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Operation Technique of Spatial Data Change Recognition Data per File (파일 단위 공간데이터 변경 인식 데이터 운영 기법)

  • LEE, Bong-Jun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.184-193
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    • 2021
  • The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

Implementation of CoMirror System with Video Call and Messaging Function between Smart Mirrors (스마트 미러간 화상 통화와 메시징 기능을 가진 CoMirror 시스템 구현)

  • Hwang, Kitae;Kim, Kyung-Mi;Kim, Yu-Jin;Park, Chae-Won;Yoo, Song-Yeon;Jung, Inhwan;Lee, Jae-Moon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.121-127
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    • 2022
  • Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the useer along with the mirror function. This paper went beyond the form of dealing with smart mirrors only stand alone device the provide information to users, and constructed a network in which smart mirrors are connected, and proposed and implemented a CoMirror system that allows users to talk and share information with other smart mirror users. The CoMirror system has a structure in which several CoMirror clients are connected on one CoMirror server. The CoMirror client consists of Raspberry Pi, a mirror film, a touch pad, a display device, an web camera, etc. The server has functions such as face learning and recognition, user management, a relay role for exchanging messages between clients, and setting up for video call. Users can communicate with other CoMirror users via the server, such as text, image, and audio messages, as well as 1:1 video call.

A Research on the Scenography of the Musical 『All Shook Up』 - Focusing on the Design Construction Process and Performance Application Cases - (뮤지컬 『All Shook Up』의 연출적 시노그래피 연구 - 디자인 구축 과정과 공연 적용 사례를 중심으로 -)

  • Park, Geun-Hyung;Cho, Joon-Hui
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.8
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    • pp.175-187
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    • 2020
  • The purpose of this study is to discuss the elements and meanings of the performative scenography which has been revealed through the new directorial interpretation and deconstruction process of the musical 『All Shook Up』. The performative scenography characteristics after postmodernism aim to create individual active perceptions and various social meanings through audience's voluntary and particular emergence. To this end, the theoretical foundation of scenography was examined by periods in advance. Based on this, I attempted to establish performative scenography for synthesized scenic and media design through the reconstruction process for the 『All Shook Up Travelers』. As a result, I set up visual narrative based world of 『All Shook Up Travelers』 which was produced by text-based intense images for a direct medium in order to expand actors' inner narrative and established unique performative scenography of its own: 1. enhancing the adapted one's narratives for the actors' and audience's co-existence and detachment, 2. delivering its own independent meanings which have double meanings, 3. encouraging audience's critical and active perception experiences through collage and montage of media.

A Case Study on the Application of AI-OCR for Data Transformation of Paper Records (종이기록 데이터화를 위한 AI-OCR 적용 사례연구)

  • Ahn, Sejin;Hwang, Hyunho;Yim, Jin Hee
    • Journal of the Korean Society for information Management
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    • v.39 no.3
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    • pp.165-193
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    • 2022
  • It can be said that digital technology is at the center of the change in the modern work environment. In particular, in general public institutions that prove their work with records produced by business management systems and document production systems, the record management system is also the work environment itself. Gimpo City applied for the 2021 public cloud leading project of the National Information Society Agency (NIA) to proactively respond to the 4th industrial revolution technology era and implemented a public cloud-based AI-OCR technology enhancement project with 330 million won in support of 330 million won. Through this, it was converted into data beyond the limitations of non-electronic records limited to search and image viewing that depend on standardized index values. In addition, a 98% recognition rate was realized by applying a new technology called AI-OCR. Since digital technology has been used to improve work efficiency, productivity, development cost, and record management service levels of internal and external users, we would like to share the direction of enhancing expertise in the record management and implementation of work environment innovation.

Sign Language Dataset Built from S. Korean Government Briefing on COVID-19 (대한민국 정부의 코로나 19 브리핑을 기반으로 구축된 수어 데이터셋 연구)

  • Sim, Hohyun;Sung, Horyeol;Lee, Seungjae;Cho, Hyeonjoong
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.8
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    • pp.325-330
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    • 2022
  • This paper conducts the collection and experiment of datasets for deep learning research on sign language such as sign language recognition, sign language translation, and sign language segmentation for Korean sign language. There exist difficulties for deep learning research of sign language. First, it is difficult to recognize sign languages since they contain multiple modalities including hand movements, hand directions, and facial expressions. Second, it is the absence of training data to conduct deep learning research. Currently, KETI dataset is the only known dataset for Korean sign language for deep learning. Sign language datasets for deep learning research are classified into two categories: Isolated sign language and Continuous sign language. Although several foreign sign language datasets have been collected over time. they are also insufficient for deep learning research of sign language. Therefore, we attempted to collect a large-scale Korean sign language dataset and evaluate it using a baseline model named TSPNet which has the performance of SOTA in the field of sign language translation. The collected dataset consists of a total of 11,402 image and text. Our experimental result with the baseline model using the dataset shows BLEU-4 score 3.63, which would be used as a basic performance of a baseline model for Korean sign language dataset. We hope that our experience of collecting Korean sign language dataset helps facilitate further research directions on Korean sign language.

Prediction of Music Generation on Time Series Using Bi-LSTM Model (Bi-LSTM 모델을 이용한 음악 생성 시계열 예측)

  • Kwangjin, Kim;Chilwoo, Lee
    • Smart Media Journal
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    • v.11 no.10
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    • pp.65-75
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    • 2022
  • Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

Suitable clothing recommendation system by size and skin color (의류 사이즈별 및 피부톤에 기반을 둔 의류 추천 시스템)

  • Park, Chang-Young;Lim, Byeong-Chan;Lee, Won-Joon;Lee, Chang-Su;Kim, Min-Su;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.407-413
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    • 2022
  • Existing clothing recommendation systems remain at the level of showing appropriate photos when a user selects a type of clothing he or she likes after entering his or her own body size or body size. When a user purchases clothing using such recommendation systems, there are many cases in which it does not fit or does not fit the user's body size. In this study, to solve these problems of existing clothing recommendation systems, a system was implemented in which the user receives not only size but also skin tone and recommends clothing suitable for the user's body size as well as skin tone. In this system, clothing size information obtained through web crawling was periodically stored in a database for eight male tops to recommend clothing, and the entire pixel of the clothing image was analyzed to extract color text values. In order to confirm the performance of this system, a survey was conducted on 100 male college students, and the satisfaction level was 70%. Most of the reasons for not being satisfied are that the recommended clothing is limited, so it is judged that it is necessary to expand the target clothing in the future.

Performance Evaluation of CoMirror System with Video Call and Messaging Function between Smart Mirrors (스마트 미러간 화상 통화와 메시징 기능을 가진 CoMirror 시스템의 성능평가)

  • Kitae Hwang;Kyung-Mi Kim;Yu-Jin Kim;Chae-Won Park;Song-Yeon Yoo;In-Hwan Jung;Jae-Moon Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.51-57
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    • 2023
  • Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the user along with the mirror function. This paper presents performance evaluation of the CoMirror system as an extension of the previous research in which proposed and implemented the CoMirror system that connects Smart Mirrors using a network. First, the login performance utilizing face recognition was evaluated. As result of the performance evaluation, it was concluded that the 40 face images are most suitable for face learning and only one face image is most suitable for face recognition for login. Second, as a result of evaluating the message transmission time, the average time was 0.5 seconds for text, 0.63 seconds for audio, and 2.9 seconds for images. Third, as a result of measuring a video communication performance, the average setup time for video communication was 1.8 seconds and the average video reception time was 1.9 seconds. Finally, according to the performance evaluation results, we conclude that the CoMirror system has high practicality.

An Investigation Into the Effects of AI-Based Chemistry I Class Using Classification Models (분류 모델을 활용한 AI 기반 화학 I 수업의 효과에 대한 연구)

  • Heesun Yang;Seonghyeok Ahn;Seung-Hyun Kim;Seong-Joo Kang
    • Journal of the Korean Chemical Society
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    • v.68 no.3
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    • pp.160-175
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    • 2024
  • The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.

Analysis of Generative AI Technology Trends Based on Patent Data (특허 데이터 기반 생성형 AI 기술 동향 분석)

  • Seongmu Ryu;Taewon Song;Minjeong Lee;Yoonju Choi;Soonuk Seol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.1
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    • pp.1-9
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    • 2024
  • This paper analyzes the trends in generative AI technology based on patent application documents. To achieve this, we selected 5,433 generative AI-related patents filed in South Korea, the United States, and Europe from 2003 to 2023, and analyzed the data by country, technology category, year, and applicant, presenting it visually to find insights and understand the flow of technology. The analysis shows that patents in the image category account for 36.9%, the largest share, with a continuous increase in filings, while filings in the text/document and music/speech categories have either decreased or remained stable since 2019. Although the company with the highest number of filings is a South Korean company, four out of the top five filers are U.S. companies, and all companies have filed the majority of their patents in the U.S., indicating that generative AI is growing and competing centered around the U.S. market. The findings of this paper are expected to be useful for future research and development in generative AI, as well as for formulating strategies for acquiring intellectual property.