• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.3
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• pp.1-7
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• 2022

In this study, inaccurate RSSI values of beacons are corrected using extended Kalman filter. For the experiment, the beacon was manufactured using Arduino Uno board and HM-10 Bluetooth module. RSSI values according to the distance between beacon and the viewer were measured at intervals of 1m, 1.5m, 2m, 2.5m, 3m, 3.5m, 4m, 4.5m, and 5m. To remove the irregular signal pattern of the beacon, the extended Kalman filter was applied to obtain the average and standard deviation of the actual distance and the measured distance, and it was confirmed that more than 76.6% of the irregular signal pattern was removed after using the extended Kalman filter.In addition, through the smartphone app, it was confirmed that the distance accuracy between the beacon and the measurer was less than the actual distance and the measured distance within 2m, and the standard deviation was small.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.4
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• pp.194-200
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• 2013

In this study, an exhaust filter unit for removing bad smells is designed and manufactured to understand the characteristics, damages, and effects on humans and animals of bad smell substances in laboratory animal breeding facilities. Using the exhaust filter unit, a deodorization performance test using ammonia gas, as a typical bad smell in an animal breeding room, was carried out for three types of activated and impregnated charcoal filters. The experimental results showed that the pressure loss of the HEPA and carbon filter was increased with flow rate and that the average deodorization performance for the case where an impregnated carbon filter was installed was a maximum value of between 93 and 96%, with various fractional flow rates ranging from 1,500 to $3,500m^3/h$ in a laboratory animal breeding room. The experimental results will also be used for the design and manufacture of a practical and efficient exhaust filter unit to cope with bad smell problems in animal breeding facilities.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.1
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• pp.121-128
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• 2009

Objectives of this study were to investigate influencing factors of detention time, particle size distribution, and filter medium characteristics for waterworks sludge dewatering. The stepped pressure filtration was carried out with lab scale apparatus and the filter press pilot test for dewatering was conducted at the water treatment plant. Effects of filter medium and polymer dose were examined through observing water content and dewatering velocity and cyclic dewatering rate with filter press pilot test. Relationships among detention time, particle size distribution and filtration resistance were analyzed. Prolongation of sludge detention time was found to cause blinding phenomenon in cake and filter medium and to decrease dewatering process efficiency. The average specific resistance increased according to detention time. In pilot test of dewatering for thickened sludge with Nylon Multi-NY840D and Nylon Mono-100% filter media, dewatering velocities were 0.92 and $0.93kg\;DS/m^2{\cdot}hr$ according to 0.1% polymer dose of dried solids weight base. And cyclic dewatering rates were 2.45 and $2.50kg\;DS/m^2{\cdot}cycle$ cycle for the Nylon Multi-NY840D and Nylon Mono-100% media. Dewatering velocity of polymer dosed sludge was observed to be higher than that of non-polymer sludge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.986-991
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• 2014

The PPG signal used in mobile-healthcare and telemedicine system is including the various motion artifact that is signal generated from patient's movements. Recently, although the various methods to remove motion artifacts have been suggested, the performances of these methods are still not satisfactory. Therefore, this s study suggested the novel method based on the Kalman filter and adaptive filter to remove motion artifacts, and we used various motion artifacts to analyze the performance of the proposed method. In the results of experiments, the signal-to-noise ratio of proposed method showed good performace that was 4.8 times of moving average filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.911-913
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• 2013

The user's context awareness is important to the reliability of sensors data. The sensor data is constantly change to external temp, internal& external environment and vibration. This noise environment is affecting that the data collected information from sensors. Of course this method of digital filter and inference algorithm specifically request for the use of ripple noise and action inference. In this paper, experiment was a comparison of the KF(Kalman Filter) and WMAF(Weight Moving Average Filter) for noise decrease and distortion prevention according to user behavior. And, we compared the EWDF(Extended Weight Dual Filter) with several filer. In an experiment, in contrast to other filter, the proposed filter is robust in a noise-environment.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.120-134
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• 1999

Image processing steps consist of image acquisition, pre-processing, region segmentation and recognition, and the images are easily corrupted by noise during the data transmission, data capture, and data processing. Impulse noise and gaussian noise are major noises, which can occur during the process. Many filters such as mean filter, median filter, weighted median filter, Cheikh filter, and Kyu-cheol Lee filter were proposed as spatial noise reduction filters so far. Many researches have been focused on the reduction of impulse noise, but comparatively the research in the reduction of gaussian noise has been neglected. For the reduction of gaussian noise, subset averaged median filter, using median information and subset average information of pixels in a window. was proposed. At this time, consider of the window size as 3$^{*}$3 pixel. The window is divided to 4 subsets consisted of 4 pixels. First of all, we calculate the average value of each subset, and then find the median value by sorting the average values and center pixel's value. In this paper, a better reduction of gaussian noise was proved. The proposed algorithms were implemented by ANSI C language on a Sun Ultra 2 for testing purposes and the effects and results of the filter in the various levels of noise and images were proposed by comparing the values of PSNR, MSE, and RMSE with the value of the other existing filtering methods.thods.

• Journal of Korean Society on Water Environment
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• v.35 no.2
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• pp.145-151
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• 2019

The purpose of this study was to investigate treatment characteristics of diatomite filtration, that would allow water recovery from biologically-treated effluent for reuse. Diatomite, Celpure 100, and acid clay were used as filter-aids, with a support filter manufactured from polyethylene (PE), and polypropylene (PP). This pre-coating process using diatomite filter-aids, is used in the filtration range of pressure filters, and has consistently provided high-quality separation. The results showed that variations in average removal efficiency of SS, and T-P from biologically treated effluent by the diatomite-coated PE filter, were approximately 82.2 ~ 88.9 % and 4.8 ~ 21.1 %, respectively. T-P treatment efficiency of the PP filter pre-coated with diatomite and $Celpure^{(R)}100$ at $57.64g/m^2$, was approximately $24{\pm}10%$ and $40{\pm}15%$ on average, respectively. Particle size distribution of secondary effluent varied from 0.05 to $200{\mu}m$, and $d_{50}$ value was $20.76{\mu}m$. The size distribution of particles in the diatomite filtrate ranged from 1.26 to $101.1{\mu}m$ when pre-coated with diatomite filter-aid, at a content of $57.64g/m^2$. Diatomite filter aids, i.e., the particles that form the pre-coating layer, capture very fine particles as well as macromolecules, owing to their complex structure with numerous fine microscopic pores, and surface properties. The filtration process using diatomite and $Celpure^{(R)}100$ as filter aids, has been successfully applied, to recover water from sewage for reuse. The disadvantage of the process, is that the particle size of the filter-aid is spent, because of pressurization.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.43-49
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• 2023

Object tracking is being studied with various techniques such as Kalman filter and Luenberger tracker. Even in situations, such as the one in which the system model is not well specified, to which existing signal processing techniques are not successfully applicable, it is possible to design artificial neural networks to track objects. In this paper, we propose an artificial neural network, which we call 'maximum-likelihood weighted-average neural network', to continuously track unpredictably moving objects. This neural network does not directly estimate the locations of an object but obtains location estimates by making weighted average combining various results of maximum likelihood tracking with different data lengths. We compare the performance of the proposed system with those of Kalman filter and maximum likelihood object trackers and show that the proposed scheme exhibits excellent performance well adapting the change of object moving characteristics.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.92-100
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• 2006

In many common control charting situations, the statistic to be charted can be viewed as the output of a linear filter applied to the sequence of process measurement data. In recent work that has generalized this concept, the charted statistic is the output of a general linear filter in impulse response form, and the filter is designed by selecting its impulse response coefficients in order to optimize its average run length performance. In this work, we restrict attention to the class of all second-order linear filters applied to the residuals of a time series model of the process data. We present an algorithm for optimizing the design of the second-order filter that is more computationally efficient and robust than the algorithm for optimizing the general linear filter. We demonstrate that the optimal second-order filter performs almost as well as the optimal general linear filter in many situations. Both methods share a number of interesting characteristics and are tuned to detect any distinct features of the process mean shift, as it manifests itself in the residuals.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.