• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.3
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• pp.36-46
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• 1993

The purposes of this study are to develop three-layered Green-Ampt infiltration model considering temporal variation of physical properties of soil and to evaluate the model with field experiment on bare-tilled and soybean-growing soil plots under natural rainfalls. Infiltration tests were conducted on a sandy loam soil. The model has three-layered soil profile including a surface crust, a tilled layer, a subsoil and considers temporal variation of porosity, hydraulic conductivity, capillary pressure head on a tilled layer by natural rainfalls and canopy density variation of crop. Field measurement of porosity, average hydraulic conductivity and average capillary presure head on a tilled layer were conducted by soil sampler and air-entry permeameter at regular intervals-after tillage. It was found that temporal variation of porosity and average hydraulic conductivity might be expressed as a function of cumulative rainfall energy and average capillary pressure head might be expressed as a function of porosity of a tilled soil. The model was calibrated by an optimization technique, Hooke and Jeeves method using hourly surface runoff data. With the calibrated parameters, the model was verified satisfactorily.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.691-695
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• 2004

In recent years, mary studies for efact estimation of groudwater recharge has been performed. They can be categorized into three groups : analytical method by means of groundwater recession curve, water budget analysis based on watershed, and the method using groundwater model. Since groundwater recharge rate shows the spatial-temporal variability due to hydrogeological heterogeneity, existing studies have various limits to deal with these characteristics. The method of estimating daily recharge rate with spatial-temporal variation based on rainfall-runoff model is suggested in this study for this purpose. This method is expected to enhance existing indirect method by means of reflecting climatic conditions, land use and hydrogeological heterogeneity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.207-210
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• 2009

The time information of sptio-temporal data in synchronization system of a mobile environment can be applied according to time data of various kinds. However, that previous data is synchronized related with progress of synchronization operation is a problem when saving the time data of sptio-temporal data depends on the registration time. In this paper, classifies the time used as time data for synchronization data, defines time data model suitable for synchronization of sptio-temporal data and suggests a synchronization system which uses time data model.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1464-1471
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• 1999

This paper introduces complex-valued competitive learning neural network for spatio-temporal pattern recognition. There have been quite a few neural networks for spatio-temporal pattern recognition. Among them, recurrent neural network, TDNN, and avalanche model are acknowledged as standard neural network paradigms for spatio-temporal pattern recognition. Recurrent neural network has complicated learning rules and does not guarantee convergence to global minima. TDNN requires too many neurons, and can not be regarded to deal with spatio-temporal pattern basically. Grossberg's avalanche model is not able to distinguish long patterns, and has to be indicated which layer is to be used in learning. In order to remedy drawbacks of the above networks, unsupervised competitive learning using complex umber is proposed. Suggested neural network also features simultaneous recognition, time-shift invariant recognition, stable categorizing, and learning rate modulation. The network is evaluated by computer simulation with randomly generated patterns.

• Advances in Computational Design
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• v.8 no.3
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• pp.219-236
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• 2023

In this paper, finite element modeling of the laser ultrasonics (LU) process in ablation regime is of interest. The momentum resulting from the removal of material from the specimen surface by the laser beam radiation in ablation regime is modeled as a pressure pulse. To model this pressure pulse, two equations are required: one for the spatial distribution and one for the temporal distribution of the pulse. Previous researchers have proposed various equations for the spatial and temporal distributions of the pressure pulse in different laser applications. All available equations are examined and the best combination of the temporal and spatial distributions of the pressure pulse that provides the most accurate results is identified. This combination of temporal and spatial distributions has never been used for modeling laser ultrasonics before. Then by using this new model, the effects of variations in pulse duration and laser spot radius on the shape, amplitude, and frequency spectrum of ultrasonic waves are studied. Furthermore, the LU in thermoelastic regime is simulated by this model and compared with LU in ablation regime. The interaction of ultrasonic waves with a defect is also investigated in the LU process in ablation regime. Good agreement of the results obtained from the new finite element model and available experimental data confirms the accuracy of the proposed model.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.99-112
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• 1994

An important modelling requirement for multimedia systems is the representation of temporal constraints among several different media that ordinarily arise in multimedia application. The multimedia system which integrates various types of data is required to express voice, image, text and graphic data with simultaneousness or an arbitrary time intervals. The purpose of this study is to analyze the temporal reationships and synchronization among several different kinds of medium. Moreover, it proposes a Multimedia Display-Time Composition Model (MDTC Model) which guarantees a representation of any kind of temporal synchronization among more than two kinds of medium. The proposed model is applied to a company advertizing system. Finally, a multimedia authoring tool based on the MDTC Model is implemented.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.97-97
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• 2021

Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.209-212
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• 2011

Triangulation is a typical method to locate or identify the location, which requires inherently at least three pre-recognized reference points. In some cases, owing to out of reachability to communication facility the target node can not reachable always to three base stations. This paper presents a predictive method, which can estimate the location of the moving target node in real time even though the target could not get in touch with all three base stations. The method is based on the PID-controlled Moving Objects Spatio-Temporal Model Algorithm. This can predict the moving direction of the moving target, and then combine with the past target position information to judge accurately the location.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.17-28
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• 2002

Time is regarded as an essential feature of land information enabling to track historical landmarks of land uses, ownerships, and taxations based on cadastral maps. Object-oriented temporal modeling helps to simulate and imitate time-varying cadastral data in a chronological and persistent manner. The aim of study is to analyze the role of temporal cadastre tracing footprints of foregoing events in response to various needs and demands associated with historical information of cadastral transactions. In this paper, temporal cadastral object model (TCOM) is proposed to delineate object version history. As an evidence of a new approach and conceptual idea for the importance of temporal cadastre, a part of spatio-temporal processes is illustrated to explain major changes of cadastral map. The feasibility and application of the approach is confirmed by proof-of-concept of temporal cadastre in land information management.