• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Korean Journal of Food Science and Technology
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• v.47 no.1
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• pp.95-102
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• 2015

The Maillard reaction is a non-enzymatic reaction between amino and carbonyl groups. During milk processing, lactose reacts with milk protein through this reaction. Infant formulas (IFs) are milk-based products processed with heat-treatments, including spray-drying and sterilization. Because IFs contain higher Maillard reaction products (MRPs) than breast milk, formula-fed infants are subject to higher MRP exposure than breast milk-fed ones. In this study, we investigated the optimization of conditions for minimal MRP formation with the addition of $\small{L}$-carnitine ($\small{L}$-car), pyridoxine hydrochloride (PH), and $\small{DL}$-${\alpha}$-tocopheryl acetate (${\alpha}$-T) in an IF model system. MRP formation was monitored by response surface methodology using fluorescence intensity (FI) and 5-hydroxymethylfurfural (HMF) content. The optimal condition for minimizing the formation of MRPs was with $2.3{\mu}M$ $\small{L}$-car, $15.8{\mu}M$ PH, and $20.6{\mu}M$ ${\alpha}$-T. Under this condition, the predicted values were 77.4% FI and 248.7 ppb HMF.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Pediatric Infection and Vaccine
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• v.26 no.1
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• pp.1-10
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• 2019

Purpose: We investigated the distribution and antimicrobial resistance of pneumococcal isolates from hospitalized children at Asan Medical Center for recent 4 years, and aimed to recommend proper choice of empirical antibiotics for pneumococcal infection. Methods: From March 2014 to May 2018, children admitted to Asan Medical Center Childrens' Hospital with pneumococcal infection were subjected for evaluation of minimal inhibitory concentration (MIC) for ${\beta}-lactams$ and macrolide antibiotics. Patient's age, underlying disease, gender were retrospectively collected. Using Monte Carlo simulation model and MIC from our study, we predicted the rate of treatment success with amoxicillin treatment. Results: Sixty-three isolates were analyzed including 20.6% (n=13) of invasive isolates, and 79.4% (n=50) of non-invasive isolates; median age were 3.3 years old, and 87.3% of the pneumococcal infections occurred to children with underlying disease. Overall susceptibility rate was 49.2%, 68.2%, and 74.6% for amoxicillin, parenteral penicillin, and cefotaxime respectively. 23.8% and 9.5% of the isolates showed high resistance for amoxicillin, and cefotaxime. Only 4.8% (n=3) were susceptible to erythromycin. Monte Carlo simulation model revealed the likelihood of treatment success was 46.0% at the dosage of 90 mg/kg/day of amoxicillin. Conclusions: Recent pneumococcal isolates from pediatric patients with underlying disease revealed high resistance for amoxicillin and cefotaxime, and high resistance for erythromycin. Prudent choice of antibiotics based on the local data of resistance cannot be emphasized enough, especially in high risk patients with underlying disease, and timely vaccination should be implemented for prevention of the spread of resistant strains.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1120-1133
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• 2018

The purpose of this study is to validate the failure attribution factors affecting emotional changes after a failed service by local restaurant users, and the relapse effects of the perceived failure of a customer's brand relationship. In this study, the implications of this study can be divided into the null theory and the homogenous theory, in which the study of the relationship between individual belief that influences the null theory and the post-gender emotional response is minimal. The independence of the crash response (angerous VS compassion) has been equally validated as building a belief-gathering-emotion three-step model. First, emotional BRQ (intimate and love) has a reduction effect on controllable geeks, and behavioral BRQ (relative existence) has an extended effect on controllable geeks. From a management perspective, restaurant managers should be less aware of the repeatability of a customer's service failure and call for customer sympathy. Integratedly, restaurant managers must control the customer's perception of service failure and restore the impact of the customer's BRQ on emotional reactions. A variety of service recovery measures should be established and the cerumen should be controlled. In addition, since BRQs have different effects on anger and sympathy (extended VS), different service failure recovery plans should be presented depending on the characteristics of the customer BRQ. For example, measures such as monetary compensation or fair dealing, emotional distribution to close and loving customers, and persuasion of reciprocal benefits to interdependent customers should be developed according to circumstances. This study explored the effectiveness of the geeks after a service failure and has limitations that do not take into account the various regulatory factors in the BRQ-return-Empression process. Thus, in further studies, the effects of adjusting service failure strength should be considered and a more complete model should be built.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.101-109
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• 2022

The mobility and transport of radioactive cesium are crucial factors to consider for the safety assessment of high-level radioactive waste disposal sites in granite. The retardation of radionuclides in the fractured crystalline rock is mainly controlled by the hydrochemical condition of groundwater and surface reactions with minerals present in the fractures. This paper reports the experimental results of cesium sorption to the Wonju Granite, a typical Mesozoic granite in Korea, performed in an anaerobic chamber that mimics the anoxic environment of a deep disposal site. We measured the rates and amounts of cesium (¹³³Cs) removed by crushed granite samples in different electrolyte (NaCl, KCl, and CaCl₂) solutions and a synthetic groundwater solution, with variations in the initial cesium concentration (10^-5, 5×10^-6, 10^-6, 5×10^-7 M). The cesium sorption kinetic and isotherm data were successfully simulated by the pseudo-second-order kinetic model (r²= 0.99) and the Freundlich isotherm model (r²= 0.99), respectively. The sorption distribution coefficient of granite increased almost linearly with increasing biotite content in granite samples, indicating that biotite is an effective cesium scavenger. The cesium removal was minimal in KCl solution compared to that in NaCl or CaCl₂ solution, regardless of the ionic strength and initial cesium concentration that we examined, showing that K⁺ is the most competitive ion against cesium in sorption to granite. Because it is the main source mineral of K⁺ in fracture fluids, biotite may also hinder the sorption of cesium, which warrants further research.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.1
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• pp.33-39
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• 2006

Purpose: To determine appropriate sampling frequency and time of multiple blood sampling dual exponential method with $^{99m}Tc$-DTPA for calculating glomerular filtration rate (GFR). Materials & Methods: Thirty four patients were included in this study. Three mCi of $^{99m}Tc$-DTPA was intravenously injected and blood sampling at 9 different times, 5ml each, were done. Using the radioactivity of serum, measured by gamma counter, the GFR was calculated using dual exponential method and corrected with the body surface area. Using spontaneously chosen 2 data points of serum radioactivity, 15 collections of 2-sample GFR were calculated. And 10 collections of 3-sample GFR and 12 collections of 4-sample GFR were also calculated. Using the 9-sample GFR as a reference value, degree of agreement was analyzed with Kendall's $\tau$ correlation coefficients, mean difference and standard deviation. Results: Although some of the 2-sample GFR showed high correlation coefficient, over or underestimation had evolved as the renal function change. The 10-120-240 min 3-sample GFR showed a high correlation coefficient (${\tau}=0.93$), minimal difference ($Mean{\pm}SD=-1.784{\pm}3.972$), and no over or underestimation as the renal function changed. The 4-sample GFR showed no better accuracy than the 3-sample GFR. Conclusions: In the wide spectrum of renal function, the 10-120-240 min 3-sample GFC could be the best choice for estimating the patients' renal function.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.34 no.2
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• pp.180-186
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• 2008

Purpose: This study was performed to evaluate the effect of the implant recipient site preparation methods on primary stability of implants with the instruments of $Osstell^{TM}$ and $Periotest^{(R)}$ in the iliac bone of cadaver. Methods and materials: The 8 iliac bones in 4 cadavers and implants treated with resorbable blasting media (RBM) were used. $Periotest^{(R)}$ (Simens AG, Germany) and $Osstell^{TM}$ (Model 6 Resonance Frequency Analyser: Integration Diagnostics Ltd., Sweden) were used to measure primary stability of implants. Implants were inserted into the iliac crest of the cadaver. In control group, the recipient site was prepared according to the manufacturer's recommendation: 1.8 mm guide drill, 2.0 mm initial drill, 2.7 mm pilot drill, 2.7 mm twist drill, 3.0 mm twist drill, 3.3 mm pilot drill, 3.3 mm twist drill, and 3.3 mm countersink drill as well as tapping drill were used in order. In the group 1, implant recipient sites were prepared by sequentially drilling from 1.8 mm guide drill to 3.0 mm twist drill and then inserted implants without countersinking and tapping. In the group 2, implant recipient sites were prepared to 3.0 mm twist drill and countersink drill and then inserted implants without tapping. In the group 3, the sites were prepared to 3.0 mm twist drill and countersink drill as well as tapping drill. In the group 4, the sites were prepared to 3.3 mm twist drill. In the group 5, the sites were prepared to 3.3 mm twist drill and countersink drill. A total of 60 implants were placed (n=10). The stability was measured using $Osstell^{TM}$ and $Periotest^{(R)}$ mesiodistally and buccolingually. To compare the mean stability of each group statistically, One-way ANOVA was used and correlation of instrument were analyzed using SPSS 12.0. The results obtained were as follows; 1. The stability of group 1 measured using $Osstell^{TM}$ and $Periotest^{(R)}$ buccolingually showed the highest, and there are significant difference statistically between control group and experimental group 1,2,4 in each instruments respectively (p<0.05). 2. The stability of group 1 measured using $Osstell^{TM}$ and $Periotest^{(R)}$ mesiodistally showed the highest. There are significant difference statistically between control group and all experimental groups in $Osstell^{TM}$, and between control group and experimental group 1,2,3,4 (p<0.05). 3. There are high correlation between the measurements of $Osstell^{TM}$ and $Periotest^{(R)}$ (p<0.05). Conclusion: These results indicate that the primary stability of implant can be obtained by the recipient sites preparation with smaller diameter drill than that of implant or minimal drilling.

• Food Science and Preservation
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• v.11 no.2
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• pp.195-200
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• 2004

Microbial lethal value and nutrient retention of sous vide processed spinach were evaluated with mathematical model prediction and experimental trial for different package sizes and pasteurization temperatures. The package size covers 500 g, 1 kg and 2 kg, while the pasteurization temperature includes 80, 90 and 97$^{\circ}C$. The basic process scheme consists of filling blanched spinach into barrier plastic film pouch, sealing under vacuum, pasteurization in hot water with over pressure and final cooling to 3$^{\circ}C$. Pasteurization condition was designed based on attainment of 6 decimal inactivation of Listeria monocytogenes at geometric center of the pouch package by heating cycle, which was determined by general method. Heat penetration property of the package and thermal destruction kinetics were combined to estimate the retention of ascorbic acid and chlorophyll. Smaller packages with shorter pasteurization time gave better nutrient retention, physical and chemical qualities. Larger package size was estimated and confirmed experimentally to give higher pasteurization value at center, lower ascorbic acid and chlorophyll contents caused by longer heat process time. Lower pasteurization temperature with longer process time was predicted to give lower pasteurization value at center and lower ascorbic acid, while chlorophyll content was affected little by the temperature. Experimental trial showed better retention of ascorbic acid and chlorophyll for smaller package and higher pasteurization temperature with shorter heating time. The beneficial effect of smaller package and higher pasteurization temperature was also observed in texture, color retention and drip production.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.11
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• pp.1386-1396
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• 2017

The purpose of this study was to determine the optimum Platycodon grandiflorum root concentrate (PGRC, $65^{\circ}Brix$), fermented P. grandiflorum root extract by Lactobacillus plantarum (FPGRE, $2^{\circ}Brix$), and cactus Chounnyouncho extract (Cactus-E, $2^{\circ}Brix$) for preparation of PGRC stick product with FPGRE using response surface methodology (RSM). The experimental conditions were designed according to a central composite design with 20 experimental points, including three replicates for three independent variables such as amount of PGRC (8~12 g), FPGRE (0~20 g), and Cactus-E (0~20 g). The experimental data for the sensory evaluation and functional properties based on antioxidant activity and antimicrobial activity were fitted with the quadratic model, and accuracy of equations was analyzed by ANOVA. For the responses, sensory and functional properties showed significant correlation with contents of three independent variables. The results indicate that addition of PGRC contributed to increased bitterness and acridity based on the sensory test and antimicrobial activity, addition of FPGRE contributed to increased antioxidant activity and antimicrobial activity, and addition of Cactus-E contributed to increased fluidity based on the sensory test, antioxidant activity, and antimicrobial activity. Based on the results of RSM, the optimum formulation of PGRC stick product was calculated as PGRC 8.456 g, FPGRE 20.00 g, and Cactus-Ex 20.00 g with minimal bitterness and acridity, as well as optimized fluidity, antioxidant activity, and antimicrobial activity.