• Environmental Engineering Research
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• v.20 no.3
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• pp.237-245
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• 2015

Particulate matter in indoor environments has caused public concerns in recent years. The objective of this research is to explore the influence of radiators on particle size distributions and concentrations. The particle size distributions as well as concentrations above radiators and in the adjacent indoor air are monitored in forty-two indoor environments in Xi'an, China. The temperatures, relative humidity and air velocities are also measured. The particle size distributions above radiators at ten locations are analyzed. The results show that the functional difference of indoor environments has little impact on the particle size distributions above radiators. Then the effects of the environmental parameters (particle concentrations in the adjacent indoor air, temperatures, relative humidities and air velocities) on particle concentrations above radiators are assessed by applying multiple linear regression analysis. Three multiple linear regression models are established to predict the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_1$ above radiators.

• Particle and aerosol research
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• v.14 no.3
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• pp.81-88
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• 2018

The market for improving the indoor air quality is continuously increasing, and air cleaners are the representative products. As interest in indoor air quality increases, so are the ultrafine particle which are harmful to the human body. Despite its many advantages, electrostatic precipitators are less used in indoor air due to ozone production. In this study, the carbon fiber sheet was applied to the discharge electrode and compared with the conventional tungsten wire discharge electrode. The particle collection efficiency and the amount of ozone generation were measured for 10-100 nm particles. Furthermore, it was applied to commercial air purifier with electrostatic precipitator to compare particle removal performance. The carbon fiber sheet type discharge electrode generates a small amount of ozone, and thus it can be applied to improve indoor air quality.

• KIEAE Journal
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• v.7 no.6
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• pp.9-15
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• 2007

Ventilation of buildings provide occupants with comfort and plays a very informant role in supplying indoor ventilation requirement. Also, natural ventilation is more comfortable than forced ventilation taking account of mental comfort. Especially factors, airflow velocity and direction etc., should be reflected in establishment of comfortable indoor environment because indoor airflow can directly affect comfort of occupants. However, a device which enables indoor air movement to be analyzed has not existed until now. Hence, it has mostly depended on simulation results of fluid analysis but the results often differ far from reality. PST(Particle-Streak-Tracking) System, an alternative to improve this problem, is currently applied to natural ventilation in building, air conditioning, and airflow analysis in the inside of a plane etc. This study closely examine the property and strength and weakness of PST that is first introduced into KICT and then evaluate applicable possibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.1
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• pp.115-120
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• 2004

An indoor air cleaner consisting of a dielectric barrier discharge system and an electrostatic precipitator (ESP) was experimentally investigated. The function of the dielectric barrier discharge is to precharge particles by producing nonthermal plasma before indoor air enters ESP, leading to an enhancement in dust collection efficiency. The dependence of particle size distribution on the plasma discharge was examined to understand the mechanism of the particle precharging. The plasma discharge was found to increase the electrical force of the particles, rather than agglomerate them. Coarse particles in the range of 0.5 to $5.0{\mu}m$ were observed to be easily collected by this indoor air cleaner, and the present study laid emphasis on the removal of fine particles of $0.3{\mu}m$. The collection efficiency of the fine particles was largely enhanced by the plasma discharge.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3534-3553
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• 2021

The low cost of Bluetooth technology has led to its wide usage in indoor positioning. However, some inherent shortcomings of Bluetooth technology have limited its further development in indoor positioning, such as the unstable positioning state caused by the fluctuation of Received Signal Strength Indicator (RSSI) and the low transmission frequency accompanied by a poor real-time performance in positioning and tracking moving targets. To address these problems, an indoor fusion positioning algorithm of Bluetooth technology and pedestrian dead reckoning (PDR) based on a particle filter with dynamic adjustment of weights calculation strategy (BPDW) will be proposed. First, an orderly statistical filter (OSF) sorts the RSSI values of a period and then eliminates outliers to obtain relatively stable RSSI values. Next, the Group-based Trilateration algorithm (GTP) enhances positioning accuracy. Finally, the particle filter algorithm with dynamic adjustment of weight calculation strategy fuses the results of Bluetooth positing and PDR to improve the performance of positioning moving targets. To evaluate the performance of BPDW, we compared BPDW with other representative indoor positioning algorithms, including fingerprint positioning, trilateral positioning (TP), multilateral positioning (MP), Kalman filter, and strong tracking filter. The results showed that BPDW has the best positioning performance on static and moving targets in simulation and actual scenes.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.2
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• pp.155-163
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• 2020

Indoor airborne particles are consisted of outdoor- and indoor-generated particles, which can be characterized by their compositions, generation features and toxicity. The identification of source contribution of indoor and outdoor origin to indoor particles is important to understand PM_2.5 transport in a building as well as its impact on occupant health. The objective of this study is to investigate seasonal source contribution to indoor PM_2.5 concentration depending on airtightness of apartment units. To evaluate the source contribution, particle transport including penetration, generation, exfiltration in an apartment housing unit was simulated by using CONTAM with particle and airflow simulation parameters obtained from field measurements. The result showed that the outdoor source contribution to indoor air was relatively dominant in the leaky housing unit during spring (77.2%) and winter (73.9%), and the indoor source was dominant in the airtight housing unit during summer (60.3%) and fall (60.7%). These results indicate the seasonal health risk of indoor PM_2.5 can be varied according to airtightness of apartment units.

• Particle and aerosol research
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• v.16 no.1
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• pp.9-17
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• 2020

The characteristics of particulate matter made from daily cooking at a Korean residential apartment house with three dwellers had been investigated for about 3 months. All data were recorded by an optical particle counter every minute at the kitchen. Types of cooking such as boiling, frying, and grilling that performed in the house were listed. Boiling only was used in 32% cases among total 234 meals. Frying and grilling were 14% and 11%, respectively. From an initial indoor particulate matter smaller than 10 ㎛ in diameter, the increases due to cooking are reported by size. In case of boiling, PM at 1-10 ㎛ size and under 1 ㎛ size little increased. Normally, particles from oil or combustion in a process of frying or grilling increased indoor PM. In a case of grilling, particle mass concentration in a region of 1-10 ㎛ in diameter increased as much as 295 ㎍/㎥. Mass concentration of particles smaller than 1 ㎛ increased as much as 33 ㎍/㎥.

• Particle and aerosol research
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• v.10 no.3
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• pp.119-130
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• 2014

Home is a major living environment of children. In urban area, indoor air at home could be severely influenced by combustion sources such as vehicle exhaust and cooking. In this work, the air quality of a high-rise apartment was investigated by monitoring combustion-related air pollutants at both indoor and outdoor in winter of 2014. From 48-h continuous monitoring data, large amount of $NO_x$ was observed at the balcony of the high-rise apartment during the morning traffic hours. It deteriorated indoor air quality of the apartment. During the cooking activity, high peak episodes of ultrafine particles were seen. It was concluded that effects of vehicle exhaust and cooking activity on the indoor air of the high-rise apartment could be easily checked by $NO_x$ and ultrafine particle indicators, respectively.