A parsimonious SVM model selection criterion for classification of real-world data sets via an adaptive population-based algorithm

2017 ◽  
Vol 30 (11) ◽  
pp. 3421-3429 ◽  
Author(s):  
Omid Naghash Almasi ◽  
Mohammad Hassan Khooban
Keyword(s):  
Model Selection ◽  
Real World ◽  
Selection Criterion ◽  
Population Based ◽  
Data Sets ◽  
Real World Data ◽  
World Data ◽  
Svm Model ◽  
Population Based Algorithm

scholarly journals Hfinger: Malware HTTP Request Fingerprinting

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 507
Author(s):  
Piotr Białczak ◽  
Wojciech Mazurczyk
Keyword(s):  
Real World ◽  
Network Traffic ◽  
Experimental Evaluation ◽  
Data Sets ◽  
Real World Data ◽  
Malicious Software ◽  
Default Mode ◽  
World Data ◽  
Effectiveness Analysis ◽  
Http Protocol

Malicious software utilizes HTTP protocol for communication purposes, creating network traffic that is hard to identify as it blends into the traffic generated by benign applications. To this aim, fingerprinting tools have been developed to help track and identify such traffic by providing a short representation of malicious HTTP requests. However, currently existing tools do not analyze all information included in the HTTP message or analyze it insufficiently. To address these issues, we propose Hfinger, a novel malware HTTP request fingerprinting tool. It extracts information from the parts of the request such as URI, protocol information, headers, and payload, providing a concise request representation that preserves the extracted information in a form interpretable by a human analyst. For the developed solution, we have performed an extensive experimental evaluation using real-world data sets and we also compared Hfinger with the most related and popular existing tools such as FATT, Mercury, and p0f. The conducted effectiveness analysis reveals that on average only 1.85% of requests fingerprinted by Hfinger collide between malware families, what is 8–34 times lower than existing tools. Moreover, unlike these tools, in default mode, Hfinger does not introduce collisions between malware and benign applications and achieves it by increasing the number of fingerprints by at most 3 times. As a result, Hfinger can effectively track and hunt malware by providing more unique fingerprints than other standard tools.

Comparison of M2M Traffic Models Against Real World Data Sets

2018 ◽  
Author(s):  
Marco Sansoni ◽  
Giuseppe Ravagnani ◽  
Daniel Zucchetto ◽  
Chiara Pielli ◽  
Andrea Zanella ◽  
...  
Keyword(s):  
Real World ◽  
Data Sets ◽  
Real World Data ◽  
Traffic Models ◽  
World Data

Real-world cost-effectiveness of pertuzumab (P) with trastuzumab + chemo (T+Chemo) in patients (pts) with metastatic breast cancer (MBC): A population-based retrospective cohort study by the Canadian Real-world Evidence for Value in Cancer Drugs (CanREValue) collaboration.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1048-1048
Author(s):  
Wei Fang Dai ◽  
Jaclyn Marie Beca ◽  
Chenthila Nagamuthu ◽  
Ning Liu ◽  
Maureen E. Trudeau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cost Effectiveness ◽  
Incremental Cost ◽  
Real World ◽  
Retrospective Cohort ◽  
Health Technology ◽  
Population Based ◽  
Net Benefit ◽  
Real World Data ◽  
World Data

1048 Background: Addition of P to T+chemo for MBC pts has been shown to improve overall survival (OS) in a pivotal randomized trial (hazard ratio [HR] = 0.66, 95% CI: 0.52, 0.84) (Baselga et al., NEJM 2012). In Canada, the manufacturer submission to the health technology assessment agency estimated that P produced 0.64 life years gained (LYG) with an incremental cost-effectiveness ratio (ICER) of $187,376/LYG over 10 years (CADTH-pCODR, 2013). This retrospective cohort analysis aims to determine the comparative real-world population-based effectiveness and cost-effectiveness of P among MBC pts in Ontario, Canada. Methods: MBC pts were identified from the Ontario Cancer Registry and linked to the New Drug Funding Program database to identify receipt of treatment between 1/1/2008 and 3/31/2018. Cases received P-T-chemo after universal public funding of P (Nov 2013) and controls received T-chemo before. Demographic (age, socioeconomic, rurality) and clinical (comorbidities, prior adjuvant treatments, prior breast cancer surgery, prior radiation, stage at diagnosis, ER/PR status) characteristics were identified from linked admin databases balanced between cases and controls using propensity score matching. Kaplan-Meier methods and Cox regressions accounting for matched pairs were used to estimate median OS and HR. 5-year mean total costs from the public health system perspective were estimated from admin claims databases using established direct statistical methods and adjusted for censoring of both cost and effectiveness using inverse probability weighting. ICERs and 95% bootstrapped CIs were calculated, along with incremental net benefit (INB) at various willingness-to-pay values using net benefit regression. Results: We identified 1,823 MBC pts with 912 cases and 911 controls (mean age = 55 years), of which 579 pairs were matched. Cases had improved OS (HR = 0.66; 95% CI: 0.57, 0.78), with median 3.4 years, compared to controls median OS of 2.1. P provided an additional 0.63 (95% CI: 0.48 – 0.84) LYG at an incremental cost of $196,622 (95% CI: $180,774, $219,172), with a mean ICER = $312,147/LYG (95% CI: $260,752, $375,492). At threshold of $100,000/LYG, the INB was -$133,632 (95% CI: -$151,525, -$115,739) with < 1% probability of being cost-effective. Key drivers of incremental cost increase between groups included drug and cancer clinic costs. Conclusions: The addition of P to T-chemo for MBC increased survival but at significant costs. The ICER based on direct real-world data was higher than the initial economic model due to higher total costs for pts receiving P. This study demonstrated feasibility to derive ICER from person-level real-world data to inform cancer drug life-cycle health technology reassessment.

Activities for Students: As the Ball Rolls: A Quadratic Investigation Using Multiple Representations

2009 ◽  
Vol 103 (1) ◽  
pp. 62-68
Author(s):  
Kathleen Cage Mittag ◽  
Sharon Taylor
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Physical Model ◽  
Real World ◽  
Graphing Calculator ◽  
Data Sets ◽  
Real World Data ◽  
World Data ◽  
Hands On ◽  
Modeling Data

Using activities to create and collect data is not a new idea. Teachers have been incorporating real-world data into their classes since at least the advent of the graphing calculator. Plenty of data collection activities and data sets exist, and the graphing calculator has made modeling data much easier. However, the authors were in search of a better physical model for a quadratic. We wanted students to see an actual parabola take shape in real time and then explore its characteristics, but we could not find such a hands-on model.

scholarly journals Comparing ICP variants on real-world data sets

2013 ◽  
Vol 34 (3) ◽  
pp. 133-148 ◽  
Author(s):  
François Pomerleau ◽  
Francis Colas ◽  
Roland Siegwart ◽  
Stéphane Magnenat
Keyword(s):  
Real World ◽  
Data Sets ◽  
Real World Data ◽  
World Data

scholarly journals Fracture Risk Assessment With FRAX Using Real-World Data in a Population-Based Cohort From Israel

2017 ◽  
Vol 187 (1) ◽  
pp. 94-102 ◽  
Author(s):  
Inbal Goldshtein ◽  
Yariv Gerber ◽  
Sophia Ish-Shalom ◽  
Moshe Leshno
Keyword(s):  
Risk Assessment ◽  
Fracture Risk ◽  
Real World ◽  
Population Based ◽  
Fracture Risk Assessment ◽  
Real World Data ◽  
World Data

scholarly journals Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology

2021 ◽  
Author(s):  
Jochen Jankowai ◽  
Bei Wang ◽  
Ingrid Hotz
Keyword(s):  
Structural Stability ◽  
Real World ◽  
Tensor Field ◽  
Symmetric Tensor ◽  
Tensor Fields ◽  
Real World Data ◽  
World Data ◽  
Labeling Algorithm ◽  
Edge Labeling

In this work, we propose a controlled simplification strategy for degenerated points in symmetric 2D tensor fields that is based on the topological notion of robustness. Robustness measures the structural stability of the degenerate points with respect to variation in the underlying field. We consider an entire pipeline for generating a hierarchical set of degenerate points based on their robustness values. Such a pipeline includes the following steps: the stable extraction and classification of degenerate points using an edge labeling algorithm, the computation and assignment of robustness values to the degenerate points, and the construction of a simplification hierarchy. We also discuss the challenges that arise from the discretization and interpolation of real world data.

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