• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.365-371
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• 2023

In this study, we proposed a plan to educate computer students at industrial specialized high schools about artificial intelligence programming using Raspberry Pi. To create an educational program, we received advice from experts working in schools and industries, analyzed existing research and requirements, designed weekly learning plans, developed teaching materials, and conducted classes. Due to the small number of research subjects, interviews were conducted with students, and the results of the teacher's diary were also presented to derive qualitative research results. The main interview results show that although it is true that interest in the field of artificial intelligence has increased through the class, many responded that the learning content is still difficult. The teacher's diary mainly included information about the latest trends in the industry that informatics and computer teachers should not miss out on. We hope that this study will provide an opportunity to meet the needs of the industry by increasing the proportion of artificial intelligence programming in industrial specialized high schools.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.91-97
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• 2007

Game program had been classed by 3D or on-line game etc, and engine and game programming simply, But, game programmer's kind more classified new, Artifical Intelligence game programmer's role is important. This paper makes game character study and moved by intelligence using reinforcement learning algorithm. Fought with character enemy using developed game, Confirmed whether embodied game character is facile by intelligence, As result of an experiment, we know, studied character defends excellently than randomly moved character.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.189-199
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• 2023

This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.289-297
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• 2024

This study was attempted to confirm the effects of nursing students' artificial intelligence literacy and grit on their creative convergence capabilities. This study targeted 133 students attending two nursing colleges located in G Province. Data analysis was analyzed using SPSS 21 program with descriptive statistics, t-test, ANOVA, Pearson correlation coefficient, and multiple regression analysis. The average creative convergence competency of the subjects was 3.53 points, and there was a significant difference in creative convergence competency according to general characteristics in grades (F=8.65, p<.005) and major satisfaction (F=3.95, p=.021). there was. The subject's creative convergence capability had a statistically significant positive correlation with artificial intelligence literacy (r=.599, p<.001) and grit (r=473, p<.001). The influencing factors on the subjects' creative convergence capabilities were artificial intelligence literacy (β=0.350, p<.001) and grit (β=0.192, p<.001), and the explanatory power of these variables was 45.6%. Based on the above research results, it is necessary to develop and apply curriculum and extracurricular programs that can improve artificial intelligence literacy and grit in order to improve the creative convergence capabilities of nursing students.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.10-17
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• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.367-375
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• 2021

This study developed and applied an artificial intelligence education program as an educational method for increasing computational thinking of elementary school students and verified its effectiveness. The educational program was designed based on the results of a demand analysis conducted using Google survey of 100 elementary school teachers in advance according to the ADDIE(Analysis-Design-Development-Implementation-Evaluation) model. Among Machine Learning for Kids, we use scratch for block-based programming and develop and apply textbooks to improve computational thinking in the programming process of learning the principles of artificial intelligence and solving problems directly by utilizing numerical data. The degree of change in computational thinking was analyzed through pre- and post-test results using beaver challenge, and the analysis showed that this study had a positive impact on improving computational thinking of elementary school students.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.715-723
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• 2024

The purpose of this study was to identify research trends related to future education through keyword network analysis. To this end, 308 academic papers and master's and doctoral dissertations published from 2000 to 2023 in Korea, and 146 keywords were selected for analysis, divided into 5 periods, and used and analyzed with the Microsoft Excel 365 program and NetMiner 4 program. The results of the study are as follows. First, the publication of future education research has steadily increased since 2000, but has increased significantly since the second half of the 2010s, and the number has exploded in 2021. Second, the number of new keywords that emerged in future education research has increased in recent times, but the frequency of 'future society' keywords appearing in all periods has been high. Third, in future education research results, the number of keywords that simultaneously appear among keywords has increased as time passes, and the contents of keywords that simultaneously have changed in various ways. This study is meaningful in that it suggested the direction of future education by analyzing the past and present of future education with artificial intelligence more than 20 years later.

• Journal of the Korean Society of Radiology
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• v.18 no.5
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• pp.419-427
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• 2024

The objective of this study is to analyze and evaluate the diagnostic performance and utility of elastography and artificial intelligence program in distinguishing between benign and malignant thyroid nodule. In a hospital outpatient clinic, we performed thyroid ultrasound from January 2023 to June 2024, and retrospectively analyzed 126 patients who performed elastography, S-detect, and fine needle aspiration cytology(FNAC) because nodules were found. The analysis of differences based on cytology results showed statistically significant differences in age, nodule size, echogenicity, nodule orientation, margins, shape, presence of calcification, posterior shadowing, K-TIRADS ultrasound interpretation, S-detect results and elasticity contrast index. The ROC curve analysis determined a cut off value for the elasticity contrast index at 2.32, with diagnostic concordance rates of 0.66 for expert interpretation, 0.49 for S-detect, and 0.67 for the elasticity contrast index, indicating superior diagnostic performance with elastography. Thus, elastography may ge used as an adjunct tool to minimize unnecessary repeat examinations and the frequency of tissue biopsies in the diagnosis of thyroid nodules.

• Imaging Science in Dentistry
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• v.53 no.3
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• pp.199-207
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• 2023

Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs(PRs), as well as to assess the appropriateness of its treatment recommendations. Materials and Methods: PRs from 100 patients(representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Conclusion: Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.27-33
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• 2001

The aim of the present work is to propose a model for Computer Aided programming of numerical Control lathe. This model is based on the concept by features. It has been developed in an Artificial Intelligence environment, that offers a rapidity as well as a precision for NC code elaboration. In this study a pre-processor has been elaborated to study the geometry of turning workpiece. This pre-processor is a hybrid system which combine a module of design by features and a module of features recognition for a piece provided from an other CAD software. Then, we have conceived a processor that is the heart of the CAD/CAM software. The main functions are to study the fixture of the workpiece, to choose automatically manufacturing cycles, to choose automatically cutting tools (the most relevant), to simulate tool path of manufacturing and calculate cutting conditions, end to elaborate a typical manufacturing process. Finally, the system generates the NC program from information delivered by the processor.