• Title/Summary/Keyword: 데이터 수집 모듈

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Comparative Analysis of Growth and Development of Paddy Rice (Oryza sativa L.) by Light Intensity under Farm-type Solar Photovoltanic Power Station (추적식 영농형 태양광발전시스템 구축에 따른 음영별 하부작물 벼(Oryza sativa L.)의 생육비교)

  • Eon-Yak Kim;Ye-Jin Lee;In-Jin Kang;Hye-Min Son;Min-Ho Shin;Chang-Hyu Bae
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2022.09a
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    • pp.85-85
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    • 2022
  • 영농형 태양광발전은 태양의 일사량을 전기발전과 영농에 공유하는(solar-sharing) 방식이다. 본 연구는 신재생에너지의 활용의 극대화를 위하여 추적식 영농형 태양광발전시스템을 구축하고 시설하부에서 일정 기간 재배중인 작물의 하부 환경과 생육을 조사하여 영농형태양광 하부작물개발을 위한 기초자료를 확보하고자 하였다. 구축한 추적식 영농형 태양광발전시스템은 4열 6단의 24장 모듈(8m × 6m)을 가지며, 발전시설 중심축 기둥 간 중심간격 14m로 단일지주식 스크루 공법으로 순천대학교 부속농장 답작포(순천시 죽평리)에 설치하여 하부 환경과 하부작물의 생육을 조사하였다. 태양광발전시설 하부작물의 생육을 조사하기 위하여 순천 농협육묘장에서 벼(신동진)를 육묘하여 2022년 6월 16일 이앙하였다. 태양광발전시스템 하부 지역을 4방위 방향에 따라 강음영(중심축으로부터 1~3m), 중음영(5m), 약음영(7~9m) 구역으로 설정하여 생육을 조사한 결과, 방위에 따른 초장은 남쪽에서 음영간 차이가 상대적으로 낮게 나타났으며, 1번기 태양광 발전시설에 의하여 음영이 중첩된 2번기 시설의 동쪽에서 대조구 대비 초장이 상대적으로 낮은 경향을 나타내었다. 음영강도에 따른 초장은 대체로 강음영구에서 낮게 나타났으며, 약음영구로 갈수록 높게 나타났다. 엽수는 방위에 따라서, 그리고 음영의 강도에 따른 차이가 초장에 비하여 작게 나타났다. 출수기의 경우 방위별로는 남쪽에서 음영별 차이가 작게 나타났으며, 음영강도에 따라서 차이를 보였다. 또한 태양광시설 하부에 데이터수집장치(Model 1650, Spctrum Technonogies, USA)를 설치하여 음영에 따른 토양전도도, 토양함수량, 토양온도, par light 등 생육환경을 조사, 비교하였다.

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A Study on Differences of Contents and Tones of Arguments among Newspapers Using Text Mining Analysis (텍스트 마이닝을 활용한 신문사에 따른 내용 및 논조 차이점 분석)

  • Kam, Miah;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.53-77
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    • 2012
  • This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

  • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.67-88
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    • 2018
  • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

Exploring Twitter Follower-Networks of Startup Companies Employing Social Network Analysis and Cluster Analysis (소셜네트워크 분석과 클러스터 분석 방법을 활용한 스타트업 회사의 트위터 팔로워 네트워크에 대한 탐색적 연구)

  • Yu, Seunghee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.14 no.4
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    • pp.199-209
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    • 2019
  • The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

Investigation of Study Items for the Patterns of Care Study in the Radiotherapy of Laryngeal Cancer: Preliminary Results (후두암의 방사선치료 Patterns of Care Study를 위한 프로그램 항목 개발: 예비 결과)

  • Chung Woong-Ki;Kim I1-Han;Ahn Sung-Ja;Nam Taek-Keun;Oh Yoon-Kyeong;Song Ju-Young;Nah Byung-Sik;Chung Gyung-Ai;Kwon Hyoung-Cheol;Kim Jung-Soo;Kim Soo-Kon;Kang Jeong-Ku
    • Radiation Oncology Journal
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    • v.21 no.4
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    • pp.299-305
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    • 2003
  • Purpose: In order to develop the national guide-lines for the standardization of radiotherapy we are planning to establish a web-based, on-line data-base system for laryngeal cancer. As a first step this study was performed to accumulate the basic clinical information of laryngeal cancer and to determine the items needed for the data-base system. Materials and Methods: We analyzed the clinical data on patients who were treated under the diagnosis of laryngeal cancer from January 1998 through December 1999 In the South-west area of Korea. Eligiblity criteria of the patients are as follows: 18 years or older, currently diagnosed with primary epithelial carcinoma of larynx, and no history of previous treatments for another cancers and the other laryngeal diseases. The items were developed and filled out by radiation oncologlst who are members of forean Southwest Radiation Oncology Group. SPSS vl0.0 software was used for statistical analysis. Results: Data of forty-five patients were collected. Age distribution of patients ranged from 28 to 88 years(median, 61). Laryngeal cancer occurred predominantly In males (10 : 1 sex ratio). Twenty-eight patients (62$\%$) had primary cancers in the glottis and 17 (38$\%$) in the supraglottis. Most of them were diagnosed pathologically as squamous cell carcinoma (44/45, 98$\%$). Twenty-four of 28 glottic cancer patients (86$\%$) had AJCC (American Joint Committee on Cancer) stage I/II, but 50$\%$ (8/16) had In supraglottic cancer patients (p=0.02). Most patients(89$\%$) had the symptom of hoarseness. indirect laryngoscopy was done in all patients and direct laryngoscopy was peformed in 43 (98$\%$) patients. Twenty-one of 28 (75$\%$) glottic cancer cases and 6 of 17 (35$\%$) supraglottic cancer cases were treated with radiation alone, respectively. The combined treatment of surgery and radiation was used in 5 (18$\%$) glottic and 8 (47$\%$) supraglottic patients. Chemotherapy and radiation was used in 2 (7$\%$) glottic and 3 (18$\%$) supraglottic patients. There was no statistically significant difference in the use of combined modality treatments between glottic and supraglottic cancers (p=0.20). In all patients, 6 MV X-ray was used with conventional fractionation. The iraction size was 2 Gy In 80$\%$ of glottic cancer patients compared with 1.8 Gy in 59$\%$ of the patients with supraglottic cancers. The mean total dose delivered to primary lesions were 65.98 ey and 70.15 Gy in glottic and supraglottic patients treated, respectively, with radiation alone. Based on the collected data, 12 modules with 90 items were developed or the study of the patterns of care In laryngeal cancer. Conclusion: The study Items for laryngeal cancer were developed. In the near future, a web system will be established based on the Items Investigated, and then a nation-wide analysis on laryngeal cancer will be processed for the standardization and optimization of radlotherapy.

Evaluation of K-Cabbage Model for Yield Prediction of Chinese Cabbage in Highland Areas (고랭지 배추 생산 예측을 위한 K-배추 모델 평가)

  • Seong Eun Lee;Hyun Hee Han;Kyung Hwan Moon;Dae Hyun Kim;Byung-Hyuk Kim;Sang Gyu Lee;Hee Ju Lee;Suhyun Ryu;Hyerim Lee;Joon Yong Shim;Yong Soon Shin;Mun Il Ahn;Hee Ae Lee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.398-403
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    • 2023
  • Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R2=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.