• Title/Summary/Keyword: reference prediction.

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Scalar First Replacement Strategy for Reference Prediction Table Used in Prefetching Streaming Data (스트리밍 데이터의 선인출에 사용되는 참조예측표의 스칼라 우선 교체 전략)

  • Lim, Chul-hoo;Chon, Young-Suk;Kim, Suk-il;Jeon, Joong-nam
    • The KIPS Transactions:PartA
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    • v.11A no.3
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    • pp.163-172
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    • 2004
  • Multimedia applications tend to access their data as a streaming pattern with regular intervals. This characteristic can be utilized in prefetching the multimedia data into cache memory so as to reduce their execution speeds. The reference-prediction prefetch algorithm predicts the memory address that seems to be used in the next time based on the previous history of memory references stored in the prediction reference table. This paper proposes a strategy to manipulate the reference prediction table which contains all of the data reference instructions to scalar and streaming data. We have recognized that the scalar reference instructions do not contribute to the data prefetching algorithm. Therefore, when replacing an element in the reference prediction table, the proposed algorithm preferentially selects the scalar reference instruction before the stream reference instruction. It makes the stream reference instruction to stay for a long time compared to the FIFO replacement policy, and eventually improves the performance of data prefetching.

Comparison of prediction accuracy for genomic estimated breeding value using the reference pig population of single-breed and admixed-breed

  • Lee, Soo Hyun;Seo, Dongwon;Lee, Doo Ho;Kang, Ji Min;Kim, Yeong Kuk;Lee, Kyung Tai;Kim, Tae Hun;Choi, Bong Hwan;Lee, Seung Hwan
    • Journal of Animal Science and Technology
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    • v.62 no.4
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    • pp.438-448
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    • 2020
  • This study was performed to increase the accuracy of genomic estimated breeding value (GEBV) predictions for domestic pigs using single-breed and admixed reference populations (single-breed of Berkshire pigs [BS] with cross breed of Korean native pigs and Landrace pigs [CB]). The principal component analysis (PCA), linkage disequilibrium (LD), and genome-wide association study (GWAS) were performed to analyze the population structure prior to genomic prediction. Reference and test population data sets were randomly sampled 10 times each and precision accuracy was analyzed according to the size of the reference population (100, 200, 300, or 400 animals). For the BS population, prediction accuracy was higher for all economically important traits with larger reference population size. Prediction accuracy was ranged from -0.05 to 0.003, for all traits except carcass weight (CWT), when CB was used as the reference population and BS as the test. The accuracy of CB for backfat thickness (BF) and shear force (SF) using admixed population as reference increased with reference population size, while the results for CWT and muscle pH at 24 hours after slaughter (pH) were equivocal with respect to the relationship between accuracy and reference population size, although overall accuracy was similar to that using the BS as the reference.

Variation of Crop Coefficient With Respect to the Reference Crop Evapotranspiration Estimation Methods in Ponded Direct Seeding Paddy Rice (담수직파재배 논벼의 기준작물 잠재증발산량 산정방법별 작물계수의 변화)

  • 정상옥
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.39 no.4
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    • pp.114-121
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    • 1997
  • In order to provide basic information for the estimation of evapotranspiration in the ponded direct seeding paddy field, both field lysimeter experiment and model prediction were performed to estimate daily ET. Various methods were used to predict daily reference crop ET and crop coefficients. Measure4 mean daily ET during the 1995 growing season varied from 5.9 to 6.1 mm depending on the species, while it varied from 5.1 to 5.5 mm in 1996. Model predicted mean daily ET during the 1995 growing season varied from 3.9 to 4.9 mm depending on the prediction model, while it varied from 3.5 to 4.7 mm in 1996. The smaller ET values both measured and predicted in 1996 were caused by the low values of temperature, sunshine hours, and solar radiation. Crop coefficients varied from 1.20 to 1.50 in 1995 depending on the prediction model, while it varied from 1.10 to 1.47 in 1996. Comparison of the seven reference crop ET prediction methods used in this study shows that the Penman-Monteith method and the FAO-Radiation method gave the lowest ET while the corrected Penman method and the Hargreaves method gave the largest ET. Since crop coefficients vary to a large extent based on the prediction methods, reference crop ET prediction method should be carefully selected in irrigation planning.

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Computation of Reference Crop Evapotranspiration for Irrigation Scheduling (관개계획을 위한 기준작물 증발산량 산정 -고삼 저수지에 대한 사례연구-)

  • 정상옥
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.40 no.1
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    • pp.43-48
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    • 1998
  • In order to provide basic information for the estimation of evapotranspiration for grass (Joycia Japonica), both field lysimeter experiment and model prediction were performed to estimate daily ET Various methods were used to predict daily reference crop ET and crop coefficients. Measured mean daily ET during the 1997 growing season was 4.5mm Model predicted mean daily ET during the 1997 growing season varied from 3.6 to 4.7mm depending on the prediction model Crop coefficients varied from 0.96 to 1.27 depending on the prediction model Comparison of the seven reference crop ET prediction methods used in this study shows that the Penman-Monteith method gave the smallest ET while the Hargreaves method gave the largest ET. The crop coefficient by the corrected Penman method was 1.03, which is closest to 1.0, suggesting that this method may he the best prediction method.

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An Efficient VLC Table Prediction Scheme for H.264 Using Weighting Multiple Reference Blocks (H.264 표준에서 가중된 다중 참조 블록을 이용한 효율적인 VLC 표 예측 방법)

  • Heo, Jin;Oh, Kwan-Jung;Ho, Yo-Sung
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.39-42
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    • 2005
  • H.264, a recently proposed international video coding standard, has adopted context-based adaptive variable length coding (CAVLC) as the entropy coding tool in the baseline profile. By combining an adaptive variable length coding technique with context modeling, we can achieve a high degree of redundancy reduction. However, CAVLC in H.264 has weakness that the correct prediction rate of the variable length coding (VLC) table is low in a complex area, such as the boundary of an object. In this paper, we propose a VLC table prediction scheme considering multiple reference blocks; the same position block of the previous frame and the neighboring blocks of the current frame. The proposed algorithm obtains the new weighting values considering correctness of the VLC table for each reference block. Using this method, we can enhance the prediction rate of the VLC table and reduce the bit-rate.

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Intra Prediction Method for Depth Picture Using CNN and Attention Mechanism (CNN과 Attention을 통한 깊이 화면 내 예측 방법)

  • Jae-hyuk Yoon;Dong-seok Lee;Byoung-ju Yun;Soon-kak Kwon
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.2
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    • pp.35-45
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    • 2024
  • In this paper, we propose an intra prediction method for depth picture using CNN and Attention mechanism. The proposed method allows each pixel in a block to predict to select pixels among reference area. Spatial features in the vertical and horizontal directions for reference pixels are extracted from the top and left areas adjacent to the block, respectively, through a CNN layer. The two spatial features are merged into the feature direction and the spatial direction to predict features for the prediction block and reference pixels, respectively. the correlation between the prediction block and the reference pixel is predicted through attention mechanism. The predicted correlations are restored to the pixel domain through CNN layers to predict the pixels in the block. The average prediction error of intra prediction is reduced by 5.8% when the proposed method is added to VVC intra modes.

Nondestructive Prediction of Fatty Acid Composition in Sesame Seeds by Near Infrared Reflectance Spectroscopy

  • Kim, Kwan-Su;Park, Si-Hyung;Choung, Myoung-Gun;Kim, Sun-Lim
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.spc1
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    • pp.304-309
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    • 2006
  • Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

Minimisation Technique for Seismic Noise Using a Neural Network (인공신경망을 이용한 탄성파 잡음제거)

  • Hwang Hak Soo;Lee Sang Kyu;Lee Tai Sup;Sung Nak Hoon
    • Geophysics and Geophysical Exploration
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    • v.3 no.3
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    • pp.83-87
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    • 2000
  • The noise prediction filter using a local/remote reference was developed to obtain a high quality data from seismic surveys over the area where seismic transmission power is limited. The method used in the noise prediction filter is a 3-layer neural network whose algorithm is backpropagation. A NRF (Noise Reduction Factor) value of about 3.0 was obtained with appling training and test data to the trained noise prediction filter. However, the scaling technique generally used for minimizing EM noise from electric and electromagnetic data cannot reduce seismic noise, since the technique can allow only amplitude difference between two time series measured at the primary and reference sites.

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A design of High-Profile Intra Prediction module for H.264 (H.264 High-Profile Intra Prediction 모듈 설계)

  • Suh, Ki-Bum;Lee, Hye-Yoon;Lee, Yong-Ju;Kim, Ho-Eui
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.11
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    • pp.2045-2049
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    • 2008
  • In this paper, we propose an novel architecture for H.264 High Profile Encoder Intra Prediction module. This designed module can be operated in 306 cycle for one-macroblock. To verify the Encoder architecture, we developed the reference C from JM 13.2 and verified the our developed hardware using test vector generated by reference C. We adopt plan removal and SAD calculation to reduce the Hardware cost and cycle. The designed circuit can be operated in 133MHz clock system, and has 250K gate counts using TSMC 0.18 um process including SRAM memory.

Intra Prediction Method by Quadric Surface Modeling for Depth Video (깊이 영상의 이차 곡면 모델링을 통한 화면 내 예측 방법)

  • Lee, Dong-seok;Kwon, Soon-kak
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.35-44
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    • 2022
  • In this paper, we propose an intra-picture prediction method by a quadratic surface modeling method for depth video coding. The pixels of depth video are transformed to 3D coordinates using distance information. A quadratic surface with the smallest error is found by least square method for reference pixels. The reference pixel can be either the upper pixels or the left pixels. In the intra prediction using the quadratic surface, two predcition values are computed for one pixel. Two errors are computed as the square sums of differences between each prediction values and the pixel values of the reference pixels. The pixel sof the block are predicted by the reference pixels and prediction method that they have the lowest error. Comparing with the-state-of-art video coding method, simulation results show that the distortion and the bit rate are improved by up to 5.16% and 5.12%, respectively.