• Journal of the Korean Vacuum Society
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• v.11 no.3
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• pp.183-188
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• 2002

In the present study AI$(CH_3)_3)$films were deposited by the ALD technique using trimethylaluminum(TMA) and ozone to improve the quality of the AI$(CH_3)_3)$ films, since the $OH^-$ radicals existing in the AI$(CH_3)_3)$ films deposited using TMA and $H_2O$ degrade the physical and the dielectric properties of the AI$(CH_3)_3)$ film. The XPS analysis results indicate that the $OH^-$ radical concentration in the AI$(CH_3)_3)$film deposited using $O_3$is lower than that using $H_2O$. The etch rate of the AI$(CH_3)_3)$film deposited using $O_3$is also lower than that using $H_2O$, suggesting that the chemical inertness of the former is better than the latter. The MIS capacitor fabricated with the TiN conductor and the $Al_2$O$_3$dielectrics formed using $O_3$offers lower leakage current, better insulating property and smaller flat band voltage shift $({\Delta}V_{FB})$.

• The Mathematical Education
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• v.63 no.3
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• pp.549-571
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• 2024

As digital·AI-based teaching and learning is emphasized, discussions on the educational use of generative AI are becoming more active. This study analyzed the mathematical performance of ChatGPT 4, Claude 3 Opus, and Gemini Advanced on solving examples and problems from five first-year high school math textbooks. As a result of examining the overall correct answer rate and characteristics of each skill for a total of 1,317 questions, ChatGPT 4 had the highest overall correct answer rate of 0.85, followed by Claude 3 Opus at 0.67, and Gemini Advanced at 0.42. By skills, all three models showed high correct answer rates in 'Find functions' and 'Prove', while relatively low correct answer rates in 'Explain' and 'Draw graphs'. In particular, in 'Count', ChatGPT 4 and Claude 3 Opus had a correct answer rate of 1.00, while Gemini Advanced was low at 0.56. Additionally, all models had difficulty in explaining using Venn diagrams and creating images. Based on the research results, teachers should identify the strengths and limitations of each AI model and use them appropriately in class. This study is significant in that it suggested the possibility of use in actual classes by analyzing the mathematical performance of generative AI. It also provided important implications for redefining the role of teachers in mathematics education in the era of artificial intelligence. Further research is needed to develop a cooperative educational model between generative AI and teachers and to study individualized learning plans using AI.

• The Korea Journal of Herbology
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• v.33 no.3
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• pp.55-61
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• 2018

Objectives : Artemisia capillaris Thunberg (AC) and Artemisia iwayomogi Kitamura (AI) have been used without distinguishment since ancient times due to similar appearance. In this study, we compared the inhibitory effects of AC and AI on the expression of inflammatory cytokines induced by lipopolysaccharide (LPS) in murine macrophages. Methods : AC and AI were extracted by reflux with distilled water (DW) and 70% ethanol (EtOH). We investigated the inhibitory effects of AC and AI on the expression of nitric oxide (NO), inducible NO synthase (iNOS) and tumor necrosis $factor-{\alpha}$($TNF-{\alpha}$) induced by LPS in macrophages. Results : Firstly, yield of the samples was higher in order of Artemisia iwayomogi DW Extract (AID), Artemisia iwayomogi 70% EtOH Extract (AIE), Artemisia capillaris DW Extract (ACD) and Artemisia capillaris 70% EtOH Extract (ACE). All of the samples were not toxic in macrophages. The inhibitory effect of the samples on LPS-induced NO expression was stronger in the order of AIE, ACE, AID and ACD. The inhibitory effect of the samples on LPS-induced inducible iNOS expression was stronger in the order of AIE, ACE and AID. Effect of ACD was same with that of AID. In addition, inhibitory effect of the samples on LPS induced $TNF-{\alpha}$expression wes stronger in the order of AIE, ACE, AID and ACD. Conclusion: These results showed that AI would be more effective than AC and 70% EtOH would be more effective than DW as an extraction solvent in inflammatory diseases.

• Smart Media Journal
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• v.9 no.3
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• pp.59-70
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• 2020

This paper presents a fully automatic tool to recognize the liver region from CT images based on a deep learning model, namely Multiple Filter U-net, MFUnet. The advantages of both U-net and Multiple Filters were utilized to construct an autoencoder model, called MFUnet for segmenting the liver region from computed tomograph. The MFUnet architecture includes the autoencoding model which is used for regenerating the liver region, the backbone model for extracting features which is trained on ImageNet, and the predicting model used for liver segmentation. The LiTS dataset and Chaos dataset were used for the evaluation of our research. This result shows that the integration of Multiple Filter to U-net improves the performance of liver segmentation and it opens up many research directions in medical imaging processing field.

• ETRI Journal
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• v.44 no.5
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• pp.859-874
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• 2022

This paper presents a low-power and lightweight human body communication (HBC) receiver with an embedded dummy electrode for improved signal acquisition. The clock data recovery (CDR) circuit in the receiver operates with a low supply voltage and utilizes a clock phase inversion scheme. The receiver is equipped with a main electrode and dummy electrode that strengthen the capacitive-coupled signal at the receiver frontend. The receiver CDR circuit exploits a clock inversion scheme to allow 0.9-V operation while achieving a shorter lock time than at 3.3-V operation. In experiments, a receiver chip fabricated using 130-nm complementary metal-oxide-semiconductor technology was demonstrated to successfully receive the transmitted signal when the transmitter and receiver are placed separately on each hand of the user while consuming only 4.98 mW at a 0.9-V supply voltage.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.166-173
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• 2022

Recently, studies have been conducted on intelligent transportation systems (ITS) that provide safety and convenience to humans. Systems that compose the ITS adopt architectures that applied the cloud computing which consists of a high-performance general-purpose processor or graphics processing unit. However, an architecture that only used the cloud computing requires a high network bandwidth and consumes much power. Therefore, applying edge computing to ITS is essential for solving these problems. In this paper, we propose an edge artificial intelligence (AI) device based ITS. Edge AI which is applicable to various systems in ITS has been applied to license plate recognition. We implemented edge AI on a field-programmable gate array (FPGA). The accuracy of the edge AI for license plate recognition was 0.94. Finally, we synthesized the edge AI logic with Magnachip/Hynix 180nm CMOS technology and the power consumption measured using the Synopsys's design compiler tool was 482.583mW.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.33-42
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• 2024

With the recent rapid development of artificial intelligence (AI) technology, its use is gradually expanding to include creative areas and building new content using generative AI solutions, reaching beyond existing data analysis and reasoning applications. Content creation using generative AI faces challenges owing to technical limitations and other aspects such as copyright compliance. Nevertheless, generative AI may increase the productivity of experts and overcome barriers to creative work by allowing users to easily express their ideas as digital content. Thus, various types of applications will continue to emerge. As images and videos can be created using text input on a prompt, generative AI allows to create and edit digital assets quickly. We present trends in generative AI technology for images, videos, three-dimensional (3D) assets and scenes, digital humans, interactive content, and interfaces. In addition, the prospects for future technological development in this field are discussed.

• The Mathematical Education
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• v.63 no.3
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• pp.573-591
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• 2024

The purpose of this study is to explore research trends on AI-based mathematics teaching and learning. For this purpose, a systematic literature review was conducted on 57 literatures in terms of research subject, research method, research purpose, learning content, type of AI, role of AI, and role of teachers. The results indicate that student accounted for the largest proportion at 51% among the research subjects, and quantitative research was the highest at 49% among the research methods. The purpose of study was distributed as follows: effect analysis 44%, theoretical discussion 35%, case study 21%. 'Numbers and Operations' and 'Variables and Expressions' covered learning contents most, and Intelligent Tutoring System (ITS) was used the most among the types of AI. 'Student teaching' was the largest parts of role of AI at 40.4%, followed by 'teacher support' at 22.8%, 'student support' at 21%, and 'system support' at 15.8%. The role of teachers as 'AI recipients' was highlighted in earlier studies, and the role of teachers as 'constructive partner with AI' was highlighted in more recent studies. Also, role of teachers was explored in pedagogical, AI-technological, content aspects. Through this, follow-up research was suggested and the roles that teachers should have in AI-based mathematics teaching and learning were discussed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.3
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• pp.238-243
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• 2002

The dielectric properties and synthesis of $LaAIO_3$ ceramics from mixtures of $La_2O_3$ and $AI(OH)_3$ via ground(planetary ball mill) and unground(wet ball mill) were investigated. The single phase $LaAIO_3$ of ground powder was formed at $1000^{\circ}C$, while that of unground powder was formed at $1300^{\circ}C$. Density and grains of ground sample showed 98% of theory density and a uniform size of 0.75\mu\textrm{m}$, respectively, However those of unground sample showed 93% and non-uniform sizes of 4-5 $\mu\textrm{m}$. Dielectric constant and temperature coefficient of capacitance ($\tau$c) of both ground and unground samples were 21~22 and +70~74 ppm$/^{\circ}C$, respectively. Dielectric loss of ground sample(0.0004) was 10 times as low as that of unground sample(0.003) due to a uniform and small gram size.