• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.299-314
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• 2017

Predicting compound-protein interactions in-silico is significant for the drug discovery. In this paper, we propose an scalable machine learning model to predict compound-protein interaction. The key idea of this scalable machine learning model is the architecture of pairwise neural network model and feature embedding method from the raw data, especially for protein. This method automatically extracts the features without additional knowledge of compound and protein. Also, the pairwise architecture elevate the expressiveness and compact dimension of feature by preventing biased learning from occurring due to the dimension and type of features. Through the 5-fold cross validation results on large scale database show that pairwise neural network improves the performance of predicting compound-protein interaction compared to previous prediction models.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.55-67
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• 2012

Real-time image georeferencing is required to generate spatial information rapidly from the image sequences acquired by multi-sensor systems. To complement the performance of position/attitude sensors and process in real-time, we should employ on-line aerial triangulation based on a sequential estimation algorithm. In this study, we thus attempt to derive an efficient on-line aerial triangulation algorithm for real-time georeferencing of image sequences. We implemented on-line aerial triangulation using the existing Given transformation update algorithm, and a new inverse normal matrix update algorithm based on observation classification, respectively. To compare the performance of two algorithms in terms of the accuracy and processing time, we applied these algorithms to simulated airborne multi-sensory data. The experimental results indicate that the inverse normal matrix update algorithm shows 40 % higher accuracy in the estimated ground point coordinates and eight times faster processing speed comparing to the Given transformation update algorithm. Therefore, the inverse normal matrix update algorithm is more appropriate for the real-time image georeferencing.

• Journal of computational fluids engineering
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• v.16 no.4
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• pp.39-46
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• 2011

A numerical study of a turbulent natural convection in an enclosure with the lattice Boltzmann method (LBM) is presented. The primary emphasis of the present study is placed on investigation of accuracy and numerical stability of the LBM for the turbulent natural convection flow. A HYBRID method in which the thermal equation is solved by the conventional Reynolds averaged Navier-Stokes equation method while the conservation of mass and momentum equations are resolved by the LBM is employed in the present study. The elliptic-relaxation model is employed for the turbulence model and the turbulent heat fluxes are treated by the algebraic flux model. All the governing equations are discretized on a cell-centered, non-uniform grid using the finite-volume method. The convection terms are treated by a second-order central-difference scheme with the deferred correction way to ensure accuracy and stability of solutions. The present LBM is applied to the prediction of a turbulent natural convection in a rectangular cavity and the computed results are compared with the experimental data commonly used for the validation of turbulence models and those by the conventional finite-volume method. It is shown that the LBM with the present HYBRID thermal model predicts the mean velocity components and turbulent quantities which are as good as those by the conventional finite-volume method. It is also found that the accuracy and stability of the solution is significantly affected by the treatment of the convection term, especially near the wall.

• Journal of computational fluids engineering
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• v.21 no.4
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• pp.102-111
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• 2016

In this paper a computation of turbulent natural convection in enclosures with the elliptic-blending based differential and algebraic flux models is presented. The primary emphasis of the study is placed on an investigation of accuracy of the treatment of turbulent heat fluxes with the elliptic-blending second-moment closure for the turbulent natural convection flows. The turbulent heat fluxes in this study are treated by the elliptic-blending based algebraic and differential flux models. The previous turbulence model constants are adjusted to produce accurate solutions. The proposed models are applied to the prediction of turbulent natural convections in a 1:5 rectangular cavity and in a square cavity with conducting top and bottom walls, which are commonly used for validation of the turbulence models. The relative performance between the algebraic and differential flux model is examined through comparing with experimental data. It is shown that both the elliptic-blending based models predict well the mean velocity and temperature, thereby the wall shear stress and Nusselt number. It is also shown that the elliptic-blending based algebraic flux model produces solutions which are as accurate as those by the differential flux model.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.20-30
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• 2014

To develop a unconventional gas reservoir, an analysis of tight rock property are required. Especially, conventional measurements are difficult to be applied to unconventional resources such as tight gas reservoir because the permeability are extremely low compared to a conventional gas reservoir. In this study, an apparatus was developed for measuring low permeability and porosity based on a pressure pulse decay method under unsteady state conditions. The apparatus was applied for measuring the porosity and permeability of tight sand core samples from Gyeongsang basin in Korea. As a validation of the measurement, regression analysis was carried out using the dimensionless pseudo-pressure between the measured data and analytical solution. The results show the correlation coefficients above 0.96. Therefore, it is believed that the apparatus has a high accuracy.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.5
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• pp.495-501
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• 2013

This paper describes a flexible wireless telemetering system using a mesoscale cantilever sensor, which is microfabricated with a patterned thin Ni-Cu foil on a resin substrate. The dynamic validation of the sensor has been conducted in a flow. The wireless telemetry is used to obtain data regarding the oscillating flows. It is shown that the sensor is nearly independent of the environmental temperature and is suitable for application to primary healthcare and diagnostic devices. It can be easily integrated with other modules for measuring physiological parameters, e.g., blood pressure, oxygen saturation, and heart rate, to increase the convenience and reliability of diagnosis. The precision and reliability of the sensor are also dependent on the design of the analog front-end and noise reduction techniques. It is shown that the present system's minimum interval between packet transmissions is ~16 ms.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.95-102
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• 2004

The COSMOS is an adaptive traffic control systems that can adjust signal timing parameters in response to various traffic conditions. To evaluate the performance of the COSMOS systems, the field study is only practical option because any evaluation tools are not available. To overcome this limitation, a newly integrated interfacing simulator between a microscopic simulation program and COSMOS was developed. In this paper, a detector module and a signal timing module as well as general feature of the simulator were described. A validation test was performed to verify the accuracy of the data flow within the simulator. It was shown that the accuracy level of information from the simulator was high enough for real application. Several practical comments on further studies were also included to enhance the functional specifications of the simulator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.10
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• pp.859-867
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• 2007

The objective of this study is to develop and validate a numerical method which can handle the multi-rotor aerodynamic characteristics. For the purpose of power estimation, table look-up method is implemented to the existing unsteady panel code that is coupled with a time-marching free wake model. Also, the Reynolds number scaling is implemented for the application to various regions of Reynolds number. The computed results are validated against the available experimental data for coaxial and tandem rotors. In the validation case for the coaxial rotor, more accurate result is acquired when the thickness effect is considered. The wake instability problem occurs at a particular separation distance between the rotors for tandem rotors. The wake instability is avoided by setting the single-rotor wake geometry as the initial wake geometry for the multi-rotor analysis. The estimated result for rotor separation effect is compared with the result of the momentum theory.

• Toxicological Research
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• v.17
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• pp.293-297
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• 2001

The international pharmaceutical and regulatory communities had been recognizing the limited utility of conventional rodent carcinogenicity study particularly on the second species, mouse, after intense investigation of carcinogenicity data base worldwide, and a new scheme for carcinogenicity testing for pharmaceuticals was proposed at the Expert Working Group on Safety in the International Conference on Harmonization (ICH) in 1996. CB6F 1-Tg rasH2 mouse carrying human prototype c-Ha-ras gene with its own promoter/enhancer is one oj the new carcinogenicity assay model for human cancer risk assessment. Studies have been conducted since 1992 to validate the transgenic (Tg) mice for rapid carcinogenicity test-ing, short term (26 weeks) studies with genotoxic (by Salmonella), non-genotoxic carcinogens, genotoxic non-carcinogens, non-genotoxic non-carcinogens revealed relatively high concordance oj the response of the Tg mouse with classical bioassay across classes of carcinogenic agents. Mechanistic basis for carcinogensis in the model are being elucidated in terms of the role of overexpression and/or point mutation of the transgene. This report review the initial studies of validation of the model and preliminary results of on-going ILSI HESI ACT project will be presented.