• Title/Summary/Keyword: Data Paper

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A new model and testing verification for evaluating the carbon efficiency of server

  • Liang Guo;Yue Wang;Yixing Zhang;Caihong Zhou;Kexin Xu;Shaopeng Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2682-2700
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    • 2023
  • To cope with the risks of climate change and promote the realization of carbon peaking and carbon neutrality, this paper first comprehensively considers the policy background, technical trends and carbon reduction paths of energy conservation and emission reduction in data center server industry. Second, we propose a computing power carbon efficiency of data center server, and constructs the carbon emission per performance of server (CEPS) model. According to the model, this paper selects the mainstream data center servers for testing. The result shows that with the improvement of server performance, the total carbon emissions are rising. However, the speed of performance improvement is faster than that of carbon emission, hence the relative carbon emission per unit computing power shows a continuous decreasing trend. Moreover, there are some differences between different products, and it is calculated that the carbon emission per unit performance is 20-60KG when the service life of the server is five years.

A Study on Awareness and Experience of Data Publishing by Scientists (과학기술분야 연구자들의 데이터 출판경험 및 인식 연구)

  • Hyekyong Hwang;Youngim Jung;Sung-Nam Cho;Tae-Sul Seo;Jihyun Kim
    • Journal of Korean Library and Information Science Society
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    • v.54 no.1
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    • pp.45-68
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    • 2023
  • This study aims to investigate the awareness and experiences of domestic researchers regarding data publishing, which has been recognized as a new channel of data sharing as scholarly communication evolves in the open science environment. A survey is conducted among researchers from five government-funded research institutes in the field of science and technology and members of the GeoAI Data Society to confirm the awareness of data publishing. As a result of the study, domestic researchers recognized providing explanations for data, stable access to data, citation, and quality assurance through peer review as the advantages of data journals. On the contrary, a low level of recognition for data paper as one of the research outputs was presented. With regard to the properties of data publication, the respondents answered that the data description, metadata description, and permanent identifiers are highly related, however, their recognition of the relation between the properties of data publication and the data submission to a repository and data peer review was relatively low. Finally, to expand the data publication, the need for the development of an editorial system that supports data paper peer review and cross-linking to a data repository as well as the development of a repository that supports data citation was identified. This study on the domestic researchers' experience and awareness of data publishing can provide insights for the implementation of data publishing services and infrastructure in the future.

Development of Standard Golf Swing Motion Modeling System (골프 표준 스윙 자세 구현 시스템 개발)

  • 이지홍;조복기;김기웅;심형원;유병욱
    • Proceedings of the IEEK Conference
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    • 2002.06e
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    • pp.121-124
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    • 2002
  • This paper explains the system which finds the data of the joint of Wire Frame(that express the body structure of the golfer) from standard golf swing movie. Also, this paper used interpolation and the method which modify the distance between a joint and a close joint to general new joint data. Last this paper explains the system that make a standard golf swing attitude by continuous display the static attitude(which are formed with Wire Frame) of golf swing operations.

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Bayesian Inference for Littlewood-Verrall Reliability Model

  • Choi, Ki-Heon;Choi, Hae-Ja
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.1-9
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    • 2003
  • In this paper we discuss Bayesian computation and model selection for Littlewood-Verrall model using Gibbs sampling. A numerical example with a simulated data is given.

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A Design and Implementation of Real-time Video frame data Processing control for Block Matching Algorithm (고속블럭정합 알고리즘을 위한 실시간 영상프레임 데이터 처리 제어 방법의 설계 및 구현)

  • 이강환;황호정
    • Proceedings of the IEEK Conference
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    • 2001.06b
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    • pp.373-376
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    • 2001
  • This paper has been studied a real-time video frame data processing control that used the linear systolic array for motion estimation. The proposed data control processing provides to the input data into the multiple processor array unit(MPAU) from search area and reference block data. The proposed data control architecture has based on two slice band for input data processing. And it has no required external control logic blocks for input data as like reference block or search area data.

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Generic Multidimensional Model of Complex Data: Design and Implementation

  • Khrouf, Kais;Turki, Hela
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.643-647
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    • 2021
  • The use of data analysis on large volumes of data constitutes a challenge for deducting knowledge and new information. Data can be heterogeneous and complex: Semi-structured data (Example: XML), Data from social networks (Example: Tweets) and Factual data (Example: Spreading of Covid-19). In this paper, we propose a generic multidimensional model in order to analyze complex data, according to several dimensions.

Blending between machining data of surfaces (가공데이터로 주어진 곡면 간의 블렌딩)

  • Ju, Sang-Yoon;Jun, Cha-Soo
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.1
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    • pp.108-113
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    • 1993
  • This paper proposes a method for obtaining blend surfaces between machining data of surfaces. This blending algorithm consists of trangation, detection, tracing, construction of blend surfaces, and generation of machining data for the blend surfaces. Inpus of the algorithm are a blend radius and machining data of surfaces to be blended. CL data as well as CC data can be applied as an input machining data of the algorithm.

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A study on Code System of Latin Character to Improve Transmission Efficiency in Data Communications (데이터통신 전송효율과 라틴어 부호 체계 고찰)

  • Hong, Wan-Pyo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.761-776
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    • 2012
  • This paper proposes the revised Roman character code system using Unicode 3.0. The background of the paper is whether the Latin character code system th using in the world in Unicode V.3 is proper or not in the side of the transmission efficiency in data communications. In data communications, when the consecutive 4 bits or 8 bits of "0" bit from the information devices input into the line coder, its consecutive "0" bits are scrambled to the predetermined bit patterns to avoid the syncronization loss. The paper was based on the statistical data for the using frequency of the alphabet letter and the proposed rule for characters coding in [1]. The paper was focused to improve of Unicode itself and UTF-8 code system. As a result of the paper, when the proposed coding systems for Latin character in Unicode 3.0 itself and UTF-8 code system, the scrambler efficiency using HDB-3 in the line coder of the data transmission system could be improved about 3645 ~ 31400% and 480 ~ 1700% respectively.

The extension of the largest generalized-eigenvalue based distance metric Dij1) in arbitrary feature spaces to classify composite data points

  • Daoud, Mosaab
    • Genomics & Informatics
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    • v.17 no.4
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    • pp.39.1-39.20
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    • 2019
  • Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric Dij1) in any linear and non-linear feature spaces. We prove that Dij1) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of Dij1)) in classification of heterogeneous sets of biosequences compared with the decision rules min𝚵iand median𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

A Study on Improvement of Accounting Curriculum in Big Data Age (빅데이터시대의 회계교육과정 개선방안 연구)

  • Jeong, Eun-Han;Kim, Kyung-Ihl
    • Journal of Convergence for Information Technology
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    • v.8 no.5
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    • pp.145-152
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    • 2018
  • The paper aims to present the direction in which accounting education should proceed to enhance the expertise of accounting works in the new era in which big data is the center. This paper examines the definition and analysis of big data, and reviews the effectiveness through big data development in accounting expertise with specific references. Also, this paper presents some of the plans selected by professional accounting bodies and universities to address the topic of big data in the accounting curriculum. According to the plan, big data could provide a blueprint for the future role of accounting and financial experts. Therefore, what this study suggests is to improve educational content by adding big data topics to current accounting curricula in order to help accounting professionals of future generations prepare for technologies related to big data analysis in advance.