• Title/Summary/Keyword: data-based model

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The Lower Flash Points of the n-Butanol+n-Decane System

  • Dong-Myeong Ha;Yong-Chan Choi;Sung-Jin Lee
    • Fire Science and Engineering
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    • v.17 no.2
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    • pp.50-55
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    • 2003
  • The lower flash points for the binary system, n-butanol+n-decane, were measured by Pensky-Martens closed cup tester. The experimental results showed the minimum in the flash point versus composition curve. The experimental data were compared with the values calculated by the reduced model under an ideal solution assumption and the flash point-prediction models based on the Van Laar and Wilson equations. The predictive curve based upon the reduced model deviated form the experimental data for this system. The experimental results were in good agreement with the predictive curves, which use the Van Laar and Wilson equations to estimate activity coefficients. However, the predictive curve of the flash point prediction model based on the Willson equation described the experimentally-derived data more effectively than that of the flash point prediction model based on the Van Laar equation.

Biomechanical analysis of human foot using the computer graphic-based model during walking (컴퓨터 그래픽 모델을 통한 보행 시 발의 생체역학적 해석)

  • 최현기;김시열;이범현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.1088-1092
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    • 2002
  • The purpose of this investigation was to study the kinematics of joints between foot segments based on computer graphic-based model during the stance phase of walking. In the model, ail joints were assumed to act as monocentric, single degree of freedom hinge joints. The motion of foot was captured by a video collection system using four cameras. The model fitted in an individual subject was simulated with this motion data. The kinematic data of tarsometatarsal joints and metatarso-phalangeal joint were quantitatively similar to the previous data. Therefore, our method using the computer graphic-based model is considered useful.

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Design of an Aquaculture Decision Support Model for Improving Profitability of Land-based Fish Farm Based on Statistical Data

  • Jaeho Lee;Wongi Jeon;Juhyoung Sung;Kiwon Kwon;Yangseob Kim;Kyungwon Park;Jongho Paik;Sungyoon Cho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.8
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    • pp.2431-2449
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    • 2024
  • As problems such as water pollution and fish species depletion have become serious, a land-based fish farming is receiving a great attention for ensuring stable productivity. In the fish farming, it is important to determine the timing of shipments, as one of key factors to increase net profit on the aquaculture. In this paper, we propose a system for predicting net profit to support decision of timing of shipment using fish farming-related statistical data. The prediction system consists of growth and farm-gate price prediction models, a cost statistics table, and a net profit estimation algorithm. The Gaussian process regression (GPR) model is exploited for weight prediction based on the analysis that represents the characteristics of the weight data of cultured fish under the assumption of Gaussian probability processes. Moreover, the long short-term memory (LSTM) model is applied considering the simple time series characteristics of the farm-gate price data. In the case of GPR model, it allows to cope with data missing problem of the weight data collected from the fish farm in the time and temperature domains. To solve the problem that the data acquired from the fish farm is aperiodic and small in amount, we generate the corresponding data by adopting a data augmentation method based on the Gaussian model. Finally, the estimation method for net profit is proposed by concatenating weight, price, and cost predictions. The performance of the proposed system is analyzed by applying the system to the Korean flounder data.

The Life Cycle Model Considering Legal and Technical Characteristics of Personal Data (개인정보의 법적·기술적 특성을 고려한 라이프 사이클(Life Cycle) 모델)

  • Jang, Jae-Young;Park, Tae-Hwan;Kim, Beom-Soo
    • The Journal of Society for e-Business Studies
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    • v.17 no.3
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    • pp.43-60
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    • 2012
  • This study reviews the life cycle models considering legal and technical characteristics of personal data respectively. Based on the reviews, this research proposes 'consent and management based model of personal data' which is applicable to the domestic IT companies. The model suggested in this paper has characteristics that 'Consent' and 'Management' factors are ㅁpositively considered, which is overlooked in the other models. The validity of the model is examined by two methods, validation of the model of excellence by contrast of the other models, and 'consent' and 'management' factors cover all the life cycle processes. Using this model, IT companies will be contributed to the analysis of the personal data utilization and the development of IT system protection.

Activity Capability Level-based Maturity Evaluation Model for Public Data Quality Management (활동능력수준 기반의 공공데이터 품질관리 성숙수준 평가 모델)

  • Kim, Sun-Ho;Lee, Jin-Woo;Lee, Chang-Soo
    • Informatization Policy
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    • v.24 no.1
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    • pp.30-47
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    • 2017
  • The Korean government developed an organizational maturity model for public data quality management based on international standards to evaluate the data quality management level of public organizations, However, as the model has too many indicators to apply on the site, a new model with reduced number of indicators is proposed in this paper. First, the number of processes is reduced by integrating and modifying the processes of the previous model. Second, a new maturity evaluation method is proposed based on capability levels focused on the activity, not on the process. Third, the maturity level of public data quality management is represented by five discrete levels or real values of 1 through 5. Finally, characteristics of the proposed model are compared with those of the previous model.

Role-Based Access Control in Object-Oriented GIS (객체지향 지리정보시스템에서의 역할 기반 접근 제어)

  • Kim, Mi-Yeon;Lee, Cheol-Min;Lee, Dong-Hoon;Moon, Chang-Joo
    • Journal of Information Technology Applications and Management
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    • v.14 no.3
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    • pp.49-77
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    • 2007
  • Role-based access control (RBAC) models are recently receiving considerable attention as a generalized approach to access control. In line with the increase in applications that deal with spatial data. an advanced RBAC model whose entities and constraints depend on the characteristics of spatial data is required. Even if some approaches have been proposed for geographic information systems. most studies focus on the location of users instead of the characteristics of spatial data. In this paper. we extend the traditional RBAC model in order to deal with the characteristics of spatial data and propose new spatial constraints. We use the object-oriented modeling based on open GIS consortium geometric model to formalize spatial objects and spatial relations such as hierarchy relation and topology relation. As a result of the formalization for spatial relations. we present spatial constraints classified according to the characteristics of each relation. We demonstrate our extended-RBAC model called OOGIS-RBAC and spatial constraints through case studies. Finally. we compare our OOGIS-RBAC model and the DAC model in the management of access control to prove the efficiency of our model.

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Hierarchical Flow-Based Anomaly Detection Model for Motor Gearbox Defect Detection

  • Younghwa Lee;Il-Sik Chang;Suseong Oh;Youngjin Nam;Youngteuk Chae;Geonyoung Choi;Gooman Park
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1516-1529
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    • 2023
  • In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

Testing the exchange rate data for the parameter change based on ARMA-GARCH model

  • Song, Junmo;Ko, Bangwon
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1551-1559
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    • 2013
  • In this paper, we analyze the Korean Won/Japanese 100 Yen exchange rate data based on the ARMA-GARCH model, and perform the test for detecting the parameter changes. As a test statistics, we employ the cumulative sum (CUSUM) test for ARMA-GARCH model, which is introduced by Lee and Song (2008). Our empirical analysis indicates that the KRW/JPY exchange rate series experienced several parameter changes during the period from January 2000 to December 2012, which leads to a fitting of AR-IGARCH model to the whole series.

A Study on the Noisy Speech Recognition Based on the Data-Driven Model Parameter Compensation (직접데이터 기반의 모델적응 방식을 이용한 잡음음성인식에 관한 연구)

  • Chung, Yong-Joo
    • Speech Sciences
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    • v.11 no.2
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    • pp.247-257
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    • 2004
  • There has been many research efforts to overcome the problems of speech recognition in the noisy conditions. Among them, the model-based compensation methods such as the parallel model combination (PMC) and vector Taylor series (VTS) have been found to perform efficiently compared with the previous speech enhancement methods or the feature-based approaches. In this paper, a data-driven model compensation approach that adapts the HMM(hidden Markv model) parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional model-based methods such as the PMC, the statistics necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared with the PMC for the noisy speech recognition.

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A Study on Location-Based Services Based on Semantic Web

  • Kim, Jong-Woo;Kim, Ju-Yeon;Kim, Chang-Soo
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1752-1761
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    • 2007
  • Location-based services are a recent concept that integrates a mobile device's location with other information in order to provide added value to a user. Although Location-based Services provide users with comfortable information, it is a complex task to manage and share heterogeneous and numerous data in decentralized environments. In this paper, we propose the Semantic LBS Model as one of the solution to resolve the problem. The Semantic LBS Model is a LBS middleware model that includes an ontology-based data model for LBS POI information and its processing mechanism based on Semantic Web technologies. Our model enables POI information to be described and retrieved over various domain-specific ontologies based on our proposed POIDL ontology. This mechanism provide rich expressiveness, interoperability, flexibility in describing and using information about POls, and it can enhance POI retrieval services.

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