• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.247-260
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• 2023

In this study, when applying the 'geological structure' content element of high school earth science I developed according to the 2015 curriculum to the STEAM program using a web-based expert system using 3D data of Google Earth and drones, the creative problem-solving ability of high school students, attitudes toward STEAM, and the results of this study are as follows. First, after applying the STEAM program, high school students' creative problem-solving ability showed meaningful results at the p<.001 level. Second, STEAM attitudes showed a significant value at the p<.001 level, confirming that they had a positive impact on high school students' attitudes towards STEAM. It was judged that web-based class activities using Google Earth and drones were useful for integrated thinking such as learners' sense of efficacy and value recognition for usefulness of knowledge. High school students' satisfaction with the STEAM program was 3.251, showing a slightly high average. It was confirmed that web-based class activities such as drones and Google Earth had a positive impact on learners' class satisfaction. However, it was interpreted that the lack of time for class activities limited the ability of the learners to increase their interest in class. The proposal of this research is as follows. First of all, in consideration of the production of presentation materials and practical training in the STEAM program, activities such as block time and advance instruction for class understanding before class are necessary. Secondly, in order to revitalize STEAM education in the high school curriculum, we judge that research on the development of various integrated education programs that can be applied to the high school grade system is necessary.

• 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 Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.300-320
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• 2007

정보기술의 발달과 함께 소프트웨어 제품은 모든 산업에 필수요소가 되었고, 품질과 평가에 대한 관심도 점차 증가되고 있다. 하지만 일부 산업에서는 소프트웨어 품질 평가에 대한 사용자들의 만병 통치적 기대, 품질 표준의 부족, 측정을 위한 양질의 데이터 부족, 소프트웨어 분석과 디자인에 대한 공학적 한계로 소프트웨어 품질 평가에 대해 많은 문제점이 지적되고 있다. 국내에서도 의료산업 관련 정보시스템의 오류 및 사용자들의 운영 미숙은 매년 많은 금액의 사회적 비용을 증가시켰고, 병원정보시스템의 품질에 대한 관심을 초래하였다. 특히, 산업적 특성이 강한 병원정보시스템은 성공적 구축을 위해 사용자 중심의 소프트웨어 디자인과 다양한 전문가들의 지식 통합이 필요하며, 정보시스템 품질 측정으로 연구자들과 개발자들의 시스템 설계 혼란을 감소시키는 방법론이 필요하다는 연구들이 등장하고 있다. 대부분의 병원정보시스템이 단편적인 업무처리 위주로 개발 운영되고 있고, 장기적 경영전략이나 임상연구를 위한 분석적 정보처리 기능들은 결여되어 있다. 또한 소프트웨어 재설계나 추가적 개발 에 활용될 수 있는 객관적 품질 기준이 부족하고, 사용자들의 요구사항에 대해 소프트웨어 설계에 있어서 효율적으로 반영되지 못하고 있다. 이에 본 연구는 최근 발표된 병원정보시스템 품질 평가에 대한 연구 경향을 종합하고, 품질 평가에 대 해 효율적으로 활용되고 있는 사용성(Usability)을 기준으로 병원산업의 특수성을 포함한 품질 평가 방법과 품질척도를 제안하고자 한다. 국제표준기구(ISO:International Standards Organization)에서는 품질 특성을 기능성, 신뢰성, 사용성, 효율성, 유지 보수성과 이식성의 특성을 제시하고 있다. 특히 Folmer & Bosch(2004)가 정리한 ISO9126에서는 품질의 특성을 배움의 용이성, 운영의 용이성, 이해성과 매력성으로 분류하였고, ISO9241-11는 효과성, 효율성과 만족성으로 분류하였다. 또한 Shackel(1991)은 배움의 용이성(배움과 시간, 기억력), 효과성(오류, 직무시간), 유연성과 마음가짐으로 분류하고 있다(Shackel, 1991). Nielsen(1997)은 배움의 용이성, 기억의 용이성, 오류, 효율성, 만족성으로 분류하고 있고(Nielsen, 1997), Shneiderman(1998)는 효과성(직무시간, 배움의 시간), 효율성(기억의 지속시간, 오류), 만족도를 품질의 특성으로 분류하였다. 이와 같은 소프트웨어의 품질은 소프트웨어 계획, 개발, 성장과 쇠퇴의 모든 과정에 적용되며, 환경적 변화에 따라 사용자들의 정보욕구를 적절하게 반영하여 만족도를 높이 는 것이라고 요약할 수 있다. 그러나 현재까지 소프트웨어 품질 평가에 대한 연구들 은 보편적인 평가 항목들을 대상으로 측정하여 일반적인 품질기준을 제시하고 있고, 유사한 측정 내용들이 중복되어 있다. 이러한 경향은 산업별 특수성이 강한 소프트웨어에 대해서는 정확한 품질측정이 어려웠고, 품질측정에 대한 신뢰성을 떨어뜨리는 계기가 되었다. 이러한 한계를 극복하고자 나타난 방법론이 최종사용자들의 요구사항을 얼마나 적절하게 시스템에 반영했는지에 대한 사용성(Usability) 측정이다. 사용성에 대한 정의는 사용자들이 실질적으로 일하는 장소에서 직접 사용자들의 시스템 운용실태를 파악하여 문제점을 개선하는 것으로 요약할 수 있다. ISO9124-11에서는 사용성을 "어떤 제품이 구체적인 사용자들에 의해 구체적인 목적을 달성하기 위한 구체적인 사용의 맥락에서 효율성, 효과성을 만족함으로 사용될 수 있는 정도"로 정의하고 있다. 지난 10년간 병원정보시스템 평가에 대한 문헌들을 고찰한 결과 품질 측정의 효과는 정보화에 대한 동기유발과 의료품질을 높이는 게기가 되었으며, 질병에 대한 예방효과도 높은 것으로 조사되었다. 그러나 평가에 대한 인식의 문제, 평가 방법의 신뢰성 부족, 평가 지침과 부분적 평가에 따른 인증의 어려움 평가 결과에 대한 확산과 단편적 연구의 한계 등으로 연구결과에 대한 신뢰도와 활용도는 낮은 것으로 조사되었고, HIS에 대한 연구 빈도와 범위 가 매우 미약하였다. 특히, 품질속성은 같은 용어이지만 연구자에 따라 전혀 다른 측정 내용을 제시하고 있어 효율적인 품질 지표를 제시하는데 많은 혼란을 초래하고 있다. 이러한 품질 평가의 경향은 시스템 설계 및 개발자들에게 필요한 사용자들의 구체적이고 독특한 욕구나 병원정보시스템 환경의 특수성 파악에 한계를 보였으며, 평가 범위도 부분적으로 이루어져 전사적 시스템 설계 및 개발에 중요한 자료를 제공하지 못하고 있다. 이러한 문제점과 한계를 극복하고자 ISO와 같은 품질 표준 속성과 컨텍스트(Context)를 중심으로 사용자에 의한 평가 척도의 설정은 구체적이고 실용적이며 신뢰성 있는 평가 방법이 될 것이다.

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

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

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.

• Cartoon and Animation Studies
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• s.41
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• pp.455-486
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• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.