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RISS 인기검색어
- 검색키워드
- 저자 : ( Fabio Cruz ) (검색결과 3 건)
- 무료
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- 유료
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Bivariate odd-log-logistic-Weibull regression model for oral health-related quality of life
Cruz, Jose N. da,Ortega, Edwin M.M.,Cordeiro, Gauss M.,Suzuki, Adriano K.,Mialhe, Fabio L. The Korean Statistical Society 2017 Communications for statistical applications and me Vol.24 No.3
We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.
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Structure and Challenges of a Security Policy on Small and Medium Enterprises
( Fernando Almeida ),( Ines Carvalho ),( Fabio Cruz ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.2
Information Technology (IT) plays an increasingly important role for small and medium-sized enterprises. It has become fundamental for these companies to protect information and IT assets in relation to risks and threats that have grown in recent years. This study aims to understand the importance and structure of an information security policy, using a quantitative study that intends to identify the most important and least relevant elements of an information security policy document. The findings of this study reveal that the top three most important elements in the structure of a security policy are the asset management, security risk management and define the scope of the policy. On the other side, the three least relevant elements include the executive summary, contacts and manual inspection. Additionally, the study reveals that the importance given to each element of the security policy is slightly changed according to the sectors of activity. The elements that show the greatest variability are the review process, executive summary and penalties. On the other side, the purpose of the policy and the asset management present a stable importance for all sectors of activity.
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Improving classification of low-resource COVID-19 literature by using Named Entity Recognition
Lithgow-Serrano, Oscar,Cornelius, Joseph,Kanjirangat, Vani,Mendez-Cruz, Carlos-Francisco,Rinaldi, Fabio Korea Genome Organization 2021 Genomics & informatics Vol.19 No.3
Automatic document classification for highly interrelated classes is a demanding task that becomes more challenging when there is little labeled data for training. Such is the case of the coronavirus disease 2019 (COVID-19) clinical repository-a repository of classified and translated academic articles related to COVID-19 and relevant to the clinical practice-where a 3-way classification scheme is being applied to COVID-19 literature. During the 7th Biomedical Linked Annotation Hackathon (BLAH7) hackathon, we performed experiments to explore the use of named-entity-recognition (NER) to improve the classification. We processed the literature with OntoGene's Biomedical Entity Recogniser (OGER) and used the resulting identified Named Entities (NE) and their links to major biological databases as extra input features for the classifier. We compared the results with a baseline model without the OGER extracted features. In these proof-of-concept experiments, we observed a clear gain on COVID-19 literature classification. In particular, NE's origin was useful to classify document types and NE's type for clinical specialties. Due to the limitations of the small dataset, we can only conclude that our results suggests that NER would benefit this classification task. In order to accurately estimate this benefit, further experiments with a larger dataset would be needed.
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