• Title/Summary/Keyword: data-based model

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GIS Application Model for Spatial Simulation of Surface Runoff from a Small Watershed( II) (소유역 지표유출의 공간적 해석을 위한 지리정보시스템의 응용모형(II) - 격자 물수지 모형을 위한 GIS응용 모형 개발 -)

  • 김대식;정하우;김성준;최진용
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.37 no.5
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    • pp.35-42
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    • 1995
  • his paper is to develop a GIS application model (GISCELWAB) for the spatial simulation of surface runoff from a small watershed. The model was constituted by three submodels : The input data extraction model (GISINDATA) which prepares cell-based input data automatically for a given watershed, the cell water balance model (CELWAB) which calculates the water balance for a cell and simulates surface runoff of watershed simultaneously by the interaction of cells, and the output data management model (GISOUTDISP) which visualize the results of temporal and spatial variation of surface runoff. The input data extraction model was developed to solve the time-consuming problems for the input-data preparation of distributed hydrologic model. The input data for CELWAB can be obtained by extracting ASCII data from a vector map. The output data management model was developed to convert the storage depth and discharge of cells into grid map. This model enables to visualize the spatial formulation process of watershed storage depth and surface runoff wholly with time increment.

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A Model-Based Image Steganography Method Using Watson's Visual Model

  • Fakhredanesh, Mohammad;Safabakhsh, Reza;Rahmati, Mohammad
    • ETRI Journal
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    • v.36 no.3
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    • pp.479-489
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    • 2014
  • This paper presents a model-based image steganography method based on Watson's visual model. Model-based steganography assumes a model for cover image statistics. This approach, however, has some weaknesses, including perceptual detectability. We propose to use Watson's visual model to improve perceptual undetectability of model-based steganography. The proposed method prevents visually perceptible changes during embedding. First, the maximum acceptable change in each discrete cosine transform coefficient is extracted based on Watson's visual model. Then, a model is fitted to a low-precision histogram of such coefficients and the message bits are encoded to this model. Finally, the encoded message bits are embedded in those coefficients whose maximum possible changes are visually imperceptible. Experimental results show that changes resulting from the proposed method are perceptually undetectable, whereas model-based steganography retains perceptually detectable changes. This perceptual undetectability is achieved while the perceptual quality - based on the structural similarity measure - and the security - based on two steganalysis methods - do not show any significant changes.

The Spreadsheet-Based Tool Model for Efficient MMORPG Data Management (효율적인 MMORPG 데이터 관리를 위한 스프레드시트 기반 툴 모델)

  • Kang, Shin-Jin;Kim, Chang-Hun
    • Journal of Korea Multimedia Society
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    • v.12 no.10
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    • pp.1457-1465
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    • 2009
  • In MMORPG development process, spreadsheet based data management has advantages in the handling of functions and analysis of large data set. But it has limitations in inserting, deleting, searching and relational management of that. In this paper, we proposed the spreadsheet based tool model for large data set for MMORPG development. Our system can reduce the risk of data management failure in MMORPG development process and improve the efficiency of data handling in the large-scale team.

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Integration of Gear Design Data using XML in the Web-based Environment (웹 기반 환경에서 XML을 이용한 기어 설계 데이터의 통합)

  • 정태형;박승현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.627-630
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    • 2001
  • XML is suitable to integrate various forms of engineering design data since it possesses the characteristics of both documents and data. In this research a web-based design system has been developed, which integrates various gear design data in the form of XML. The system generates XML document containing gear design data and transforms gear design data in the relational database into XML document form automatically. The XML documents are transmitted to gear modeler agent through SOAP, and then the agent is automatically executed and generates CAD model files and VRML files. The designer can check the generated VRML model of gear immediately in the web service.

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Research on Design of DDS-based Conventional Railway Signal Data Specification for Real-time Railway Safety Monitoring and Control (실시간 철도 안전관제를 위한 DDS 기반의 일반철도 신호 데이터 규격 설계 연구)

  • Park, Yunjung;Lim, Damsub;Min, Dugki;Kim, Sang Ahm
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.739-746
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    • 2016
  • The real-time railway safety monitoring and control system is for prevention of safety accidents, and this system adopts DDS (Data Distribution Service) standard based data transmission method to support integrated management of data from existing on-site safety detection devices. In this paper, we introduce the design of DDS-based data specification from on-site signal equipment on the conventional railway. For this, we (1) design UML data model of KRS SG 0062 standard which defines existing data specification, (2) define DDS Topics for DDS transmission and map KRS model to DDS Topic model, (3) suggest data transformation rules and (4) design network control QoS polices. In addition, we analysis actual on-site log data and validate our data specification design. DDS-based data transmission enables data compatibility among on-site devices and the real-time railway safety monitoring and control system, and allows efficient network management for a large amount of data transfer.

Empirical Study on Analyzing Training Data for CNN-based Product Classification Deep Learning Model (CNN기반 상품분류 딥러닝모델을 위한 학습데이터 영향 실증 분석)

  • Lee, Nakyong;Kim, Jooyeon;Shim, Junho
    • The Journal of Society for e-Business Studies
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    • v.26 no.1
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    • pp.107-126
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    • 2021
  • In e-commerce, rapid and accurate automatic product classification according to product information is important. Recent developments in deep learning technology have been actively applied to automatic product classification. In order to develop a deep learning model with good performance, the quality of training data and data preprocessing suitable for the model are crucial. In this study, when categories are inferred based on text product data using a deep learning model, both effects of the data preprocessing and of the selection of training data are extensively compared and analyzed. We employ our CNN model as an example of deep learning model. In the experimental analysis, we use a real e-commerce data to ensure the verification of the study results. The empirical analysis and results shown in this study may be meaningful as a reference study for improving performance when developing a deep learning product classification model.

A Method for Group Mobility Model Construction and Model Representation from Positioning Data Set Using GPGPU (GPGPU에 기반하는 위치 정보 집합에서 집단 이동성 모델의 도출 기법과 그 표현 기법)

  • Song, Ha Yoon;Kim, Dong Yup
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.3
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    • pp.141-148
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    • 2017
  • The current advancement of mobile devices enables users to collect a sequence of user positions by use of the positioning technology and thus the related research regarding positioning or location information are quite arising. An individual mobility model based on positioning data and time data are already established while group mobility model is not done yet. In this research, group mobility model, an extension of individual mobility model, and the process of establishment of group mobility model will be studied. Based on the previous research of group mobility model from two individual mobility model, a group mobility model with more than two individual model has been established and the transition pattern of the model is represented by Markov chain. In consideration of real application, the computing time to establish group mobility mode from huge positioning data has been drastically improved by use of GPGPU comparing to the use of traditional multicore systems.

A Simultaneous Perturbation Stochastic Approximation (SPSA)-Based Model Approximation and its Application for Power System Stabilizers

  • Ko, Hee-Sang;Lee, Kwang-Y.;Kim, Ho-Chan
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.506-514
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    • 2008
  • This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

Two Machine Learning Models for Mobile Phone Battery Discharge Rate Prediction Based on Usage Patterns

  • Chantrapornchai, Chantana;Nusawat, Paingruthai
    • Journal of Information Processing Systems
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    • v.12 no.3
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    • pp.436-454
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    • 2016
  • This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

Evaluation of Non-linear FEM Tunnel Analysis by using Hoek-Brown반s Insitu Rock Model (Hoek-Brown 암반모델을 이용한 비선형 유한요소 터널해석 및 평가)

  • Lee, Bong-Yeol;Kim, Gwang-Jin;Kim, Hak-Mun
    • Proceedings of the Korean Geotechical Society Conference
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    • 1994.09a
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    • pp.235-246
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    • 1994
  • At pre-construction design stage, most of the design data are based on the site investigation results or property estimation which often does not provide satisfactory output for the tunnel analysis. Nonlinear FEM tunnel analysis was cariied out by Hoek-Brown model which is principly semi-empirical design method based on insitu rock descriptions, rock test results as well as field measurement data. The results of the analytical methods from Hoek-Brown model and Mohr-Coulomb model are compared with the sige measurement data from two-NATM tunnel construction sites. It was found that the Hoek-Brown model can be satisfactorily adopted as a feed back analysis technique in order to examin the safety of NATM tunnel at any construction stage.

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