• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.870-878
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• 2003

The maintenance of thermal equilibrium between the human body and its environment is one of the primary requirements for health, wellbeing and comfort. For the effective control of indoor thermal environment, thermostat or humidistat is used. But, it is not sufficient to control the indoor thermal environment using only one or two parameters as human response for the indoor comfortable environment. So an environmental thermal index is required for the control of indoor thermal environment effectively. In this study, a PMV sensor has been developed which has integrated from various kinds of individual sensors for temperature, humidity, air velocity, radiant temperature. After applying the PMV and PPD equation, it is possible to monitor the indoor thermal environment with the sensor system, which is adopted to the circuit for optimization according to the human response with the metabolic rate and activities. The measurement was carried out to verify the performance of the integrated sensor system in comparison with existing measurement system, the PMV meter. As a result, the possibility of applying the PMV sensor to control the indoor thermal environment simultaneously was examined.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.15-22
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• 2013

The purpose of this study is to analyse the effects of air conditioned room controlled by PMV(Predicted Mean Vote)for energy consumption and human comfort in office building. The 'EnergyPlus' was used for the evaluation of indoor thermal environment and energy consumption by the controls of room temperature and PMV. The result indicates that the PMV control could prove more profitable method for improvement of indoor thermal environment and energy conservation. Consequently, PMV control has a distinct advantage over most other control methods. An additional study is required to establish the various thermal comfort control for rooms on the basis of this work.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.311-318
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• 2013

This research examined the validity of whether the PMV index-based comfort- or uncomfort-indoor environments could be classified by the facial skin temperature, one of the physiological indicator for human. To do this, we distinguished between a comfort thermal environment and an uncomfort thermal environment using the PMV value, and then facial skin temperatures were measured in both environments. As a result, the facial skin temperature of occupants were different between the comfort- and uncomfort-indoor environments. It suggested that the facial skin temperature could be used in shaping the comfortable indoor environment based on the PMV index. While this result suggested the PMV index-based on comfort and uncomfort indoor environments could not be valid, because the facial skin temperature was lower in the uncomfort thermal environment than in the comfort thermal environment.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.55-62
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• 2014

In this study, a questionnaire was developed to assess error search and correction tasks, and an analysis was performed on the accuracy of the tasks and the time required for their completion in order to identify the effects of LED light source illumination on visual performance according to changes in a predicted mean vote(PMV) thermal environment. In addition, a subjective evaluation was performed by conducting a survey on the level of visual fatigue experienced during the tasks. In the experiment, four types of PMV thermal environments were established according to PMV values in the temperature range of $(17{\pm}1-29{\pm}1)^{\circ}C$ and the humidity range of $(50{\pm}5-60{\pm}5)%$, and the LED light source illumination was divided into three types: 400lx, 700lx, and 1000lx. The experimental results confirmed that the accuracy of the error search(LED p value=0.058, PMV*LED p value=0.083) and correction tasks and the time required(LED p value=0.004, PMV p value=0.000) for their completion were affected by changes in both the PMV thermal environment and the LED light source illumination, whereas a significant difference in visual fatigue was observed only in the PMV thermal environment(p value=0.003).

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.6
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• pp.624-632
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• 2016

Attention plays vital role either students academic performance in classroom or work performance of workers. This study was accomplished among elementary school students of elementary school classroom for two years. Three experiment cases were designed based on the Predicted Mean Vote (PMV) indexes. Thermal environment and PMV were directly monitored; Thermal Sensation Vote (TSV) and Comfort Sensation Vote (CSV) were analyzed based on survey data; and attention was analyzed for different comfort level using FAIR program. PMV, TSV and CSV were varied with the change in thermal environment and there was not noticeable gender influence on impact. The good correlation between thermal environment, PMV, TSV and CSV confirmed the impact of thermal environment on indoor comfort. There were different impacts on attention with comfort conditions. Academic attention of low attention group i.e. weak students, can be improved by providing the comfort environment. Thermal environment influences the comfort and the comfort influences the attention, it is possible to assess the impact of thermal environment on attention in further.

• Journal of the Korean housing association
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• v.14 no.3
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• pp.1-8
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• 2003

It is not sufficient to control the indoor thermal environment using only one or two parameters by itself as human response for the control of indoor thermal environment. So a proper environmental thermal index is required for the control of indoor thermal environment effectively. In this study, the physical environment was measured and analysed and the skin temperature of the subjects and their response were investigated to evaluate the optimum thermal comfort range for cooling season in an apartment house. As a result, the optimal temperature was 26.1$^{\circ}C$ and the temperature ranges which more than 80% responded as satisfactory were 24.1~28.$0^{\circ}C$, respectively. As the OT had most significant interrelation with the PMV, it is desirable to use the OT in evaluating the thermal environment during cooling. Also, the comfort range was concluded between OT 25.5~27.3$^{\circ}C$ by appointing the PMV of -0.5~0.5 as the optimum comfort condition. In addition, the Human responses were compared with calculated PMV, OT and MRT and the relationships are suggested in order to utilize to control indoor thermal environment.

• Land and Housing Review
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• v.1 no.1
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• pp.19-25
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• 2010

Thermal comfort provide satisfaction of thermal environment and affects productivity of occupants in residential building. However, temperature control can not provide the thermal comfort at all the time. because thermal comfort is influenced by many environmental variables such as temperature, relative humidity, air velocity, radiation temperature, activity level and clothing insulation. The purpose of this study is that predicted mean vote(PMV) index is used as control. And, Thermal comfort is evaluated both PMV control and temperature control by simulation. Each other cases were compared, in which set-point temperatures of $22^{\circ}C$ and $24^{\circ}C$ and, set-point PMV index through the respective heating season in the simulation. The results show that PMV control is better to maintain comfort state and save energy than temperature control.

• Journal of the Korean housing association
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• v.15 no.1
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• pp.25-32
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• 2004

The purpose of this study is to understand the indoor thermal environment in the earth brick wall building what is called a ecological Architecture. To investigate thermal performances of the earth brick walls, it measured indoor and outdoor air temperature, relative humidity, globe temperature and PMV in reference house. The result of this study were summarized as the followings; 1) When the outdoor average air temperature was $21.8^{\circ}$, livingroom was $24.9^{\circ}$, kitchen was $25.1^{\circ}$ and 2nd floor room was $25.6^{\circ}$ at 150 cm height from the floor. 2) Although the average outdoor relative humidity was 78%, the livingroom was 67.5%. 3) As the air temperature difference between at the top and bottom was $0.6^{\circ}$ in living room, this value was below 1 % of PPD by ASHRAE Handbook. 4) Predicted Mean Vote(PMV) by ISO-7730 was +0.41.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.69-77
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• 2015

The PMV regression analysis was conducted for this model based on a database of the PMV variables. PMV regression model simplification was completed through sensitivity and data analysis. The simplified PMV regression model's and Fanger PMV model was confirmed through MAE and RMSE. And the EMS in EnergyPlus was used to establish a simplified PMV regression analysis-based thermal comfort control. Also, the thermal comfort controls based on simplified PMV model and the Fanger PMV model were applied to the building model, it was confirmed that both controls met the thermal comfort range in more than 90% of cases during the air conditioning period.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.45-46
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• 2012