• Title/Summary/Keyword: 데이터모델링

Search Result 3,141, Processing Time 0.034 seconds

Data-Driven Senior Cognitive Response Modeling Using Cognitive Measurement Data (인지측정데이터를 이용한 데이터 기반 시니어 인지반응 모델링)

  • Lee, Seolhwa;Yun, Youdong;Ji, Hyesung;Lim, Heuiseok
    • The Journal of Korean Association of Computer Education
    • /
    • v.20 no.2
    • /
    • pp.57-65
    • /
    • 2017
  • The world's senior population is on the rise. In particular, unlike the past seniors who were in the digital insensitivity class, the smart seniors who want to continue to use smart devices and the Internet are emerging. Although the definition of senior is merely defined as a senior group, research on the characteristics of seniors has been done in psychology studies, but research using data based senior cognitive response is only at an early stage. In order to provide contents according to the cognitive characteristics of Smart Senior, there is a need to classify the cognitive characteristics of Smart Senior well. Therefore, this paper suggests a data - driven senior cognitive response modeling method that helps the enjoyment of culture for seniors through classification of cognitive responses to smart seniors.

확장형 히든마코브모델을 이용한 산화막 플라즈마 식각공정의 식각종료점 검출방법

  • Jeon, Seong-Ik;Kim, Seung-Gyun;Hong, Sang-Jin;Han, Seung-Su
    • Proceedings of the Korean Vacuum Society Conference
    • /
    • 2010.02a
    • /
    • pp.407-407
    • /
    • 2010
  • 본 논문에서는 확장된 히든마코브모델을 이용하여 플라즈마 식각공정에서 식각종료검출을 위한 방법을 연구하였다. 플라즈마 식각장비는 유도성 결합플라즈마 시스템을 사용하였으며, 종료점 검출을 위해 식각공정이 진행됨에 따른 플라즈마의 상태를 확인할 수 있는 광학 방사 분광기(Optical Emission Spectroscopy: OES)를 사용하였다. 식각이 진행되는 동안 여기되는 입자들은 특정한 재료에 해당하는 파장에서 빛을 방출한다. 플라즈마상태에서 여기되는 원자와 분자들에 의해서 방출되는 빛은 OES를 통해 식각되는 물질을 확인하기 위해서 특별한 파장의 빛을 선택하여 분석한다. 본 논문에서는 확장된 히든마코브모델을 이용해 산화물이 식각될 때 방출하는 고유한 파장의 빛을 분석하여 식각이 종료되는 시점을 찾는 연구를 하였다. 제안된 확장형 히든마코브 모델은 세미-마코브모델과 분절특징 히든마코브모델을 결합한 것으로, 확률적 통계기법을 통해 종료시점을 찾아내는 방법이다. OES를 통해 얻은 데이터는 식각 종료가 일어나기 전의 파장의 상태와 식각이 종료된 후의 파장의 상태로 구분되어지는데, 식각종료시점에서 파장의 상태가 변화하며 이를 감지하여 식각종료점을 검출한다. 분절특징 히든마코브모델을 이용하여 식각종료시점 전후의 파장의 상태를 모델링 하였으며, 일반적인 마코브 모델의 특정상태가 유지될 시간의 확률을 변형된 세미-마코브 모델을 이용하여 OES를 통해 얻은 데이터 내에서 식각 종료가 일어나기 전의 상태가 유지될 수 있는 확률을 모델링 하였다. 실험을 통해 얻어진 6개의 데이터중 4개를 학습을 위해 사용하여 모델링을 하였고 나머지 2개의 데이터를 검증을 위해 사용한 결과, 확장형 히든마코브모델의 식각종료시점검출에 있어 뛰어난 정확성과 우수성을 증명하였다.

  • PDF

Data Analysis of Dropouts of University Students Using Topic Modeling (토픽모델링을 활용한 대학생의 중도탈락 데이터 분석)

  • Jeong, Do-Heon;Park, Ju-Yeon
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.25 no.1
    • /
    • pp.88-95
    • /
    • 2021
  • This study aims to provide implications for establishing support policies for students by empirically analyzing data on university students dropouts. To this end, data of students enrolled in D University after 2017 were sampled and collected. The collected data was analyzed using topic modeling(LDA: Latent Dirichlet Allocation) technique, which is a probabilistic model based on text mining. As a result of the study, it was found that topics that were characteristic of dropout students were found, and the classification performance between groups through topics was also excellent. Based on these results, a specific educational support system was proposed to prevent dropout of university students. This study is meaningful in that it shows the use of text mining techniques in the education field and suggests an education policy based on data analysis.

A Study on Search Query Topics and Types using Topic Modeling and Principal Components Analysis (토픽모델링 및 주성분 분석 기반 검색 질의 유형 분류 연구)

  • Kang, Hyun-Ah;Lim, Heui-Seok
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.10 no.6
    • /
    • pp.223-234
    • /
    • 2021
  • Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

Analysis of global trends on smart manufacturing technology using topic modeling (토픽모델링을 활용한 주요국의 스마트제조 기술 동향 분석)

  • Oh, Yoonhwan;Moon, HyungBin
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.27 no.4
    • /
    • pp.65-79
    • /
    • 2022
  • This study identified smart manufacturing technologies using patent and topic modeling, and compared the technology development trends in countries such as the United States, Japan, Germany, China, and South Korea. To this purpose, this study collected patents in the United States and Europe between 1991 and 2020, processed patent abstracts, and identified topics by applying latent Dirichlet allocation model to the data. As a result, technologies related to smart manufacturing are divided into seven categories. At a global level, it was found that the proportion of patents in 'data processing system' and 'thermal/fluid management' technologies is increasing. Considering the fact that South Korea has relative competitiveness in thermal/fluid management technologies related to smart manufacturing, it would be a successful strategy for South Korea to promote smart manufacturing in heavy and chemical industry. This study is significant in that it overcomes the limitations of quantitative technology level evaluation proposed a new methodology that applies text mining.

Design and Implementation of Dangerous Situation Assessment System using YOLOv4 and Data Modeling (YOLOv4와 데이터 모델링을 활용한 위험 상황 판정 시스템의 설계 및 구현)

  • Lee, Taejun;Kim, Sohyun;Yang, Seungeui;Hwang, Chulhyun;Jung, Hoekyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.05a
    • /
    • pp.488-490
    • /
    • 2022
  • Recently, interest in industrial accidents such as the Industrial Safety and Health Act and the Serious Accident Punishment Act is increasing, and the demand for safety managers for safety management of workers in research institutes and industrial fields of various fields is increasing. For worker safety management, CCTVs are being installed in factories and workplaces, and workers are monitored to enhance safety management. In this paper, we intend to design a dangerous situation assessment system by constructing data using CCTV in such a workplace and modeling it in JSON format. The data modeling was produced by referring to the data set construction guide for artificial intelligence learning and the quality management guideline of the Korea National Information Society(NIA). Through this system, we want to check what kind of risk management exists in the workplace by risk situation scenario and use it to build a more systematic system.

  • PDF

A Dynamic Rain Attenuation Model for Adaptive Satellite Communication Systems (적응형 위성통신 시스템 설계를 위한 동적 강우 감쇠 모델)

  • Zhang, Meixiang;Kim, Soo-Young;Pack, Jeong-Ki
    • Journal of Satellite, Information and Communications
    • /
    • v.6 no.1
    • /
    • pp.12-18
    • /
    • 2011
  • Signal fading due to rain is one of the most significant factors degrading link quality in satellite communication systems. Adaptive transmission is considered to be the most efficient means to countermeasure the rain attenuation. In order to develop and design a good adaptive transmission system, we need a dynamic rain attenuation model which can synthesize time series of rain attenuation. In this paper, we present a modeling technique for dynamic rain attenuation using a Markov process. We derive statistical fading properties of the rain attenuation data measured in second time interval and define four states in the Markov process. We synthesize the rain attenuation data using the 4-state Markov process, and compare statistical properties of the simulated data to those of the measured data.

Composing Recommended Route through Machine Learning of Navigational Data (항적 데이터 학습을 통한 추천 항로 구성에 관한 연구)

  • Kim, Joo-Sung;Jeong, Jung Sik;Lee, Seong-Yong;Lee, Eun-seok
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
    • /
    • 2016.05a
    • /
    • pp.285-286
    • /
    • 2016
  • We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

  • PDF

A study of XML application to test S-100 web-service for casualty information (S-100 표준의 웹 서비스 실험을 위한 해양사고정보의 XML 응용 연구)

  • Lee, Seojeong;Kim, Hyo-Seung;Lee, Hee-Yong
    • Journal of Digital Contents Society
    • /
    • v.14 no.3
    • /
    • pp.391-400
    • /
    • 2013
  • IMO developed e-navigation implementation plan which is a new paradigm of vessel safety navigation using harmonized information technology. S-100 standard for electronic navigational chart is also adopted as one of e-navigation strategies. In S-100 framework, not only geographic features of electronic chart but every safety related objects can be expressed by UML so that can be provided by web services. This paper research to test S-100 web service for casualty information. It is processed by modeling with UML, converting XML document by XML schema. Finally, the XML data is represented by web-based application.

EM Algorithm based Neuro-Fuzzy Modeling (EM알고리즘을 기반으로 한 뉴로-퍼지 모델링)

  • Kim, Seoung-Suk;Jun, Beung-Suk;Kim, Ju-Sik;Ryu, Jeoung-Woong
    • Proceedings of the KIEE Conference
    • /
    • 2002.07d
    • /
    • pp.2846-2849
    • /
    • 2002
  • 본 논문은 뉴로-퍼지 시스템에서의 규칙 선택 및 모델 학술에 대하여 EM 알고리즘을 기반으로 하는 구조 동정을 제안한다. 뉴로-퍼지 모델링에서의 초기 파라미터가 학습과정에서의 모델 성능에 큰 영향을 주고 있다. 주어진 데이터에 근거한 파라미터 추정에는 다양한 방법들이 소개되고 응용되어져 왔는데 이전 연구들에서 볼 수 있는 HCM, FCM 등은 데이터와의 유클리디언 거리를 최소화하는 중심점을 파라미터로 선택하는 등의 방법과 퍼지 균등화 등은 데이터의 확률 밀도함수를 이용하여 파라미터를 추정하였다. 제안된 방법에서는 데이터에서의 Maximum Likelihood Estimator를 기반으로 하는 방법으로 EM 알고리즘을 이용하였다. 초기 파라미터의 결정에서 EM 알고리즘을 이용하여 뉴로-퍼지 모델의 전제부 소속함수 파라미터 추정을 실시한다. EM 알고리즘을 이용한 퍼지 모델의 특징으로는 전제부가 클러스터링에 의하여 생성되므로 입력의 차원이나 소속함수의 수가 증가하여도 규칙의 수는 증가하지 않는다. 이를 자동차 MPG 예제를 통하여 제안된 방법의 유용성을 보이고자 한다.

  • PDF