort of passengers significantly. To effectively monitor and control the IAQ in subway stations, several key air pollutants data were collected by the air sampler and tele-monitoring system. In this study, an air pollutant prediction model based an adaptive network-based fuzzy inference system (ANFIS) was used to detect sensor fault, and a structured residual approach with maximum sensitivity (SRAMS) method was used to identify and reconstruct sensor faults existing in subway system. When a sensor failure was detected, the faulty sensor was identified using the exponential weighted moving average filtered squared residual (FSR). Four identification indices, including the identification index based on FSR (IFSR), the identification index based on generalized likelihood ratio (IGLR), the identification index based on cumulative sum of residuals (IQsum), and the identification index based on cumulative variances index (IVsum) were used to assist in identifying sensor faults. The best reconstructed sensor value can be estimated based on a given sensor fault direction. The drifting sensor failure was tested and the effectiveness of the proposed sensor validation procedure was verified.