• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.21-28
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• 2001

Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.

• Journal of Food Hygiene and Safety
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• v.33 no.5
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• pp.354-360
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• 2018

This study presents a method validation for extraction and quantitative analysis of trichothecene mycotoxins in nuts based on quick, easy, cheap, effective, rugged, and safe (QuEChERS) approach for extraction and enhanced matrix removal (EMR)-lipid-disperive-SPE (d-SPE) cleanup method, with detection and quantification by high-performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) in positive- and negative-ion modes. Linearity, precision, and accuracy were validated for LC-MS/MS methods. Results obtained with LC-MS/MS were linear, with correlation coefficient ($R^2$) of 0.998. Limits of detection and quantification for mycotoxins were $0.41-3.57{\mu}g/kg$ and $1.23-10.82{\mu}g/kg$, respectively. Intra- and inter-day precisions (RSD, %) were 0.40-8.44% and 1.93-12.46%, respectively. Results indicated to be rapidly and accurately identifying trichothecene mycotoxins and may be used as a suitable safety management method for nuts and nuts related commodities.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.277-284
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• 2020

To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO₂ is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO₂. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO₂. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.

• Trans-
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• v.2
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• pp.161-190
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• 2017

As times progress, creative change is achieved by attempts to embrace different needs. These attempts are expressed as the form of an Object which pulls down the barriers of genre between art. There is now in fact difficult to find a work that doesn't contain the characteristic of an Object. The necessity of this study is that it tries to approach an Object with a holistic perspective and understand it as a single system. It also tries to analyze the roles that an Object's characteristic and expression and the research ways they influence the dance work by contemplating the aesthetic discussion process of an Object in the art field. Also, by researching the characteristics of expression and how Objects stimulate a dance work, this study will take an important part in developing the dance works. Based on this necessity, this research choose the works of William Forsythe, (2006), (2009), (2009) which clearly depicts the expression characteristics of an Object. It is noted that the usage of an Object maximized creativity and brought expansion of expressions in a dance performance by using diverse mediums, body actions and even nonmaterial components without losing the essence of a dance. As a result, this usage of an Object provides theories that bring the enlargement of expression and suggests various ways to overcome the limits of other existing dance works.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.104-115
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• 2013

In a shallow water waveguide, reverberation signals and their Doppler effects form the primary limitation on sonar system performance. Therefore, in the reverberation-limited environment, it is necessary to estimate the reverberation level to be encountered under the conditions in which the sonar system is operated. In this paper, high-frequency reverberation model capable of simulating the reverberation signals received by a high-speed moving source in a range independent waveguide is suggested. In this model, eigenray information from the source to each boundary is calculated using the ray-based approach and the optimizing method for the launch angles. And the source receiving position changed by the moving source is found by a scattering path-finding algorithm, which considers the speed and direction of source and sound speed to find the path of source movement. The scattering effects from sea surface and bottom boundaries are considered by APL-UW scattering models. The model suggested in this paper is verified by a comparison to the measurements made in August 2010. Lastly, this model reflects well statistical properties of the reverberation signals.

• Journal of Korea Water Resources Association
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• v.48 no.5
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• pp.367-377
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• 2015

ADCPs have been highlighted so far for measuring steramflow discharge in terms of their high-order of accuracy, relatively low cost and less field operators driven by their easy in-situ operation. While ADCPs become increasingly dominant in hydrometric area, their actual measurement accuracy for velocity and bathymetry measurement has not been sufficiently validated due to the lack of reliable bench-mark data, and subsequently there are still many uncertain aspects for using ADCPs in the field. This research aimed at analyzing inter-comparison results between ADCP measurements with respect to the detailed ADV measurement in a specified field environment. Overall, 184 ADV points were collected for densely designed grids for the given cross-section that has 6 m of width, 1 m of depth, and 0.7 m/s of averaged mean flow velocity. Concurrently, ADCP fixed-points measurements were conducted for each 0.2m and 0.02m of horizontal and vertical spacing respectively. The inter-comparison results indicated that ADCP matched ADV velocity very accurately for 0.4~0.8 of relative depth (y/h), but noticeable deviation occurred between them in near surface and bottom region. For evaluating the capacity of measuring bathymetry of ADCPs, bottom tracking bathymetry based on oblique beams showed better performance than vertical beam approach, and similar results were shown for fixed and moving-boat method as well. Error analysis for velocity and bathymetry measurements of ADCP can be potentially able to be utilized for the more detailed uncertainty analysis of the ADCP discharge measurement.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.241-249
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• 2006

Due to the long tectonic history and the very complex geologic formations in Korea, the anisotropic characteristics of subsurface material may often change very greatly and locally. The algorithms commonly used, however, may not give sufficiently precise computational results of traveltime data particularly for the complex and strong anisotropic model, since they are based on the two-dimensional (2D) earth and/or weak anisotropy assumptions. This study is intended to develope a three-dimensional (3D) modeling algorithm to precisely calculate the first arrival time in the complex anisotropic media. Considering the complex geology of Korea, we assume 3D TTI (tilted transversely isotropy) medium having the arbitrary symmetry axis. The algorithm includes the 2D non-linear interpolation scheme to calculate the traveltimes inside the grid and the 3D traveltime mapping to fill the 3D model with first arrival times. The weak anisotropy assumption, moreover, can be overcome through devising a numerical approach of the steepest descent method in the calculation of minimum traveltime, instead of using approximate solution. The performance of the algorithm developed in this study is demonstrated by the comparison of the analytic and numerical solutions for the homogeneous anisotropic earth as well as through the numerical experiment for the two layer model whose anisotropic properties are greatly different each other. We expect that the developed modeling algorithm can be used in the development of processing and inversion schemes of seismic data acquired in strongly anisotropic environment, such as migration, velocity analysis, cross-well tomography and so on.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.12
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• pp.60-69
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• 2000

This paper describes a single-chip full-custom implementation of pipelined adaptive decision-feedback equalizer(PADFE) using a 0.25-${\mu}m$ CMOS technology for wide-band wireless digital communication systems. To enhance the throughput rate of ADFE, two pipeline stages are inserted into the critical path of the ADFE by using delayed least-mean-square(DLMS) algorithm. Redundant binary (RB) arithmetic is applied to all the data processing of the PADFE including filter taps and coefficient update blocks. When compared with conventional methods based on two's complement arithmetic, the proposed approach reduces arithmetic complexity, as well as results in a very simple complex-valued filter structure, thus suitable for VLSI implementation. The design parameters including pipeline stage, filter tap, coefficient and internal bit-width, and equalization performance such as bit error rate (BER) and convergence speed are analyzed by algorithm-level simulation using COSSAP. The single-chip PADFE contains about 205,000 transistors on an area of about $1.96\times1.35-mm^2$. Simulation results show that it can safely operate with 200-MHz clock frequency at 2.5-V supply, and its estimated power dissipation is about 890-mW. Test results show that the fabricated chip works functionally well.

• Journal of Korea Water Resources Association
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• v.46 no.10
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• pp.1029-1040
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• 2013

This study aims to develop a multivariate daily rainfall simulation model considering spatial coherence across watershed. The existing Hidden Markov Model (HMM) has been mainly applied to single site case so that the spatial coherences are not properly addressed. In this regard, HMM coupled with Chow-Liu Tree (CLT) that is designed to consider inter-dependences across rainfall networks was proposed. The proposed approach is applied to Han-River watershed where long-term and reliable hydrologic data is available, and a rigorous validation is finally conducted to verify the model's capability. It was found that the proposed model showed better performance in terms of reproducing daily rainfall statistics as well as seasonal rainfall statistics. Also, correlation matrix across stations for observation and simulation was compared and examined. It was confirmed that the spatial coherence was well reproduced via CLT-HMM model.