• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.61-69
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• 2021

In this study, scale down model bridge piers were fabricated and non-destructive experiments conducted with an impact load to determine scours in the ground adjacent to the bridge piers using the natural frequency of the bridge piers. Three scale-model bridge piers with different heights were fabricated, and they penetrated the ground at a depth of 0.35 m. The scours around the bridge piers were simulated as a side scour and foundation scour. The experiments were conducted in 13 steps, in which scouring around the model bridge piers was performed in 0.05 m excavation units. To derive the natural frequency, the impact load was measured with three accelerometers attached to the model bridge piers. The impact load was applied with an impact hammer, and the top of the model bridge pier was struck perpendicularly to the bridge axis. The natural frequency according to the scour progress was calculated with a fast Fourier transform. The results demonstrated that the natural frequency of each bridge pier tended to decrease with scour progress. The natural frequency also decreased with increasing pier height. With scour progress, a side scour occurred at 70% or higher of the initial natural frequency, and a foundation scour occurred at less than 70%.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.188-194
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• 2022

This work presents a non-destructive and straightforward approach to assemble a large-scale conductive electronic film made of a pre-treated single-walled carbon nanotube (SWCNT) solution. For effective electron transfer between the immobilized enzyme and SWCNT electronic film, we optimized the pre-treatment step of SWCNT with p-terphenyl-4,4"-dithiol and dithiothreitol. Glucose oxidase (GOx, a model enzyme in this study) was immobilized on the SWCNT electronic film following the positively charged polyelectrolyte layer deposition. The glucose detection was realized through effective electron transfer between the immobilized GOx and SWCNT electronic film at the negative potential value (-0.45 V vs. Ag/AgCl). The SWCNT electronic film-based glucose biosensor exhibited a sensitivity of 98 ㎂/mM·cm². In addition, the SWCNT electronic film biosensor showed the excellent selectivity (less than 4 % change) against a variety of redox-active interfering substances, such as ascorbic acid, uric acid, dopamine, and acetaminophen, by avoiding co-oxidation of the interfering substances at the negative potential value.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.120-128
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• 2022

There are 17,000 reservoir dams in Korea, of which more than 85% were built over 50 years ago. Old embankment dams are weakened by internal erosion and suffusion phenomena due to preferential leakage paths and this ongoing weakening can cause their failure. Therefore, early warning associated with leakage in an embankment dam is crucial to prevent its failure. An electrical resistivity survey is a non-destructive, real-time and in-situ technique for detecting the development of leakage zones and general conditions of embankment dams. Because of its advantages, the electrical resistivity survey is widely used for reservoir safety inspections. However, the electrical resistivity survey is still not officially included in the precise safety inspection of reservoir dams because it cannot present a quantitative index of dam safety. In this study, we propose a method for calculating the leak index according to the water content evaluated from the electrical resistivity survey and/or induced polarization survey. Particularly, by proposing a quantitative leak index calculation method from monitoring surveys and independent surveys, we provide a theoretical basis for including electrical resistivity and induced polarization surveys as components of the precise safety inspection of reservoirs dams.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• Women's Studies Review
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• v.26 no.1
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• pp.207-237
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• 2009

This paper aims to show that Sylvia Plath searched for the female poetic voice, by tracing the aspects of her early poems. This study attempts to demonstrate that Plath disclosed the violence of male-centered literary tradition against women poets although her early poems seem to be written from a male point of view. In her poems, "Snakecharmer", "Full Fathom Five", and "The Colossus", it is particularly found that Plath hoped to be empowered with the poet's voice, which nevertheless resulted almost in silence or babbling. Plath, indeed, devised a strategy in order to show that, for women poets, the patriarchal literary tradition is a destructive power rather than a generative one. Namely, women poets are not able to fully grow out of a male-oriented tradition. On that account, she tried to represent in her early poems herself who sought to be empowered with an authoritative voice, invoking the male muse, but this ended in failure. Plath was skeptical about the way she had desired to find her own voice by relying upon the male muse, and she needed to free herself from that literary tradition.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.2
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• pp.141-155
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• 2023

Monitoring technology based on electrical resistivity is widely used for non-destructive data collection and health analysis of underground structures and tunnels. Vulnerable sections such as fault zone generates many problems during construction of the tunnel. These problems cause displacement and stress changes of the ground. Therefore, it is necessary to predict the state of the fault zone section to ensure the mechanical stability of the underground structure. Monitoring the size of joints and the porosity of the fillings is essential for rocks. Previous studies have not considered the variety of fillings in rock joints. In this study, electrical resistivity tests were conducted according to the particle mixing state of the sandy fillings. When the size of fillings is decreased at the constant porosity, the electrical resistivity tends to increase. The results of this study are expected to be useful as basic electrical resistivity data for predicting the ground conditions and evaluation of the ground behavior that is containing sandy fillings in the rock joint for tunnels.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.145-156
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• 2023

In this study, Fourier-transform near-infrared (FT-NIR) spectra of Korean red pine seeds stored at -18℃ and 4℃ for 18 years were analyzed. To develop seed-germination prediction models, the performance of seven machine learning methods, namely XGBoost, Boosted Tree, Bootstrap Forest, Neural Networks, Decision Tree, Support Vector Machine, PLS-DA, were compared. The predictive performance, assessed by accuracy, misclassification, and area under the curve (0.9722, 0.0278, and 0.9735 for XGBoost, and 0.9653, 0.0347, and 0.9647 for Boosted Tree), was better for the XGBoost and decision tree models when compared with other models. The 54 wave-number variables of the two models were of high relative importance in seed-germination prediction and were grouped into six spectral ranges (811~1,088 nm, 1,137~1,273 nm, 1,336~1,453 nm, 1,666~1,671 nm, 1,879~2,045 nm, and 2,058~2,409 nm) for aromatic amino acids, cellulose, lignin, starch, fatty acids, and moisture, respectively. Use of the NIR spectral data and two machine learning models developed in this study gave >96% accuracy for the prediction of pine-seed germination after long-term storage, indicating this approach could be useful for non-destructive viability testing of stored seed genetic resources.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.33-46
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• 2007

HWAW (Harmonic Wavelet Analysis of Wave) method, which is non-destructive method using body and surface waves, has the advantages of obtaining 2D subsurface imaging because it uses a short receiver spacing to obtain the $V_s$ profile of whole depth. Even though the reliability of HWAW method has already been verified by using the numerical simulation in the various layered models, it is very difficult to evaluate the reliability of HWAW in the field because the exact $V_s$ values of the experimental site are unknown. In this study, a model testing site where the material properties and layer information could be controlled was constructed to verify the reliability of HWAW method. The detailed geometry of the testing site was strictly measured by surveying, and 140 vertical and horizontal geophones were established at the boundary of each layer to evaluate the dynamic material properties. Using the interval travel times between the upper and lower geophones, the body wave velocities of each layer were 2 dimensionally obtained as reference data, and comparative study using HWAW method was performed. By comparing 2D Vs profile obtained by HWAW method to the reference data, the reliability of HWAW method was verified.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.117-127
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• 2008

The volumetric pressure plate extractor (VPPE) was modified for the measurement of shear wave velocity ($V_s$) at various levels of matric suction as well as soil water characteristic curve (SWCC). A non-destructive technique with a pair of bender element (BE) was employed in order to measure the $V_s$ and the corresponding maximum shear modulus ($G_{max}$) of unsaturated soil specimens. Three types of soil were collected from different road construction sites in Korea. For all test soils, the variations in $G_{max}$ with the various levels of water content and matric suction were investigated using the developed apparatus. Compared with the preceding results from the suction-controlled torsional shear (TS) testing system and in-situ seismic tests, the feasibility fur evaluating modulus characteristics of unsaturated compacted soils with the developed VPPE-BE system was assessed. It was confirmed that the newly developed system would be potentially helpful in modeling seasonal variation of modulus.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.