• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.9
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• pp.733-737
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• 2003

The purpose of this study is to analyze the particle removal characteristics of a commercial air cleaner based on the electrostatic precipitator. The air cleaner consists of a positive corona precharger to precharge particles and a collector to remove the charged particles. The test for particle removal efficiency is conducted with tobacco smoke particles of 1.27${\mu}{\textrm}{m}$ in mass median diameter. The result of one-pass filtration test shows that the filtration efficiency is more than 90% for the particles larger than 2.5 Um, while the efficiency for the particles of 0.5～1.0${\mu}{\textrm}{m}$ in case of 4.18 CMM is 70%. For the test room of 5,800${\times}$3,400${\times}$2,600㎣, the concentration of tobacco smoke particles decreases up to 30% of initial values within 30 minutes due to natural reduction and up to 90% of initial values within 30 minutes with the air cleaner operation.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1215-1220
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• 2019

Currently, each farm bears both the outbreak of foot-and-mouth disease and the damage caused by AI. In addition, complaints about odors in the livestock industry are constantly being recovered and are expected to occur in the future. The purpose of this study is to improve the indoor air quality of enclosed facilities such as barns, houses, pigsty, and etc. This paper develops low-temperature plasma waste heat ventilation system to be installed in ventilation unit location and standardizes heat exchange element, low-temperature plasma lamp, and ballast for enhanced air cleaning function. In addition, this study intends to develop a new control system so that the farmers can connect with existing weather systems, flow fans, and other facility equipment by incorporating ICT.

• Membrane Journal
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• v.27 no.4
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• pp.336-343
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• 2017

These days, the quality of indoor air is a very important concept for modern people who have lived in building and is a matter of new thinking. The quality is determined by the temperature and humidity of indoor air. In addition, there is a disadvantage in that energy consumption is severe for indoor air improvement. Therefore, researches on methods to solve such problems using total heat exchange have been actively conducted. So, in this study, aminated poly(styrene-ethylene-butylene-styrene) polymers were synthesized by introducing a hydrophilic substituent, ammonium, into main chain and the properties of synthesized polymers were evaluated. The synthesis was carried out through chloromethylation and amination reactions to introduce ammonium into main chain. As a result, the water uptake and the ion exchange capacity of the synthesized polymers increased as the content of the reaction reagent solution increased. It was confirmed that the important data at the total heat exchange membrane, water vapor transmission rate also increased according to temperature, equivalent.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.1
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• pp.117-123
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• 2022

Recently, due to COV ID-19, many people are spending most of their time indoors. So, there is a rising interest on the indoor air quality in the field of building construction. The main sources for the indoor air pollution are human indoors activity, building materials, living supplies and the polluted air from outdoor. The Korean government has designated 17 indoor air pollutants including fine dust, total airborne bacteria, fungi and carbon dioxide, etc.. Most people are always exposed to assorted bacteria and molds in our daily life, because indoor environment for human, moderate temperature are humidity, it is favourable to the growth of most of bacteria and fungi. Pine needles have an antibacterial effect against bacteria and fungi. In this study, the antibacterial activity against bacteria and fungi was tested by cement matrix using pine needle extract. As a result, the cement matrix using pine needle extract showed antibacterial activities against bacteria, but in the case of fungi, it did not show antifungal activity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.140-145
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• 2022

In an advanced modern society, among air pollutants caused by urban industrialization and public transportation, fine dust flows into indoors from the outdoors. The fine dust meter used indoors provides limited information and measures the pollution level differently, so there is a problem that users cannot monitor and monitor the data they want. To solve this problem, in this paper, indoor air quality data fine dust and ultra-fine dust (PM1.0, PM2.5, PM10), VOC (Volatile Organic Compounds) and PIR (Passive Infrared Sensor) are used to measure fine dust. and a monitoring system were designed and implemented. We propose a fine dust meter and monitoring system that is installed in a designated area to measure fine dust in real time, collects, stores, and visualizes data through App Engine of Google Cloud Platform and provides it to users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.389-392
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• 2010

The problem for the air pollution in the office or the indoor except a specific working area is the continuously issue since the human beings have lived in the dwelling facilities. Measures for that problem are urgently needed. It's possible to solve for the freshair of outside with enough ventilation but that is the awkward situation to be managed by person. It's feasible to supervison and control easily if you use to sensor network under the network. It works out to sense, storage, process, deliver every kind of appliances and environmental information from the stucktags and sensors. And it is possible to utilize to measure and monitor about the place of environmental pollution which is difficult for human to install. It's studied constantly since it be able to compose easily more subminiature, low-power, low-cost than previous one. And also it spotlights an important field of study, graft the green IT and IT of which the environment and IT unite stragically onto the Network. This study compose a IAQM(Indoor Air Quality Management) under the network, suggest the application of supervision and control.

• Journal of Food Hygiene and Safety
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• v.36 no.6
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• pp.520-527
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• 2021

In this study, toxin gene and antibiotic resistance of food poisoning strains isolated from indoor air in the cafeteria were analyzed to prevent food poisoning. Staphylococcus aureus (16 strains) and Bacillus cereus (37 strains) isolated from indoor air in child care center were tested. The toxin genes of S. aureus and B. cereus were detected by PCR assay. The antimicrobial susceptibility test followed the disc diffusion method described by the Clinical and Laboratory Standard Institute. The seg and sei toxin genes were detected in 11 of 16 S. aureus strains (68.6%). The nheA and nheB toxin genes were detected in 37 B. cereus strains. In this study, a total of 12 toxin gene patterns of B. cereus were found, among which the nheA-nheB-nheC toxin gene was found to be the most frequent pattern. The result of the antimicrobial susceptibility test of S. aureus revealed 93.8% and 87.5% resistance to ampicillin and penicillin antibiotics, but methicillin resistance S. aureus and vancomycin resistance S. aureus were not detected. All 37 B. cereus tested in this study were resistant to ampicillin and penicillin antibiotics. Based on the result of this study, it was judged that regular ventilation and air quality management were necessary to prevent food poisoning caused by S. aureus and B. cereus contaminated in the indoor air of child care centers.

• Journal of Environmental Impact Assessment
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• v.30 no.6
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• pp.380-392
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• 2021

An indoor air quality index for school classrooms based on the Hazard Quotient (HQ) was developed in this study. The current index (IAQI-S) covered PM₁₀, PM_2.5, and CO₂, and breakpoints of IAQI-S were calculated using each HQ value. IAQI-S was applied to the real-time data obtained from 123 classrooms of 46 schools during November 2017 to December 2020. As a result of the comprehensive assessment, 93.1% of PM₁₀ and 94% of PM_2.5 belonged to 'good' and 'moderate', respectively. The IAQI-S based on an 8-hour predicted moving average was compared with Comprehensive Air-quality Index (CAI) and with the IAQI of a foreign reference. The IAQI-S includes CO₂ and consists of more stringent levels comparing to outdoor index (CAI).

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.532-533
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• 2008

본 논문에서는 하루에 수백만 명이 이용하는 지하철 역사내의 환경 관리를 유비쿼터스(Ubiquitous) 기술을 적용하여 실질적이고 효과적으로 실행하는 방안을 제안하고자 한다. 지하철 역사는 지하라는 특수한 환경이기 때문에 외부의 신선한 공기를 유입하여 역사내의 공기질을 쾌적하게 유지해야할 필요가 있다. 또한 실내 공기질을 오염시키는 환경가스나 미세먼지 등의 오염도에 대해서도 지속적으로 감시하여야 한다. 이를 위해 설치가 간편하고 소형의 측정 장치를 지하역사내의 주요 지점에 설치하여 오염물질을 측정하고 그 결과 데이터를 모으는 집중기(Collector)를 운영하여 최종적으로 측정 데이터를 중앙 서버까지 전송할 수 있다면 지하철 관리자에 의한 지하역사내의 오염물질을 효과적으로 관리 감독하는 종합적인 지하철 환경 관리시스템의 운영이 가능할 것으로 판단된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.536-539
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• 2018

In this paper, we propose a system that analyzes environment information by using deep learning and then provides a suitable environment for users by predicting environmental information change. As the level of living improves, interest in improving the quality of life is increasing. In particular, as the air quality deteriorated due to the recent occurrence of dust, smog, fine dust, and ultrafine dust, the indoor air quality as well as the outdoor air became a serious problem. The increase of indoor pollution due to the lack of ventilation and the use of chemicals is a serious problem for modern people who have a lot of indoor living. In order to solve this indoor air pollution, a system has been proposed that measures the state of air quality through sensors and maintains proper temperature and humidity. However, existing system has a difficulty to apply most of the atmospheric environment information to various users depending on sensors only. The system proposed in this paper predicts the indoor environment by analyzing the indoor pollution information collected through the sensor using the deep learning. Then, the predicted indoor environment is modeled and learned in this system, and the environment suitable for the user is suggested. Afterwards, the system receives feedback from the user and repeats the process of re-learning the proposed environment so that it can create the optimal environment for the user.