• Title/Summary/Keyword: Cold data

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Correlated Locality Data Distribution Policy for Improving Performance in SSD

  • Park, Jung Kyu
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.2
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    • pp.1-7
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    • 2016
  • In this paper, we propose in this paper present a novel locality data allocation policy as COLD(Correlated Locality Data) allocation policy. COLD is defined as a set of data that will be updated together later. By distributing a COLD into a NAND block separately, it can preserve th locality. In addition, by handling multiple COLD simultaneously, it can obtain the parallelism among NAND chips. We perform two experiment to demonstrate the effectiveness of the COLD data allocation policy. First, we implement COLD detector, and then, analyze a well-known workload. And we confirm the amount of COLD found depending on the size of data constituting the COLD. Secondly, we compared the traditional page-level mapping policy and COLD for garbage collection overhead in actual development board Cosmos OpenSSD. Experimental results have shown that COLD data allocation policy is significantly reduces the garbage collection overhead. Also, we confirmed that garbage collection overhead vary depending on the COLD size.

Study on the Anthropometric and Body Composition Indices for Prediction of Cold and Heat Pattern

  • Mun, Sujeong;Park, Kihyun;Lee, Siwoo
    • The Journal of Korean Medicine
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    • v.42 no.4
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    • pp.185-196
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    • 2021
  • Objectives: Many symptoms of cold and heat patterns are related to the thermoregulation of the body. Thus, we aimed to study the association of cold and heat patterns with anthropometry/body composition. Methods: The cold and heat patterns of 2000 individuals aged 30-55 years were evaluated using a self-administered questionnaire. Results: Among the anthropometric and body composition variables, body mass index (-0.37, 0.39) and fat mass index (-0.35, 0.38) had the highest correlation coefficients with the cold and heat pattern scores after adjustment for age and sex in the cold-heat group, while the correlation coefficients were relatively lower in the non-cold-heat group. In the cold-heat group, the most parsimonious model for the cold pattern with the variables selected by the best subset method and Lasso included sex, body mass index, waist-hip ratio, and extracellular water/total body water (adjusted R2 = 0.324), and the model for heat pattern additionally included age (adjusted R2 = 0.292). Conclusions: The variables related to obesity and water balance were the most useful for predicting cold and heat patterns. Further studies are required to improve the performance of prediction models.

Densification Behavior of Metal Powder under Cold Compaction (냉간 압축 하에서 금속 분말의 치밀화 거동)

  • Lee, Sung-Chul;Kim, Ki-Tae
    • Proceedings of the KSME Conference
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    • 2001.06a
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    • pp.652-657
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    • 2001
  • Densification behavior of aluminum alloy(A16061) powder was investigated under cold compaction. Experimental data were obtained under triaxial compression with various loading conditions. A special form of the Cap model was proposed from experimental data of A16061 powder under triaxial compression. The proposed yield function and several yield functions in the literature were implemented into a finite element program (ABAQUS) to compare with experimental data for densification behavior of A16061 powder under cold isostatic pressing and die compaction. The agreement between finite element calculations from the proposed yield function and experimental data is very good under cold isostatic pressing and die compaction.

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Densification Behavior of Metal Powder Under Cold Compaction (냉간 압축 하에서 금속 분말의 치밀화 거동)

  • Lee, Seong-Cheol;Kim, Gi-Tae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.1
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    • pp.95-104
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    • 2002
  • Densification behavior of aluminum alloy(A16061) powder was investigated under cold compaction. Experimental data were obtained under triaxial compression with various loading conditions. A special form of the Cap model was proposed from experimental data of A16061 powder under triaxial compression. The proposed yield function and several yield functions in the literature were implemented into a finite element program (ABAQUS) to compare with experimental data for densifcation behavior of A16061 powder under cold isostatic pressing and die compaction. The agreement between finite element calculations from the proposed yield function and experimental data is very good under cold isostatic pressing and die compaction.

Densification Behavior of Nanocrystalline Ceramic Powder under Cold Compaction (냉간 압축 하에서 나노 세라믹 분말의 치밀화 거동)

  • Lee Sung-Chul;Kim Ki-Tae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.10 s.253
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    • pp.1242-1248
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    • 2006
  • Densification behavior of nanocrystalline titania powder was investigated under cold compaction. Experimental data were obtained under triaxial compression with various loading conditions. Lee and Kim proposed the Cap model by developing the parameters involved in the yield function of general Cap model and volumetric strain evolution under cold isostatic pressing. The parameters in the Drucker/Prager Cap model and the proposed model were obtained from experimental data under triaxial compression. Finite element results from the models were compared with experimental data for densification behavior of nanocystalline ceramic powder under cold isostatic pressing and die compaction. The proposed model agreed well with experimental data under cold compaction, but the Drucker/Prager Cap model underestimated at the low density range. Finite element results, also, show the relative density distribution of nanocystalline ceramic powder compacts is severe compared to conventional micron powder compacts with the same averaged relative density.

Supervised Learning-Based Collaborative Filtering Using Market Basket Data for the Cold-Start Problem

  • Hwang, Wook-Yeon;Jun, Chi-Hyuck
    • Industrial Engineering and Management Systems
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    • v.13 no.4
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    • pp.421-431
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    • 2014
  • The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

Addressing the Cold Start Problem of Recommendation Method based on App (초기 사용자 문제 개선을 위한 앱 기반의 추천 기법)

  • Kim, Sung Rim;Kwon, Joon Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.69-78
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    • 2019
  • The amount of data is increasing significantly as information and communication technology advances, mobile, cloud computing, the Internet of Things and social network services become commonplace. As the data grows exponentially, there is a growing demand for services that recommend the information that users want from large amounts of data. Collaborative filtering method is commonly used in information recommendation methods. One of the problems with collaborative filtering-based recommendation method is the cold start problem. In this paper, we propose a method to improve the cold start problem. That is, it solves the cold start problem by mapping the item evaluation data that does not exist to the initial user to the automatically generated data from the mobile app. We describe the main contents of the proposed method and explain the proposed method through the book recommendation scenario. We show the superiority of the proposed method through comparison with existing methods.

Determination of Cold Weather Concrete Periods Using Meteorological Data of Republic of Korea (기상자료를 이용한 한중콘크리트 적용 기간 산정)

  • Chung, Ji-Man;Han, Jun-Hui;Baek, Seong-Jin;Park, Jae-Woong;Kim, Jong;Han, Min-Cheol
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2023.11a
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    • pp.57-58
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    • 2023
  • This study is to estimate cold weather concrete periods by analyzing data of Korea Meteorological Administration in terms of recently revised cold weather concrete regulation of Korea Concrete Institute.

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Gramene database: A resource for comparative plant genomics, pathways and phylogenomics analyses

  • Tello-Ruiz, Marcela K.;Stein, Joshua;Wei, Sharon;Preece, Justin;Naithani, Sushma;Olson, Andrew;Jiao, Yinping;Gupta, Parul;Kumari, Sunita;Chougule, Kapeel;Elser, Justin;Wang, Bo;Thomason, James;Zhang, Lifang;D'Eustachio, Peter;Petryszak, Robert;Kersey, Paul;Lee, PanYoung Koung;Jaiswal, kaj;Ware, Doreen
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2017.06a
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    • pp.135-135
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    • 2017
  • The Gramene database (http://www.gramene.org) is a powerful online resource for agricultural researchers, plant breeders and educators that provides easy access to reference data, visualizations and analytical tools for conducting cross-species comparisons. Learn the benefits of using Gramene to enrich your lectures, accelerate your research goals, and respond to your organismal community needs. Gramene's genomes portal hosts browsers for 44 complete reference genomes, including crops and model organisms, each displaying functional annotations, gene-trees with orthologous and paralogous gene classification, and whole-genome alignments. SNP and structural diversity data, available for 11 species, are displayed in the context of gene annotation, protein domains and functional consequences on transcript structure (e.g., missense variant). Browsers from multiple species can be viewed simultaneously with links to community-driven organismal databases. Thus, while hosting the underlying data for comparative studies, the portal also provides unified access to diverse plant community resources, and the ability for communities to upload and display private data sets in multiple standard formats. Our BioMart data mining interface enable complex queries and bulk download of sequence, annotation, homology and variation data. Gramene's pathway portal, the Plant Reactome, hosts over 240 pathways curated in rice and inferred in 66 additional plant species by orthology projection. Users may compare pathways across species, query and visualize curated expression data from EMBL-EBI's Expression Atlas in the context of pathways, analyze genome-scale expression data, and conduct pathway enrichment analysis. Our integrated search database and modern user interface leverage these diverse annotations to facilitate finding genes through selecting auto-suggested filters with interactive views of the results.

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A Study of the Cap Model for Metal and Ceramic Powder under Cold Compaction (냉간 압축 하에서 금속 및 세라믹 분말에 대한 캡 모델의 연구)

  • Lee, Sung-Chul;Kim, Ki-Tae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.11 s.254
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    • pp.1376-1383
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    • 2006
  • Densification behavior of various metal and ceramic powders was investigated under cold compaction. The Cap model was proposed by using the parameters involved in the yield function for sintered metal powder and volumetric strain evolution under cold isostatic pressing. The parameters for ceramic powder can also be obtained from experimental data under triaxial compression. The Cap model was implemented into a finite element program (ABAQUS) to compare with experimental data for densification behavior of various metal and ceramic powders under cold compaction. The agreement between finite element calculations from the Cap model and experimental data is very good for metal and ceramic powder under cold compaction.