• Korean Journal of Ecology and Environment
• /
• v.46 no.1
• /
• pp.33-40
• /
• 2013

From March 2012 to January 2013, this study was conducted as a part of the project for making a precise electronic ecological zoning map of vegetation on a highly reduced scale of 1 to 5,000 with a view to improving management efficiency of national parks and enlarging the availability of the data produced from the basic research monitoring the resources of national parks. For the research accuracy and rapidity, a vegetation map was specially created for the on-the-site-vegetation research. To make the map more meticulous, we categorized the vegetation database into five groups: broadleaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. After comparing the results of the data built for the vegetation research and the actual research findings, it was made clear that vegetation of both categories was almost the same in case of broad-leaved forest with 72.20% and 78.45% respectively, and also equivalent in other groups like, for example, coniferous forest (16.70%, 13.41%), mixed forest (9.50%, 7.49%) and rock vegetation (0.60%, 0.15%). According to the precise vegetation map produced from the research, the deciduous broad-leaved forest was the most widely prevalent type in the correlated hierarchical classification of vegetation, occupying 65.78% of the overall vegetation. It was followed by mountain valley forest (15.17%), coniferous forest (10.90%), and plantation forest (7.00%) in order. It is particularly noteworthy that Mt. Deogyusan national park has retained a very stable and versatile forest vegetation in the outstanding state since approximately 20% of the mountain turns out to belong to the I grade vegetation conservation classification which contains climax forests, unique vegetation, subalpine vegetation, matured stands which are older than 50 years and etc.

• Korean Journal of Environment and Ecology
• /
• v.32 no.5
• /
• pp.486-496
• /
• 2018

In this study, we have selected Larix kaempferi as a study area in Woraksan National Park for understanding the ion index according to the difference of topography in national parks. We measured the weather and ion at two fixed points, ridge and valley, where the Larix kaempferi dominates in the same ecological structure in Woraksan National Park. The weather measurement results showed the average, maximum, and minimum temperatures of $28.22^{\circ}C$, $29.9^{\circ}C$, and $26.4^{\circ}C$, respectively at the ridge. The average, maximum, and minimum temperatures at the valley were $27.08^{\circ}C$, $27.8^{\circ}C$, and $25.5^{\circ}C$, respectively. The average, maximum, and minimum relatively humidities at the ridge were 67.02%, 75.25%, and 61.95%, respectively. he average, maximum, and minimum relatively humidities at the valley were 69.74%, 76.8%, and 63.75%, respectively. The average, maximum, and minimum amounts of positive ions generated in the ridge was $698.40{\pm}59.80ea/cm^3$, $885.88ea/cm^3$, and $597.88ea/cm^3$, respectively. The average, maximum, and minimum amounts of negative ions generated in the ridge were $736.07{\pm}83.89ea/cm^3$, $934.53ea/cm^3$, and $599.32ea/cm^3$, respectively. The ion index is calculated to be 1.06. The average, maximum, and minimum amounts of positive ions generated in the valley were $1,732.49{\pm}354.08ea/cm^3$, $2,652.10ea/cm^3$, and $1,110.92ea/cm^3$, respectively. The average, maximum, and minimum amounts of negative ions generated in the valley were $1,990.47{\pm}433.57ea/cm^3$, $3,126.75ea/cm^3$, and the minimum value was $1,352.17ea/cm^3$. The ion index is calculated to be 1.16. The difference in the amount of negative ions generated in ridge and valley was $1089.26ea/cm^3$, and the difference of the calculated ion index between the ridge portion and the valley portion was 0.10. The results of this study were provided as the reference weather data of national parks for health management.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.131-146
• /
• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• Korean Journal of Environment and Ecology
• /
• v.27 no.2
• /
• pp.219-229
• /
• 2013

This research is performed in order to suggest seasonal effective research time that is applied to wild birds research which lives in a forest. The subject area of this research is Mulgun-ri village forest in Samdong-Myeon, Namhe-gun. To investigate suitability of the project, existing land-use, existing vegetation, vegetational structure, and etc. of the subject and whole area are figured out. To suggest adequate research time, based on seasonal sun rise and set time for 3days, repetitive research is performed at hourly intervals. The subject area is connected with a forest and is possible for forest wild birds to flows in and provides various habitats and feeding areas. And also the subject area is a appropriate area for wild birds research and is like a natural forest in that a layer structure development of the forest itself, a distribution of Zelkova serrata and Aphananthe aspera and so on. 105 species which is observed in subject area are categorized and mountain birds are classified. After time-based peak value is selected in each season, hourly species richness, diversity, and index of similarity are analyzed as compared with the appearing number of species and individual bird. As a result, 7~11 hour is the most effective time in spring, and 8~9 hour is the best time. In summer, 6~9 hour is the most appropriate time when whole appearing species are similar to species structure. In fall, 7~11(30~60 minutes after sun rise) when wild birds movements are vigorous is analyzed easy to observe and 8~9 hour is the most appropriate research time because each analysis shows the best values. In winter, 7~12 hour is the most effective time although 10~11 hour is the best time but it is decided that similar results are drawn because hourly deviation is not so big except 1 hour before sun rise. In every four season, it is decided that 30~60 minutes after sun rise is appropriate to research a group of wild birds in the subject area.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.1
• /
• pp.101-111
• /
• 2015

Stream restoration projects have become threats to riparian ecosystem in Rep. of korea. Riparian wildlife becomes isolated and the animals are often experience difficulties in crossing riparian corridors. The purposes of this study is to select suitable wildlife passages for wild animals crossing riparian corridors. Maximum entropy model and snow tracking data on embankment in winter seasons were used to develop species distribution models to select suitable wildlife passages for water deer. The analysis suggests the following. Firstly, most significant factors for water deer's habitat in area nearby riparian area are shown to distance to water, age-class, land cover, slope, aspect, digital elevation model, tree density, and distance to road. For the riparian area, significant factors are shown to be land cover, size of riparian area, distance to tributary, and distance to built-up. Secondly, the suitable wildlife passages are recommended to reflect areas of high suitability with Maximum Entropy model in riparian areas and the surrounding areas and moving passages. The selected suitable areas are shown to be areas with low connectivity due to roads and vertical levee although typical habitats for water deer are forest, grassland, and farmland. In addition, the analysis of traces on snow suggests that the water deer make a detour around the artificial structures. In addition, the water deer are shown to make a detour around the fences of roads and embankment around farmland. Lastly, the water deer prefer habitats around riparian areas following tributaries. The method used in this study is expected to provide cost-efficient and functional analysis in selecting suitable areas.

• Korean Journal of Environment and Ecology
• /
• v.36 no.2
• /
• pp.139-149
• /
• 2022

This study aimed to prepare basic data for protecting the habitat of Fairy Pitta Pitta nympha and coping with climate change by detecting songs with bio-acoustic recording technology and identifying phenological characteristics in protected areas in Korea. The study sites were 36 protected areas nationwide. Data were collected between January and December 2019, and the analysis period was from May 1 to August 31, 2019. The main results are described as follows. Firstly, songs were detected in 22 out of 36 study sites. Frequency analysis results of songs show that high frequency was observed in southern inland, including Jeju island, and the area with the highest latitude was Seoraksan National Park. Secondly, the first song was observed in Hallyeohaesang National Park Geumsan on May 14, 2019, and the last song was observed in Ungok wetland in Gochang on August 6, 2019. Thirdly, circadian rhythm analysis results of songs show that the frequency rapidly increased at five o'clock in the morning, peaked at six o'clock, and then decreased afterward. Fourthly, seasonal cycle analysis results of songs show that they were observed from May 14, 2019 to August 6, and the day with the highest accumulated frequency of songs was June 3, 2019 (Julian date: 154). The average temperature of the day the songs were detected was 17.4℃, the average precipitation was 0.02mm, and the average humidity was 82.6%. Fifthly, a correlation analysis result between Fairy Pitta's songs and meteorological factors shows that temperature indicated a negative correlation with Fairy Pitta's songs (p<0.001), but precipitation (p=0.053) and humidity (p=0.077) did not indicate a statistical significance (df=471). This study is significant in that it confirmed the distribution of Fairy Pitta's songs using bio-acoustic recording technology in protected areas nationwide and identified their ecological characteristics by precisely analyzing the relationship between the song period and meteorological factors.

• Journal of Bio-Environment Control
• /
• v.31 no.1
• /
• pp.67-76
• /
• 2022

This study aimed to determine the photosynthesis and growth characteristics of Peucedanum japonicum T. grown under aquaponics in a plant factory (AP) by comparing those grown under hydroponic cultivation system (HP). The AP system raised 30 fishes at a density of 10.6 kg·m^-3 in a 367.5 L tank, and at HP, nutrient solution was controlled with EC 1.3 dS·m^-1 and pH 6.5. The pH level ranged from 4.0 to 7.1 for the AP system and 4.0 to 7.4 for the HP system. The pH level in the AP began to decrease with an increase in nitrate nitrogen (NO₃-N) and lasted bellower than pH 5.5 for 15-67 DAT. It was found that ammonium nitrogen (NH₄-N) continued to increase even under low pH conditions. EC was maintained at 1.3 to 1.5 dS·m^-1 in both systems. The concentration of major mineral elements in the fish tank was higher than that of the hydroponics, except for K and Mg. There was no significant difference in the photosynthesis characteristics, but the PIABS parameters were 30.4% lower in the AP compared to the HP at the 34DAT and 12.0% lower at the 74DAT. There was no significant difference in the growth characteristics, but the petiole length was 56% longer in the leaf grown under the AP system. While there was no significant difference in the fresh and dry weights of leaf and root, the leaf area ratio was 36.43% higher in the AP system. All the integrated results suggest that aquaponics is a highly-sustainable farming to safely produce food by recycling agricultural by-products, and to produce Peucedanum japonicum as much as hydroponics under a proper fish density and pH level.

• Korean Journal of Environment and Ecology
• /
• v.38 no.2
• /
• pp.204-216
• /
• 2024

Understanding the trade-off effect in ecosystem services and measuring the interrelationships between services are crucial for managing limited environmental resources. Accordingly, in this study, we identified the dominant trends and increases and decreases in ecosystem services derived from changes in land cover over about 30 years and tracked changes in the relationships between ecosystem services that occurred over time. Through it, we determined the relationship between land cover changes and ecosystem service changes, as well as the distinct characteristics of service changes in different areas. The research primarily utilized the InVEST model, an ecosystem service assessment model. After standardizing the evaluation results between 0 and 1, it went through principal component analysis, a dimensionality reduction technique, to observe the time-series changes and understand the relationships between the services. According to the research results, the area of urbanized regions dramatically increased between 1989 and 2019, while forests showed a significant increase between 2009 and 2019. Between 1989 and 2019, the national ecosystem service supply witnessed a 13.9% decrease in water supply, a 10.5% decrease in nitrogen retention, a 2.6% increase in phosphorus retention, a 0.9% decrease in carbon storage, a 1.2% increase in air purification, and a 3.4% decrease in habitat quality. Over the past 30 years, South Korea experienced an increase in urbanized areas, a decrease in agricultural land, and an increase in forests, resulting in a trade-off effect between phosphorus retention and habitat quality. This study concluded that South Korea's environment management policies contribute to improving ecosystem quality, which has declined due to urbanization, and maximizing ecosystem services. These findings can help policymakers establish and implement forestry policies focusing on sustainable environmental conservation and ecosystem service provision.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.221-241
• /
• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Korean Journal of Environment and Ecology
• /
• v.32 no.6
• /
• pp.698-708
• /
• 2018

The purpose of this study was to investigate differences in the breeding call characteristics of cicada species found in urban and forest areas in the central region of Korea by examining the interspecific effects and environmental factors affecting the breeding calls and breeding call patterns. The selected research sites were Gyungnam Apartment in Bangbae-dong, Seoul for the urban area and Chiak Mountain National Park in Wonju for the forest area. The research method for both sites was to record cicada breeding calls for 24 hours with a recorder installed at the site and analyze the results. Data from the Korea Meteorological Administration were used for environmental factors. The research period was from June 19, 2017 to September 30, 2017. As a result of the study, there were differences in the emergence of species between the two research sites: while Platypleura kaempferi, Hyalessa fuscata, Meimuna opalifera, Graptopsaltria nigrofuscata, and Suisha coreana were observed at both sites, Cryptotympana atrata was observed in the urban area and Leptosemia takanonis in the forest area only. The emergence periods of cicadas at the two sites were also different. The activities of P. kaempferi and L. takanonis were noticeable in the forest area. In the urban area, however, L. takanonis was not observed and the duration of activity of P. kaempferi was short. In the urban area, C. atrata appeared and sang for a long period; H. fuscata, M. opalifera, and G. nigrofuscata appeared earlier than in the forest area. S. coreana appeared earlier in the forest area than in the urban area. According to the daily call cycle analysis, even cospecific cicada showed a wide variation in their daily cycle depending on the region and the interspecific effects between different cicadas, and the environmental differences between the urban and forest areas affected the calls of cicadas. The results of correlation analysis between each cicada breeding calls and environmental factors of each site showed positive correlation with average temperature of most cicadas except P. kaempferi and C. atrata. The same species of each site showed positive correlations with more diverse weather factors such as solar irradiance. Logistic regression analysis showed that cicadas with overlapping calling times had significant effects on each other's breeding calls. C. atrata, which appeared only in the urban area, had a positive effect on the calling frequency of H. fuscata, M. opalifera, and G. nigrofuscata, which called in the same period. Additionally, L. takanonis, which appeared only in the forest area, and P. kaempferi had a positive effect on each other, and M. opalifera had a positive effect on the calling frequency of H. fuscata and G. nigrofuscata in the forest area. For the environmental factors, the calling frequency of cicadas was affected by the average temperatures of the urban and forest areas, and cicadas that appeared in the forest area were also affected by the amount of solar radiation. According to the results of statistical analysis, urban cicadas with similar activity periods are influenced by species, especially with respect to urban dominant species, C. atrata. Forest cicadas were influenced by species, mainly M. opalifera, which is a forest dominant species. The results of the meteorological impact analysis were similar to those of the correlation analysis, and were influenced mainly by the temperature, and the influence of the insolation was more increased in the forests.