• Title/Summary/Keyword: LRR

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Graph Construction Based on Fast Low-Rank Representation in Graph-Based Semi-Supervised Learning (그래프 기반 준지도 학습에서 빠른 낮은 계수 표현 기반 그래프 구축)

  • Oh, Byonghwa;Yang, Jihoon
    • Journal of KIISE
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    • v.45 no.1
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    • pp.15-21
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    • 2018
  • Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

Application of hybrid LRR technique to protein crystallization

  • Jin, Mi-Sun;Lee, Jie-Oh
    • BMB Reports
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    • v.41 no.5
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    • pp.353-357
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    • 2008
  • LRR family proteins play important roles in a variety of physiological processes. To facilitate their production and crystallization, we have invented a novel method termed "Hybrid LRR Technique". Using this technique, the first crystal structures of three TLR family proteins could be determined. In this review, design principles and application of the technique to protein crystallization will be summarized. For crystallization of TLRs, hagfish VLR receptors were chosen as the fusion partners and the TLR and the VLR fragments were fused at the conserved LxxLxLxxN motif to minimize local structural incompatibility. TLR-VLR hybridization did not disturb structures and functions of the target TLR proteins. The Hybrid LRR Technique is a general technique that can be applied to structural studies of other LRR proteins. It may also have broader application in biochemical and medical application of LRR proteins by modifying them without compromising their structural integrity.

MSHR-Aware Dynamic Warp Scheduler for High Performance GPUs (GPU 성능 향상을 위한 MSHR 활용률 기반 동적 워프 스케줄러)

  • Kim, Gwang Bok;Kim, Jong Myon;Kim, Cheol Hong
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.5
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    • pp.111-118
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    • 2019
  • Recent graphic processing units (GPUs) provide high throughput by using powerful hardware resources. However, massive memory accesses cause GPU performance degradation due to cache inefficiency. Therefore, the performance of GPU can be improved by reducing thread parallelism when cache suffers memory contention. In this paper, we propose a dynamic warp scheduler which controls thread parallelism according to degree of cache contention. Usually, the greedy then oldest (GTO) policy for issuing warp shows lower parallelism than loose round robin (LRR) policy. Therefore, the proposed warp scheduler employs the LRR warp scheduling policy when Miss Status Holding Register(MSHR) utilization is low. On the other hand, the GTO policy is employed in order to reduce thread parallelism when MSHRs utilization is high. Our proposed technique shows better performance compared with LRR and GTO policy since it selects efficient scheduling policy dynamically. According to our experimental results, our proposed technique provides IPC improvement by 12.8% and 3.5% over LRR and GTO on average, respectively.

Unequal Loss Protection Using Layer-Based Recovery Rate (ULP-LRR) for Robust Scalable Video Streaming over Wireless Networks

  • Quan, Shan Guo;Ha, Hojin;Ran, Rong
    • Journal of information and communication convergence engineering
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    • v.14 no.4
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    • pp.240-245
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    • 2016
  • Scalable video streaming over wireless networks has many challenges. The most significant challenge is related to packet loss. To overcome this problem, in this paper, we propose an unequal loss protection (ULP) method using a new forward error correction (FEC) mechanism for robust scalable video streaming over wireless networks. For an efficient FEC assignment considering video quality, we first introduce a simple and efficient performance metric, the layer-based recovery rate (LRR), for quantifying the unequal error propagation effects of the temporal and quality layers on the basis of packet losses. LRR is based on the unequal importance in both the temporal and the quality layers of a hierarchical scalable video coding structure. Then, the proposed ULP-LRR method assigns an appropriate number of FEC packets on the basis of the LRR to protect the video layers against packet lossy network environments. Compared with conventional ULP algorithms, the proposed ULP-LRR algorithm demonstrates a higher performance for various error-prone wireless channel statuses.

Sensitivity Analysis in Latent Root Regression

  • Shin, Jae-Kyoung;Tomoyuki Tarumi;Yutaka Tanaka
    • Communications for Statistical Applications and Methods
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    • v.1 no.1
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    • pp.102-111
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    • 1994
  • We Propose a method of sensitivity analysis in latent root regression analysis (LRRA). For this purpose we derive the quantities ${\beta\limits^\wedge \;_{LRR}}^{(1)}$, which correspond to the theoretical influence function $I(x, y \;;\;\beta\limits^\wedge \;_{LRR})$ for the regression coefficient ${\beta\limits^\wedge}_{LRR}$ based on LRRA. We give a numerical example for illustration and also investigate numerically the relationship between the estimated values of ${\beta\limits^\wedge \;_{LRR}}^{(1)}$ with the values of the other measures called sample influence curve(SIC) based on the recomputation for the data with a single observation deleted. We also discuss the comparision among the results of LRRA, ordinary least square regression analysis (OLSRA) and ridge regression analysis(RRA).

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Comparison of Two-Equation Model and Reynolds Stress Models with Experimental Data for the Three-Dimensional Turbulent Boundary Layer in a 30 Degree Bend

  • Lee, In-Sub;Ryou, Hong-Sun;Lee, Seong-Hyuk;Chae, Soo
    • Journal of Mechanical Science and Technology
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    • v.14 no.1
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    • pp.93-102
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    • 2000
  • The objective of the present study is to investigate the pressure-strain correlation terms of the Reynolds stress models for the three dimensional turbulent boundary layer in a $30^{\circ}$ bend tunnel. The numerical results obtained by models of Launder, Reece and Rodi (LRR) , Fu and Speziale, Sarkar and Gatski (SSG) for the pressure-strain correlation terms are compared against experimental data and the calculated results from the standard k-${\varepsilon}$ model. The governing equations are discretized by the finite volume method and SIMPLE algorithm is used to calculate the pressure field. The results show that the models of LRR and SSG predict the anisotropy of turbulent structure better than the standard k-${\varepsilon}$ model. Also, the results obtained from the LRR and SSG models are in better agreement with the experimental data than those of the Fu and standard k-${\varepsilon}$ models with regard to turbulent normal stresses. Nevertheless, LRR and SSG models do not effectively predict pressure-strain redistribution terms in the inner layer because the pressure-strain terms are based on the locally homogeneous approximation. Therefore, to give better predictions of the pressure-strain terms, non-local effects should be considered.

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A study on the properties of sensitivity analysis in principal component regression and latent root regression (주성분회귀와 고유값회귀에 대한 감도분석의 성질에 대한 연구)

  • Shin, Jae-Kyoung;Chang, Duk-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.2
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    • pp.321-328
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    • 2009
  • In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

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Latency Hiding based Warp Scheduling Policy for High Performance GPUs

  • Kim, Gwang Bok;Kim, Jong Myon;Kim, Cheol Hong
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.4
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    • pp.1-9
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    • 2019
  • LRR(Loose Round Robin) warp scheduling policy for GPU architecture results in high warp-level parallelism and balanced loads across multiple warps. However, traditional LRR policy makes multiple warps execute long latency operations at the same time. In cases that no more warps to be issued under long latency, the throughput of GPUs may be degraded significantly. In this paper, we propose a new warp scheduling policy which utilizes latency hiding, leading to more utilized memory resources in high performance GPUs. The proposed warp scheduler prioritizes memory instruction based on GTO(Greedy Then Oldest) policy in order to provide reduced memory stalls. When no warps can execute memory instruction any more, the warp scheduler selects a warp for computation instruction by round robin manner. Furthermore, our proposed technique achieves high performance by using additional information about recently committed warps. According to our experimental results, our proposed technique improves GPU performance by 12.7% and 5.6% over LRR and GTO on average, respectively.

Treatment results of breast cancer patients with locoregional recurrence after mastectomy

  • Jeong, Yuri;Kim, Su Ssan;Gong, Gyungyub;Lee, Hee Jin;Ahn, Sei Hyun;Son, Byung Ho;Lee, Jong Won;Choi, Eun Kyung;Lee, Sang-Wook;Joo, Ji Hyeon;Ahn, Seung Do
    • Radiation Oncology Journal
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    • v.31 no.3
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    • pp.138-146
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    • 2013
  • Purpose: To analyze the results of locoregional and systemic therapy in the breast cancer patients with locoregional recurrence (LRR) after mastectomy. Materials and Methods: Seventy-one patients who received radiotherapy for isolated LRR after mastectomy between January 1999 and December 2009 were retrospectively reviewed. Among the 71 patients, 59 (83.1%) underwent wide excision and radiotherapy and 12 (16.9%) received radiotherapy alone. Adjuvant hormonal therapy was given to 45 patients (63.4%). Oncologic outcomes including locoregional recurrence-free survival, disease-free survival (DFS), and overall survival (OS) and prognostic factors were analyzed. Results: Median follow-up time was 49.2 months. Of the 71 patients, 5 (7%) experienced second isolated LRR, and 40 (56%) underwent distant metastasis (DM). The median DFS was 35.6 months, and the 3- and 5-year DFS were 49.1% and 28.6%, respectively. The median OS was 86.7 months, and the 5-year OS was 62.3%. Patients who received hormone therapy together showed better 5-year DFS and OS than the patients treated with locoregional therapy only (31.6% vs. 22.1%, p = 0.036; 66.5% vs. 55.2%, p = 0.022). In multivariate analysis, higher N stage at recurrence was a significant prognostic factor for DFS and OS. Disease free interval (${\leq}30$ months vs. >30 months) from mastectomy to LRR was also significant for OS. The patients who received hormone therapy showed superior DFS and showed trend to better OS. Conclusion: DM was a major pattern of failure after the treatment of LRR after mastectomy. The role of systemic treatment for LRR after mastectomy should be investigated at prospective trials.

The Glucosinolate and Sulforaphane Contents of Land Race Radish and Wild Race Radish Extracts and Their Inhibititory Effects on Cancer Cell Lines (재래종 무와 갯무 추출물의 암세포주 증식 저해 활성 및 Glucosinolate와 Sulforaphane의 함량)

  • Choi, Sun-Ju;Choi, A-Reum;Cho, Eun-Hye;Kim, So-Young;Lee, Gun-Soon;Lee, Soo-Seong;Chae, Hee-Jeong
    • Journal of the East Asian Society of Dietary Life
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    • v.19 no.4
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    • pp.558-563
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    • 2009
  • The inhibitory effects of land race radish (LRR) and wild race radish (WRR) extracts on cancer cell lines were investigated. A and their glucosinolate and sulforaphane contents were analyzed. The anticancer activitiesy of the LRR and WRR extracts on the breast cancer cell line MCF-7 were determined by a CCK (cell counting kit) assay, in which WWR showed higher inhibition rates than LRR. The sulforaphane content of WRR was higher than that of LRR. In the lung cancer cell line, A-549, WRR showed higher inhibition rates and a higher total glucosinolate content than LRR. The glucosinolate contents of the radishes were analyzed by the Pd-quicktest method, showing that WRR contained more glucosinolate than LRR in both the trunk and root. In conclusion, these results indicate that wild race radish could be used for the quality improvement of radishes.

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