Search results for: random match probability
3461 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 5733460 Stabilization of Rotational Motion of Spacecrafts Using Quantized Two Torque Inputs Based on Random Dither
Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara
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The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.Keywords: spacecraft control, quantized control, nonlinear control, random dither method
Procedia PDF Downloads 1733459 Random Forest Classification for Population Segmentation
Authors: Regina Chua
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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling
Procedia PDF Downloads 883458 Statistical Characteristics of Distribution of Radiation-Induced Defects under Random Generation
Authors: P. Selyshchev
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We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.Keywords: irradiation, primary defects, interaction, fluctuations
Procedia PDF Downloads 3353457 Quality of Service of Transportation Networks: A Hybrid Measurement of Travel Time and Reliability
Authors: Chin-Chia Jane
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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.Keywords: quality of service, reliability, transportation network, travel time
Procedia PDF Downloads 2163456 Reliability-Based Method for Assessing Liquefaction Potential of Soils
Authors: Mehran Naghizaderokni, Asscar Janalizadechobbasty
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This paper explores probabilistic method for assessing the liquefaction potential of sandy soils. The current simplified methods for assessing soil liquefaction potential use a deterministic safety factor in order to determine whether liquefaction will occur or not. However, these methods are unable to determine the liquefaction probability related to a safety factor. A solution to this problem can be found by reliability analysis.This paper presents a reliability analysis method based on the popular certain liquefaction analysis method. The proposed probabilistic method is formulated based on the results of reliability analyses of 190 field records and observations of soil performance against liquefaction. The results of the present study show that confidence coefficient greater and smaller than 1 does not mean safety and/or liquefaction in cadence for liquefaction, and for assuring liquefaction probability, reliability based method analysis should be used. This reliability method uses the empirical acceleration attenuation law in the Chalos area to derive the probability density distribution function and the statistics for the earthquake-induced cyclic shear stress ratio (CSR). The CSR and CRR statistics are used in continuity with the first order and second moment method to calculate the relation between the liquefaction probability, the safety factor and the reliability index. Based on the proposed method, the liquefaction probability related to a safety factor can be easily calculated. The influence of some of the soil parameters on the liquefaction probability can be quantitatively evaluated.Keywords: liquefaction, reliability analysis, chalos area, civil and structural engineering
Procedia PDF Downloads 4623455 Quality of the Ruin Probabilities Approximation Using the Regenerative Processes Approach regarding to Large Claims
Authors: Safia Hocine, Djamil Aïssani
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Risk models, recently studied in the literature, are becoming increasingly complex. It is rare to find explicit analytical relations to calculate the ruin probability. Indeed, the stability issue occurs naturally in ruin theory, when parameters in risk cannot be estimated than with uncertainty. However, in most cases, there are no explicit formulas for the ruin probability. Hence, the interest to obtain explicit stability bounds for these probabilities in different risk models. In this paper, we interest to the stability bounds of the univariate classical risk model established using the regenerative processes approach. By adopting an algorithmic approach, we implement this approximation and determine numerically the bounds of ruin probability in the case of large claims (heavy-tailed distribution).Keywords: heavy-tailed distribution, large claims, regenerative process, risk model, ruin probability, stability
Procedia PDF Downloads 3543454 Analysis of the Unreliable M/G/1 Retrial Queue with Impatient Customers and Server Vacation
Authors: Fazia Rahmoune, Sofiane Ziani
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Retrial queueing systems have been extensively used to stochastically model many problems arising in computer networks, telecommunication, telephone systems, among others. In this work, we consider a $M/G/1$ retrial queue with an unreliable server with random vacations and two types of primary customers, persistent and impatient. This model involves the unreliability of the server, which can be subject to physical breakdowns and takes into account the correctives maintenances for restoring the service when a failure occurs. On the other hand, we consider random vacations, which can model the preventives maintenances for improving system performances and preventing breakdowns. We give the necessary and sufficient stability condition of the system. Then, we obtain the joint probability distribution of the server state and the number of customers in orbit and derive the more useful performance measures analytically. Moreover, we also analyze the busy period of the system. Finally, we derive the stability condition and the generating function of the stationary distribution of the number of customers in the system when there is no vacations and impatient customers, and when there is no vacations, server failures and impatient customers.Keywords: modeling, retrial queue, unreliable server, vacation, stochastic analysis
Procedia PDF Downloads 1783453 Generation of Symmetric Key Using Randomness of Hash Function
Authors: Sai Charan Kamana, Harsha Vardhan Nakkina, B.R. Chandavarkar
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In a highly secure and robust key generation process, a key role is played by randomness and random numbers when current real-world cryptosystems are observed. Most of the present-day cryptographic protocols depend upon the Random Number Generators (RNG), Pseudo-Random Number Generator (PRNG). These protocols often use noisy channels such as Disk seek time, CPU temperature, Mouse pointer movement, Fan noise to obtain true random values. Despite being cost-effective, these noisy channels may need additional hardware devices to continuously communicate with them. On the other hand, Hash functions are Pseudo-Random (because of their requirements). So, they are a good replacement for these noisy channels and have low hardware requirements. This paper discusses, some of the key generation methodologies, and their drawbacks. This paper explains how hash functions can be used in key generation, how to combine Key Derivation Functions with hash functions.Keywords: key derivation, hash based key derivation, password based key derivation, symmetric key derivation
Procedia PDF Downloads 1553452 Evaluation of Best-Fit Probability Distribution for Prediction of Extreme Hydrologic Phenomena
Authors: Karim Hamidi Machekposhti, Hossein Sedghi
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The probability distributions are the best method for forecasting of extreme hydrologic phenomena such as rainfall and flood flows. In this research, in order to determine suitable probability distribution for estimating of annual extreme rainfall and flood flows (discharge) series with different return periods, precipitation with 40 and discharge with 58 years time period had been collected from Karkheh River at Iran. After homogeneity and adequacy tests, data have been analyzed by Stormwater Management and Design Aid (SMADA) software and residual sum of squares (R.S.S). The best probability distribution was Log Pearson Type III with R.S.S value (145.91) and value (13.67) for peak discharge and Log Pearson Type III with R.S.S values (141.08) and (8.95) for maximum discharge in Jelogir Majin and Pole Zal stations, respectively. The best distribution for maximum precipitation in Jelogir Majin and Pole Zal stations was Log Pearson Type III distribution with R.S.S values (1.74&1.90) and then Pearson Type III distribution with R.S.S values (1.53&1.69). Overall, the Log Pearson Type III distributions are acceptable distribution types for representing statistics of extreme hydrologic phenomena in Karkheh River at Iran with the Pearson Type III distribution as a potential alternative.Keywords: Karkheh River, Log Pearson Type III, probability distribution, residual sum of squares
Procedia PDF Downloads 1933451 Reliability Analysis for Cyclic Fatigue Life Prediction in Railroad Bolt Hole
Authors: Hasan Keshavarzian, Tayebeh Nesari
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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis
Procedia PDF Downloads 3763450 Development of Probability Distribution Models for Degree of Bending (DoB) in Chord Member of Tubular X-Joints under Bending Loads
Authors: Hamid Ahmadi, Amirreza Ghaffari
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Fatigue life of tubular joints in offshore structures is not only dependent on the value of hot-spot stress, but is also significantly influenced by the through-the-thickness stress distribution characterized by the degree of bending (DoB). The DoB exhibits considerable scatter calling for greater emphasis in accurate determination of its governing probability distribution which is a key input for the fatigue reliability analysis of a tubular joint. Although the tubular X-joints are commonly found in offshore jacket structures, as far as the authors are aware, no comprehensive research has been carried out on the probability distribution of the DoB in tubular X-joints. What has been used so far as the probability distribution of the DoB in reliability analyses is mainly based on assumptions and limited observations, especially in terms of distribution parameters. In the present paper, results of parametric equations available for the calculation of the DoB have been used to develop probability distribution models for the DoB in the chord member of tubular X-joints subjected to four types of bending loads. Based on a parametric study, a set of samples was prepared and density histograms were generated for these samples using Freedman-Diaconis method. Twelve different probability density functions (PDFs) were fitted to these histograms. The maximum likelihood method was utilized to determine the parameters of fitted distributions. In each case, Kolmogorov-Smirnov test was used to evaluate the goodness of fit. Finally, after substituting the values of estimated parameters for each distribution, a set of fully defined PDFs have been proposed for the DoB in tubular X-joints subjected to bending loads.Keywords: tubular X-joint, degree of bending (DoB), probability density function (PDF), Kolmogorov-Smirnov goodness-of-fit test
Procedia PDF Downloads 7143449 Estimation of Population Mean under Random Non-Response in Two-Phase Successive Sampling
Authors: M. Khalid, G. N. Singh
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In this paper, we have considered the problem of estimation for population mean, on current (second) occasion in the presence of random non response in two-occasion successive sampling under two phase set-up. Modified exponential type estimators have been proposed, and their properties are studied under the assumptions that numbers of sampling units follow a distribution due to random non response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.Keywords: successive sampling, random non-response, auxiliary variable, bias, mean square error
Procedia PDF Downloads 5133448 Determining Best Fitting Distributions for Minimum Flows of Streams in Gediz Basin
Authors: Naci Büyükkaracığan
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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.Keywords: Gediz Basin, goodness-of-fit tests, minimum flows, probability distribution
Procedia PDF Downloads 2683447 Spatially Random Sampling for Retail Food Risk Factors Study
Authors: Guilan Huang
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In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.Keywords: geospatial technology, restaurant, retail food risk factor study, spatially random sampling
Procedia PDF Downloads 3473446 TRNG Based Key Generation for Certificateless Signcryption
Authors: S.Balaji, R.Sujatha, M. Ramakrishnan
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Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously in low cost when compared with the traditional signature-then-encryption approach. In this paper, we propose a novel mouse movement based key generation technique to generate secret keys which is secure against the outer and insider attacks. Tag Key Encapsulation Mechanism (KEM) process is implemented using True Random Number Generator (TRNG) method. This TRNG based key is used for data encryption in the Data Encapsulation Mechanism (DEM). We compare the statistical reports of the proposed system with the previous methods which implements TKEM based on pseudo random number generatorKeywords: pseudo random umber generator, signcryption, true random number generator, node deployment
Procedia PDF Downloads 3373445 Nonlinear Analysis with Failure Using the Boundary Element Method
Authors: Ernesto Pineda Leon, Dante Tolentino Lopez, Janis Zapata Lopez
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The current paper shows the application of the boundary element method for the analysis of plates under shear stress causing plasticity. In this case, the shear deformation of a plate is considered by means of the Reissner’s theory. The probability of failure of a Reissner’s plate due to a proposed index plastic behavior is calculated taken into account the uncertainty in mechanical and geometrical properties. The problem is developed in two dimensions. The classic plasticity’s theory is applied and a formulation for initial stresses that lead to the boundary integral equations due to plasticity is also used. For the plasticity calculation, the Von Misses criteria is used. To solve the non-linear equations an incremental method is employed. The results show a relatively small failure probability for the ranges of loads between 0.6 and 1.0. However, for values between 1.0 and 2.5, the probability of failure increases significantly. Consequently, for load bigger than 2.5 the plate failure is a safe event. The results are compared to those that were found in the literature and the agreement is good.Keywords: boundary element method, failure, plasticity, probability
Procedia PDF Downloads 3033444 Evaluation of Expected Annual Loss Probabilities of RC Moment Resisting Frames
Authors: Saemee Jun, Dong-Hyeon Shin, Tae-Sang Ahn, Hyung-Joon Kim
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Building loss estimation methodologies which have been advanced considerably in recent decades are usually used to estimate socio and economic impacts resulting from seismic structural damage. In accordance with these methods, this paper presents the evaluation of an annual loss probability of a reinforced concrete moment resisting frame designed according to Korean Building Code. The annual loss probability is defined by (1) a fragility curve obtained from a capacity spectrum method which is similar to a method adopted from HAZUS, and (2) a seismic hazard curve derived from annual frequencies of exceedance per peak ground acceleration. Seismic fragilities are computed to calculate the annual loss probability of a certain structure using functions depending on structural capacity, seismic demand, structural response and the probability of exceeding damage state thresholds. This study carried out a nonlinear static analysis to obtain the capacity of a RC moment resisting frame selected as a prototype building. The analysis results show that the probability of being extensive structural damage in the prototype building is expected to 0.004% in a year.Keywords: expected annual loss, loss estimation, RC structure, fragility analysis
Procedia PDF Downloads 3943443 Numerical Simulations on Feasibility of Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization
Authors: Taiki Baba, Tomoaki Hashimoto
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The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.Keywords: model predictive control, stochastic systems, probabilistic constraints, random dither quantization
Procedia PDF Downloads 2743442 Coverage Probability Analysis of WiMAX Network under Additive White Gaussian Noise and Predicted Empirical Path Loss Model
Authors: Chaudhuri Manoj Kumar Swain, Susmita Das
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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis
Procedia PDF Downloads 1643441 Improving Decision Support for Organ Transplant
Authors: Ian McCulloh, Andrew Placona, Darren Stewart, Daniel Gause, Kevin Kiernan, Morgan Stuart, Christopher Zinner, Laura Cartwright
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An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.Keywords: decision science, KDPI, optimism bias, organ transplant
Procedia PDF Downloads 983440 Estimation of Population Mean under Random Non-Response in Two-Occasion Successive Sampling
Authors: M. Khalid, G. N. Singh
Abstract:
In this paper, we have considered the problems of estimation for the population mean on current (second) occasion in two-occasion successive sampling under random non-response situations. Some modified exponential type estimators have been proposed and their properties are studied under the assumptions that the number of sampling unit follows a discrete distribution due to random non-response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.Keywords: modified exponential estimator, successive sampling, random non-response, auxiliary variable, bias, mean square error
Procedia PDF Downloads 3453439 Numerical Study of Natural Convection Heat Transfer Performance in an Inclined Cavity: Nanofluid and Random Temperature
Authors: Hicham Salhi, Mohamed Si-Ameur, Nadjib Chafai
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Natural convection of a nanofluid consisting of water and nanoparticles (Ag or TiO2) in an inclined enclosure cavity, has been studied numerically, heated by a (random temperature, based on the random function). The governing equations are solved numerically using the finite-volume. Results are presented in the form of streamlines, isotherms, and average Nusselt number. In addition, a parametric study is carried out to examine explicitly the volume fraction effects of nanoparticles (Ψ= 0.1, 0.2), the Rayleigh number (Ra=103, 104, 105, 106),the inclination angle of the cavity( égale à 0°, 30°, 45°, 90°, 135°, 180°), types of temperature (constant ,random), types of (NF) (Ag andTiO2). The results reveal that (NPs) addition remarkably enhances heat transfer in the cavity especially for (Ψ= 0.2). Besides, the effect of inclination angle and type of temperature is more pronounced at higher Rayleigh number.Keywords: nanofluid, natural convection, inclined cavity, random temperature, finite-volume
Procedia PDF Downloads 2803438 Virtual Player for Learning by Observation to Assist Karate Training
Authors: Kazumoto Tanaka
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It is well known that sport skill learning is facilitated by video observation of players’ actions in sports. The optimal viewpoint for the observation of actions depends on sport scenes. On the other hand, it is impossible to change viewpoint for the observation in general, because most videos are filmed from fixed points. The study has tackled the problem and focused on karate match as a first step. The study developed a method for observing karate player’s actions from any point of view by using 3D-CG model (i.e. virtual player) obtained from video images, and verified the effectiveness of the method on karate match.Keywords: computer graphics, karate training, learning by observation, motion capture, virtual player
Procedia PDF Downloads 2693437 A Hyperexponential Approximation to Finite-Time and Infinite-Time Ruin Probabilities of Compound Poisson Processes
Authors: Amir T. Payandeh Najafabadi
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This article considers the problem of evaluating infinite-time (or finite-time) ruin probability under a given compound Poisson surplus process by approximating the claim size distribution by a finite mixture exponential, say Hyperexponential, distribution. It restates the infinite-time (or finite-time) ruin probability as a solvable ordinary differential equation (or a partial differential equation). Application of our findings has been given through a simulation study.Keywords: ruin probability, compound poisson processes, mixture exponential (hyperexponential) distribution, heavy-tailed distributions
Procedia PDF Downloads 3323436 Disaggregation the Daily Rainfall Dataset into Sub-Daily Resolution in the Temperate Oceanic Climate Region
Authors: Mohammad Bakhshi, Firas Al Janabi
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High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.Keywords: DiMoN Tool, disaggregation, exceedance probability, Kolmogorov-Smirnov test, rainfall
Procedia PDF Downloads 1973435 An Insite to the Probabilistic Assessment of Reserves in Conventional Reservoirs
Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar
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The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.Keywords: simulation, probability, confidence interval, sensitivity analysis
Procedia PDF Downloads 3753434 Random Subspace Ensemble of CMAC Classifiers
Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi
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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.Keywords: classification, random subspace, ensemble, CMAC neural network
Procedia PDF Downloads 3233433 Using Indigenous Games to Demystify Probability Theorem in Ghanaian Classrooms: Mathematical Analysis of Ampe
Authors: Peter Akayuure, Michael Johnson Nabie
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Similar to many colonized nations in the world, one indelible mark left by colonial masters after Ghana’s independence in 1957 has been the fact that many contexts used to teach statistics and probability concepts are often alien and do not resonate with the social domain of our indigenous Ghanaian child. This has seriously limited the understanding, discoveries, and applications of mathematics for national developments. With the recent curriculum demands of making the Ghanaian child mathematically literate, this qualitative study involved video recordings and mathematical analysis of play sessions of an indigenous girl game called Ampe with the aim to demystify the concepts in probability theorem, which is applied in mathematics related fields of study. The mathematical analysis shows that the game of Ampe, which is widely played by school girls in Ghana, is suitable for learning concepts of the probability theorems. It was also revealed that as a girl game, the use of Ampe provides good lessons to educators, textbook writers, and teachers to rethink about the selection of mathematics tasks and learning contexts that are sensitive to gender. As we undertake to transform teacher education and student learning, the use of indigenous games should be critically revisited.Keywords: Ampe, mathematical analysis, probability theorem, Ghanaian girl game
Procedia PDF Downloads 3633432 Preliminary Results on a Maximum Mean Discrepancy Approach for Seizure Detection
Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary
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We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning
Procedia PDF Downloads 229