• Journal of Energy Engineering
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• v.23 no.1
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• pp.40-45
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• 2014

The ventilation frequency of 0.5 times in residential facilities is applied mandatorily to the housing facilities containing more than 100 house units to improve the indoor air quality and create comfortable interior conditions and pleasantness for residents. The Building Energy Efficiency Rating system requires the implementation of leakage test based on ventilation frequency with the test results being reflected in the efficiency ratings, thereby stimulating the precise construction of the fittings in the periphery of windows and savings of energy that can be lost due to the infiltration air. The inspection results of the Building Energy Efficiency Rating at the site showed that the ventilation frequency was in the range between 0.63 and 0.71 and that the difference was found to have a significant effect on the amount of energy reduction. It is urgent to conduct the study on highly leakage-proof buildings and construction methods, along with the expansion of mandatory leakage-proof diagnosis of non-residential buildings, considering the mandatory ventilation frequency below 0.6 for passive houses under the European standards and the target set by Korea to introduce the passive house, the rigorous standard for energy efficiency in buildings and mitigating their ecological footprint, by 2017 and achieve the zero house by 2025.

• Journal of the Korean Home Economics Association
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• v.42 no.10 s.200
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• pp.91-104
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• 2004

The purpose of this study was to examine the differences of clothing microclimates and the subjective sensations according to age, gender and clothing weight for $19^{\circ}C$ air temperature. This study was done to gain fundamental data related to saving heating energy and to improve health through wearing underwear (long johns) in lower indoor temperatures. The subjects were divided into four groups (6 young males, 5 young females, 6 old males, 6 old females), and our experiment consisted of three conditions; the first condition was wearing long underwear in $19^{\circ}C$ air (19CUW condition); the second condition was without wearing long underwear in $19^{\circ}C$ air (19C condition); and the third condition was without wearing underwear in $24^{\circ}C$ air (24C condition). The experiment showed that the clothing microclimate temperature and humidity was the lowest in the 19C condition and the highest in the 24C condition irrespective of age and gender. The clothing microclimate in the 19CUW condition was not significantly distinguishable from the other conditions. Clothing microclimate temperature and humidity when the subjects responded thermal comfort was $28\~34^{\circ}C$ and $15\~40\%$RH without any significant difference according to age and gender. For the thermal sensation, the 24C condition was regarded as the warmest environment by the four groups, and the next preference was the 19CUW condition (p<0.001). Young females and old males showed a tendency to feel colder than young males and old females. For the thermal sensation of hands and feet, the young groups felt the warmest in the 24C condition and the coolest in the 19 C condition (p<0.001). However, old males felt neutral for the foot thermal sensation without any significant difference between the three conditions. Old females felt neutral for both the hands and feet thermal sensations without any significant difference between the three conditions. Thermal preference was the highest in the 24C condition for the 4 groups. In the 19CUW condition, for the thermal preference, most young males and females responded 'No change'; on the other hand, mea of the old responded 'Warmer'(p<0.001). It was the 24C condition that the 4 subject groups felt the most thermally comfortable. In the 19CUW condition, over $80\%$ of responses of each group expressed satisfaction and in the 19C condition, over $80\%$ of responses of each group, except young females, expressed satisfaction. In conclusion, in view of the clothing microclimate and subjective sensations, the 24C condition was the condition that gave subjects the least cold stress and the best subjective preference. However, the 19C condition and the 19CUW condition was not such a cold stress as to give healthy subjects a thermal burden.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.7
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• pp.705-711
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• 2008

In case of the domestic condition, as the initiating from Sumjin River Dam, total 14 units of multipurpose dams had been constructed in 1965 for the roles of flood control, waterpower generation, irrigation, water supply, industrial water supply. In the case of such multipurpose dam, it produces electric energy by converting the potential energy utilizing its head and quantity of the water into kinetic energy. However, in this process, since during the time when the turbine connected to the hydraulic turbine dynamo revolves and there occurs a loud noise, it brings the physical, mental bad influences to those people also a decline of an effective working efficiency. On such point of view, after selection of various 16 measurement points, this study has measured and analyzed the travelling characteristics of noise generated at the hydraulic turbine dynamo in Daechung Dam, and also has evaluated the degree of indoor noise using the evaluation index such as PSIL, NC. As the result of noise-evaluation, in case of Daechung Dam, since the noise damage grade appears very seriously at various spaces, it is considering that its soundproof measure would be necessitated keenly. Also, it is considered that such data could be utilized as the valuable material hereafter for establishment of an efficient noise-reduction countermeasure and a comfortable working environment for the hydraulic turbine dynamo plant.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.169-181
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• 2017

Objective: The aim of this study was to explore the influence of outdoor weather conditions on subjective responses during physical activity. Background: The largest difference between indoor and outdoor conditions is the existence of the sun. The heat load from the sun has an influence on the heat gain of the human body and the intense degree of solar radiation affected thermal comfort. Method: Thirty eight people were exposed to a range of climatic conditions in the UK. Weather in England does not have extremely hot and cold temperature, and the current study was conducted under warm (summer and autumn) and cool (spring and summer) climates. Measurements of the climate included air temperature, radiant temperature (including solar load), humidity and wind around the subjects. Subjective responses were taken and physiological measurements included internal body temperature, heart rate and sweat loss. Results: This study was conducted under four kinds of environmental conditions and the environmental measurement was performed in September, December, March, and June. The values for sensation, comfort, preference, and pleasantness about four conditions were from 'neutral' to 'warm', from 'not uncomfortable' to 'slightly comfortable', from 'slightly cooler' to 'slightly warmer', and from 'neither pleasant nor unpleasant' and 'slightly unpleasant', respectively. All subjective responses showed differences depending on air temperature and wind speed, and had correlations with air temperature and wind speed (p<0.05). However, subjective responses showed no differences depending on the radiant temperature. The combined effects of environmental parameters were showed on some subjective responses. The combined effects of air temperature and radiant temperature on thermal sensation and pleasantness were significant. The combined effects of metabolic rate with air temperature, wind speed and solar radiation respectively have influences on some subjective responses. In the case of the relationships among subjective responses, thermal sensation had significant correlations with all subjective responses. The largest relationship was shown between preference and thermal sensation but acceptance showed the lowest relationship with the other subjective responses. Conclusion: The ranges of air temperature, radiant temperature, wind speed and solar radiation were $6.7^{\circ}C$ to $24.7^{\circ}C$, $17.9^{\circ}C$ to $56.6^{\circ}C$, $0.84ms^{-1}$ to $2.4ms^{-1}$, and $123Wm^{-2}$ to $876Wm^{-2}$ respectively. Each of air temperature and wind speed had significant relationships with subjective responses. The combined effects of environmental parameters on subjective responses were shown. Each radiant temperature and solar radiation did not show any relationships with subjective responses but the combinations of each radiant temperature and solar radiation with other environmental parameters had influences on subjective responses. The combinations of metabolic rate with air temperature, wind speed and solar radiation respectively have influences on subjective responses although metabolic rate alone hardly made influences on them. There were also significant relationships among subjective responses, and pleasantness generally showed relatively high relationships with comfort, preference, acceptance and satisfaction. Application: Subjective responses might be utilized to predict thermal stress of human and the application products reflecting human subjective responses might apply to the different fields such as fashion technology, wearable devices, and environmental design considering human's response etc.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.31-37
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• 2021

As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.327-342
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• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.