Search results for: probabilistic scoring distribution
5468 Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution
Authors: Tomoaki Hashimoto
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In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research field. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method with the unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with the unknown probability distribution.Keywords: optimal control, stochastic systems, discrete time systems, probabilistic constraints
Procedia PDF Downloads 5685467 Solutions to Probabilistic Constrained Optimal Control Problems Using Concentration Inequalities
Authors: Tomoaki Hashimoto
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Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints
Procedia PDF Downloads 2665466 Constructing a Probabilistic Ontology from a DBLP Data
Authors: Emna Hlel, Salma Jamousi, Abdelmajid Ben Hamadou
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Every model for knowledge representation to model real-world applications must be able to cope with the effects of uncertain phenomena. One of main defects of classical ontology is its inability to represent and reason with uncertainty. To remedy this defect, we try to propose a method to construct probabilistic ontology for integrating uncertain information in an ontology modeling a set of basic publications DBLP (Digital Bibliography & Library Project) using a probabilistic model.Keywords: classical ontology, probabilistic ontology, uncertainty, Bayesian network
Procedia PDF Downloads 3405465 Influence of Maximum Fatigue Load on Probabilistic Aspect of Fatigue Crack Propagation Life at Specified Grown Crack in Magnesium Alloys
Authors: Seon Soon Choi
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The principal purpose of this paper is to find the influence of maximum fatigue load on the probabilistic aspect of fatigue crack propagation life at a specified grown crack in magnesium alloys. The experiments of fatigue crack propagation are carried out in laboratory air under different conditions of the maximum fatigue loads to obtain the fatigue crack propagation data for the statistical analysis. In order to analyze the probabilistic aspect of fatigue crack propagation life, the goodness-of fit test for probability distribution of the fatigue crack propagation life at a specified grown crack is implemented through Anderson-Darling test. The good probability distribution of the fatigue crack propagation life is also verified under the conditions of the maximum fatigue loads.Keywords: fatigue crack propagation life, magnesium alloys, maximum fatigue load, probability
Procedia PDF Downloads 3735464 Probabilistic Graphical Model for the Web
Authors: M. Nekri, A. Khelladi
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The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.Keywords: clustering coefficient, preferential attachment, small world, web community
Procedia PDF Downloads 2675463 A Joint Possibilistic-Probabilistic Tool for Load Flow Uncertainty Assessment-Part II: Case Studies
Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad
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Power systems are innately uncertain systems. To face with such uncertain systems, robust uncertainty assessment tools are appealed. This paper inspects the uncertainty assessment formulation of the load flow (LF) problem considering different kinds of uncertainties, developed in its companion paper through some case studies. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. The load and wind power generation are considered as probabilistic uncertain variables and the electric vehicles (EVs) and gas turbine distributed generation (DG) units are considered as possibilistic uncertain variables. The cumulative distribution function (CDF) of the system output parameters obtained by the pure probabilistic method lies within the belief and plausibility functions obtained by the joint propagation approach. Furthermore, the imprecision in the DG parameters is explicitly reflected by the gap between the belief and plausibility functions. This gap, due to the epistemic uncertainty on the DG resources parameters grows as the penetration level increases.Keywords: electric vehicles, joint possibilistic- probabilistic uncertainty modeling, uncertain load flow, wind turbine generator
Procedia PDF Downloads 4225462 A Hierarchical Method for Multi-Class Probabilistic Classification Vector Machines
Authors: P. Byrnes, F. A. DiazDelaO
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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines
Procedia PDF Downloads 2175461 A Joint Possibilistic-Probabilistic Tool for Load Flow Uncertainty Assessment-Part I: Formulation
Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad
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As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator
Procedia PDF Downloads 5495460 An Information System for Strategic Performance Scoring in Municipal Management
Authors: Emin Gundogar, Aysegul Yilmaz
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Strategic performance scoring is a significant procedure in management. There are various methods to improve this procedure. This study introduces an information system that is developed to score performance for municipal management. The application of the system is clarified by exemplifying municipal processes.Keywords: management information system, municipal management, performance scoring
Procedia PDF Downloads 7585459 Probabilistic Approach to Contrast Theoretical Predictions from a Public Corruption Game Using Bayesian Networks
Authors: Jaime E. Fernandez, Pablo J. Valverde
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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games
Procedia PDF Downloads 1985458 Improving Detection of Illegitimate Scores and Assessment in Most Advantageous Tenders
Authors: Hao-Hsi Tseng, Hsin-Yun Lee
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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method
Procedia PDF Downloads 4585457 Pudhaiyal: A Maze-Based Treasure Hunt Game for Tamil Words
Authors: Aarthy Anandan, Anitha Narasimhan, Madhan Karky
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Word-based games are popular in helping people to improve their vocabulary skills. Games like ‘word search’ and crosswords provide a smart way of increasing vocabulary skills. Word search games are fun to play, but also educational which actually helps to learn a language. Finding the words from word search puzzle helps the player to remember words in an easier way, and it also helps to learn the spellings of words. In this paper, we present a tile distribution algorithm for a Maze-Based Treasure Hunt Game 'Pudhaiyal’ for Tamil words, which describes how words can be distributed horizontally, vertically or diagonally in a 10 x 10 grid. Along with the tile distribution algorithm, we also present an algorithm for the scoring model of the game. The proposed game has been tested with 20,000 Tamil words.Keywords: Pudhaiyal, Tamil word game, word search, scoring, maze, algorithm
Procedia PDF Downloads 4285456 Application of Scoring Rubrics by Lecturers towards Objective Assessment of Essay Questions in the Department of Social Science Education, University of Calabar, Nigeria
Authors: Donald B. Enu, Clement O. Ukpor, Abigail E. Okon
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Unreliable scoring of students’ performance by lecturers short-chains students’ assessment in terms of underequipping the school authority with facts as intended by society through the curriculum hence, the learners, the school and the society are cheated because the usefulness of testing is defeated. This study, therefore, examined lecturers’ scoring objectivity of essay items in the Department of Social Science Education, University of Calabar, Nigeria. Specifically, it assessed lecturers’ perception of the relevance of scoring rubrics and its level of application. Data were collected from all the 36 lecturers in the Department (28 members and 8 non-members adjourned to the department), through a 20-item questionnaire and checklist instruments. A case-study design was adopted. Descriptive statistics of frequency counts, weighted means, standard deviations, and percentages were used to analyze data gathered. A mean score of 2.5 and or 60 percent and above formed the acceptance or significant level in decision taking. It was found that lecturers perceived the use of scoring rubrics as a relevant practice to ensure fairness and reliable treatment of examiners scripts particularly in marking essay items and that there is a moderately high level of adherence to the application of scoring rubrics. It was also observed that some criteria necessary for the scoring objectivity of essay items were not fully put in place in the department. It was recommended strongly that students’ identities be hidden while marking and that pre-determined marking scheme should be prepared centrally and strictly adhered to during marking and recording of scores. Conference marking should be enforced in the department.Keywords: essay items, objective scoring, scorers reliability, scoring rubrics
Procedia PDF Downloads 1695455 The Lexicographic Serial Rule
Authors: Thi Thao Nguyen, Andrew McLennan, Shino Takayama
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We study the probabilistic allocation of finitely many indivisible objects to finitely many agents. Well known allocation rules for this problem include random priority, the market mechanism proposed by Hylland and Zeckhauser [1979], and the probabilistic serial rule of Bogomolnaia and Moulin [2001]. We propose a new allocation rule, which we call the lexico-graphic (serial) rule, that is tailored for situations in which each agent's primary concern is to maximize the probability of receiving her favourite object. Three axioms, lex efficiency, lex envy freeness and fairness, are proposed and fully characterize the lexicographic serial rule. We also discuss how our axioms and the lexicographic rule are related to other allocation rules, particularly the probabilistic serial rule.Keywords: Efficiency, Envy free, Lexicographic, Probabilistic Serial Rule
Procedia PDF Downloads 1375454 Applications of Analytical Probabilistic Approach in Urban Stormwater Modeling in New Zealand
Authors: Asaad Y. Shamseldin
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Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management
Procedia PDF Downloads 3345453 Efficient Sampling of Probabilistic Program for Biological Systems
Authors: Keerthi S. Shetty, Annappa Basava
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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.Keywords: systems biology, probabilistic model, inference, biology, model
Procedia PDF Downloads 3365452 Probabilistic Simulation of Triaxial Undrained Cyclic Behavior of Soils
Authors: Arezoo Sadrinezhad, Kallol Sett, S. I. Hariharan
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In this paper, a probabilistic framework based on Fokker-Planck-Kolmogorov (FPK) approach has been applied to simulate triaxial cyclic constitutive behavior of uncertain soils. The framework builds upon previous work of the writers, and it has been extended for cyclic probabilistic simulation of triaxial undrained behavior of soils. von Mises elastic-perfectly plastic material model is considered. It is shown that by using probabilistic framework, some of the most important aspects of soil behavior under cyclic loading can be captured even with a simple elastic-perfectly plastic constitutive model.Keywords: elasto-plasticity, uncertainty, soils, fokker-planck equation, fourier spectral method, finite difference method
Procedia PDF Downloads 3635451 Applications of Probabilistic Interpolation via Orthogonal Matrices
Authors: Dariusz Jacek Jakóbczak
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Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation
Procedia PDF Downloads 5185450 Probabilistic Fracture Evaluation of Reactor Pressure Vessel Subjected to Pressurized Thermal Shock
Authors: Jianguo Chen, Fenggang Zang, Yu Yang, Liangang Zheng
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Reactor Pressure Vessel (RPV) is an important security barrier in nuclear power plant. Crack like defects may be produced on RPV during the whole operation lifetime due to the harsh operation condition and irradiation embrittlement. During the severe loss of coolant accident, thermal shock happened as the injection of emergency cooling water into RPV, which results in re-pressurization of the vessel and very high tension stress on the vessel wall, this event called Pressurized Thermal Shock (PTS). Crack on the vessel wall may propagate even penetrate the vessel, so the safety of the RPV would undergo great challenge. Many assumptions in structure integrity evaluation make the result of deterministic fracture mechanics very conservative, which affect the operation lifetime of the plant. Actually, many parameters in the evaluation process, such as fracture toughness and nil-ductility transition temperature, have statistical distribution characteristics. So it is necessary to assess the structural integrity of RPV subjected to PTS event by means of Probabilistic Fracture Mechanics (PFM). Structure integrity evaluation methods of RPV subjected to PTS event are summarized firstly, then evaluation method based on probabilistic fracture mechanics are presented by considering the probabilistic characteristics of material and structure parameters. A comprehensive analysis example is carried out at last. The results show that the probability of crack penetrates through wall increases gradually with the growth of fast neutron irradiation flux. The results give advice for reactor life extension.Keywords: fracture toughness, integrity evaluation, pressurized thermal shock, probabilistic fracture mechanics, reactor pressure vessel
Procedia PDF Downloads 2435449 Application of Adaptive Particle Filter for Localizing a Mobile Robot Using 3D Camera Data
Authors: Maysam Shahsavari, Seyed Jamalaldin Haddadi
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There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment.Keywords: particle filter, localization, methods, odometry, kinect
Procedia PDF Downloads 2575448 Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Authors: Abdelhadi Lotfi, Abdelkader Benyettou
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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.Keywords: classification, probabilistic neural networks, network optimization, pattern recognition
Procedia PDF Downloads 2525447 On the Added Value of Probabilistic Forecasts Applied to the Optimal Scheduling of a PV Power Plant with Batteries in French Guiana
Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet
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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems
Procedia PDF Downloads 725446 Comparison between Deterministic and Probabilistic Stability Analysis, Featuring Consequent Risk Assessment
Authors: Isabela Moreira Queiroz
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Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management.Keywords: probabilistic methods, risk assessment, risk management, slope stability
Procedia PDF Downloads 3755445 Probabilistic and Stochastic Analysis of a Retaining Wall for C-Φ Soil Backfill
Authors: André Luís Brasil Cavalcante, Juan Felix Rodriguez Rebolledo, Lucas Parreira de Faria Borges
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A methodology for the probabilistic analysis of active earth pressure on retaining wall for c-Φ soil backfill is described in this paper. The Rosenblueth point estimate method is used to measure the failure probability of a gravity retaining wall. The basic principle of this methodology is to use two point estimates, i.e., the standard deviation and the mean value, to examine a variable in the safety analysis. The simplicity of this framework assures to its wide application. For the calculation is required 2ⁿ repetitions during the analysis, since the system is governed by n variables. In this study, a probabilistic model based on the Rosenblueth approach for the computation of the overturning probability of failure of a retaining wall is presented. The obtained results have shown the advantages of this kind of models in comparison with the deterministic solution. In a relatively easy way, the uncertainty on the wall and fill parameters are taken into account, and some practical results can be obtained for the retaining structure design.Keywords: retaining wall, active earth pressure, backfill, probabilistic analysis
Procedia PDF Downloads 4045444 Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping
Authors: Adnan A. Y. Mustafa
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In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.Keywords: big images, binary images, image matching, image similarity
Procedia PDF Downloads 1865443 Optimal Mitigation of Slopes by Probabilistic Methods
Authors: D. De-León-Escobedo, D. J. Delgado-Hernández, S. Pérez
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A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF<1. As the main hazard is the rainfall on the area, statistics of rainfall intensity and duration are considered and modeled with an exponential distribution. The expected life-cycle cost is assessed by considering a monetary value on the slope failure consequences. Alternative mitigation measures are simulated, and the formulation is used to get the measures driving to the optimal one (minimum life-cycle costs). For the example, the optimal mitigation measure is the reduction on the slope inclination angle.Keywords: expected life-cycle cost, failure probability, slopes failure, storms
Procedia PDF Downloads 1515442 External Validation of Established Pre-Operative Scoring Systems in Predicting Response to Microvascular Decompression for Trigeminal Neuralgia
Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger
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Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia
Procedia PDF Downloads 685441 Weighted Risk Scores Method Proposal for Occupational Safety Risk Assessment
Authors: Ulas Cinar, Omer Faruk Ugurlu, Selcuk Cebi
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Occupational safety risk management is the most important element of a safe working environment. Effective risk management can only be possible with accurate analysis and evaluations. Scoring-based risk assessment methods offer considerable ease of application as they convert linguistic expressions into numerical results. It can also be easily adapted to any field. Contrary to all these advantages, important problems in scoring-based methods are frequently discussed. Effective measurability is one of the most critical problems. Existing methods allow experts to choose a score equivalent to each parameter. Therefore, experts prefer the score of the most likely outcome for risk. However, all other possible consequences are neglected. Assessments of the existing methods express the most probable level of risk, not the real risk of the enterprises. In this study, it is aimed to develop a method that will present a more comprehensive evaluation compared to the existing methods by evaluating the probability and severity scores, all sub-parameters, and potential results, and a new scoring-based method is proposed in the literature.Keywords: occupational health and safety, risk assessment, scoring based risk assessment method, underground mining, weighted risk scores
Procedia PDF Downloads 1295440 Logical-Probabilistic Modeling of the Reliability of Complex Systems
Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia
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The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element
Procedia PDF Downloads 575439 Probabilistic Study of Impact Threat to Civil Aircraft and Realistic Impact Energy
Authors: Ye Zhang, Chuanjun Liu
Abstract:
In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.Keywords: composite structure, damage tolerance, impact threat, probabilistic
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