• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

• Educational Technology International
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• v.6 no.2
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• pp.23-41
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• 2005

One of the main factors that determine the quality of instruction is the teaching ability of the instructor administering the class. To evaluate teaching ability, methods such as peer review, student feedback, and teaching portfolio can be used. Among these, because feedback from the students is directly associated with how well the students feel they have learned, it is essential to improving instruction and teaching ability. The principal aim of instruction evaluation lies in the evaluation of instructor's qualification and the improvement of instruction quality by enhancing professionalism. However, the mandatory instruction evaluations currently being carried out at the term's end in universities today have limitations in improving instruction in terms of its evaluation items and times. To improve the quality of instruction and raise teaching abilities, instruction evaluations should not stop at simply being carried out but also be utilized as useful data for students and teachers. In other words, they need to be used to develop teaching and improve instruction for teachers, and consequently, should also exert a positive influence on students' scholastic achievements and learning ability. The most important thing in evaluation is the acquisition of accurate information and how to utilize it to improve instruction. The online instruction diagnosis item pool is a more realistic feedback device developed to improve instruction quality. The instruction diagnosis item pool is a cafeteria-like collection of hundreds of feedback questions provided to enable instructors to diagnose their instruction through self-diagnosis or students' feedback, and the instructors can directly select the questions that are appropriate to the special characteristics of their instruction voluntarily make use of them whenever they are needed. The current study, in order to find out if the online instruction diagnosis item pool is truly useful in reforming and improving instruction, conducted pre and post tests using 256 undergraduate students from Y university as subjects, and studied the effects of student feedback on instructions. Results showed that the implementation of instruction diagnosis improved students' responsibility regarding their classes, and students had positive opinions regarding the usefulness of online instruction diagnosis item pool in instruction evaluation. Also, after instruction diagnosis, analyzing the results through consultations with education development specialists, and then establishing and carrying out instruction reforms were shown to be more effective. In order to utilize the instruction diagnostic system more effectively, from planning the execution of instruction diagnosis to analyzing the results, consulting, and deciding how those results could be utilized to instruction, a systematic strategy is needed. In addition, professors and students need to develop a more active sense of ownership in order to elevate the level of their instruction.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.569-590
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• 2023

The purpose of this case study is to compare and analyze the covariational reasoning levels of two middle school students revealed in the process of solving and generalizing algebra word problems. A class was conducted with two middle school students who had not learned quadratic equations in school mathematics. During the retrospective analysis after the class was over, a noticeable difference between the two students was revealed in solving algebra word problems, including situations where speed changes. Accordingly, this study compared and analyzed the level of covariational reasoning revealed in the process of solving or generalizing algebra word problems including situations where speed is constant or changing, based on the theoretical framework proposed by Thompson & Carlson(2017). As a result, this study confirmed that students' covariational reasoning levels may be different even if the problem-solving methods and results of algebra word problems are similar, and the similarity of problem-solving revealed in the process of solving and generalizing algebra word problems was analyzed from a covariation perspective. This study suggests that in the teaching and learning algebra word problems, rather than focusing on finding solutions by quickly converting problem situations into equations, activities of finding changing quantities and representing the relationships between them in various ways.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.47-65
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• 2023

As stakeholder demands and sustainable finance grow, ESG management and ESG evaluation are becoming important. SMEs should also prepare for the trends of ESG rating practices that affects supply chain management and financial transactions. However, SMEs have no choice but to focus on survival first, so there are restrictions on putting into ESG management. In addition, there is a lack of research on the legitimacy of ESG management by SMEs, and volatility in ESG evaluation systems and rating grades is also increasing. Accordingly, it is necessary to review ESG evaluation trends and practical guidelines along with the review of previous studies. As a result of the exploratory study, SMEs need to implement ESG management and make efforts to specialize in ESG related new businesses under conditions in which their survival base is guaranteed in terms of implementation strategies. In addition, it is necessary to focus on the strategic use of various evaluation results along with accumulating information favorable for ESG evaluation through organizational learning and software management. The implications of this study are that various studies such as the classification criteria for SMEs and the relationship between ESG evaluation grades and long-term survival rates are needed in ESG evaluation of SMEs. At the government policy level, it is time to consider the ESG evaluation system exclusively for SMEs so that ESG management can be implemented and ESG evaluation at different levels by industry and size.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.8-16
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• 2024

This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

• Journal of The Korean Association For Science Education
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• v.29 no.6
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• pp.712-729
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• 2009

This study aims to research high school students' misconception of botanic photosynthesis and respiration, and as the measure of rectifying the misconception, to develop the teaching program based on Driver's conceptual change model, applying it to classes and observing the effect. Selected as the research subject was sixty-six students in 1st year of a highschool located in Busan who had chosen Biology Learning as discretionary subject, with their conceptual level on botanic photosynthesis and respiration researched through tests in drawing and descriptive writing. As a consequence of applying drawing as a way of classifying the levels of students' misconception on photosynthesis and respiration, many students' drawings included their misconception caused by textbooks or scientists, but after application of Driver's conceptual change model, they drew scientific drawings including the fundamental factors of botanic photosynthesis and respiration such as light, carbon dioxide, water, glucose, oxygen, leaf, chloroplast, mitochondria, stoma, and energy. Likewise, as a result of the descriptive writing test implemented for researching the students' conception on the various aspects of botanic photosynthesis and respiration, many students in the pretest showed misconception on the point of time and location at which botanic photosynthesis and respiration occur, botanic nutrient, the role of a leaf in photosynthesis, and the relation between botanic photosynthesis and respiration, but after teaching based on Driver's conceptual change model, their misconceptions on photosynthesis and respiration were rectified to a high degree.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.19-32
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• 2024

This study examined the feasibility of image-based surveys by detecting objects in facilities and agricultural land using the YOLO algorithm based on drone images and comparing them with the land category by law. As a result of detecting objects through the YOLO algorithm, buildings showed a performance of detecting objects corresponding to 96.3% of the buildings provided in the existing digital map. In addition, the YOLO algorithm developed in this study detected 136 additional buildings that were not located in the digital map. Plastic greenhouses detected a total of 297 objects, but the detection rate was low for some plastic greenhouses for fruit trees. Also, agricultural land had the lowest detection rate. This result is because agricultural land has a larger area and irregular shape than buildings, so the accuracy is lower than buildings due to the inconsistency of training data. Therefore, segmentation detection, rather than box-shaped detection, is likely to be more effective for agricultural fields. Comparing the detected objects with the land category by law, it was analyzed that some buildings exist in agricultural and forest areas where it is difficult to locate buildings. It seems that it is necessary to link with administrative information to understand that these buildings are used illegally. Therefore, at the current level, it is possible to objectively determine the existence of buildings in fields where it is difficult to locate buildings.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.415-436
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• 2023

In this study, we aimed to examine the level of implementation of the second comprehensive plan for promoting academic libraries (2019-2023) by analyzing key statistics of academic libraries and gathering perceptions from library staff. We analyzed the changes in major statistical indicators of libraries over the past five years. Additionally, we surveyed library staff to understand their overall perceptions of the plan and their attitudes towards the 17 sub-tasks outlined in it. The analysis of 369 survey responses revealed several key findings. Firstly, most respondents comprehended the plan well and frequently utilized it for developing their libraries' development and implementation plans. Secondly, the IPA results indicated that regardless of the type of university, there should be a continuous focus on facility improvement, teaching-learning support, and expanding access to academic resources. Efforts to develop library policies and strengthen human and financial resources were identified as crucial. Thirdly, four-year universities particularly emphasized the importance of expanding access to international academic resources compared to junior colleges. Conversely, junior colleges perceived foundational skill-building programs and inclusive services as more significant than four-year universities. The application of the IPA diagonal model revealed that the performance levels of all sub-tasks were lower than their perceived importance levels, suggesting the need for strategies to enhance effectiveness in future comprehensive plan formulation.