• Title/Summary/Keyword: 경영 정보 시스템

Search Result 2,951, Processing Time 0.027 seconds

Development of Mask-RCNN Model for Detecting Greenhouses Based on Satellite Image (위성이미지 기반 시설하우스 판별 Mask-RCNN 모델 개발)

  • Kim, Yun Seok;Heo, Seong;Yoon, Seong Uk;Ahn, Jinhyun;Choi, Inchan;Chang, Sungyul;Lee, Seung-Jae;Chung, Yong Suk
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.23 no.3
    • /
    • pp.156-162
    • /
    • 2021
  • The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

Domain Knowledge Incorporated Counterfactual Example-Based Explanation for Bankruptcy Prediction Model (부도예측모형에서 도메인 지식을 통합한 반사실적 예시 기반 설명력 증진 방법)

  • Cho, Soo Hyun;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
    • /
    • v.28 no.2
    • /
    • pp.307-332
    • /
    • 2022
  • One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

Proposal of Promotion Strategy of Mobile Easy Payment Service Using Topic Modeling and PEST-SWOT Analysis (모바일 간편 결제 서비스 활성화 전략 : 토픽 모델링과 PEST - SWOT 분석 방법론을 기반으로)

  • Park, Seongwoo;Kim, Sehyoung;Kang, Juyoung
    • Journal of Intelligence and Information Systems
    • /
    • v.28 no.4
    • /
    • pp.365-385
    • /
    • 2022
  • The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.

Development of Demand Forecasting Model for Public Bicycles in Seoul Using GRU (GRU 기법을 활용한 서울시 공공자전거 수요예측 모델 개발)

  • Lee, Seung-Woon;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
    • /
    • v.28 no.4
    • /
    • pp.1-25
    • /
    • 2022
  • After the first Covid-19 confirmed case occurred in Korea in January 2020, interest in personal transportation such as public bicycles not public transportation such as buses and subways, increased. The demand for 'Ddareungi', a public bicycle operated by the Seoul Metropolitan Government, has also increased. In this study, a demand prediction model of a GRU(Gated Recurrent Unit) was presented based on the rental history of public bicycles by time zone(2019~2021) in Seoul. The usefulness of the GRU method presented in this study was verified based on the rental history of Around Exit 1 of Yeouido, Yeongdengpo-gu, Seoul. In particular, it was compared and analyzed with multiple linear regression models and recurrent neural network models under the same conditions. In addition, when developing the model, in addition to weather factors, the Seoul living population was used as a variable and verified. MAE and RMSE were used as performance indicators for the model, and through this, the usefulness of the GRU model proposed in this study was presented. As a result of this study, the proposed GRU model showed higher prediction accuracy than the traditional multi-linear regression model and the LSTM model and Conv-LSTM model, which have recently been in the spotlight. Also the GRU model was faster than the LSTM model and the Conv-LSTM model. Through this study, it will be possible to help solve the problem of relocation in the future by predicting the demand for public bicycles in Seoul more quickly and accurately.

Analysis of Discriminatory Patterns in Performing Arts Recognized by Large Language Models (LLMs): Focused on ChatGPT (거대언어모델(LLM)이 인식하는 공연예술의 차별 양상 분석: ChatGPT를 중심으로)

  • Jiae Choi
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.3
    • /
    • pp.401-418
    • /
    • 2023
  • Recently, the socio-economic interest in Large Language Models (LLMs) has been growing due to the emergence of ChatGPT. As a type of generative AI, LLMs have reached the level of script creation. In this regard, it is important to address the issue of discrimination (sexism, racism, religious discrimination, ageism, etc.) in the performing arts in general or in specific performing arts works or organizations in a large language model that will be widely used by the general public and professionals. However, there has not yet been a full-scale investigation and discussion on the issue of discrimination in the performing arts in large-scale language models. Therefore, the purpose of this study is to textually analyze the perceptions of discrimination issues in the performing arts from LMMs and to derive implications for the performing arts field and the development of LMMs. First, BBQ (Bias Benchmark for QA) questions and measures for nine discrimination issues were used to measure the sensitivity to discrimination of the giant language models, and the answers derived from the representative giant language models were verified by performing arts experts to see if there were any parts of the giant language models' misperceptions, and then the giant language models' perceptions of the ethics of discriminatory views in the performing arts field were analyzed through the content analysis method. As a result of the analysis, implications for the performing arts field and points to be noted in the development of large-scale linguistic models were derived and discussed.

A Study on the influence of e-Service Quality of Internet Open-Market as Perceived Value, Customer Satisfaction and e-Loyalty (인터넷 오픈마켓의 e-서비스 품질이 지각된 가치, 고객만족 및 e-충성도에 마치는 영향에 관한 연구)

  • Kim, Bon-Su;Bae, Mu-Eun
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.15 no.4
    • /
    • pp.83-101
    • /
    • 2010
  • Competition in Internet open-market has become fiercer as much for its growth possibility in differentiating from the general commercial market. For this reason, internet open-market entrepreneurs should make effective strategy in improving customers' e-loyalty to survive in the highly competitive internet open-market as in off-line market and to aim for growth through constant profit making. To satisfy with the goal, this study has been performed as the empirical research that confirms to the influence and relationship of e-service quality affected on the perceived value, customer satisfaction and e-loyalty. This is based on the result that e-service quality affected on e-loyalty for internet open-market. The research results are shown as follows; first, all factors including the perceived value and customer satisfaction, except possibility of system use, have the effect of e-service quality. Second, the perceived value between measurements affects significantly on customer satisfaction. And third, the perceive value and the customer satisfaction are a1so meaningfully influential to e-loyalty. The result presents important point that entrepreneurs in Internet open-market need to do their best to maintain in making profits for the future by improving the customers' e-loyalty and securing customers with high loyalty via continually revealing new influential factors on e-service quality, perceived value, and customer satisfaction.

A Study on the Korean Patent Registration Trend of Outdoor Exercise Equipment for the Elderly (노인 관련 야외운동기구의 국내 특허 등록 동향에 관한 연구)

  • Dong-Cheol Chi;Hong-Young Jang
    • Journal of Industrial Convergence
    • /
    • v.21 no.6
    • /
    • pp.43-51
    • /
    • 2023
  • This study analyzed the patent status of the outdoor exercise equipment used primarily by the elderly. The purpose is to utilize the basic data obtained to promote the health of the elderly. The information on the patent was collected from KIPRIS, an information search service provided by the Korean Intellectual Property Office. The search term used was 'outdoor exercise equipment', directly related patents were selected, and a final 157 were analyzed. As a result of the analysis, first, patent registration began in 2007, and 2-3 patents were registered on average every year. Second, patents from the perspective of sports convergence that provide an exercise prescription system using wireless communication, such as the ability to generate electricity by operating a power generation module, providing information on the user's exercise amount, or preventing the loss and theft of weights and safety accidents due to their characteristics, were searched for. Lastly, patents related to exercise equipment that can provide user convenience and increase the frequency of use of exercise equipment were searched. The results of this study confirmed that outdoor exercise equipment is being developed more for the elderly and their convenience, and that companies and public institutions are showing increased interest in outdoor exercise equipment for the elderly. In addition to patent trends analysis, follow-up research in connection with exercise programs using outdoor exercise equipment is needed to develop practical and convenient outdoor exercise equipment in the future.

A study of the impact of Metaverse attributes on intention to use - based on the Extended Technology Acceptance Model (메타버스특성이 이용의도에 미치는 영향에 관한 연구 - 확장된 기술수용모델을 기반으로)

  • Seung Beom Kim;Hyoung-Yong Lee
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.2
    • /
    • pp.149-170
    • /
    • 2023
  • This study analyzed the factors influencing users' intention to use the Metaverse by applying the extended technology acceptance model. In other words, the factors affecting users' intention to use the Metaverse were defined as technical characteristics (telepresence, interoperability, seamlessness, concurrence, and economy flow) and personal characteristics (social influence and perceived enjoyment) from the perspective of the Extended Technology Acceptance Model. For this purpose, a survey was conducted among men and women of various ages ranging from teenagers to 60s, and the data collected from 327 participants were analyzed using SPSS 22.0 and Smart PLS 4.0. The results showed that perceived usefulness and perceived ease of use, which are antecedents of the Extended Technology Acceptance Model, influence the intention to use Metaverse, and perceived ease of use influences perceived usefulness. Telepresence, interoperability and economy flow were found to have a positive effect on perceived usefulness, and interoperability, seamlessness and concurrence were found to have a positive effect on perceived ease of use. In addition, social influence and perceived enjoyment had a positive effect on intention to use the Metaverse. This study is significant in that it empirically analyzed the factors of users' acceptance of the Metaverse, which is attracting attention as a new platform that will bring significant changes to our daily lives and platform consumption environments.

A Reflection of Aging Society in Online Communities: An Exploratory Study on Changes in Conversation Style and Language Usage (온라인 커뮤니티에서 보여지는 노령화 사회의 단면: 대화 방식과 사용 언어의 변화에 대한 탐색적 연구)

  • Jung Lee;Jinyoung Han;Juyeon Ham
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.4
    • /
    • pp.51-68
    • /
    • 2023
  • With the emergence of the internet and the increasing use of online communities for over 20 years, the age range of users has also been rising. This study explores the linguistic changes that have occurred as the user age in online communities has increased. To do this, data was collected and analyzed from an online community that has been actively operating, despite new member registrations being closed nine years ago. By comparing the posts over an 11-year period from 2012 to 2022, changes such as an increase in average comments, a decrease in interrogative sentences, and a decrease in imperative statements were observed. The study also proposed loneliness due to aging and a decline in curiosity and confidence as potential causes of these changes. In South Korea, which is rapidly entering an aging society unprecedentedly fast on a global scale, the increase in single-person households has evolved loneliness from a personal issue to a social problem, manifested in an increase in solitary deaths and reclusive individuals. This research sheds light on one aspect of these social phenomena through the analysis of data from a large online community.

Impact of customer experience characteristics on perceived value and revisit intention: Focusing on offline home appliance stores (고객체험특성이 지각된 가치와 재방문 의도에 미치는 영향: 가전 오프라인 매장을 중심으로)

  • Hosun Jeong;Jungmin Park;Hyoung-Yong Lee
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.4
    • /
    • pp.395-413
    • /
    • 2023
  • This research studied the effect of customer experience characteristics in offline home appliance stores on perceived value and revisit intention. Among the offline distribution of home appliances with more than 100 stores nationwide, two home appliance retailers (HiMart, E-Land), three hypermarkets (E-Mart, Homeplus, Lotte Hi-Mart), and two home appliance stores (LG Best Shop, Samsung Digital Plaza) were selected, and a survey was conducted on men and women in their 20s or older in Seoul, Gyeonggi, and Incheon who had visited and purchased the home appliance store within the last 6 months. As a result of the survey, a statistical analysis was conducted on a total of 330 samples using the PLS (Partial Least Squares) structural equation model and SPSS statistical package. Through this study, the following research results can be obtained. First, educational experience, deviant experience, and aesthetic experience had a positive (+) effect on the functional value. However, entertainment experience did not affect functional value. Second, educational experience, deviant experience, and aesthetic experience all had a positive (+) effect on emotional value. Third, both functional and sensory values had a positive (+) effect on the revisit intention. Fourth, it was confirmed that brand loyalty had no moderating effect between functional value and sensory value revisit intention. The results of this study show the structural relationship between customer experience characteristics, perceived value (functional value, sensory value), and revisit intention. This result provides guidelines on what activities home appliance offline stores should do at a time when online channels threaten the survival of offline channels.