• Title/Summary/Keyword: 기업데이터 분석

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Defect Detection and Cause Analysis for Copper Filter Dryer Quality Assurance (Copper Filter Dryer 품질보증을 위한 결함 검출 및 원인 분석)

  • SeokMin Oh;JinJe Park;Van-Quan Dao;ByungHo Jang;HeungJae Kim;ChangSoon Kim
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.1
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    • pp.107-116
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    • 2024
  • Copper Filter Dryer (CFD) are responsible for removing impurities from the circulation of refrigerant in refrigeration and cooling systems to maintain clean refrigerant, and defects in CFD can lead to product defects such as leakage and reduced lifespan in refrigeration and cooling systems, making quality assurance essential. In the quality inspection stage, human inspection and defect judgment methods are traditionally used, but these methods are subjective and inaccurate. In this paper, YOLOv7 object detection algorithm was used to detect defects occurring during the CFD Shaft pipe and welding process to replace the existing quality inspection, and the detection performance of F1-Score 0.954 and 0.895 was confirmed. In addition, the cause of defects occurring during the welding process was analyzed by analyzing the sensor data corresponding to the Timestamp of the defect image. This paper proposes a method for manufacturing quality assurance and improvement by detecting defects that occur during CFD process and analyzing their causes.

A Data Mining using Data Information Technology (데이터정보기술을 이용한 데이터 마이닝)

  • Jeon, Seong-Hae;Lee, Seung-Ju;O, Gyeong-Hwan
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.264-265
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    • 2008
  • 문제의 정의부터 데이터의 조사, 측정, 수집, 전송, 분석, 지식의 창출, 그리고 최적의 의사결정 및 피드백에 이르는 전체 과정을 다루는 데이터기술은 2000년 전,후에 제안되었다. 아직 이에 대한 폭넓은 연구는 이루어지고 있지 못하지만 기업 비즈니스를 위한 CRM 등의 경영을 위한 효과적인 데이터 마이닝 방법론에 대한 개선을 위한 중요한 역할이 기대된다. 본 논문에서는 현재 연구되고 있는 데이터기술과 정보기술의 창조적인 융합을 제안하고 이를 통하여 효과적인 데이터 마이닝의 수행방안에 대하여 연구한다.

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Predictive Modeling for the Data having Marcov property (마코프성분을 갖는 데이터셋의 예측모델링)

  • 김선철;서성보;이준욱;류근호
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.172-174
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    • 2000
  • 기업과 산업등 여러분야에 적용하기 위하여 인공지능, 통계학, 데이터베이스등의 각 분야에서 활발히 연구되고 있는 데이터마이닝은 알 수 없는 미래에 대한 예측이 가능하다는 장점을 갖기 때문에 더욱 가치가 있다. 데이터셋을 설명하기 위한 설명모델링과 예측을 하기 위한 예측모델링의 두 가지 범주로 나뉘어 발전되어왔으나, 데이터셋을 설명하기 위한 분석보다는 미래를 예측하기 위한 분석의 중요성이 점점 증가되고 있다. 이 논문에서는 마코프 성분을 갖는 과거의 이력 데이터를 기반으로 일정한 시점 또는 일정 기간동안의 변화량을 예측할 수 있는 예측모델링 방법을 제시한다.

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SME Bakery's Marketing Strategies Based on Apriori Algorithm (Apriori 알고리즘 기반의 중소 베이커리 기업의 대응 전략)

  • Kim, Do Hoon;Lee, Hyeon June;Lee, Bong Gyou
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.328-337
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    • 2022
  • The importance of online marketing is emerging due to the prevalence of COVID-19. In order to respond to the changing business environment, we have collected ten years of sales data of SME bakery company that have experienced a decrease in sales due to the COVID-19. As a result of the analysis, we found that switching from offline markets to omnichannel B2B and B2C markets and taking 'small quantity batch production' to 'mass production in a small variety can improve management. This study presented online and offline marketing strategies through data analysis of small and medium-sized bakery companies, which have relatively insufficient digital capabilities compared to large companies, and could be a guideline for many SMEs.

Effective Countermeasure to APT Attacks using Big Data (빅데이터를 이용한 APT 공격 시도에 대한 효과적인 대응 방안)

  • Mun, Hyung-Jin;Choi, Seung-Hyeon;Hwang, Yooncheol
    • Journal of Convergence Society for SMB
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    • v.6 no.1
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    • pp.17-23
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    • 2016
  • Recently, Internet services via various devices including smartphone have become available. Because of the development of ICT, numerous hacking incidents have occurred and most of those attacks turned out to be APT attacks. APT attack means an attack method by which a hacker continues to collect information to achieve his goal, and analyzes the weakness of the target and infects it with malicious code, and being hidden, leaks the data in time. In this paper, we examine the information collection method the APT attackers use to invade the target system in a short time using big data, and we suggest and evaluate the countermeasure to protect against the attack method using big data.

The Characteristics of Migration in Gangwon Innovation City and Wonju Company Town (강원혁신도시와 원주기업도시의 인구이동 특성 분석)

  • Hong, Giljong;Bae, Sunhak
    • Journal of the Economic Geographical Society of Korea
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    • v.24 no.3
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    • pp.300-312
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    • 2021
  • The purpose of this study was to compare and analyze characteristics of Gangwon Innovation City and Wonju Company Town. Both were created with similar purpose, place, time, and scale. However, they were created with different approaches: relocating public institutions and attracting private institutions. For research data, population microdata provided by the National Statistical Office were used. As a result of the analysis, the Gangwon Innovation City and the Wonju Company Town greatly influenced the population growth of Wonju and the movement of the population within Wonju. The influx of population into the study area brought positive changes in both demographic structure and population indices. Excluding relocation to Wonju-si, Innovation Cities and Company Town accounted for more than 50% of those who migrated from the metropolitan area (Seoul, Gyeonggi and Incheon). The supply of apartment houses (apartments) in the Innovation City and the Company Town stimulated the transfer from the inside of Wonju to this area. For households that moved to Gangwon Innovation City and Wonju Company Town, the most common reasons for moving in were housing, occupation, and family.

Government Financial Support and Firm Performance: A Multilevel Analysis of the Moderating Effects of Firm and Cluster Characteristics (정부 자금지원과 기업 경영성과: 기업 및 클러스터 특성의 조절효과에 관한 다수준 분석)

  • Hee Jae Kim;Myung-Ho Chung
    • Journal of Industrial Convergence
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    • v.22 no.1
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    • pp.1-20
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    • 2024
  • Regarding the discourse on the correlation between governmental financial support and firm performance, much emphasis has been placed on the role of individual corporate characteristics as well as spatial features. However, there is a notable scarcity of empirical research examining the integrated impact of corporate and cluster characteristics on managerial performance. This study addresses this gap by empirically analyzing the financial and non-financial outcomes resulting from specific allocations of governmental financial support. Additionally, it explores corporate and cluster characteristics predicted to moderate the influence between governmental financial support and firm performance. The analysis employs a two-level hierarchical linear model (HLM) at individual and group levels. The data, reorganized based on business registration numbers at the firm and cluster levels, ultimately utilized panel data from 83,395 firms and 641 clusters. The research findings indicate that governmental financial support demonstrates a positive effect (+) on both sales and patents for firms, suggesting its effectiveness in complementing market failures. Results from the hierarchical linear model analysis show that when combined with human capital capacity, absorptive capacity, and cluster network density, governmental financial support exhibits significant positive effects on sales. This study contributes theoretical and practical insights by analyzing the relationship between governmental financial support and firm performance using a two-level hierarchical linear model. It highlights the role of corporate characteristics such as human capital and absorptive capacity, along with cluster characteristics like cluster network density, in moderating the effects of governmental financial support on firm performance.

Design and Implementation of OLAP/DataMining integration Tool using XMLA (XMLA를 이용한 OLAP/데이터마이닝 통합 툴의 설계 및 구현)

  • Kim, Seong-Ju;Choi, Ji-Woong;Kim, Myung-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.11a
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    • pp.409-412
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    • 2006
  • 빠르게 변화하는 시장 및 기업 간의 경쟁 환경에서 기업의 의사결정권자들은 보다 신속한 의사결정을 내려야 하고, 의사결정의 위험을 최소화해야 하는 무거운 중책이 새롭게 추가 되었다. 이에 비즈니스 인텔리전스는 주로 고차원의 분석을 필요로 하는 시장분석가나, IT조직의 소수 멤버들을 위한 여러가지 BI툴을 제공 하였다. 과거의 비즈니스 인텔리전스 제품 가격이나 솔루션 구축에 따른 비용은 사용자가 적음에도 불구하고 만만치 않았다. 최근 들어, 환경 변화와 사용자의 요구의 다양성에 따라 기업 내의 많은 사용자들은 데이터를 분석하길 원한다. 또한 기업의 업무를 보다 원할히 진행시키기 위해 많은 의사결정이 하부조직에서 이루어지고 있으며, 그에 따라 현장 직원들에게 의사결정에 대한 책임이 부과되고 있다. 또한 BI 제품의 데이터 저장소의 기술차이에 따라 호환성이 떨어지는 플랫폼을 기반으로 보고서를 작성하였다. 이에 본 논문에서는 XMLA 웹서비스를 이용하여 다중 플랫폼을 지원하는 자바 기반의 리포팅 툴과 연동 가능한 OLAP/데이터마이닝 비즈니스 인텔리전스 툴을 제안한다. 구현 시스템은 다양한 형태로 표현 가능한 프론트엔드 툴을 제공함으로써 최종 사용자의 편의성을 제공하며 BI의 기능을 지원한다.

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A Study for Big Data Analytics Platform with Raspberry Pi Cluster and Apache Spark (라즈베리 파이 클러스터와 아파치 스파크를 활용한 빅데이터 분석 플랫폼 연구)

  • Kim, Young-Sun;Park, Ji-Young;Yoon, Bo-Ram;Lee, Jung-Hyun;Yong, Hwan-Seung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1272-1275
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    • 2015
  • 최근 관심이 증대되고 있는 빅데이터 분석 및 처리를 위한 병렬분산처리 시스템은 대용량 서버가 필요하고 인프라 구축을 위해 고비용을 지불해야 한다. 이를 해결하기 위해 본 연구에서는 저렴한 라즈베리 파이로 클러스터를 구성하고, 하둡보다 빠른 속도의 처리를 제공하는 아파치 스파크를 분석 솔루션으로 하는 빅데이터 분석 플랫폼을 구축하였다. 구축한 플랫폼이 빅데이터 활용을 위해 적절한 성능을 보이는지 확인하기 위해 텍스트 마이닝을 수행하였고, 분석 결과 유효한 성능을 보였다. 적절한 비용으로 빅데이터 분석이 가능해지면서 중소기업과 개인, 교육 기관에서도 빅데이터 활용이 가능해지면서 활용 분야가 크게 확대될 것으로 보인다.

The Validity Test of Statistical Matching Simulation Using the Data of Korea Venture Firms and Korea Innovation Survey (벤처기업정밀실태조사와 한국기업혁신조사 데이터를 활용한 통계적 매칭의 타당성 검증)

  • An, Kyungmin;Lee, Young-Chan
    • Knowledge Management Research
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    • v.24 no.1
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    • pp.245-271
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    • 2023
  • The change to the data economy requires a new analysis beyond ordinary research in the management field. Data matching refers to a technique or processing method that combines data sets collected from different samples with the same population. In this study, statistical matching was performed using random hotdeck and Mahalanobis distance functions using 2020 Survey of Korea Venture Firms and 2020 Korea Innovation Survey datas. Among the variables used for statistical matching simulation, the industry and the number of workers were set to be completely consistent, and region, business power, listed market, and sales were set as common variables. Simulation verification was confirmed by mean test and kernel density. As a result of the analysis, it was confirmed that statistical matching was appropriate because there was a difference in the average test, but a similar pattern was shown in the kernel density. This result attempted to expand the spectrum of the research method by experimenting with a data matching research methodology that has not been sufficiently attempted in the management field, and suggests implications in terms of data utilization and diversity.