• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.180-187
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• 2022

In order to select suitable light in a plant factory, electric energy use efficiency and light use efficiency should be considered simultaneously to consider operating costs as well as quantitative and functional aspects. The growth characteristics, electric energy use efficiency, light use efficiency by light intensity, LED ratio, and photoperiod conditions were compared together. Light intensity is 60, 130, 230, and 320 µmol·m^-2·s^-1 treatments, and light quality is the mixing ratio of red light and blue light 8:2, 6:4, 4:6, and 2:8 treatments. Photoperiod is 9, 12, 15, and 18 hours treatments based on the daytime. In the light intensity experiment, the growth rate increased as the light intensity increased, but there was no significant difference in the light use efficiency. When comparing the leaf fresh weight per power consumption, only the 320 µmol·m^-2·s^-1 treatment group showed significantly low efficiency, and there was no significant difference in the other treatments, so 230 µmol·m^-2·s^-1, which produced the most, was the most efficient. In the light quality experiment, the ratio of red light and blue light was measured to be high at the same time as the growth rate and light use efficiency in RB 8:2, and there was no significant difference in color difference and flavonoids content, so a Red:Blue ratio of 8:2 was the most suitable condition. In the photoperiod experiment, the longer the photoperiod, the higher the growth rate. However, there was no significant difference in the growth rate over 12 hours of daytime, so 12 hours considering the light consumption efficiency was a suitable condition. Based on the above results, LED light environmental conditions for perilla growth in plant factories were light intensity, light quality, and day length of 230 µmol·m^-2·s^-1 or more, 8:2, and 12 hours or more, respectively.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.1-14
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• 2023

When carrying out development projects around Ardeidae breeding habitats, we intend to devise a plan for sustainable coexistence by presenting measures to select and reduce key evaluation items so that conflicts can be prevented in advance at the environmental impact assessment stage. The results of the study are as follows. The main evaluation items are animal and plant items for preservation of Ardeidae breeding habitats and odor and noise items that can evaluate the effects of odors and noise in Ardeidae breeding habitats. First, the scope of the survey in animals and plants categories is not limited to legal guardian species, but includes egrets breeding and feeding grounds corresponding to major species breeding grounds and migratory birds, and preservation measures are established according to the reduction of the area of breeding and feeding grounds. Second, in the odor category, the irradiation period includes the period when the odor generation is the highest from the end of June to the end of July. The odor evaluation standard is based on the complex odor discharge standard, which is a concentration regulation, and the odor concentration felt by humans shall be 2 to 5OU/m³ and the frequency shall be 2% or less. Third, in the noise category, the timing of the survey is measured every month from May to August, including when the sound of egrets and young birds is combined to maximize noise generation. Since the noise of Ardeidae, a bird in summer, occurs only for a certain period of time, measures are taken to reduce noise by securing separation distances, securing buffer green areas, and installing construction rather than installing artificial structures such as soundproof walls. In order for existing Ardeidae breeding sites to maintain an appropriate density of populations and not move populations elsewhere, it is necessary to manage nesting tree and maintain stable habitat quantity and quality.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• The Korean Journal of Mycology
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• v.51 no.2
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• pp.81-90
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• 2023

The cultivation method of shiitake is divided into two methods: log cultivation and sawdust cultivation. Recently, the importance of sawdust cultivation has been highlighted due to problems such as environmental problems, rising labor costs, and a reduced labor force. Among the 24 Sawdust-cultivated Lentinula edodes cultivars in Korea stored by the National Institute of Forest Science, this study was conducted to select excellent cultivars under the sawdust block cultivation method. After inoculation, the sawdust mediums were cultured for 100 days (60 days in dark and then 40 days in light), and only Sanjo 712ho sprouted the primordia on the 10^th day of light culture (total 70 days of cultivation). As a result of cultivation, the average total yield of the 24 cultivars were 1,816 g and Sanjo 712ho was 2,267 g. The fruiting body yield was the highest in Sanjo 713ho with 3,443 g followed by Sanjo 710ho (3,355 g). Sanlim 10ho, Sansanhyang, and Sanjo 716ho showed low production with 174, 238, and 214 g, respectively. As a result of investigating the morphological characteristics of the fruit bodies, the fresh weight of Sansanhyang and Bambithyang was about twice as heavy as the overall average, and Sulbaekhyang was about twice as light. Bambithyang was the largest and longest in diameter and length of the stipe, and the thickness of the stem was the thickest in Sanjo 716ho. As for the hardness of pileus, Bambithyang showed the highest value at 1,276 g/5 mm, and Sanjo 711ho showed the lowest value at 542 g/5 mm. In summary, Bambithyang showed the best fruiting body characteristics and Sanjo 713ho showed the highest yield in the sawdust block cultivation method. This study, the cultivar with shortened cultivation periods and cultivars with excellent morphological characteristics and high yields.

• Journal of Science Education
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• v.47 no.2
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• pp.180-191
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• 2023

The purpose of this study was to investigate the preferred SSI topics of students and teachers in elementary, middle, and high schools. It analyzed the similarity of students' and teachers' preferred SSI topics by school level using the cosine similarity measure. A total of 566 students and 327 teachers from elementary, middle, and high schools participated in the study. Sixty topics were identified and listed in the areas of environment, science and technology, health and medicine, and other social issues based on the literature and SSI programs. Students and teachers were asked to select five of their favorite topics. The data was collected online using SurveyMonkey. The collected data was divided into six groups of students and teachers, and the frequency of topic selection was analyzed within each group. The topic preference similarity was analyzed by calculating vector values based on the frequency of the selected topics and measuring the cosine similarity between students, teachers, and teachers and students by school level. The results are as follows: First, the cosine similarity of SSI Preferred Topics between students' school-level cohorts was higher between middle and high school students (0.982) than between elementary and middle school students (0.651) or between elementary and high school students (0.662). Second, the cosine similarity of SSI Preferred Topics between teachers' school-level cohorts was similar for all comparison groups between elementary, middle, and high school. Third, the SSI topic preference similarity between students and teachers by school level had a higher cosine similarity between the elementary student and teacher cohorts (0.974) than the other school level comparisons, middle school (0.621) or high school (0.645). Access to topics of interest to students in SSI education is strongly associated with motivation and persistence in learning, as well as an enjoyable learning experience and positive attitudes toward learning. Therefore, when designing SSI lessons, it is important to examine topics from the perspective of student interest, especially if the teacher has selected SSI topics that are different from students' preferences. Careful instructional design will be needed to overcome the gap.

• Korean Journal of Forensic Psychology
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• v.12 no.1
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• pp.15-33
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• 2021

In this study, we analyzed the difference in survival rates of those subject to electronic supervision of sex crimes based on the tracking of the period of recidivism and whether they were recidivism, and wanted to confirm the ability of the criminal record to predict recidivism. The criteria for recidivism were defined as cases where a conviction was confirmed due to a criminal case that occurred during the execution of electronic monitoring, and the date of recidivism was the date of occurrence of a case that was confirmed guilty. A total of 122 re-offenders were used in the analysis, and all of them were charged with electronic supervision for committing sex crimes. Studies have confirmed that the subjects commit the most recidivism within three years. In addition, in this study, the difference in survival rate between groups was analyzed after classifying mixed and sex recidivism cases. The number of members was 88 for the mixed recidivism group and 34 for the sex recidivism group. The analysis confirmed that both groups had the most recidivism within three years. There was a slight difference between the survival rate of the mixed recidivism group and the survival rate of the sex recidivism group. So the Log Rank Test and the Generalized Wilcoxon Test were conducted, but no statistically significant differences were identified(Wilcoxon statistic = 2.326, df = 1, p = .13, Log Rank = 1.345, df = 1, p = .25). Next, a Cox Regression analysis was performed to confirm the ability of the criminal record to predict recidivism. As a result, the number of criminal records(sex offense, violent crime) have been confirmed to be a good predictor of recidivism(X²=27.33, df=1, p< .001). As a result, the recidivism rate is gradually decreasing due to the implementation of the electronic monitoring. However, the duration of recidivism required by sex offenders in high-risk groups was found to be rather short. Currently, security measures against felons are being strengthened, so it is necessary to select high-risk groups. Therefore, based on the related studies, the characteristics of high-risk groups and the results of recidivism studies will be used as a basis for disposal within the criminal justice system, which will play a major role in granting objectivity.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.737-760
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• 2022

For the geological disposal of high-level radioactive wastes (HLW), an understanding of deep subsurface environment is essential through geological, hydrogeological, geochemical, and geotechnical investigations. Although South Korea plans the geological disposal of HLW, only a few studies have been conducted for characterizing the geochemistry of deep subsurface environment. To guide the hydrogeochemical research for selecting suitable repository sites, this study overviewed the status and trends in hydrogeochemical characterization of deep groundwater for the deep geological disposal of HLW in developed countries. As a result of examining the selection process of geological disposal sites in 8 countries including USA, Canada, Finland, Sweden, France, Japan, Germany, and Switzerland, the following geochemical parameters were needed for the geochemical characterization of deep subsurface environment: major and minor elements and isotopes (e.g., ³⁴S and ¹⁸O of SO₄^2-, ¹³C and ¹⁴C of DIC, ²H and ¹⁸O of water) of both groundwater and pore water (in aquitard), fracture-filling minerals, organic materials, colloids, and oxidation-reduction indicators (e.g., Eh, Fe²⁺/Fe³⁺, H₂S/SO₄^2-, NH₄⁺/NO₃^-). A suitable repository was selected based on the integrated interpretation of these geochemical data from deep subsurface. In South Korea, hydrochemical types and evolutionary patterns of deep groundwater were identified using artificial neural networks (e.g., Self-Organizing Map), and the impact of shallow groundwater mixing was evaluated based on multivariate statistics (e.g., M3 modeling). The relationship between fracture-filling minerals and groundwater chemistry also has been investigated through a reaction-path modeling. However, these previous studies in South Korea had been conducted without some important geochemical data including isotopes, oxidationreduction indicators and DOC, mainly due to the lack of available data. Therefore, a detailed geochemical investigation is required over the country to collect these hydrochemical data to select a geological disposal site based on scientific evidence.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.70-83
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• 2022

This study aims to select evaluation items that can be used in planning park creation to evaluate the proposal to solve the environmental and social problems in promoting private-initiated park development projects. To this end, evaluation items that can consider various aspects of the development project were selected, and the indicators' validity and appropriateness were carried out through an expert Focus Group Interview (FGI). Firstly, an expert FGI was performed for six major categories and 50 evaluation items derived from literature reviews and brainstorming. As a result, five major and 27 middle category items were selected. Based on the derived major and middle classification items, 95 detailed items were selected. Secondly, 55 sub-items were derived through a suitability questionnaire. As a result of the suitability survey, the average scores of the subcategories for the major categories of natural environment, function of parks, and use of land were relatively high. The average scores for environmental index items such as ecology/vegetation, topography and slope, landscape, park service, wildlife, wide-area ecosystem, and park items were high in the middle classification. The average score of indicators in the natural environment was relatively high, and the average score in the function of parks also soared. In the environmental impact assessment, the occurrence of plan change issues, including the reappraisal of the location, led to unclear detailed evaluation factors for the faithfulness of the plan and the appropriateness of the plan direction. This study is significant in that it is a study on the selection of evaluation items that can minimize the problem of plan alteration and achieve objective evaluation when promoting development projects. This study could be used to forward development projects in the future and evaluate long-term unexecuted urban parks.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.285-299
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• 2023

Estimating the evapotranspiration is very important factor for effective water resources management, and FAO Penman-Monteith (FAO P-M) model has been applied for reference evapotranspiration estimation by many researchers. However, because various input data are required for the application of FAO P-M model, understanding the effect of each input data on FAO P-M model is necessary. Therefore, in this study, for 56 study stations located in South Korea, the effects of 8 meteorological factors (maximum and minimum temperature, wind speed, relative humidity, solar radiation, vapor pressure deficit, net radiation, ground heat flux), energy and aerodynamic terms of FAO P-M model, and elevation on FAO P-M reference evapotranspiration (RET) estimation were analyzed. The relative sensitivity analysis was performed to determine how 10% increment of each specific independent variable affects a reference evapotranspiration under given set of condition that other independent variables are unchanged. Furthermore, to select the 5 representative stations and perform the monthly relative sensitivity analysis for those stations, 56 study stations were classified into 5 clusters using cluster analysis. The study results showed that net radiation was turned out to be the most sensitive factor in 8 meteorological factors for 56 study stations. The next most sensitive factor was relative humidity, solar radiation, maximum temperature, vapor pressure deficit and wind speed, followed by minimum temperature in order. Ground heat flux was the least sensitive factor. In case of ground surface condition, elevation showed very low positive relative sensitivity. Relativity sensitivities of energy and aerodynamic terms of FAO P-M model were 0.707 for energy term and 0.293 for aerodynamic term respectively, indicating that energy term was more contributable than aerodynamic term for reference evapotranspiration. The monthly relative sensitivities of meteorological factors showed the seasonal effects, and also the relative sensitivity of elevation showed different pattern each other among study stations. Therefore, for the application of FAO P-M model, the seasonal and regional sensitivity differences of each input variable should be considered.