• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.959-974
• /
• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• 한국사회정책
• /
• v.25 no.3
• /
• pp.37-71
• /
• 2018

Since 2016, public and political interest on basic income has been increased beyond academic interest. The recent debate on basic income has expanded on issues regarding to the concrete implementation of basic income moving further than the debate on conception of the basic income in the abstract level. This study examines major critiques of basic income which was raised from social policy area and makes a counter-argument on these critiques. Major points summarized as follows. First, the problem of jobs and social insurance exclusion is not serious enough to call for basic income. Second, existing social security systems will be crowded out by excessive financial burden if basic income is introduced. Third, policies to cultivate citizens' capacities to cope with a technological change should be given priority over basic income. This study disputes these critiques by counter arguing four points. First, it is necessary to reconstruct welfare state based on basic income, given the labor market changes, such as long-term trend of employment change, newly emerging employment of platform companies, and inconsistency of platform labor and social insurance. Second, hypothesis of crowding-out effect on social security system is just a criticism that can be applied to the basic income initiative of the right-wing. Also, it is unable to find a logical basis or evidence of this hypothesis from the historical process of welfare state development or previous studies. Third, it is necessary to discuss how to reconfigure existing social security system and basic income which are complementary to each other and also have consistency with labor market as a configuration, not as a matter of choosing between basic income and social security system. Fourth, de-laborization does not mean a refusal to labor but a free choice, and the basic principle of social security is not needs but right. In conclusion, in order to develop more productive debate on basic income, it requires more sophisticated discussion and criticism from the point of view of the distributive justice; the debate on the sustainability of social insurance-centered welfare states; and debates on the political realization of basic income.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.5
• /
• pp.78-90
• /
• 2019

The purpose of this study is to explore the direction of developing policies for parks and green spaces for inclusive urban planning and regeneration. By reviewing the status, budget, and laws pertaining to urban parks in Korea, as well as assessing the inclusivity of urban parks, this study revealed the problems and limitations in Korea as follows. First, the urban park system, which takes into account indicators such as park area per capita and green space ratio, is focused only on quantitative expansion. Second, the distribution of urban parks is unequal; hence, the higher the number of vulnerable residents, the lower the quality of urban parks and green spaces. Moreover, this study focused on the UK central government, along with the five local governments, including London, Edinburgh, Cardiff, Belfast, and Liverpool. Through an analysis of the contexts and contents establishing UK park and green space policies that can reduce socioeconomic inequalities while at the same time increase inclusiveness. This study discovered the following. The government's awareness of the necessity of tackling socioeconomic inequalities to make an inclusive society, the change in the urban regeneration policies from physical redevelopment to neighborhood renewal, and the survey and research on the correlation of parks and green spaces, inequality, health, and well-being provided the background for policy establishment. As a result, the creation of an inclusive society has been reflected in the stated goals of the UK's national plan and the strategies for park and green space supply and qualitative improvement. Deprived areas and vulnerable groups have been included in many local governments' park and green space policies. Also, tools for analyzing deficiencies in parks and methods for examining the qualitative evaluation of parks were developed. Besides, for the sustainability of each project, various funding programs have been set up, such as raising funds and fund-matching schemes. Different ways of supporting partnerships have been arranged, such as the establishment of collaborative bodies for government organizations, allowing for the participation of private organizations. The study results suggested five policy schemes, including conducting research on inequality and inclusiveness for parks and green spaces, developing strategies for improving the quality of park services, identifying tools for analyzing policy areas, developing park project models for urban regeneration, and building partnerships and establishing support systems.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.75-94
• /
• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.17-32
• /
• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.104-115
• /
• 2022

Purpose: Infrastructure inspection and its diagnostics technique have been rapidly developing recently. Therefore, it is important to secure the reliability of diagnostic equipment, and this paper deals with inspection of diagnostic equipment, introduction to a certification system and development plans for infrastructure. Method: Several certification systems are established and introduction plans are reviewed through experts by synthesizing the contents of certification research for existing infrastructure diagnosis equipment. In addition, the revision of the law for introduction of the system is reviewed, detailed operation regulations are prepared and phased development plans are reviewed, which are based on the operation scenario. Result: Inspection and certification plans were constructed through four routes in order to consider infrastructure inspection and diagnostic equipment in use, and new diagnostic equipment using state-of-the-art technology. Furthermore, market confusion depending on the introduction of a new certification system is minimized and reliability is secured by transforming a simple inspection system in the short term into a formal certification system in the long term. The law amendments according to the introduction of the system were reviewed and detailed operation regulations were developed. Also, phased development plans, which are based on the long-term development scenario including manpower, infrastructure and specifications, were presented. Conclusion: It is important to secure reliability through the distribution and certification of diagnostic equipment using 4th industrial technology to strengthen the safety management of infrastructure at the national level since the infrastructure is various in type and increasingly large in size. It is also essential to train human resources who can use new technology with inspection and diagnosis system in order to enhance the safety management of all infrastructures. Moreover, it is necessary to introduce a regular inspection system for infrastructure that combines loT technology in the long-term point of view and to promote the introduction by giving active incentives to institutions that actively accept it.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.185-209
• /
• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.16 no.1
• /
• pp.193-206
• /
• 2014

The objectives of the project are to increase farmers' income through GAP and to reduce the loss of agricultural produce, for which the Korean partner takes a role of transferring needed technologies to the project site. To accomplish the project plan, it is set to implement the project with six components: construction of buildings, installation of agricultural facilities, establishment of demonstration farms, dispatching experts, conducting training program in Korea and provision of equipments. The Project Management Committee and the Project Implementation Team are consisted of Korean experts and senior officials from Department of Agriculture, Myanmar that managed the project systematically to ensure the success of the project. The process of the project are; the ceremony of laying the foundation and commencing the construction of training center in April, 2012. The Ribbon Cutting Ceremony for the completion of GAP Training Center was successfully held under PMC (MOAI, GAPI/ARDC) arrangement in SAl, Naypyitaw on June 17, 2012. The Chairman of GAPI, Dr. Sang Mu Lee, Director General U Kyaw Win of DOA, officials and staff members from Korea and Myanmar, teachers and students from SAl attended the ceremony. The team carried out an inspection and fixing donors' plates on donated project machineries, agro-equipments, vehicles, computers and printer, furniture, tools and so forth. Demonstration farm for paddy rice, fruits and vegetables was laid out in April, 2012. Twenty nine Korean rice varieties and many Korean vegetable varieties were introduced into GAP Project farm to check the suitability of the varieties under Myanmar growing conditions. Paddy was cultivated three times in DAR and twice in SAl. In June 2012, vinyl houses were started to be constructed for raising seedlings and finished in December 2012. Fruit orchard for mango, longan and dragon fruit was established in June, 2012. Vegetables were grown until successful harvest and the harvested produce was used for panel testing and distribution in January 2013. Machineries for postharvest handling systems were imported in November 2012. Setting the washing line for vegetables were finished and the system as run for testing in June 2013. New water tanks, pine lines, pump house and electricity were set up in October 2013.

• Korean Journal of Environmental Biology
• /
• v.39 no.4
• /
• pp.526-535
• /
• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.69-88
• /
• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.