• Title/Summary/Keyword: Bigdata project

Search Result 13, Processing Time 0.018 seconds

Technology Commercialization and Management Performance Analysis of Smart farm Venture companies (스마트팜 벤처기업의 기술사업화와 경영성과 분석)

  • Dae-Yu, Kim;Taiheoun Park;Won-Shik Na
    • Advanced Industrial SCIence
    • /
    • v.2 no.2
    • /
    • pp.25-30
    • /
    • 2023
  • The purpose of this study is to empirically analyze the impact of corporate innovation activities on corporate innovation performance using data from companies participating in the smart farm project. A company's innovation activities were divided into planning capacity, R&D capacity, and commercialization capacity, and the impact of each innovation activity on the company's sales and patent creation was estimated. The moderating effect was also analyzed. Regression analysis was conducted as a research method, and as a result of the analysis, it was found that planning capacity, R&D capacity, and commercialization capacity related to innovation within a company have an impact on corporate performance creation. appeared to be In order to increase the business performance of technology commercialization, it was confirmed that planning and R&D capabilities as well as governmental technology policy support are needed.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen

  • Jo, Hye-Yeong;Kim, Sang Cheol;Ahn, Do-hwan;Lee, Siyoung;Chang, Se-Hyun;Jung, So-Young;Kim, Young-Jin;Kim, Eugene;Kim, Jung-Eun;Kim, Yeon-Sook;Park, Woong-Yang;Cho, Nam-Hyuk;Park, Donghyun;Lee, Ju-Hee;Park, Hyun-Young
    • BMB Reports
    • /
    • v.55 no.9
    • /
    • pp.465-471
    • /
    • 2022
  • Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.

A Study on Consumer Type Data Analysis Methodology - Focusing on www.ethno-mining.com data - (소비자유형 데이터 분석방법론 연구 - www.ethno-mining.com 데이터를 중심으로 -)

  • Wookwhan, Jung;Jinho, Ahn;Joseph, Na
    • Journal of Service Research and Studies
    • /
    • v.12 no.2
    • /
    • pp.80-93
    • /
    • 2022
  • This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.