• Food Engineering Progress
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• v.23 no.3
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• pp.193-199
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• 2019

This study aimed to investigate the impact of protease treatments on the yield of rice starch (RST) from frozen rice flours, and to compare the physicochemical properties of RST by alkaline steeping (control) and enzymatic isolation (E-RST) methods. Although the yield of E-RST, prepared according to conditions designed by the modified 23 complete factorial design, was lower than the control, the opposite trends were observed in its purity. E-RST (RST1, isolated for 8 h at 15℃ with 0.5% protease; RST2, isolated for 24 h at 15℃ with 1.5% protease; RST3, isolated for 24 h at 15℃ with 0.5% protease) with the yields above 50% were selected. Amylose contents did not significantly differ for the control and RST2. Relative to the control, solubilities were higher for all E-RST, but swelling power did not significantly differ for E-RST except for RST1. Although all E-RST revealed higher gelatinization temperatures than the control, the reversed trends were found in the gelatinization enthalpy. The pasting viscosities of all E-RST were lower than those of the control. Consequently, the enzymatic isolation method using protease would be a more time-saving and eco-friendly way of preparing RST than the alkaline steeping method, even though its characteristics are different.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.141-149
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• 2018

In this study, compacting, passing performance, segregation resistance and rheological properties were tested to improve the stability of fresh concrete in the production and construction of self-compacting concrete (SCC) using hollow glass powder(GB). As a result, T50 reaching time was shortened up to amount of GB $2.0kg/m^3$. The compacting according to the amount of GB was improved by ball bearing effect of GB. However, T50 reaching time was slightly increased at $4.0kg/m^3$. In the case of passing performance, the result showed that plain was Class 1, GB $0.5{\sim}2.0kg/m^3$ was Class 0, GB $4.0kg/m^3$ was Class 1. Therefore, the passing performance was improved with 'No blocking' up to amount of GB $2.0kg/m^3$. Passing performance Block step (PJ) number by J-ring method was also best at GB $1.0kg/m^3$. In the case of segregation resistance according to the amount of GB, dynamic segregation resistance was increased compared to plain regardless of the amount of GB. And static segregation resistance showed 2.5% of segregation rate at GB $1.0kg/m^3$. Therefore, it was greatly improved compared to plain (12.5%). In the case of rheology property according to the amount of GB, plastic consistency by increasing of GB content didn't show big difference. However, yield stress by increasing of GB content was decreased with GB $1.0kg/m^3$. In conclusion, GB $1.0kg/m^3$ was effective for improvement of compacting, passing performance and yield stress. Also, it will be useful for stability of SCC by improving segregation.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.469-477
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• 2018

Hanabusaya asiatica is an endemic species whose distribution is limited in the mid-eastern part of the Korean peninsula. Due to its narrow range and small population, it is necessary to protect its habitats by identifying it as Key Biodiversity Areas (KBAs) adopted by the International Union for Conservation of Nature (IUCN). In this paper, we estimated potential natural habitats for H. asiatica using maximum entropy model (MaxEnt) and identified candidate sites for KBA based on the model results. MaxEnt is a machine learning algorithm that can predict habitats for species of interest unbiasedly with presence-only data. This property is particularly useful for the study area where data collection via a field survey is unavailable. We trained MaxEnt using 38 locations of H. asiatica and 11 environmental variables that measured climate, topography, and vegetation status of the study area which encompassed all locations of the border region between South and North Korea. Results showed that the potential habitats where the occurrence probabilities of H. asiatica exceeded 0.5 were $778km^2$, and the KBA candidate area identified by taking into account existing protected areas was $1,321km^2$. Of 11 environmental variables, elevation, annual average precipitation, average precipitation in growing seasons, and the average temperature in the coldest month had impacts on habitat selection, indicating that H. asiatica prefers cool regions at a relatively high elevation. These results can be used not only for identifying KBAs but also for the reference to a protection plan for H. asiatica in preparation of Korean reunification and climate change.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.2
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• pp.169-181
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• 2007

Statement of problem: Titanium is well known as a proper metal for the dental restorations, because it has an excellent biocompatibility, resistance to corrosion, and mechanical property. However, adhesion between titanium and dental porcelains is related to the diffusion of oxygen to the reaction layers formed on cast-titanium surfaces during porcelain firing and those oxidized layers make the adhesion difficult to be formed. Many studies using mechanical, chemical and physical methods to enhance the titanium-ceramic adhesion have been actively performed. Purpose: This study meant to comparatively analyse the adhesion characteristics depending on different titanium surface coatings after coating the casts and wrought titanium surfaces with Au and TiN. Material and method: In this study, the titanium specimens (CP-Ti, Grade 2, Kobe still Co. Japan) were categorized into cast and wrought titanium. The wrought titanium was cast by using the MgO-based investment(Selevest CB, Selec). The cast and wrought titanium were treated with Au coating($ParaOne^{(R)}$., Gold Ion Sputter, Model PS-1200) and TiN coating(ATEC system, Korea) and the ultra low fusing dental porcelain was fused and fired onto the samples. Biaxial flection test was done on the fired samples and the porcelain was separated. The adhesion characteristics of porcelain and titanium after firing and the specimen surfaces before and after the porcelain fracture test were observed with SEM. The atomic percent of Si on all sample surfaces was comparatively analysed by EDS. In addition, the constituents of specimen surface layers after the porcelain fracture and the formed compound were evaluated by X-ray diffraction diagnosis. Result: The results of this study were obtained as follows : 1. The surface characteristics of cast and wrought titanium after surface treatment(Au, TiN, $Al_2O_3$ sandblasting) were similar and each cast and wrought titanium showed similar bonding characteristics. 2. Before and after the biaxial flection test, the highest atomic weight change of Si component was found in $Al_2O_3$ sandblasted wrought titanium(28.6at.% $\rightarrow$ 8.3at.%). On the other hand, the least change was seen in Au-Pd-In alloy(24.5at.% $\rightarrow$ 9.1at.%). 3. Much amount of Si components was uniformly distributed in Au and TiN coated titanium, but less amount of Si's was unevenly dispersed on Al2O3 sandblasting surfaces. 4. In X-ray diffraction diagnosis after porcelain debonding, we could see $Au_2Ti$ compound and TiN coating layers on Au and TiN coated surfaces and $TiO_2$, typical oxide of titanium, on all titanium surfaces. 5. Debonding of porcelain on cast and wrought titanium surface after the biaxial flection is considered as a result of adhesion deterioration between coating layers and titanium surfaces. We found that there are both adhesive failure and cohesive failure at the same time. Conclusion: These results showed that the titanium-ceramic adhesion could be improved by coating cast and wrought titanium surfaces with Au and TiN when making porcelain fused to metal crowns. In order to use porcelain fused to titanium clinically, it is considered that coating technique to enhance the bonding strength between coating kKlayers and titanium surfaces should be developed first.

• Economic and Environmental Geology
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• v.46 no.3
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• pp.221-234
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• 2013

Laboratory experiments for the reaction with supercritical $CO_2$ under the $CO_2$ sequestration condition were performed to investigate the mineralogical and geochemical weathering process of the sandstones and mudstones in the Pohang basin. To simulate the supercritical $CO_2$-rock-groundwater reaction, rock samples used in the experiment were pulverized and the high pressurized cell (200 ml of capacity) was filled with 100 ml of groundwater and 30 g of powdered rock samples. The void space of the high pressurized cell was saturated with the supercritical $CO_2$ and maintained at 100 bar and $50^{\circ}C$ for 60 days. The changes of mineralogical and geochemical properties of rocks were measured by using XRD (X-Ray Diffractometer) and BET (Brunauer-Emmett-Teller). Concentrations of dissolved cations in groundwater were also measured for 60 days of the supercritical $CO_2$-rock-groundwater reaction. Results of XRD analyses indicated that the proportion of plagioclase and K-feldspar in the sandstone decreased and the proportion of illite, pyrite and smectite increased during the reaction. In the case of mudstone, the proportion of illite and kaolinite and cabonate-fluorapatite increased during the reaction. Concentration of $Ca^{2+}$ and $Na^+$ dissolved in groundwater increased during the reaction, suggesting that calcite and feldspars of the sandstone and mudstone would be significantly dissolved when it contacts with supercritical $CO_2$ and groundwater at $CO_2$ sequestration sites in Pohang basin. The average specific surface area of sandstone and mudstone using BET analysis increased from $27.3m^2/g$ and $19.6m^2/g$ to $28.6m^2/g$ and $26.6m^2/g$, respectively, and the average size of micro scale void spaces for the sandstone and mudstone decreased over 60 days reaction, resulting in the increase of micro pore spaces of rocks by the dissolution. Results suggested that the injection of supercritical $CO_2$ in Pohang basin would affect the physical property change of rocks and also $CO_2$ storage capacity in Pohang basin.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.3
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• pp.267-274
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• 2017

This study discusses the applicability of environmental friendly EVA based butyl rubber self-adhesive waterproof sheet designed to prevent corrosion of large scale pipes used in the water treatment facilities during th water treatment process. The experiments conducted tested the waterproofing sheet's adhesion strength on the steel surface of the pipes and checked for whether the material has the proper response properties against the various environmental conditions. In addition, it the sheet adhered to the steel pipe was to see if the adhesion hold against the water pressure due to the ingress of inflow water. Finally, the waterproofing sheet's adhesion strength was tested on a rusted steel surface to confirm whether the material has the necessary properties to secure stable adhesion strength and prevent corrosion of steel pipes at the same time during the process of installation or maintenance. As a result, the self-adhesive waterproof sheets showed that all attachments in the untreated, long term pressuring, immersion in chemical substance (hydrochloric acid, hypochlorous acid, sodium hydroxide), low temperature ($-20^{\circ}C$) conditions showed a adhesion performance of higher than 1.5N/mm, which is the performance standard of KS F 4934. Also, in the testing to check for the adhesion property against inverse water pressure, it was observed that the adhesion failure did not occur even up to $3.0N/mm^2$ pressure. Also, in the process of assessing the adhesion performance on rusted steel surface, specimens after 12 hours of corrosion treatment was shown to have 2.1N/mm, and specimens after 168 hours of corrosion treatment was shown to have 2.0N/mm adhesion strength performance.

• Journal of Chest Surgery
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• v.42 no.2
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• pp.148-156
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• 2009

Background: As cardiovascular operations become more complex and sophisticated, there is an increasing need for various bioprostheses for use as components of blood vessels and heart valves. We developed a fatigue stimuli test instrument to objectively evaluate the mechanical durability of a bioprosthesis, and we tested several currently known processing methods for bovine pericardium and we then compared the results. Material and Method: Fresh bovine pericardium was collected at the butcher shop with using aseptic technique, and each piece of pericardium was fixated and/or decellularized by 16 representative methods. We measured the permeability and compliance of the processed bovine pericardium samples, and measured them again after exposure to the fatigue stimuli. All the pieces of pericardium underwent microscopic examinations before and after the fatigue stimuli. Result: A mixture of glutaraldehyde and solvent treatment showed better mechanical durability than did the single glutaraldehyde treatment. High concentration glutaraldehyde treatment showed equal or no worse results than did low concentration glutaraldehyde treatment. After SDS (sodium dodecylsulfate) decellularization, the mechanical property of the bioprosthesis became much worse ($20{\sim}190$ times) and the mechanical durability to the fatigue stimuli was also very poor. Conclusion: We obtained the basic durability data after various fixation methods with using a home-made fatigue test instrument.