• Particle and aerosol research
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• v.18 no.3
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• pp.79-86
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• 2022

Many commercial air purifiers currently have deployed granular activated carbon (GAC) filters for removing volatile organic compounds in the indoor air. GACs are generally used to remove gaseous contaminants in the air through adsorption by the inner surfaces of pores. In addition, airborne particles can be also filtered by the surface adsorption of the GACs, which can improve the life-time of the particulate filters. In this study, the filtration efficiency of GACs to ultrafine particles through surface adsorption was investigated at different volume flow rates by deploying a continuous particle filtration system. The polydisperse sodium chloride (NaCl) particles were generated by a set of an atomizer and a diffusion dryer, and then mixed with particle-free air at different volume flow rates. The penetration of ultrafine particles and pressure drop for each experimental condition were measured to figure out the effect of the volume flow rate on the surface adsoprtion of the GACs to particles, ~ 2 mm. The particle filtration efficiency of the GACs decreased as the volume flow rate increased from 4 to 14 lpm. However, the 5 times thicker GAC filter layer decreased the penetration of ultraparticles than a preious study. The filtration efficiency of the single granule was also higher than the previous result in the literature with smaller granule filter materials.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1341-1345
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• 2005

Sequential Monte Carlo techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. We can use Monte Carlo particle filters adaptively, i.e. so that they simultaneously estimate the parameters and the signal. However, Sequential Monte Carlo techniques require the use of special panicle filtering techniques which suffer from several drawbacks. We consider here an alternative approach combining particle filtering and Sequential Hybrid Monte Carlo. We give some examples of applications in fisheries(luespotted mud hopper data).

• Journal of Korean Society of Water and Wastewater
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• v.20 no.6
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• pp.823-828
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• 2006

For this study, an online particle counter was installed before and after the activated carbon filtration process of D water treatment plant where has advanced water treatment processes, produces average 900,000ton/day of drinking water and supply the produced drinking water to Busan citizens. We collected and analyzed particle count data for about 1 year. We inspected particle breakthrough in three out of sixteen filter processes operated at same conditions, i.e. 5th filter, 6th filter and 7th filter. According to the monitoring results, 6th and 7th filters showed similar results while 5th filter showed different results. When compared seasonal effect, the particle count for dry season was below 10 particles/ml while the particle count for August when monthly average rainfall is over 200mm was much higher than for dry season. In January and August, there was a difference in breakthrough particle size. In January, small particles in 2~3um were mainly detected while in August 10um particles were mainly detected and the size distribution was 40% of total count.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.6 no.4
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• pp.417-426
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• 1994

Filter media performance was evaluated using monodisperse NaCl particles with Differential Mobility Analyzer and Ultrafine Condensation Particle Counter. Low or medium performance filters show that the most penetrating particles size(MPPS) is around $0.3{\mu}m$ in diameter and is shifted to smaller sizes as the filter face velocity increases. However, HEPA and ULPA filters show MPPS is around $0.15{\mu}m$ in diameter and is also shifted to $0.1{\mu}m$ in diameter as the face velocity increases. In case of electret filter, the MPPS is found around $0.04{\mu}m$ region for Boltzmann charge equilibrium particles. There is a tendency of strong collection efficiency decrease for large particles as the face velocity increases on the contrary to the other filters. One of the medium performance filter efficiency was compared with filtration theory and the good agreetment was found in the experimental range.

• Transactions on Electrical and Electronic Materials
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• v.13 no.5
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• pp.233-236
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• 2012

The driving properties of a particle-insertion method that filters non-moving particles are analyzed, by measuring its optical and electrical properties. An area that is occupied by the moved particles is proposed, as a desirable evaluation method for a reflective display. To compare the driving property of the particle-moving method with that of the reported simple particle-loading method, two panels are fabricated, according to the different particle-insertion methods, in the same panel condition, of which the width of ribs is $30{\mu}m$, the cell size is $220{\mu}m{\times}220{\mu}m$, the cell gap is $116-120{\mu}m$, the q/m value of the black particles is $+1.8{\mu}C/g$ and that for the white particles is $-4.3{\mu}C/g$. The particle-moving method has a filtering effect which excludes the non-moving particles, inserting only movable particles into the respective cell, so that a panel fabricated by the particle-moving method can drive most of the particles in a cell. Also, most of the particles move at the threshold voltage of 40 V, with enhanced reflectivity. The driving property is also verified by measurement of the occupation rate of the moved particles.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.3
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• pp.222-229
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• 1993

Total suspended particles in the atmosphere were collected on the quartz fiber filters using an ANdersen Hi-volume air sampler from March 1989 to October 1989 and from June 1990 to February 1991, at Chung-Ang University in Seoul. A total amount of eight heavy metals (Cr, Zn, Cd, Pb, Fe, V, Ti, Mn) in total suspended particles were determined by ICP spectrophotometer. The annual arithmetic mean concentration of total suspended particle was 162.3$\mug/m^3$ and eight metals(Cr, Zn, Cd, Pb, Fe, V, Ti, Mn) were 11.6, 609.2, 3.5, 337.1, 2739.5, 15.1, 89.4 and 100.5ng/$m^3$, respectively. The concentration of total suspended particle was highest in the spring(343.7$\mug/m^3$) and lowest in the summer(91.8$\mug/m^3$). These heavy metals were distinguished into two groups in terms of their particle size distribution. The contents of first-group heavy metals (Fe, Ti, Mn) were increased in accordance with the growth of the particle size. The contents of the second-group ones such as Pb, Cd, V, and Zn, on the contrary, came to increase according as the particle size reduced. Statistical analysis indicated that there was a correlation between total suspended particle and Fe in coarse particles, and between total Suspended Particle and Zn, Pb in fine particle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2032-2038
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• 2006

The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle Inter and apply the MATLAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.46-51
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• 2005

Intelligent Space(ISpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.372-379
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• 2014

This paper surveys past and state-of-the-art SLAM technologies. The standard methods for solving the SLAM problem are the Kalman filter, particle filter, graph, and bundle adjustment-based methods. Kalman filters such as EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter) have provided successful results for estimating the state of nonlinear systems and integrating various sensor information. However, traditional EKF-based methods suffer from the increase of computation burden as the number of features increases. To cope with this problem, particle filter-based SLAM approaches such as FastSLAM have been widely used. While particle filter-based methods can deal with a large number of features, the computation time still increases as the map grows. Graph-based SLAM methods have recently received considerable attention, and they can provide successful real-time SLAM results in large urban environments.