• 정보와 통신
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• 제34권2호
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• pp.12-19
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• 2017

The LED technology advancement introduce cuttingedge technology on Internet of Things (IoT) to connect the physical world to the digital realm, using digital smart lighting infrastructure called Internet of light (IoL). This paper proposes an Integrated IoT agent on networked smart LED lighting controller called IoL Filed Gateway using lighting infrastructure in which a lighting system that can connect to a network and can be monitored and controlled from a centralized system or via the cloud. The IoL Field Gateway defines new world of smart connected intelligence, lighting can become an integral and responsive part of everyday human life environments. The proposed connected lighting gateway uses the concept of multi-hop ad hoc network using visible light communication (VLC) with RF wireless technologies and Wired PLC (Power Line Communication). This connectivity and intelligence integrated into LED-based luminaires form the backbone of smart buildings and cities and make the Internet of Things (IoT) vision feasible and enables the lighting administrator can control numerous lightings easily and visitors can get visual information from the lightings with their smart devices. The proposed IoL gateway design is emulated on Arduino based HW platform with VLC, RF, and PLC connectivity and evaluated with four sensor interface.

• 한국의류산업학회지
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• 제23권6호
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• pp.691-708
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• 2021

The emerging Fourth Industrial Revolution has triggered fundamental shifts in the fashion industry. Advanced digital technologies are not only reshaping how the fashion supply chains function, but also requisitioning new skill sets for jobs in this industry. A mismatch in required skills between current and future jobs is a critical issue that needs to be addressed in the fashion industry. Similarly, it is imperative that fashion programs in higher education keep pace with the rapid changes disrupting the fashion sector. Nevertheless, the increasing speed and the magnitude of digital transformation make it challenging to keep fashion curricula up to date. This paper presents the case of a Digital Merchandising course. Using the principles of designing flexible curricula and backward design, this Digital Merchandising course was developed to be flexible and responsive to the changing business environment. Building digital intelligence was the central learning goal for students to accomplish. The paper discusses the conceptual development processes for the course and provides, visual examples of major learning assignments, and a variety of digital tools. Fashion educators are encouraged to consider backward design and flexible curricula design guides as complementary tools to the widely used Bloom's taxonomy.

• 감성과학
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• 제25권3호
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• pp.107-116
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• 2022

Purpose: Researchers have shown that aesthetic judgments of artworks depend on contexts, such as the authenticity of an artwork (Newman & Bloom, 2011) and an artwork's location of display (Kirk et al., 2009; Silveira et al., 2015). The present study aims to examine whether contextual information related to the creator, such as whether an artwork was created by a human or artificial intelligence (AI), influences viewers' preference judgments of an artwork. Methods: Images of Impressionist landscape paintings were selected as human-made artworks. AI-made artwork stimuli were created using Google's Deep Dream Generator by mimicking the Impressionist style via deep learning algorithms. Participants performed a preference rating task on each of the 108 artwork stimuli accompanied by one of the two creator labels. After this task, an art experience questionnaire (AEQ) was given to participants to examine whether individual differences in art experience influence their preference judgments. Results: Setting AEQ scores as a covariate in a two-way ANCOVA analysis, the stimuli with the human-made context were preferred over the stimuli with the AI-made context. Regarding the types of stimuli, the viewers preferred AI-made stimuli to human-made stimuli. There was no interaction effect between the two factors. Conclusion: These results suggest that preferences for visual artworks are influenced by the contextual information of the creator when the individual differences in art experience are controlled.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• 전자통신동향분석
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• 제38권6호
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• pp.1-11
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• 2023

Large language models seem promising for handling reasoning problems, but their underlying solving mechanisms remain unclear. Large language models will establish a new paradigm in artificial intelligence and the society as a whole. However, a major challenge of large language models is the massive resources required for training and operation. To address this issue, researchers are actively exploring compact large language models that retain the capabilities of large language models while notably reducing the model size. These research efforts are mainly focused on improving pretraining, instruction tuning, and alignment. On the other hand, chain-of-thought prompting is a technique aimed at enhancing the reasoning ability of large language models. It provides an answer through a series of intermediate reasoning steps when given a problem. By guiding the model through a multistep problem-solving process, chain-of-thought prompting may improve the model reasoning skills. Mathematical reasoning, which is a fundamental aspect of human intelligence, has played a crucial role in advancing large language models toward human-level performance. As a result, mathematical reasoning is being widely explored in the context of large language models. This type of research extends to various domains such as geometry problem solving, tabular mathematical reasoning, visual question answering, and other areas.

• 식물병연구
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• 제30권1호
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• pp.99-102
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• 2024

Integrated pest management is essential for controlling plant diseases that reduce crop yields. Rapid diagnosis is crucial for effective management in the event of an outbreak to identify the cause and minimize damage. Diagnosis methods range from indirect visual observation, which can be subjective and inaccurate, to machine learning and deep learning predictions that may suffer from biased data. Direct molecular-based methods, while accurate, are complex and time-consuming. However, the development of large multimodal models, like GPT-4, combines image recognition with natural language processing for more accurate diagnostic information. This study introduces GPT-4-based system for diagnosing plant diseases utilizing a detailed knowledge base with 1,420 host plants, 2,462 pathogens, and 37,467 pesticide instances from the official plant disease and pesticide registries of Korea. The AI plant doctor offers interactive advice on diagnosis, control methods, and pesticide use for diseases in Korea and is accessible at https://pdoc.scnu.ac.kr/.

• 대한한의학회지
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• 제25권4호
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• pp.129-138
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• 2004

Objective : Treatments for patients with mental retardation and pervasive developmental disorders are not curative, and are designed to help those with disabilities adjust to their environments and daily demands. As clinicians, the present authors tried to find agents with potentially curative properties. Among the numerous herbal formulations available, we chose and assessed Gami-jiwhang-tang (GJT) in the hope that it would improve cognitive development of children. Methods : Subjects were typically-developing healthy, 7- to 8-year-old boys and girls living in Seoul, Korea. The experimental group took GJT for six weeks and was followed up six weeks after discontinuation of GJT. The control group was assessed at the same intervals but did not receive placebos. To measure the effects of GJT, neuropsychological tests and intelligence test were taken before commencing GJT and twelve weeks later. Resulets and Conclusion : For all of the ANOVAs, the treatment by time interaction terms was not significant. However, the experimental group showed the tendency to be progressed in most subscales compared with the control group, especially on performance intelligence, visual organization, and verbal fluency. Conclusion : Although GJT failed to reveal significant improvement in cognition, we remain hopeful about the compound and believe that it should be evaluated by a double-blind, placebo-controlled trial in the future.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제18권2호
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• pp.145-153
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• 2007

Objectives: This study was focused on the influence of chronic aircraft noise exposure on children's continuous performance, intelligence and reading skill. Methods: We enrolled 586 children in 4-6th grade of 7 primary schools near air base in Korea. Continuous performance was measured using the computerized ADS program. We analyzed 477-512 children on the visual continuous performance test, auditory continuous performance test, intelligence test, and reading and the vocabulary test. Intelligence was measured using vocabulary, digit span, block design, and digit symbol tests of K-WISC-III. Results: The commission error and variability deviation of auditory continuous performance test and reading test were significantly higher among children in schools with the helicopter noise and the fighting plane noise compared to children in the low noised schools. Conclusion: There was a possibility that chronic aircraft noise exposure was associated with impairment of the school performance. The result of our study also shows chronic aircraft noise was associated with reading ability.

• 기술혁신학회지
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• 제22권3호
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• pp.340-361
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• 2019

본 연구는 특허 데이터를 활용하여 인공지능 기술의 구조를 파악하고 주요 글로벌 IT 기업들의 인공지능 기술역량을 분석한다. 2007년부터 2017년까지 미국 특허청에 등록된 2,589개의 인공지능 특허를 바탕으로 LDA 토픽모델링을 수행하여 인공지능 분야의 20개의 기술 토픽을 도출하였다. 인공지능 기술 분야 중 언어이해, 음성처리보다는 시각이해, 데이터분석, 동작제어, 그리고 기계학습 분야의 연구개발이 최근 활발한 것으로 나타났다. 또한 기업별 인공지능 기술 역량을 분석하여 인공지능 기술 분야별로 우수 역량을 보유한 기업을 도출하고, 기업별로 강점을 가지고 있는 세부 기술 분야를 도출하였다. 본 연구 결과는 인공지능 기업들의 기술기획 및 전략 수립에 유용하게 활용될 수 있을 것으로 기대된다.

• 트랜스-
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• 제13권
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• pp.117-140
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• 2022

최근 인공지능 기술은 산업전반에 걸쳐서 활용되고 있다. 현재 예술 창작도구는 NFT 산업에서 사용되고 있으며, 이를 활용한 작품이 전시, 판매되기도 하였다. 미술 분야의 창작도구는 Gerated Photos, Google Deep Dream, Skech-RNN, Auto draw가 있으며, 음악분야의 인공지능 창작도구는 Beat Blender, Google Doodle Bach, AIVA, Duet, Neural Synth 등이 있다. 인공지능 예술 창작도구의 특징은 다음과 같다. 첫째, 예술분야 인공지능 창작도구는 기존의 작품 데이터를 바탕으로 새로운 작품을 창작하는 데에 활용되고 있다. 둘째, 창작 결과물을 빠르고 신속하게 도출하여 창작자에게 아이디어를 제공하거나, 창작 재료를 다양하게 구현해 볼 수 있다. 향후 인공지능 창작물은 인공지능 기술이 미술, 영상, 문학, 음악 등 콘텐츠 기획 및 제작에 많은 영향을 끼칠 것이다.