• Analytical Science and Technology
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• v.15 no.4
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• pp.335-340
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• 2002

An analytical method has been developed to determine multi-elements in human hair samples by inductively coupled plasma mass spectrometry (ICP-MS). 0.05 g of hair sample was added to the Teflon digestion bomb together with 1.5 mL of nitric acid and an appropriate amount of In as an internal standard. The sample was then decomposed in the microwave digestion system. The hair certified reference material, GBW 09101, was analyzed for the validation of the analytical method. The determined values were in good agreement with the certified values within the uncertainty range.

• Journal of the korean society of oceanography
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• v.38 no.4
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• pp.166-172
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• 2003

Multi­Sensor Core Logger (MSCL) is a useful system for logging the physical properties (compressional wave velocity, wet bulk density, fractional porosity, magnetic susceptibility and/or natural gamma radiation) of marine sediments through scanning of whole cores in a nondestructive fashion. But MSCL has a number of problems that can lead to spurious results depending on the various factors such as core slumping, gas expansion, mechanical stretching, and the thickness variation of core liner and sediment. For the verification of MSCL data, compressional wave velocity, wet bulk density, and porosity were measured on discrete samples by Hamilton Frame and Gravimetric method, respectively. Acoustic impedance was also calculated. Physical property data (velocity, wet bulk density, and impedance) logged by MSCL were slightly larger than those of discrete sample, and porosity is reverse. Average difference between MSCL and discrete sample at both sites is relatively small such as 22­24 m/s in velocity, $0.02­-0.08\;g/\textrm{cm}^3$ in wet bulk density, and 2.5­2.7% in porosity. The values also show systematic variation with sediment depth. A variety of factors are probably responsible for the differences including instrument error, various measurement method, sediment disturbance, and accuracy of calibration. Therefore, MSCL can be effectively used to collect physical property data with high resolution and quality, if the calibration is accurately completed.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.79-114
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• 2018

Although former scholarly studies mostly focus on exploring leadership effectiveness under the traditional hierarchical leader-subordinate relationship, the research of leadership performance for non-hierarchical organizational structures, particularly the mediating factors of higher-order goals, trust-in-leader, and self-efficacy have been ignored. This study, therefore, makes an attempt to ascertain the impacts of transformational leadership on the performance of subordinates through the mediating effects of higher-order goals, trust-in-leader, and self-efficacy and the differences of these effects in the context of multi-level marketing (MLM). Like the small-sample studies adopted by Barling, Weber, and Kelloway [1996], Barling, Slater, and Kelloway [2000] and Bass, Avolio, Jung, and Berson [2003], this study adopts a sample of 123 MLM distributors of an MLM company in Hong Kong, with a high response rate of 80.4%. The results indicate that the mediating effect of self-efficacy between transformational leadership and performance is significant under non-hierarchical organizational structures such as MLM in China.

• Environmental Mutagens and Carcinogens
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• v.15 no.2
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• pp.106-114
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• 1995

A method was developed to detect total mutagenicity of fried fish for S. typhimurium TA98, using Ames assay. Method described herein circumvented problems associated with the sample preparation for Ames assay, i.e., a multi-purification step of sample and interference with solvent residuals. Experiment A, the best method developed in the present study, consisted of two important steps: pH adjustment of the aqueous sample solution from fried fish samples to remove impurities, and simultaneous distillation extraction (SDE) for partially purified samples to remove volatile compounds from solvents. The procedure and results were described as below. Fillet of gizzard shad (Konosirus punctatus) fish sample fried for 10 min each side on the temperature-controlled fry-pan (210$\circ$C) was homogenized in an aqueous acidic solution (pH 2) with a homogenizer, followed by filtration through Celite. The tiltrate (pH 2), removed some impurities by extraction with chloroform:methanol (2:1, v/v) mixture, was adjusted pH to 10 and then centrifuged to remove precipitate. The ethylacetate extract from the tiltrate of pH 10 was rotoevaporated and purified by SDE apparatus for 2 hours. Experiment A revealed significantly higher revertants (1928 per 25 g fried sample) than other Experiment (B, C, or D) tested. Experiment A gave good results in the mutagenicity test of fried fish sample with few purification steps using only 25 g fried sample and 650 ml of solvents; and thus this method could be a useful tool for the screening the mutagenicity or antimutagenicity of other foods as well.

• Fashion & Textile Research Journal
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• v.12 no.3
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• pp.318-326
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• 2010

The advantages of the multi-channel retailing have been widely discussed but empirical research on fashion multi-channel retailing has been limited. In this study, multi-channel concept was discussed and then, channel choosing condition of apparel shopper and channel choosing criteria for information search and buying were investigated as a empirical study. Drawing on a sample of 298 customers of apparel products in Korea, the result demonstrated that some differences in the perception of experience goods and search goods among apparel products. And, according to buying channel, consumers were different from each other in information search time and clothing expenses. Some suggestion for the future research of multi-channel retailing was given.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.997-1000
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• 2004

This paper introduces our basic research about a carbon nanotube(CNT) sample for the fabrication of nanotweezer. We have made the nanotweezer through the physical adhesion of multi-walled carbon nanotubes(MWCNTs) on two sharp tungsten tips. Thereby we needed the CNT sample which is proper to this fabrication process. And we applied the dielectrophoretic methods to the fabrication of the CNT sample. During the basic experiment, we used a sharp edged electrode and a flat electrode as electrodes for dielectrophoresis and just a function generator as a voltage source for the generation of electric field.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.68-73
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• 1999

Generally, most of machining processes are done according to the dimention of the draft made by CAD. However, there are many cases that a sample is given without the draft because of the simplicity of the shape in the machining of 2D objects. To cut the same shape as the given sample, this paper proposes the method to extract the geometric information about a large sample using the robot vision and to draw the demensional draft for the machining. Because the resolution of one frame in the vision system is too low, it is necessary to set up a camera according to the desired resolution and to capture the image moving along the contour. And the overall outline can be compounded of the sequentially captured images. In the experiment, we compared the product after the cutting with the original sample and found that the size of two objects was coincided within the allowed error bound.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.145-152
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• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.388-389
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• 2005

In this paper, the electric properties of mercury Iodide multi-layer samples has been investigated. We measured and analyzed their performance parameters such as the X-ray sensitivity and dark-current for a mercury Iodide multi-layer X-ray detector with a dielectric layer. The digital X-ray image detector can be constructed by integrating photoconduction multi-layer that dielectric layer has characteristics of low dark-current, high X-ray sensitivity. However this process has found to have complexity on the performance of the sample. We have investigate dielectric layer that it substitute dielectric layer for HgO(Mercury Oxide). We have employed two approaches for producing the mercury Iodide sample : 1) Physical Vapor Deposition(PVD) and 2) Particle-In-Binder(PIB). In this paper fabricated by PIB Method with thicknesses ranging from approximately 180um to 240um and we could produce high-quality samples for each technique particular application. As results, the dielectric materials such as HgO between the dielectric layer and the top electrode may reduce the dark-current of the samples. Mercury Iodide multi-layer having HgO has characteristics of low dark-current, high X-ray sensitivity and simple processing. So we can acquired a enhanced signal to noise ratio. In this paper offer the method can reduce the dark-current in the X-ray detector.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.