• Smart Media Journal
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• v.9 no.2
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• pp.22-32
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• 2020

The hippocampal volume atrophy is known to be linked with neuro-degenerative disorders and it is also one of the most important early biomarkers for Alzheimer's disease detection. The measurements of hippocampal pure volumes from Magnetic Resonance Imaging (MRI) is a crucial task and state-of-the-art methods require a large amount of time. In addition, the structural brain development is investigated using MRI data, where brain morphometry (e.g. cortical thickness, volume, surface area etc.) study is one of the significant parts of the analysis. In this study, we have proposed a patch-based ensemble model of 3-D convolutional neural network (CNN) to measure the hippocampal pure volume from MRI data. The 3-D patches were extracted from the volumetric MRI scans to train the proposed 3-D CNN models. The trained models are used to construct the ensemble 3-D CNN model and the aggregated model predicts the pure volume in one-step in the test phase. Our approach takes only 5 seconds to estimate the volumes from an MRI scan. The average errors for the proposed ensemble 3-D CNN model are 11.7±8.8 (error%±STD) and 12.5±12.8 (error%±STD) for the left and right hippocampi of 65 test MRI scans, respectively. The quantitative study on the predicted volumes over the ground truth volumes shows that the proposed approach can be used as a proxy.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.157-163
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• 2011

In this study, after the target basin was divided into both overland and channel grids, the travel time from center of each grid cell to watershed's outlet was calculated based on the manning equation. Through this process, volumetric discharge was calculated according to the isochrones and finally, the direct runoff hydrograph was estimated considering watershed's hydrodynamic characteristics. Sanseong subwatershed located in main stream of Bocheong basin was selected as a target basin. The model parameters are only two: area threshold and channel velocity correction factor; the optimized values were estimated at 3,800 and 3.3, respectively. The developed model based on the tuned parameters led to well-matching results between observed and calculated hydrographs (mean of absolute error of peak discharge: 3.41%, mean of absolute error of peak time: 0.67 hr). Moreover, the analysis results regarding histogram of travel time-contribution area demonstrates that the proposed model characterizes relatively well hydrodynamic characteristics of the catchment due to effective rainfall.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.16-25
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• 2009

Testing engine performance using an engine dynamometer requires high technical researchers and many facilities. Nowadays, different variables of CAE program are used for identifying the engine performance instead of engine dynamometer test. This is more convenience, as it does not necessitate an abundance of engine dynamometer experiments and, in addition, produces better results. However, CAE programs also contain various variables which can affect engine performance. Those are coupled with each other, thus making it difficult to determine the effectiveness of different variables on engines. DoE (Design of Experiments) methodology is an efficient way to verify the magnitude of effectiveness on engine performance as well as making responses to be optimized at once without trial & error. This study used data from WAVE simulations, which modeled the DOHC SI engine with in-line 4 cylinders at 1500, 3000 and 4500rpm. DoE methodology is designed properly to determine the effectiveness of five variables on power, BSFC, and volumetric efficiency, as well as to find the optimal response conditions at each rpm through a minimized number of experiments. After finishing DoE process, all the results are examined concerning the reliability of test through a verification experiment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1887-1891
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• 2005

Despite significant advances in multimedia transferring technologies in various fields of robotics, it is sometimes quite difficult for the operator to fully understand the context of 3D remote environments from 2D image feedback. Particularly, in the remote control of mobile robots, the recognition of the object associated with the task is very important, because the operator has to control the robot safely in various situations not through trial and error. Therefore, it is necessary to provide the operator with 3D volumetric models of the object and object-related information as well such as locations, shape, size, material properties, and so on. Thus, in this paper, we propose a vision-based human interface system that provides an interactive, information-rich map through network-based information brokering. The system consists of an object recognition part, a 3D map building part, a networked knowledge base part, and a control part of the mobile robot.

• Computers and Concrete
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• v.7 no.5
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• pp.469-482
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• 2010

This paper investigates the concrete permeability through a numerical and statistical approach. Concrete is considered as a random heterogeneous composite of three phases: aggregates, interfacial transition zones (ITZ) and matrix. The paper begins with some classical bound and estimate theories applied to concrete permeability and the influence of ITZ on these bound and estimate values is discussed. Numerical samples for permeability analysis are established through random aggregate structure (RAS) scheme, each numerical sample containing randomly distributed aggregates coated with ITZ and dispersed in a homogeneous matrix. The volumetric fraction of aggregates is fixed and the size distribution of aggregates observes Fuller's curve. Then finite element method is used to solve the steady permeation problem on 2D numerical samples and the overall permeability is deduced from flux-pressure relation. The impact of ITZ on overall permeability is analyzed in terms of ITZ width and contrast ratio between ITZ and matrix permeabilities. Hereafter, 3680 samples are generated for 23 sample sizes and 4 contrast ratios, and statistical analysis is performed on the permeability dispersion in terms of sample size and ITZ characteristics. By sample theory, the size of representative volume element (RVE) for permeability is then quantified considering sample realization number and expected error. Concluding remarks are provided for the impact of ITZ on concrete permeability and its statistical characteristics.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.195-200
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• 2006

Laboratory creep experiments show that compaction of unconsolidated shale is an irrecoverable process caused by viscous time-dependent deformation. Using Perzyna's viscoplasticity framework combined with the modified Cam-clay theory, we found the constitutive equation expressed in the form of strain rate as a power law function of the ratio between the sizes of dynamic and static yield surfaces. We derived the volumetric creep strain at a constant hydrostatic pressure level as a logarithmic function of time, which is in good agreement with experimental results. The determined material constants indicate that the yield stress of the shale increases by 6% as strain rate rises by an order of magnitude. This demonstrates that the laboratory-based prediction of yield stress (and porosity) may result in a significant error in estimating the properties in situ.

• Geotechnical Engineering
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• v.8 no.2
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• pp.81-96
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• 1992

This paper dealt with the influence of experimental error generated inevitably during performing experiments on the granular soil behaviour analysis selecting Lade's Single Work-Hardening constitutive model. Several isotropic compression-expansion tests and a series of drained conventional triaxial tests with various confining pressures for Baekma river sands were performed and the values of parameters for the above model were determined using computer program developed for this study based on regression analysis. By finding the range of the upper and lower bound for deviator stress and volumetric strain versus axial strain dependant on the increase and decrease of the standard deviation from mean value of parameters, sensitivities of all the parameters were examined. Practical use of program to determine the parameters and capability to predict the behaviour of granular soil by Lade's Single Work -Hardening model verified.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.57-63
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• 2017

In the paper, we propose a new reliable technique for measuring food intake based on image automatically without user intervention. First, food and bowl image before and after meal is obtained by user. The food and the bowl are divided into each region by the K-means clustering, Otsu algorithm, Morphology, etc. And the volume of food is measured by a proportional expression based on the information of the container such as it's entrance diameter, depth, and bottom diameter. Finally, our method calculates the volume of the consumed food by the difference between before and after meal. The proposed technique has higher accuracy than existing method for measuring food intake automatically. The experiment result shows that the average error rate is up to 7% for three types of containers. Computer simulation results indicate that the proposed algorithm is a convenient and accurate method of measuring the food intake.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.2
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• pp.193-204
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• 1999

Performance of a variable-speed, roller-type vane compressor was evaluated at low evaporating temperature. First, an experimental investigation was conducted to examine the performance variation as functions of both outdoor temperature and rotating speed. For this purpose, a typical heat pump was implemented as a test apparatus to measure mass flow rate and power input. Secondly, computational investigations corresponding to the heat pump test conditions were performed to predict compressor performance using ORNL Map-Based compressor model. Results obtained from the heat-pump experiments showed that both mass flow rate and power consumption were sensitively dependent on both evaporating temperature and compressor speed as was predicted from the computational results. From the comparisons of both experimental and computational results, it was well recognized that the ORNL model was subjected to larger error in the accuracy of prediction as outdoor temperature decreased. When the outdoor temperature was above $-5^{\cire}C$, errors of predicted values corresponding to both mass flow rate and power consumption were estimated as $\pm$10% and $\pm$ 15%, respectively. Finally, it is suggested that the ORNL model needs to be re-evaluated if compressor map data tested below $-5^{\cire}C$(in evaporating temperature) are available.