• The Journal of Natural Sciences
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• v.5 no.1
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• pp.87-93
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• 1992

A robotically assisted field material handling system designed for loading and unloading of a planar pallet with a forklift in unstructured field environment is presented. The system uses combined acoustic/visual sensing data to define the position/orientation of the pallet and to determine the specific locations of the two slots of the pallet, so that the forklift can move close to the slot and engage it for transport. In order to reduce the complexity of the material handling operation, we have developed a method based on the integration of 2-D range data of Poraloid ultrasonic sensor along with 2-D visual data of an optical camera. Data obtained from the two separate sources complements each other and is used in an efficient algorithm to control this robotically assisted field material handling system . Range data obtained from two linear scannings is used to determine the pan and tilt angles of a pallet using least mean square method. Then 2-D visual data is used to determine the swing angle and engagement location of a pallet by using edge detection and Hough transform techniques. The limitations of the pan and tilt orientation to be determined arc discussed. The system developed is evaluated through the hardware and software implementation. The experimental results are presented.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.29-35
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• 2010

While diversification of the use of video in the prevalence of cheap video equipment, augmented reality can print additional real-world images and video image. Although many recent advent augmented reality techniques, currently attempting to correct the character recognition is performed. In this paper characters marked with a visual marker recognition, and the color to match the marker color of the characters finds. And, it was shown on the screen by the character recognition. In this paper, by applying the phoneme pattern segmentation algorithm by the horizontal projection, we propose to segment the phoneme to match the six types of Hangul representation. Throughout the experiment sample of phoneme segmentation using augmented reality showed proceeding result at each step, and the experimental results was found to be that detection rate was above 90%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.3
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• pp.9-17
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• 2000

In this paper we implement computer simulation system of 4FSK signal MODEM using Quadrature detector and analyze overall tranceiver system. We follow the FLEX wireless paging system standards and construct premodulation filter and data frame. We propose an efficient open loop symbol timing recovery algorithm which takes advantage of 128 bit length preamble pattern and also propose a 32 bit UW pattern which Is based on the optimal UW detection method, and excellent aperiodic autocorrelation characteristic. The BER simulation in the fading channel as well as AWGN is performed with BCH coding and Interleaving to the Quadrature detector system and it is shown that a high coding fain occurs in the fading channel rather than AWGN channel.

• Bulletin of the Korean Chemical Society
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• v.34 no.8
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• pp.2413-2418
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• 2013

Forensic and legal medicine require reliable data to indicate excessive alcohol consumption. Ethanol is oxidatively metabolized to acetate by alcohol dehydrogenase and non-oxidatively metabolized to ethyl glucuronide (EtG), ethyl sulfate (EtS), phosphatidylethanol, or fatty acid ethyl esters (FAEE). Oxidative metabolism is too rapid to provide biomarkers for the detection of ethanol ingestion. However, the non-oxidative metabolite EtG is a useful biomarker because it is stable, non-volatile, water soluble, highly sensitive, and is detected in body fluid, hair, and tissues. EtG analysis methods such as mass spectroscopy, chromatography, or enzyme-linked immunosorbent assay techniques are currently in use. We suggest that nuclear magnetic resonance (NMR) spectroscopy could be used to monitor ethanol intake. As with current conventional methods, NMR spectroscopy doesn't require complicated pretreatments or sample separation. This method has the advantages of short acquisition time, simple sample preparation, reproducibility, and accuracy. In addition, all proton-containing compounds can be detected. In this study, we performed $^1H$ NMR analyses of urine to monitor the ethanol and EtG. Urinary samples were collected over time from 5 male volunteers. We confirmed that ethanol and EtG signals could be detected with NMR spectroscopy. Ethanol signals increased immediately upon alcohol intake, but decreased sharply over time. In contrast, EtG signal increased and reached a maximum about 9 h later, after which the EtG signal decreased gradually and remained detectable after 20-25 h. Based on these results, we suggest that $^1H$ NMR spectroscopy may be used to identify ethanol non-oxidative metabolites without the need for sample pretreatment.

• Journal of The Korean Astronomical Society
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• v.45 no.6
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• pp.167-173
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• 2012

Inter-granular Bright Points (igBPs) are small-scale objects in the Solar photosphere which can be seen within dark inter-granular lanes. We present a new algorithm to automatically detect and extract igBPs. Laplacian and Morphological Dilation (LMD) technique is employed by the algorithm. It involves three basic processing steps: (1) obtaining candidate "seed" regions by Laplacian; (2) determining the boundary and size of igBPs by morphological dilation; (3) discarding brighter granules by a probability criterion. For validating our algorithm, we used the observed samples of the Dutch Open Telescope (DOT), collected on April 12, 2007. They contain 180 high-resolution images, and each has a $85{\times}68\;arcsec^2$ field of view (FOV). Two important results are obtained: first, the identified rate of igBPs reaches 95% and is higher than previous results; second, the diameter distribution is $220{\pm}25km$, which is fully consistent with previously published data. We conclude that the presented algorithm can detect and extract igBPs automatically and effectively.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.51-57
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• 2008

We present a modeling of constraint satisfaction problems and provide heuristic algorithms of backtracking search to optimize the frequency assignment. Our research objective is to find a frequency assignment that satisfies all the constraints using minimum number of frequencies while maximizing the number of community radio stations served for a given area. In order to get a effective solution, some ordering heuristics such as variable orderings and value orderings are provided to minimize the backtracking in finding all solutions within a limited time. To complement the late detection of inconsistency in the backtracking, we provide the consistency enforcing technique or constraint propagation to eliminate the values that are inconsistent with some constraints. By integrating backtracking search algorithms with consistency enforcing techniques, it is possible to obtain more powerful and effective algorithms of constraint satisfaction problems. We also provide the performance evaluation of proposed algorithms by comparing the theoretical lower bound and our computed solution.

• Convergence Security Journal
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• v.11 no.1
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• pp.25-32
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R_{sq}$.

• Convergence Security Journal
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• v.12 no.3
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• pp.19-26
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The log type hazard function applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).

• KSBB Journal
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• v.22 no.6
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• pp.393-400
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• 2007

Analysis of protein interactions/functions in a microarray format has been of great potential in drug discovery, diagnostics, and cell biology, because it is amenable to large-scale and high-throughput biological assays in a rapid and economical way. In recent years, the protein microarray have broaden their utility towards the global analysis of protein interactions on a proteome scale, the functional activity analysis based on protein interactions and post-translational modifications (PTMs), and the discovery of biomarkers through profiling of protein expression between sample and reference pool. As a promising tool for proteomics, the protein microarray technology has advanced outstandingly over the past decade in terms of surface chemistry, acquisition of relevant proteins on a proteomic level, and detection methods. In this article, we briefly describe various techniques for development of protein microarray, and introduce developmental state of protein microarray and its applications.

• Journal of the Korean Ceramic Society
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• v.40 no.11
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• pp.1073-1077
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• 2003

The Sn $O_2$-based gas sensors can detect inflammable and toxic gases of low concentration by the modulation of surface resistance, but they lack in selectivity on the whole. To give selectivity to the Sn $O_2$-based gas sensors, studies on the sensing mechanism, selective gas sensing materials and signal processing techniques are demanded. Ethanol (C$_2$ $H_{5}$OH) and acetonitrile ($CH_3$CN) were confirmed to undergo catalytic oxidation on Sn $O_2$ by gas chromatography. PdCl$_2$-doped Sn $O_2$ showed excellent sensitivity to ethanol and acetonitrile, while La$_2$ $O_3$-doped Sn $O_2$ showed excellent sensitivity to ethanol, but poor sensitivity to acetonitrile. Using these two sensors and pattern recognition, the selectivity to acetonitrile is greatly enhanced. The minimum detection level of acetonitrile was 15 ppm in air and 20 to 100 ppm when exposed to interfering gases together with acetonitrile.