• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• Clean Technology
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• v.22 no.2
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• pp.122-131
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• 2016

Caesium radioisotopes, ¹³⁴Cs and ¹³⁷Cs which come from the atmospheric nuclear tests and discharges from nuclear power plants, are very important to study artificial radioactivity. In this work, in order to lower the minimum detection activity (MDA) we investigated environmental radioactivity according to the Environment Measurement Laboratory procedure by ¹³⁷Cs and ¹³⁴Cs which is similar to chemical and environmental behaviors of ¹³⁷Cs. The environmental soils in high mountain areas near nuclear power plant were collected, and an Ammonium Molybdophosphate (AMP) precipitation method, which showed high selectivity toward Cs⁺ ions, was applied to chemically extract and concentrate Caesium radioisotopes. Radioactivity was estimated by a gamma-ray spectrometry. In gamma energy spectrum, with an increasing of ⁴⁰K radioactivity, it increased the MDA of ¹³⁴Cs and ¹³⁷Cs. Therefore, if the natural radionuclides were removed from the soil samples, the MDA of Caesium may be reduced, and the contents of ¹³⁷Cs of in the environmental soils can effectively be estimated. In the standard soil sample of Korea Institute of Nuclear Safety, radioactivity of ⁴⁰K was removed more than 84% on average, and the MDA of ¹³⁴Cs was reduced 2 times. The content of ¹³⁷Cs was recovered over 84%. On the other hand, in environmental soils, AMP precipitation method showed removal ratio of ⁴⁰K up to 180 times, which reduced the MDA about 5 times smaller than those of Direct method. ¹³⁷Cs recovery ratio showed from 54.54% to 70.06%. When considering the MDA and recovery ratio, AMP precipitation method is effective for detection of Caesium radioisotopes in low concentration.

• Restorative Dentistry and Endodontics
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• v.20 no.2
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• pp.699-720
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• 1995

This study was conducted to evaluate the effect of benzalkonium chloride solution as a wetting agent instead of water on dentin bonding with NTG-GMA/BPDM system (All-bond 2, Bisco.) and DSDM system (Aelitebond, Bisco.). Benzalkonium chloride solution is a chemical disinfectant widely used in medical and dental clinics for preoperative preparation of skin and mucosa due to its strong effect of cationic surface active detergent. Eighty freshly extracted bovine lower incisor were grinded labially to expose flat dentin surface, and then were acid-etched with 10 % phosphoric acid for 15 second, water-rinsed, and dried for 10 second with air syringe. The specimens were randomly divided into 8 groups of 10 teeth. The specimens of control group were remoistured with water and the specimens of experimental groups were remoistured with 0.1 %, 0.5 %, and 1.0 % benzalkonium chloride solution respectively. And then, the Aelitefil composite resin was bonded to the pretreated surface of the specimens by use of All-bond 2 dentin bonding system or Aelitebond dentin bonding system in equal number of the specimens. The bonded specimens were stored in $37^{\circ}C$ distilled water for 24 hours, then the tensile bond strength was measured, the mode of failure was observed, the fractured dentin surface were examined under scanning electron microscopy, and FT-IR spectroscopy was taken for the purpose of investigating the changes of the dentin surface pretreated with benzal konium chloride solution followed by each primer of the dentin bonding systems. The results were as follows : In the group of bonding with NTG-GMA/BPDM dentin bonding agent(All-bond 2), higher tensile bond strength was only seen in the experimental group remoistured with 0.1 % benzal konium chloride solution than that in water-remoistured control group(p<0.05). In the group of bonding with DSDM dentin bonding agent (Aelitebond), no significant differences were seen between the control and each one of the experimental group(p<0.05). Higher tensile bond strength were seen in NTG-GMAIBPDM dentin bonding agent group than in DSDM dentin bonding agent group regardless of remoistur ization with benzal konium chloride solution. On the examination of failure mode, cohesive and mixed failure were predominantly seen in the group of bonding with NTG-GMAIBPDM dentin bonding agent, while adhesive failure was predominantly seen in the group of bonding with DSDM dentin bonding agent. On SEM examination of fractured surfaces, no differences of findings of primed dentin surface between the groups with and without remoisturization with benzal konium chloride solution. FT-IR spectroscopy taken from the control and the experimental group reve::.led that some higher absorbance derived from the primers binding to dentin surface was seen at the group pretreated with 0.1 % benzal konium chloride solution than at the control group of remoisturizing with water.

• Restorative Dentistry and Endodontics
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• v.32 no.4
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• pp.343-355
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• 2007

The objectives of this study was to evaluate the durability of 4 resin cements by means of microtensile bond strength test combined with thermocycling method and fractographic FE-SEM analysis. Experimental groups were prepared according to thermocycling (0, 1,000, 5,000) and the kind of resin cements, those were Variolink II, Multilink, Panavia F 2.0, Rely X Unicem. Flat dentin surfaces were created on mid-coronal dentin of extracted third molars. Then fresh dentin surface was grounded with 320-grit silicon carbide abrasive papers to create uniform smear layers. Indirect composite block (Tescera, Bisco Inc., Schaumburg, IL, USA) was fabricated ($12\;{\times}\;12\;{\times}\;6\;mm^3$). It's surface for bonding to tooth was grounded with silicon carbide abrasive papers from 180- to 600-grit serially, then sandblasted witk $20\;-\;50\;{\mu}m$ alumina oxide. According to each manufacturer's instruction, dentin surface was treated and indirect composite block was luted on it using each resin cement. For Rely X Unicem, dentin surface was not treated. The bonded tooth-resin block were stored in distilled water at $37^{\circ}C$ for 24 hours. After thermocycling, the bonded tooth-resin block was sectioned occluso-gingivally to 1.0 mm thick serial slabs using all Isomet slow-speed saw (Isomet, Buehler Ltd, Lake Bluff, IL, USA). These sectioned slabs were further sectioned to $1.0\;{\times}\;1.0\;mm^2$ composite-dentin beams. The specimens were tested with universal testing machine (EZ-Test, Shimadzu, Japan) at a crosshead speed of 1.0 mm/min with maximum load of 500 N. The data was analyzed using one-way ANOVA and Duncan's multiple comparison test at $p\;{\leq}\;0.05$ level. Within the limited results, we conclude as follows; 1. The bond strength of Variolink II was evaluated the highest among experimental groups and was significantly decreased after 1,000 thermocycling (p < 0.05). 2. The bond strength of Multilink was more affected by thermocycling than the other experimental groups and significantly decreased after 1,000 thermocycling (p < 0.05). 3. Panavia F 2.0 and Rely X Unicem showed the gradually decreased tendency of microtensile bond strength according to thermocycling but there was no significant difference (p > 0.05). 4. Adhesive based-resin cements showed lower bond strength with or without thermocycling than composite based-resin cements. 5. Variolink II & Multilink showed high bond strength and mixed failure, which was occurred with a thin layer of luting resin cement before thermocycling and gradually increased adhesive failure along the dentin surface after thermocycling. The bonding performance of resin cement can be affected by application procedure and chemical composition. Composite based-resin cement showed higher bond strength and durability than adhesive based-resin cement.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.1
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• pp.35-42
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• 2018

Objectives: The objectives of this study are to research the usage characteristics of asbestos-containing building materials and to conduct exposure risk assessment by applying no. 2016-230 "Methods of Risk Assessment of Asbestos-Containing Buildings" from the Ministry of Environment. Methods: One hundred buildings located in the Seoul and Gyeonggi-Incheon area were chosen, with 29 in Seoul, 20 in Incheon, and 51 in Gyeonggi-do Province. The year of construction was divided between three buildings in the 1970s, 11 buildings in the 1980s, 42 buildings in the 1990s, and 44 buildings in the 2000s. The bulk samples were analyzed by using a polarizing microscope after a pre-process using a stereomicroscope in a hood with an HEPA filter. This study defined ACMs(asbestos-containing materials) as asbestos when the content percentage was over 1% in the analysis result. Methods and standards of risk assessment of asbestos-containing building materials were conducted by refering to no. 2016-230 "Method of Risk Assessment of Asbestos-Containing Buildings" from the Ministry of Environment. The risk of exposure to ACMs was rated by a score based on three categories(high, middle, low risk of asbestos exposure). Results: In this study, 30 of the 100 buildings and 36 of the 416 bulk samples(8.6%) were found to have had asbestos. Asbestos was detected at a high rate, in 18 out of 42, in buildings constructed in the 1990s and at the lowest rate(7 out of 44) for buildings constructed in the 2000s. As a result of the evaluation according to no. 2016-230 "Method of Risk Assessment of Asbestos-Containing Buildings" of the Ministry of Environment, the risk assessment level of two asbestos-containing building materials was found to be "Medium", and 28 buildings materials were found to be at the "Low" level. Conclusion: As asbestos is regulated by the government, it is required to conduct active management and implemention by introducing methods of risk assessment of asbestos exposure that are supported by data from various situations. In the case of buildings owned by individuals, building owners should be aware of the risk of exposure to asbestos.

• The Korean Journal of Nuclear Medicine
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• v.36 no.4
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• pp.261-270
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• 2002

Purpose: Nicotinic acetylcholine receptors (nAChRs), which mediate excitatory neurotransmission, are known to participate in various neurophysiological functions. Severe losses of nAChRs have been noted in Alzheimer's and Parkinson's diseases. Therefore, noninvasive and quantitative imaging of nAChRs would offer a better understanding on the function of these receptors. In this study, $2-[^{18}F]fluoro-A85380\;([^{18}F]1)$, an ${\alpha}_4{\beta}_2$ nAChRs radioligand, was prepared using one HPLC purification and evaluated in mouse brain, and the results were compared with those in the literature. Materials and Methods: $[^{18}F]1$ was prepared by $[^{18}F]$fluorination of the iodo precursor followed by acidic deprotection and then purified by HPLC. Tissue distribution studies were performed in mouse brain at the indicated time points and the result was expressed as %ID/g. Inhibition studies were also carried out with pretreatment of various ligands. Results: One HPLC purification method gave the desired product in 15-20% radiochemical yield and with high specific activity ($38-55GBq/{\mu}mol$). Tissue distribution studies showed that $[^{18}F]1$ specifically labeled nAChRs in mouse brain with a high thalamus to cerebellum uptake ratio (13.8 at 90 min). Inhibition studios demonstrated selective binding of $[^{18}F]1$ to nAChRs, blocking the uptake of the $[^{18}F]1$ in nAChR-rich legions by selective ligands such as cytisine and nicotine which are well-known nAChRs agonists. Conclusion: This study demonstrated that the $[^{18}F]1$ produced by the method using one HPLC purification gave the results similar to those reported in the literature. Therefore, this synthetic method can be readily applied to the routine preparation of $[^{18}F]1$, a PET radioligand for ${\alpha}_4{\beta}_2$ nAChRs imaging.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Food Science and Preservation
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• v.19 no.6
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• pp.799-806
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• 2012

This experiment was conducted to establish the optimum conditions for high $CO_2$ gas treatment in combination with a proper gas-permeable packaging film to maintain the quality of fig fruit (Ficus carica L). Among the fig fruits with different high $CO_2$ treatments, the quality change was most effectively controlled during storage in the 70%-$CO_2$-treated fig fruit. Harvested fig fruit was packaged using microperforated oriented polypropylene (MP) film to maintain the optimum gas concentrations in the headspace of packaging for the modified-atmosphere system. MP film had an oxygen transmission rate of about $10,295cm^3/m^2$/day/atm at $25^{\circ}C$. The weight loss, firmness, soluble-solid content (SSC), acidity (pH), skin color (Hunter L, a, b), and decay ratio of the fig fruits were monitored during storage at 5 and $25^{\circ}C$. The results of this study showed that the OPP film, OPP film + 70% $CO_2$, and MP film+70% $CO_2$ were highly effective in reducing the loss rate, firmness and decay occurrence rate of fig fruits that were packaged with them during storage. In the case of using treatments with packages of OPP film and OPP film+70% $CO_2$, however, adverse effects like package bursting or physiological injury of the fig may occur due to the gas pressure or long exposure to $CO_2$. Therefore, the results indicated that MP film containing 70% $CO_2$ can be used as an effective treatment to extend the freshness of fig fruits for storage at a proper low temperature.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Food Science and Technology
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• v.53 no.4
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• pp.470-478
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• 2021

This study was conducted to monitor residual pesticides in a total of 527 school foodservice agricultural products from 2019 to 2020 in Incheon. Pesticide residues in the samples were analyzed by the multi-residue method in the Korean food code for 373 pesticides using GC-MS/MS, LC-MS/MS, GC-ECD, GC-NPD, and HPLC-UVD. By monitoring the pesticides, 12 (2.3%) of the 527 pesticides were detected, and 2 (0.4%) samples exceeded the maximum residue limit. Twelve types of pesticides were detected in the agricultural products of carrot, chard, chili pepper, chwinamul, crown daisy, parsley, perilla leaves, and spinach. As a means of risk assessment through the consumption of agricultural products detected with pesticide residues, the proportion of estimated daily intake to acceptable daily intake was estimated in the range of 0.0000-39.7425%. Results showed no particular health risk through the consumption of school foodservice agricultural products with pesticide residues.