Survivability Evaluation Modeling Techniques and Measures

2009 ◽  
pp. 504-517
Author(s):  
Hai Wang
Keyword(s):  
Information Security ◽  
Evaluation Criteria ◽  
Database System ◽  
Fundamental Difference ◽  
Security Evaluation ◽  
Whole Process ◽  
Modeling Techniques ◽  
Evaluation Techniques ◽  
Intrusion Tolerant

This chapter introduces the survivability evaluation, especially on the corresponding evaluation criteria and modeling techniques. The content of this chapter includes an overview of the literature of computer system dependability or security evaluation techniques and their limitation. The concept of survivability and the techniques for modeling and evaluating survivability are introduced. In addition, the whole process of modeling and evaluating the survivability of an intrusion tolerant database system (ITDB) is shown as a case study. The discussion included in this chapter would facilitate the readers to understand the fundamental difference among reliability, availability, survivability, and related concepts. This chapter would also help information security professionals to learn the methods of measuring information security and survivability.

scholarly journals Evaluating Predictive Models of Student Success: Closing the Methodological Gap

2018 ◽  
Vol 5 (2) ◽  
pp. 105-125 ◽  
Author(s):  
Joshua Patrick Gardner ◽  
Christopher Brooks
Keyword(s):  
Predictive Model ◽  
Predictive Models ◽  
Model Evaluation ◽  
Learning Analytics ◽  
Statistical Tests ◽  
Significance Test ◽  
Large Set ◽  
Modeling Techniques ◽  
Evaluation Techniques

Model evaluation – the process of making inferences about the performance of predictive models – is a critical component of predictive model-ing research in learning analytics. In this work, we present an overview of the state-of-the-practice of model evaluation in learning analytics, which overwhelmingly uses only na ̈ıve methods for model evaluation or, less commonly, statistical tests which are not appropriate for predictive model evaluation. We then provide an overview of more appropriate methods for model evaluation, presenting both frequentist and a preferred Bayesian method. Finally, we apply three methods – the na ̈ıve average commonly used in learning analytics, frequentist null hypothesis significance test(NHST), and hierarchical Bayesian model evaluation – to a large set ofMOOC data. We compare 96 different predictive modeling techniques,including different feature sets, statistical modeling algorithms, and tuning hyperparameters for each, using this case study to demonstrate the different experimental conclusions these evaluation techniques provide.

scholarly journals Appraising psychotherapy case studies in practice-based evidence: introducing Case Study Evaluation-tool (CaSE)

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Greta Kaluzeviciute
Keyword(s):  
Case Studies ◽  
Evaluation Criteria ◽  
Internal Validity ◽  
Knowledge Generation ◽  
Evaluation Tool ◽  
Third Way ◽  
Study Evaluation ◽  
Essential Components ◽  
Randomised Controlled

AbstractSystematic case studies are often placed at the low end of evidence-based practice (EBP) due to lack of critical appraisal. This paper seeks to attend to this research gap by introducing a novel Case Study Evaluation-tool (CaSE). First, issues around knowledge generation and validity are assessed in both EBP and practice-based evidence (PBE) paradigms. Although systematic case studies are more aligned with PBE paradigm, the paper argues for a complimentary, third way approach between the two paradigms and their ‘exemplary’ methodologies: case studies and randomised controlled trials (RCTs). Second, the paper argues that all forms of research can produce ‘valid evidence’ but the validity itself needs to be assessed against each specific research method and purpose. Existing appraisal tools for qualitative research (JBI, CASP, ETQS) are shown to have limited relevance for the appraisal of systematic case studies through a comparative tool assessment. Third, the paper develops purpose-oriented evaluation criteria for systematic case studies through CaSE Checklist for Essential Components in Systematic Case Studies and CaSE Purpose-based Evaluative Framework for Systematic Case Studies. The checklist approach aids reviewers in assessing the presence or absence of essential case study components (internal validity). The framework approach aims to assess the effectiveness of each case against its set out research objectives and aims (external validity), based on different systematic case study purposes in psychotherapy. Finally, the paper demonstrates the application of the tool with a case example and notes further research trajectories for the development of CaSE tool.

scholarly journals A clarified typology of core-periphery structure in networks

2021 ◽  
Vol 7 (12) ◽  
pp. eabc9800
Author(s):  
Ryan J. Gallagher ◽  
Jean-Gabriel Young ◽  
Brooke Foucault Welles
Keyword(s):  
Dense Core ◽  
Block Model ◽  
Hub And Spoke ◽  
Block Modeling ◽  
Domain Specific ◽  
The Core ◽  
Detailed Case ◽  
Rich Diversity ◽  
Modeling Techniques

Core-periphery structure, the arrangement of a network into a dense core and sparse periphery, is a versatile descriptor of various social, biological, and technological networks. In practice, different core-periphery algorithms are often applied interchangeably despite the fact that they can yield inconsistent descriptions of core-periphery structure. For example, two of the most widely used algorithms, the k-cores decomposition and the classic two-block model of Borgatti and Everett, extract fundamentally different structures: The latter partitions a network into a binary hub-and-spoke layout, while the former divides it into a layered hierarchy. We introduce a core-periphery typology to clarify these differences, along with Bayesian stochastic block modeling techniques to classify networks in accordance with this typology. Empirically, we find a rich diversity of core-periphery structure among networks. Through a detailed case study, we demonstrate the importance of acknowledging this diversity and situating networks within the core-periphery typology when conducting domain-specific analyses.

scholarly journals Path Planning for Autonomous Ships: A Hybrid Approach Based on Improved APF and Modified VO Methods

2021 ◽  
Vol 9 (7) ◽  
pp. 761
Author(s):  
Liang Zhang ◽  
Junmin Mou ◽  
Pengfei Chen ◽  
Mengxia Li
Keyword(s):  
Path Planning ◽  
Local Minimum ◽  
Hybrid Approach ◽  
Artificial Potential Field ◽  
Whole Process ◽  
International Regulations ◽  
Local Path ◽  
Velocity Obstacle ◽  
Global And Local

In this research, a hybrid approach for path planning of autonomous ships that generates both global and local paths, respectively, is proposed. The global path is obtained via an improved artificial potential field (APF) method, which makes up for the shortcoming that the typical APF method easily falls into a local minimum. A modified velocity obstacle (VO) method that incorporates the closest point of approach (CPA) model and the International Regulations for Preventing Collisions at Sea (COLREGS), based on the typical VO method, can be used to get the local path. The contribution of this research is two-fold: (1) improvement of the typical APF and VO methods, making up for previous shortcomings, and integrated COLREGS rules and good seamanship, making the paths obtained more in line with navigation practice; (2) the research included global and local path planning, considering both the safety and maneuverability of the ship in the process of avoiding collision, and studied the whole process of avoiding collision in a relatively entirely way. A case study was then conducted to test the proposed approach in different situations. The results indicate that the proposed approach can find both global and local paths to avoid the target ship.

On the Application of the Lu-Gre Model to Simulate Joint Friction in Multi-Body Systems

2011 ◽  
Author(s):  
Kedar Gajanan Kale ◽  
Rajiv Rampalli
Keyword(s):  
Friction Model ◽  
Lugre Model ◽  
Friction Forces ◽  
Joint Friction ◽  
Modeling Techniques ◽  
Static Regime ◽  
Increasing Demand ◽  
Automotive Suspension ◽  
Multi Body

Advances in the application of multi-body simulation technology to real world problems have led to an ever increasing demand for higher fidelity modeling techniques. Of these, accurate modeling of friction is of strategic interest in applications such as control system design, automotive suspension analysis, robotics etc. Joints (sometimes referred to as constraints) play an important role in defining the dynamics of a multi-body system. Hence, it is imperative to accurately account for friction forces arising at these joints due to the underlying interface dynamics. In this paper, we discuss the application of LuGre, a dynamic friction model to simulate joint friction. We choose the LuGre model due to its ability to capture important effects such as the Stribeck effect and the Dahl effect. The native 1-d LuGre model is extended to formulate friction computations for non-trivial joint geometries and dynamics in 2 and 3 dimensions. It is also extended to work in the quasi-static regime. Specific applications to revolute, cylindrical and spherical joints in multi-body systems are discussed. Finally, an engineering case study on the effects of joint friction in automotive suspension analysis is presented.

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