• Title/Summary/Keyword: Data Share

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Distributed Data Management based on t-(v,k,1) Combinatorial Design (t-(v,k,1) 조합 디자인 기반의 데이터 분산 관리 방식)

  • Song, You-Jin;Park, Kwang-Yong;Kang, Yeon-Jung
    • The KIPS Transactions:PartC
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    • v.17C no.5
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    • pp.399-406
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    • 2010
  • Many problems are arisen due to the weakness in the security and invasion to privacy by malicious attacker or internal users while various data services are available in ubiquitous network environment. The matter of controlling security for various contents and large capacity of data has appeared as an important issue to solve this problem. The allocation methods of Ito, Saito and Nishizeki based on traditional polynomial require all shares to restore the secret information shared. On the contrary, the secret information can be restored if the shares beyond the threshold value is collected. In addition, it has the effect of distributed DBMS operation which distributes and restores the data, especially the flexibility in realization by using parameters t,v,k in combinatorial design which has regularity in DB server and share selection. This paper discuss the construction of new share allocation method and data distribution/storage management with the application of matrix structure of t-(v,k,1) design for allocating share when using secret sharing in management scheme to solve the matter of allocating share.

Analysis and Estimation for Market Share of Biologics based on Google Trends Big Data (구글 트렌드 빅데이터를 통한 바이오의약품의 시장 점유율 분석과 추정)

  • Bong, Ki Tae;Lee, Heesang
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.2
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    • pp.14-24
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    • 2020
  • Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

Scheduling algirithm of data sampling times in the real-time distributed control systems

  • Hong, Seung-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.112-117
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    • 1992
  • The Real-time Distributed Control Systems(RDCS) consist of several distributed control processes which share a network medium to exchange their data. Performance of feedback control loops in the RDCS is subject to the network-induced delays from sensor to controller and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of the control components which share a network medium. In this study, a scheduling algorithm of determining data sampling times is developed using the window concept, where the sampling data from the control components dynamically share a limited number of windows.

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The Amount of Earnings Per Share's Adjustment and Earnings Management

  • Paricheh, Monireh;Mehrazeen, Alireza;Shiri, Mahmoud Mousavi
    • The Journal of Industrial Distribution & Business
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    • v.4 no.1
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    • pp.15-21
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    • 2013
  • Purpose - Our goal was to determine whether there is a relationship between actual profits' deviation from the profits expected in earnings per share's adjustment announcements and the degree of apparent earnings management in annual financial statements. Research design, data, and methodology - The samples consisted of 133 companies from ten industries. The companies were selected among those listed in the stock exchange, and their data were examined covering the two-year period from 2008 to 2010. Tests were conducted using a regression model and SPSS statistical software. Results - The findings indicate the following. There is no significantly positive relationship among the last earnings per share's adjustment forecast, the first earnings forecast per share, and earnings management. Moreover, the amount of the latest earnings per share's adjustment forecast relative to its first forecast is not associated with the companies' discretionary accruals items. Finally, the hypothesis that a relationship exists between companies' latest adjustments of their earnings per share and earnings management was tested the results indicate that there is no such relationship. Conclusions - The study's results suggest that the amount of earnings per share's adjustment is not a motivation for earnings management.

ShareSafe: An Improved Version of SecGraph

  • Tang, Kaiyu;Han, Meng;Gu, Qinchen;Zhou, Anni;Beyah, Raheem;Ji, Shouling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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    • pp.5731-5754
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    • 2019
  • In this paper, we redesign, implement, and evaluate ShareSafe (Based on SecGraph), an open-source secure graph data sharing/publishing platform. Within ShareSafe, we propose De-anonymization Quantification Module and Recommendation Module. Besides, we model the attackers' background knowledge and evaluate the relation between graph data privacy and the structure of the graph. To the best of our knowledge, ShareSafe is the first platform that enables users to perform data perturbation, utility evaluation, De-A evaluation, and Privacy Quantification. Leveraging ShareSafe, we conduct a more comprehensive and advanced utility and privacy evaluation. The results demonstrate that (1) The risk of privacy leakage of anonymized graph increases with the attackers' background knowledge. (2) For a successful de-anonymization attack, the seed mapping, even relatively small, plays a much more important role than the auxiliary graph. (3) The structure of graph has a fundamental and significant effect on the utility and privacy of the graph. (4) There is no optimal anonymization/de-anonymization algorithm. For different environment, the performance of each algorithm varies from each other.

Design of P2P Server System to execute Dynamic Distribution Policy (동적 분배정책을 수행하는 P2P 서버 시스템의 설계)

  • 박정민;김홍일
    • Journal of Internet Computing and Services
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    • v.3 no.6
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    • pp.25-33
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    • 2002
  • The efficiency of the data share service of P2P method is decided by the maintaining guard method of a sharing list, This paper suggests the data sharing system of the P2P base that it should retain a shared data list at a client, The Server at a proposed system guards inclusively client. divided into several groups and at each individual group, a client appointed the TopHost uses the method guarding a free share list of a applicating group, The TopHost designs to execute it relating with server in case of the mergence and the division of a group as well as a maintaining management of a data share list, The efficiency of the suggested system regard the maintaining guard of groups formed of a client of the appropriate level of a kernel and exams examination to measure it through a really executed data share service.

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Analysis of market share attraction data using LS-SVM (최소제곱 서포트벡터기계를 이용한 시장점유율 자료 분석)

  • Park, Hye-Jung
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.879-886
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    • 2009
  • The purpose of this article is to present the application of Least Squares Support Vector Machine in analyzing the existing structure of brand. We estimate the parameters of the Market Share Attraction Model using a non-parametric technique for function estimation called Least Squares Support Vector Machine, which allows us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. Estimation by Least Squares Support Vector Machine technique makes it a good candidate for solving the Market Share Attraction Model. To illustrate the performance of the proposed method, we use the car sales data in South Korea's car market.

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An Algorithm of Determining Data Sampling Times in the Network-Based Real-Time Distributed Control Systems (네트워크를 이용한 실시간 분산제어시스템에서 데이터 샘플링 주기 결정 알고리듬)

  • Seung Ho Hong
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.1
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    • pp.18-28
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    • 1993
  • Processes in the real-time distributed control systems share a network medium to exchange their data. Performance of feedback control loops in the real-time distributed control systems is subject to the network-induced delays from sensor to controller, and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of control components which share a network medium. In this study, an algorithm of determining data sampling times is developed using the "window concept". where the sampling datafrom the control components dynamically share a limited number of windows. The scheduling algorithm is validated through the aimulation experiments.

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Study on Out-of-pocket Money among Medical Expenses of an Oriental Medical University Hospital (한방의료의 본인부담금 연구)

  • Shin Sang-Moon;Kang Sung-Wook
    • Journal of Society of Preventive Korean Medicine
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    • v.3 no.1
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    • pp.67-82
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    • 1999
  • This study was performed to investigate out-of-pocket money among medical expenses of an oriental medical university hospital by the use of internal data of an oriental hospital because medical insurance program data could not show us insuree's out-of-pocket money among medical expenses. The purpose of this study was to analyze out-of-pocket money among medical expenses of ambulatory and hospitalized patients. Under this purpose, We analyzed actual medical expenses data of 1389 out-patients and 858 in-patients of the oriental medical university hospital with 90 beds that could be approach to internal data from July 1, 1998 to March 31, 1999. The major findings are as follows : 1. In ambulatory patients, the cost share ratio of insuree & that of insurer was 90 : 10 respectly. 2. In hospitalized patients, the cost share ratio of insuree & that of insurer was 72 : 28 respectly.

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Estimating multiplicative competitive interaction model using kernel machine technique

  • Shim, Joo-Yong;Kim, Mal-Suk;Park, Hye-Jung
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.825-832
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    • 2012
  • We propose a novel way of forecasting the market shares of several brands simultaneously in a multiplicative competitive interaction model, which uses kernel regression technique incorporated with kernel machine technique applied in support vector machines and other machine learning techniques. Traditionally, the estimations of the market share attraction model are performed via a maximum likelihood estimation procedure under the assumption that the data are drawn from a normal distribution. The proposed method is shown to be a good candidate for forecasting method of the market share attraction model when normal distribution is not assumed. We apply the proposed method to forecast the market shares of 4 Korean car brands simultaneously and represent better performances than maximum likelihood estimation procedure.