• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.1
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• pp.1-19
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• 2022

The Geumgang Pine (Pinus densiflora) Forest in Sogwang-ri, Uljin has traditionally been a pine tree protection area (prohibited forest) for timber production purposes, and is now designated and managed as a protected area for forest genetic resource conservation by the Korea Forest Service. This study, we analyzed topographical characteristics, existing vegetation, tree age, and plant community structure, and proposed a sustainable management method for the Geumgang Pine (Pinus densiflora) Forest in Sogwang-ri, Uljin for timber havesting purposes. The topographical characteristics of the target area were 36.7% ridges and 38.7% valleys; the ratio of ridges to valleys was similar, and the slopes formed 24.7% of the total area. The types of pine forest communities are divided into six types based on the progress of pine forest renewal, the competition with other species such as deciduous broadleaf trees, and the formation of layered structures. It has been confirmed that the age of the large-diameter pine trees (40~60cm in diameter) is approximately 60~70 years, which is relatively low. As a result of the analysis of the relative importance percentage and layered structure, differences depended on the progress of the pine forest renewal project, and not only the maintenance of the pine forest, but also the creation of a secondary growth forest, the density adjustment of pine trees, and the active management of competitive trees. The average basal area by the community was 12,642.1~25,424.4cm² for the tree layer and 1.8~1,956.5cm² for the low tree layer based on a quadrat of 400m². The difference in the basal area appeared to depend on the size and number of trees forming the tree layer and the degree of pine forest renewal (the degree of time elapsed after thinning pine trees). The average number of species that appeared in each community was 8.7-20.3; there were many species located in valleys, and the type competes with deciduous broadleaf trees due to the lack of management. The diversity of species ranged from 0.6915-1.0942, and was evaluated as low compared to pine communities in central temperate zones. In this paper, we determined the management goals of Geumgang Pine (Pinus densiflora) Forest in Sogwang-ri, Uljin to produce timber with high economic value, and suggested efficient vegetation management for continuous afforestation, the establishment of a timber production system, and improvement of wood production as a management direction.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.41-59
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• 2022

The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.

• Journal of fish pathology
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• v.35 no.1
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• pp.1-25
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• 2022

The aquaculture industry has developed rapidly over the last three decades and is an important industry that supplies over 15% of humans' animal protein intake; therefore, there is a need to increase production to meet the continuous demand. The fish cage farms on the southern coast (Kyengsangnam-do and Jeollanam-do) of Korea are critical resources in aquaculture because they account for approximately 90% of the national total fish cage farms by water area ratio. However, the current aquaculture environment is being gradually affected by climate change, which is a global issue, and its effects are expected to intensify in the future. Therefore, it is urgently imperative to accurately evaluate the effects of climate change on South Korean aquaculture industries and to develop social and national strategies to minimize damage to the fishing industry. The damage to fish farmed in cage farms on the southern coast is increasing annually and the leading causes are high and low water temperature and red tides, which are directly or indirectly related to climate change. At present, global warming can provide opportunities for aquaculture industrialization of fish or other novel species, with economic implications. However, despite such opportunities, the influx of new species can also cause problems such as ecological disturbances, increase in the reproduction frequency of microalgae such as red tide, increase in disease incidence, and occurrence and periods of high water temperatures in summer. The scale of farmed fish mortality is increasing due to the complex effects of these factors. Increased damages due to fish mortality not only have severe economic impacts on the aquaculture industry, but the social costs of responding to the damage and follow-up measures also increase. various active responses can reduce the mortality damage in fish farms such as improving the management skills in aquaculture, improved species breeding, efficient food management, disease prevention, proactive responses, and system-wide improvements. This review article analyzes the large-scale mortality cases occurring in fish cage farms on the southern coast of Korea and proposes measures to mitigate mortality and enhance responses to such scenarios.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.1
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• pp.1-17
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• 2023

Purpose. The purpose of this study was to examine the correlation between the finish line designs and the marginal adaptation of nonprecious metal alloy coping produced by different digital manufacturing methods. Materials and methods. Nonprecious metal alloy copings were made respectively from each master model with three different methods; SLS, milling and casting by computer aided design and computer aided manufacturing (CAD-CAM). Twelve copings were made by each method resulting in 72 copings in total. The measurement was conducted at 40 determined reference points along the circumferential margin with the confocal laser scanning microscope at magnification ×150. Results. Mean values of marginal gap of laser sintered copings were 11.8 ± 7.4 ㎛ for deep chamfer margin and 6.3 ± 3.5 ㎛ for rounded shoulder margin and the difference between them was statistically significant (P < .0001). Mean values of marginal gap of casted copings were 18.8 ± 20.2 ㎛ for deep chamfer margin and 33 ± 20.5 ㎛ for rounded shoulder margin and the difference between them was significant (P = .0004). Conclusion. Within the limitation of this study, the following conclusions were drawn. 1. The variation of finish line design influences the marginal adaptation of laser sintered metal coping and casted metal coping. 2. Laser sintered copings with rounded shoulder margin had better marginal fit than deep chamfer margin. 3. Casted copings with deep chamfer margin had better marginal fit than rounded shoulder margin. 4. According to the manufacturing method, SLS system showed the best marginal fit among three different methods. Casting and milling method followed that in order.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.15-19
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• 2022

Purpose [⁶⁸Ga]PSMA-11 is needed the high reproducibility, excellent radiochemical yield and purity. In term of radiation safety, the radiation exposure of operator for its production also should be considered. In this work, we performed a comparative study for the fully automated synthesis of [⁶⁸Ga]PSMA-11 between non-cassette type and cassette type. Materials and Methods Two different type of modules (TRACERlab FX N pro for non-cassette type and BIKBox for cassette type) were used for the automated production of [⁶⁸Ga]PSMA-11. According to the previously identified elution profile, Only 2.5 ml with high radioactivity was used for the reaction. After adjusting the pH of the reaction solution with HEPES buffer solution, the precursor was added and reacted with at 95 ℃ for 15 minutes. The reaction mixture was separated and purified using a C18 light cartridge. The product was eluted with 50% EtOH/saline solution and diluted with saline. It was completed by sterilizing filter. In the non-cassette type, the aforementioned process must be prepared directly. However, in the cassette method, synthesis was possible simply by installing a kit that was already completed. Results Both total [⁶⁸Ga]PSMA-11 production time were 25±3(non-cassette type) and 23±3 minutes(cassette type). The radiochemical yield of the non-cassette type(65.5±5.7%) was higher than that of the cassette type(61.6±4.8%) after sterilization filter. The non-cassette type took about 120 minutes of preparation time before synthesis due to washing of synthesizer and reagent preparation. However, since the cassette type does not require washing and reagent preparation, it took about 20 minutes to prepare before synthesis. Both type of synthesizer had a radiochemical high purity(>99%). Conclusion The non-cassette type production of [⁶⁸Ga]PSMA-11 showed higher radiochemical yield and lower cost than the cassette type. However, The cassette type has an advantage in terms of preparation time, convenience, and equipment maintenance.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.361-381
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• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.

• 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.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.