• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.252-257
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• 2012

Purpose: The net rind pattern and color of melon surface are important for a high market value of melon fruits. The development of the net and color are closely related to the changes in shape, size, and maturing. Therefore, the net and color characteristics can be used indicators for assessment of melon quality. The goal of this study was to investigate the possibility of estimating melon soluble solids content (SSC) and firmness by analyzing the net and color characteristics of fruit surface. Methods: The true color images of melon surface obtained at fruit equator were analyzed with 18 color features and 9 texture features. The partial least squares (PLS) method was used to estimate SSC and firmness in melons using their color and texture features. Results: In sensing melon SSC, the coefficients of determination of validation (${R_v}^2$) of the prediction models using the color and texture features were 0.84 (root mean square error of validation, RMSEV: 1.92 $^{\circ}Brix$) and 0.96 (RMSEV: 0.60 $^{\circ}Brix$), respectively. The ${R_v}^2$ values of the models for predicting melon firmness using the color and texture features were 0.64 (RMSEV: 4.62 N) and 0.79 (RMSEV: 2.99 N), respectively. Conclusions: In general, the texture features were more useful for estimating melon internal quality than the color features. However, to strengthen the usefulness of the color and texture features of melon surface for estimation of melon quality, additional experiments with more fruit samples need to be conducted.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.381-393
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• 2012

This study is to understand the logistic area effect for the satisfaction of military service; service people work the unit of Marine Corps which is close or far away from North Korea and infantry people from the structural equation models based on the component based method(PLS). From the result, we note that the trustworthy and suitability of supply are the most important factors in their of military service satisfaction for Marine Corps.

• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.413-420
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• 2012

Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

• Food Science and Preservation
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• v.12 no.6
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• pp.608-612
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• 2005

Fourier transform-near infrared (FT-NIR) spectroscopy is a simple, rapid, non-destructive technique which can be used to make quantitative analysis of chemical composition in grain. An interest in total dietary fiber (TDF) of grain such as rice has been increased due to its beneficial effects for health. Since measuring methods for TDF content were highly depending on experimental technique and time consumptions, the application of FT-NIR spectroscopy to determine TDF content in milled rice. Results of enzymatic-gravimetric method were $1.17-1.92\%$ Partial least square (PLS) regression on raw NIR spectra to predict TDF content was developed Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP). The r, SEE and SEP were 0.9705, 0.0464, and 0.0604, respectively. The results indicated that FT-NIR techniques could be very useful in the food industry and rice processing complex for determination of TDF in milled rice on real time analysis.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.179-185
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• 2015

Along with the recent advances of mobile internet technology, use of social network service(SNS) is very common among adolescents or college students in their daily lives. Although there have been a lot of studies on Internet addiction or mobile phone addiction, however, there were little research on SNS addiction so far. Scholars investigated somewhat broader and obscure phenomenon of Internet addiction. In this regard, the current study tried to examine factors which influence SNS addiction behavior. Unlike Internet addiction, there are positive influencing factors such socialization, enjoyment as well as problematic ones like loneliness. Data were collected from college students in Korea to examine how those factors influence addiction behavior and hypotheses were tested using the partial least square method. All three factors, socialization, enjoyment, and loneliness, were found to significantly influence SNS addiction and socialization was positively associated with enjoyment.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1529-1529
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• 2001

The watercore in apple is very important factor in storage and sorting of fruit. Most consumers tend to prefer the apple included watercore in immediately after harvest, however the watercore causes fruit flesh to brown during storage and lose the worth after all. But it is practically impossible to judge to the naked eye whether an apple has watercore or not. Therefore, the rapid, accurate and non-destructive analysis method for discrimination of watercore should be settled without delay. In this study we attempted the discrimination and quantitative analysis of watercore in apple fruit using near-infrared transmittance spectroscopy ‘Fuji’ apple fruits produced in Kyungpook of Korea was used in this experiment. The watercore content in apple was evaluated by graphic treatment of culled slice sections(10 mm). NIR transmittance spectra were collected over the 500 to 1000 nm spectral region with a spectrometer (Sentronic Co., Germany). The calibration models were carried out by partial least squares (PLS) analysis between NIR spectra data of apples and chemical data of watercore content. The spectra were different in absorbance between apple included watercore and not included one. Apple included watercore had higher absorption band than sample not included one at 732 and 820 nm. The calibration model seems to be accurate to predict the watercore content in apple fruit, the correlation coefficient (R) and root mean square error of prediction (RMSEP) were 0.99 and 0.93%, respectively. This result indicates that the PLSR calibration model by using NIR transmittance spectroscopy could be used for discrimination of watercore in apple fruit.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.104-108
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• 2011

Technology is one of the major competitive advantages for small and medium enterprises (SME), especially ones operating in the manufacturing sector. Increasing technological capabilities is the basis for SME's business performance improvement. The main problem of SME's is a limitation in the areas of production facilities, technology, and human resources. Some of these constraints cause a decline in business performance and competitiveness of SME's. In this case analysis of technology components has to be carried out to determine the effect of technology on SME's business performance improvement. This study aims to measure the components of technology and to analyze the influence of each technology component on business performance of rattan processing SME's in South Kalimantan. The assessment is carried out on the technoware, humanware, inforware, and orgaware components using the technometric method (UNESCAP). Business performance is measured through a combination of financial and non-financial aspects deducted from financial and marketing figures. Analysis of the influence of technology components on business performance of SME's is done using the Structural Equation Model (SEM) with Partial Least Square software (PLS). Data is collected through interviews and questionnaires from 21 rattan processing SME's in South Kalimantan that produce rattan furnitures. The results show that the value of the contribution of technology (TCC) to the performance of rattan processing SME's in South Kalimantan is still quite low. Analysis of the results shows a direct influence of technoware and humanware on business performance, while orgaware influences business performance indirectly through humanware.

• Horticultural Science & Technology
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• v.30 no.6
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• pp.709-717
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• 2012

To establish the standard of ripe kiwifruit sorting, near infrared (NIR) spectroscopy was performed on kiwifruit sampled from three farms. Destructive measurements of flesh firmness, soluble solids content (SSC), and acidity were performed and compared to measurement using NIR reflectance spectrums from 408 to 2,492 nm. NIR predictions of those quality factors were calculated using the modified partial least square regression method. Flesh firmness was predicted with a standard error of prediction (SEP) of 3.32 N and with a correlation coefficient ($R^2$) of 0.88. SSC was predicted with SEP of $0.49^{\circ}Brix$ and with $R^2$ of 0.98. Acidity was predicted with SEP of 0.28% and with $R^2$ of 0.91. Kiwifruit ripened at $20^{\circ}C$ for 15 days showed uneven qualities with normal distribution. Considering the SEP of each parameter, kiwifruit after ripening treatment could be non-destructively predicted their qualities and sorted by flesh firmness or soluble solids content through NIR prediction.

• Korean Journal of Agricultural Science
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• v.41 no.1
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• pp.59-63
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• 2014

Precision farming aims at reduced environmental impacts with increased productivity. Soils are multi-functional media in which air, water and biota occur together and form an essential part of the landscape with a fundamental role in the environment. The requirement for herbicides and fertilizers can vary within a field in response to spatial differences in soil properties. Near infrared (NIR) spectroscopy is widely used today as a nondestructive analytical technique which is capable of determining a number of physio-chemical parameters. The objectives of this study were to develop optimal models to predict chemical properties of paddy soils by visible and NIR reflectance spectra. Total of 60 soil samples were collected in spring from 20 paddy fields within central regions in Korea. Reflectance spectra, moisture contents, pH, total nitrogen (N), organic matter, available phosphate ($P_2O_5$) of soil samples were measured. The reflectance spectra were measured in wavelength ranges of 400-2,500 nm with 2 nm interval. The method of partial least square (PLS) analysis was used to determine the soil properties. The PLS analyses showed good correlation between predicted and measured chemical properties of paddy soils in the wavelength range of 1,800-2,400 nm. Especially, it showed better performance than the previous results which used the entire wavelength range of the spectrophotometer, without considering the optimal wavelength of each soil properties.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.995-999
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• 2015

Inductive sensors are versatile and economical devices that are widely used to measure a wide variety of physical variables, such as displacement, force, and pressure. In this paper, we propose a simple inductive sensor consisting of a thin partial ring and a coil set. The self-inductance of the sensor was estimated using magnetic circuit analysis and validated through finite element analysis (FEA). The natural frequency of the ring was estimated using Castigliano's theorem and the method of equivalent mass. The estimation was validated through experiments and FEA. A prototype sensor with a signal processing circuit is built and applied to noninvasively sense the pressure inside a flexible tube. The obtained sensor outputs show quadratic behavior with respect to the pressure. When fitted to a quadratic equation, the least-square measurement error was less than 2%. The results confirm the feasibility of pressure sensing using the proposed inductive sensor.