• Title/Summary/Keyword: 포스트 넷

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Automatic post address print out system based on QRcode or CVS (QR 코드 및 CVS 기반 주소지 자동 기표지 출력 시스템)

  • Choi, Jae-Ho;Jeong, Yang-Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.1
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    • pp.113-118
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    • 2016
  • This study found that there are problems in sending mails at the postal service reception desks and proposes a system which transmits address information to POSNET(the terminals at post office reception) without the use of an additional security system based on address information which is stored in the terminals of mobile phones. The system proposed transforms the information of users into two-dimensional barcode(QR code) of the POSNET and a number of address information is texturized and transmitted to the POSNET with the use of how to read QR code and LAN such as bluetooth. When the system proposed is connected to the postal reception system, it can create and output mail addresses for mobile computers automatically and contribute to better performance for the post office reception clerks and better economic results.

A Study on the Direction of Art Policy through Semantic Network Analysis in New Normal Era (뉴노멀(New Normal) 시대 언어네트워크 분석에 의한 예술정책 방향 연구)

  • Kim, Mi Yeon;Kwon, Byeong Woong
    • Korean Association of Arts Management
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    • no.58
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    • pp.153-177
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    • 2021
  • This study attempted to analyze language networks based on the theory of art policy in the New Normal era triggered by COVID-19 and domestic and foreign policy trends. For analysis, data containing key words of "Corona" and "Art" were collected from Google News and Web documents from March to September 2020 to extract 227 refined subject words, and the extracted subject words were analyzed as indicators of frequency and centrality of subject words through the Netminor program. In addition, visualization analysis of semantic networks has been attempted for the analysis of relationships between each topic languages. As a result of the semantic network analysis, the most frequent topic was "Corona," and "Culture and Art," "Art," "Performance," "Online" and "Support" were included in the group with the most frequencies. In the centrality analysis, "Corona" was the most popular, followed by "the era," "after," "post," "art," and "cultural arts," with high frequency, "Corona," "art," and "cultural arts" also dominated most centrality. In particular, the top-level key words in the analysis of frequency and centrality of the topic are 'online' and 'support' and 'policy'. This can be seen as indicating that the rapid rise of non-face-to-face and online content and support policies for the artistic communities are needed due to the dailyization of social distance due to COVID-19.

Outdoor Healing Places Perception Analysis Using Named Entity Recognition of Social Media Big Data (소셜미디어 빅데이터의 개체명 인식을 활용한 옥외 힐링 장소 인식 분석)

  • Sung, Junghan;Lee, Kyungjin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.50 no.5
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    • pp.90-102
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    • 2022
  • In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.