• Journal of the Korean Recycled Construction Resources Institute
• /
• v.9 no.2
• /
• pp.167-176
• /
• 2021

When producing recycled asphalt mix, it is important that the old binder of reclaimed asphalt pavement(RAP) should be well melted during blending in the mixer. The recycled asphalt mix is produced by instant mixing(IM) of all materials(RAP, virgin asphalt and new aggregates) all together in the mixer. However, in the same recycled mix, the binder around RAP aggregate was found to show higher oxidation level than the binder coated around the virgin aggregate because the old binder of RAP was not rejuvenated properly while instant mixing. The partially-rejuvenated RAP binder is assumed to be a high stiffness point in IM recycled mix. In this study, the stage mixing(SM) method was introduced; blending RAP and virgin asphalt for the first stage, and then mixing all together with hot new aggregates for the second stage. To compare the effect of the two mixing methods on moisture resistance of recycled mixes, a statistical t-test was performed between SM and IM using indirect tensile strength(ITS) and tensile strength ratio(TSR). Three conditioning methods were used; a 16-h freezing and then 24-h submerging, 48-h submerging, and 72-h submerging in 60℃ water. It was found that the TSR(=ITS_wet/ITS_dry) values of the mixes prepared by SM was clearly higher than the IM mixes, and coefficients of variation of SM mixes were lower than the IM mixes. It was also observed that the ITS_WET of SM was significantly different from the IM at α=0.05 level by statistical t-test. The ITS_WET of SM mix was reduced less than the IM mix in severer conditioned mixes. Therefore, it was concluded that the stage mixing method was an important blending technique for producing better-quality of recycled asphalt mixes, which would show higher moisture resistance than the recycled mixes produced by conventional instant mixing.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.143-174
• /
• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Journal of Food Hygiene and Safety
• /
• v.38 no.1
• /
• pp.1-11
• /
• 2023

Skin sanitizers are effective in killing or removing pathogenic microbial contaminants from the skin of food handlers, and the progressive growth of consumer interest in personal hygiene tends to drive product diversification. This review covers the advances in the application of efficacy tests for hand sanitizers to suggest future perspectives to establish an assessment system that is optimized to each product type (gel, liquid, and wipes). Previous research on the in vivo simulative test of actual consumer use has adopted diverse experimental conditions regardless of the product type. This highlights the importance of establishing optimal test protocols specialized for the compositional characteristics of sanitizers through the comparative analysis of test methods. Although the operational conditions of the mechanical actions associated with wiping can affect the efficacy of the removal and/or the inactivation of target microorganisms from the skin's surface, currently there is a lack of standardized use patterns for the exposure of hand sanitizing wipes to skin. Thus, major determinants affecting the results from each step of the overall assessment procedures [pre-treatment - exposure of sanitizers - microbial recovery] should be identified to modify current protocols and develop novel test methods. The ex vivo test, designed to overcome the limited reproducibility of in vivo human trials, is also expected to replicate the environment for the contact of sanitizers targeting skin microorganisms. Recent progress in the area of skin microbiome research revealed distinct microbial characteristics and distribution patterns after the application of sanitizers on hands to establish the test methods with the perspectives on the antimicrobial effects at the community level. The future perspectives presented in this study on the improvement of efficacy test methods for hand sanitizers can also contribute to public health and food safety through the commercialization of effective sanitizer products.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.11 no.3
• /
• pp.282-288
• /
• 2023

In this study, we analyzed the amount of roadside fine dust generated from newly constructed specially modified asphalt pavement and general asphalt pavement from existing roads. We collected the 1,000 g (100 g/day) of dust samples from the roadside of the express bus terminal and commercial facility area in Chungcheongnam-do's C site at three-day intervals during the summer of 2022 and 2023. The collected samples were separated from fine dust according to size in the 75-150 ㎛ range and, were separated only from Tire and Road Wear Particles through density separation. No.1-3 are general asphalt pavement section as an existing road. Fine dust and Tire and Road Wear Particles in No.1-3 were 24.27 g, 24.36 g, 0.53 g, and 0.53 g, respectively, and the quantitative results for 2022 and 2023 were similar. On the other hand, No.4-6 are newly constructed specially modified asphalt pavement section. Fine dust decreased by 14.8 % and tire and road wear particles decreased by 29.6 % in 2023 compared to 2022 in No.4-6. In addition, according to the results of thermogravimetric analysis, Tire and road wear particles in No.1-3 are tire and road components at 30 % and 70 %, respectively. And Tire and road wear particles in No.4-6 are tire and road components at 35 % and 65 % in 2023, respectively. From these results, it was confirmed that the newly constructed specially modified asphalt pavement can be effective in reducing roadside fine dust and Tire and Road Wear Particles. However, there may be some shortcomings in conclusive research results due to limited space and sample collection period. In the future, we plan to conduct various case studies.

• Korean Journal of Heritage: History & Science
• /
• v.56 no.3
• /
• pp.158-171
• /
• 2023

Pottery filled with organic materials was excavated from the G-2 building site of Yongjangseong Fortress, Jingo, a relic of the Goryeo Dynasty. In this study, the characteristics of organic material were confirmed by a scientific analysis of organic material in pottery found at the palace in Yongjangseong, Jindo. In addition, it was intended to review the analysis method to identify the natural resin and to secure characteristic components(biomarkers) for each natural resin and use them as basic data in the future. The organic materials in the pottery were analyzed using attenuated total reflectance Fourier-transformed infrared spectroscopy(ATR-FTIR) and gas chromatography mass spectrometry(GC-MS). The infrared spectral characteristics were estimated to be natural resin, and biomarkers of organic materials were identified as sesquiterpene-based compounds(C₁₅H₂₄, MW 204) and derivatives. The lacquer(T.vemicifluum) is composed mainly of alkenes, alkanes, and catechol. Pine resin(P.densiflora), on the other hand, is primarily composed of diterpenoid(abietic acid, pimaric acid) and Whangchil(yellow lacquer) is identified to have sesquiterpenes(such as selinene, muurolene, calamenene) as its main components. So, the organic material in the pottery can be identified as Whangchil by comparing their compounds with modern resin materials from Dendropanax. morbifera that correspond with the results. Whangchil, which is exuded from the Dendropanax. morbifera, has been used as a natural coating materials since ancient times, and it has been confirmed that the characteristic components are well preserved even 700 years later. It can be assumed that the interior Whangchil was stored not for use as a coating, but rather for ritual purposes when the building was constructed, because the pottery was found near the cornerstone. Furthermore, based on simplified sample preparation using pyrolysis-gas chromatography mass spectrometry(Py-GC-MS), the thermal decomposition products were found to be similar to the characteristic components, suggesting that this method can be applied to the identification of natural resins used in historic artifacts.

• Journal of Korea Water Resources Association
• /
• v.57 no.3
• /
• pp.181-193
• /
• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.73-85
• /
• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• THE JOURNAL OF KOREAN ORIENTAL ONCOLOGY
• /
• v.4 no.1
• /
• pp.37-53
• /
• 1998

The sprig of Jinryungtang Gagambang has been used for curing as a traditional medicine without any experimental evidence to support the rational basis for their clinical use. This experiment was carried out to evaluate the possible therapeutic or antitumoral effects of Jinryungtang Gagambang extract against cancer, and to study some mechanisms responsible for its effect. The cytotoxic and antitumor effects were evaluated on human cell liens (A549, hep3B, Caki-1, Sarcoma 180) after exposure to Jinryungtang Gagambang extract using in ILS, colony forming efficency and SRB assay which were regarded as a valuable method for cytotoxic and antitumor effects of unknown compound on tumor cell lines. The results obtained in this studies were as follows. 1. As a result of exposure to Jinryungtang Gagambang extract, the proliferation of A549, hep3B, Caki-1, good correlations were shown from the results of SRB assay and those of clogenetic assay. 2. The oral administration of Jinryungtang Gagambang extract showed significant effects of increase of MST(mean survival time) and ILS(increased life span) depending on the increasing concentration. 3. Against squamous cell carcinoma induced by MCA, Jinryungtang Gagambang decreased not only the frequency of tumor production but also the number and weight of tumors per tumor bearing mice(TBM). Jinryungtang Gagambang also significantly suppressed the development of 3LL cell-implanted tumors by frequency and their size, and some developed tumors were regressed by the continuous treatment of Jinryungtang Gagambang extract into TBM. 4. Jinryungtang Gagambang extract also increased NK cell activities. According to the above results, it could be suggested that Jinryungtang Gagambang extract has prominent antiutmor effect.