• Preventive Nutrition and Food Science
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• v.8 no.4
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• pp.301-305
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• 2003

This study was conducted to develop an HPLC method for determining vitamin B$_{12}$ in fortified foods which has typically been determined by microbiological assays according to AOAC and Korean Food Code approved methods. Vitamin B$_{12}$ (cyanocobalamin) was determined by reversed-phase HPLC with a triple column and UV/VIS dectector (550 nm) using the column switching technique after extraction with 5 mM potassium phosphate solution by sonication without a clean-up procedure. The recovery of spiked samples and limit of detection (LOD) by HPLC were 78.6 ∼107.5 % and 2 ppb ($\mu\textrm{g}$/kg), respectively. The LOD of the microbiological assay (MBA) was much lower than that of HPLC. The concentrations of vitamin B$_{12}$ analyzed in all tested samples (n=12) confirmed compliance with declared label claims. The range of recovery ratio by the HPLC method when compared to the microbiological assay was 76.2 ∼140.0 %. There was not significant difference between the HPLC and MBA methods (p < 0.01) with r=0.9791 and linear regression y=0.9923x-0.04. The HPLC method for determining vitamin B$_{12}$ using the column-switching technique appears to be suitable for determining vitamin B$_{12}$ concentrations above 1 $\mu\textrm{g}$/100 g in fortified foods.ied foods.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.1
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• pp.71-81
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• 2011

Due to increased human activities and intensive rainfall events in a watershed, soil erosion and sediment transport have been hot issues in many areas of the world. To evaluate soil erosion problems spatially and temporarily, many computer models have been developed and evaluated over the years. However, it would not be reasonable to apply the model to a watershed if topography and environment are different to some degrees. Also, source codes of these models are not always public for modification. The ArcGIS model builder provides ease-of-use interface to develop model by linking several processes and input/output data together. In addition, it would be much easier to modify/enhance the model developed by others. Thus, simple model was developed to decide soil erosion hot spot areas using ArcGIS model builder tool in this study. This tool was applied to a watershed to evaluate model performance. It was found that sediment yield was estimated to be 13.7 ton/ha/yr at the most severe soil erosion hot spot area in the study watershed. As shown in this study, the ArcGIS model builder is an efficient tool to develop simple models without professional programming abilities. The model, developed in this study, is available at http://www.EnvSys.co.kr/~sateec/toolbox for free download. This tool can be easily modified for further enhancement with simple operations within ArcGIS model builder interface. Although very simple soil erosion and sediment yield were developed using model builder and applied to study watershed for soil erosion hot spot area in this study. The approaches shown in this study provides insights for model development and code sharing for the researchers in the related areas.

• The Journal of Economics, Marketing and Management
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• v.8 no.2
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• pp.13-17
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• 2020

Purpose: In modern corporate management, the establishment of a crisis management system that minimizes damage through measures used to respond to corporate crises is no longer an option. The importance of corporate reputation and brand asset management in modern enterprise management cannot be overemphasized and negative events that might arise from a number of different causes can cause brand crises. Research design, data and methodology: More than half of the questionnaire respondents were female (252 or 53%). More than a fourth of the respondents were aged 20 (122 or 26%) and the number of married participants was 196 (41%). Of the participants, 32% (153) had graduated from college. Only 18% (87) were employees and the monthly household income was 121. In this study, we conducted factor analysis in order to extract the variables that may enhance the explanation capability of each variable. For the method of factor extraction, an Eigen value of at least 1 was used as was factor loading. An analysis was performed using the Cronbach's alpha coefficient to verify the reliability of the measurement scale. Results: First, the analysis of the impact of the social responsibility activities on brand image revealed that the social, economic, philanthropic, ethical, and environmental responsibility activities significantly affected brand image, but legal responsibility activities were not statistically significant. Second, the analysis of the impact of brand image on loyalty showed that brand image had a significant impact on loyalty. Third, the analysis of the impact of social responsibility activities on loyalty showed that they had a significant impact on loyalty. Conclusions: The pro-social enterprise image is not only a brand asset that can be shared, but also a heavy proposition followed by a corresponding social responsibility, it will have to practice transparent corporate management based on clear principles through the establishment of various systems and the implementation of a strict code of conduct within the enterprise.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.61-68
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• 2021

Recently, various technologies that use machine learning to classify malicious code have been studied. In order to enhance the effectiveness of machine learning, it is most important to extract properties to identify malicious codes and normal binaries. In this paper, we propose a feature extraction method for use in machine learning using recursive methods. The proposed method selects the final feature using recursive methods for individual features to maximize the performance of machine learning. In detail, we use the method of extracting the best performing features among individual feature at each stage, and then combining the extracted features. We extract features with the proposed method and apply them to machine learning algorithms such as Decision Tree, SVM, Random Forest, and KNN, to validate that machine learning performance improves as the steps continue.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.93-105
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• 2022

With the exploitation of natural resources in China, underground resource extraction and underground space development, as well as other engineering activities are increasing, resulting in the creation of many defective rocks. In this paper, uniaxial compression tests were performed on rocks with double holes and fractures at different angles using particle flow code (PFC2D) numerical simulations and laboratory experiments. The failure behavior and mechanical properties of rock samples with holes and fractures at different angles were analyzed. The failure modes of rock with defects at different angles were identified. The fracture propagation and stress evolution characteristics of rock with fractures at different angles were determined. The results reveal that compared to intact rocks, the peak stress, elastic modulus, peak strain, initiation stress, and damage stress of fractured rocks with different fracture angles around holes are lower. As the fracture angle increases, the gap in mechanical properties between the defective rock and the intact rock gradually decreased. In the force chain diagram, the compressive stress concentration range of the combined defect of cracks and holes starts to decrease, and the model is gradually destroyed as the tensile stress range gradually increases. When the peak stress is reached, the acoustic emission energy is highest and the rock undergoes brittle damage. Through a comparative study using laboratory tests, the results of laboratory real rocks and numerical simulation experiments were verified and the macroscopic failure characteristics of the real and simulated rocks were determined to be similar. This study can help us correctly understand the mechanical properties of rocks with defects and provide theoretical guidance for practical rock engineering.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.171-181
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• 2022

Purpose: In this paper, we show our blending ratio of 10 types of Essential Oils that survives beneficial bacteria and kills harmful bacteria in the scalp, and we investigate the possibility of application of our blending ratio to the development of anti-dandruff products and the possibility of being used as a raw material for clinical beauty and customized cosmetics. Methods: The scalp microorganisms used in our study were M. furfur, S. epidermidis, E. coli, and P. nitroreducens. There are a total of 10 Essential Oils such as True Lavender, Lime, Roman chamomile, Rosemary camphor, Cedarwood, Geranium, Clove, Tea tree, Palmalosa, and Peppermint. The antibacterial test of the blended Essential Oil was carried out according to the test method of the standardized evaluation methodology of "Food and Food Additives Code". Since M. furfur is related to the growth of sebum in the scalp, in this study we used the fnLNB and the fnLNA with 20 ㎖ of whole fat cow milk added. Results: The blending ratio of EO, which inhibits dandruff-causing bacteria such as M. furfur, S. epidermidis, E. coli, and does not inhibit P. nitroreducens showing dominant growth in a healthy scalp, was B8(Clove 0.2%, Roman chamomile 0.5%, Tea tree 0.3%), B9(Geranium 0.1%, Palmarosa 0.1%, Roman chamomile 0.5%, Tea tree 0.3%), B10(Clove 0.1%, Geranium 0.1%, Palmarosa 0.1%, Roman chamomile 0.5%, Tea tree 0.2%). Conclusion: It is thought that the blending ratio of BEO obtained as a result of this study can provide a basis for use as an alternative to antibiotics in developing anti-dandruff drugs and emerge as a new alternative to solve scalp microbial imbalance. In order for EO to be used as a useful raw material for anti-dandruff preparation, researches on 1) Standardization (the effects of products differ according to the types, regions, climate, extraction methods, etc.), 2) Antimicrobial effects, 3) Safety, etc., must be established.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.1-6
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• 2023

Morphological analysis is a branch of natural language processing, is now a rapidly growing field. The fundamental tenet of morphological analysis is that it can establish the roots or stems of words and enable comparison to the original term. Arabic is a highly inflected and derivational language and it has a strong structure. Each root or stem can have a large number of affixes attached to it due to the non-concatenative nature of Arabic morphology, increasing the number of possible inflected words that can be created. Accurate verb recognition and extraction are necessary nearly all issues in well-known study topics include Web Search, Information Retrieval, Machine Translation, Question Answering and so forth. in this work we have designed and implemented an algorithm to detect and recognize Arbic Verbs from Arabic text.The suggested technique was created with "Python" and the "pyqt5" visual package, allowing for quick modification and easy addition of new patterns. We employed 17 alternative patterns to represent all verbs in terms of singular, plural, masculine, and feminine pronouns as well as past, present, and imperative verb tenses. All of the verbs that matched these patterns were used when a verb has a root, and the outcomes were reliable. The approach is able to recognize all verbs with the same structure without requiring any alterations to the code or design. The verbs that are not recognized by our method have no antecedents in the Arabic roots. According to our work, the strategy can rapidly and precisely identify verbs with roots, but it cannot be used to identify verbs that are not in the Arabic language. We advise employing a hybrid approach that combines many principles as a result.

• The Journal of Korean Medicine
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• v.43 no.3
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• pp.27-35
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• 2022

Objectives: The purpose of this study is to investigate and analyze Korean domestic patents on aconiti ciliare radix and to identify the trend of aconitum tuber technology. Methods: To analyze the patent, a combinations of words such as "aconitum" or "korean aconite root" were used in search engine Kipris(www.kirpis.or.kr). The patents of aconiti ciliare radix were analyzed in three ways: year trend analysis, internatonal patent classification (IPC) code analysis related to content classification, and patent registration status analysis. Results: Among the patents found in the search results, 17 patents with significant contents were analyzed. Results showed that, first, patents were steadily registered until 2018, but recently there has been no new patent registration. Second, there were many patents related to efficacy verification and decoction method, and the number of IPC codes related to them was also high. Third, there are five patents maintaining the registration status, and they are patents related to the aconiti ciliare radix extraction method, toxicity removal, and combination method. Conclusions: In this study, the domestic patents of aconiti ciliare radix were analyzed. The analysis results of this study are expected to be exploited as basic data for the development of Korean medicine analgesics with fewer side effects by suppressing tuber toxicity and the creation of new medical technologies.

• Korea Journal of Hospital Management
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• v.28 no.3
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• pp.1-14
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• 2023

Purposes: It is very important to establish a clinical data warehouse based on a common data model to offset the different data characteristics of each medical institution and for drug surveillance. This study attempted to establish a clinical data warehouse for Dankook university hospital for drug surveillance, and to derive the main items necessary for development. Methodology/Approach: This study extracted the electronic medical record data of Dankook university hospital tracked for 9 years from 2013 (2013.01.01. to 2021.12.31) to build a clinical data warehouse. The extracted data was converted into the Observational Medical Outcomes Partnership Common Data Model (Version 5.4). Data term mapping was performed using the electronic medical record data of Dankook university hospital and the standard term mapping guide. To verify the clinical data warehouse, the use of angiotensin receptor blockers and the incidence of liver toxicity were analyzed, and the results were compared with the analysis of hospital raw data. Findings: This study used a total of 670,933 data from electronic medical records for the Dankook university clinical data warehouse. Excluding the number of overlapping cases among the total number of cases, the target data was mapped into standard terms. Diagnosis (100% of total cases), drug (92.1%), and measurement (94.5%) were standardized. For treatment and surgery, the insurance EDI (electronic data interchange) code was used as it is. Extraction, conversion and loading were completed. R language-based conversion and loading software for the process was developed, and clinical data warehouse construction was completed through data verification. Practical Implications: In this study, a clinical data warehouse for Dankook university hospitals based on a common data model supporting drug surveillance research was established and verified. The results of this study provide guidelines for institutions that want to build a clinical data warehouse in the future by deriving key points necessary for building a clinical data warehouse.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.500-510
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• 2023

Passive sonar signals mainly contain both normal and abnormal signals. The abnormal signals mixed with normal signals are primarily detected using an AutoEncoder (AE) that learns only normal signals. However, existing AEs may perform inaccurate detection by reconstructing distorted normal signals from mixed signal. To address these limitations, we propose an abnormal signal detection model based on a Recurrent Neural Network (RNN) and vector quantization. The proposed model generates a codebook representing the learned latent vectors and detects abnormal signals more accurately through the proposed search process of code vectors. In experiments using publicly available underwater acoustic data, the AE and Variational AutoEncoder (VAE) using the proposed method showed at least a 2.4 % improvement in the detection performance and at least a 9.2 % improvement in the extraction performance for abnormal signals than the existing models.