• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of Energy Engineering
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• v.28 no.2
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• pp.18-35
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• 2019

The Korea District Heating Corporation operates a gas engine generator with a capacity of $4500m^3 /day$ of biogas generated from the sewage treatment plant of the Nanji Water Recycling Center and 1,500 kW. However, the actual operation experience of the biogas power plant is insufficient, and due to lack of accumulated technology and know-how, frequent breakdown and stoppage of the gas engine causes a lot of economic loss. Therefore, it is necessary to prepare technical fundamental measures for stable operation of the power plant In this study, a series of process problems of the gas engine plant using the biogas generated in the sewage treatment plant of the Nanji Water Recovery Center were identified and the optimization of the actual operation was made by minimizing the problems in each step. In order to purify the gas, which is the main cause of the failure stop, the conditions for establishing the quality standard of the adsorption capacity of the activated carbon were established through the analysis of the components and the adsorption test for the active carbon being used at present. In addition, the system was applied to actual operation by applying standards for replacement cycle of activated carbon to minimize impurities, strengthening measurement period of hydrogen sulfide, localization of activated carbon, and strengthening and improving the operation standards of the plant. As a result, the operating performance of gas engine # 1 was increased by 530% and the operation of the second engine was increased by 250%. In addition, improvement of vent line equipment has reduced work process and increased normal operation time and operation rate. In terms of economic efficiency, it also showed a sales increase of KRW 77,000 / year. By applying the strengthening and improvement measures of operating standards, it is possible to reduce the stoppage of the biogas plant, increase the utilization rate, It is judged to be an operational plan.

• Food Engineering Progress
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• v.21 no.1
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• pp.42-48
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• 2017

The purpose of this study was to verify the drying characteristics of steamed sweet potato and to establish optimal drying conditions for far-infrared drying of steamed sweet potato. 4 kg of steamed sweet potato was sliced to thicknesses of 8 and 10 mm, and dried by a far-infrared dryer until a final moisture content of $25{\pm}0.5%$. The far-infrared dryer conditions were an air velocity of 0.6, 0.8 m/s and drying temperature of 60, 70, and $80^{\circ}C$. The results can be summarized as follows. The drying time tended to be reduced as temperature and air velocity for drying increased. The Lewis and Modified Wang and Singh models were found to be suitable for drying of steamed sweet potato by a far-infrared dryer. The color difference was 35.09 on the following conditions: Thickness of 8 mm, temperature of $80^{\circ}C$, and air velocity of 0.8 m/s. The highest sugar content ($59.11^{\circ}Brix$) was observed on the conditions of a thickness of 8 mm, temperature of 80, and air velocity of 0.8 m/s. Energy consumption decreased on the conditions of higher temperature, slower air velocity, and thinner steamed sweet potato.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Food Hygiene and Safety
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• v.36 no.4
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• pp.298-309
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• 2021

In this study we sought to develop a simultaneous analysis method for cis-bixin and cis-norbixin, the main components, to detect annatto pigment in food. To establish the optimal test method, the HPLC analysis methods of the European Food Safety Authority (EFSA), Japan's Ministry of Health, Labor and Welfare (MHLW), and National Institute of Food and Drug Safety Evaluation (NIFDS) were compared and reviewed. In addition, a new pretreatment method applicable to various foods was developed after selecting conditions for simultaneous high-performance liquid chromatography (HPLC) analysis in consideration of linearity, limit of detection (LOD), limit of quantification (LOQ), and analysis time. The HPLC analysis method of NIFDS showed the best linearity (R² ≥ 0.999), exhibiting low detection and quantification limits for cis-norbixin and cis-bixin as 0.03, 0.05 ㎍/mL, and 0.097, 0.16 ㎍/mL, respectively. All previously reported pretreatment methods had limitations in various food applications. However, the new pretreatment method showed a high recovery rate for all three main food groups of fish meat and meat products, processed cheese and beverages. This method showed an excellent simultaneous recovery rate of 98% or more for cis-bixin and cis-norbixin. The HPLC analysis method with a new pretreatment method showed high linearity with a coefficient of determination (R²) of 1 for both substances, and the accuracy (recovery rate) and precision (%RSD) were 98% and between 0.4-7.9, respectively. From this result, the optimized analytical method was considered to be very suitable for the simultaneous analysis of cis-bixin and cis-norbixin, two main components of annatto pigment in food.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.21-33
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• 2021

The purpose of this study is to determine the order of priority for the use of amendments, matching the optimal amendment to the specific site in Korea. This decision-making process must prioritize the stabilization and economic efficiency of amendment for heavy metals and metalloid based on domestic site contamination scenarios. For this study, total 5 domestic heavy metal contaminated sites were selected based on different pollution scenarios and 13 amendments, which were previously studied as the soil stabilizer. Batch extraction experiments were performed to quantify the stabilization efficiency for 8 heavy metals (including As and Hg) for 5 soil samples, representing 5 different pollution scenarios. For each amendment, the analyses using XRD and XRF to identify their properties, the toxicity characteristics leaching procedure (TCLP) test, and the synthetic precipitation leaching procedure (SPLP) test were also conducted to evaluate the leaching safety in applied site. From results of batch experiments, the amendments showing > 20% extraction lowering efficiency for each heavy metal (metalloid) was selected and the top 5 ranked amendments were determined at different amount of amendment and on different extraction time conditions. For each amendment, the total number of times ranked in the top 5 was counted, prioritizing the feasible amendment for specific domestic contaminated sites in Korea. Mine drainage treatment sludge, iron oxide, calcium oxide, calcium hydroxide, calcite, iron sulfide, biochar showed high extraction decreasing efficiency for heavy metals in descending order. When the economic efficiency for these amendments was analyzed, mine drainage treatment sludge, limestone, steel making slag, calcium oxide, calcium hydroxide were determined as the priority amendment for the Korean field application in descending order.

• Clean Technology
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• v.28 no.1
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• pp.24-31
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• 2022

Petroleum-based plastics are used for various purposes and pose a significant threat to the earth's environment and ecosystem. Many efforts have been taken globally in different areas to find alternatives. As part of these efforts, this study manufactured alginate-based polyvinyl alcohol (PVA) blended films by casting from an aqueous solution prepared by mixing 10 wt% petroleum-based PVA with biodegradable, marine biomass-derived alginate. Glutaraldehyde was used as a cross-linking agent, and cardanol, an alkyl phenol-based bio-oil extracted from cashew nut shell, was added in the range of 0.1 to 2.0 wt% to grant antibacterial activity to the films. FTIR and TGA were performed to characterize the manufactured blended films, and the tensile strength, degree of swelling, and antibacterial activity were measured. Results obtained from the FTIR, TGA, and tensile strength test showed that alginate, the main component, was well distributed in the PVA by forming a matrix phase. The brittleness of alginate, a known weakness as a single component, and the low thermal durability of PVA were improved by cross-linking and hydrogen bonding of the functional groups between alginate and PVA. Addition of cardanol to the alginate-based PVA blend significantly improved the antibacterial activity against S. aureus and E. coli. The antibacterial performance was excellent with a death rate of 98% or higher for S. aureus and about 70% for E. coli at a contact time of 60 minutes. The optimal antibacterial activity of the alginate-PVA blended films was found with a cardanol content range between 0.1 to 0.5 wt%. These results show that cardanol-containing alginate-PVA blended films are suitable for use as various antibacterial materials, including as food packaging.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.257-270
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• 2022

This study evaluated the hydraulic factors contributing to the decreasing groundwater levels across Jeju island. Time-series data for groundwater level, precipitation, and groundwater usage and information on land use were acquired, and the correlations among them were analyzed to evaluate the causes of the decreasing groundwater. The effects of precipitation and groundwater usage on the fluctuations of groundwater level were quantified using response surface analysis and sensitivity analysis, and methods for groundwater quantity management by region were proposed. The results showed that the rate of groundwater decrease in the western region was larger than that in the eastern region. For the eastern region, the influence of precipitation was large and the rate of decrease in the groundwater level was relatively small. The geological formation of this part of the island and continuous seawater intrusion suggest that although the absolute amount of groundwater extracted for use was large, the decrease in the groundwater level was not seen to be great due to an increase in pressure by seawater intrusion. Overall, precipitation and groundwater usage had the greatest effect on the amount of groundwater in the western region, and thus their data would be most useful for informing groundwater management, whereas other factors (e.g., sea level and the location of the freshwater-seawater transition zone) must be considered when understanding Jeju's eastern region. As the characteristics of groundwater level fluctuations in the eastern and western regions are distinct, an optimal management plan for each region should be proposed to ensure the efficient management of groundwater quantity.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.51-61
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• 2022

Earthenware horn cups with horse head decorations were excavated from Tomb No. 7 of Bokcheon-dong, Dongraegu, Busan Metropolitan City. Made of earth in the shape of a horn, these cups are considered to have been used to drink alcohol or beverage. Large numbers of earthenware horn cups of various shapes were excavated from tombs located in the old territories of Silla and Gaya. A pair of earthenware horn cups were excavated from Tomb No. 7, and the two cups are almost identical in overall shapes and manufacturing techniques despite different sizes. Conservation treatment was carried out for the bigger one of the two horn cups this time. There are two cracks toward the horse head decorations around the mouth with missing parts observed. The chest of the horse touches the ground with one side decorating the horse head and the other side facing the conical mouth of the horn cup. It is in the U shape, striking a balance based on two legs attached behind. The surface of the horn cup was made with a potter's wheel, and the connection to the horse head has traces of cutting and trimming. The horse head is expressed realistically with its features including the ears, eyes, nose, and mouth well apprehended and its color is grey This study intended to investigate manufacturing techniques of the artifact by examining its internal structure through the condition survey in a non-destructive way. CT imaging was used to figure out its manufacturing techniques and to diagnose its condition, and accordingly the scientific conservation treatment was conducted to stabilize the artifact. The precise diagnosis on conservation condition found that there are two chips in the spout with their cracks extended. One of the chips is connected with separation added to the crack. The material which has been used for connection in the past was collected for the infrared spectroscopic analysis, which was identified to be nitrocellulose resin for the connection. Therefore, this conservation treatment focused on removing the old material and preventing the spread of cracks. Before conservation treatment, the condition survey and scientific examination for the artifact were carried out to secure data about the earthenware horn cup with horse head decorations(Treasure). Based on them, effective plans for its conservation treatment was sought for and then existing adhesive was safely removed, and restoration material was selected to take into account its reversibility. In addition, the conservation treatment according to optimal methodologies was conducted through the consultation meeting with experts.