• Title/Summary/Keyword: WordPress

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Research of the Possibility and Awareness for Open Source WordPress (Open Source WordPress의 인식과 가능성에 관한 연구)

  • Yoon, Kyung Seob;Park, Joon Tae;Im, Dong Hyeok
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2013.07a
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    • pp.255-257
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    • 2013
  • 최근 OS와 개발 정보에 대한 일반 사용자들의 접근성이 좋아지면서 오픈소스(Open Source)와 관련 툴들이 각광 받고 있다. 이러한 툴 중 많은 사람들이 사용하고 있는 블로그 개발 툴의 하나인 워드프레스(WordPress)는 다양한 프로그래밍 언어와 플랫폼(platform), 브라우저(browser)에 구애 받지 않고 강력한 기능을 제공함으로써 web과 관련하여 이용 빈도가 늘어나고 있다. 따라서 본 연구에서는 오픈 소스 툴 중 하나인 워드프레스의 기능성을 중점적으로 서술하고 일반 사용자가 워드프레스를 사용할 때 가장 큰 어려움이 무엇인지 짚어보고 문제에 대한 해결책을 제시한다.

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The Information Search Method According to Eating-out Motivation of College Students in Eastern Area of Kangwon Province (강원도 영동권 지역 대학생들의 외식동기에 의한 정보탐색방법)

  • Yoon Tae-Hwan
    • Korean journal of food and cookery science
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    • v.22 no.2 s.92
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    • pp.213-221
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    • 2006
  • Although motivation and information search have both been studied continuously and separately as important marketing strategies, the relation between cause and effect has received little research attention. Therefore the objective of this study was to research the causal relationships between motivation and information search method. Frequency analysis and reliability analysis, factor analysis, and SEM(Structure Equation Model) were adopted to analyze the data. Motivation was divided into 5 factors which significantly influenced information search method. Factor 1, 'Reception and congratulation', influenced information search positively through 'newspaper, magazine', and 'word of mouth' but negatively through 'TV-advertising' and 'Flyer, Press copy'. Factor 2, 'Change of dietary life', influenced positively 'TV-advertising'. Factor 3, 'Economic saving', influenced positively 'newspaper, magazine', and 'the e-mail's advertising' Factor 4, 'Preference motivation', influenced negatively 'word of mouth' Factor 5, 'Advertisement and companion's need', influenced positively 'newspaper, magazine', and 'the e-mail's advertising' but negatively 'TV-advertising' As a result, customers appeared to choose various information search methods according to their eating-out motivation. 'The e-mail's advertising', and 'word of mouth' are popular among customers' information search methods. Therefore, food-service corporations need to try eliminating negative images of various advertisements and activate positive word of mouth marketing, promotion through internet.

Covid 19 News Data Analysis and Visualization

  • Hur, Tai-Sung;Hwang, In-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.4
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    • pp.37-43
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    • 2022
  • In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

An Analysis of Diffusion of Main Information and Peripheral Information: Focusing on Visibility and Connectivity of Word based on Network Analysis (핵심 정보와 주변 정보의 확산 과정 연구: 단어의 가시성(visibility)과 연결성(connectivity) 분석을 중심으로 본 언론의 프레임)

  • Hong, Ju-Hyun
    • The Journal of the Korea Contents Association
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    • v.16 no.3
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    • pp.269-287
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    • 2016
  • This study explores of press report on the death of Beongen Yoo based on network analysis and how issue diffuses via Internet and SNS in mainstream news and conservative channels of comprehensive programming. Issue salience, word's visibility and word's connectivity are the main keyword and analysis criteria of this study. Conservative channel of comprehensive programming focused on the surrounding information rather than core information compared to Mainstream media, Conservative channels of comprehensive media was interested in Yu, Beongeon, an article left, brand, rumor of a body and Mainstream media focused on the results of DNA test. Mainstream media covers this case as the discovery of the Yu, Beongeon body, Mainstream media reported as 'the discovery of the body frame, conservative channels of comprehensive programming reports as blame of investigation at the first stage. The former focuses on the cause of death and the latter focuses on the raising of strong doubts frame at the second stage. In case of the third stage the latter covered on the emphasis of the surrounding information. They frames the issue differently based on network analysis. The view point of conservative channel of comprehensive programming is diffused via SNS. This study highlights the role of journalist of mainstream media in the process of agenda-setting

Construction of Shopping Mall Site using Wordpress (워드프레스를 이용한 쇼핑몰 사이트 구축)

  • Baek, Yeong-Tae;Lee, Se-Hoon;Park, Hyun-Ji
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2014.07a
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    • pp.209-212
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    • 2014
  • 본 논문에서는 PHP와 MySQl의 언어를 기반으로 한 오픈 소스 기반의 콘텐츠 관리시스템인 워드프레스(Wordpress)를 설치하고 이를 기반으로 쇼핑몰을 구축 한다. 워드프레스는 각종 테마를 통해 자신이 원하는 디자인으로 홈페이지를 꾸밀 수 있고 수많은 플러그인으로 사용자가 원하는 기능을 추가할 수 있는데, 이 논문에서는 우커머스(Woocommerce)라는 플러그인 설치하여 상품의 주문 내역을 확인 할 수 있고 쿠폰을 등록할 수 있고 '보고서'라는 기능을 통해 이들에 대한 내용을 관리 분석할 수 있으며, 상품을 추가, 삭제, 수정 할 수 있으며 재고관리도 가능한 쇼핑몰을 구축한다.

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Differences in High Pitch Accents between News Speech and Natural Speech (영어 뉴스와 자연발화에 나타나는 고성조 피치액센트의 차이점)

  • Choi, Yun-Hui;Lee, Joo-Kyeong
    • Speech Sciences
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    • v.12 no.2
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    • pp.17-28
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    • 2005
  • This paper argues that news speech entails a distinct intonational pattern from natural speech, effectively reflecting that it primarily focuses on providing new information. We conducted a phonetic experiment to compare the tonal contours between news speech and natural speech, examining the distributions of pitch accents and the overall pitch ranges. We utilized 70 American Press (AP) radio news utterances and 70 natural utterances extracted from TV dramas. Results show that news speech involves 3.38 H*'s (including L+H* and !H*) within an intonational phrase (IP) or intermediate phrase (ip) whereas natural speech, 1.8 in average. The number of IP/ip's per sentence is 3 in news speech, which is shown in the highest rate of 32.07% of the news speech, but it is merely 1, taking up the highest 41.42% in natural speech. Next, declination tends to be prevented in news speech, and the pitch range is much greater in news speech than in natural speech. Finally, a secondary stress syllable is comparatively frequently given a pitch accent in news speech, explicitly distinct from natural speech. These results can be interpreted as stating that news has the particular purpose of providing new information; every content word tends to be given a H* or its related pitch accent like L+H* or !H* because news speech assumes that every word conveys new information. This definitely brings about more IP/ip's per sentence due to a human physiological constraint; that is, more H*'s will cause more respiratory breaks. Also, greater pitch ranges and pitch accents imposed on secondary stress may be attributed to exaggerating new information.

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A Study on the Promotion Strategy for Internet Fashion Soho Shopping Mall (인터넷 패션 소호 쇼핑몰 활성화를 위한 촉진전략 연구)

  • Kim, Hee-Sun
    • Journal of the Korea Fashion and Costume Design Association
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    • v.9 no.3
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    • pp.59-73
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    • 2007
  • The purpose of this study is to find out the promotion methods for successful management of 'the fashion saho internet shopping mall' with a small capital. This study analyze the research reports, the news items, the documents on the internet shopping mall and data on promotion method which are offered by the hosting companies of the internet shopping mall like 'Cafe 24', 'Make shop', 'Whoismall' and the promotion consulting companies like 'Whoisad', 'Naver keyword shop'. And also analyze the data that interviewed the administrator of internet shopping mall and directly observed the famous internet shopping mall sites. Generally speaking, the promotion mix, marketing communication program can classify 'advertisement', 'publicity', 'personal selling', and 'sales promotion'. This study analyze the research materials on the basis of advertisement, publicity, personal selling, and sales promotion. The result are as follows. 1. The promotion methods at the stage of information the shopping mall site to the consumer are advertisement, and publicity. ${\bigcirc}$ The methods of advertisement are 'searching engine registration', 'advertisement of key word', 'advertisement of overture', 'advertisement of banner', 'advertisement cooperation marketing', 'advertisement of e-mail'. ${\bigcirc}$ The methods of publicity are using 'cafe', 'blog', 'Naver information site', 'community bulletin board', 'the fashion magazine or a press report' and 'cosponsorship'. 2. The main promotion methods at the stage of inducing the purchase are 'personal selling', and various 'sales promotion'. ${\bigcirc}$ 'Personal selling' at the shopping mall have an effect on the communication at bulletin board over the internet and the telephone. ${\bigcirc}$ 'Sales promotion' are attempted by 'VMD', 'deposit system', 'sale', etc.

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Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after "the Thanks to You Challenge" during the COVID-19 Pandemic (COVID-19 '덕분에 챌린지' 전후 간호사 관련 뉴스 기사의 토픽 모델링 및 키워드 네트워크 분석)

  • Yun, Eun Kyoung;Kim, Jung Ok;Byun, Hye Min;Lee, Guk Geun
    • Journal of Korean Academy of Nursing
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    • v.51 no.4
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    • pp.442-453
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    • 2021
  • Purpose: This study was conducted to assess public awareness and policy challenges faced by practicing nurses. Methods: After collecting nurse-related news articles published before and after 'the Thanks to You Challenge' campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. Results: Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics 'infection of medical staff' and 'return of overseas Koreans' disappeared, but 'the Thanks to You Challenge' emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of 'the Thanks to You Challenge' topic. Conclusion: The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.

Synthetic data augmentation for pixel-wise steel fatigue crack identification using fully convolutional networks

  • Zhai, Guanghao;Narazaki, Yasutaka;Wang, Shuo;Shajihan, Shaik Althaf V.;Spencer, Billie F. Jr.
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.237-250
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    • 2022
  • Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.