• Title/Summary/Keyword: Reduction Method

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A Study on the Purity Change of Silicon Metal According to the Purity of Silica Stone in Metal Silicon Extraction by Thermit Reaction (테르밋 반응을 이용하여 금속실리콘을 추출할 때 규석 순도에 따라 금속실리콘 순도 변화에 대한 고찰)

  • Kim, Jaehee;Han, Jinho;Shin, Hyunmyung
    • Resources Recycling
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    • v.26 no.4
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    • pp.19-25
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    • 2017
  • The ways of producing metal silicon include a carbon reduction method, a plasma reduction method, and a thermite reaction method. The carbon reduction process produces metal silicon by metallurgical refining. The carbon reduction method is produced by adding a raw material mixed with quartz and coke to an electric arc furnace which is for carbon reduction. The cost of high energy costs and environmental protection facilities is an issue when producing metal silicon using electric arc furnaces. For this reason, there is no metal silicon production facility in Korea yet. Therefore, the optimal manufacturing conditions by the carbon reduction method are being studied through the experimental facilities by the companies and research institutes. The present study investigated the change of metal silicon purity according to the purity of silicon when extracting metal silicon using the thermit reaction, which has a relatively lower manufacturing cost than the carbon reduction method.

Determinant-based two-channel noise reduction method using speech presence probability (음성존재확률을 이용한 행렬식 기반 2채널 잡음제거기법)

  • Park, Jinuk;Hong, Jungpyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.5
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    • pp.649-655
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    • 2022
  • In this paper, a determinant-based two-channel noise reduction method which utilizes speech presence probability (SPP) is proposed. The proposed method improves noise reduction performance from the conventional determinant-based two-channel noise reduction method in [7] by applying SPP to the Wiener filter gain. Consequently, the proposed method adaptively controls the amount of noise reduction depending on the SPP. For performance evaluation, the segmental signal-to-noise ratio (SNR), the perceptual evaluation of speech quality, the short time objective intelligibility, and the log spectral distance were measured in the simulated noisy environments considered various types of noise, reverberation, SNR, and the direction and number of noise sources. The experimental results presented that determinant-based methods outperform phase difference-based methods in most cases. In particular, the proposed method achieved the best noise reduction performance maintaining minimum speech distortion.

An Efficient Management of Sediment Deposit for Reservoir Long-Term Operation (2) - Sediment Distribution and Reduction Method in Reservoir (저수지 장기운영을 위한 퇴적토사의 효율적 관리(2) - 저수지 퇴사분포 및 저감방안)

  • Ahn, Jae Hyun;Jang, Su Hyung;Choi, Won Suk;Yoon, Yong Nam
    • Journal of Korean Society on Water Environment
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    • v.22 no.6
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    • pp.1094-1100
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    • 2006
  • In this study, the reservoir sediment reduction methods for long-term operation are proposed by the analysis of both sediment deposit characteristics and sediment reduction effect by each method. To that end, a flowchart for sediment analysis in reservoir is established and sediment deposit is simulated by SMS-SED2D model. The sediment reduction methods which are sediment passing (sluicing), flushing, trapping, bypassing and mechanical removal are used. From the simulation results, the effective method for sediment reduction is operation which is coupled by both sediment passing with sand gate and sediment trapping with debris dam. And If sediment flushing will be used once a year after 50 years, conservation storage can be secured until 100 years after dam construction.

A Study on Application of Dimethoxy Methane and EGR Method for Simultaneous Reduction of Smoke and NOx Emission (매연과 NOx의 동기저감을 위한 Dimethoxy Methane과 EGR방법의 적용에 관한 연구)

  • Choi, Seung-Hun;Oh, Young-Taig;Hwang, Yun-Taig;Song, Ki-Hong
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.448-453
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    • 2003
  • In this study, the effects of oxygen component in fuel and exhaust gas recirculation(EGR) method on the exhaust emissions has been investigated for a D.I. diesel engine. It was tested to estimate change of exhaust emission characteristics for the commercial diesel fuel and oxygenate blended fuel which has five kinds of blending ratio. Dimethoxy methane(DMM) contains oxygen component 42.5% in itself. and it is a kind of effective oxygenated fuel for reduction of smoke emission. It was affirmed that smoke emission was decreased with increasing of DMM blending ratio. But, NOx emission was increased compared with commercial diesel fuel. It was needed a NOx reduction countermeasure that EGR method was used as a countermeasure for NOx reduction. It was found that simultaneous reduction of smoke and NOx emission was achieved with DMM blended fuel and cooled EGR method($10{\sim}15%$).

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A MULTI-DIMENSIONAL REDUCTION METHOD OF LARGE-SCALE SURVEY DATABASE

  • Lee, Y.;Kim, Y.S.;Kang, H.W.;Jung, J.H.;Lee, C.H.;Yim, I.S.;Kim, B.G.;Kim, H.G.;Kim, K.T.
    • Publications of The Korean Astronomical Society
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    • v.28 no.1
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    • pp.7-13
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    • 2013
  • We present a multi-dimensional reduction method of the surveyed cube database obtained using a single- dish radio telescope in Taeduk Radio Astronomy Observatory (TRAO). The multibeam receiver system installed at the 14 m telescope in TRAO was not optimized at the initial stage, though it became more stabilized in the following season. We conducted a Galactic Plane survey using the multibeam receiver system. We show that the noise level of the first part of the survey was higher than expected, and a special reduction process seemed to be definitely required. Along with a brief review of classical methods, a multi-dimensional method of reduction is introduced; It is found that the 'background' task within IRAF (Image Reduction and Analysis Facility) can be applied to all three directions of the cube database. Various statistics of reduction results is tested using several IRAF tasks. The rms value of raw survey data is 0.241 K, and after primitive baseline subtraction and elimination of bad channel sections, the rms value turned out to be 0.210 K. After the one-dimensional reduction using 'background' task, the rms value is estimated to be 0.176 K. The average rms of the final reduced image is 0.137 K. Thus, the image quality is found to be improved about 43% using the new reduction method.

Noise-reduction Function and its Affecting Factors of Plant Communities

  • Song, Xiu-hua;Wu, Qian-qian;Yu, Dong-ming;PIAO, Yong-ji;Cho, Tae-Dong
    • Journal of Environmental Science International
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    • v.25 no.10
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    • pp.1407-1415
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    • 2016
  • In this study, we investigated the relationship between noise reduction and the community structure of nine groups of typical plant communities as well as the reduction in noise at different frequencies. The semantic differential method was adopted to explore the perception of noise reduction. The results indicated that there was a significantly positive correlation between noise reduction and coverage, a significantly negative correlation between noise reduction and bifurcate height, and a negative correlation between noise reduction and bare rate. However, there was no significant correlation between noise reduction and height, diameter at breast height, or crown width. The reduction of middle-frequency noise was better than that of low- and high-frequency noise. The indicators "quiet" and "calm" showed that plant communities could reduce the noise perceived by humans. However, overly dense woodland caused nervousness, fear, depression, and other negative effects. Relatively open environments and those with large forest gaps obtained the highest evaluation.

A new approach to model reduction using matrix pencil method (Matrix Pencil을 이용한 모델 저차화의 새로운 접근방법)

  • 권혁성;정정주;서병설
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.105-108
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    • 1997
  • This paper proposes a new approach of balanced model reduction using matrix pencil. The algorithm presented in this paper is to convert full-rank high-order system into rank-deficient system using perturbation made by matrix pencil method. Then the system can be truncated to a low-order system that we want via balanced realization. We discuss the comparison with other methods and the various observations by simulations.

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Noise reduction and De-interlacing with motion vector validation (움직임 추정 보정을 이용한 잡음 제거 및 디인터레이싱 기법)

  • 정재한;양승준
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.149-152
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    • 2003
  • This paper presents a method to find motion vectors that are closer to true motion with noisy images for simultaneous noise reduction and do-interlacing. The proposed method requires four interlaced field images: one noisy field image and three field images from which noise is already removed. The validation of motion provides accurate motion vectors and allows us to utilize them even in very noisy environment. The validated motion vectors are first used for the noise reduction, buffered and used later for the noise reduction and de -interlacing.

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A study on the sheet drawing using the Matrix method (Matrix법을 이용한 판재 인발에 관한 연구)

  • 유홍균;전병희
    • Journal of the korean Society of Automotive Engineers
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    • v.13 no.6
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    • pp.90-100
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    • 1991
  • This paper represents the analysis of the sheet drawing by applying the Matrix method to Hill's slip-line field for small reduction and indirect type slip-line field in case of large reduction. Results of the analysis represent the relation between the reduction ratio and the die wall pressure, mean drawing stress through rough die. The limitation on the use of this slip-line field is described. When the reduction ratio is given, the optimum die angle is analyzed in this paper.

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A Classification Method Using Data Reduction

  • Uhm, Daiho;Jun, Sung-Hae;Lee, Seung-Joo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.1-5
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    • 2012
  • Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.