Search results for: STOCHASTIC
215 Quality of Service of Transportation Networks: A Hybrid Measurement of Travel Time and Reliability
Authors: Chin-Chia Jane
Abstract:
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 216214 Model of Optimal Centroids Approach for Multivariate Data Classification
Authors: Pham Van Nha, Le Cam Binh
Abstract:
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization
Procedia PDF Downloads 202213 Stochastic Modeling of Secretion Dynamics in Inner Hair Cells of the Auditory Pathway
Authors: Jessica A. Soto-Bear, Virginia González-Vélez, Norma Castañeda-Villa, Amparo Gil
Abstract:
Glutamate release of the cochlear inner hair cell (IHC) ribbon synapse is a fundamental step in transferring sound information in the auditory pathway. Otoferlin is the calcium sensor in the IHC and its activity has been related to many auditory disorders. In order to simulate secretion dynamics occurring in the IHC in a few milliseconds timescale and with high spatial resolution, we proposed an active-zone model solved with Monte Carlo algorithms. We included models for calcium buffered diffusion, calcium-binding schemes for vesicle fusion, and L-type voltage-gated calcium channels. Our results indicate that calcium influx and calcium binding is managing IHC secretion as a function of voltage depolarization, which in turn mean that IHC response depends on sound intensity.Keywords: inner hair cells, Monte Carlo algorithm, Otoferlin, secretion
Procedia PDF Downloads 214212 Analysis of Technical Efficiency and Its Determinants among Cattle Fattening Enterprises in Kebbi State, Nigeria
Authors: Gona Ayuba, Isiaka Mohammed, Kotom Mohammed Baba, Mohammed Aabubakar Maikasuwa
Abstract:
The study examined the technical efficiency and its determinants of cattle fattening enterprises in Kebbi state, Nigeria. Data were collected from a sample of 160 fatteners between June 2010 and June 2011 using the multistage random sampling technique. Translog stochastic frontier production function was employed for the analysis. Results of the analysis show that technical efficiency indices varied from 0.74 to 0.98%, with a mean of 0.90%, indicating that there was no wide gap between the efficiency of best technical efficient fatteners and that of the average fattener. The result also showed that fattening experience and herd size influenced the level of technical efficiency at 1% levels. It is recommended that credit agencies should ensure that credit made available to the fatteners is monitored to ensure appropriate utilization.Keywords: technical efficiency, determinants, cattle, fattening enterprises
Procedia PDF Downloads 437211 Obsessive-Compulsive Disorder: Development of Demand-Controlled Deep Brain Stimulation with Methods from Stochastic Phase Resetting
Authors: Mahdi Akhbardeh
Abstract:
Synchronization of neuronal firing is a hallmark of several neurological diseases. Recently, stimulation techniques have been developed which make it possible to desynchronize oscillatory neuronal activity in a mild and effective way, without suppressing the neurons' firing. As yet, these techniques are being used to establish demand-controlled deep brain stimulation (DBS) techniques for the therapy of movement disorders like severe Parkinson's disease or essential tremor. We here present a first conceptualization suggesting that the nucleus accumbens is a promising target for the standard, that is, permanent high-frequency, DBS in patients with severe and chronic obsessive-compulsive disorder (OCD). In addition, we explain how demand-controlled DBS techniques may be applied to the therapy of OCD in those cases that are refractory to behavioral therapies and pharmacological treatment.Keywords: stereotactic neurosurgery, deep brain stimulation, obsessive-compulsive disorder, phase resetting
Procedia PDF Downloads 508210 Commodity Price Shocks and Monetary Policy
Authors: Faisal Algosair
Abstract:
We examine the role of monetary policy in the presence of commodity price shocks using a Dynamic stochastic general equilibrium (DSGE) model with price and wage rigidities. The model characterizes a commodity exporter by its degree of export diversification, and explores the following monetary regimes: flexible domestic inflation targeting; flexible Consumer Price Index inflation targeting; exchange rate peg; and optimal rule. An increase in the degree of diversification is found to mitigate responses to commodity shocks. The welfare comparison suggests that a flexible exchange rate regime under the optimal rule is preferred to an exchange rate peg. However, monetary policy provides limited stabilization effects in an economy with low degree of export diversification.Keywords: business cycle, commodity price, exchange rate, global financial cycle
Procedia PDF Downloads 91209 Effective Scheduling of Hybrid Reconfigurable Microgrids Considering High Penetration of Renewable Sources
Authors: Abdollah Kavousi Fard
Abstract:
This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.Keywords: microgrid, renewable energy sources, reconfiguration, optimization
Procedia PDF Downloads 263208 Disruption Coordination of Supply Chain with Loss-Averse Retailer Under Buy-Back Contract
Abstract:
This paper aims to investigate a two stage supply chain of one leading supplier and one following retailer that experiences two factors perturbation out of supplier's production cost, retailer's marginal cost and retail price in stochastic demand environment. Granted that risk neutral condition has long been discussed, little attention has been given to disruptions under the premise of risk neutral supplier and risk aversion retailer. We establish the optimal order quantity and revealed the profit distribution coefficient in risk-neutral static model, make adjustment under disruption scenario, and then select utility function method for risk aversion model. Using buy-back contract policy, the improvement of parameters can achieve channel coordination where Pareto optimal is realized.Keywords: supply chain coordination, disruption management, buy-back contract, lose aversion
Procedia PDF Downloads 321207 General Mathematical Framework for Analysis of Cattle Farm System
Authors: Krzysztof Pomorski
Abstract:
In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations
Procedia PDF Downloads 136206 Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution
Authors: Tomoaki Hashimoto
Abstract:
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 573205 Data-Driven Dynamic Overbooking Model for Tour Operators
Authors: Kannapha Amaruchkul
Abstract:
We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator
Procedia PDF Downloads 125204 Mean-Field Type Modeling of Non-Local Congestion in Pedestrian Crowd Dynamics
Authors: Alexander Aurell
Abstract:
One of the latest trends in the modeling of human crowds is the mean-field game approach. In the mean-field game approach, the motion of a human crowd is described by a nonstandard stochastic optimal control problem. It is nonstandard since congestion is considered, introduced through a dependence in the performance functional on the distribution of the crowd. This study extends the class of mean-field pedestrian crowd models to allow for non-local congestion and arbitrary, but finitely, many interacting crowds. The new congestion feature grants pedestrians a 'personal space' where crowding is undesirable. The model is treated as a mean-field type game which is derived from a particle picture. This, in contrast to a mean-field game, better describes a situation where the crowd can be controlled by a central planner. The latter is suitable for decentralized situations. Solutions to the mean-field type game are characterized via a Pontryagin-type Maximum Principle.Keywords: congestion, crowd dynamics, interacting populations, mean-field approximation, optimal control
Procedia PDF Downloads 437203 Closed-Form Sharma-Mittal Entropy Rate for Gaussian Processes
Authors: Septimia Sarbu
Abstract:
The entropy rate of a stochastic process is a fundamental concept in information theory. It provides a limit to the amount of information that can be transmitted reliably over a communication channel, as stated by Shannon's coding theorems. Recently, researchers have focused on developing new measures of information that generalize Shannon's classical theory. The aim is to design more efficient information encoding and transmission schemes. This paper continues the study of generalized entropy rates, by deriving a closed-form solution to the Sharma-Mittal entropy rate for Gaussian processes. Using the squeeze theorem, we solve the limit in the definition of the entropy rate, for different values of alpha and beta, which are the parameters of the Sharma-Mittal entropy. In the end, we compare it with Shannon and Rényi's entropy rates for Gaussian processes.Keywords: generalized entropies, Sharma-Mittal entropy rate, Gaussian processes, eigenvalues of the covariance matrix, squeeze theorem
Procedia PDF Downloads 508202 Spatio-Temporal Properties of p53 States Raised by Glucose
Authors: Md. Jahoor Alam
Abstract:
Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.Keywords: oscillation, temporal behavior, p53, glucose
Procedia PDF Downloads 293201 Coarse-Graining in Micromagnetic Simulations of Magnetic Hyperthermia
Authors: Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod
Abstract:
Micromagnetic simulations based on the stochastic Landau-Lifshitz-Gilbert equation are used to calculate dynamic magnetic hysteresis loops relevant to magnetic hyperthermia applications. With the goal to effectively simulate room-temperature loops for large iron-oxide based systems at relatively slow sweep rates on the order of 1 Oe/ns or less, a coarse-graining scheme is proposed and tested. The scheme is derived from a previously developed renormalization-group approach. Loops associated with nanorods, used as building blocks for larger nanoparticles that were employed in preclinical trials (Dennis et al., 2009 Nanotechnology 20 395103), serve as the model test system. The scaling algorithm is shown to produce nearly identical loops over several decades in the model grain sizes. Sweep-rate scaling involving the damping constant alpha is also demonstrated.Keywords: coarse-graining, hyperthermia, hysteresis loops, micromagnetic simulations
Procedia PDF Downloads 141200 Persistent Homology of Convection Cycles in Network Flows
Authors: Minh Quang Le, Dane Taylor
Abstract:
Convection is a well-studied topic in fluid dynamics, yet it is less understood in the context of networks flows. Here, we incorporate techniques from topological data analysis (namely, persistent homology) to automate the detection and characterization of convective/cyclic/chiral flows over networks, particularly those that arise for irreversible Markov chains (MCs). As two applications, we study convection cycles arising under the PageRank algorithm, and we investigate chiral edges flows for a stochastic model of a bi-monomer's configuration dynamics. Our experiments highlight how system parameters---e.g., the teleportation rate for PageRank and the transition rates of external and internal state changes for a monomer---can act as homology regularizers of convection, which we summarize with persistence barcodes and homological bifurcation diagrams. Our approach establishes a new connection between the study of convection cycles and homology, the branch of mathematics that formally studies cycles, which has diverse potential applications throughout the sciences and engineering.Keywords: homology, persistent homolgy, markov chains, convection cycles, filtration
Procedia PDF Downloads 128199 Cyclostationary Gaussian Linearization for Analyzing Nonlinear System Response Under Sinusoidal Signal and White Noise Excitation
Authors: R. J. Chang
Abstract:
A cyclostationary Gaussian linearization method is formulated for investigating the time average response of nonlinear system under sinusoidal signal and white noise excitation. The quantitative measure of cyclostationary mean, variance, spectrum of mean amplitude, and mean power spectral density of noise is analyzed. The qualitative response behavior of stochastic jump and bifurcation are investigated. The validity of the present approach in predicting the quantitative and qualitative statistical responses is supported by utilizing Monte Carlo simulations. The present analysis without imposing restrictive analytical conditions can be directly derived by solving non-linear algebraic equations. The analytical solution gives reliable quantitative and qualitative prediction of mean and noise response for the Duffing system subjected to both sinusoidal signal and white noise excitation.Keywords: cyclostationary, duffing system, Gaussian linearization, sinusoidal, white noise
Procedia PDF Downloads 478198 A Reinforcement Learning Approach for Evaluation of Real-Time Disaster Relief Demand and Network Condition
Authors: Ali Nadi, Ali Edrissi
Abstract:
Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.Keywords: disaster management, real-time demand, reinforcement learning, relief demand
Procedia PDF Downloads 307197 The Performance of Saudi Banking Industry 2000 -2011: Have the Banks Distinguished Themselves from One Another?
Authors: Bukhari M. S. Sillah, Imran Khokhar, Muhammad Nauman Khan
Abstract:
This paper studies the technical efficiency of Saudi banking sector using stochastic frontier model. A sample of 12 banks over the period 2000-2011 is selected to investigate their technical efficiencies in mobilizing deposits, producing investment and generating income. The banks are categorized as Saudi-owned banks, Saudi-foreign-owned banks and Islamic banks. The findings show some consistent pattern of these bank types; and there exist significant disparities among the banks in term of technical efficiency. The Banque Saudi Fransi stands out as a benchmark bank for the industry, and it is a Saudi-foreign owned bank type. The Saudi owned bank types have shown fluctuating performance during the period; and the Islamic bank types are no significantly different from Saudi-owned bank types.Keywords: technical efficiency, production frontier model, Islamic banking
Procedia PDF Downloads 478196 Quantifying Freeway Capacity Reductions by Rainfall Intensities Based on Stochastic Nature of Flow Breakdown
Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson
Abstract:
This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.
Keywords: capacity randomness, flow breakdown, freeway capacity, rainfall
Procedia PDF Downloads 376195 Air Cargo Overbooking Model under Stochastic Weight and Volume Cancellation
Authors: Naragain Phumchusri, Krisada Roekdethawesab, Manoj Lohatepanont
Abstract:
Overbooking is an approach of selling more goods or services than available capacities because sellers anticipate that some buyers will not show-up or may cancel their bookings. At present, many airlines deploy overbooking strategy in order to deal with the uncertainty of their customers. Particularly, some airlines sell more cargo capacity than what they have available to freight forwarders with beliefs that some of them will cancel later. In this paper, we propose methods to find the optimal overbooking level of volume and weight for air cargo in order to minimize the total cost, containing cost of spoilage and cost of offloaded. Cancellations of volume and weight are jointly random variables with a known joint distribution. Heuristic approaches applying the idea of weight and volume independency is considered to find an appropriate answer to the full problem. Computational experiments are used to explore the performance of approaches presented in this paper, as compared to a naïve method under different scenarios.Keywords: air cargo overbooking, offloading capacity, optimal overbooking level, revenue management, spoilage capacity
Procedia PDF Downloads 318194 Micromechanical Analysis of Interface Properties Effects on Transverse Tensile Response of Fiber-Reinforced Composites
Authors: M. Naderi, N. Iyyer, K. Goel, N. Phan
Abstract:
A micromechanical analysis of the influence of fiber-matrix interface fracture properties on the transverse tensile response of fiber-reinforced composite is investigated. Augmented finite element method (AFEM) is used to provide high-fidelity damage initiation and propagation along the micromechanical analysis. Effects of fiber volume fraction and fiber shapes are also studies in representative volume elements (RVE) to capture the stochastic behavior of the composite under loading. In addition, defects and voids influence on the composite response are investigated in micromechanical analysis. The results reveal that the response of RVE with constant interface properties overestimates the composite transverse strength. It is also seen that the damage initiation and propagation locations are controlled by the distributions of fracture properties, fibers’ shapes, and defects.Keywords: cohesive model, fracture, computational mechanics, micromechanics
Procedia PDF Downloads 287193 Maximizing Coverage with Mobile Crime Cameras in a Stochastic Spatiotemporal Bipartite Network
Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup
Abstract:
This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis
Procedia PDF Downloads 102192 Divergence of Innovation Capabilities within the EU
Authors: Vishal Jaunky, Jonas Grafström
Abstract:
The development of the European Union’s (EU) single economic market and rapid technological change has resulted in major structural changes in EU’s member states economies. The general liberalization process that the countries has undergone together has convinced the governments of the member states of need to upgrade their economic and training systems in order to be able to face the economic globalization. Several signs of economic convergence have been found but less is known about the knowledge production. This paper addresses the convergence pattern of technological innovation in 13 European Union (EU) states over the time period 1990-2011 by means of parametric and non-parametric techniques. Parametric approaches revolve around the neoclassical convergence theories. This paper reveals divergence of both the β and σ types. Further, we found evidence of stochastic divergence and non-parametric convergence approach such as distribution dynamics shows a tendency towards divergence. This result is supported with the occurrence of γ-divergence. The policies of the EU to reduce technological gap among its member states seem to be missing its target, something that can have negative long run consequences for the market.Keywords: convergence, patents, panel data, European union
Procedia PDF Downloads 281191 An Alternative Richards’ Growth Model Based on Hyperbolic Sine Function
Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu
Abstract:
Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model
Procedia PDF Downloads 386190 Nonequilibrium Effects in Photoinduced Ultrafast Charge Transfer Reactions
Authors: Valentina A. Mikhailova, Serguei V. Feskov, Anatoly I. Ivanov
Abstract:
In the last decade the nonequilibrium charge transfer have attracted considerable interest from the scientific community. Examples of such processes are the charge recombination in excited donor-acceptor complexes and the intramolecular electron transfer from the second excited electronic state. In these reactions the charge transfer proceeds predominantly in the nonequilibrium mode. In the excited donor-acceptor complexes the nuclear nonequilibrium is created by the pump pulse. The intramolecular electron transfer from the second excited electronic state is an example where the nuclear nonequilibrium is created by the forward electron transfer. The kinetics of these nonequilibrium reactions demonstrate a number of peculiar properties. Most important from them are: (i) the absence of the Marcus normal region in the free energy gap law for the charge recombination in excited donor-acceptor complexes, (ii) extremely low quantum yield of thermalized charge separated state in the ultrafast charge transfer from the second excited state, (iii) the nonexponential charge recombination dynamics in excited donor-acceptor complexes, (iv) the dependence of the charge transfer rate constant on the excitation pulse frequency. This report shows that most of these kinetic features can be well reproduced in the framework of stochastic point-transition multichannel model. The model involves an explicit description of the nonequilibrium excited state formation by the pump pulse and accounts for the reorganization of intramolecular high-frequency vibrational modes, for their relaxation as well as for the solvent relaxation. The model is able to quantitatively reproduce complex nonequilibrium charge transfer kinetics observed in modern experiments. The interpretation of the nonequilibrium effects from a unified point of view in the terms of the multichannel point transition stochastic model allows to see similarities and differences of electron transfer mechanism in various molecular donor-acceptor systems and formulates general regularities inherent in these phenomena. The nonequilibrium effects in photoinduced ultrafast charge transfer which have been studied for the last 10 years are analyzed. The methods of suppression of the ultrafast charge recombination, similarities and dissimilarities of electron transfer mechanism in different molecular donor-acceptor systems are discussed. The extremely low quantum yield of the thermalized charge separated state observed in the ultrafast charge transfer from the second excited state in the complex consisting of 1,2,4-trimethoxybenzene and tetracyanoethylene in acetonitrile solution directly demonstrates that its effectiveness can be close to unity. This experimental finding supports the idea that the nonequilibrium charge recombination in the excited donor-acceptor complexes can be also very effective so that the part of thermalized complexes is negligible. It is discussed the regularities inherent to the equilibrium and nonequilibrium reactions. Their fundamental differences are analyzed. Namely the opposite dependencies of the charge transfer rates on the dynamical properties of the solvent. The increase of the solvent viscosity results in decreasing the thermal rate and vice versa increasing the nonequilibrium rate. The dependencies of the rates on the solvent reorganization energy and the free energy gap also can considerably differ. This work was supported by the Russian Science Foundation (Grant No. 16-13-10122).Keywords: Charge recombination, higher excited states, free energy gap law, nonequilibrium
Procedia PDF Downloads 319189 Improving the Efficiency of a High Pressure Turbine by Using Non-Axisymmetric Endwall: A Comparison of Two Optimization Algorithms
Authors: Abdul Rehman, Bo Liu
Abstract:
Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization
Procedia PDF Downloads 221188 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
Abstract:
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 410187 Detecting Cyberbullying, Spam and Bot Behavior and Fake News in Social Media Accounts Using Machine Learning
Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana
Abstract:
Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning
Procedia PDF Downloads 28186 Towards an Enhanced Compartmental Model for Profiling Malware Dynamics
Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova
Abstract:
We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.Keywords: cybersecurity, epidemiology, cyber epidemiology, malware
Procedia PDF Downloads 101