• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.127-135
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• 2012

This paper introduced the flow forecast modeling system that a water management agency in west central Florida, Tampa Bay Water has been operated to forecast monthly rainfall and streamflow in the Tampa Bay region, Florida. We evaluated current 1-year monthly rainfall forecasts and flow forecasts and actual observations to investigate the benefits of incorporating rainfall forecasts into monthly flow forecast. Results for rainfall forecasts showed that the observed annual cycle of monthly rainfall was accurately reproduced by the $50^{th}$ percentile of forecasts. While observed monthly rainfall was within the $25^{th}$ and $75^{th}$ percentile of forecasts for most months, several outliers were found during the dry months especially in the dry year of 2007. The flow forecast results for the three streamflow stations (HRD, MB, and BS) indicated that while the 90 % confidence interval mostly covers the observed monthly streamflow, the $50^{th}$ percentile forecast generally overestimated observed streamflow. Especially for HRD station, observed streamflow was reproduced within $5^{th}$ and $25^{th}$ percentile of forecasts while monthly rainfall observations closely followed the $50^{th}$ percentile of rainfall forecasts. This was due to the historical variability at the station was significantly high and it resulted in a wide range of forecasts. Additionally, it was found that the forecasts for each station tend to converge after several months as the influence of the initial condition diminished. The forecast period to converge to simulation bounds was estimated by comparing the forecast results for 2006 and 2007. We found that initial conditions have influence on forecasts during the first 4-6 months, indicating that FMS forecasts should be updated at least every 4-6 months. That is, knowledge of initial condition (i.e., monthly flow observation in the last-recent month) provided no foreknowledge of the flows after 4-6 months of simulation. Based on the experimental flow forecasts using the observed rainfall data, we found that the 90 % confidence interval band for flow predictions was significantly reduced for all stations. This result evidently shows that accurate short-term rainfall forecasts could reduce the range of streamflow forecasts and improve forecast skill compared to employing the stochastic rainfall forecasts. We expect that the framework employed in this study using available observations could be used to investigate the applicability of existing hydrological and water management modeling system for use of stateof-the-art climate forecasts.

• Korean Journal of Heritage: History & Science
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• v.38
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• pp.329-358
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• 2005

The Three storied Stone pagoda in Gameunsa Temple site, one of the early staged stone pagodas, has been known as a standard for Silla stone pagodas. A stone pagoda is not only a stone art work and but also a stone structure. Most studies and investigation of the stone pagoda has done mainly based on style and chronological research according to an art historical view. However, there is not an attempt to research the stone pagoda as a stone architecture. Most Korean experts at the stone pagoda has art history in their background. Engineers who can understand the structure of the stone pagoda are very limited. More architectural and engineering approach is need to research not only art historial understanding but also safety as a structure. We can find many technical know-how from our ancestors who made stone pagodas. 1. To reduce any deformation such as relaxation and sinking of BuJae which is caused by a heavy load, the BuJae (consist of a foundation stone and lower stereobates) should be enlarged. 2. A special construction method for connection between Myonsuk and Tangjoo was invented. This unique method is not used any longer after the Three storied Stone pagoda in Gameunsa Temple site. 3. The upper BuJae and the lower BuJae are missed each other by making a difference of Okgaesuk and Okgaebatchim in size. It is done for a distribution of perpendicular load and a prevention for relaxation of BuJae. 4. The center of gravity in the BuJae is located to the center of the stone pagoda by trimming the upper surface of the Okgaebatchim into a convex shape. The man who made stone pagodas had excellent knowledge on the engineering and techniques to understand the structure of the stone pagodas. We can confirm it as follows: the enlarged BuJae, dislocated connection between upper Bujae and lower BuJae, and moving the center of gravity close to the center of the stone pagoda.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.1-9
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• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.2
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• pp.14-25
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• 2009

We live in an age which is exponentially growing as the knowledge paradigm is changing. New sites are subject to contemporary landscape architecture function as "fields" in which this hybrid aspect is both actively practiced and becoming a catalyst for change in the area of landscape architecture. With this as its background, this study attempts to deal with how the aspect of integration in environmental design is manifested. For this purpose, the tendencies for the discussion of integration in various fields of practice were examined: planning theories, urban theories, architecture, public environment, engineering, and landscape architecture. As yet, the discussions of interdisciplinary integration, which occur in practice in these respective fields, mainly tend to be oriented toward the effective implementation of the merits of other related fields. Seen from these examples of practice, integrated design approaches can be found in the following three aspects: design objects, respective professional areas, and methodologies of approaches and design. In terms of design objects, the positions of individual design subjects present themselves as most obvious, and integration or combination of the physical targets that come to exist through design can be easily seen. Most examples of integration turn out to be this, in almost every case of which the theme and the target of expression are integrated via a small number of certain methods. In terms of professional areas, what can be mainly evidenced is how the individual subject acts when the subject designs. The strong points of professionals from each field seem to create synergy, achieving through integration optimum results. In terms of methodologies of approaches and design, there are attempts to create integrated approaches as ways of effective decision-making, in which case the integration of all of the interest parties is of primary concern. As yet, few instances have been found in which integrated design has had enough strength to be seen as a concrete design methodology based on practical examples. However, it is encouraging that theoretical approaches and the necessity for integrated design have been identified from multiple perspectives, and that a practical movement such as landscape urbanism has come into active being. The authors of this study find this point in time to be ripe for discussions on integrated practices in terms of environmental design, on the basis of the synthetic approaches mentioned above.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.175-182
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• 2018

Knowledge of the optimum cultivation period for Chinese cabbage would help growers especially in spring in Korea. Growth and yield of Chinese cabbage in a temperature gradient chamber was evaluated for the growing periods of 64 days from three set of transplanting dates including March 6, March 20, and April 3 in 2017. Air temperature in the chamber was elevated step-by-step, by $2^{\circ}C$ above the ambient temperature. This increment was divided into three phases; i.e. low (ambient+$2^{\circ}C$, A), medium (ambient+$4^{\circ}C$, B), and high temperature (ambient+$6^{\circ}C$, C). The fresh weight of Chinese cabbage was greater under B and C conditions in the first period and A in the second period, which indicated that GDDs affected the fresh weight considerably. However, leaf growth (number, area, length, and width) did not differ by GDDs. Bolting appeared under A condition in the first period, which was caused by low temperature in the early growth stage. Soft rot was developed under C condition in the second period and all temperature conditions in the third period, which resulted from high temperature in the late stage. Fresh weight increased when GDDs ranged from 587 to 729. However, it decreased when GDDs > 729. The maximum expected yield (16.3 MT/10a) was attained for the growing period of 64 days from transplanting date during which GDDs reached 601. The GDDs for optimum cultivation ranged from 478-724 under which the yield was about 95% (15.5 MT/10a) of maximum fresh weight. Such an optimum condition for GDDs was validated at five main cultivation regions including Jindo, Haenam, Naju, Seosan, and Pyeongtaek in Korea. In these regions, GDDs ranged from 619-719. This suggested that the optimum GDDs for Chinese cabbage cultivation would range from 478-724, which would give the useful information to expect the cultivation periods for ensuring maximum yield.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.4
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• pp.227-235
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• 2005

This study aimed at suggesting management policy directions for the uninhabited islands of Korea which are national land resources with economic potential for tourism and development and strategic value for boundary delineation of territorial waters and exclusive economic zone as well as their unique ecological status. Review of existing management arrangements related to the uninhabited islands revealed six management issues to be addressed: insufficient data and their low reliability, lack of management policy directions, increase in ecosystem deterioration and perturbation by human activities, lack of policy measures for meeting utilization and development demands, weak management base with insufficient personnel and budget, and legal measures not taking Into account their unique ecological and socioeconomic characteristics. The management policy directions to improve the management of the uninhabited islands of Korea include management directions and strategies, and suggestions for legal improvement. Considering the unique ecological value of the uninhabited islands, management directions suggested are anti-degradation in which current and future demands for their utilization and development do not degrade the ecological potential of the uninhabited islands and integration in which land and sea areas are managed as an integrated management unit. Four strategies proposed to follow the management directions are enhancement of the knowledge base through a comprehensive survey, development and legislation of guidelines for the rational management of utilization and development demands, establishment of the comprehensive island debris collection and disposal system, and enhancement of management capacity. Legal improvement for the effective implementation of the management policy directions should include comprehensive uninhabited islands survey, legal utilization restraints and management guidelines based on classification of the islands, management boundary, and improvement of regulations on designated islands.

• Journal of Science Education
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• v.46 no.1
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• pp.93-108
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• 2022

The purpose of this study is to develop a STEAM program that can be used in the high school credit system to be fully implemented in 2025, and to examine its validity and effectiveness. The STEAM program analyzed the 2015 revised curriculum centering on science, technology, and engineering through the 2015 revised curriculum analysis, and then selected the five latest issues: hydrogen fuel, climate crisis, data science, appropriate technology, and barista. In accordance with this self-developed program development format (frame), it was developed for seven months through a process of group deliberation. The draft of the STEAM program for 29 sessions of five types, developed to indirectly experience the career path and occupation of high school students, was verified through consultation with 2 STEAM education experts. It was applied at five different high schools for a pilot implementation. As a result of the pilot application, it was confirmed that the students' STEAM attitude significantly improved in the post-test than the pre-test, and the students' high satisfaction with the program was confirmed. In addition, through an interview with the pilot application teacher, it was positively evaluated that 'the content and level of the program are suitable and through experience solving real-life problems, you can apply the content knowledge of related subjects and have an opportunity to experience careers.' Based on the results of the pilot application, the high school credit system STEAM program for students and teachers was finally completed in 29 lessons of five types. Through this study, the development and operation of the next-generation STEAM program that can be applied in the high school credit system should be actively developed, and a plan to improve teachers' professionalism so that the high school credit system can be established and operated properly for blended classes triggered by COVID-19. The necessity of design was suggested. This study is expected to be used as basic data for the development and operation of STEAM programs in the high school credit system, which will be fully implemented in 2025.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.