• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.118-120
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• 2021

In modern society, with the development of IoT technology, various digital equipment is being distributed in a wide range of fields such as CCTV and exploration robots. Accordingly, the importance of data processing is increasing, and various studies are being conducted to remove noise generated in the process of receiving data in the imaging field. Representative noise includes additive white Gaussian noise (AWGN), and existing filters for removing noise include an average filter (AF), an alpha trimmed average filter (A-TAF), and a median filter (MF). However, existing filters have a disadvantage in that they show somewhat insufficient performance in noise removal characteristics in high frequency areas. Therefore, in this paper, in order to effectively remove AWGN existing in the high frequency region, a weight filter according to a distance based on the standard deviation is proposed.

• Journal of the Korean Society of Tobacco Science
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• v.23 no.2
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• pp.179-184
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• 2001

This study was conducted to determine the smoke component distribution and the relationship between chemical components and physical characteristics of cigarettes. 16 different cigarette brands which were sold in the market were selected for this study. Five kinds of smoke components which have been tar, nicotine, water, carbon monoxide(CO) puff No., and six kinds of physical characteristics which were filter type, leaf weight, filter weight, UPD, EPD, dilution rate were analyzed. The average values in tar, nicotine, water, CO concentration were 6.5 mg/cig. 0.66 mg/cig, 1.12 mg/cig. and 6.32 mg/cig., respectively. The average ratios of nicotine/tar and CO/tar were 0.10, and 1.02 respectively. The distribution of smoke components collected in the cambridge filter and cigarette filter was different. The averages of tar and nicotine removal efficiency by a cigarette filter were 53%, and 48%, respectively. All smoking components were positively correlated with other smoking components. filter types, EPD, and dilution rate were showed high correlation to the changes of smoke components. Especially, dilution rate of cigarette strongly affected on the changes of all smoke components.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.779-781
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• 2013

As the demand for various multimedia service increases the technology that utilizes image as information transfer method develops rapidly. Though average filter, median filter and weight filter etc. have been proposed to remove various noises that are added to images, the existing methods are short of noise removal and edge reservation performance. Therefore, in this paper an algorithm, in which noise is decided at the first hand, and then it is processed through modified median filter and adaptive weighted average filter, is proposed to effectively remove the complex noise that has been added to an image. And it was compared with existing methods through simulation and PSNR(peak signal to noise ratio) has been used as a criterion.

• Korean Journal of Plant Resources
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• v.33 no.1
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• pp.33-39
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• 2020

This study was carried out to provide basic information for mass breeding and cultivating the saplings of Camellia japonica. The germination rates did not show definite tendency according to the changes of seed weight at room temperature and 4℃ dry storage conditions. The germination rate of 4℃ wet sand storage was increased with seed weight, but showed very low germination rate for 120 days of storage. The germination rate was above 80% in 60 days, 90 days and 120 days, respectively, at 4℃ wet filter paper storage conditions. The average days taken for those germinations were about 30 days at room temperature and 4℃ dry storage conditions, but wet storage (sand, filter paper) condition took the shortly nearly 13 days for those germinations. Leaf number, leaf dry weight, stem diameter and root dry weight were higher than total average by more than 1.21 g for seed weight. Stem length was higher than the average by more than 1.01 g, plant dry weight was higher than the average by more than 0.81 g, and stem dry weight was higher than the average by more than 0.61 g. In the case of seed weight becoming heavier, seedling growth was good but T/R ratio tended to decrease. In order to increase the mass production of seedlings using Camellia japonica seeds, we need to specify the weight and size of those seeds. The 4℃ wet filter paper storage condition was evaluated as the most efficient method for the seed storage used for seeding.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.145-150
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• 2014

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

• 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.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.2
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• pp.188-194
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• 2014

Recently, indoor localization systems based on wireless sensor networks have received a great deal of attention because they help achieve high accuracy in position determination by using various algorithms. In order to minimize the error in the estimated azimuth that can occur owing to sensor drift and recursive calculation in these algorithms, we propose a novel relative azimuth estimation algorithm. The advantages of the proposed technique in an indoor environment are that an improved weight average filter is used to effectively reduce impulse noise from the raw data acquired from nodes with inherent errors and a rotational displacement algorithm is applied to obtain a precise relative azimuth without using additional sensors, which can be affected by electromagnetic noise. Results from simulations show that the proposed filter reduces the impulse noise, and the acquired estimation error does not accumulate with time by using proposed algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.73-76
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• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.