• Korean journal of food and cookery science
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• v.8 no.4
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• pp.397-403
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• 1992

국수의 물성 측정에 있어서 기존의 방법들은 많은 시간을 요하고 또한 시간 경과에 따른 국수의 물성값에 오차를 주는 단점이 있다. 컴퓨터의 소프트웨어(Xtra)를 이용한 Texture Analyser로 부터 얻어낸 Texture Profile Analysis (TRA)곡선은 국수의 물성변화를 6∼8개의 상수들을 사용해서 설명할 수 있었다. 이 측정방법은 빠르고 효율적이며 시간을 단축할 수 있었다. 그러므로 국수와 파스타(pasta)의 물성 연구에는 이 방법을 도입할 것을 제시하였다.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.1-6
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• 2017

PURPOSES : Pavement textures can be categorized into four according to wavelength: microtexture, macrotexture, megatexture (roads), and roughness. Pavement surface texture influences a number of aspects of tire-pavement interaction such as wet-weather friction, tire-pavement noise, splash, spray, tire-wear, and rolling resistance. In particular, macrotexture is the pavement surface characteristic that considerably impacts tire-pavement noise. In general, it can be demonstrated that tire-pavement noise increases with the increase of texture depth and wavelength. Recently, mean profile depth (MPD) and wavelength have been used to evaluate tire-pavement noise. This study aimed to identify the relationship between mean profile depth and average wavelength for asphalt pavement based on the information obtained on a number of asphalt pavement sections. METHODS : Profile data were collected from a number of expressway sections in Korea. In addition, mean profile depth and average wavelength were calculated by using this profile data. Statistical analysis was performed to determine the correlationship between mean profile depth and average wavelength. RESULTS:This study demonstrates a linear relationship between mean profile depth and average wavelength for asphalt concrete pavement. CONCLUSIONS :The strong relationship between mean profile depth and average wavelength of asphalt pavement was determined in this study.

• Journal of the Korean Home Economics Association
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• v.23 no.3
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• pp.49-53
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• 1985

The typical texture profile analysis of acorn flour gel was investigated with Instron univ. testing machine by two experimental designs, 3$\times$3 latin square and $3^{3}$factorial experiment. As the result, it was revealed that Latin square is a useful method to reduce the number of experiments, in the case of a negligible interaction.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.9-16
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• 2013

PURPOSES: There is a need to develop a method to incorporate tire-pavement noise in the pavement management system. Tire-pavement noise highly depends on the characteristics of pavement texture. Therefore, estimation of texture characteristics may give useful information to predict tire-pavement noise. This study aimed to find the relationship between tire-pavement noise and MPD(Mean Profile Depth) for concrete pavement. METHODS: MPD and tire-pavement noise were collected on the number of expressway sections including Central Inland Test Road in Korea. Statistical analysis was performed to find the correlationship between MPD and tire-pavement noise. In addition, multiple regression analysis to find the tire-pavement noise based on MPD and type of concrete pavement texture. RESULTS: Linear relationship between MPD and tire-pavement noise is observed for concrete pavement. Furthermore, a forensic equation to estimate tire-pavement noise based on MPD and texture types of concrete pavement is suggested. CONCLUSIONS: Tire-pavement noise on concrete pavement can be predicted based on the consideration of texture type and MPD estimation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.118-126
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• 2014

In this paper, a new method is proposed for the five-degree-of-freedom precision alignment and stitching of three-dimensional surface-profile data sets. The control parameters for correcting thealignment error are calculated from the surface profile data for overlapped areas among the adjacent measuring areas by using the "least squares method" and "maximum lag position of cross correlation function." To ensure the alignment and stitching reliability, the relationships betweenthe alignment uncertainty, overlapped area, and signal-to-noise level of the measured profile data are investigated. Based on the results of this uncertainty analysis, an appropriate size is proposed for the overlapped area according to the specimen's surface texture and noise level.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.1-6
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• 2015

PURPOSES : Recently, attempts have been made to evaluate tire-pavement noise based on a measure of Mean Profile Depth (MPD). However, equivalent values of MPD appear to correspond to different levels of tire-pavement noise, which indicates that other factors such as texture wavelength need to be included to improve the accuracy of noise prediction. A single index to represent texture wavelength is proposed in this study. A consistent relationship between tire-pavement noise and texture wavelength on asphalt concrete pavement is observed. METHODS : Profile data and tire-pavement noise data were collected from a number of expressway sections in Korea. In addition, texture wavelength was defined by a Peak Number (PN), which was calculated using profile data. Statistical analysis was performed to find the relationship between the PN and tire-pavement noise. RESULTS : As a result of this study, a linear relationship between PN and tire-pavement noise is observed on asphalt concrete pavement. CONCLUSIONS : Tire-pavement noise on asphalt concrete pavement can be predicted from PN information.

• Korean journal of food and cookery science
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• v.33 no.1
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• pp.28-36
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• 2017

Purpose: This study was conducted to understand the factors that affect the texture of gluten-free rice pasta prepared buckwheat, mung bean, and acorn starches and to compare textural properties of samples 100% semolina. Methods: The moisture content, weight and water absorption test investigated and texture profile analysis measured by texture analyzer. Results: 100% semolina sample's value was lower than gluten-free rice pasta moisture content, weight and water absorption test. moisture content weight was in pasta with mung bean starchin pasta with buckwheat starch. Texture profile analysis showed that increasing amount of buckwheat, mung bean, and acorn starches increased hardness, chewiness, cohesiveness and springiness, and decreased adhesiveness of gluten free rice pasta. Conclusion: This study suggested that adding buckwheat, mungbean and acorn starches could improve texture properties of gluten-free rice pasta.

• Korean Journal of Food Science and Technology
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• v.32 no.5
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• pp.1073-1078
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• 2000

Wet noodles were prepared with all purposed flour and whey powder, and effects of added whey powder on dough rheology and noodle quality were examined using texture profile analysis, sensory evaluation and colorimeter. The initial pasting temperature in amylograph and the maximum resistance in extensograph increased with the addition of whey powder, while the water absorption and the dough development time in farinograph and the extensibility in extensograph decreased. The weight and volume of cooked noodles decreased and turbidity of soup increased with the addition of whey powder. Sensory evaluation revealed that the texture, taste and overall acceptabillity of cooked noodle from 5% whey powder were significantly different from the others. Texture profile analysis of cooked noodles showed decrease of hardness, cohesiveness, chewiness and springiness with the increase of whey powder. L and a values of wet noodles decreased with the addition of whey powder and b value increased.

• Korean journal of food and cookery science
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• v.26 no.5
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• pp.545-551
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• 2010

In this study, Sulgidduk samples were prepared with 0%, 3%, 5% and 7% yacon powder. Sulgidduk samples were then examined for quality characteristics such as moisture content, general components, color, texture profile analysis, sensory qualities, and sugar content, in order to determine the optimal ratio of yacon powder in the formulation. Regarding the general components of yacon Sulgidduk, the contents of crude protein and lipid decreased as the ratio of yacon powder increased. The L-value for color decreased, whereas a- and b-values increased. In the texture profile analysis, 7%-added yacon showed significantly lower hardness, whereas 7% yacon powder showed the highest values for cohesiveness, springiness, and chewiness. The contents of sucrose, fructose, and glucose in yacon Sulgidduk were found to be 3%, 5%, and 7% by LC, respectively. Sucrose showed a decreasing trend with increased yacon powder content, but fructose and glucose increased with increased amount of yacon powder. For sensory qualities, taste/flavor, texture, hardness, and overall acceptability were not significantly different among the 0%, 3%, and 5% yacon powder samples.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.7
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• pp.1029-1036
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• 2016

This study investigated the degree to which instrumental measurements explain the variation in pork loin tenderness as assessed by the sensory evaluation of trained panelists. Warner-Bratzler shear force (WBS) had a significant relationship with the sensory tenderness variables, such as softness, initial tenderness, chewiness, and rate of breakdown. In a regression analysis, WBS could account variations in these sensory variables, though only to a limited proportion of variation. On the other hand, three parameters from texture profile analysis (TPA)-hardness, gumminess, and chewiness-were significantly correlated with all sensory evaluation variables. In particular, from the result of stepwise regression analysis, TPA hardness alone explained over 15% of variation in all sensory evaluation variables, with the exception of perceptible residue. Based on these results, TPA analysis was found to be better than WBS measurement, with the TPA parameter hardness likely to prove particularly useful, in terms of predicting pork loin tenderness as rated by trained panelists. However, sensory evaluation should be conducted to investigate practical pork tenderness perceived by consumer, because both instrumental measurements could explain only a small portion (less than 20%) of the variability in sensory evaluation.