• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.315-323
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• 2013

Tire noise is divided into a road noise(structure-borne noise) and a pattern noise(air-borne noise). Whilst the road noise is caused by the structural vibration of the components on the transfer path from tire to car body, the pattern noise is generated by the air-pumping between tire and road. In this paper, a practical method to estimate the pattern noise inside a passenger car is proposed. The method is developed based on the sound intensity and airborne source quantification. Sound intensity is used for identifying the noise sources of tire. Airborne source quantification is used for estimating the sound pressure level generated by each noise source of a tire. In order to apply the airborne source quantification to the estimation of the sound pressure, the volume velocity of each source should be obtained. It is obtained by using metrics inverse method. The proposed method is successfully applied to the evaluation of the interior noises generated by four types of tires with different pattern each other.

• Bulletin of the Korean Chemical Society
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• v.32 no.4
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• pp.1221-1227
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• 2011

Ethyl pyruvate (EP) is known as a scavenger of reactive oxygen species (ROS) in the body through its role in the donation of diketone groups to metals to form an EP-metal complex. In order to develop a method for the quantification of EP in biological media, a sensitive and specific, high-performance liquid chromatographyelectrospray ionization-mass spectrometry (HPLC-ESI/MS) method is used to determine the EP-alkali metal ion binding species. The analyte was separated on a ZORBOX SB-C8 ($3.5{\mu}m$, $30mm{\times}2.1mm$ I.D.) column and analyzed in selected ion monitoring (SIM) mode with a positive ESI interface using the m/z 255 $[2M + Na]^+$ ion. The method was validated over the concentration range of $0.5-60.0\;{\mu}g$/mL under 1/9 (v/v) of acetonitrile/methanol solvent system with flow rate 0.05 mL/min. The limit of quantification (LOQ) was $0.5{\mu}g$/mL.

• Mass Spectrometry Letters
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• v.4 no.2
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• pp.25-29
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• 2013

Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

• Journal of Microbiology and Biotechnology
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• v.19 no.7
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• pp.658-665
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• 2009

Quality control QC for spot-uniformity is a critical point in fabricating an oligonucleotide array, and quantification of targets is very important in array analysis. We developed two new types of QC probes as a means of confirming the quality of the uniformity of attached probes and the quantification of targets. We compared the signal intensities and fluorescent images of the QC and target-specific probes of arrays containing only target-specific probes and those containing both QC and target-specific probes. In a comparison of quality control methods, it was found that the arrays containing QC probes could check spot-uniformity or spot defects during all processes of array fabrication, including after spotting, after washing, and after hybridization. In a comparison of quantification results, the array fabricated by the method using QC probes showed linear and regular results because it was possible to normalize variations in spot size and morphology and amount of attached probe. This method could avoid errors originating in probe concentration and spot morphology because it could be normalized by QC probes. There were significant differences in the signal intensities of all mixtures (P<0.05). This result indicates that the method using QC probes is more useful than the ordinary method for quantification of mixed target. In the quantification of mixed targets, this method could determine a range for mixed targets of various amounts. Our results suggest that methods using QC probes for array fabrication are very useful to the quality control of spots in the fabrication processes of quantitative oligonucleotide arrays.

• Journal of Microbiology and Biotechnology
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• v.33 no.5
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• pp.662-667
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• 2023

Allantoin is an abundant component of yams and has been known as a skin protectant due to its pharmacological activities. In previous methods for allantoin determination using high-performance liquid chromatography (HPLC), the separation was unsatisfactory. We herein developed a ¹H quantitative nuclear magnetic resonance (qNMR) method for quantification of allantoin in the flesh and peel of yams. The method was carried out based on the relative ratio of signals integration of allantoin to a certain amount of the internal standard dimethyl sulfone (DMSO₂) and validated in terms of specificity, linearity (range 62.5-2000 ㎍/ml), sensitivity (limit of detection (LOD) and quantification (LOQ) 4.63 and 14.03 ㎍/ml, respectively), precision (RSD% 0.02-0.26), and recovery (86.35-92.11%). The method was then applied for the evaluation of allantoin in flesh and peel extracts of four different yams cultivated in Korea.

• Smart Structures and Systems
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• v.32 no.4
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• pp.219-233
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• 2023

Crack width is an important indicator to evaluate the health condition of the concrete structure. The crack width is measured by manual using crack width gauge commonly, which is time-consuming and laborious. In this paper, we have proposed a fast and simplified crack width quantification method via deep Q learning and geometric calculation. Firstly, the crack edge is extracted by using U-Net network and edge detection operator. Then, the intelligent decision of is made by the deep Q learning model. Further, the geometric calculation method based on endpoint and curvature extreme point detection is proposed. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method, achieving high precision in the real crack width quantification.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.165-170
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• 2007

Recommendation systems provide users with proper services using context information being input from many sensors occasionally under ubiquitous computing environment. But in case there isn't sufficient context information for service recommendation in spite of much context information, there can be problems of resulting in inexact result. In addition, in the quantification step to use context information, there are problems of classifying context information inexactly because of using an absolute classification course. In this paper, we solved the problem of lack of necessary context information for service recommendation by using dynamic profile information. We also improved the problem of absolute classification by using a relative classification of context information in quantification step. As the result of experiments, expectation preference degree was improved by 7.5% as compared with collaborative filtering methods using an absolute quantification method where context information of P2P mobile agent is used.

• Applied Microscopy
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• v.51
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• pp.10.1-10.9
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• 2021

We investigate the sensitivity of symmetry quantification algorithms based on the profile R-factor (R_p) and the normalized cross-correlation (NCC) coefficient (γ). A DM (Digital Micrograph^©) script embedded in the Gatan digital microscopy software is used to develop the symmetry quantification program. Using the Bloch method, a variety of CBED patterns are simulated and used to investigate the sensitivity of symmetry quantification algorithms. The quantification results show that two symmetry quantification coefficients are significantly sensitive to structural changes even for small strain values of < 1%.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.227-234
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• 2000

The human sensibility caused by the motion of an object grasped by a human operator is defined as kinesthetic sense of arm. Due to nonlinearity and ambiguity of human sense, there is no absolute standard for quantification of kinesthetic sense. In this research, a so-called 2-dimensional arm motion generator is developed to present various mechanical impedance (i.e., stiffness or damping) characteristics to a human arm. The kinesthetic words representing arm kinesthetic sense are selected and then the subject's satisfaction levels on these words for given impedance values are measured and processed by the SD method and factor analysis. In addition, the quantification method using neural network is proposed to take into account the individual difference between the mean sensibility and each subject's sensibility. Through this proposed algorithm, the sensibility of human motion described qualitatively can be converted into engineering data ensuring objectivity, reproducibility, and universality.

• Journal of Preventive Medicine and Public Health
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• v.31 no.1 s.60
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• pp.72-81
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• 1998

The purpose of this study was to investigate the relation between health behavior patterns and demographic, socio-economic characteristics, health status, health information in Korea. The quantification method through canonical correlation analysis was conducted to the data from Korea National Health Survey in 1995, which consisted of 5,805 persons. The health lifestyle patterns were quantified as good diet lifestyle, passive lifestyle to the negative direction and drinker lifestyle, smoker lifestyle, hedonic lifestyle and fitness lifestyle to the positive direction. The covariate were related to health lifestyle patterns in the order of sex, age, marital status, occupation, health information, economic status, level of physical labour and health status. Characteristics of male, age below 50, married, blue colored worker, no health information, low in economic status, heavy level of physical labour, and poor in health status were positively related to drinker lifestyle, smoker lifestyle, hedonic lifestyle, fitness lifestyle sequentially.