Variance computations for functional of absolute risk estimates.

Science.gov (United States)

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

A climatological model for risk computations incorporating site- specific dry deposition influences

International Nuclear Information System (INIS)

Droppo, J.G. Jr.

1991-07-01

A gradient-flux dry deposition module was developed for use in a climatological atmospheric transport model, the Multimedia Environmental Pollutant Assessment System (MEPAS). The atmospheric pathway model computes long-term average contaminant air concentration and surface deposition patterns surrounding a potential release site incorporating location-specific dry deposition influences. Gradient-flux formulations are used to incorporate site and regional data in the dry deposition module for this atmospheric sector-average climatological model. Application of these formulations provide an effective means of accounting for local surface roughness in deposition computations. Linkage to a risk computation module resulted in a need for separate regional and specific surface deposition computations. 13 refs., 4 figs., 2 tabs

A Research Roadmap for Computation-Based Human Reliability Analysis

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Joe, Jeffrey [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Groth, Katrina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

A Research Roadmap for Computation-Based Human Reliability Analysis

International Nuclear Information System (INIS)

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey; Smith, Curtis; Groth, Katrina

2015-01-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

Science.gov (United States)

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

A model-based risk management framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune

2002-08-15

The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

Directory of Open Access Journals (Sweden)

Ming-Chang LEE

2015-07-01

Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets.  The risk analysis and asset allocation are the key technology of banking and risk management.  The aim of this paper, build a loan portfolio optimization model based on risk analysis.  Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank.  In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm.  This paper solves the highly difficult problem by matrix operation method.  Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space.  It is easy calculation in proposed method.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

Science.gov (United States)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

Evidence-based ergonomics education: Promoting risk factor awareness among office computer workers.

Science.gov (United States)

Mani, Karthik; Provident, Ingrid; Eckel, Emily

2016-01-01

Work-related musculoskeletal disorders (WMSDs) related to computer work have become a serious public health concern. Literature revealed a positive association between computer use and WMSDs. The purpose of this evidence-based pilot project was to provide a series of evidence-based educational sessions on ergonomics to office computer workers to enhance the awareness of risk factors of WMSDs. Seventeen office computer workers who work for the National Board of Certification in Occupational Therapy volunteered for this project. Each participant completed a baseline and post-intervention ergonomics questionnaire and attended six educational sessions. The Rapid Office Strain Assessment and an ergonomics questionnaire were used for data collection. The post-intervention data revealed that 89% of participants were able to identify a greater number of risk factors and answer more questions correctly in knowledge tests of the ergonomics questionnaire. Pre- and post-intervention comparisons showed changes in work posture and behaviors (taking rest breaks, participating in exercise, adjusting workstation) of participants. The findings have implications for injury prevention in office settings and suggest that ergonomics education may yield positive knowledge and behavioral changes among computer workers.

Review on pen-and-paper-based observational methods for assessing ergonomic risk factors of computer work.

Science.gov (United States)

Rahman, Mohd Nasrull Abdol; Mohamad, Siti Shafika

2017-01-01

Computer works are associated with Musculoskeletal Disorders (MSDs). There are several methods have been developed to assess computer work risk factor related to MSDs. This review aims to give an overview of current techniques available for pen-and-paper-based observational methods in assessing ergonomic risk factors of computer work. We searched an electronic database for materials from 1992 until 2015. The selected methods were focused on computer work, pen-and-paper observational methods, office risk factors and musculoskeletal disorders. This review was developed to assess the risk factors, reliability and validity of pen-and-paper observational method associated with computer work. Two evaluators independently carried out this review. Seven observational methods used to assess exposure to office risk factor for work-related musculoskeletal disorders were identified. The risk factors involved in current techniques of pen and paper based observational tools were postures, office components, force and repetition. From the seven methods, only five methods had been tested for reliability. They were proven to be reliable and were rated as moderate to good. For the validity testing, from seven methods only four methods were tested and the results are moderate. Many observational tools already exist, but no single tool appears to cover all of the risk factors including working posture, office component, force, repetition and office environment at office workstations and computer work. Although the most important factor in developing tool is proper validation of exposure assessment techniques, the existing observational method did not test reliability and validity. Futhermore, this review could provide the researchers with ways on how to improve the pen-and-paper-based observational method for assessing ergonomic risk factors of computer work.

Computer Profiling Based Model for Investigation

OpenAIRE

Neeraj Choudhary; Nikhil Kumar Singh; Parmalik Singh

2011-01-01

Computer profiling is used for computer forensic analysis, and proposes and elaborates on a novel model for use in computer profiling, the computer profiling object model. The computer profiling object model is an information model which models a computer as objects with various attributes and inter-relationships. These together provide the information necessary for a human investigator or an automated reasoning engine to make judgments as to the probable usage and evidentiary value of a comp...

An Agent-Based Computational Model for China’s Stock Market and Stock Index Futures Market

Directory of Open Access Journals (Sweden)

Hai-Chuan Xu

2014-01-01

Full Text Available This study presents an agent-based computational cross market model for Chinese equity market structure, which includes both stocks and CSI 300 index futures. In this model, we design several stocks and one index future to simulate this structure. This model allows heterogeneous investors to make investment decisions with restrictions including wealth, market trading mechanism, and risk management. Investors’ demands and order submissions are endogenously determined. Our model successfully reproduces several key features of the Chinese financial markets including spot-futures basis distribution, bid-ask spread distribution, volatility clustering, and long memory in absolute returns. Our model can be applied in cross market risk control, market mechanism design, and arbitrage strategies analysis.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

Science.gov (United States)

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

Home-Based Risk of Falling Assessment Test Using a Closed-Loop Balance Model.

Science.gov (United States)

Ayena, Johannes C; Zaibi, Helmi; Otis, Martin J-D; Menelas, Bob-Antoine J

2016-12-01

The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.

Statistical and RBF NN models : providing forecasts and risk assessment

OpenAIRE

Marček, Milan

2009-01-01

Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...

Risk based modelling

International Nuclear Information System (INIS)

Chapman, O.J.V.; Baker, A.E.

1993-01-01

Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

Developing Computer Model-Based Assessment of Chemical Reasoning: A Feasibility Study

Science.gov (United States)

Liu, Xiufeng; Waight, Noemi; Gregorius, Roberto; Smith, Erica; Park, Mihwa

2012-01-01

This paper reports a feasibility study on developing computer model-based assessments of chemical reasoning at the high school level. Computer models are flash and NetLogo environments to make simultaneously available three domains in chemistry: macroscopic, submicroscopic, and symbolic. Students interact with computer models to answer assessment…

Prototype Biology-Based Radiation Risk Module Project

Science.gov (United States)

Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

2015-01-01

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Risk Probability Estimating Based on Clustering

DEFF Research Database (Denmark)

Chen, Yong; Jensen, Christian D.; Gray, Elizabeth

2003-01-01

of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...

Model based risk assessment - the CORAS framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

2004-04-15

Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

Science.gov (United States)

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Design Of Computer Based Test Using The Unified Modeling Language

Science.gov (United States)

Tedyyana, Agus; Danuri; Lidyawati

2017-12-01

The Admission selection of Politeknik Negeri Bengkalis through interest and talent search (PMDK), Joint Selection of admission test for state Polytechnics (SB-UMPN) and Independent (UM-Polbeng) were conducted by using paper-based Test (PBT). Paper Based Test model has some weaknesses. They are wasting too much paper, the leaking of the questios to the public, and data manipulation of the test result. This reasearch was Aimed to create a Computer-based Test (CBT) models by using Unified Modeling Language (UML) the which consists of Use Case diagrams, Activity diagram and sequence diagrams. During the designing process of the application, it is important to pay attention on the process of giving the password for the test questions before they were shown through encryption and description process. RSA cryptography algorithm was used in this process. Then, the questions shown in the questions banks were randomized by using the Fisher-Yates Shuffle method. The network architecture used in Computer Based test application was a client-server network models and Local Area Network (LAN). The result of the design was the Computer Based Test application for admission to the selection of Politeknik Negeri Bengkalis.

Quantile uncertainty and value-at-risk model risk.

Science.gov (United States)

Alexander, Carol; Sarabia, José María

2012-08-01

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

Risk assessment through drinking water pathway via uncertainty modeling of contaminant transport using soft computing

International Nuclear Information System (INIS)

Datta, D.; Ranade, A.K.; Pandey, M.; Sathyabama, N.; Kumar, Brij

2012-01-01

The basic objective of an environmental impact assessment (EIA) is to build guidelines to reduce the associated risk or mitigate the consequences of the reactor accident at its source to prevent deterministic health effects, to reduce the risk of stochastic health effects (eg. cancer and severe hereditary effects) as much as reasonable achievable by implementing protective actions in accordance with IAEA guidance (IAEA Safety Series No. 115, 1996). The measure of exposure being the basic tool to take any appropriate decisions related to risk reduction, EIA is traditionally expressed in terms of radiation exposure to the member of the public. However, models used to estimate the exposure received by the member of the public are governed by parameters some of which are deterministic with relative uncertainty and some of which are stochastic as well as imprecise (insufficient knowledge). In an admixture environment of this type, it is essential to assess the uncertainty of a model to estimate the bounds of the exposure to the public to invoke a decision during an event of nuclear or radiological emergency. With a view to this soft computing technique such as evidence theory based assessment of model parameters is addressed to compute the risk or exposure to the member of the public. The possible pathway of exposure to the member of the public in the aquatic food stream is the drinking of water. Accordingly, this paper presents the uncertainty analysis of exposure via uncertainty analysis of the contaminated water. Evidence theory finally addresses the uncertainty in terms of lower bound as belief measure and upper bound of exposure as plausibility measure. In this work EIA is presented using evidence theory. Data fusion technique is used to aggregate the knowledge on the uncertain information. Uncertainty of concentration and exposure is expressed as an interval of belief, plausibility

Algorithms for the Computation of Debris Risk

Science.gov (United States)

Matney, Mark J.

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of satellites. A number of tools have been developed in NASA’s Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA’s Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper presents an introduction to these algorithms and the assumptions upon which they are based.

Risk Based Milk Pricing Model at Dairy Farmers Level

Directory of Open Access Journals (Sweden)

W. Septiani

2017-12-01

Full Text Available The milk price from a cooperative institution to farmer does not fully cover the production cost. Though, dairy farmers encounter various risks and uncertainties in conducting their business. The highest risk in milk supply lies in the activities at the farm. This study was designed to formulate a model for calculating milk price at farmer’s level based on risk. Risks that occur on farms include the risk of cow breeding, sanitation, health care, cattle feed management, milking and milk sales. This research used the location of the farm in West Java region. There were five main stages in the preparation of this model, (1 identification and analysis of influential factors, (2 development of a conceptual model, (3 structural analysis and the amount of production costs, (4 model calculation of production cost with risk factors, and (5 risk based milk pricing model. This research built a relationship between risks on smallholder dairy farms with the production costs to be incurred by the farmers. It was also obtained the formulation of risk adjustment factor calculation for the variable costs of production in dairy cattle farm. The difference in production costs with risk and the total production cost without risk was about 8% to 10%. It could be concluded that the basic price of milk proposed based on the research was around IDR 4,250-IDR 4,350/L for 3 to 4 cows ownership. Increasing farmer income was expected to be obtained by entering the value of this risk in the calculation of production costs. 

Computational-Model-Based Analysis of Context Effects on Harmonic Expectancy.

Science.gov (United States)

Morimoto, Satoshi; Remijn, Gerard B; Nakajima, Yoshitaka

2016-01-01

Expectancy for an upcoming musical chord, harmonic expectancy, is supposedly based on automatic activation of tonal knowledge. Since previous studies implicitly relied on interpretations based on Western music theory, the underlying computational processes involved in harmonic expectancy and how it relates to tonality need further clarification. In particular, short chord sequences which cannot lead to unique keys are difficult to interpret in music theory. In this study, we examined effects of preceding chords on harmonic expectancy from a computational perspective, using stochastic modeling. We conducted a behavioral experiment, in which participants listened to short chord sequences and evaluated the subjective relatedness of the last chord to the preceding ones. Based on these judgments, we built stochastic models of the computational process underlying harmonic expectancy. Following this, we compared the explanatory power of the models. Our results imply that, even when listening to short chord sequences, internally constructed and updated tonal assumptions determine the expectancy of the upcoming chord.

Towards Modeling False Memory With Computational Knowledge Bases.

Science.gov (United States)

Li, Justin; Kohanyi, Emma

2017-01-01

One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

Science.gov (United States)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

Algorithms for the Computation of Debris Risks

Science.gov (United States)

Matney, Mark

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of non-spherical satellites. A number of tools have been developed in NASA's Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA's Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper will present an introduction to these algorithms and the assumptions upon which they are based.

Primary care physicians’ perspectives on computer-based health risk assessment tools for chronic diseases: a mixed methods study

Directory of Open Access Journals (Sweden)

Teja Voruganti

2015-09-01

Full Text Available Background Health risk assessment tools compute an individual’s risk of developing a disease. Routine use of such tools by primary care physicians (PCPs is potentially useful in chronic disease prevention. We sought physicians’ awareness and perceptions of the usefulness, usability and feasibility of performing assessments with computer-based risk assessment tools in primary care settings.Methods Focus groups and usability testing with a computer-based risk assessment tool were conducted with PCPs from both university-affiliated and community-based practices. Analysis was derived from grounded theory methodology.Results PCPs (n = 30 were aware of several risk assessment tools although only select tools were used routinely. The decision to use a tool depended on how use impacted practice workflow and whether the tool had credibility. Participants felt that embedding tools in the electronic medical records (EMRs system might allow for health information from the medical record to auto-populate into the tool. User comprehension of risk could also be improved with computer-based interfaces that present risk in different formats.Conclusions In this study, PCPs chose to use certain tools more regularly because of usability and credibility. Despite there being differences in the particular tools a clinical practice used, there was general appreciation for the usefulness of tools for different clinical situations. Participants characterised particular features of an ideal tool, feeling strongly that embedding risk assessment tools in the EMR would maximise accessibility and use of the tool for chronic disease management. However, appropriate practice workflow integration and features that facilitate patient understanding at point-of-care are also essential. 

Computational Modeling of Space Physiology

Science.gov (United States)

Lewandowski, Beth E.; Griffin, Devon W.

2016-01-01

The Digital Astronaut Project (DAP), within NASAs Human Research Program, develops and implements computational modeling for use in the mitigation of human health and performance risks associated with long duration spaceflight. Over the past decade, DAP developed models to provide insights into space flight related changes to the central nervous system, cardiovascular system and the musculoskeletal system. Examples of the models and their applications include biomechanical models applied to advanced exercise device development, bone fracture risk quantification for mission planning, accident investigation, bone health standards development, and occupant protection. The International Space Station (ISS), in its role as a testing ground for long duration spaceflight, has been an important platform for obtaining human spaceflight data. DAP has used preflight, in-flight and post-flight data from short and long duration astronauts for computational model development and validation. Examples include preflight and post-flight bone mineral density data, muscle cross-sectional area, and muscle strength measurements. Results from computational modeling supplement space physiology research by informing experimental design. Using these computational models, DAP personnel can easily identify both important factors associated with a phenomenon and areas where data are lacking. This presentation will provide examples of DAP computational models, the data used in model development and validation, and applications of the model.

Computational neural network regression model for Host based Intrusion Detection System

Directory of Open Access Journals (Sweden)

Sunil Kumar Gautam

2016-09-01

Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

Task-and-role-based access-control model for computational grid

Institute of Scientific and Technical Information of China (English)

LONG Tao; HONG Fan; WU Chi; SUN Ling-li

2007-01-01

Access control in a grid environment is a challenging issue because the heterogeneous nature and independent administration of geographically dispersed resources in grid require access control to use fine-grained policies. We established a task-and-role-based access-control model for computational grid (CG-TRBAC model), integrating the concepts of role-based access control (RBAC) and task-based access control (TBAC). In this model, condition restrictions are defined and concepts specifically tailored to Workflow Management System are simplified or omitted so that role assignment and security administration fit computational grid better than traditional models; permissions are mutable with the task status and system variables, and can be dynamically controlled. The CG-TRBAC model is proved flexible and extendible. It can implement different control policies. It embodies the security principle of least privilege and executes active dynamic authorization. A task attribute can be extended to satisfy different requirements in a real grid system.

LIFETIME LUNG CANCER RISKS ASSOCIATED WITH INDOOR RADON EXPOSURE BASED ON VARIOUS RADON RISK MODELS FOR CANADIAN POPULATION.

Science.gov (United States)

Chen, Jing

2017-04-01

This study calculates and compares the lifetime lung cancer risks associated with indoor radon exposure based on well-known risk models in the literature; two risk models are from joint studies among miners and the other three models were developed from pooling studies on residential radon exposure from China, Europe and North America respectively. The aim of this article is to make clear that the various models are mathematical descriptions of epidemiologically observed real risks in different environmental settings. The risk from exposure to indoor radon is real and it is normal that variations could exist among different risk models even when they were applied to the same dataset. The results show that lifetime risk estimates vary significantly between the various risk models considered here: the model based on the European residential data provides the lowest risk estimates, while models based on the European miners and Chinese residential pooling with complete dosimetry give the highest values. The lifetime risk estimates based on the EPA/BEIR-VI model lie within this range and agree reasonably well with the averages of risk estimates from the five risk models considered in this study. © Crown copyright 2016.

Intrusion detection in cloud computing based attack patterns and risk assessment

Directory of Open Access Journals (Sweden)

Ben Charhi Youssef

2017-05-01

Full Text Available This paper is an extension of work originally presented in SYSCO CONF.We extend our previous work by presenting the initial results of the implementation of intrusion detection based on risk assessment on cloud computing. The idea focuses on a novel approach for detecting cyber-attacks on the cloud environment by analyzing attacks pattern using risk assessment methodologies. The aim of our solution is to combine evidences obtained from Intrusion Detection Systems (IDS deployed in a cloud with risk assessment related to each attack pattern. Our approach presents a new qualitative solution for analyzing each symptom, indicator and vulnerability analyzing impact and likelihood of distributed and multi-steps attacks directed to cloud environments. The implementation of this approach will reduce the number of false alerts and will improve the performance of the IDS.

Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Zhaosheng Yang

2014-01-01

Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

A Reputation-Based Identity Management Model for Cloud Computing

Directory of Open Access Journals (Sweden)

Lifa Wu

2015-01-01

Full Text Available In the field of cloud computing, most research on identity management has concentrated on protecting user data. However, users typically leave a trail when they access cloud services, and the resulting user traceability can potentially lead to the leakage of sensitive user information. Meanwhile, malicious users can do harm to cloud providers through the use of pseudonyms. To solve these problems, we introduce a reputation mechanism and design a reputation-based identity management model for cloud computing. In the model, pseudonyms are generated based on a reputation signature so as to guarantee the untraceability of pseudonyms, and a mechanism that calculates user reputation is proposed, which helps cloud service providers to identify malicious users. Analysis verifies that the model can ensure that users access cloud services anonymously and that cloud providers assess the credibility of users effectively without violating user privacy.

Computer code for general analysis of radon risks (GARR)

International Nuclear Information System (INIS)

Ginevan, M.

1984-09-01

This document presents a computer model for general analysis of radon risks that allow the user to specify a large number of possible models with a small number of simple commands. The model is written in a version of BASIC which conforms closely to the American National Standards Institute (ANSI) definition for minimal BASIC and thus is readily modified for use on a wide variety of computers and, in particular, microcomputers. Model capabilities include generation of single-year life tables from 5-year abridged data, calculation of multiple-decrement life tables for lung cancer for the general population, smokers, and nonsmokers, and a cohort lung cancer risk calculation that allows specification of level and duration of radon exposure, the form of the risk model, and the specific population assumed at risk. 36 references, 8 figures, 7 tables

Contribution to modeling and dynamic risk hedging in energy markets

International Nuclear Information System (INIS)

Noufel, Frikha

2010-12-01

This thesis is concerned with probabilistic numerical problems about modeling, risk control and risk hedging motivated by applications to energy markets. The main tool is based on stochastic approximation and simulation methods. This thesis consists of three parts. The first one is devoted to the computation of two risk measures of the portfolio loss distribution L: the Value-at-Risk (VaR) and the Conditional Value-at-Risk (CVaR). This computation uses a stochastic algorithm combined with an adaptive variance reduction technique. The first part of this chapter deals with the finite dimensional case, the second part extends the results of the first part to the case of a path-dependency process and the last one deals low discrepancy sequences. The second chapter is devoted with risk minimizing hedging strategies in an incomplete market operating in discrete time using quantization based stochastic approximation. Theoretical results on CVaR hedging are presented then numerical aspects are addressed in a Markovian framework. The last part deals with joint modeling of Gas and Electricity spot prices. The multi-factor model presented is based on stationary Ornstein process with parameterized diffusion coefficient. (author)

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

Science.gov (United States)

Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

2016-02-01

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Case studies: Risk-based analysis of technical specifications

International Nuclear Information System (INIS)

Wagner, D.P.; Minton, L.A.; Gaertner, J.P.

1987-01-01

The SOCRATES computer program uses the results of a Probabilistic Risk Assessment (PRA) or a system level risk analysis to calculate changes in risk due to changes in the surveillance test interval and/or the allowed outage time stated in the technical specification. The computer program can accommodate various testing strategies (such as staggered or simultaneous testing) to allow modeling of component testing as it is carried out at a plant. The methods and computer program are an integral part of a larger decision process aimed at determining benefits from technical specification changes. These benefits can include cost savings to the utilities by reducing forced shutdowns with no adverse impacts on risk. Three summaries of case study applications are included to demonstrate the types of results that can be achieved through risk-based evaluation of technical specifications. (orig.)

An agent-based computational model for tuberculosis spreading on age-structured populations

Science.gov (United States)

Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

2015-06-01

In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

Coronary risk assessment by point-based vs. equation-based Framingham models: significant implications for clinical care.

Science.gov (United States)

Gordon, William J; Polansky, Jesse M; Boscardin, W John; Fung, Kathy Z; Steinman, Michael A

2010-11-01

US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version. We assessed 2,543 subjects age 20-79 from the 2001-2006 National Health and Nutrition Examination Surveys (NHANES) for whom Adult Treatment Panel III (ATP-III) guidelines recommend formal risk stratification. For each subject, we calculated the 10-year risk of major coronary events using the original and point-based Framingham models, and then compared differences in these risk estimates and whether these differences would place subjects into different ATP-III risk groups (20% risk). Using standard procedures, all analyses were adjusted for survey weights, clustering, and stratification to make our results nationally representative. Among 39 million eligible adults, the original Framingham model categorized 71% of subjects as having "moderate" risk (20%) risk. Estimates of coronary risk by the original and point-based models often differed substantially. The point-based system classified 15% of adults (5.7 million) into different risk groups than the original model, with 10% (3.9 million) misclassified into higher risk groups and 5% (1.8 million) into lower risk groups, for a net impact of classifying 2.1 million adults into higher risk groups. These risk group misclassifications would impact guideline-recommended drug treatment strategies for 25-46% of affected subjects. Patterns of misclassifications varied significantly by gender, age, and underlying CHD risk. Compared to the original Framingham model, the point-based version misclassifies millions of Americans into risk groups for which guidelines recommend different treatment strategies.

Risk-based technical specifications: Development and application of an approach to the generation of a plant specific real-time risk model

International Nuclear Information System (INIS)

Puglia, B.; Gallagher, D.; Amico, P.; Atefi, B.

1992-10-01

This report describes a process developed to convert an existing PRA into a model amenable to real time, risk-based technical specification calculations. In earlier studies (culminating in NUREG/CR-5742), several risk-based approaches to technical specification were evaluated. A real-time approach using a plant specific PRA capable of modeling plant configurations as they change was identified as the most comprehensive approach to control plant risk. A master fault tree logic model representative of-all of the core damage sequences was developed. Portions of the system fault trees were modularized and supercomponents comprised of component failures with similar effects were developed to reduce the size of the model and, quantification times. Modifications to the master fault tree logic were made to properly model the effect of maintenance and recovery actions. Fault trees representing several actuation systems not modeled in detail in the existing PRA were added to the master fault tree logic. This process was applied to the Surry NUREG-1150 Level 1 PRA. The master logic mode was confirmed. The model was then used to evaluate frequency associated with several plant configurations using the IRRAS code. For all cases analyzed computational time was less than three minutes. This document Volume 2, contains appendices A, B, and C. These provide, respectively: Surry Technical Specifications Model Database, Surry Technical Specifications Model, and a list of supercomponents used in the Surry Technical Specifications Model

The extended RBAC model based on grid computing

Institute of Scientific and Technical Information of China (English)

CHEN Jian-gang; WANG Ru-chuan; WANG Hai-yan

2006-01-01

This article proposes the extended role-based access control (RBAC) model for solving dynamic and multidomain problems in grid computing, The formulated description of the model has been provided. The introduction of context and the mapping relations of context-to-role and context-to-permission help the model adapt to dynamic property in grid environment.The multidomain role inheritance relation by the authorization agent service realizes the multidomain authorization amongst the autonomy domain. A function has been proposed for solving the role inheritance conflict during the establishment of the multidomain role inheritance relation.

Multi-objective reverse logistics model for integrated computer waste management.

Science.gov (United States)

Ahluwalia, Poonam Khanijo; Nema, Arvind K

2006-12-01

This study aimed to address the issues involved in the planning and design of a computer waste management system in an integrated manner. A decision-support tool is presented for selecting an optimum configuration of computer waste management facilities (segregation, storage, treatment/processing, reuse/recycle and disposal) and allocation of waste to these facilities. The model is based on an integer linear programming method with the objectives of minimizing environmental risk as well as cost. The issue of uncertainty in the estimated waste quantities from multiple sources is addressed using the Monte Carlo simulation technique. An illustrated example of computer waste management in Delhi, India is presented to demonstrate the usefulness of the proposed model and to study tradeoffs between cost and risk. The results of the example problem show that it is possible to reduce the environmental risk significantly by a marginal increase in the available cost. The proposed model can serve as a powerful tool to address the environmental problems associated with exponentially growing quantities of computer waste which are presently being managed using rudimentary methods of reuse, recovery and disposal by various small-scale vendors.

A novel polar-based human face recognition computational model

Directory of Open Access Journals (Sweden)

Y. Zana

2009-07-01

Full Text Available Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Canadian population risk of radon induced lung cancer variation range assessment based on various radon risk models

International Nuclear Information System (INIS)

Chen, Jing

2017-01-01

To address public concerns regarding radon risk and variations in risk estimates based on various risk models available in the literature, lifetime lung cancer risks were calculated with five well-known risk models using more recent Canadian vital statistics (5-year averages from 2008 to 2012). Variations in population risk estimation among various models were assessed. The results showed that the Canadian population risk of radon induced lung cancer can vary from 5.0 to 17% for men and 5.1 to 18% for women based on different radon risk models. Averaged over the estimates from various risk models with better radon dosimetry, 13% of lung cancer deaths among Canadian males and 14% of lung cancer deaths among Canadian females were attributable to long-term indoor radon exposure. (authors)

A Cloud Theory-Based Trust Computing Model in Social Networks

Directory of Open Access Journals (Sweden)

Fengming Liu

2016-12-01

Full Text Available How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node’s comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved.

Stochastic Watershed Models for Risk Based Decision Making

Science.gov (United States)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

RAFT: a computer program for fault tree risk calculations

International Nuclear Information System (INIS)

Seybold, G.D.

1977-11-01

A description and user instructions are presented for RAFT, a FORTRAN computer code for calculation of a risk measure for fault tree cut sets. RAFT calculates release quantities and a risk measure based on the product of probability and release quantity for cut sets of fault trees modeling the accidental release of radioactive material from a nuclear fuel cycle facility. Cut sets and their probabilities are supplied as input to RAFT from an external fault tree analysis code. Using the total inventory available of radioactive material, along with release fractions for each event in a cut set, the release terms are calculated for each cut set. Each release term is multiplied by the cut set probability to yield the cut set risk measure. RAFT orders the dominant cut sets on the risk measure. The total risk measure of processed cut sets and their fractional contributions are supplied as output. Input options are available to eliminate redundant cut sets, apply threshold values on cut set probability and risk, and control the total number of cut sets output. Hash addressing is used to remove redundant cut sets from the analysis. Computer hardware and software restrictions are given along with a sample problem and cross-reference table of the code. Except for the use of file management utilities, RAFT is written exclusively in FORTRAN language and is operational on a Control Data, CYBER 74-18--series computer system. 4 figures

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

Science.gov (United States)

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

Model based climate information on drought risk in Africa

Science.gov (United States)

Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

2012-04-01

The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

Computer-Aided Modeling Framework

DEFF Research Database (Denmark)

Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

Models are playing important roles in design and analysis of chemicals based products and the processes that manufacture them. Computer-aided methods and tools have the potential to reduce the number of experiments, which can be expensive and time consuming, and there is a benefit of working...... development and application. The proposed work is a part of the project for development of methods and tools that will allow systematic generation, analysis and solution of models for various objectives. It will use the computer-aided modeling framework that is based on a modeling methodology, which combines....... In this contribution, the concept of template-based modeling is presented and application is highlighted for the specific case of catalytic membrane fixed bed models. The modeling template is integrated in a generic computer-aided modeling framework. Furthermore, modeling templates enable the idea of model reuse...

The Comparison of Inductive Reasoning under Risk Conditions between Chinese and Japanese Based on Computational Models: Toward the Application to CAE for Foreign Language

Science.gov (United States)

Zhang, Yujie; Terai, Asuka; Nakagawa, Masanori

2013-01-01

Inductive reasoning under risk conditions is an important thinking process not only for sciences but also in our daily life. From this viewpoint, it is very useful for language learning to construct computational models of inductive reasoning which realize the CAE for foreign languages. This study proposes the comparison of inductive reasoning…

Efficient computation of the joint probability of multiple inherited risk alleles from pedigree data.

Science.gov (United States)

Madsen, Thomas; Braun, Danielle; Peng, Gang; Parmigiani, Giovanni; Trippa, Lorenzo

2018-06-25

The Elston-Stewart peeling algorithm enables estimation of an individual's probability of harboring germline risk alleles based on pedigree data, and serves as the computational backbone of important genetic counseling tools. However, it remains limited to the analysis of risk alleles at a small number of genetic loci because its computing time grows exponentially with the number of loci considered. We propose a novel, approximate version of this algorithm, dubbed the peeling and paring algorithm, which scales polynomially in the number of loci. This allows extending peeling-based models to include many genetic loci. The algorithm creates a trade-off between accuracy and speed, and allows the user to control this trade-off. We provide exact bounds on the approximation error and evaluate it in realistic simulations. Results show that the loss of accuracy due to the approximation is negligible in important applications. This algorithm will improve genetic counseling tools by increasing the number of pathogenic risk alleles that can be addressed. To illustrate we create an extended five genes version of BRCAPRO, a widely used model for estimating the carrier probabilities of BRCA1 and BRCA2 risk alleles and assess its computational properties. © 2018 WILEY PERIODICALS, INC.

The use of biologically based cancer risk models in radiation epidemiology

International Nuclear Information System (INIS)

Krewski, D.; Zielinski, J.M.; Hazelton, W.D.; Garner, M.J.; Moolgavkar, S.H.

2003-01-01

Biologically based risk projection models for radiation carcinogenesis seek to describe the fundamental biological processes involved in neoplastic transformation of somatic cells into malignant cancer cells. A validated biologically based model, whose parameters have a direct biological interpretation, can also be used to extrapolate cancer risks to different exposure conditions with some confidence. In this article, biologically based models for radiation carcinogenesis, including the two-stage clonal expansion (TSCE) model and its extensions, are reviewed. The biological and mathematical bases for such models are described, and the implications of key model parameters for cancer risk assessment examined. Specific applications of versions of the TSCE model to important epidemiologic datasets are discussed, including the Colorado uranium miners' cohort; a cohort of Chinese tin miners; the lifespan cohort of atomic bomb survivors in Hiroshima and Nagasaki; and a cohort of over 200,000 workers included in the National Dose Registry (NDR) of Canada. (author)

Risk in the Clouds?: Security Issues Facing Government Use of Cloud Computing

Science.gov (United States)

Wyld, David C.

Cloud computing is poised to become one of the most important and fundamental shifts in how computing is consumed and used. Forecasts show that government will play a lead role in adopting cloud computing - for data storage, applications, and processing power, as IT executives seek to maximize their returns on limited procurement budgets in these challenging economic times. After an overview of the cloud computing concept, this article explores the security issues facing public sector use of cloud computing and looks to the risk and benefits of shifting to cloud-based models. It concludes with an analysis of the challenges that lie ahead for government use of cloud resources.

Towards computer-based perception by modeling visual perception : A probalistic theory

NARCIS (Netherlands)

Ciftcioglu, O.; Bittermann, M.; Sariyildiz, S.

2006-01-01

Studies on computer-based perception by vision modelling are described. The visual perception is mathematically modelled where the model receives and interprets visual data from the environment. The perception is defined in probabilistic terms so that it is in the same way quantified. Human visual

Computational framework for risk-based planning of inspections, maintenance, and condition monitoring using discrete Bayesian networks

DEFF Research Database (Denmark)

Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard

2018-01-01

This paper presents a computational framework for risk-based planning of inspections and repairs for deteriorating components. Two distinct types of decision rules are used to model decisions: simple decision rules that depend on constants or observed variables (e.g. inspection outcome...... expecte d life-cycle costs. For advanced decision rules, simulations are performed to estimate the expected costs, and dBNs are used within the simulations for decision-making. Information from inspections and condition monitoring are included if available. An example in the paper demonstrates...... the framework and the implemented strategies and decision rules, including various types of condition-based maintenance. The strategies using advanced decision rules lead to reduced costs compared to the simple decision rules when condition monitoring is applied, and the value of condition monitoring...

Validation of the What Matters Index: A brief, patient-reported index that guides care for chronic conditions and can substitute for computer-generated risk models.

Science.gov (United States)

Wasson, John H; Ho, Lynn; Soloway, Laura; Moore, L Gordon

2018-01-01

Current health care delivery relies on complex, computer-generated risk models constructed from insurance claims and medical record data. However, these models produce inaccurate predictions of risk levels for individual patients, do not explicitly guide care, and undermine health management investments in many patients at lesser risk. Therefore, this study prospectively validates a concise patient-reported risk assessment that addresses these inadequacies of computer-generated risk models. Five measures with well-documented impacts on the use of health services are summed to create a "What Matters Index." These measures are: 1) insufficient confidence to self-manage health problems, 2) pain, 3) bothersome emotions, 4) polypharmacy, and 5) adverse medication effects. We compare the sensitivity and predictive values of this index with two representative risk models in a population of 8619 Medicaid recipients. The patient-reported "What Matters Index" and the conventional risk models are found to exhibit similar sensitivities and predictive values for subsequent hospital or emergency room use. The "What Matters Index" is also reliable: akin to its performance during development, for patients with index scores of 1, 2, and ≥3, the odds ratios (with 95% confidence intervals) for subsequent hospitalization within 1 year, relative to patients with a score of 0, are 1.3 (1.1-1.6), 2.0 (1.6-2.4), and 3.4 (2.9-4.0), respectively; for emergency room use, the corresponding odds ratios are 1.3 (1.1-1.4), 1.9 (1.6-2.1), and 2.9 (2.6-3.3). Similar findings were replicated among smaller populations of 1061 mostly older patients from nine private practices and 4428 Medicaid patients without chronic conditions. In contrast to complex computer-generated risk models, the brief patient-reported "What Matters Index" immediately and unambiguously identifies fundamental, remediable needs for each patient and more sensibly directs the delivery of services to patient categories based on

An u-Service Model Based on a Smart Phone for Urban Computing Environments

Science.gov (United States)

Cho, Yongyun; Yoe, Hyun

In urban computing environments, all of services should be based on the interaction between humans and environments around them, which frequently and ordinarily in home and office. This paper propose an u-service model based on a smart phone for urban computing environments. The suggested service model includes a context-aware and personalized service scenario development environment that can instantly describe user's u-service demand or situation information with smart devices. To do this, the architecture of the suggested service model consists of a graphical service editing environment for smart devices, an u-service platform, and an infrastructure with sensors and WSN/USN. The graphic editor expresses contexts as execution conditions of a new service through a context model based on ontology. The service platform deals with the service scenario according to contexts. With the suggested service model, an user in urban computing environments can quickly and easily make u-service or new service using smart devices.

Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.

Science.gov (United States)

Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Karwoski, Ronald A; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A; Bartholmai, Brian J; Peikert, Tobias

2015-09-15

Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.

A Dynamic Object Behavior Model and Implementation Based on Computational Reflection

Institute of Scientific and Technical Information of China (English)

HE Cheng-wan; HE Fei; HE Ke-qing

2005-01-01

A dynamic object behavior model based on computational reflection is proposed. This model consists of function level and meta level, the meta objects in meta level manage the base objects and behaviors in function level, including dynamic binding and unbinding of base object and behavior.We implement this model with RoleJava Language, which is our self linguistic extension of the Java Language. Meta Objects are generated automatically at compile-time, this makes the reflecton mechanism transparent to programmers. Finally an example applying this model to a banking system is presented.

Reinforcement of qualitative risk assessment proposals from computer science

International Nuclear Information System (INIS)

Friedlhuber, T.; Hibti, M.; Rauzy, A.

2013-01-01

During the last decade a lot of research has been made to evaluate concepts and methos of quantitative risk assessment in order to predict hazards more precisely. Nevertheless, the occurrence of new catastrophes like the Indonesian Tsunami in 2004, the Deepwater Horizon accident in 2010 or recently the Fukushima accidents in 2011 raise the question whether we may underestimate some natural limits of annotative risk assessment or even mistake its significance. Especially in the case of very unlikely events, in combination with uncertainty and severe consequences, may be we would do better to concentrate more on understanding risk than on calculating probability values. In this paper we apply progresses, made in the field of computer science, to tools and modelling concepts used in risk assessment. Regarding computer science, we point out now concepts, that may improve the quality of risk models and the process of model engineering. The goal is to reinforce the importance of qualitative risk assessment with the help of sophisticated tools and modelling. Qualitative risk assessment aims to understand risk and therefore reflects the initial idea of risk assessment. Risk understanding requires understanding systems and relations of components. It is fundamental to comprehend the meaning of components in fault- and event trees, to retrace all applied modifications and to highlight critical aspects. It is important how PSA models are visualized, documented, navigated, how results are presented and how model maintenance, integration and version control are performed. Also, the conjoint usage of different type of models (for example PSA models together with event sequence diagrams) can contribute to quality assurance. We present new concepts for various kind of problems. (author)

A Two-Account Life Insurance Model for Scenario-Based Valuation Including Event Risk

Directory of Open Access Journals (Sweden)

Ninna Reitzel Jensen

2015-06-01

Full Text Available Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, such as death, disability, etc. In our treatment of participating life insurance, we have special focus on the bonus schemes “consolidation” and “additional benefits”, and one goal is to formalize how these work and interact. Another goal is to describe similarities and differences between participating life insurance and unit-linked insurance. By use of a two-account model, we are able to illustrate general concepts without making the model too abstract. To allow for complicated financial markets without dramatically increasing the mathematical complexity, we focus on economic scenarios. We illustrate the use of our model by conducting scenario analysis based on Monte Carlo simulation, but the model applies to scenarios in general and to worst-case and best-estimate scenarios in particular. In addition to easy computations, our model offers a common framework for the valuation of life insurance payments across product types. This enables comparison of participating life insurance products and unit-linked insurance products, thus building a bridge between the two different ways of formalizing life insurance products. Finally, our model distinguishes itself from the existing literature by taking into account the Markov model for the state of the policyholder and, hereby, facilitating event risk.

An Agent-Based Model of Evolving Community Flood Risk.

Science.gov (United States)

Tonn, Gina L; Guikema, Seth D

2017-11-17

Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

Automated procedure for performing computer security risk analysis

International Nuclear Information System (INIS)

Smith, S.T.; Lim, J.J.

1984-05-01

Computers, the invisible backbone of nuclear safeguards, monitor and control plant operations and support many materials accounting systems. Our automated procedure to assess computer security effectiveness differs from traditional risk analysis methods. The system is modeled as an interactive questionnaire, fully automated on a portable microcomputer. A set of modular event trees links the questionnaire to the risk assessment. Qualitative scores are obtained for target vulnerability, and qualitative impact measures are evaluated for a spectrum of threat-target pairs. These are then combined by a linguistic algebra to provide an accurate and meaningful risk measure. 12 references, 7 figures

Computational Model-Based Design of Leadership Support Based on Situational Leadership Theory

NARCIS (Netherlands)

Bosse, T.; Duell, R.; Memon, Z.A.; Treur, J.; van der Wal, C.N.

2017-01-01

This paper introduces the design of an agent-based leadership support system exploiting a computational model for development of individuals or groups. It is to be used, for example, as a basis for systems to support a group leader in the development of individual group members or a group as a

Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation

DEFF Research Database (Denmark)

Saari, Pasi; Fazekas, György; Eerola, Tuomas

2016-01-01

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are prop......This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling...... related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outperforms a semantic computing technique that does not exploit genre information, and ACTwg-SLPwg outperforms conventional techniques and other genre-adaptive alternatives. In particular, improvements......-based genre representation for genre-adaptive music mood analysis....

Pilot Study of a Computer-Based Parental Questionnaire and Visual Profile of Obesity Risk in Healthy Preschoolers.

Science.gov (United States)

Davies, Marilyn A; Terhorst, Lauren; Zhang, Peng; Nakonechny, Amanda J; Nowalk, Mary Patricia

2015-01-01

This group field-tested a computer-based, parental questionnaire entitled the Childhood Obesity Risk Questionnaire 2-5 (CORQ 2-5) designed to assess obesity risk in healthy preschoolers. COR 2-5 generates a profile of seven obesity risk factors. Field studies provided good internal reliability data and evidence of discriminant validity for the CORQ 2-5. Pediatric nurse clinicians found the CORQ 2-5 profile to be clinically relevant. The CORQ 2-5 is a promising measure of obesity risk in preschoolers who attend community-based health centers for their wellchild visits and who are not yet obese. CORQ 2-5 is intended to guide provider-parental obesity risk discussions. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

Science.gov (United States)

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

Can Dictionary-based Computational Models Outperform the Best Linear Ones?

Czech Academy of Sciences Publication Activity Database

Gnecco, G.; Kůrková, Věra; Sanguineti, M.

2011-01-01

Roč. 24, č. 8 (2011), s. 881-887 ISSN 0893-6080 R&D Project s: GA MŠk OC10047 Grant - others:CNR - AV ČR project 2010-2012(XE) Complexity of Neural-Network and Kernel Computational Models Institutional research plan: CEZ:AV0Z10300504 Keywords : dictionary-based approximation * linear approximation * rates of approximation * worst-case error * Kolmogorov width * perceptron networks Subject RIV: IN - Informatics, Computer Science Impact factor: 2.182, year: 2011

Environmental modeling and health risk analysis (ACTS/RISK)

National Research Council Canada - National Science Library

Aral, M. M

2010-01-01

... presents a review of the topics of exposure and health risk analysis. The Analytical Contaminant Transport Analysis System (ACTS) and Health RISK Analysis (RISK) software tools are an integral part of the book and provide computational platforms for all the models discussed herein. The most recent versions of these two softwa...

Noninvasive Computed Tomography–based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial

Science.gov (United States)

Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M.; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A.; Bartholmai, Brian J.

2015-01-01

Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas. PMID:26052977

Software-based risk stratification of pulmonary adenocarcinomas manifesting as pure ground glass nodules on computed tomography

Energy Technology Data Exchange (ETDEWEB)

Nemec, Ursula [Vienna General Hospital, Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Vienna (Austria); Heidinger, Benedikt H.; Bankier, Alexander A. [Harvard Medical School, Radiology, Beth Israel Deaconess Medical Center, Boston, MA (United States); Anderson, Kevin R.; VanderLaan, Paul A. [Harvard Medical School, Pathology, Beth Israel Deaconess Medical Center, Boston, MA (United States); Westmore, Michael S. [Imbio, Delafield, WI (United States)

2018-01-15

To assess the performance of the ''Computer-Aided Nodule Assessment and Risk Yield'' (CANARY) software in the differentiation and risk assessment of histological subtypes of lung adenocarcinomas manifesting as pure ground glass nodules on computed tomography (CT). 64 surgically resected and histologically proven adenocarcinomas manifesting as pure ground-glass nodules on CT were assessed using CANARY software, which classifies voxel-densities into three risk components (low, intermediate, and high risk). Differences in risk components between histological adenocarcinoma subtypes were analysed. To determine the optimal threshold reflecting the presence of an invasive focus, sensitivity, specificity, negative predictive value, and positive predictive value were calculated. 28/64 (44%) were adenocarcinomas in situ (AIS); 26/64 (41%) were minimally invasive adenocarcinomas (MIA); and 10/64 (16%) were invasive ACs (IAC). The software showed significant differences in risk components between histological subtypes (P<0.001-0.003). A relative volume of 45% or less of low-risk components was associated with histological invasiveness (specificity 100%, positive predictive value 100%). CANARY-based risk assessment of ACs manifesting as pure ground glass nodules on CT allows the differentiation of their histological subtypes. A threshold of 45% of low-risk components reflects invasiveness in these groups. (orig.)

Software-based risk stratification of pulmonary adenocarcinomas manifesting as pure ground glass nodules on computed tomography

International Nuclear Information System (INIS)

Nemec, Ursula; Heidinger, Benedikt H.; Bankier, Alexander A.; Anderson, Kevin R.; VanderLaan, Paul A.; Westmore, Michael S.

2018-01-01

To assess the performance of the ''Computer-Aided Nodule Assessment and Risk Yield'' (CANARY) software in the differentiation and risk assessment of histological subtypes of lung adenocarcinomas manifesting as pure ground glass nodules on computed tomography (CT). 64 surgically resected and histologically proven adenocarcinomas manifesting as pure ground-glass nodules on CT were assessed using CANARY software, which classifies voxel-densities into three risk components (low, intermediate, and high risk). Differences in risk components between histological adenocarcinoma subtypes were analysed. To determine the optimal threshold reflecting the presence of an invasive focus, sensitivity, specificity, negative predictive value, and positive predictive value were calculated. 28/64 (44%) were adenocarcinomas in situ (AIS); 26/64 (41%) were minimally invasive adenocarcinomas (MIA); and 10/64 (16%) were invasive ACs (IAC). The software showed significant differences in risk components between histological subtypes (P<0.001-0.003). A relative volume of 45% or less of low-risk components was associated with histological invasiveness (specificity 100%, positive predictive value 100%). CANARY-based risk assessment of ACs manifesting as pure ground glass nodules on CT allows the differentiation of their histological subtypes. A threshold of 45% of low-risk components reflects invasiveness in these groups. (orig.)

Custom v. Standardized Risk Models

Directory of Open Access Journals (Sweden)

Zura Kakushadze

2015-05-01

Full Text Available We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1 longer horizon risk factors (value, growth, etc. increase noise trades and trading costs; (2 arbitrary risk factors can neutralize alpha; (3 “standardized” industries are artificial and insufficiently granular; (4 normalization of style risk factors is lost for the trading universe; (5 diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building.

Measuring the coupled risks: A copula-based CVaR model

Science.gov (United States)

He, Xubiao; Gong, Pu

2009-01-01

Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks' coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company's stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.

Risk-based analysis methods applied to nuclear power plant technical specifications

International Nuclear Information System (INIS)

Wagner, D.P.; Minton, L.A.; Gaertner, J.P.

1989-01-01

A computer-aided methodology and practical applications of risk-based evaluation of technical specifications are described. The methodology, developed for use by the utility industry, is a part of the overall process of improving nuclear power plant technical specifications. The SOCRATES computer program uses the results of a probabilistic risk assessment or a system-level risk analysis to calculate changes in risk due to changes in the surveillance test interval and/or the allowed outage time stated in the technical specification. The computer program can accommodate various testing strategies (such as staggered or simultaneous testing) to allow modeling of component testing as it is carried out at the plant. The methods and computer program are an integral part of a larger decision process aimed at determining benefits from technical specification changes. These benefits can include cost savings to the utilities by reducing forced shutdowns and decreasing labor requirements for test and maintenance activities, with no adverse impacts on risk. The methodology and the SOCRATES computer program have been used extensively toe valuate several actual technical specifications in case studies demonstrating the methods. Summaries of these applications demonstrate the types of results achieved and the usefulness of the risk-based evaluation in improving the technical specifications

Formal safety assessment based on relative risks model in ship navigation

Energy Technology Data Exchange (ETDEWEB)

Hu Shenping [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: sphu@mmc.shmtu.edu.cn; Fang Quangen [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: qgfang@mmc.shmtu.edu.cn; Xia Haibo [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: hbxia@mmc.shmtu.edu.cn; Xi Yongtao [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: xiyt@mmc.shmtu.edu.cn

2007-03-15

Formal safety assessment (FSA) is a structured and systematic methodology aiming at enhancing maritime safety. It has been gradually and broadly used in the shipping industry nowadays around the world. On the basis of analysis and conclusion of FSA approach, this paper discusses quantitative risk assessment and generic risk model in FSA, especially frequency and severity criteria in ship navigation. Then it puts forward a new model based on relative risk assessment (MRRA). The model presents a risk-assessment approach based on fuzzy functions and takes five factors into account, including detailed information about accident characteristics. It has already been used for the assessment of pilotage safety in Shanghai harbor, China. Consequently, it can be proved that MRRA is a useful method to solve the problems in the risk assessment of ship navigation safety in practice.

Formal safety assessment based on relative risks model in ship navigation

International Nuclear Information System (INIS)

Hu Shenping; Fang Quangen; Xia Haibo; Xi Yongtao

2007-01-01

Formal safety assessment (FSA) is a structured and systematic methodology aiming at enhancing maritime safety. It has been gradually and broadly used in the shipping industry nowadays around the world. On the basis of analysis and conclusion of FSA approach, this paper discusses quantitative risk assessment and generic risk model in FSA, especially frequency and severity criteria in ship navigation. Then it puts forward a new model based on relative risk assessment (MRRA). The model presents a risk-assessment approach based on fuzzy functions and takes five factors into account, including detailed information about accident characteristics. It has already been used for the assessment of pilotage safety in Shanghai harbor, China. Consequently, it can be proved that MRRA is a useful method to solve the problems in the risk assessment of ship navigation safety in practice

Developing points-based risk-scoring systems in the presence of competing risks.

Science.gov (United States)

Austin, Peter C; Lee, Douglas S; D'Agostino, Ralph B; Fine, Jason P

2016-09-30

Predicting the occurrence of an adverse event over time is an important issue in clinical medicine. Clinical prediction models and associated points-based risk-scoring systems are popular statistical methods for summarizing the relationship between a multivariable set of patient risk factors and the risk of the occurrence of an adverse event. Points-based risk-scoring systems are popular amongst physicians as they permit a rapid assessment of patient risk without the use of computers or other electronic devices. The use of such points-based risk-scoring systems facilitates evidence-based clinical decision making. There is a growing interest in cause-specific mortality and in non-fatal outcomes. However, when considering these types of outcomes, one must account for competing risks whose occurrence precludes the occurrence of the event of interest. We describe how points-based risk-scoring systems can be developed in the presence of competing events. We illustrate the application of these methods by developing risk-scoring systems for predicting cardiovascular mortality in patients hospitalized with acute myocardial infarction. Code in the R statistical programming language is provided for the implementation of the described methods. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Learning-based computing techniques in geoid modeling for precise height transformation

Science.gov (United States)

Erol, B.; Erol, S.

2013-03-01

Precise determination of local geoid is of particular importance for establishing height control in geodetic GNSS applications, since the classical leveling technique is too laborious. A geoid model can be accurately obtained employing properly distributed benchmarks having GNSS and leveling observations using an appropriate computing algorithm. Besides the classical multivariable polynomial regression equations (MPRE), this study attempts an evaluation of learning based computing algorithms: artificial neural networks (ANNs), adaptive network-based fuzzy inference system (ANFIS) and especially the wavelet neural networks (WNNs) approach in geoid surface approximation. These algorithms were developed parallel to advances in computer technologies and recently have been used for solving complex nonlinear problems of many applications. However, they are rather new in dealing with precise modeling problem of the Earth gravity field. In the scope of the study, these methods were applied to Istanbul GPS Triangulation Network data. The performances of the methods were assessed considering the validation results of the geoid models at the observation points. In conclusion the ANFIS and WNN revealed higher prediction accuracies compared to ANN and MPRE methods. Beside the prediction capabilities, these methods were also compared and discussed from the practical point of view in conclusions.

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

Science.gov (United States)

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Blended Risk Approach in Applying PSA Models to Risk-Based Regulations

International Nuclear Information System (INIS)

Dimitrijevic, V. B.; Chapman, J. R.

1996-01-01

In this paper, the authors will discuss a modern approach in applying PSA models in risk-based regulation. The Blended Risk Approach is a combination of traditional and probabilistic processes. It is receiving increased attention in different industries in the U. S. and abroad. The use of the deterministic regulations and standards provides a proven and well understood basis on which to assess and communicate the impact of change to plant design and operation. Incorporation of traditional values into risk evaluation is working very well in the blended approach. This approach is very application specific. It includes multiple risk attributes, qualitative risk analysis, and basic deterministic principles. In blending deterministic and probabilistic principles, this approach ensures that the objectives of the traditional defense-in-depth concept are not compromised and the design basis of the plant is explicitly considered. (author)

Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model.

Science.gov (United States)

Alawieh, Ali; Sabra, Zahraa; Langley, E Farris; Bizri, Abdul Rahman; Hamadeh, Randa; Zaraket, Fadi A

2017-11-25

After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak of polio among nationals and refugees. In this work, we used a computational individual-simulation model to assess the risk of poliovirus threat to Lebanon prior and after the immunization campaign and to quantitatively assess the healthcare impact of the campaign and the required standards that need to be maintained nationally to prevent a future outbreak. Acute poliomyelitis surveillance in Lebanon was along with the design and coverage rate of the recent national polio immunization campaign were reviewed from the records of the Lebanese Ministry of Public Health. Lebanese population demographics including Syrian and Palestinian refugees were reviewed to design individual-based models that predicts the consequences of polio spread to Lebanon and evaluate the outcome of immunization campaigns. The model takes into account geographic, demographic and health-related features. Our simulations confirmed the high risk of polio outbreaks in Lebanon within 10 days of case introduction prior to the immunization campaign, and showed that the current immunization campaign significantly reduced the speed of the infection in the event poliomyelitis cases enter the country. A minimum of 90% national immunization coverage was found to be required to prevent exponential propagation of potential transmission. Both surveillance and immunization efforts should be maintained at high standards in Lebanon and other countries in the area to detect and limit any potential outbreak. The use of computational population simulation models can provide a quantitative approach to assess the impact of immunization campaigns and the burden of infectious diseases even in the context of population migration.

Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model

Directory of Open Access Journals (Sweden)

Ali Alawieh

2017-11-01

Full Text Available Abstract Background After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak of polio among nationals and refugees. In this work, we used a computational individual-simulation model to assess the risk of poliovirus threat to Lebanon prior and after the immunization campaign and to quantitatively assess the healthcare impact of the campaign and the required standards that need to be maintained nationally to prevent a future outbreak. Methods Acute poliomyelitis surveillance in Lebanon was along with the design and coverage rate of the recent national polio immunization campaign were reviewed from the records of the Lebanese Ministry of Public Health. Lebanese population demographics including Syrian and Palestinian refugees were reviewed to design individual-based models that predicts the consequences of polio spread to Lebanon and evaluate the outcome of immunization campaigns. The model takes into account geographic, demographic and health-related features. Results Our simulations confirmed the high risk of polio outbreaks in Lebanon within 10 days of case introduction prior to the immunization campaign, and showed that the current immunization campaign significantly reduced the speed of the infection in the event poliomyelitis cases enter the country. A minimum of 90% national immunization coverage was found to be required to prevent exponential propagation of potential transmission. Conclusions Both surveillance and immunization efforts should be maintained at high standards in Lebanon and other countries in the area to detect and limit any potential outbreak. The use of computational population simulation models can provide a quantitative approach to assess the impact of immunization campaigns and the burden of

Image analysis and modeling in medical image computing. Recent developments and advances.

Science.gov (United States)

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

Children, computer exposure and musculoskeletal outcomes: the development of pathway models for school and home computer-related musculoskeletal outcomes.

Science.gov (United States)

Harris, Courtenay; Straker, Leon; Pollock, Clare; Smith, Anne

2015-01-01

Children's computer use is rapidly growing, together with reports of related musculoskeletal outcomes. Models and theories of adult-related risk factors demonstrate multivariate risk factors associated with computer use. Children's use of computers is different from adult's computer use at work. This study developed and tested a child-specific model demonstrating multivariate relationships between musculoskeletal outcomes, computer exposure and child factors. Using pathway modelling, factors such as gender, age, television exposure, computer anxiety, sustained attention (flow), socio-economic status and somatic complaints (headache and stomach pain) were found to have effects on children's reports of musculoskeletal symptoms. The potential for children's computer exposure to follow a dose-response relationship was also evident. Developing a child-related model can assist in understanding risk factors for children's computer use and support the development of recommendations to encourage children to use this valuable resource in educational, recreational and communication environments in a safe and productive manner. Computer use is an important part of children's school and home life. Application of this developed model, that encapsulates related risk factors, enables practitioners, researchers, teachers and parents to develop strategies that assist young people to use information technology for school, home and leisure in a safe and productive manner.

Computational fluid dynamics modelling in cardiovascular medicine.

Science.gov (United States)

Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

2016-01-01

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission

Globally-Applicable Predictive Wildfire Model   a Temporal-Spatial GIS Based Risk Analysis Using Data Driven Fuzzy Logic Functions

Science.gov (United States)

van den Dool, G.

2017-11-01

This study (van den Dool, 2017) is a proof of concept for a global predictive wildfire model, in which the temporal-spatial characteristics of wildfires are placed in a Geographical Information System (GIS), and the risk analysis is based on data-driven fuzzy logic functions. The data sources used in this model are available as global datasets, but subdivided into three pilot areas: North America (California/Nevada), Europe (Spain), and Asia (Mongolia), and are downscaled to the highest resolution (3-arc second). The GIS is constructed around three themes: topography, fuel availability and climate. From the topographical data, six derived sub-themes are created and converted to a fuzzy membership based on the catchment area statistics. The fuel availability score is a composite of four data layers: land cover, wood loads, biomass, biovolumes. As input for the climatological sub-model reanalysed daily averaged, weather-related data is used, which is accumulated to a global weekly time-window (to account for the uncertainty within the climatological model) and forms the temporal component of the model. The final product is a wildfire risk score (from 0 to 1) by week, representing the average wildfire risk in an area. To compute the potential wildfire risk the sub-models are combined usinga Multi-Criteria Approach, and the model results are validated against the area under the Receiver Operating Characteristic curve.

Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

Science.gov (United States)

Hu, Yong

2017-12-01

In this paper, the data processing and storage characteristics of cloud computing are analyzed and studied. On this basis, a cloud computing data storage model based on BP neural network is proposed. In this data storage model, it can carry out the choice of server cluster according to the different attributes of the data, so as to complete the spatial data storage model with load balancing function, and have certain feasibility and application advantages.

Trust Models in Ubiquitous Computing

DEFF Research Database (Denmark)

Nielsen, Mogens; Krukow, Karl; Sassone, Vladimiro

2008-01-01

We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models.......We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models....

Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.

Science.gov (United States)

Chung, Chi-Jung; Kuo, Yu-Chen; Hsieh, Yun-Yu; Li, Tsai-Chung; Lin, Cheng-Chieh; Liang, Wen-Miin; Liao, Li-Na; Li, Chia-Ing; Lin, Hsueh-Chun

2017-11-01

This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing. The infrastructure of the proposed model comprises three domains: 1) the health measurement data warehouse (HMDW) for the case study repository, 2) the self-developed modules of online health risk information statistics (HRIStat) for cloud computing, and 3) the prototype of a Web-based process automation system in statistics (PASIS) for the health risk assessment of case studies with subject-enabled evaluation. The system design employed freeware including Java applications, MySQL, and R packages to drive a health risk expert system (HRES). In the design, the HRIStat modules enforce the typical analytics methods for biomedical statistics, and the PASIS interfaces enable process automation of the HRES for cloud computing. The Web-based model supports both modes, step-by-step analysis and auto-computing process, respectively for preliminary evaluation and real time computation. The proposed model was evaluated by computing prior researches in relation to the epidemiological measurement of diseases that were caused by either heavy metal exposures in the environment or clinical complications in hospital. The simulation validity was approved by the commercial statistics software. The model was installed in a stand-alone computer and in a cloud-server workstation to verify computing performance for a data amount of more than 230K sets. Both setups reached efficiency of about 10 5 sets per second. The Web-based PASIS interface can be used for cloud computing, and the HRIStat module can be flexibly expanded with advanced subjects for measurement statistics. The analytics procedure of the HRES prototype is capable of providing assessment criteria prior to estimating the potential risk to public health. Copyright © 2017 Elsevier B.V. All rights reserved.

The CMS Computing Model

International Nuclear Information System (INIS)

Bonacorsi, D.

2007-01-01

The CMS experiment at LHC has developed a baseline Computing Model addressing the needs of a computing system capable to operate in the first years of LHC running. It is focused on a data model with heavy streaming at the raw data level based on trigger, and on the achievement of the maximum flexibility in the use of distributed computing resources. The CMS distributed Computing Model includes a Tier-0 centre at CERN, a CMS Analysis Facility at CERN, several Tier-1 centres located at large regional computing centres, and many Tier-2 centres worldwide. The workflows have been identified, along with a baseline architecture for the data management infrastructure. This model is also being tested in Grid Service Challenges of increasing complexity, coordinated with the Worldwide LHC Computing Grid community

Impact of implementation choices on quantitative predictions of cell-based computational models

Science.gov (United States)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

Knowledge-based computer security advisor

International Nuclear Information System (INIS)

Hunteman, W.J.; Squire, M.B.

1991-01-01

The rapid expansion of computer security information and technology has included little support to help the security officer identify the safeguards needed to comply with a policy and to secure a computing system. This paper reports that Los Alamos is developing a knowledge-based computer security system to provide expert knowledge to the security officer. This system includes a model for expressing the complex requirements in computer security policy statements. The model is part of an expert system that allows a security officer to describe a computer system and then determine compliance with the policy. The model contains a generic representation that contains network relationships among the policy concepts to support inferencing based on information represented in the generic policy description

A Model of Computation for Bit-Level Concurrent Computing and Programming: APEC

Science.gov (United States)

Ajiro, Takashi; Tsuchida, Kensei

A concurrent model of computation and a language based on the model for bit-level operation are useful for developing asynchronous and concurrent programs compositionally, which frequently use bit-level operations. Some examples are programs for video games, hardware emulation (including virtual machines), and signal processing. However, few models and languages are optimized and oriented to bit-level concurrent computation. We previously developed a visual programming language called A-BITS for bit-level concurrent programming. The language is based on a dataflow-like model that computes using processes that provide serial bit-level operations and FIFO buffers connected to them. It can express bit-level computation naturally and develop compositionally. We then devised a concurrent computation model called APEC (Asynchronous Program Elements Connection) for bit-level concurrent computation. This model enables precise and formal expression of the process of computation, and a notion of primitive program elements for controlling and operating can be expressed synthetically. Specifically, the model is based on a notion of uniform primitive processes, called primitives, that have three terminals and four ordered rules at most, as well as on bidirectional communication using vehicles called carriers. A new notion is that a carrier moving between two terminals can briefly express some kinds of computation such as synchronization and bidirectional communication. The model's properties make it most applicable to bit-level computation compositionally, since the uniform computation elements are enough to develop components that have practical functionality. Through future application of the model, our research may enable further research on a base model of fine-grain parallel computer architecture, since the model is suitable for expressing massive concurrency by a network of primitives.

A computer-aided framework for development, identification andmanagement of physiologically-based pharmacokinetic models

DEFF Research Database (Denmark)

Heitzig, Martina; Linninger, Andreas; Sin, Gürkan

2014-01-01

The objective of this work is the development of a generic computer-aided modelling framework to support the development of physiologically-based pharmacokinetic models thereby increasing the efficiency and quality of the modelling process. In particular, the framework systematizes the modelling...

Cloud computing assessing the risks

CERN Document Server

Carstensen, Jared; Golden, Bernard

2012-01-01

Cloud Computing: Assessing the risks answers these questions and many more. Using jargon-free language and relevant examples, analogies and diagrams, it is an up-to-date, clear and comprehensive guide the security, governance, risk, and compliance elements of Cloud Computing.

A border-ownership model based on computational electromagnetism.

Science.gov (United States)

Zainal, Zaem Arif; Satoh, Shunji

2018-03-01

The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the side of the object: so-called border ownership (BO). BO coding is a key process for extracting the objects from the background, allowing one to organize a cluttered scene. We propose that the problem is solvable simultaneously by application of a theorem of electromagnetism, i.e., "conservative vector fields have zero rotation, or "curl." We hypothesize that (i) the BO signal is definable as a vector electric field with arrowheads pointing to the inner side of perceived objects, and (ii) its corresponding scalar field carries information related to perceived order in depth of occluding/occluded objects. A simple model was developed based on this computational theory. Model results qualitatively agree with object-side selectivity of BO-coding neurons, and with perceptions of object order. The model update rule can be reproduced as a plausible neural network that presents new interpretations of existing physiological results. Results of this study also suggest that T-junction detectors are unnecessary to calculate depth order. Copyright © 2017 Elsevier Ltd. All rights reserved.

Operational risk quantification and modelling within Romanian insurance industry

Directory of Open Access Journals (Sweden)

Tudor Răzvan

2017-07-01

Full Text Available This paper aims at covering and describing the shortcomings of various models used to quantify and model the operational risk within insurance industry with a particular focus on Romanian specific regulation: Norm 6/2015 concerning the operational risk issued by IT systems. While most of the local insurers are focusing on implementing the standard model to compute the Operational Risk solvency capital required, the local regulator has issued a local norm that requires to identify and assess the IT based operational risks from an ISO 27001 perspective. The challenges raised by the correlations assumed in the Standard model are substantially increased by this new regulation that requires only the identification and quantification of the IT operational risks. The solvency capital requirement stipulated by the implementation of Solvency II doesn’t recommend a model or formula on how to integrate the newly identified risks in the Operational Risk capital requirements. In this context we are going to assess the academic and practitioner’s understanding in what concerns: The Frequency-Severity approach, Bayesian estimation techniques, Scenario Analysis and Risk Accounting based on risk units, and how they could support the modelling of operational risk that are IT based. Developing an internal model only for the operational risk capital requirement proved to be, so far, costly and not necessarily beneficial for the local insurers. As the IT component will play a key role in the future of the insurance industry, the result of this analysis will provide a specific approach in operational risk modelling that can be implemented in the context of Solvency II, in a particular situation when (internal or external operational risk databases are scarce or not available.

Framework for generating expert systems to perform computer security risk analysis

International Nuclear Information System (INIS)

Smith, S.T.; Lim, J.J.

1985-01-01

At Los Alamos we are developing a framework to generate knowledge-based expert systems for performing automated risk analyses upon a subject system. The expert system is a computer program that models experts' knowledge about a topic, including facts, assumptions, insights, and decision rationale. The subject system, defined as the collection of information, procedures, devices, and real property upon which the risk analysis is to be performed, is a member of the class of systems that have three identifying characteristics: a set of desirable assets (or targets), a set of adversaries (or threats) desiring to obtain or to do harm to the assets, and a set of protective mechanisms to safeguard the assets from the adversaries. Risk analysis evaluates both vulnerability to and the impact of successful threats against the targets by determining the overall effectiveness of the subject system safeguards, identifying vulnerabilities in that set of safeguards, and determining cost-effective improvements to the safeguards. As a testbed, we evaluate the inherent vulnerabilities and risks in a system of computer security safeguards. The method considers safeguards protecting four generic targets (physical plant of the computer installation, its hardware, its software, and its documents and displays) against three generic threats (natural hazards, direct human actions requiring the presence of the adversary, and indirect human actions wherein the adversary is not on the premises-perhaps using such access tools as wiretaps, dialup lines, and so forth). Our automated procedure to assess the effectiveness of computer security safeguards differs from traditional risk analysis methods

Research on Digital Forensic Readiness Design in a Cloud Computing-Based Smart Work Environment

Directory of Open Access Journals (Sweden)

Sangho Park

2018-04-01

Full Text Available Recently, the work environments of organizations have been in the process of transitioning into smart work environments by applying cloud computing technology in the existing work environment. The smart work environment has the characteristic of being able to access information assets inside the company from outside the company through cloud computing technology, share information without restrictions on location by using mobile terminals, and provide a work environment where work can be conducted effectively in various locations and mobile environments. Thus, in the cloud computing-based smart work environment, changes are occurring in terms of security risks, such as an increase in the leakage risk of an organization’s information assets through mobile terminals which have a high risk of loss and theft and increase the hacking risk of wireless networks in mobile environments. According to these changes in security risk, the reactive digital forensic method, which investigates digital evidence after the occurrence of security incidents, appears to have a limit which has led to a rise in the necessity of proactive digital forensic approaches wherein security incidents can be addressed preemptively. Accordingly, in this research, we design a digital forensic readiness model at the level of preemptive prevention by considering changes in the cloud computing-based smart work environment. Firstly, we investigate previous research related to the cloud computing-based smart work environment and digital forensic readiness and analyze a total of 50 components of digital forensic readiness. In addition, through the analysis of the corresponding preceding research, we design seven detailed areas, namely, outside the organization environment, within the organization guideline, system information, terminal information, user information, usage information, and additional function. Then, we design a draft of the digital forensic readiness model in the cloud

Computational models of neuromodulation.

Science.gov (United States)

Fellous, J M; Linster, C

1998-05-15

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

Radiomics-based differentiation of lung disease models generated by polluted air based on X-ray computed tomography data.

Science.gov (United States)

Szigeti, Krisztián; Szabó, Tibor; Korom, Csaba; Czibak, Ilona; Horváth, Ildikó; Veres, Dániel S; Gyöngyi, Zoltán; Karlinger, Kinga; Bergmann, Ralf; Pócsik, Márta; Budán, Ferenc; Máthé, Domokos

2016-02-11

Lung diseases (resulting from air pollution) require a widely accessible method for risk estimation and early diagnosis to ensure proper and responsive treatment. Radiomics-based fractal dimension analysis of X-ray computed tomography attenuation patterns in chest voxels of mice exposed to different air polluting agents was performed to model early stages of disease and establish differential diagnosis. To model different types of air pollution, BALBc/ByJ mouse groups were exposed to cigarette smoke combined with ozone, sulphur dioxide gas and a control group was established. Two weeks after exposure, the frequency distributions of image voxel attenuation data were evaluated. Specific cut-off ranges were defined to group voxels by attenuation. Cut-off ranges were binarized and their spatial pattern was associated with calculated fractal dimension, then abstracted by the fractal dimension -- cut-off range mathematical function. Nonparametric Kruskal-Wallis (KW) and Mann-Whitney post hoc (MWph) tests were used. Each cut-off range versus fractal dimension function plot was found to contain two distinctive Gaussian curves. The ratios of the Gaussian curve parameters are considerably significant and are statistically distinguishable within the three exposure groups. A new radiomics evaluation method was established based on analysis of the fractal dimension of chest X-ray computed tomography data segments. The specific attenuation patterns calculated utilizing our method may diagnose and monitor certain lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma, tuberculosis or lung carcinomas.

Model-free and model-based reward prediction errors in EEG.

Science.gov (United States)

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Risk-based systems analysis for emerging technologies: Applications of a technology risk assessment model to public decision making

International Nuclear Information System (INIS)

Quadrel, M.J.; Fowler, K.M.; Cameron, R.; Treat, R.J.; McCormack, W.D.; Cruse, J.

1995-01-01

The risk-based systems analysis model was designed to establish funding priorities among competing technologies for tank waste remediation. The model addresses a gap in the Department of Energy's (DOE's) ''toolkit'' for establishing funding priorities among emerging technologies by providing disciplined risk and cost assessments of candidate technologies within the context of a complete remediation system. The model is comprised of a risk and cost assessment and a decision interface. The former assesses the potential reductions in risk and cost offered by new technology relative to the baseline risk and cost of an entire system. The latter places this critical information in context of other values articulated by decision makers and stakeholders in the DOE system. The risk assessment portion of the model is demonstrated for two candidate technologies for tank waste retrieval (arm-based mechanical retrieval -- the ''long reach arm'') and subsurface barriers (close-coupled chemical barriers). Relative changes from the base case in cost and risk are presented for these two technologies to illustrate how the model works. The model and associated software build on previous work performed for DOE's Office of Technology Development and the former Underground Storage Tank Integrated Demonstration, and complement a decision making tool presented at Waste Management 1994 for integrating technical judgements and non-technical (stakeholder) values when making technology funding decisions

Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

Directory of Open Access Journals (Sweden)

Zhiyong Yang

2008-11-01

Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

Directory of Open Access Journals (Sweden)

Zhiyong Yang

2008-03-01

Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

Research on application of intelligent computation based LUCC model in urbanization process

Science.gov (United States)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Science.gov (United States)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Optimization of the cumulative risk assessment of pesticides and biocides using computational techniques: Pilot project

DEFF Research Database (Denmark)

Jonsdottir, Svava Osk; Reffstrup, Trine Klein; Petersen, Annette

This pilot project is intended as the first step in developing a computational strategy to assist in refining methods for higher tier cumulative and aggregate risk assessment of exposure to mixture of pesticides and biocides. For this purpose, physiologically based toxicokinetic (PBTK) models were...

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Directory of Open Access Journals (Sweden)

Qiang Liu

2018-05-01

Full Text Available Computing speed is a significant issue of large-scale flood simulations for real-time response to disaster prevention and mitigation. Even today, most of the large-scale flood simulations are generally run on supercomputers due to the massive amounts of data and computations necessary. In this work, a two-dimensional shallow water model based on an unstructured Godunov-type finite volume scheme was proposed for flood simulation. To realize a fast simulation of large-scale floods on a personal computer, a Graphics Processing Unit (GPU-based, high-performance computing method using the OpenACC application was adopted to parallelize the shallow water model. An unstructured data management method was presented to control the data transportation between the GPU and CPU (Central Processing Unit with minimum overhead, and then both computation and data were offloaded from the CPU to the GPU, which exploited the computational capability of the GPU as much as possible. The parallel model was validated using various benchmarks and real-world case studies. The results demonstrate that speed-ups of up to one order of magnitude can be achieved in comparison with the serial model. The proposed parallel model provides a fast and reliable tool with which to quickly assess flood hazards in large-scale areas and, thus, has a bright application prospect for dynamic inundation risk identification and disaster assessment.

Addressing dependability by applying an approach for model-based risk assessment

International Nuclear Information System (INIS)

Gran, Bjorn Axel; Fredriksen, Rune; Thunem, Atoosa P.-J.

2007-01-01

This paper describes how an approach for model-based risk assessment (MBRA) can be applied for addressing different dependability factors in a critical application. Dependability factors, such as availability, reliability, safety and security, are important when assessing the dependability degree of total systems involving digital instrumentation and control (I and C) sub-systems. In order to identify risk sources their roles with regard to intentional system aspects such as system functions, component behaviours and intercommunications must be clarified. Traditional risk assessment is based on fault or risk models of the system. In contrast to this, MBRA utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tried out within the telemedicine and e-commerce areas, and provided through a series of seven trials a sound basis for risk assessments. In this paper the results from the CORAS project are presented, and it is discussed how the approach for applying MBRA meets the needs of a risk-informed Man-Technology-Organization (MTO) model, and how methodology can be applied as a part of a trust case development

Addressing dependability by applying an approach for model-based risk assessment

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjorn Axel [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: bjorn.axel.gran@hrp.no; Fredriksen, Rune [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: rune.fredriksen@hrp.no; Thunem, Atoosa P.-J. [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: atoosa.p-j.thunem@hrp.no

2007-11-15

This paper describes how an approach for model-based risk assessment (MBRA) can be applied for addressing different dependability factors in a critical application. Dependability factors, such as availability, reliability, safety and security, are important when assessing the dependability degree of total systems involving digital instrumentation and control (I and C) sub-systems. In order to identify risk sources their roles with regard to intentional system aspects such as system functions, component behaviours and intercommunications must be clarified. Traditional risk assessment is based on fault or risk models of the system. In contrast to this, MBRA utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tried out within the telemedicine and e-commerce areas, and provided through a series of seven trials a sound basis for risk assessments. In this paper the results from the CORAS project are presented, and it is discussed how the approach for applying MBRA meets the needs of a risk-informed Man-Technology-Organization (MTO) model, and how methodology can be applied as a part of a trust case development.

Application of Computer Simulation Modeling to Medication Administration Process Redesign

OpenAIRE

Huynh, Nathan; Snyder, Rita; Vidal, Jose M.; Tavakoli, Abbas S.; Cai, Bo

2012-01-01

The medication administration process (MAP) is one of the most high-risk processes in health care. MAP workflow redesign can precipitate both unanticipated and unintended consequences that can lead to new medication safety risks and workflow inefficiencies. Thus, it is necessary to have a tool to evaluate the impact of redesign approaches in advance of their clinical implementation. This paper discusses the development of an agent-based MAP computer simulation model that can be used to assess...

A spread willingness computing-based information dissemination model.

Science.gov (United States)

Huang, Haojing; Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network.

Risk Assessment of Engineering Project Financing Based on PPP Model

Directory of Open Access Journals (Sweden)

Ma Qiuli

2017-01-01

Full Text Available At present, the project financing channel is single, and the urban facilities are in short supply, and the risk assessment and prevention mechanism of financing should be further improved to reduce the risk of project financing. In view of this, the fuzzy comprehensive evaluation model of project financing risk which combined the method of fuzzy comprehensive evaluation and analytic hierarchy process is established. The scientificalness and effectiveness of the model are verified by the example of the world port project in Luohe city, and it provides basis and reference for engineering project financing based on PPP mode.

Risk perception and risk management in cloud computing: results from a case study of Swiss companies

OpenAIRE

Brender, Nathalie; Markov, Iliya

2013-01-01

In today's economic turmoil, the pay-per-use pricing model of cloud computing, its flexibility and scalability and the potential for better security and availability levels are alluring to both SMEs and large enterprises. However, cloud computing is fraught with security risks which need to be carefully evaluated before any engagement in this area. This article elaborates on the most important risks inherent to the cloud such as information security, regulatory compliance, data location, inve...

Model of Procedure Usage – Results from a Qualitative Study to Inform Design of Computer-Based Procedures

Energy Technology Data Exchange (ETDEWEB)

Johanna H Oxstrand; Katya L Le Blanc

2012-07-01

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory, the Institute for Energy Technology, and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field operators. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do this. The underlying philosophy in the research effort is “Stop – Start – Continue”, i.e. what features from the use of paper-based procedures should we not incorporate (Stop), what should we keep (Continue), and what new features or work processes should be added (Start). One step in identifying the Stop – Start – Continue was to conduct a baseline study where affordances related to the current usage of paper-based procedures were identified. The purpose of the study was to develop a model of paper based procedure use which will help to identify desirable features for computer based procedure prototypes. Affordances such as note taking, markups

WORKSHOP ON APPLICATION OF STATISTICAL METHODS TO BIOLOGICALLY-BASED PHARMACOKINETIC MODELING FOR RISK ASSESSMENT

Science.gov (United States)

Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...

Large-scale model-based assessment of deer-vehicle collision risk.

Directory of Open Access Journals (Sweden)

Torsten Hothorn

Full Text Available Ungulates, in particular the Central European roe deer Capreolus capreolus and the North American white-tailed deer Odocoileus virginianus, are economically and ecologically important. The two species are risk factors for deer-vehicle collisions and as browsers of palatable trees have implications for forest regeneration. However, no large-scale management systems for ungulates have been implemented, mainly because of the high efforts and costs associated with attempts to estimate population sizes of free-living ungulates living in a complex landscape. Attempts to directly estimate population sizes of deer are problematic owing to poor data quality and lack of spatial representation on larger scales. We used data on >74,000 deer-vehicle collisions observed in 2006 and 2009 in Bavaria, Germany, to model the local risk of deer-vehicle collisions and to investigate the relationship between deer-vehicle collisions and both environmental conditions and browsing intensities. An innovative modelling approach for the number of deer-vehicle collisions, which allows nonlinear environment-deer relationships and assessment of spatial heterogeneity, was the basis for estimating the local risk of collisions for specific road types on the scale of Bavarian municipalities. Based on this risk model, we propose a new "deer-vehicle collision index" for deer management. We show that the risk of deer-vehicle collisions is positively correlated to browsing intensity and to harvest numbers. Overall, our results demonstrate that the number of deer-vehicle collisions can be predicted with high precision on the scale of municipalities. In the densely populated and intensively used landscapes of Central Europe and North America, a model-based risk assessment for deer-vehicle collisions provides a cost-efficient instrument for deer management on the landscape scale. The measures derived from our model provide valuable information for planning road protection and defining

Model-based computer-aided design for controlled release of pesticides

DEFF Research Database (Denmark)

Muro Sunè, Nuria; Gani, Rafiqul; Bell, G.

2005-01-01

In the field of controlled release technology for pesticides or active ingredients (AI), models that can predict its delivery during application are important for purposes of design and marketing of the pesticide product. Appropriate models for the controlled release of pesticides, if available, ...... extended models have been developed and implemented into a computer-aided system. The total model consisting of the property models embedded into the release models are then employed to study the release of different combinations of AIs and polymer-based microcapsules.......In the field of controlled release technology for pesticides or active ingredients (AI), models that can predict its delivery during application are important for purposes of design and marketing of the pesticide product. Appropriate models for the controlled release of pesticides, if available...

A web-based, collaborative modeling, simulation, and parallel computing environment for electromechanical systems

Directory of Open Access Journals (Sweden)

Xiaoliang Yin

2015-03-01

Full Text Available Complex electromechanical system is usually composed of multiple components from different domains, including mechanical, electronic, hydraulic, control, and so on. Modeling and simulation for electromechanical system on a unified platform is one of the research hotspots in system engineering at present. It is also the development trend of the design for complex electromechanical system. The unified modeling techniques and tools based on Modelica language provide a satisfactory solution. To meet with the requirements of collaborative modeling, simulation, and parallel computing for complex electromechanical systems based on Modelica, a general web-based modeling and simulation prototype environment, namely, WebMWorks, is designed and implemented. Based on the rich Internet application technologies, an interactive graphic user interface for modeling and post-processing on web browser was implemented; with the collaborative design module, the environment supports top-down, concurrent modeling and team cooperation; additionally, service-oriented architecture–based architecture was applied to supply compiling and solving services which run on cloud-like servers, so the environment can manage and dispatch large-scale simulation tasks in parallel on multiple computing servers simultaneously. An engineering application about pure electric vehicle is tested on WebMWorks. The results of simulation and parametric experiment demonstrate that the tested web-based environment can effectively shorten the design cycle of the complex electromechanical system.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

Science.gov (United States)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Web-Based Real Time Earthquake Forecasting and Personal Risk Management

Science.gov (United States)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

2012-12-01

Earthquake forecasts have been computed by a variety of countries and economies world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. One example is the Working Group on California Earthquake Probabilities that has been responsible for the official California earthquake forecast since 1988. However, in a time of increasingly severe global financial constraints, we are now moving inexorably towards personal risk management, wherein mitigating risk is becoming the responsibility of individual members of the public. Under these circumstances, open access to a variety of web-based tools, utilities and information is a necessity. Here we describe a web-based system that has been operational since 2009 at www.openhazards.com and www.quakesim.org. Models for earthquake physics and forecasting require input data, along with model parameters. The models we consider are the Natural Time Weibull (NTW) model for regional earthquake forecasting, together with models for activation and quiescence. These models use small earthquakes ('seismicity-based models") to forecast the occurrence of large earthquakes, either through varying rates of small earthquake activity, or via an accumulation of this activity over time. These approaches use data-mining algorithms combined with the ANSS earthquake catalog. The basic idea is to compute large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Each of these approaches has computational challenges associated with computing forecast information in real time. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we show that real-time forecasting is possible at a grid scale of 0.1o. We have analyzed the performance of these models using Reliability/Attributes and standard Receiver Operating Characteristic (ROC) tests. We show how the Reliability and

Risk-based safety indicators

International Nuclear Information System (INIS)

Sedlak, J.

2001-12-01

The report is structured as follows: 1. Risk-based safety indicators: Typology of risk-based indicators (RBIs); Tools for defining RBIs; Requirements for the PSA model; Data sources for RBIs; Types of risks monitored; RBIs and operational safety indicators; Feedback from operating experience; PSO model modification for RBIs; RBI categorization; RBI assessment; RBI applications; Suitable RBI applications. 2. Proposal for risk-based indicators: Acquiring information from operational experience; Method of acquiring safety relevance coefficients for the systems from a PSA model; Indicator definitions; On-line indicators. 3. Annex: Application of RBIs worldwide. (P.A.)

Computational model of precision grip in Parkinson’s disease: A Utility based approach

Directory of Open Access Journals (Sweden)

Ankur eGupta

2013-12-01

Full Text Available We propose a computational model of Precision Grip (PG performance in normal subjects and Parkinson’s Disease (PD patients. Prior studies on grip force generation in PD patients show an increase in grip force during ON medication and an increase in the variability of the grip force during OFF medication (Fellows et al 1998; Ingvarsson et al 1997. Changes in grip force generation in dopamine-deficient PD conditions strongly suggest contribution of the Basal Ganglia, a deep brain system having a crucial role in translating dopamine signals to decision making. The present approach is to treat the problem of modeling grip force generation as a problem of action selection, which is one of the key functions of the Basal Ganglia. The model consists of two components: 1 the sensory-motor loop component, and 2 the Basal Ganglia component. The sensory-motor loop component converts a reference position and a reference grip force, into lift force and grip force profiles, respectively. These two forces cooperate in grip-lifting a load. The sensory-motor loop component also includes a plant model that represents the interaction between two fingers involved in PG, and the object to be lifted. The Basal Ganglia component is modeled using Reinforcement Learning with the significant difference that the action selection is performed using utility distribution instead of using purely Value-based distribution, thereby incorporating risk-based decision making. The proposed model is able to account for the precision grip results from normal and PD patients accurately (Fellows et. al. 1998; Ingvarsson et. al. 1997. To our knowledge the model is the first model of precision grip in PD conditions.

Radiomics-based differentiation of lung disease models generated by polluted air based on X-ray computed tomography data

International Nuclear Information System (INIS)

Szigeti, Krisztián; Szabó, Tibor; Korom, Csaba; Czibak, Ilona; Horváth, Ildikó; Veres, Dániel S.; Gyöngyi, Zoltán; Karlinger, Kinga; Bergmann, Ralf; Pócsik, Márta; Budán, Ferenc; Máthé, Domokos

2016-01-01

Lung diseases (resulting from air pollution) require a widely accessible method for risk estimation and early diagnosis to ensure proper and responsive treatment. Radiomics-based fractal dimension analysis of X-ray computed tomography attenuation patterns in chest voxels of mice exposed to different air polluting agents was performed to model early stages of disease and establish differential diagnosis. To model different types of air pollution, BALBc/ByJ mouse groups were exposed to cigarette smoke combined with ozone, sulphur dioxide gas and a control group was established. Two weeks after exposure, the frequency distributions of image voxel attenuation data were evaluated. Specific cut-off ranges were defined to group voxels by attenuation. Cut-off ranges were binarized and their spatial pattern was associated with calculated fractal dimension, then abstracted by the fractal dimension -- cut-off range mathematical function. Nonparametric Kruskal-Wallis (KW) and Mann–Whitney post hoc (MWph) tests were used. Each cut-off range versus fractal dimension function plot was found to contain two distinctive Gaussian curves. The ratios of the Gaussian curve parameters are considerably significant and are statistically distinguishable within the three exposure groups. A new radiomics evaluation method was established based on analysis of the fractal dimension of chest X-ray computed tomography data segments. The specific attenuation patterns calculated utilizing our method may diagnose and monitor certain lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma, tuberculosis or lung carcinomas. The online version of this article (doi:10.1186/s12880-016-0118-z) contains supplementary material, which is available to authorized users

Agent-Based Computational Modeling of Cell Culture ...

Science.gov (United States)

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

Security, Privacy, Threats and Risks in Cloud Computing ― A Vital Review

OpenAIRE

Goyal, Sumit

2016-01-01

Cloud computing is a multi million dollar business. As more and more enterprises are adopting cloud services for their businesses, threat of security has become a big concern for these enterprises and cloud users. This review describes the latest threats and risks associated with cloud computing and suggests techniques for better privacy and security of data in cloud environment. Threats and risks associated with cloud service models (SaaS, PaaS and IaaS) along with cloud deployment models (p...

Blood leakage detection during dialysis therapy based on fog computing with array photocell sensors and heteroassociative memory model.

Science.gov (United States)

Wu, Jian-Xing; Huang, Ping-Tzan; Lin, Chia-Hung; Li, Chien-Ming

2018-02-01

Blood leakage and blood loss are serious life-threatening complications occurring during dialysis therapy. These events have been of concerns to both healthcare givers and patients. More than 40% of adult blood volume can be lost in just a few minutes, resulting in morbidities and mortality. The authors intend to propose the design of a warning tool for the detection of blood leakage/blood loss during dialysis therapy based on fog computing with an array of photocell sensors and heteroassociative memory (HAM) model. Photocell sensors are arranged in an array on a flexible substrate to detect blood leakage via the resistance changes with illumination in the visible spectrum of 500-700 nm. The HAM model is implemented to design a virtual alarm unit using electricity changes in an embedded system. The proposed warning tool can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and fog/cloud computing. The animal experimental results (pig blood) will demonstrate the feasibility.

Computational Aspects of Dam Risk Analysis: Findings and Challenges

Directory of Open Access Journals (Sweden)

Ignacio Escuder-Bueno

2016-09-01

Full Text Available In recent years, risk analysis techniques have proved to be a useful tool to inform dam safety management. This paper summarizes the outcomes of three themes related to dam risk analysis discussed in the Benchmark Workshops organized by the International Commission on Large Dams Technical Committee on “Computational Aspects of Analysis and Design of Dams.” In the 2011 Benchmark Workshop, estimation of the probability of failure of a gravity dam for the sliding failure mode was discussed. Next, in 2013, the discussion focused on the computational challenges of the estimation of consequences in dam risk analysis. Finally, in 2015, the probability of sliding and overtopping in an embankment was analyzed. These Benchmark Workshops have allowed a complete review of numerical aspects for dam risk analysis, showing that risk analysis methods are a very useful tool to analyze the risk of dam systems, including downstream consequence assessments and the uncertainty of structural models.

A Spread Willingness Computing-Based Information Dissemination Model

Science.gov (United States)

Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network. PMID:25110738

A Spread Willingness Computing-Based Information Dissemination Model

Directory of Open Access Journals (Sweden)

Haojing Huang

2014-01-01

Full Text Available This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user’s spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network.

A probabilistic method for computing quantitative risk indexes from medical injuries compensation claims.

Science.gov (United States)

Dalle Carbonare, S; Folli, F; Patrini, E; Giudici, P; Bellazzi, R

2013-01-01

The increasing demand of health care services and the complexity of health care delivery require Health Care Organizations (HCOs) to approach clinical risk management through proper methods and tools. An important aspect of risk management is to exploit the analysis of medical injuries compensation claims in order to reduce adverse events and, at the same time, to optimize the costs of health insurance policies. This work provides a probabilistic method to estimate the risk level of a HCO by computing quantitative risk indexes from medical injury compensation claims. Our method is based on the estimate of a loss probability distribution from compensation claims data through parametric and non-parametric modeling and Monte Carlo simulations. The loss distribution can be estimated both on the whole dataset and, thanks to the application of a Bayesian hierarchical model, on stratified data. The approach allows to quantitatively assessing the risk structure of the HCO by analyzing the loss distribution and deriving its expected value and percentiles. We applied the proposed method to 206 cases of injuries with compensation requests collected from 1999 to the first semester of 2007 by the HCO of Lodi, in the Northern part of Italy. We computed the risk indexes taking into account the different clinical departments and the different hospitals involved. The approach proved to be useful to understand the HCO risk structure in terms of frequency, severity, expected and unexpected loss related to adverse events.

Constructing a Computer Model of the Human Eye Based on Tissue Slice Images

OpenAIRE

Dai, Peishan; Wang, Boliang; Bao, Chunbo; Ju, Ying

2010-01-01

Computer simulation of the biomechanical and biological heat transfer in ophthalmology greatly relies on having a reliable computer model of the human eye. This paper proposes a novel method on the construction of a geometric model of the human eye based on tissue slice images. Slice images were obtained from an in vitro Chinese human eye through an embryo specimen processing methods. A level set algorithm was used to extract contour points of eye tissues while a principle component analysi...

Modeling risk assessment for nuclear processing plants with LAVA

International Nuclear Information System (INIS)

Smith, S.T.; Tisinger, R.M.

1988-01-01

Using the Los Alamos Vulnerability and Risk Assessment (LAVA) methodology, the authors developed a model for assessing risks associated with nuclear processing plants. LAVA is a three-part systematic approach to risk assessment. The first part is the mathematical methodology; the second is the general personal computer-based software engine; and the third is the application itself. The methodology provides a framework for creating applications for the software engine to operate upon; all application-specific information is data. Using LAVA, the authors build knowledge-based expert systems to assess risks in applications systems comprising a subject system and a safeguards system. The subject system model is sets of threats, assets, and undesirable outcomes. The safeguards system model is sets of safeguards functions for protecting the assets from the threats by preventing or ameliorating the undesirable outcomes, sets of safeguards subfunctions whose performance determine whether the function is adequate and complete, and sets of issues, appearing as interactive questionnaires, whose measures (in both monetary and linguistic terms) define both the weaknesses in the safeguards system and the potential costs of an undesirable outcome occurring

Which risk models perform best in selecting ever-smokers for lung cancer screening?

Science.gov (United States)

A new analysis by scientists at NCI evaluates nine different individualized lung cancer risk prediction models based on their selections of ever-smokers for computed tomography (CT) lung cancer screening.

Application of Computer Simulation Modeling to Medication Administration Process Redesign

Directory of Open Access Journals (Sweden)

Nathan Huynh

2012-01-01

Full Text Available The medication administration process (MAP is one of the most high-risk processes in health care. MAP workflow redesign can precipitate both unanticipated and unintended consequences that can lead to new medication safety risks and workflow inefficiencies. Thus, it is necessary to have a tool to evaluate the impact of redesign approaches in advance of their clinical implementation. This paper discusses the development of an agent-based MAP computer simulation model that can be used to assess the impact of MAP workflow redesign on MAP performance. The agent-based approach is adopted in order to capture Registered Nurse medication administration performance. The process of designing, developing, validating, and testing such a model is explained. Work is underway to collect MAP data in a hospital setting to provide more complex MAP observations to extend development of the model to better represent the complexity of MAP.

Television, computer, and video viewing; physical activity; and upper limb fracture risk in children: a population-based case control study.

Science.gov (United States)

Ma, Deqiong; Jones, Graeme

2003-11-01

The effect of physical activity on upper limb fractures was examined in this population-based case control study with 321 age- and gender-matched pairs. Sports participation increased fracture risk in boys and decreased risk in girls. Television viewing had a deleterious dose response association with wrist and forearm fractures while light physical activity was protective. The aim of this population-based case control study was to examine the association between television, computer, and video viewing; types and levels of physical activity; and upper limb fractures in children 9-16 years of age. A total of 321 fracture cases and 321 randomly selected individually matched controls were studied. Television, computer, and video viewing and types and levels of physical activity were determined by interview-administered questionnaire. Bone strength was assessed by DXA and metacarpal morphometry. In general, sports participation increased total upper limb fracture risk in boys and decreased risk in girls. Gender-specific risk estimates were significantly different for total, contact, noncontact, and high-risk sports participation as well as four individual sports (soccer, cricket, surfing, and swimming). In multivariate analysis, time spent television, computer, and video viewing in both sexes was positively associated with wrist and forearm fracture risk (OR 1.6/category, 95% CI: 1.1-2.2), whereas days involved in light physical activity participation decreased fracture risk (OR 0.8/category, 95% CI: 0.7-1.0). Sports participation increased hand (OR 1.5/sport, 95% CI: 1.1-2.0) and upper arm (OR 29.8/sport, 95% CI: 1.7-535) fracture risk in boys only and decreased wrist and forearm fracture risk in girls only (OR 0.5/sport, 95% CI: 0.3-0.9). Adjustment for bone density and metacarpal morphometry did not alter these associations. There is gender discordance with regard to sports participation and fracture risk in children, which may reflect different approaches to sport

Multi-binding site model-based curve-fitting program for the computation of RIA data

International Nuclear Information System (INIS)

Malan, P.G.; Ekins, R.P.; Cox, M.G.; Long, E.M.R.

1977-01-01

In this paper, a comparison will be made of model-based and empirical curve-fitting procedures. The implementation of a multiple binding-site curve-fitting model which will successfully fit a wide range of assay data, and which can be run on a mini-computer is described. The latter sophisticated model also provides estimates of binding site concentrations and the values of the respective equilibrium constants present: the latter have been used for refining assay conditions using computer optimisation techniques. (orig./AJ) [de

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

Energy Technology Data Exchange (ETDEWEB)

Johnson, J. D. (Prostat, Mesa, AZ); Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

2006-10-01

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

Science.gov (United States)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

Identity-Based Authentication for Cloud Computing

Science.gov (United States)

Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao

Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.

Task-based dermal exposure models for regulatory risk assessment

NARCIS (Netherlands)

Warren, N.D.; Marquart, H.; Christopher, Y.; Laitinen, J.; Hemmen, J.J. van

2006-01-01

The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

Science.gov (United States)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Analytical Modeling for Underground Risk Assessment in Smart Cities

Directory of Open Access Journals (Sweden)

Israr Ullah

2018-06-01

Full Text Available In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a simple linear approximation based on multiple linear regression analysis; (b hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c hybrid approximation approach which is a combination of (a and (b. Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.

A novel computer based expert decision making model for prostate cancer disease management.

Science.gov (United States)

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42

Computed tomography in children: multicenter cohort study design for the evaluation of cancer risk

International Nuclear Information System (INIS)

Krille, L.; Jahnen, A.; Mildenberger, P.; Schneider, K.; Weisser, G.; Zeeb, H.; Blettner, M.

2011-01-01

Exposure to ionizing radiation is a known risk factor for cancer. Cancer risk is highest after exposure in childhood. The computed tomography is the major contributor to the average, individual radiation exposure. Until now the association has been addressed only in statistical modeling. We present the first feasible study design on childhood cancer risk after exposure to computed tomography.

A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

Science.gov (United States)

Boursi, Ben; Mamtani, Ronac; Hwang, Wei-Ting; Haynes, Kevin; Yang, Yu-Xiao

2016-07-01

Current risk scores for colorectal cancer (CRC) are based on demographic and behavioral factors and have limited predictive values. To develop a novel risk prediction model for sporadic CRC using clinical and laboratory data in electronic medical records. We conducted a nested case-control study in a UK primary care database. Cases included those with a diagnostic code of CRC, aged 50-85. Each case was matched with four controls using incidence density sampling. CRC predictors were examined using univariate conditional logistic regression. Variables with p value CRC prediction models which included age, sex, height, obesity, ever smoking, alcohol dependence, and previous screening colonoscopy had an AUC of 0.58 (0.57-0.59) with poor goodness of fit. A laboratory-based model including hematocrit, MCV, lymphocytes, and neutrophil-lymphocyte ratio (NLR) had an AUC of 0.76 (0.76-0.77) and a McFadden's R2 of 0.21 with a NRI of 47.6 %. A combined model including sex, hemoglobin, MCV, white blood cells, platelets, NLR, and oral hypoglycemic use had an AUC of 0.80 (0.79-0.81) with a McFadden's R2 of 0.27 and a NRI of 60.7 %. Similar results were shown in an internal validation set. A laboratory-based risk model had good predictive power for sporadic CRC risk.

Credit Risk Analysis Using Machine and Deep Learning Models

Directory of Open Access Journals (Sweden)

Peter Martey Addo

2018-04-01

Full Text Available Due to the advanced technology associated with Big Data, data availability and computing power, most banks or lending institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision-making and transparency. In this work, we build binary classifiers based on machine and deep learning models on real data in predicting loan default probability. The top 10 important features from these models are selected and then used in the modeling process to test the stability of binary classifiers by comparing their performance on separate data. We observe that the tree-based models are more stable than the models based on multilayer artificial neural networks. This opens several questions relative to the intensive use of deep learning systems in enterprises.

The role of computer modelling in participatory integrated assessments

International Nuclear Information System (INIS)

Siebenhuener, Bernd; Barth, Volker

2005-01-01

In a number of recent research projects, computer models have been included in participatory procedures to assess global environmental change. The intention was to support knowledge production and to help the involved non-scientists to develop a deeper understanding of the interactions between natural and social systems. This paper analyses the experiences made in three projects with the use of computer models from a participatory and a risk management perspective. Our cross-cutting analysis of the objectives, the employed project designs and moderation schemes and the observed learning processes in participatory processes with model use shows that models play a mixed role in informing participants and stimulating discussions. However, no deeper reflection on values and belief systems could be achieved. In terms of the risk management phases, computer models serve best the purposes of problem definition and option assessment within participatory integrated assessment (PIA) processes

Comparison of prospective risk estimates for postoperative complications: human vs computer model.

Science.gov (United States)

Glasgow, Robert E; Hawn, Mary T; Hosokawa, Patrick W; Henderson, William G; Min, Sung-Joon; Richman, Joshua S; Tomeh, Majed G; Campbell, Darrell; Neumayer, Leigh A

2014-02-01

Surgical quality improvement tools such as NSQIP are limited in their ability to prospectively affect individual patient care by the retrospective audit and feedback nature of their design. We hypothesized that statistical models using patient preoperative characteristics could prospectively provide risk estimates of postoperative adverse events comparable to risk estimates provided by experienced surgeons, and could be useful for stratifying preoperative assessment of patient risk. This was a prospective observational cohort. Using previously developed models for 30-day postoperative mortality, overall morbidity, cardiac, thromboembolic, pulmonary, renal, and surgical site infection (SSI) complications, model and surgeon estimates of risk were compared with each other and with actual 30-day outcomes. The study cohort included 1,791 general surgery patients operated on between June 2010 and January 2012. Observed outcomes were mortality (0.2%), overall morbidity (8.2%), and pulmonary (1.3%), cardiac (0.3%), thromboembolism (0.2%), renal (0.4%), and SSI (3.8%) complications. Model and surgeon risk estimates showed significant correlation (p risk for overall morbidity to be low, the model-predicted risk and observed morbidity rates were 2.8% and 4.1%, respectively, compared with 10% and 18% in perceived high risk patients. Patients in the highest quartile of model-predicted risk accounted for 75% of observed mortality and 52% of morbidity. Across a broad range of general surgical operations, we confirmed that the model risk estimates are in fairly good agreement with risk estimates of experienced surgeons. Using these models prospectively can identify patients at high risk for morbidity and mortality, who could then be targeted for intervention to reduce postoperative complications. Published by Elsevier Inc.

Computer Support of Groups: Theory-Based Models for GDSS Research

OpenAIRE

V. Srinivasan Rao; Sirkka L. Jarvenpaa

1991-01-01

Empirical research in the area of computer support of groups is characterized by inconsistent results across studies. This paper attempts to reconcile the inconsistencies by linking the ad hoc reasoning in the studies to existing theories of communication, minority influence and human information processing. Contingency models are then presented based on the theories discussed. The paper concludes by discussing the linkages between the current work and other recently published integrations of...

Full 3-D OCT-based pseudophakic custom computer eye model

Science.gov (United States)

Sun, M.; Pérez-Merino, P.; Martinez-Enriquez, E.; Velasco-Ocana, M.; Marcos, S.

2016-01-01

We compared measured wave aberrations in pseudophakic eyes implanted with aspheric intraocular lenses (IOLs) with simulated aberrations from numerical ray tracing on customized computer eye models, built using quantitative 3-D OCT-based patient-specific ocular geometry. Experimental and simulated aberrations show high correlation (R = 0.93; poptical geometrical and surgically-related factors to image quality, and are an excellent tool for characterizing and improving cataract surgery. PMID:27231608

Computer Modeling and Simulation

Energy Technology Data Exchange (ETDEWEB)

Pronskikh, V. S. [Fermilab

2014-05-09

Verification and validation of computer codes and models used in simulation are two aspects of the scientific practice of high importance and have recently been discussed by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to model’s relation to the real world and its intended use. It has been argued that because complex simulations are generally not transparent to a practitioner, the Duhem problem can arise for verification and validation due to their entanglement; such an entanglement makes it impossible to distinguish whether a coding error or model’s general inadequacy to its target should be blamed in the case of the model failure. I argue that in order to disentangle verification and validation, a clear distinction between computer modeling (construction of mathematical computer models of elementary processes) and simulation (construction of models of composite objects and processes by means of numerical experimenting with them) needs to be made. Holding on to that distinction, I propose to relate verification (based on theoretical strategies such as inferences) to modeling and validation, which shares the common epistemology with experimentation, to simulation. To explain reasons of their intermittent entanglement I propose a weberian ideal-typical model of modeling and simulation as roles in practice. I suggest an approach to alleviate the Duhem problem for verification and validation generally applicable in practice and based on differences in epistemic strategies and scopes

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

Science.gov (United States)

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Component Degradation Susceptibilities As The Bases For Modeling Reactor Aging Risk

International Nuclear Information System (INIS)

Unwin, Stephen D.; Lowry, Peter P.; Toyooka, Michael Y.

2010-01-01

The extension of nuclear power plant operating licenses beyond 60 years in the United States will be necessary if we are to meet national energy needs while addressing the issues of carbon and climate. Characterizing the operating risks associated with aging reactors is problematic because the principal tool for risk-informed decision-making, Probabilistic Risk Assessment (PRA), is not ideally-suited to addressing aging systems. The components most likely to drive risk in an aging reactor - the passives - receive limited treatment in PRA, and furthermore, standard PRA methods are based on the assumption of stationary failure rates: a condition unlikely to be met in an aging system. A critical barrier to modeling passives aging on the wide scale required for a PRA is that there is seldom sufficient field data to populate parametric failure models, and nor is there the availability of practical physics models to predict out-year component reliability. The methodology described here circumvents some of these data and modeling needs by using materials degradation metrics, integrated with conventional PRA models, to produce risk importance measures for specific aging mechanisms and component types. We suggest that these measures have multiple applications, from the risk-screening of components to the prioritization of materials research.

Forewarning model for water pollution risk based on Bayes theory.

Science.gov (United States)

Zhao, Jun; Jin, Juliang; Guo, Qizhong; Chen, Yaqian; Lu, Mengxiong; Tinoco, Luis

2014-02-01

In order to reduce the losses by water pollution, forewarning model for water pollution risk based on Bayes theory was studied. This model is built upon risk indexes in complex systems, proceeding from the whole structure and its components. In this study, the principal components analysis is used to screen out index systems. Hydrological model is employed to simulate index value according to the prediction principle. Bayes theory is adopted to obtain posterior distribution by prior distribution with sample information which can make samples' features preferably reflect and represent the totals to some extent. Forewarning level is judged on the maximum probability rule, and then local conditions for proposing management strategies that will have the effect of transforming heavy warnings to a lesser degree. This study takes Taihu Basin as an example. After forewarning model application and vertification for water pollution risk from 2000 to 2009 between the actual and simulated data, forewarning level in 2010 is given as a severe warning, which is well coincide with logistic curve. It is shown that the model is rigorous in theory with flexible method, reasonable in result with simple structure, and it has strong logic superiority and regional adaptability, providing a new way for warning water pollution risk.

Computer - based modeling in extract sciences research -III ...

African Journals Online (AJOL)

Molecular modeling techniques have been of great applicability in the study of the biological sciences and other exact science fields like agriculture, mathematics, computer science and the like. In this write up, a list of computer programs for predicting, for instance, the structure of proteins has been provided. Discussions on ...

Nuclear fuel cycle risk assessment: survey and computer compilation of risk-related literature

International Nuclear Information System (INIS)

Yates, K.R.; Schreiber, A.M.; Rudolph, A.W.

1982-10-01

The US Nuclear Regulatory Commission has initiated the Fuel Cycle Risk Assessment Program to provide risk assessment methods for assistance in the regulatory process for nuclear fuel cycle facilities other than reactors. Both the once-through cycle and plutonium recycle are being considered. A previous report generated by this program defines and describes fuel cycle facilities, or elements, considered in the program. This report, the second from the program, describes the survey and computer compilation of fuel cycle risk-related literature. Sources of available information on the design, safety, and risk associated with the defined set of fuel cycle elements were searched and documents obtained were catalogued and characterized with respect to fuel cycle elements and specific risk/safety information. Both US and foreign surveys were conducted. Battelle's computer-based BASIS information management system was used to facilitate the establishment of the literature compilation. A complete listing of the literature compilation and several useful indexes are included. Future updates of the literature compilation will be published periodically. 760 annotated citations are included

Dealing with project complexity by matrix-based propagation modelling for project risk analysis

OpenAIRE

Fang , Chao; Marle , Franck

2012-01-01

International audience; Engineering projects are facing a growing complexity and are thus exposed to numerous and interdependent risks. In this paper, we present a quantitative method for modelling propagation behaviour in the project risk network. The construction of the network requires the involvement of the project manager and related experts using the Design Structure Matrix (DSM) method. A matrix-based risk propagation model is introduced to calculate risk propagation and thus to re-eva...

Computing risk for oil prospects: principles and programs

International Nuclear Information System (INIS)

Harbaugh, J.W.; Davis, J.C.; Wendebourg, J.

1995-01-01

This volume in the series Computer Methods in the Geosciences examines the challenge of risk assessment, field size distributions, and success, sequence and gambler's ruin. The estimation of the discovery size from the prospect size, outcome probabilities and success ratios, modeling prospects, and mapping properties and uncertainties are reviewed, and discriminating discoveries and dry holes, forecasting cash flow for a prospect, the worth of money, and use of risk analysis tables, decision tables and trees are considered. Appendices cover the installation of the RISK program and user manuals, and two disks are included with the volume. (UK)

Computational Modeling in Liver Surgery

Directory of Open Access Journals (Sweden)

Bruno Christ

2017-11-01

Full Text Available The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.

Epistemic Gameplay and Discovery in Computational Model-Based Inquiry Activities

Science.gov (United States)

Wilkerson, Michelle Hoda; Shareff, Rebecca; Laina, Vasiliki; Gravel, Brian

2018-01-01

In computational modeling activities, learners are expected to discover the inner workings of scientific and mathematical systems: First elaborating their understandings of a given system through constructing a computer model, then "debugging" that knowledge by testing and refining the model. While such activities have been shown to…

An agent-based computational model of the spread of tuberculosis

International Nuclear Information System (INIS)

De Espíndola, Aquino L; Bauch, Chris T; Troca Cabella, Brenno C; Martinez, Alexandre Souto

2011-01-01

In this work we propose an alternative model of the spread of tuberculosis (TB) and the emergence of drug resistance due to the treatment with antibiotics. We implement the simulations by an agent-based model computational approach where the spatial structure is taken into account. The spread of tuberculosis occurs according to probabilities defined by the interactions among individuals. The model was validated by reproducing results already known from the literature in which different treatment regimes yield the emergence of drug resistance. The different patterns of TB spread can be visualized at any time of the system evolution. The implementation details as well as some results of this alternative approach are discussed

The air emissions risk assessment model (AERAM)

International Nuclear Information System (INIS)

Gratt, L.B.

1991-01-01

AERAM is an environmental analysis and power generation station investment decision support tool. AERAM calculates the public health risk (in terms of the lifetime cancers) in the nearby population from pollutants released into the air. AERAM consists of four main subroutines: Emissions, Air, Exposure and Risk. The Emission subroutine uses power plant parameters to calculate the expected release of the pollutants. A coal-fired and oil-fired power plant are currently available. A gas-fired plant model is under preparation. The release of the pollutants into the air is followed by their dispersal in the environment. The dispersion in the Air Subroutine uses the Environmental Protection Agency's model, Industrial Source Complex-Long Term. Additional dispersion models (Industrial Source Complex - Short Term and Cooling Tower Drift) are being implemented for future AERAM versions. The Expose Subroutine uses the ambient concentrations to compute population exposures for the pollutants of concern. The exposures are used with corresponding dose-response model in the Risk Subroutine to estimate both the total population risk and individual risk. The risk for the dispersion receptor-population centroid for the maximum concentration is also calculated for regulatory-population purposes. In addition, automated interfaces with AirTox (an air risk decision model) have been implemented to extend AERAM's steady-state single solution to the decision-under-uncertainty domain. AERAM was used for public health risks, the investment decision for additional pollution control systems based on health risk reductions, and the economics of fuel vs. health risk tradeoffs. AERAM provides that state-of-the-art capability for evaluating the public health impact airborne toxic substances in response to regulations and public concern

Mesh influence on the fire computer modeling in nuclear power plants

Directory of Open Access Journals (Sweden)

D. Lázaro

2018-04-01

Full Text Available Fire computer models allow to study real fire scenarios consequences. Its use in nuclear power plants has increased with the new regulations to apply risk informed performance-based methods for the analysis and design of fire safety solutions. The selection of the cell side factor is very important in these kinds of models. The mesh must establish a compromise between the geometry adjustment, the resolution of the equations and the computation times. This paper aims to study the impact of several cell sizes, using the fire computer model FDS, to evaluate the relative affectation in the final simulation results. In order to validate that, we have employed several scenarios of interest for nuclear power plants. Conclusions offer relevant data for users and show some cell sizes that can be selected to guarantee the quality of the simulations and reduce the results uncertainty.

Computational electromagnetics and model-based inversion a modern paradigm for eddy-current nondestructive evaluation

CERN Document Server

Sabbagh, Harold A; Sabbagh, Elias H; Aldrin, John C; Knopp, Jeremy S

2013-01-01

Computational Electromagnetics and Model-Based Inversion: A Modern Paradigm for Eddy Current Nondestructive Evaluation describes the natural marriage of the computer to eddy-current NDE. Three distinct topics are emphasized in the book: (a) fundamental mathematical principles of volume-integral equations as a subset of computational electromagnetics, (b) mathematical algorithms applied to signal-processing and inverse scattering problems, and (c) applications of these two topics to problems in which real and model data are used. By showing how mathematics and the computer can solve problems more effectively than current analog practices, this book defines the modern technology of eddy-current NDE. This book will be useful to advanced students and practitioners in the fields of computational electromagnetics, electromagnetic inverse-scattering theory, nondestructive evaluation, materials evaluation and biomedical imaging. Users of eddy-current NDE technology in industries as varied as nuclear power, aerospace,...

Evaluating Pharmacokinetic and Pharmacodynamic Interactions with Computational Models in Supporting Cumulative Risk Assessment

Science.gov (United States)

Tan, Yu-Mei; Clewell, Harvey; Campbell, Jerry; Andersen, Melvin

2011-01-01

Simultaneous or sequential exposure to multiple chemicals may cause interactions in the pharmacokinetics (PK) and/or pharmacodynamics (PD) of the individual chemicals. Such interactions can cause modification of the internal or target dose/response of one chemical in the mixture by other chemical(s), resulting in a change in the toxicity from that predicted from the summation of the effects of the single chemicals using dose additivity. In such cases, conducting quantitative cumulative risk assessment for chemicals present as a mixture is difficult. The uncertainties that arise from PK interactions can be addressed by developing physiologically based pharmacokinetic (PBPK) models to describe the disposition of chemical mixtures. Further, PK models can be developed to describe mechanisms of action and tissue responses. In this article, PBPK/PD modeling efforts conducted to investigate chemical interactions at the PK and PD levels are reviewed to demonstrate the use of this predictive modeling framework in assessing health risks associated with exposures to complex chemical mixtures. PMID:21655141

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

International Nuclear Information System (INIS)

Boring, Ronald; Mandelli, Diego; Rasmussen, Martin; Ulrich, Thomas; Groth, Katrina; Smith, Curtis

2016-01-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rasmussen, Martin [Norwegian Univ. of Science and Technology, Trondheim (Norway). Social Research; Herberger, Sarah [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ulrich, Thomas [Idaho National Lab. (INL), Idaho Falls, ID (United States); Groth, Katrina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2016-06-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

A Risk Assessment Example for Soil Invertebrates Using Spatially Explicit Agent-Based Models

DEFF Research Database (Denmark)

Reed, Melissa; Alvarez, Tania; Chelinho, Sonia

2016-01-01

Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier...... population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different...... application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed “overall”], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover...

Blood leakage detection during dialysis therapy based on fog computing with array photocell sensors and heteroassociative memory model

Science.gov (United States)

Wu, Jian-Xing; Huang, Ping-Tzan; Li, Chien-Ming

2018-01-01

Blood leakage and blood loss are serious life-threatening complications occurring during dialysis therapy. These events have been of concerns to both healthcare givers and patients. More than 40% of adult blood volume can be lost in just a few minutes, resulting in morbidities and mortality. The authors intend to propose the design of a warning tool for the detection of blood leakage/blood loss during dialysis therapy based on fog computing with an array of photocell sensors and heteroassociative memory (HAM) model. Photocell sensors are arranged in an array on a flexible substrate to detect blood leakage via the resistance changes with illumination in the visible spectrum of 500–700 nm. The HAM model is implemented to design a virtual alarm unit using electricity changes in an embedded system. The proposed warning tool can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and fog/cloud computing. The animal experimental results (pig blood) will demonstrate the feasibility. PMID:29515815

Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

Science.gov (United States)

Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

2017-06-01

In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

A Fuzzy Comprehensive Evaluation Model for Sustainability Risk Evaluation of PPP Projects

Directory of Open Access Journals (Sweden)

Libiao Bai

2017-10-01

Full Text Available Evaluating the sustainability risk level of public–private partnership (PPP projects can reduce project risk incidents and achieve the sustainable development of the organization. However, the existing studies about PPP projects risk management mainly focus on exploring the impact of financial and revenue risks but ignore the sustainability risks, causing the concept of “sustainability” to be missing while evaluating the risk level of PPP projects. To evaluate the sustainability risk level and achieve the most important objective of providing a reference for the public and private sectors when making decisions on PPP project management, this paper constructs a factor system of sustainability risk of PPP projects based on an extensive literature review and develops a mathematical model based on the methods of fuzzy comprehensive evaluation model (FCEM and failure mode, effects and criticality analysis (FMECA for evaluating the sustainability risk level of PPP projects. In addition, this paper conducts computational experiment based on a questionnaire survey to verify the effectiveness and feasibility of this proposed model. The results suggest that this model is reasonable for evaluating the sustainability risk level of PPP projects. To our knowledge, this paper is the first study to evaluate the sustainability risk of PPP projects, which would not only enrich the theories of project risk management, but also serve as a reference for the public and private sectors for the sustainable planning and development. Keywords: sustainability risk eva

Computationally-optimized bone mechanical modeling from high-resolution structural images.

Directory of Open Access Journals (Sweden)

Jeremy F Magland

Full Text Available Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time, which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM. To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging.

Identification and ranking of the risk factors of cloud computing in State-Owned organizations

Directory of Open Access Journals (Sweden)

Noor Mohammad Yaghoubi

2015-05-01

Full Text Available Rapid development of processing and storage technologies and the success of the Internet have made computing resources cheaper, more powerful and more available than before. This technological trend has enabled the realization of a new computing model called cloud computing. Recently, the State-Owned organizations have begun to utilize cloud computing architectures, platforms, and applications to deliver services and meet constituents’ needs. Despite all of the advantages and opportunities of cloud computing technology, there are so many risks that State-Owned organizations need to know about before their migration to cloud environment. The purpose of this study is to identify and rank the risks factors of cloud computing in State-Owned organizations by making use of IT experts’ opinion. Firstly, by reviewing key articles, a comprehensive list of risks factors were extracted and classified into two categories: tangible and intangible. Then, six experts were interviewed about these risks and their classifications, and 10 risks were identified. After that, process of ranking the risks was done by seeking help from 52 experts and by fuzzy analytic hierarchy process. The results show that experts have identified intangible risks as the most important risks in cloud computing usage by State-Owned organizations. As the results indicate, "data confidentiality" risk has the highest place among the other risks.

Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization

OpenAIRE

Xiaoqin Xu; Xiaoqiao Geng; Yuanqiao Wen

2016-01-01

Ship collision risk index is the basic and important concept in the domain of ship collision avoidance. In this paper, the advantages and deficiencies of the various calculation methods of ship collision risk index are pointed out. Then the ship collision risk model based on complex plane, which can well make up for the deficiencies of the widely-used evaluation model proposed by Kearon.J and Liu ruru is proposed. On this basis, the calculation method of collision risk index under the encount...

Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening.

Science.gov (United States)

Katki, Hormuzd A; Kovalchik, Stephanie A; Petito, Lucia C; Cheung, Li C; Jacobs, Eric; Jemal, Ahmedin; Berg, Christine D; Chaturvedi, Anil K

2018-05-15

Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown. To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts. Population-based prospective studies. United States. Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health-AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort. Model calibration (ratio of model-predicted to observed cases [expected-observed ratio]) and discrimination (area under the curve [AUC]). At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected-observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected-observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the

Generation of three-dimensional prototype models based on cone beam computed tomography

Energy Technology Data Exchange (ETDEWEB)

Lambrecht, J.T.; Berndt, D.C.; Zehnder, M. [University of Basel, Department of Oral Surgery, University Hospital for Oral Surgery, Oral Radiology and Oral Medicine, Basel (Switzerland); Schumacher, R. [University of Applied Sciences Northwestern Switzerland, School of Life Sciences, Institute for Medical and Analytical Technologies, Muttenz (Switzerland)

2009-03-15

The purpose of this study was to generate three-dimensional models based on digital volumetric data that can be used in basic and advanced education. Four sets of digital volumetric data were established by cone beam computed tomography (CBCT) (Accuitomo, J. Morita, Kyoto, Japan). Datasets were exported as Dicom formats and imported into Mimics and Magic software programs to separate the different tissues such as nerve, tooth and bone. These data were transferred to a Polyjet 3D Printing machine (Eden 330, Object, Israel) to generate the models. Three-dimensional prototype models of certain limited anatomical structures as acquired volumetrically were fabricated. Generating three-dimensional models based on CBCT datasets is possible. Automated routine fabrication of these models, with the given infrastructure, is too time-consuming and therefore too expensive. (orig.)

Generation of three-dimensional prototype models based on cone beam computed tomography

International Nuclear Information System (INIS)

Lambrecht, J.T.; Berndt, D.C.; Zehnder, M.; Schumacher, R.

2009-01-01

The purpose of this study was to generate three-dimensional models based on digital volumetric data that can be used in basic and advanced education. Four sets of digital volumetric data were established by cone beam computed tomography (CBCT) (Accuitomo, J. Morita, Kyoto, Japan). Datasets were exported as Dicom formats and imported into Mimics and Magic software programs to separate the different tissues such as nerve, tooth and bone. These data were transferred to a Polyjet 3D Printing machine (Eden 330, Object, Israel) to generate the models. Three-dimensional prototype models of certain limited anatomical structures as acquired volumetrically were fabricated. Generating three-dimensional models based on CBCT datasets is possible. Automated routine fabrication of these models, with the given infrastructure, is too time-consuming and therefore too expensive. (orig.)

Risk based surveillance for vector borne diseases

DEFF Research Database (Denmark)

Bødker, Rene

of samples and hence early detection of outbreaks. Models for vector borne diseases in Denmark have demonstrated dramatic variation in outbreak risk during the season and between years. The Danish VetMap project aims to make these risk based surveillance estimates available on the veterinarians smart phones...... in Northern Europe. This model approach may be used as a basis for risk based surveillance. In risk based surveillance limited resources for surveillance are targeted at geographical areas most at risk and only when the risk is high. This makes risk based surveillance a cost effective alternative...... sample to a diagnostic laboratory. Risk based surveillance models may reduce this delay. An important feature of risk based surveillance models is their ability to continuously communicate the level of risk to veterinarians and hence increase awareness when risk is high. This is essential for submission...

Causal Loop-based Modeling on System Dynamics for Risk Communication

Energy Technology Data Exchange (ETDEWEB)

Lee, Chang Ju [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of); Kang, Kyung Min [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2009-10-15

It is true that a national policy should be based on public confidence, analyzing their recognition and attitude on life safety, since they have very special risk perception characteristics. For achieving effective public consensus regarding a national policy such as nuclear power, we have to utilize a risk communication (hereafter, calls RiCom) process. However, domestic research models on RiCom process do not provide a practical guideline, because most of them are still superficial and stick on an administrative aspect. Also, most of current models have no experience in terms of verification and validation for effective applications to diverse stake holders. This study focuses on public's dynamic mechanism through the modeling on system dynamics, basically utilizing casual loop diagram (CLD) and stock flow diagram (SFD), which regards as a critical technique for decision making in many industrial RiCom models.

Causal Loop-based Modeling on System Dynamics for Risk Communication

International Nuclear Information System (INIS)

Lee, Chang Ju; Kang, Kyung Min

2009-01-01

It is true that a national policy should be based on public confidence, analyzing their recognition and attitude on life safety, since they have very special risk perception characteristics. For achieving effective public consensus regarding a national policy such as nuclear power, we have to utilize a risk communication (hereafter, calls RiCom) process. However, domestic research models on RiCom process do not provide a practical guideline, because most of them are still superficial and stick on an administrative aspect. Also, most of current models have no experience in terms of verification and validation for effective applications to diverse stake holders. This study focuses on public's dynamic mechanism through the modeling on system dynamics, basically utilizing casual loop diagram (CLD) and stock flow diagram (SFD), which regards as a critical technique for decision making in many industrial RiCom models

Life cycle cost-based risk model for energy performance contracting retrofits

Science.gov (United States)

Berghorn, George H.

Buildings account for 41% of the primary energy consumption in the United States, nearly half of which is accounted for by commercial buildings. Among the greatest energy users are those in the municipalities, universities, schools, and hospitals (MUSH) market. Correctional facilities are in the upper half of all commercial building types for energy intensity. Public agencies have experienced reduced capital budgets to fund retrofits; this has led to the increased use of energy performance contracts (EPC), which are implemented by energy services companies (ESCOs). These companies guarantee a minimum amount of energy savings resulting from the retrofit activities, which in essence transfers performance risk from the owner to the contractor. Building retrofits in the MUSH market, especially correctional facilities, are well-suited to EPC, yet despite this potential and their high energy intensities, efficiency improvements lag behind that of other public building types. Complexities in project execution, lack of support for data requests and sub-metering, and conflicting project objectives have been cited as reasons for this lag effect. As a result, project-level risks must be understood in order to support wider adoption of retrofits in the public market, in particular the correctional facility sub-market. The goal of this research is to understand risks related to the execution of energy efficiency retrofits delivered via EPC in the MUSH market. To achieve this goal, in-depth analysis and improved understanding was sought with regard to ESCO risks that are unique to EPC in this market. The proposed work contributes to this understanding by developing a life cycle cost-based risk model to improve project decision making with regard to risk control and reduction. The specific objectives of the research are: (1) to perform an exploratory analysis of the EPC retrofit process and identify key areas of performance risk requiring in-depth analysis; (2) to construct a

Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

Energy Technology Data Exchange (ETDEWEB)

Joe, Jeffrey Clark [Idaho National Lab. (INL), Idaho Falls, ID (United States); Boring, Ronald Laurids [Idaho National Lab. (INL), Idaho Falls, ID (United States); Herberger, Sarah Elizabeth Marie [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-09-01

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS “pathways,” or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with other experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.

Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

International Nuclear Information System (INIS)

Joe, Jeffrey Clark; Boring, Ronald Laurids; Herberger, Sarah Elizabeth Marie; Mandelli, Diego; Smith, Curtis Lee

2015-01-01

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS 'pathways,' or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with other experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.

Methodological Bases for Describing Risks of the Enterprise Business Model in Integrated Reporting

Directory of Open Access Journals (Sweden)

Nesterenko Oksana O.

2017-12-01

Full Text Available The aim of the article is to substantiate the methodological bases for describing the business and accounting risks of an enterprise business model in integrated reporting for their timely detection and assessment, and develop methods for their leveling or minimizing and possible prevention. It is proposed to consider risks in the process of forming integrated reporting from two sides: first, risks that arise in the business model of an organization and should be disclosed in its integrated report; second, accounting risks of integrated reporting, which should be taken into account by members of the cross-sectoral working group and management personnel in the process of forming and promulgating integrated reporting. To develop an adequate accounting and analytical tool for disclosure of information about the risks of the business model and integrated reporting, their leveling or minimization, in the article a terminological analysis of the essence of entrepreneurial and accounting risks is carried out. The entrepreneurial risk is defined as an objective-subjective economic category that characterizes the probability of negative or positive consequences of economic-social-ecological activity within the framework of the business model of an enterprise under uncertainty. The accounting risk is suggested to be understood as the probability of unfavorable consequences as a result of organizational, methodological errors in the integrated accounting system, which present threat to the quality, accuracy and reliability of the reporting information on economic, social and environmental activities in integrated reporting as well as threat of inappropriate decision-making by stakeholders based on the integrated report. For the timely identification of business risks and maximum leveling of the influence of accounting risks on the process of formation and publication of integrated reporting, in the study the place of entrepreneurial and accounting risks in

A Trust-Based Model for Security Cooperating in Vehicular Cloud Computing

Directory of Open Access Journals (Sweden)

Zhipeng Tang

2016-01-01

Full Text Available VCC is a computing paradigm which consists of vehicles cooperating with each other to realize a lot of practical applications, such as delivering packages. Security cooperation is a fundamental research topic in Vehicular Cloud Computing (VCC. Because of the existence of malicious vehicles, the security cooperation has become a challenging issue in VCC. In this paper, a trust-based model for security cooperating, named DBTEC, is proposed to promote vehicles’ security cooperation in VCC. DBTEC combines the indirect trust estimation in Public board and the direct trust estimation in Private board to compute the trust value of vehicles when choosing cooperative partners; a trustworthy cooperation path generating scheme is proposed to ensure the safety of cooperation and increase the cooperation completion rates in VCC. Extensive experiments show that our scheme improves the overall cooperation completion rates by 6~7%.

Process-Based Development of Competence Models to Computer Science Education

Science.gov (United States)

Zendler, Andreas; Seitz, Cornelia; Klaudt, Dieter

2016-01-01

A process model ("cpm.4.CSE") is introduced that allows the development of competence models in computer science education related to curricular requirements. It includes eight subprocesses: (a) determine competence concept, (b) determine competence areas, (c) identify computer science concepts, (d) assign competence dimensions to…

DualTrust: A Trust Management Model for Swarm-Based Autonomic Computing Systems

Energy Technology Data Exchange (ETDEWEB)

Maiden, Wendy M. [Washington State Univ., Pullman, WA (United States)

2010-05-01

Trust management techniques must be adapted to the unique needs of the application architectures and problem domains to which they are applied. For autonomic computing systems that utilize mobile agents and ant colony algorithms for their sensor layer, certain characteristics of the mobile agent ant swarm -- their lightweight, ephemeral nature and indirect communication -- make this adaptation especially challenging. This thesis looks at the trust issues and opportunities in swarm-based autonomic computing systems and finds that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust management problem becomes much more scalable and still serves to protect the swarm. After analyzing the applicability of trust management research as it has been applied to architectures with similar characteristics, this thesis specifies the required characteristics for trust management mechanisms used to monitor the trustworthiness of entities in a swarm-based autonomic computing system and describes a trust model that meets these requirements.

Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

Directory of Open Access Journals (Sweden)

Hui Chen

2014-01-01

Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

Efficacy of computer technology-based HIV prevention interventions: a meta-analysis.

Science.gov (United States)

Noar, Seth M; Black, Hulda G; Pierce, Larson B

2009-01-02

To conduct a meta-analysis of computer technology-based HIV prevention behavioral interventions aimed at increasing condom use among a variety of at-risk populations. Systematic review and meta-analysis of existing published and unpublished studies testing computer-based interventions. Meta-analytic techniques were used to compute and aggregate effect sizes for 12 randomized controlled trials that met inclusion criteria. Variables that had the potential to moderate intervention efficacy were also tested. The overall mean weighted effect size for condom use was d = 0.259 (95% confidence interval = 0.201, 0.317; Z = 8.74, P partners, and incident sexually transmitted diseases. In addition, interventions were significantly more efficacious when they were directed at men or women (versus mixed sex groups), utilized individualized tailoring, used a Stages of Change model, and had more intervention sessions. Computer technology-based HIV prevention interventions have similar efficacy to more traditional human-delivered interventions. Given their low cost to deliver, ability to customize intervention content, and flexible dissemination channels, they hold much promise for the future of HIV prevention.

Review of calculational models and computer codes for environmental dose assessment of radioactive releases

International Nuclear Information System (INIS)

Strenge, D.L.; Watson, E.C.; Droppo, J.G.

1976-06-01

The development of technological bases for siting nuclear fuel cycle facilities requires calculational models and computer codes for the evaluation of risks and the assessment of environmental impact of radioactive effluents. A literature search and review of available computer programs revealed that no one program was capable of performing all of the great variety of calculations (i.e., external dose, internal dose, population dose, chronic release, accidental release, etc.). Available literature on existing computer programs has been reviewed and a description of each program reviewed is given

Review of calculational models and computer codes for environmental dose assessment of radioactive releases

Energy Technology Data Exchange (ETDEWEB)

Strenge, D.L.; Watson, E.C.; Droppo, J.G.

1976-06-01

The development of technological bases for siting nuclear fuel cycle facilities requires calculational models and computer codes for the evaluation of risks and the assessment of environmental impact of radioactive effluents. A literature search and review of available computer programs revealed that no one program was capable of performing all of the great variety of calculations (i.e., external dose, internal dose, population dose, chronic release, accidental release, etc.). Available literature on existing computer programs has been reviewed and a description of each program reviewed is given.

Programming Non-Trivial Algorithms in the Measurement Based Quantum Computation Model

Energy Technology Data Exchange (ETDEWEB)

Alsing, Paul [United States Air Force Research Laboratory, Wright-Patterson Air Force Base; Fanto, Michael [United States Air Force Research Laboratory, Wright-Patterson Air Force Base; Lott, Capt. Gordon [United States Air Force Research Laboratory, Wright-Patterson Air Force Base; Tison, Christoper C. [United States Air Force Research Laboratory, Wright-Patterson Air Force Base

2014-01-01

We provide a set of prescriptions for implementing a quantum circuit model algorithm as measurement based quantum computing (MBQC) algorithm1, 2 via a large cluster state. As means of illustration we draw upon our numerical modeling experience to describe a large graph state capable of searching a logical 8 element list (a non-trivial version of Grover's algorithm3 with feedforward). We develop several prescriptions based on analytic evaluation of cluster states and graph state equations which can be generalized into any circuit model operations. Such a resulting cluster state will be able to carry out the desired operation with appropriate measurements and feed forward error correction. We also discuss the physical implementation and the analysis of the principal 3-qubit entangling gate (Toffoli) required for a non-trivial feedforward realization of an 8-element Grover search algorithm.

Computationally Modeling Interpersonal Trust

Directory of Open Access Journals (Sweden)

Jin Joo eLee

2013-12-01

Full Text Available We present a computational model capable of predicting—above human accuracy—the degree of trust a person has toward their novel partner by observing the trust-related nonverbal cues expressed in their social interaction. We summarize our prior work, in which we identify nonverbal cues that signal untrustworthy behavior and also demonstrate the human mind’s readiness to interpret those cues to assess the trustworthiness of a social robot. We demonstrate that domain knowledge gained from our prior work using human-subjects experiments, when incorporated into the feature engineering process, permits a computational model to outperform both human predictions and a baseline model built in naivete' of this domain knowledge. We then present the construction of hidden Markov models to incorporate temporal relationships among the trust-related nonverbal cues. By interpreting the resulting learned structure, we observe that models built to emulate different levels of trust exhibit different sequences of nonverbal cues. From this observation, we derived sequence-based temporal features that further improve the accuracy of our computational model. Our multi-step research process presented in this paper combines the strength of experimental manipulation and machine learning to not only design a computational trust model but also to further our understanding of the dynamics of interpersonal trust.

Trust models in ubiquitous computing.

Science.gov (United States)

Krukow, Karl; Nielsen, Mogens; Sassone, Vladimiro

2008-10-28

We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models.

Modeling issues in nuclear plant fire risk analysis

International Nuclear Information System (INIS)

Siu, N.

1989-01-01

This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

Computational Modeling of Cobalt-based Water Oxidation: Current Status and Future Challenges

Science.gov (United States)

Schilling, Mauro; Luber, Sandra

2018-04-01

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysis. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability towards real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions.

Computational Modeling of Cobalt-Based Water Oxidation: Current Status and Future Challenges

Directory of Open Access Journals (Sweden)

Mauro Schilling

2018-04-01

Full Text Available A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context, mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysts. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability toward real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions.

Measuring attitudes towards nuclear and technological risks (computer programs in SPSS language)

International Nuclear Information System (INIS)

Leonin, T.V. Jr.

1981-04-01

A number of methodologies have been developed for measuring public attitudes towards nuclear and other technological risks. The Fishbein model, as modified by the IAEA Risk Assessment group, and which was found to be applicable for Philippine public attitude measurements, is briefly explained together with two other models which are utilized for comparative correlations. A step by step guide on the procedures involved and the calculations required in measuring and analyzing attitude using these models is likewise described, with special emphasis on the computer processing aspect. The use of the Statistical Package for the Social Sciences (SPSS) in the analysis is also described and a number of computer programs in SPSS for the various statistical calculations required in the analysis is presented. (author)

Novel Schemes for Measurement-Based Quantum Computation

International Nuclear Information System (INIS)

Gross, D.; Eisert, J.

2007-01-01

We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics--based on finitely correlated or projected entangled pair states--to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems

Novel schemes for measurement-based quantum computation.

Science.gov (United States)

Gross, D; Eisert, J

2007-06-01

We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics-based on finitely correlated or projected entangled pair states-to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems.

Modeling Computer Virus and Its Dynamics

Directory of Open Access Journals (Sweden)

Mei Peng

2013-01-01

Full Text Available Based on that the computer will be infected by infected computer and exposed computer, and some of the computers which are in suscepitible status and exposed status can get immunity by antivirus ability, a novel coumputer virus model is established. The dynamic behaviors of this model are investigated. First, the basic reproduction number R0, which is a threshold of the computer virus spreading in internet, is determined. Second, this model has a virus-free equilibrium P0, which means that the infected part of the computer disappears, and the virus dies out, and P0 is a globally asymptotically stable equilibrium if R01 then this model has only one viral equilibrium P*, which means that the computer persists at a constant endemic level, and P* is also globally asymptotically stable. Finally, some numerical examples are given to demonstrate the analytical results.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Directory of Open Access Journals (Sweden)

Samreen Laghari

Full Text Available Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT implies an inherent difficulty in modeling problems.It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS. The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC framework to model a Complex communication network problem.We use Exploratory Agent-based Modeling (EABM, as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy.The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

Science.gov (United States)

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Applying a Global Sensitivity Analysis Workflow to Improve the Computational Efficiencies in Physiologically-Based Pharmacokinetic Modeling

Directory of Open Access Journals (Sweden)

Nan-Hung Hsieh

2018-06-01

Full Text Available Traditionally, the solution to reduce parameter dimensionality in a physiologically-based pharmacokinetic (PBPK model is through expert judgment. However, this approach may lead to bias in parameter estimates and model predictions if important parameters are fixed at uncertain or inappropriate values. The purpose of this study was to explore the application of global sensitivity analysis (GSA to ascertain which parameters in the PBPK model are non-influential, and therefore can be assigned fixed values in Bayesian parameter estimation with minimal bias. We compared the elementary effect-based Morris method and three variance-based Sobol indices in their ability to distinguish “influential” parameters to be estimated and “non-influential” parameters to be fixed. We illustrated this approach using a published human PBPK model for acetaminophen (APAP and its two primary metabolites APAP-glucuronide and APAP-sulfate. We first applied GSA to the original published model, comparing Bayesian model calibration results using all the 21 originally calibrated model parameters (OMP, determined by “expert judgment”-based approach vs. the subset of original influential parameters (OIP, determined by GSA from the OMP. We then applied GSA to all the PBPK parameters, including those fixed in the published model, comparing the model calibration results using this full set of 58 model parameters (FMP vs. the full set influential parameters (FIP, determined by GSA from FMP. We also examined the impact of different cut-off points to distinguish the influential and non-influential parameters. We found that Sobol indices calculated by eFAST provided the best combination of reliability (consistency with other variance-based methods and efficiency (lowest computational cost to achieve convergence in identifying influential parameters. We identified several originally calibrated parameters that were not influential, and could be fixed to improve computational

Mapping the Most Significant Computer Hacking Events to a Temporal Computer Attack Model

OpenAIRE

Heerden , Renier ,; Pieterse , Heloise; Irwin , Barry

2012-01-01

Part 4: Section 3: ICT for Peace and War; International audience; This paper presents eight of the most significant computer hacking events (also known as computer attacks). These events were selected because of their unique impact, methodology, or other properties. A temporal computer attack model is presented that can be used to model computer based attacks. This model consists of the following stages: Target Identification, Reconnaissance, Attack, and Post-Attack Reconnaissance stages. The...

A Cloud Computing Approach to Personal Risk Management: The Open Hazards Group

Science.gov (United States)

Graves, W. R.; Holliday, J. R.; Rundle, J. B.

2010-12-01

are then used in a computationally efficient workflow to produce real-time estimates of damage and loss for individual structures. All models are based on techniques that either have been published in the literature or will soon be published. Using these results, members of the public can gain an appreciation of their risk of exposure to damage from destructive earthquakes, information that has heretofore only been available to a few members of the financial and insurance industries.

Electromagnetic Computation and Visualization of Transmission Particle Model and Its Simulation Based on GPU

Directory of Open Access Journals (Sweden)

Yingnian Wu

2014-01-01

Full Text Available Electromagnetic calculation plays an important role in both military and civic fields. Some methods and models proposed for calculation of electromagnetic wave propagation in a large range bring heavy burden in CPU computation and also require huge amount of memory. Using the GPU to accelerate computation and visualization can reduce the computational burden on the CPU. Based on forward ray-tracing method, a transmission particle model (TPM for calculating electromagnetic field is presented to combine the particle method. The movement of a particle obeys the principle of the propagation of electromagnetic wave, and then the particle distribution density in space reflects the electromagnetic distribution status. The algorithm with particle transmission, movement, reflection, and diffraction is described in detail. Since the particles in TPM are completely independent, it is very suitable for the parallel computing based on GPU. Deduction verification of TPM with the electric dipole antenna as the transmission source is conducted to prove that the particle movement itself represents the variation of electromagnetic field intensity caused by diffusion. Finally, the simulation comparisons are made against the forward and backward ray-tracing methods. The simulation results verified the effectiveness of the proposed method.

A New Computationally Frugal Method For Sensitivity Analysis Of Environmental Models

Science.gov (United States)

Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A.; Teuling, R.; Borgonovo, E.; Uijlenhoet, R.

2013-12-01

Effective and efficient parameter sensitivity analysis methods are crucial to understand the behaviour of complex environmental models and use of models in risk assessment. This paper proposes a new computationally frugal method for analyzing parameter sensitivity: the Distributed Evaluation of Local Sensitivity Analysis (DELSA). The DELSA method can be considered a hybrid of local and global methods, and focuses explicitly on multiscale evaluation of parameter sensitivity across the parameter space. Results of the DELSA method are compared with the popular global, variance-based Sobol' method and the delta method. We assess the parameter sensitivity of both (1) a simple non-linear reservoir model with only two parameters, and (2) five different "bucket-style" hydrologic models applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both the synthetic and real-world examples, the global Sobol' method and the DELSA method provide similar sensitivities, with the DELSA method providing more detailed insight at much lower computational cost. The ability to understand how sensitivity measures vary through parameter space with modest computational requirements provides exciting new opportunities.

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Science.gov (United States)

Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

2016-02-01

The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - the Portuguese continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns ("hot spots") or developing sensitivity analysis to specific conditions, whereas real

Sierra toolkit computational mesh conceptual model

International Nuclear Information System (INIS)

Baur, David G.; Edwards, Harold Carter; Cochran, William K.; Williams, Alan B.; Sjaardema, Gregory D.

2010-01-01

The Sierra Toolkit computational mesh is a software library intended to support massively parallel multi-physics computations on dynamically changing unstructured meshes. This domain of intended use is inherently complex due to distributed memory parallelism, parallel scalability, heterogeneity of physics, heterogeneous discretization of an unstructured mesh, and runtime adaptation of the mesh. Management of this inherent complexity begins with a conceptual analysis and modeling of this domain of intended use; i.e., development of a domain model. The Sierra Toolkit computational mesh software library is designed and implemented based upon this domain model. Software developers using, maintaining, or extending the Sierra Toolkit computational mesh library must be familiar with the concepts/domain model presented in this report.

Computational red teaming risk analytics of big-data-to-decisions intelligent systems

CERN Document Server

Abbass, Hussein A

2015-01-01

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blend...

Engineering models for catastrophe risk and their application to insurance

Science.gov (United States)

Dong, Weimin

2002-06-01

Internationally earthquake insurance, like all other insurance (fire, auto), adopted actuarial approach in the past, which is, based on historical loss experience to determine insurance rate. Due to the fact that earthquake is a rare event with severe consequence, irrational determination of premium rate and lack of understanding scale of potential loss led to many insurance companies insolvent after Northridge earthquake in 1994. Along with recent advances in earth science, computer science and engineering, computerized loss estimation methodologies based on first principles have been developed to the point that losses from destructive earthquakes can be quantified with reasonable accuracy using scientific modeling techniques. This paper intends to introduce how engineering models can assist to quantify earthquake risk and how insurance industry can use this information to manage their risk in the United States and abroad.

Improvements in fast-response flood modeling: desktop parallel computing and domain tracking

Energy Technology Data Exchange (ETDEWEB)

Judi, David R [Los Alamos National Laboratory; Mcpherson, Timothy N [Los Alamos National Laboratory; Burian, Steven J [UNIV. OF UTAH

2009-01-01

It is becoming increasingly important to have the ability to accurately forecast flooding, as flooding accounts for the most losses due to natural disasters in the world and the United States. Flood inundation modeling has been dominated by one-dimensional approaches. These models are computationally efficient and are considered by many engineers to produce reasonably accurate water surface profiles. However, because the profiles estimated in these models must be superimposed on digital elevation data to create a two-dimensional map, the result may be sensitive to the ability of the elevation data to capture relevant features (e.g. dikes/levees, roads, walls, etc...). Moreover, one-dimensional models do not explicitly represent the complex flow processes present in floodplains and urban environments and because two-dimensional models based on the shallow water equations have significantly greater ability to determine flow velocity and direction, the National Research Council (NRC) has recommended that two-dimensional models be used over one-dimensional models for flood inundation studies. This paper has shown that two-dimensional flood modeling computational time can be greatly reduced through the use of Java multithreading on multi-core computers which effectively provides a means for parallel computing on a desktop computer. In addition, this paper has shown that when desktop parallel computing is coupled with a domain tracking algorithm, significant computation time can be eliminated when computations are completed only on inundated cells. The drastic reduction in computational time shown here enhances the ability of two-dimensional flood inundation models to be used as a near-real time flood forecasting tool, engineering, design tool, or planning tool. Perhaps even of greater significance, the reduction in computation time makes the incorporation of risk and uncertainty/ensemble forecasting more feasible for flood inundation modeling (NRC 2000; Sayers et al

Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization

Directory of Open Access Journals (Sweden)

Xiaoqin Xu

2016-07-01

Full Text Available Ship collision risk index is the basic and important concept in the domain of ship collision avoidance. In this paper, the advantages and deficiencies of the various calculation methods of ship collision risk index are pointed out. Then the ship collision risk model based on complex plane, which can well make up for the deficiencies of the widely-used evaluation model proposed by Kearon.J and Liu ruru is proposed. On this basis, the calculation method of collision risk index under the encountering situation of multi-ships is constructed, then the three-dimensional image and spatial curve of the risk index are figured out. Finally, single chip microcomputer is used to realize the model. And attaching this single chip microcomputer to ARPA is helpful to the decision-making of the marine navigators.

A novel cost based model for energy consumption in cloud computing.

Science.gov (United States)

Horri, A; Dastghaibyfard, Gh

2015-01-01

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment.

Towards Cloud Computing SLA Risk Management: Issues and Challenges

OpenAIRE

Morin, Jean-Henry; Aubert, Jocelyn; Gateau, Benjamin

2012-01-01

Cloud Computing has become mainstream technology offering a commoditized approach to software, platform and infrastructure as a service over the Internet on a global scale. This raises important new security issues beyond traditional perimeter based approaches. This paper attempts to identify these issues and their corresponding challenges, proposing to use risk and Service Level Agreement (SLA) management as the basis for a service level framework to improve governance, risk and compliance i...

Time-based collision risk modeling for air traffic management

Science.gov (United States)

Bell, Alan E.

Since the emergence of commercial aviation in the early part of last century, economic forces have driven a steadily increasing demand for air transportation. Increasing density of aircraft operating in a finite volume of airspace is accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any collision risk management system is to project conflicts and provide operators with sufficient opportunity to recognize potential collisions and take necessary actions to avoid them. It is therefore the assertion of this research that the currency of collision risk management is time. Future Air Traffic Management Systems are being designed around the foundational principle of four dimensional trajectory based operations, a method that replaces legacy first-come, first-served sequencing priorities with time-based reservations throughout the airspace system. This research will demonstrate that if aircraft are to be sequenced in four dimensions, they must also be separated in four dimensions. In order to separate aircraft in four dimensions, time must emerge as the primary tool by which air traffic is managed. A functional relationship exists between the time-based performance of aircraft, the interval between aircraft scheduled to cross some three dimensional point in space, and the risk of collision. This research models that relationship and presents two key findings. First, a method is developed by which the ability of an aircraft to meet a required time of arrival may be expressed as a robust standard for both industry and operations. Second, a method by which airspace system capacity may be increased while maintaining an acceptable level of collision risk is presented and demonstrated for the purpose of formulating recommendations for procedures

Experimental and Computer Modelling Studies of Metastability of Amorphous Silicon Based Solar Cells

NARCIS (Netherlands)

Munyeme, Geoffrey

2003-01-01

We present a combination of experimental and computer modelling studies of the light induced degradation in the performance of amorphous silicon based single junction solar cells. Of particular interest in this study is the degradation kinetics of different types of amorphous silicon single junction

Risk assessment of storm surge disaster based on numerical models and remote sensing

Science.gov (United States)

Liu, Qingrong; Ruan, Chengqing; Zhong, Shan; Li, Jian; Yin, Zhonghui; Lian, Xihu

2018-06-01

Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

A quantitative risk-based model for reasoning over critical system properties

Science.gov (United States)

Feather, M. S.

2002-01-01

This position paper suggests the use of a quantitative risk-based model to help support reeasoning and decision making that spans many of the critical properties such as security, safety, survivability, fault tolerance, and real-time.

Reliability Analysis Based on a Jump Diffusion Model with Two Wiener Processes for Cloud Computing with Big Data

Directory of Open Access Journals (Sweden)

Yoshinobu Tamura

2015-06-01

Full Text Available At present, many cloud services are managed by using open source software, such as OpenStack and Eucalyptus, because of the unification management of data, cost reduction, quick delivery and work savings. The operation phase of cloud computing has a unique feature, such as the provisioning processes, the network-based operation and the diversity of data, because the operation phase of cloud computing changes depending on many external factors. We propose a jump diffusion model with two-dimensional Wiener processes in order to consider the interesting aspects of the network traffic and big data on cloud computing. In particular, we assess the stability of cloud software by using the sample paths obtained from the jump diffusion model with two-dimensional Wiener processes. Moreover, we discuss the optimal maintenance problem based on the proposed jump diffusion model. Furthermore, we analyze actual data to show numerical examples of dependability optimization based on the software maintenance cost considering big data on cloud computing.

Exploratory analysis regarding the domain definitions for computer based analytical models

Science.gov (United States)

Raicu, A.; Oanta, E.; Barhalescu, M.

2017-08-01

Our previous computer based studies dedicated to structural problems using analytical methods defined the composite cross section of a beam as a result of Boolean operations with so-called ‘simple’ shapes. Using generalisations, in the class of the ‘simple’ shapes were included areas bounded by curves approximated using spline functions and areas approximated as polygons. However, particular definitions lead to particular solutions. In order to ascend above the actual limitations, we conceived a general definition of the cross sections that are considered now calculus domains consisting of several subdomains. The according set of input data use complex parameterizations. This new vision allows us to naturally assign a general number of attributes to the subdomains. In this way there may be modelled new phenomena that use map-wise information, such as the metal alloys equilibrium diagrams. The hierarchy of the input data text files that use the comma-separated-value format and their structure are also presented and discussed in the paper. This new approach allows us to reuse the concepts and part of the data processing software instruments already developed. The according software to be subsequently developed will be modularised and generalised in order to be used in the upcoming projects that require rapid development of computer based models.

Stochastic models in risk theory and management accounting

NARCIS (Netherlands)

Brekelmans, R.C.M.

2000-01-01

This thesis deals with stochastic models in two fields: risk theory and management accounting. Firstly, two extensions of the classical risk process are analyzed. A method is developed that computes bounds of the probability of ruin for the classical risk rocess extended with a constant interest

Plant and control system reliability and risk model

International Nuclear Information System (INIS)

Niemelae, I.M.

1986-01-01

A new reliability modelling technique for control systems and plants is demonstrated. It is based on modified boolean algebra and it has been automated into an efficient computer code called RELVEC. The code is useful for getting an overall view of the reliability parameters or for an in-depth reliability analysis, which is essential in risk analysis, where the model must be capable of answering to specific questions like: 'What is the probability of this temperature limiter to provide a false alarm', or 'what is the probability of air pressure in this subsystem to drop below lower limit'. (orig./DG)

Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

Science.gov (United States)

Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

2018-03-01

Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

A computational model of in vitro angiogenesis based on extracellular matrix fibre orientation.

Science.gov (United States)

Edgar, Lowell T; Sibole, Scott C; Underwood, Clayton J; Guilkey, James E; Weiss, Jeffrey A

2013-01-01

Recent interest in the process of vascularisation within the biomedical community has motivated numerous new research efforts focusing on the process of angiogenesis. Although the role of chemical factors during angiogenesis has been well documented, the role of mechanical factors, such as the interaction between angiogenic vessels and the extracellular matrix, remains poorly understood. In vitro methods for studying angiogenesis exist; however, measurements available using such techniques often suffer from limited spatial and temporal resolutions. For this reason, computational models have been extensively employed to investigate various aspects of angiogenesis. This paper outlines the formulation and validation of a simple and robust computational model developed to accurately simulate angiogenesis based on length, branching and orientation morphometrics collected from vascularised tissue constructs. Microvessels were represented as a series of connected line segments. The morphology of the vessels was determined by a linear combination of the collagen fibre orientation, the vessel density gradient and a random walk component. Excellent agreement was observed between computational and experimental morphometric data over time. Computational predictions of microvessel orientation within an anisotropic matrix correlated well with experimental data. The accuracy of this modelling approach makes it a valuable platform for investigating the role of mechanical interactions during angiogenesis.

Parallel computing in enterprise modeling.

Energy Technology Data Exchange (ETDEWEB)

Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.; Vanderveen, Keith; Ray, Jaideep; Heath, Zach; Allan, Benjamin A.

2008-08-01

This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priori ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.

Evidence Report: Risk of Inadequate Human-Computer Interaction

Science.gov (United States)

Holden, Kritina; Ezer, Neta; Vos, Gordon

2013-01-01

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Performance Models and Risk Management in Communications Systems

CERN Document Server

Harrison, Peter; Rüstem, Berç

2011-01-01

This volume covers recent developments in the design, operation, and management of telecommunication and computer network systems in performance engineering and addresses issues of uncertainty, robustness, and risk. Uncertainty regarding loading and system parameters leads to challenging optimization and robustness issues. Stochastic modeling combined with optimization theory ensures the optimum end-to-end performance of telecommunication or computer network systems. In view of the diverse design options possible, supporting models have many adjustable parameters and choosing the best set for a particular performance objective is delicate and time-consuming. An optimization based approach determines the optimal possible allocation for these parameters. Researchers and graduate students working at the interface of telecommunications and operations research will benefit from this book. Due to the practical approach, this book will also serve as a reference tool for scientists and engineers in telecommunication ...

Questioning the quantity equation using an agent-based computational model

DEFF Research Database (Denmark)

Bruun, Charlotte

2000-01-01

by Stutzel (1954), argues that the functional relationship may as well be negative. Even focusing the money needed to carry out transactions, there is no immediate answer to the question of the functional relationship between trade turnover and money demand. An agent-based computational model is used......In the literature we find two opposing hypotheses relating the volume of money to the volume of transactions or national income. The classic hypothesis, implicitly entailed in the quantity equation, argues that this relation must be positive, while an opposing hypothesis, most strongly presented...

A Lévy HJM Multiple-Curve Model with Application to CVA Computation

DEFF Research Database (Denmark)

Crépey, Stéphane; Grbac, Zorana; Ngor, Nathalie

2015-01-01

, the calibration to OTM swaptions guaranteeing that the model correctly captures volatility smile effects and the calibration to co-terminal ATM swaptions ensuring an appropriate term structure of the volatility in the model. To account for counterparty risk and funding issues, we use the calibrated multiple......-curve model as an underlying model for CVA computation. We follow a reduced-form methodology through which the problem of pricing the counterparty risk and funding costs can be reduced to a pre-default Markovian BSDE, or an equivalent semi-linear PDE. As an illustration, we study the case of a basis swap...... and a related swaption, for which we compute the counterparty risk and funding adjustments...

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

Science.gov (United States)

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Spintronics-based computing

CERN Document Server

Prenat, Guillaume

2015-01-01

This book provides a comprehensive introduction to spintronics-based computing for the next generation of ultra-low power/highly reliable logic, which is widely considered a promising candidate to replace conventional, pure CMOS-based logic. It will cover aspects from device to system-level, including magnetic memory cells, device modeling, hybrid circuit structure, design methodology, CAD tools, and technological integration methods. This book is accessible to a variety of readers and little or no background in magnetism and spin electronics are required to understand its content.  The multidisciplinary team of expert authors from circuits, devices, computer architecture, CAD and system design reveal to readers the potential of spintronics nanodevices to reduce power consumption, improve reliability and enable new functionality.  .

Model Selection and Risk Estimation with Applications to Nonlinear Ordinary Differential Equation Systems

DEFF Research Database (Denmark)

Mikkelsen, Frederik Vissing

eective computational tools for estimating unknown structures in dynamical systems, such as gene regulatory networks, which may be used to predict downstream eects of interventions in the system. A recommended algorithm based on the computational tools is presented and thoroughly tested in various......Broadly speaking, this thesis is devoted to model selection applied to ordinary dierential equations and risk estimation under model selection. A model selection framework was developed for modelling time course data by ordinary dierential equations. The framework is accompanied by the R software...... package, episode. This package incorporates a collection of sparsity inducing penalties into two types of loss functions: a squared loss function relying on numerically solving the equations and an approximate loss function based on inverse collocation methods. The goal of this framework is to provide...

The numerical computation of seismic fragility of base-isolated Nuclear Power Plants buildings

International Nuclear Information System (INIS)

Perotti, Federico; Domaneschi, Marco; De Grandis, Silvia

2013-01-01

Highlights: • Seismic fragility of structural components in base isolated NPP is computed. • Dynamic integration, Response Surface, FORM and Monte Carlo Simulation are adopted. • Refined approach for modeling the non-linearities behavior of isolators is proposed. • Beyond-design conditions are addressed. • The preliminary design of the isolated IRIS is the application of the procedure. -- Abstract: The research work here described is devoted to the development of a numerical procedure for the computation of seismic fragilities for equipment and structural components in Nuclear Power Plants; in particular, reference is made, in the present paper, to the case of isolated buildings. The proposed procedure for fragility computation makes use of the Response Surface Methodology to model the influence of the random variables on the dynamic response. To account for stochastic loading, the latter is computed by means of a simulation procedure. Given the Response Surface, the Monte Carlo method is used to compute the failure probability. The procedure is here applied to the preliminary design of the Nuclear Power Plant reactor building within the International Reactor Innovative and Secure international project; the building is equipped with a base isolation system based on the introduction of High Damping Rubber Bearing elements showing a markedly non linear mechanical behavior. The fragility analysis is performed assuming that the isolation devices become the critical elements in terms of seismic risk and that, once base-isolation is introduced, the dynamic behavior of the building can be captured by low-dimensional numerical models

Lifestyle-based risk model for fall risk assessment

OpenAIRE

Sannino, Giovanna; De Falco, Ivanoe; De Pietro, Guiseppe

2016-01-01

Purpose: The aim of this study was to identify the explicit relationship between life-style and the risk of falling under the form of a mathematical model. Starting from some personal and behavioral information of a subject as, e.g., weight, height, age, data about physical activity habits, and concern about falling, the model would estimate the score of her/his Mini-Balance Evaluation Systems (Mini-BES) test. This score ranges within 0 and 28, and the lower its value the more likely the subj...

GRAVTool, a Package to Compute Geoid Model by Remove-Compute-Restore Technique

Science.gov (United States)

Marotta, G. S.; Blitzkow, D.; Vidotti, R. M.

2015-12-01

Currently, there are several methods to determine geoid models. They can be based on terrestrial gravity data, geopotential coefficients, astro-geodetic data or a combination of them. Among the techniques to compute a precise geoid model, the Remove-Compute-Restore (RCR) has been widely applied. It considers short, medium and long wavelengths derived from altitude data provided by Digital Terrain Models (DTM), terrestrial gravity data and global geopotential coefficients, respectively. In order to apply this technique, it is necessary to create procedures that compute gravity anomalies and geoid models, by the integration of different wavelengths, and that adjust these models to one local vertical datum. This research presents a developed package called GRAVTool based on MATLAB software to compute local geoid models by RCR technique and its application in a study area. The studied area comprehends the federal district of Brazil, with ~6000 km², wavy relief, heights varying from 600 m to 1340 m, located between the coordinates 48.25ºW, 15.45ºS and 47.33ºW, 16.06ºS. The results of the numerical example on the studied area show the local geoid model computed by the GRAVTool package (Figure), using 1377 terrestrial gravity data, SRTM data with 3 arc second of resolution, and geopotential coefficients of the EIGEN-6C4 model to degree 360. The accuracy of the computed model (σ = ± 0.071 m, RMS = 0.069 m, maximum = 0.178 m and minimum = -0.123 m) matches the uncertainty (σ =± 0.073) of 21 points randomly spaced where the geoid was computed by geometrical leveling technique supported by positioning GNSS. The results were also better than those achieved by Brazilian official regional geoid model (σ = ± 0.099 m, RMS = 0.208 m, maximum = 0.419 m and minimum = -0.040 m).

A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph

Directory of Open Access Journals (Sweden)

Jin Xu

2018-02-01

Full Text Available The biggest bottleneck in DNA computing is exponential explosion, in which the DNA molecules used as data in information processing grow exponentially with an increase of problem size. To overcome this bottleneck and improve the processing speed, we propose a DNA computing model to solve the graph vertex coloring problem. The main points of the model are as follows: ① The exponential explosion problem is solved by dividing subgraphs, reducing the vertex colors without losing the solutions, and ordering the vertices in subgraphs; and ② the bio-operation times are reduced considerably by a designed parallel polymerase chain reaction (PCR technology that dramatically improves the processing speed. In this article, a 3-colorable graph with 61 vertices is used to illustrate the capability of the DNA computing model. The experiment showed that not only are all the solutions of the graph found, but also more than 99% of false solutions are deleted when the initial solution space is constructed. The powerful computational capability of the model was based on specific reactions among the large number of nanoscale oligonucleotide strands. All these tiny strands are operated by DNA self-assembly and parallel PCR. After thousands of accurate PCR operations, the solutions were found by recognizing, splicing, and assembling. We also prove that the searching capability of this model is up to O(359. By means of an exhaustive search, it would take more than 896 000 years for an electronic computer (5 × 1014 s−1 to achieve this enormous task. This searching capability is the largest among both the electronic and non-electronic computers that have been developed since the DNA computing model was proposed by Adleman’s research group in 2002 (with a searching capability of O(220. Keywords: DNA computing, Graph vertex coloring problem, Polymerase chain reaction

A risk-return based model to measure the performance of portfolio management

Directory of Open Access Journals (Sweden)

Hamid Reza Vakili Fard

2014-10-01

Full Text Available The primary concern in all portfolio management systems is to find a good tradeoff between risk and expected return and a good balance between accepted risk and actual return indicates the performance of a particular portfolio. This paper develops “A-Y Model” to measure the performance of a portfolio and analyze it during the bull and the bear market. This paper considers the daily information of one year before and one year after Iran's 2013 precedential election. The proposed model of this paper provides lost profit and unrealized loss to measure the portfolio performance. The proposed study first ranks the resulted data and then uses some non-parametric methods to see whether there is any change because of the changes in markets on the performance of the portfolio. The results indicate that despite increasing profitable opportunities in bull market, the performance of the portfolio did not match the target risk. As a result, using A-Y Model as a risk and return base model to measure portfolio management's performance appears to reduce risks and increases return of portfolio.

A response-modeling alternative to surrogate models for support in computational analyses

International Nuclear Information System (INIS)

Rutherford, Brian

2006-01-01

Often, the objectives in a computational analysis involve characterization of system performance based on some function of the computed response. In general, this characterization includes (at least) an estimate or prediction for some performance measure and an estimate of the associated uncertainty. Surrogate models can be used to approximate the response in regions where simulations were not performed. For most surrogate modeling approaches, however (1) estimates are based on smoothing of available data and (2) uncertainty in the response is specified in a point-wise (in the input space) fashion. These aspects of the surrogate model construction might limit their capabilities. One alternative is to construct a probability measure, G(r), for the computer response, r, based on available data. This 'response-modeling' approach will permit probability estimation for an arbitrary event, E(r), based on the computer response. In this general setting, event probabilities can be computed: prob(E)=∫ r I(E(r))dG(r) where I is the indicator function. Furthermore, one can use G(r) to calculate an induced distribution on a performance measure, pm. For prediction problems where the performance measure is a scalar, its distribution F pm is determined by: F pm (z)=∫ r I(pm(r)≤z)dG(r). We introduce response models for scalar computer output and then generalize the approach to more complicated responses that utilize multiple response models

Task-based dermal exposure models for regulatory risk assessment.

Science.gov (United States)

Warren, Nicholas D; Marquart, Hans; Christopher, Yvette; Laitinen, Juha; VAN Hemmen, Joop J

2006-07-01

The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

Data driven model generation based on computational intelligence

Science.gov (United States)

Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

2010-05-01

The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion

Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

DEFF Research Database (Denmark)

Jonsdottir, Svava Osk; Reffstrup, Trine Klein; Petersen, Annette

2016-01-01

(ADME) of tebuconazole. The developed models were validated on in vivo half-life data for rabbit with good results, and on plasma and tissue concentration-time course data of tebuconazole after i.v. administration in rabbit. In most cases, the predicted concentration levels were seen to be within......A series of physiologically based toxicokinetic (PBTK) models for tebuconazole were developed in four species, rat, rabbit, rhesus monkey, and human. The developed models were analyzed with respect to the application of the models in higher tier human risk assessment, and the prospect of using...... such models in risk assessment of cumulative and aggregate exposure is discussed. Relatively simple and biologically sound models were developed using available experimental data as parameters for describing the physiology of the species, as well as the absorption, distribution, metabolism, and elimination...

A Probabilistic Asteroid Impact Risk Model

Science.gov (United States)

Mathias, Donovan L.; Wheeler, Lorien F.; Dotson, Jessie L.

2016-01-01

Asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data has little effect on the metrics of interest.

Rational Multi-curve Models with Counterparty-risk Valuation Adjustments

DEFF Research Database (Denmark)

Crépey, Stéphane; Macrina, Andrea; Nguyen, Tuyet Mai

2016-01-01

We develop a multi-curve term structure set-up in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to London Interbank Offer Rate swaptions data and show that a rational two-factor log-normal multi-curve model is sufficient to match market da...... with regulatory obligations. In order to compute counterparty-risk valuation adjustments, such as credit valuation adjustment, we show how default intensity processes with rational form can be derived. We flesh out our study by applying the results to a basis swap contract....... with accuracy. We elucidate the relationship between the models developed and calibrated under a risk-neutral measure Q and their consistent equivalence class under the real-world probability measure P. The consistent P-pricing models are applied to compute the risk exposures which may be required to comply...

Transitions in the computational power of thermal states for measurement-based quantum computation

International Nuclear Information System (INIS)

Barrett, Sean D.; Bartlett, Stephen D.; Jennings, David; Doherty, Andrew C.; Rudolph, Terry

2009-01-01

We show that the usefulness of the thermal state of a specific spin-lattice model for measurement-based quantum computing exhibits a transition between two distinct 'phases' - one in which every state is a universal resource for quantum computation, and another in which any local measurement sequence can be simulated efficiently on a classical computer. Remarkably, this transition in computational power does not coincide with any phase transition, classical, or quantum in the underlying spin-lattice model.

Research on Risk Evaluation of Transnational Power Networking Projects Based on the Matter-Element Extension Theory and Granular Computing

Directory of Open Access Journals (Sweden)

Jinying Li

2017-10-01

Full Text Available In project management, risk assessment is crucial for stakeholders to identify the risk factors during the whole life cycle of the project. A risk evaluation index system of a transnational networking project, which provides an effective way for the grid integration of clean electricity and the sustainable development of the power industry, is constructed in this paper. Meanwhile, a combination of granular computing and order relation analysis (G1 method is applied to determine the weight of each indicator and the matter-element extension evaluation model is also employed to seek the global optimal decision during the risk assessment. Finally, a case study is given to validate the index system and evaluation model established in this paper by assessing two different investment schemes of a transnational high voltage direct current (HVDC transmission project. The result shows that the comprehensive risk level of Scheme 1 is “Low” and the level of Scheme 2 is “General”, which means Scheme 1 is better for the stakeholders from the angle of risk control. The main practical significance of this paper lies in that it can provide a reference and decision support for the government’s power sectors, investment companies and other stakeholders when carrying out related activities.

Development and Sensitivity Analysis of a Frost Risk model based primarily on freely distributed Earth Observation data

Science.gov (United States)

Louka, Panagiota; Petropoulos, George; Papanikolaou, Ioannis

2015-04-01

The ability to map the spatiotemporal distribution of extreme climatic conditions, such as frost, is a significant tool in successful agricultural management and decision making. Nowadays, with the development of Earth Observation (EO) technology, it is possible to obtain accurately, timely and in a cost-effective way information on the spatiotemporal distribution of frost conditions, particularly over large and otherwise inaccessible areas. The present study aimed at developing and evaluating a frost risk prediction model, exploiting primarily EO data from MODIS and ASTER sensors and ancillary ground observation data. For the evaluation of our model, a region in north-western Greece was selected as test site and a detailed sensitivity analysis was implemented. The agreement between the model predictions and the observed (remotely sensed) frost frequency obtained by MODIS sensor was evaluated thoroughly. Also, detailed comparisons of the model predictions were performed against reference frost ground observations acquired from the Greek Agricultural Insurance Organization (ELGA) over a period of 10-years (2000-2010). Overall, results evidenced the ability of the model to produce reasonably well the frost conditions, following largely explainable patterns in respect to the study site and local weather conditions characteristics. Implementation of our proposed frost risk model is based primarily on satellite imagery analysis provided nowadays globally at no cost. It is also straightforward and computationally inexpensive, requiring much less effort in comparison for example to field surveying. Finally, the method is adjustable to be potentially integrated with other high resolution data available from both commercial and non-commercial vendors. Keywords: Sensitivity analysis, frost risk mapping, GIS, remote sensing, MODIS, Greece

A computer graphics based model for scattering from objects of arbitrary shapes in the optical region

Science.gov (United States)

Goel, Narendra S.; Rozehnal, Ivan; Thompson, Richard L.

1991-01-01

A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.

Mean-variance model for portfolio optimization with background risk based on uncertainty theory

Science.gov (United States)

Zhai, Jia; Bai, Manying

2018-04-01

The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

The Global Earthquake Model and Disaster Risk Reduction

Science.gov (United States)

Smolka, A. J.

2015-12-01

Advanced, reliable and transparent tools and data to assess earthquake risk are inaccessible to most, especially in less developed regions of the world while few, if any, globally accepted standards currently allow a meaningful comparison of risk between places. The Global Earthquake Model (GEM) is a collaborative effort that aims to provide models, datasets and state-of-the-art tools for transparent assessment of earthquake hazard and risk. As part of this goal, GEM and its global network of collaborators have developed the OpenQuake engine (an open-source software for hazard and risk calculations), the OpenQuake platform (a web-based portal making GEM's resources and datasets freely available to all potential users), and a suite of tools to support modelers and other experts in the development of hazard, exposure and vulnerability models. These resources are being used extensively across the world in hazard and risk assessment, from individual practitioners to local and national institutions, and in regional projects to inform disaster risk reduction. Practical examples for how GEM is bridging the gap between science and disaster risk reduction are: - Several countries including Switzerland, Turkey, Italy, Ecuador, Papua-New Guinea and Taiwan (with more to follow) are computing national seismic hazard using the OpenQuake-engine. In some cases these results are used for the definition of actions in building codes. - Technical support, tools and data for the development of hazard, exposure, vulnerability and risk models for regional projects in South America and Sub-Saharan Africa. - Going beyond physical risk, GEM's scorecard approach evaluates local resilience by bringing together neighborhood/community leaders and the risk reduction community as a basis for designing risk reduction programs at various levels of geography. Actual case studies are Lalitpur in the Kathmandu Valley in Nepal and Quito/Ecuador. In agreement with GEM's collaborative approach, all

Category-theoretic models of algebraic computer systems

Science.gov (United States)

Kovalyov, S. P.

2016-01-01

A computer system is said to be algebraic if it contains nodes that implement unconventional computation paradigms based on universal algebra. A category-based approach to modeling such systems that provides a theoretical basis for mapping tasks to these systems' architecture is proposed. The construction of algebraic models of general-purpose computations involving conditional statements and overflow control is formally described by a reflector in an appropriate category of algebras. It is proved that this reflector takes the modulo ring whose operations are implemented in the conventional arithmetic processors to the Łukasiewicz logic matrix. Enrichments of the set of ring operations that form bases in the Łukasiewicz logic matrix are found.

Quantum vertex model for reversible classical computing.

Science.gov (United States)

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Computational aeroelasticity using a pressure-based solver

Science.gov (United States)

Kamakoti, Ramji

A computational methodology for performing fluid-structure interaction computations for three-dimensional elastic wing geometries is presented. The flow solver used is based on an unsteady Reynolds-Averaged Navier-Stokes (RANS) model. A well validated k-ε turbulence model with wall function treatment for near wall region was used to perform turbulent flow calculations. Relative merits of alternative flow solvers were investigated. The predictor-corrector-based Pressure Implicit Splitting of Operators (PISO) algorithm was found to be computationally economic for unsteady flow computations. Wing structure was modeled using Bernoulli-Euler beam theory. A fully implicit time-marching scheme (using the Newmark integration method) was used to integrate the equations of motion for structure. Bilinear interpolation and linear extrapolation techniques were used to transfer necessary information between fluid and structure solvers. Geometry deformation was accounted for by using a moving boundary module. The moving grid capability was based on a master/slave concept and transfinite interpolation techniques. Since computations were performed on a moving mesh system, the geometric conservation law must be preserved. This is achieved by appropriately evaluating the Jacobian values associated with each cell. Accurate computation of contravariant velocities for unsteady flows using the momentum interpolation method on collocated, curvilinear grids was also addressed. Flutter computations were performed for the AGARD 445.6 wing at subsonic, transonic and supersonic Mach numbers. Unsteady computations were performed at various dynamic pressures to predict the flutter boundary. Results showed favorable agreement of experiment and previous numerical results. The computational methodology exhibited capabilities to predict both qualitative and quantitative features of aeroelasticity.

An RES-Based Model for Risk Assessment and Prediction of Backbreak in Bench Blasting

Science.gov (United States)

Faramarzi, F.; Ebrahimi Farsangi, M. A.; Mansouri, H.

2013-07-01

Most blasting operations are associated with various forms of energy loss, emerging as environmental side effects of rock blasting, such as flyrock, vibration, airblast, and backbreak. Backbreak is an adverse phenomenon in rock blasting operations, which imposes risk and increases operation expenses because of safety reduction due to the instability of walls, poor fragmentation, and uneven burden in subsequent blasts. In this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the prediction of backbreak and the risk associated with a blast is presented. The newly suggested model involves 16 effective parameters on backbreak due to blasting, while retaining simplicity as well. The data for 30 blasts, carried out at Sungun copper mine, western Iran, were used to predict backbreak and the level of risk corresponding to each blast by the RES-based model. The results obtained were compared with the backbreak measured for each blast, which showed that the level of risk achieved is in consistence with the backbreak measured. The maximum level of risk [vulnerability index (VI) = 60] was associated with blast No. 2, for which the corresponding average backbreak was the highest achieved (9.25 m). Also, for blasts with levels of risk under 40, the minimum average backbreaks (<4 m) were observed. Furthermore, to evaluate the model performance for backbreak prediction, the coefficient of correlation ( R 2) and root mean square error (RMSE) of the model were calculated ( R 2 = 0.8; RMSE = 1.07), indicating the good performance of the model.

Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

Science.gov (United States)

Erdogan, Yavuz

2009-01-01

The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

A measurement-based X-ray source model characterization for CT dosimetry computations.

Science.gov (United States)

Sommerville, Mitchell; Poirier, Yannick; Tambasco, Mauro

2015-11-08

within the experimental uncertainties associated with measurement reproducibility and chamber volume effects for the PMMA phantom. The agreement between calculation and measurement was within experimental uncertainty for 19 out of 20 simulation conditions at five points of interest in the anthropomorphic thorax phantom for the four beam energies modeled. The source model and characterization technique based on HVL measurements and nominal kVp can be used to accurately compute CT dose. This accuracy provides experimental validation of kVDoseCalc for computing CT dose.

Model-based Computer Aided Framework for Design of Process Monitoring and Analysis Systems

DEFF Research Database (Denmark)

Singh, Ravendra; Gernaey, Krist; Gani, Rafiqul

2009-01-01

In the manufacturing industry, for example, the pharmaceutical industry, a thorough understanding of the process is necessary in addition to a properly designed monitoring and analysis system (PAT system) to consistently obtain the desired end-product properties. A model-based computer....... The knowledge base provides the necessary information/data during the design of the PAT system while the model library generates additional or missing data needed for design and analysis. Optimization of the PAT system design is achieved in terms of product data analysis time and/or cost of monitoring equipment......-aided framework including the methods and tools through which the design of monitoring and analysis systems for product quality control can be generated, analyzed and/or validated, has been developed. Two important supporting tools developed as part of the framework are a knowledge base and a model library...

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences

Science.gov (United States)

Rudd, Michael E.

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4. PMID:25202253

A Cortical Edge-integration Model of Object-Based Lightness Computation that Explains Effects of Spatial Context and Individual Differences

Directory of Open Access Journals (Sweden)

Michael E Rudd

2014-08-01

Full Text Available Previous work demonstrated that perceived surface reflectance (lightness can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatial integrates these steps along paths through the image to compute lightness (Rudd & Zemach, 2004, 2005, 2007. This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013 suggests that the human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010 further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer’s interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd & Zemach, 2005. Here, I show how the separate influences of grouping and attention on lightness can be together modeled by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013, and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences.

Science.gov (United States)

Rudd, Michael E

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

Risk assessment using Analytical Hierarchy Process - Development and evaluation of a new computer-based tool; Riskvaerdering med Analytical Hierarchy Process - Utveckling och utprovning av ett nytt datorbaserat verktyg

Energy Technology Data Exchange (ETDEWEB)

Ritchey, Tom (Swedish Defence Research Agency, Stockholm (Sweden))

2008-11-15

Risk analysis concerning the management of contaminated areas involves comparing and evaluating the relationship between ecological, technical, economic and other factors, in order to determine a reasonable level of remediation. Risk analysis of this kind is a relatively new phenomenon. In order to develop methodology in this area, the Sustainable Remediation program contributes both to comprehensive risk analysis projects and to projects concentrating on specific aspects of remediation risk analysis. In the project described in this report, the Swedish Defence Research Agency (FOI) was given a grant by the Sustainable Remediation program to apply the Analytic Hierarchy Process (AHP) in order to develop a computer-aided instrument to support remediation risk analysis. AHP is one of several so-called multi-criteria decision support methods. These methods are applied in order to systematically compare and evaluate different solutions or measures, when there are many different goal criteria involved. Such criteria can be both quantitative and qualitative. The project has resulted in the development of a computer-aided instrument which can be employed to give a better structure, consistency and traceability to risk analyses for the remediation of contaminated areas. Project was carried out in two phases with two different working groups. The first phase involved the development of a generic base-model for remediation risk analysis. This was performed by a 'development group'. The second phase entailed the testing of the generic model in a specific, on-going remediation project. This was performed by a 'test group'. The remediation project in question concerned the decontamination of a closed-down sawmill in Vaeckelsaang, in the Swedish municipality of Tingsryd

Safety Metrics for Human-Computer Controlled Systems

Science.gov (United States)

Leveson, Nancy G; Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Evaluation of kriging based surrogate models constructed from mesoscale computations of shock interaction with particles

Energy Technology Data Exchange (ETDEWEB)

Sen, Oishik, E-mail: oishik-sen@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Gaul, Nicholas J., E-mail: nicholas-gaul@ramdosolutions.com [RAMDO Solutions, LLC, Iowa City, IA 52240 (United States); Choi, K.K., E-mail: kyung-choi@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Jacobs, Gustaaf, E-mail: gjacobs@sdsu.edu [Aerospace Engineering, San Diego State University, San Diego, CA 92115 (United States); Udaykumar, H.S., E-mail: hs-kumar@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

2017-05-01

Macro-scale computations of shocked particulate flows require closure laws that model the exchange of momentum/energy between the fluid and particle phases. Closure laws are constructed in this work in the form of surrogate models derived from highly resolved mesoscale computations of shock-particle interactions. The mesoscale computations are performed to calculate the drag force on a cluster of particles for different values of Mach Number and particle volume fraction. Two Kriging-based methods, viz. the Dynamic Kriging Method (DKG) and the Modified Bayesian Kriging Method (MBKG) are evaluated for their ability to construct surrogate models with sparse data; i.e. using the least number of mesoscale simulations. It is shown that if the input data is noise-free, the DKG method converges monotonically; convergence is less robust in the presence of noise. The MBKG method converges monotonically even with noisy input data and is therefore more suitable for surrogate model construction from numerical experiments. This work is the first step towards a full multiscale modeling of interaction of shocked particle laden flows.

A risk based model supporting long term maintenance and reinvestment strategy decision making

Energy Technology Data Exchange (ETDEWEB)

Sand, Kjell; Montard, Julien; Tremoen, Tord H.

2010-02-15

This Technical Report is a product from the project Risk-Based Distribution System Asset Management (short: RISK DSAM) - Work Package 3 Risk exposure on company/strategic level. In the report a concept for portfolio distribution system asset management is presented. The approach comprises four main steps: 1. Decide the asset base. 2. Divide the asset base into relevant archetypes. 3. Develop or select relevant maintenance and reinvestment strategies for the different archetypes. 4. Estimate risks and costs for each archetype for the relevant strategies. For the different steps guidelines are given and a proposal for implementation of the concept is given in terms of a proposed IT system architecture.To evaluate the feasibility of such a concept, a prototype was developed in by using Visual Basic macros in Excel using real technical data from a small DSO. The experience from using the prototype shows that the concept is realistic. All assets are included and depending of the ambition of the risk analysis both simple simulation models and more advanced might be embedded. Presentations of the concept for a utility engineers have receive positive feedback indicating that the concept is regarded as a practical way to develop risk based asset management strategies for the asset fleet. It should be noted that the concept should be applied on a company strategic level and is thus not designed to be applied for a specific project or asset decisions. For this, more detailed models with area specific information, topology etc. are needed. (Author)

WASTE-PRA: a computer package for probabilistic risk assessment of shallow-land burial of low-level radioactive waste

International Nuclear Information System (INIS)

Cox, N.D.; Atwood, C.L.

1985-12-01

This report is a user's manual for a package of computer programs and data files to be used for probabilistic risk assessment of shallow-land burial of low-level radioactive waste. The nuclide transport pathways modeled are an unsaturated groundwater column, an aquifer, and the atmosphere. An individual or the population receives a dose commitment through shine, inhalation, ingestion, direct exposure, and/or a puncture wound. The methodology of risk assessment is based on the response surface method of uncertainty analysis. The parameters of the model for predicting dose commitment due to a release are treated as statistical variables, in order to compute statistical distributions for various contributions to the dose commitment. The likelihood of a release is similarly treated as a statistical variable. Uncertainty distributions are obtained both for the dose commitment and for the corresponding risk. Plots and printouts are produced to aid in comparing the importance of various release scenarios and in assessing the total risk of a set of scenarios. The entire methodology is illustrated by an example. Information is included on parameter uncertainties, reference site characteristics, and probabilities of release events

Ranked retrieval of Computational Biology models.

Science.gov (United States)

Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab

Radiation risk estimation based on measurement error models

CERN Document Server

Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya

2017-01-01

This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.

Methodology for risk-based analysis of technical specifications

International Nuclear Information System (INIS)

Vesely, W.E.; Gaertner, J.P.; Wagner, D.P.

1985-01-01

Part of the effort by EPRI to apply probabilistic risk assessment methods and results to the solution of utility problems involves the investigation of methods for risk-based analysis of technical specifications. The culmination of this investigation is the SOCRATES computer code developed by Battelle's Columbus Laboratories to assist in the evaluation of technical specifications of nuclear power plants. The program is designed to use information found in PRAs to re-evaluate risk for changes in component allowed outage times (AOTs) and surveillance test intervals (STIs). The SOCRATES program is a unique and important tool for technical specification evaluations. The detailed component unavailability model allows a detailed analysis of AOT and STI contributions to risk. Explicit equations allow fast and inexpensive calculations. Because the code is designed to accept ranges of parameters and to save results of calculations that do not change during the analysis, sensitivity studies are efficiently performed and results are clearly displayed

WRF-based fire risk modelling and evaluation for years 2010 and 2012 in Poland

Science.gov (United States)

Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej

2016-04-01

Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The

Application of Physiologically Based Pharmacokinetic Models in Chemical Risk Assessment

Directory of Open Access Journals (Sweden)

Moiz Mumtaz

2012-01-01

Full Text Available Post-exposure risk assessment of chemical and environmental stressors is a public health challenge. Linking exposure to health outcomes is a 4-step process: exposure assessment, hazard identification, dose response assessment, and risk characterization. This process is increasingly adopting “in silico” tools such as physiologically based pharmacokinetic (PBPK models to fine-tune exposure assessments and determine internal doses in target organs/tissues. Many excellent PBPK models have been developed. But most, because of their scientific sophistication, have found limited field application—health assessors rarely use them. Over the years, government agencies, stakeholders/partners, and the scientific community have attempted to use these models or their underlying principles in combination with other practical procedures. During the past two decades, through cooperative agreements and contracts at several research and higher education institutions, ATSDR funded translational research has encouraged the use of various types of models. Such collaborative efforts have led to the development and use of transparent and user-friendly models. The “human PBPK model toolkit” is one such project. While not necessarily state of the art, this toolkit is sufficiently accurate for screening purposes. Highlighted in this paper are some selected examples of environmental and occupational exposure assessments of chemicals and their mixtures.

Technical methods for a risk-informed, performance-based fire protection program at nuclear power plants

International Nuclear Information System (INIS)

Dey, M.K.

2000-01-01

This paper presents a technical review and examination of technical methods that are available for developing a risk-informed, performance-based fire protection program at a nuclear plant. The technical methods include 'engineering tools' for examining the fire dynamics of fire protection problems, reliability techniques for establishing an optimal fire protection surveillance program, fire computer codes for analyzing important fire protection safety parameters, and risk-informed approaches that can range from drawing qualitative insights from risk information to quantifying the risk impact of alternative fire protection approaches. Based on this technical review and examination, it is concluded that methods for modeling fires, and reliability and fire probabilistic risk analyses (PRA) are currently available to support the initial implementation of simple risk-informed, performance-based approaches in fire protection programs. (orig.) [de

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

Energy Technology Data Exchange (ETDEWEB)

Wittwehr, Clemens; Aladjov, Hristo; Ankley, Gerald; Byrne, Hugh J.; de Knecht, Joop; Heinzle, Elmar; Klambauer, Günter; Landesmann, Brigitte; Luijten, Mirjam; MacKay, Cameron; Maxwell, Gavin; Meek, M. E. (Bette); Paini, Alicia; Perkins, Edward; Sobanski, Tomasz; Villeneuve, Dan; Waters, Katrina M.; Whelan, Maurice

2016-12-19

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework has emerged as a systematic approach for organizing knowledge that supports such inference. We argue that this systematic organization of knowledge can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.

Modelling computer networks

International Nuclear Information System (INIS)

Max, G

2011-01-01

Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

Integration of an Evidence Base into a Probabilistic Risk Assessment Model. The Integrated Medical Model Database: An Organized Evidence Base for Assessing In-Flight Crew Health Risk and System Design

Science.gov (United States)

Saile, Lynn; Lopez, Vilma; Bickham, Grandin; FreiredeCarvalho, Mary; Kerstman, Eric; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) database, which is an organized evidence base for assessing in-flight crew health risk. The database is a relational database accessible to many people. The database quantifies the model inputs by a ranking based on the highest value of the data as Level of Evidence (LOE) and the quality of evidence (QOE) score that provides an assessment of the evidence base for each medical condition. The IMM evidence base has already been able to provide invaluable information for designers, and for other uses.

Towards The Deep Model : Understanding Visual Recognition Through Computational Models

OpenAIRE

Wang, Panqu

2017-01-01

Understanding how visual recognition is achieved in the human brain is one of the most fundamental questions in vision research. In this thesis I seek to tackle this problem from a neurocomputational modeling perspective. More specifically, I build machine learning-based models to simulate and explain cognitive phenomena related to human visual recognition, and I improve computational models using brain-inspired principles to excel at computer vision tasks.I first describe how a neurocomputat...

Computer - based modeling in extract sciences research -I ...

African Journals Online (AJOL)

Specifically, in the discipline of chemistry, it has been of great utility. Its use dates back to the 17th Century and includes such wide areas as computational chemistry, chemoinformatics, molecular mechanics, chemical dynamics, molecular dynamics, molecular graphics and algorithms. Modeling has been employed ...

Computational neurogenetic modeling

CERN Document Server

Benuskova, Lubica

2010-01-01

Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biol

A flexible model for actuarial risks under dependence

NARCIS (Netherlands)

Albers, Willem/Wim; Kallenberg, W.C.M.; Lukocius, V.

Methods for computing risk measures, such as stop-loss premiums, tacitly assume independence of the underlying individual risks. This can lead to huge errors even when only small dependencies occur. In the present paper, a general model is developed which covers what happens in practice in a

Applications of computer modeling to fusion research

International Nuclear Information System (INIS)

Dawson, J.M.

1989-01-01

Progress achieved during this report period is presented on the following topics: Development and application of gyrokinetic particle codes to tokamak transport, development of techniques to take advantage of parallel computers; model dynamo and bootstrap current drive; and in general maintain our broad-based program in basic plasma physics and computer modeling

A System Computational Model of Implicit Emotional Learning.

Science.gov (United States)

Puviani, Luca; Rama, Sidita

2016-01-01

Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.

Agent-Based Computing: Promise and Perils

OpenAIRE

Jennings, N. R.

1999-01-01

Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more genrally, Computer Science. It has the potential to significantly improve the theory and practice of modelling, designing and implementing complex systems. Yet, to date, there has been little systematic analysis of what makes an agent such an appealing and powerful conceptual model. Moreover, even less effort has been devoted to exploring the inherent disadvantages that stem from adoptin...

Software for occupational health and safety risk analysis based on a fuzzy model.

Science.gov (United States)

Stefanovic, Miladin; Tadic, Danijela; Djapan, Marko; Macuzic, Ivan

2012-01-01

Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk.

From Levy to Brownian: a computational model based on biological fluctuation.

Directory of Open Access Journals (Sweden)

Surya G Nurzaman

Full Text Available BACKGROUND: Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. METHODOLOGY/PRINCIPAL FINDINGS: We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. CONCLUSIONS/SIGNIFICANCE: Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

Computer-Based Procedures for Field Workers in Nuclear Power Plants: Development of a Model of Procedure Usage and Identification of Requirements

Energy Technology Data Exchange (ETDEWEB)

Katya Le Blanc; Johanna Oxstrand

2012-04-01

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field workers. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do so. This paper describes the development of a Model of Procedure Use and the qualitative study on which the model is based. The study was conducted in collaboration with four nuclear utilities and five research institutes. During the qualitative study and the model development requirements and for computer-based procedures were identified.

Modelling and Simulating of Risk Behaviours in Virtual Environments Based on Multi-Agent and Fuzzy Logic

Directory of Open Access Journals (Sweden)

Linqin Cai

2013-11-01

Full Text Available Due to safety and ethical issues, traditional experimental approaches to modelling underground risk behaviours can be costly, dangerous and even impossible to realize. Based on multi-agent technology, a virtual coalmine platform for risk behaviour simulation is presented to model and simulate the human-machine-environment related risk factors in underground coalmines. To reveal mine workers' risk behaviours, a fuzzy emotional behaviour model is proposed to simulate underground miners' responding behaviours to potential hazardous events based on cognitive appraisal theories and fuzzy logic techniques. The proposed emotion model can generate more believable behaviours for virtual miners according to personalized emotion states, internal motivation needs and behaviour selection thresholds. Finally, typical accident cases of underground hazard spotting and locomotive transport were implemented. The behaviour believability of virtual miners was evaluated with a user assessment method. Experimental results show that the proposed models can create more realistic and reasonable behaviours in virtual coalmine environments, which can improve miners' risk awareness and further train miners' emergent decision-making ability when facing unexpected underground situations.

Computer-aided modeling framework for efficient model development, analysis and identification

DEFF Research Database (Denmark)

Heitzig, Martina; Sin, Gürkan; Sales Cruz, Mauricio

2011-01-01

Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy, and water. This trend is set to continue due to the substantial benefits computer-aided...... methods introduce. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms, and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task....... The methodology has been implemented into a computer-aided modeling framework, which combines expert skills, tools, and database connections that are required for the different steps of the model development work-flow with the goal to increase the efficiency of the modeling process. The framework has two main...

Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus.

Science.gov (United States)

Echouffo-Tcheugui, J-B; Kengne, A P

2013-10-01

Multivariable models for estimating cardiovascular disease (CVD) risk in people with diabetes comprise general population-based models and those from diabetic cohorts. Whether one set of models should receive preference is unclear. We evaluated the evidence on direct comparisons of the performance of general population vs diabetes-specific CVD risk models in people with diabetes. MEDLINE and EMBASE databases were searched up to March 2013. Two reviewers independently identified studies that compared the performance of general CVD models vs diabetes-specific ones in the same group of people with diabetes. Independent, dual data extraction on study design, risk models, outcomes; and measures of performance was conducted. Eleven articles reporting on 22 pair wise comparisons of a diabetes-specific model (UKPDS, ADVANCE and DCS risk models) to a general population model (three variants of the Framingham model, Prospective Cardiovascular Münster [PROCAM] score, CardioRisk Manager [CRM], Joint British Societies Coronary Risk Chart [JBSRC], Progetto Cuore algorithm and the CHD-Riskard algorithm) were eligible. Absolute differences in C-statistic of diabetes-specific vs general population-based models varied from -0.13 to 0.09. Comparisons for other performance measures were unusual. Outcomes definitions were congruent with those applied during model development. In 14 comparisons, the UKPDS, ADVANCE or DCS diabetes-specific models were superior to the general population CVD risk models. Authors reported better C-statistic for models they developed. The limited existing evidence suggests a possible discriminatory advantage of diabetes-specific over general population-based models for CVD risk stratification in diabetes. More robust head-to-head comparisons are needed to confirm this trend and strengthen recommendations. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Computational Strategy for Quantifying Human Pesticide Exposure based upon a Saliva Measurement

Directory of Open Access Journals (Sweden)

Charles eTimchalk

2015-05-01

Full Text Available Quantitative exposure data is important for evaluating toxicity risk and biomonitoring is a critical tool for evaluating human exposure. Direct personal monitoring provides the most accurate estimation of a subject’s true dose, and non-invasive methods are advocated for quantifying exposure to xenobiotics. In this regard, there is a need to identify chemicals that are cleared in saliva at concentrations that can be quantified to support the implementation of this approach. This manuscript reviews the computational modeling approaches that are coupled to in vivo and in vitro experiments to predict salivary uptake and clearance of xenobiotics and provides additional insight on species-dependent differences in partitioning that are of key importance for extrapolation. The primary mechanism by which xenobiotics leave the blood and enter saliva involves paracellular transport, passive transcellular diffusion, or trancellular active transport with the majority of xenobiotics transferred by passive diffusion. The transcellular or paracellular diffusion of unbound chemicals in plasma to saliva has been computationally modeled using compartmental and physiologically based approaches. Of key importance for determining the plasma:saliva partitioning was the utilization of the Schmitt algorithm that calculates partitioning based upon the tissue composition, pH, chemical pKa and plasma protein-binding. Sensitivity analysis identified that both protein-binding and pKa (for weak acids and bases have significant impact on determining partitioning and species dependent differences based upon physiological variance. Future strategies are focused on an in vitro salivary acinar cell based system to experimentally determine and computationally predict salivary gland uptake and clearance for xenobiotics. It is envisioned that a combination of salivary biomonitoring and computational modeling will enable the non-invasive measurement of chemical exposures in human

Credit Risk Modeling

DEFF Research Database (Denmark)

Lando, David

Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers...... and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand...

Cloud Computing Governance Lifecycle

Directory of Open Access Journals (Sweden)

Soňa Karkošková

2016-06-01

Full Text Available Externally provisioned cloud services enable flexible and on-demand sourcing of IT resources. Cloud computing introduces new challenges such as need of business process redefinition, establishment of specialized governance and management, organizational structures and relationships with external providers and managing new types of risk arising from dependency on external providers. There is a general consensus that cloud computing in addition to challenges brings many benefits but it is unclear how to achieve them. Cloud computing governance helps to create business value through obtain benefits from use of cloud computing services while optimizing investment and risk. Challenge, which organizations are facing in relation to governing of cloud services, is how to design and implement cloud computing governance to gain expected benefits. This paper aims to provide guidance on implementation activities of proposed Cloud computing governance lifecycle from cloud consumer perspective. Proposed model is based on SOA Governance Framework and consists of lifecycle for implementation and continuous improvement of cloud computing governance model.

A randomized trial of computer-based communications using imagery and text information to alter representations of heart disease risk and motivate protective behaviour.

Science.gov (United States)

Lee, Tarryn J; Cameron, Linda D; Wünsche, Burkhard; Stevens, Carey

2011-02-01

Advances in web-based animation technologies provide new opportunities to develop graphic health communications for dissemination throughout communities. We developed imagery and text contents of brief, computer-based programmes about heart disease risk, with both imagery and text contents guided by the common-sense model (CSM) of self-regulation. The imagery depicts a three-dimensional, beating heart tailored to user-specific information. A 2 × 2 × 4 factorial design was used to manipulate concrete imagery (imagery vs. no imagery) and conceptual information (text vs. no text) about heart disease risk in prevention-oriented programmes and assess changes in representations and behavioural motivations from baseline to 2 days, 2 weeks, and 4 weeks post-intervention. Sedentary young adults (N= 80) were randomized to view one of four programmes: imagery plus text, imagery only, text only, or control. Participants completed measures of risk representations, worry, and physical activity and healthy diet intentions and behaviours at baseline, 2 days post-intervention (except behaviours), and 2 weeks (intentions and behaviours only) and 4 weeks later. The imagery contents increased representational beliefs and mental imagery relating to heart disease, worry, and intentions at post-intervention. Increases in sense of coherence (understanding of heart disease) and worry were sustained after 1 month. The imagery contents also increased healthy diet efforts after 2 weeks. The text contents increased beliefs about causal factors, mental images of clogged arteries, and worry at post-intervention, and increased physical activity 2 weeks later and sense of coherence 1 month later. The CSM-based programmes induced short-term changes in risk representations and behaviour motivation. The combination of CSM-based text and imagery appears to be most effective in instilling risk representations that motivate protective behaviour. ©2010 The British Psychological Society.

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

Science.gov (United States)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the

Are Masking-Based Models of Risk Useful?

Science.gov (United States)

Gisiner, Robert C

2016-01-01

As our understanding of directly observable effects from anthropogenic sound exposure has improved, concern about "unobservable" effects such as stress and masking have received greater attention. Equal energy models of masking such as power spectrum models have the appeal of simplicity, but do they offer biologically realistic assessments of the risk of masking? Data relevant to masking such as critical ratios, critical bandwidths, temporal resolution, and directional resolution along with what is known about general mammalian antimasking mechanisms all argue for a much more complicated view of masking when making decisions about the risk of masking inherent in a given anthropogenic sound exposure scenario.

Modelling the Intention to Adopt Cloud Computing Services: A Transaction Cost Theory Perspective

Directory of Open Access Journals (Sweden)

Ogan Yigitbasioglu

2014-11-01

Full Text Available This paper uses transaction cost theory to study cloud computing adoption. A model is developed and tested with data from an Australian survey. According to the results, perceived vendor opportunism and perceived legislative uncertainty around cloud computing were significantly associated with perceived cloud computing security risk. There was also a significant negative relationship between perceived cloud computing security risk and the intention to adopt cloud services. This study also reports on adoption rates of cloud computing in terms of applications, as well as the types of services used.

Computer-based video analysis identifies infants with absence of fidgety movements.

Science.gov (United States)

Støen, Ragnhild; Songstad, Nils Thomas; Silberg, Inger Elisabeth; Fjørtoft, Toril; Jensenius, Alexander Refsum; Adde, Lars

2017-10-01

BackgroundAbsence of fidgety movements (FMs) at 3 months' corrected age is a strong predictor of cerebral palsy (CP) in high-risk infants. This study evaluates the association between computer-based video analysis and the temporal organization of FMs assessed with the General Movement Assessment (GMA).MethodsInfants were eligible for this prospective cohort study if referred to a high-risk follow-up program in a participating hospital. Video recordings taken at 10-15 weeks post term age were used for GMA and computer-based analysis. The variation of the spatial center of motion, derived from differences between subsequent video frames, was used for quantitative analysis.ResultsOf 241 recordings from 150 infants, 48 (24.1%) were classified with absence of FMs or sporadic FMs using the GMA. The variation of the spatial center of motion (C SD ) during a recording was significantly lower in infants with normal (0.320; 95% confidence interval (CI) 0.309, 0.330) vs. absence of or sporadic (0.380; 95% CI 0.361, 0.398) FMs (P<0.001). A triage model with C SD thresholds chosen for sensitivity of 90% and specificity of 80% gave a 40% referral rate for GMA.ConclusionQuantitative video analysis during the FMs' period can be used to triage infants at high risk of CP to early intervention or observational GMA.

Some Comparisons of Complexity in Dictionary-Based and Linear Computational Models

Czech Academy of Sciences Publication Activity Database

Gnecco, G.; Kůrková, Věra; Sanguineti, M.

2011-01-01

Roč. 24, č. 2 (2011), s. 171-182 ISSN 0893-6080 R&D Project s: GA ČR GA201/08/1744 Grant - others:CNR - AV ČR project 2010-2012(XE) Complexity of Neural-Network and Kernel Computational Models Institutional research plan: CEZ:AV0Z10300504 Keywords : linear approximation schemes * variable-basis approximation schemes * model complexity * worst-case errors * neural networks * kernel models Subject RIV: IN - Informatics, Computer Science Impact factor: 2.182, year: 2011

Computer-based Creativity Enhanced Conceptual Design Model for Non-routine Design of Mechanical Systems

Institute of Scientific and Technical Information of China (English)

LI Yutong; WANG Yuxin; DUFFY Alex H B

2014-01-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

Science.gov (United States)

Li, Yutong; Wang, Yuxin; Duffy, Alex H. B.

2014-11-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

Directory of Open Access Journals (Sweden)

Ian C Scott

Full Text Available The improved characterisation of risk factors for rheumatoid arthritis (RA suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA. Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls; UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls. HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG. Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001; ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.

Ex Vivo Methods for Informing Computational Models of the Mitral Valve

OpenAIRE

Bloodworth, Charles H.; Pierce, Eric L.; Easley, Thomas F.; Drach, Andrew; Khalighi, Amir H.; Toma, Milan; Jensen, Morten O.; Sacks, Michael S.; Yoganathan, Ajit P.

2016-01-01

Computational modeling of the mitral valve (MV) has potential applications for determining optimal MV repair techniques and risk of recurrent mitral regurgitation. Two key concerns for informing these models are (1) sensitivity of model performance to the accuracy of the input geometry, and, (2) acquisition of comprehensive data sets against which the simulation can be validated across clinically relevant geometries. Addressing the first concern, ex vivo micro-computed tomography (microCT) wa...

Computational Modeling | Bioenergy | NREL

Science.gov (United States)

cell walls and are the source of biofuels and biomaterials. Our modeling investigates their properties . Quantum Mechanical Models NREL studies chemical and electronic properties and processes to reduce barriers Computational Modeling Computational Modeling NREL uses computational modeling to increase the

Technical methods for a risk-informed, performance-based fire protection program at nuclear power plants

International Nuclear Information System (INIS)

Dey, M.K.

1998-01-01

This paper presents a technical review and examination of technical methods that are available for developing a risk-informed, performance-based fire protection program at a nuclear plant. The technical methods include ''engineering tools'' for examining the fire dynamics of fire protection problems, reliability techniques for establishing an optimal fire protection surveillance program, fire computer codes for analyzing important fire protection safety parameters, and risk-informed approaches that can range from drawing qualitative insights from risk information to quantifying the risk impact of alternative fire protection approaches. Based on this technical review and examination, it is concluded that methods for modeling fires, and reliability and fire PRA analyses are currently available to support the initial implementation of simple risk-informed, performance-based approaches in fire protection programs. (author)

Risk methodology for geologic disposal of radioactive waste: model description and user manual for Pathways model

International Nuclear Information System (INIS)

Helton, J.C.; Kaestner, P.C.

1981-03-01

A model for the environmental movement and human uptake of radionuclides is presented. This model is designated the Pathways-to-Man Model and was developed as part of a project funded by the Nuclear Regulatory Commission to design a methodology to assess the risk associated with the geologic disposal of high-level radioactive waste. The Pathways-to-Man Model is divided into two submodels. One of these, the Environmental Transport Model, represents the long-term distribution and accumulation of radionuclides in the environment. This model is based on a mixed-cell approach and describes radionuclide movement with a system of linear differential equations. The other, the Transport-to-Man Model, represents the movement of radionuclides from the environment to man. This model is based on concentration ratios. General descriptions of these models are provided in this report. Further, documentation is provided for the computer program which implements the Pathways Model