• Title/Summary/Keyword: Use of Artificial Intelligence

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Design and Implementation of Smart Factory System based on Manufacturing Data for Cosmetic Industry (화장품 제조업을 위한 제조데이터 기반의 스마트팩토리 시스템의 설계 및 구현)

  • Oh, Sewon;Jeong, Jongpil;Park, Jungsoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.1
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    • pp.149-162
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    • 2021
  • This paper established a new smart factory based on manufacturing data for an introductory company focusing on the personalized cosmetics manufacturing industry. We build on an example of a system that collects, manages, and analyzes documents and data that were previously managed by CGMP-based analog for data-driven use. To this end, we have established a system that can collect all data in real time at the production site by introducing artificial intelligence smart factory platform LINK5 MOS and POP system, collecting PLC data, and introducing monitoring system and pin board. It also aims to create a new business cluster space based on this project.

LH-FAS v2: Head Pose Estimation-Based Lightweight Face Anti-Spoofing (LH-FAS v2: 머리 자세 추정 기반 경량 얼굴 위조 방지 기술)

  • Hyeon-Beom Heo;Hye-Ri Yang;Sung-Uk Jung;Kyung-Jae Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.309-316
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    • 2024
  • Facial recognition technology is widely used in various fields but faces challenges due to its vulnerability to fraudulent activities such as photo spoofing. Extensive research has been conducted to overcome this challenge. Most of them, however, require the use of specialized equipment like multi-modal cameras or operation in high-performance environments. In this paper, we introduce LH-FAS v2 (: Lightweight Head-pose-based Face Anti-Spoofing v2), a system designed to operate on a commercial webcam without any specialized equipment, to address the issue of facial recognition spoofing. LH-FAS v2 utilizes FSA-Net for head pose estimation and ArcFace for facial recognition, effectively assessing changes in head pose and verifying facial identity. We developed the VD4PS dataset, incorporating photo spoofing scenarios to evaluate the model's performance. The experimental results show the model's balanced accuracy and speed, indicating that head pose estimation-based facial anti-spoofing technology can be effectively used to counteract photo spoofing.

A Study on the Operational Planning Assist System for Ground Forces (지상군 작전계획 수립 보조 시스템 설계 연구)

  • Ikhyun Kim;Sunju Lee
    • Journal of The Korean Institute of Defense Technology
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    • v.5 no.1
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    • pp.7-18
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    • 2023
  • The military leader makes an operation plan to accomplish combat missions. The current doctrine for an operation planning requires the use of simple and clear procedures and methods that can be carried out with human effort under adverse conditions in the field. The work in the process of an operation planning can be said to be a series of decision-making, and the criteria for decision-making generally apply mission variables. However, detailed standards are not fixed as doctrine, but are creatively established and applied. However, for AI-based decision-making, it is necessary to formalize the criteria and the format used. This paper first aims to standardize various criteria and forms to present a method that can be used in a semi-automated assist system, and to seek a plan to artificialize it. To this end, mathematical models and decision-making methods established in the field of operations research were applied to improve efficiency.

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An Exploratory Study on Advertising Copywriting Using ChatGPT - With the focus on in-depth interviews with college students majoring in advertising - (ChatGPT를 활용한 광고카피라이팅에 대한 탐색적 연구 - 광고전공 대학생 심층면접을 중심으로-)

  • Chung, Hae Won;Cho, Woo Ri
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.5
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    • pp.751-757
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    • 2024
  • This study evaluates the effectiveness of advertising copywriting using the artificial intelligence language model, ChatGPT, and explores its potential applications and limitations within the advertising industry. We established five key research questions and conducted in-depth focus group interviews (FGI) with university students in Busan. The findings reveal that there was no significant preference difference between copies written by ChatGPT and human copywriters. However, ChatGPT's copies were particularly effective in age-targeted advertising but showed limitations in gender targeting and reflecting cultural contexts. Additionally, consumer acceptance of AI copywriting was generally positive, though concerns were raised about the creativity and naturalness of AI-generated copies. This research provides practical insights into how AI can be utilized in advertising content creation and stimulates discussion on the appropriate use of AI technology and ethical considerations within the industry. These results offer important implications for both advertising professionals and the academic community.

Implementation of Intelligent and Human-Friendly Home Service Robot (인간 친화적인 가정용 지능형 서비스 로봇 구현)

  • Choi, Woo-Kyung;Kim, Seong-Joo;Kim, Jong-Soo;Jeo, Jae-Yong;Jeon, Hong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.6
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    • pp.720-725
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    • 2004
  • Robot systems have applied to manufacturing or industrial field for reducing the need for human presence in dangerous and/or repetitive tasks. However, robot applications are transformed from industrial field to human life in recent tendency Nowadays, final goal of robot is to make a intelligent robot that can understand what human say and learn by itself and have internal emotion. For example Home service robots are able to provice functions such as security, housework, entertainment, education and secretary To provide various functions, home robots need to recognize human`s requirement and environment, and it is indispensable to use artificial intelligence technology for implementation of home robots. In this paper, implemented robot system takes data from several sensors and fuses the data to recognize environment information. Also, it can select a proper behavior for environment using soft computing method. Each behavior is composed with intuitive motion and sound in order to let human realize robot behavior well.

Development of a Concurrency Control Technique for Multiple Inheritance in Object-Oriented Databases (객체지향 데이터베이스의 다중계승을 위한 동시성 제어 기법 개발)

  • Jun, Woochun;Hong, Suk-Ki
    • Journal of Internet Computing and Services
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    • v.15 no.1
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    • pp.63-71
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    • 2014
  • Currently many non-traditional application areas such as artificial intelligence and web databases require advanced modeling power than the existing relational data model. In those application areas, object-oriented database (OODB) is better data model since an OODB can providemodeling power as grouping similar objects into class, and organizing all classes into a hierarchy where a subclass inherits all definitions from its superclasses. The purpose of this paper is to develop an OODB concurrency control scheme dealing with multiple inheritance. The proposed scheme, called Multiple Inheritance Implicit Locking (MIIL), is based on so-called implicit locking. In the proposed scheme, we eliminate redundant locks that are necessary in the existing implicit locking scheme. Intention locks are required as the existing implicit locking scheme. In this paper, it is shown that MIIL has less locking overhead than implicit locking does. We use only OODB inheritance hierarchies, single inheritance and multiple inheritance so that no additional overhead is necessary for reducing locking overhead.

A STUDY ON SATELLITE DIAGNOSTIC EXPERT SYSTEMS USING CASE-BASED APPROACH (사례기반 추론을 이용한 위성 고장진단 전문가 시스템 구축)

  • 박영택;김재훈;박현수
    • Journal of Astronomy and Space Sciences
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    • v.14 no.1
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    • pp.166-178
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    • 1997
  • Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human expert's knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in an easy way.

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Policy Suggestions on Personal Data Utilization by Analyzing Domestic and International De-identification Policy (국내외 비식별화 현황 분석을 통한 개인정보 활용 정책 제언)

  • Kang, Hye-young;Kwon, Hun-yeong
    • Convergence Security Journal
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    • v.19 no.1
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    • pp.41-48
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    • 2019
  • In the era of Internet of Things and Artificial Intelligence, it has become essential to digitize mass data, which leads 'data-driven economy'. Digitalized personal data can be easily collected, stored, duplicated and analyzed. As ICT technology is evolving the concept of traditional personal data has changed. The United States, the European Union, Japan, Korea and many countries have introduced new concept of personal data into law such as de-identification, anonymization, and pseudonymization to protect and utilize digitalized personal information. These concepts are distinguishable depending on countries. Therefore, this study will be done by researching and analyzing personal data related policies of several countries. Based on this study, this paper will suggest policy on di-identification to draw the right balance between personal data protection and use, which contributes to the development of digital economy.

A System for Determining the Growth Stage of Fruit Tree Using a Deep Learning-Based Object Detection Model (딥러닝 기반의 객체 탐지 모델을 활용한 과수 생육 단계 판별 시스템)

  • Bang, Ji-Hyeon;Park, Jun;Park, Sung-Wook;Kim, Jun-Yung;Jung, Se-Hoon;Sim, Chun-Bo
    • Smart Media Journal
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    • v.11 no.4
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    • pp.9-18
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    • 2022
  • Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

A Study on the Moral Responsibility of Lethal Autonomous Weapon Systems (LAWS): Focused on Robert Sparrow's "Responsibility Gap" Theory (치명적 자율무기체계의 도덕적 책임 문제 연구 : 로버트 스패로우의 '책임간극' 이론에 대한 고찰)

  • Hyunyoung Moon;Sangsu Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.375-381
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    • 2023
  • In an increasingly hyperconnected battlefield, the reliance on battlefield networks and AI-based autonomous weapons systems creates uncertainty and raises ethical concerns. This article explores the responsibility gap in operating autonomous weapons systems, using Robert Sparrow's theory. By analyzing Sparrow's arguments, we propose overcoming the responsibility gap in lethal autonomous weapon systems (LAWS). Our objective is to establish a framework of responsibility that aligns with the evolving battlefield, promoting the development and use of responsible weapon systems.