• 제목/요약/키워드: Co-occurrence Networks

검색결과 56건 처리시간 0.024초

ANNs on Co-occurrence Matrices for Mobile Malware Detection

  • Xiao, Xi;Wang, Zhenlong;Li, Qi;Li, Qing;Jiang, Yong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권7호
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    • pp.2736-2754
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    • 2015
  • Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

언어 네트워크 분석 방법을 활용한 학술논문의 내용분석 (A Content Analysis of Journal Articles Using the Language Network Analysis Methods)

  • 이수상
    • 정보관리학회지
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    • 제31권4호
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    • pp.49-68
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    • 2014
  • 본 연구의 목적은 국내 학술논문 데이터베이스에서 검색한 언어 네트워크 분석 관련 53편의 국내 학술논문들을 대상으로 하는 내용분석을 통해, 언어 네트워크 분석 방법의 기초적인 체계를 파악하기 위한 것이다. 내용분석의 범주는 분석대상의 언어 텍스트 유형, 키워드 선정 방법, 동시출현관계의 파악 방법, 네트워크의 구성 방법, 네트워크 분석도구와 분석지표의 유형이다. 분석결과로 나타난 주요 특성은 다음과 같다. 첫째, 학술논문과 인터뷰 자료를 분석대상의 언어 텍스트로 많이 사용하고 있다. 둘째, 키워드는 주로 텍스트의 본문에서 추출한 단어의 출현빈도를 사용하여 선정하고 있다. 셋째, 키워드 간 관계의 파악은 거의 동시출현빈도를 사용하고 있다. 넷째, 언어 네트워크는 단수의 네트워크보다 복수의 네트워크를 구성하고 있다. 다섯째, 네트워크 분석을 위해 NetMiner, UCINET/NetDraw, NodeXL, Pajek 등을 사용하고 있다. 여섯째, 밀도, 중심성, 하위 네트워크 등 다양한 분석지표들을 사용하고 있다. 이러한 특성들은 언어 네트워크 분석 방법의 기초적인 체계를 구성하는 데 활용할 수 있을 것이다.

특허 마이닝을 이용한 국방과학기술 연결망 연구 (A Study on Networks of Defense Science and Technology using Patent Mining)

  • 김경수;조남욱
    • 품질경영학회지
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    • 제49권1호
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    • pp.97-112
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    • 2021
  • Purpose: The purpose of this paper is to analyze the technology convergence and its characteristics, focusing on the defense technologies in South Korea. Methods: Patents applied by the Agency for Defense Development (ADD) during 1979~2019 were utilized in this paper. Information Entropy analysis has been conducted on the patents to analyze the usability and potential for development. To analyze the trend of technology convergence in defense technologies, Social Network Analysis(SNA) and Association Rule Mining Analysis were applied to the co-occurrence networks of International Patent Classification (IPC) codes. Results: The results show that sensor, communication, and aviation technologies played a key role in recent development of defense science and technology. The co-occurrence network analysis also showed that the convergence has gradually enhanced over time, and the convergence between different technology sectors largely emerged, showing that the convergence has been diversified. Conclusion: By analyzing the patents of the defense technologies during the last 30 years, this study presents the comprehensive perspectives on trends and characteristics of technology convergence in defense industry. The results of this study are expected to be used as a guideline for decision making in the government's R&D policies in defence industry.

Proposal of Analysis Method for Biota Survey Data Using Co-occurrence Frequency

  • Yong-Ki Kim;Jeong-Boon Lee;Sung Je Lee;Jong-Hyun Kang
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • 제5권3호
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    • pp.76-85
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    • 2024
  • The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R2) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.

동시 출현 기반 키워드 네트워크 기법을 이용한 이동식 사다리 추락 재해 위험 요인 연관 구조 모델링 (Correlational Structure Modelling for Fall Accident Risk Factors of Portable Ladders Using Co-occurrence Keyword Networks)

  • 황종문;신성우
    • 한국안전학회지
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    • 제36권3호
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    • pp.50-59
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    • 2021
  • The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

A Study on Socio-technical System for Sustainability of the 4th Industrial Revolution: Machine Learning-based Analysis

  • Lee, Jee Young
    • International Journal of Internet, Broadcasting and Communication
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    • 제12권4호
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    • pp.204-211
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    • 2020
  • The era of the 4th industrial revolution is a complex environment in which the cyber world and the physical world are integrated and interacted. In order to successfully implement and be sustainable the 4th industrial revolution of hyper-connectivity, hyper-convergence, and hyper-intelligence, not only the technological aspects that implemented digitalization but also the social aspects must be recognized and dealt with as important. There are socio-technical systems and socio-technical systems theory as concepts that describe systems involving complex interactions between the environmental aspects of human, mechanical and tissue systems. This study confirmed how the Socio-technical System was applied in the research literature for the last 10 years through machine learning-based analysis. Eight clusters were derived by performing co-occurrence keywords network analysis, and 13 research topics were derived and analyzed by performing a structural topic model. This study provides consensus and insight on the social and technological perspectives necessary for the sustainability of the 4th industrial revolution.

연구 논문 네트워크 분석을 이용한 수소 연구 동향 (Exploration of Hydrogen Research Trends through Social Network Analysis)

  • 김혜경;최일영
    • 한국수소및신에너지학회논문집
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    • 제33권4호
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    • pp.318-329
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    • 2022
  • This study analyzed keyword networks and Author's Affiliation networks of hydrogen-related papers published in Korea Citation Index (KCI) journals from 2016 to 2020. The study investigated co-occurrence patterns of institutions over time to examine collaboration trends of hydrogen scholars. The study also conducted frequency analysis of keyword networks to identify key topics and visualized keyword networks to explore topic trends. The result showed Collaborative research between institutions has not yet been extensively expanded. However, collaboration trends were much more pronounced with local universities. Keyword network analysis exhibited continuing diversification of topics in hydrogen research of Korea. In addition centrality analysis found hydrogen research mostly deals with multi-disciplinary and complex aspects like hydrogen production, transportation, and public policy.

다문화연구의 지식구조에 관한 네트워크 분석 (The Knowledge Structure of Multicultural Research Papers in Korea)

  • 장임숙;장덕현;이수상
    • 한국도서관정보학회지
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    • 제42권4호
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    • pp.353-374
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    • 2011
  • 본 연구는 한국 다문화 지식체계의 구조를 분석하는데 목적을 두고, 2005년부터 2010년까지 발행된 등재(후보) 학술지에 수록된 다문화분야의 논문에서 저자가 부여한 키워드를 중심으로 동시단어 네트워크를 생성하고 k-core분석을 수행한다. 먼저, 2010년까지 주요 학술지에 게재된 논문들을 중심으로 한국의 다문화 연구의 현황을 살펴보고, 다문화분야의 핵심 연구주제를 추출한다. 둘째, 다문화연구가 집중적으로 생산되기 시작한 2005년부터 2010년까지의 연구 논문을 대상으로 연도별 다문화 지식구조의 변화 추이를 분석한다. 셋째, 2005년부터 2010년까지 다문화연구가 활성화된 학문분야를 중심으로 분야별 핵심 주제와 다문화 지식구조의 특성을 비교분석한다.

Benefits of procyanidins on gut microbiota in Bama minipigs and implications in replacing antibiotics

  • Zhao, Tingting;Shen, Xiaojuan;Dai, Chang;Cui, Li
    • Journal of Veterinary Science
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    • 제19권6호
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    • pp.798-807
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    • 2018
  • Several studies have reported the effect of absorption of procyanidins and their contribution to the small intestine. However, differences between dietary interventions of procyanidins and interventions via antibiotic feeding in pigs are rarely reported. Following 16S rRNA gene Illumina MiSeq sequencing, we observed that both procyanidin administration for 2 months (procyanidin-1 group) and continuous antibiotic feeding for 1 month followed by procyanidin for 1 month (procyanidin-2 group) increased the number of operational taxonomic units, as well as the Chao 1 and ACE indices, compared to those in pigs undergoing antibiotic administration for 2 months (antibiotic group). The genera Fibrobacter and Spirochaete were more abundant in the antibiotic group than in the procyanidin-1 and procyanidin-2 groups. Principal component analysis revealed clear separations among the three groups. Additionally, using the online Molecular Ecological Network Analyses pipeline, three co-occurrence networks were constructed; Lactobacillus was in a co-occurrence relationship with Trichococcus and Desulfovibrio and a co-exclusion relationship with Bacillus and Spharerochaeta. Furthermore, metabolic function analysis by phylogenetic investigation of communities by reconstruction of unobserved states demonstrated modulation of pathways involved in the metabolism of carbohydrates, amino acids, energy, and nucleotides. These data suggest that procyanidin influences the gut microbiota and the intestinal metabolic function to produce beneficial effects on metabolic homeostasis.

Automated segmentation of concrete images into microstructures: A comparative study

  • Yazdi, Mehran;Sarafrazi, Katayoon
    • Computers and Concrete
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    • 제14권3호
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    • pp.315-325
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    • 2014
  • Concrete is an important material in most of civil constructions. Many properties of concrete can be determined through analysis of concrete images. Image segmentation is the first step for the most of these analyses. An automated system for segmentation of concrete images into microstructures using texture analysis is proposed. The performance of five different classifiers has been evaluated and the results show that using an Artificial Neural Network classifier is the best choice for an automatic image segmentation of concrete.