• Title/Summary/Keyword: network activity

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User Identification and Entrance/Exit Detection System for Smart Home (지능형 홈을 위한 사용자 식별 및 출입 감지 시스템)

  • Lee, Seon-Woo
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.3
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    • pp.248-253
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    • 2008
  • This paper presents a sensing system for smart home which can detect an location transition events such as entrance/exit of a member and identify the user in a group at the same time. The proposed system is compose of two sub-systems; a wireless sensor network system and a database server system. The wireless sensing system is designed as a star network where each of sensing modules with ultrasonic sensors and a Bluetooth RF module connect to a central receiver called Bluetooth access point. We propose a method to discriminate a user by measuring the height of the user. The differences in the height of users is a key feature for discrimination. At the same time, the each sensing module can recognize whether the user goes into or out a room by using two ultrasonic sensors. The server subsystem is a sort of data logging system which read the detected event from the access point and then write it into a database system. The database system could provide the location transition information to wide range of context-aware applications for smart home easily and conveniently. We evaluate the developed method with experiments for three subjects in a family with the installation of the developed system into a real house.

Comparison of daily solar flare peak flux forecast models based on regressive and neural network methods

  • Shin, Seulki;Lee, Jin-Yi;Moon, Yong-Jae
    • The Bulletin of The Korean Astronomical Society
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    • v.39 no.1
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    • pp.75.2-75.2
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    • 2014
  • We have developed a set of daily solar flare peak flux forecast models using the multiple linear regression (MLR), the auto regression (AR), and artificial neural network (ANN) methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux, weighted total flux $T_F=1{\times}F_C+10{\times}F_M+100{\times}F_X$ of previous day, mean flare rates of a given McIntosh sunspot group (Zpc), and a Mount Wilson magnetic classification. We compute the hitting rate that is defined as the fraction of the events whose absolute differences between the observed and predicted flare fluxes in a logarithm scale are ${\leq}$ 0.5. The best three parameters related to the observed flare peak flux are as follows: weighted total flare flux of previous day (r=0.5), Mount Wilson magnetic classification (r=0.33), and McIntosh sunspot group (r=0.3). The hitting rates of flares stronger than the M5 class, which is regarded to be significant for space weather forecast, are as follows: 30% for the auto regression method and 69% for the neural network method.

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A Keyword Network Analysis on Health Disparity in Korea: Focusing on News and its application to Physical Education

  • Kim, Woo-Kyung
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.3
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    • pp.143-150
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    • 2019
  • This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

A Study on Improvement of the School Space through Socio-Spatial Network Analysis (사회-공간 네트워크 분석을 활용한 초등학교 공간계획방향에 관한 연구)

  • Jeon, Young-Hoon;Kim, Yoon-Young
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.5
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    • pp.21-30
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    • 2019
  • The purpose of this study is to present the direction of the new space plan by reflecting the opinions of the user (student) in the existing standardized elementary school space planning. The purpose of this study is to investigate the activities of elementary school students by using socio - spatial network analysis method and to propose the direction of new elementary school space planning through the results. We analyzed the results of each centrality by using the analysis of closeness analysis, betweeness analysis, girvan-newman clustering, and concor analysis. The results of this study are as follows. First, it should be planned to use the classroom and the special room as one area by utilizing the corridor. Second, it should be planned that the outdoor space and the indoor space are closely related to each other by utilizing the hall, the lobby and the classroom. Third, the school should create a small space where physical activity is possible in an indoor space of the school. In order to improve the standardized elementary school space, this study proposes a method to reflect the opinions of the users in the school planning stage.

Automated Construction Activities Extraction from Accident Reports Using Deep Neural Network and Natural Language Processing Techniques

  • Do, Quan;Le, Tuyen;Le, Chau
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.744-751
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    • 2022
  • Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

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A Study on a Method for Detecting Leak Holes in Respirators Using IoT Sensors

  • Woochang Shin
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.378-385
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    • 2023
  • The importance of wearing respiratory protective equipment has been highlighted even more during the COVID-19 pandemic. Even if the suitability of respiratory protection has been confirmed through testing in a laboratory environment, there remains the potential for leakage points in the respirators due to improper application by the wearer, damage to the equipment, or sudden movements in real working conditions. In this paper, we propose a method to detect the occurrence of leak holes by measuring the pressure changes inside the mask according to the wearer's breathing activity by attaching an IoT sensor to a full-face respirator. We designed 9 experimental scenarios by adjusting the degree of leak holes of the respirator and the breathing cycle time, and acquired respiratory data for the wearer of the respirator accordingly. Additionally, we analyzed the respiratory data to identify the duration and pressure change range for each breath, utilizing this data to train a neural network model for detecting leak holes in the respirator. The experimental results applying the developed neural network model showed a sensitivity of 100%, specificity of 94.29%, and accuracy of 97.53%. We conclude that the effective detection of leak holes can be achieved by incorporating affordable, small-sized IoT sensors into respiratory protective equipment.

Rheumatoid Fibroblast-like Synoviocytes Downregulate Foxp3 Expression by Regulatory T Cells Via GITRL/GITR Interaction

  • Kim, Sung Hoon;Youn, Jeehee
    • IMMUNE NETWORK
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    • v.12 no.5
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    • pp.217-221
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    • 2012
  • Fibroblast-like synoviocytes (FLS) colocalize with leukocyte infiltrates in rheumatoid synovia. Proinflammatory leukocytes are known to amplify inflammation by signaling to FLS, but crosstalk between FLS and regulatory T cells (Tregs) remains uncharacterized. To address this possibility, we cocultured FLS lines derived from arthritic mice with Tregs. FLS that expressed the ligand for glucocorticoid-induced TNF receptor family-related gene (GITR) decreased expression of Foxp3 and GITR in Tregs in a contact-dependent manner. This effect was abolished by blocking antibody to GITR. On the other hand, the Tregs caused the FLS to increase IL-6 production. These results demonstrate that inflamed FLS license Tregs to downregulate Foxp3 expression via the GITRL/GITR interaction while the Tregs induce the FLS to increase their production of IL-6. Our findings suggest that the interaction between FLS and Tregs dampens the anti-inflammatory activity of Tregs and amplifies the proinflammatory activity of FLS, thereby exacerbating inflammatory arthritis.

Realizing an Object-Oriented Informationalization for Activity-Based Business Processing (활동기반 업무처리를 위한 객체기반 정보화)

  • Hwang, Jong-Ho
    • Journal of Information Technology Services
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    • v.12 no.1
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    • pp.309-321
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    • 2013
  • In current complex nature of management with task-structures, a method to reach the enterprise's informationalization success is not common. To satisfy these various requirement, improving the usability of information technology (IT) is a key factor which defining the level of organizational requirement first. Imposing an IT-solution which has excess service of the organization's previous task-environment, procedure and scope is not effective to SME-level unit, which unit could not have a formal organization structure and task structure. SME level informationalization will be success if each function realizes easier on the task-employee's viewpoint. Achieving this objective, a solution provider or department must reflect their work characteristics of nature which has least level of work performing resistance. It is most useful system for SME level unit, if a provider develops single programs which based on task activities, and each program can configure network-linking.

A Discussion on the Importance of Community Youth Activities and Enhancement of Youth Competence (지역사회 중심 청소년활동의 중요성과 청소년 역량강화 방안)

  • Oh, Hae-Sub
    • Journal of Agricultural Extension & Community Development
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    • v.15 no.3
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    • pp.417-432
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    • 2008
  • The purpose of this study were to discuss on the importance of community youth development programs and review the enhancement of competence in youth The research methods used the extensive review of related literatures. Based on the major results, the implications and suggestions were as follows. First, community youth activity will need to provide the opportunities of enhancing the competencies and a full complement of positive connections to youth programs. Second, communities promote to engage youth as partners with adults in the process of positive youth development. Third, youth development organizations operate to support the programs to prevent risky-behaviors or treat specific problems in terms of community youth contexts. Finally, collaboration and network are necessarily required among youth, adults, family, school, organizations within the community. Changes to work and workplace are so significant that policies refer to 'the knowledge society' at the same time 'information society'. Future workers will need to have the skills of information and communications management and control.

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Dynamic Human Activity Recognition Based on Improved FNN Model

  • Xu, Wenkai;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.15 no.4
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    • pp.417-424
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    • 2012
  • In this paper, we propose an automatic system that recognizes dynamic human gestures activity, including Arabic numbers from 0 to 9. We assume the gesture trajectory is almost in a plane that called principal gesture plane, then the Least Squares Method is used to estimate the plane and project the 3-D trajectory model onto the principal. An improved FNN model combined with HMM is proposed for dynamic gesture recognition, which combines ability of HMM model for temporal data modeling with that of fuzzy neural network. The proposed algorithm shows that satisfactory performance and high recognition rate.