Search results for: dynamic stochastic general equilibrium

Authors: Wahyu Kurniawan

Abstract:

Indonesia developed the legal system radically since 1999. Several laws have been established and mostly the result of transplantation. Laws were made general but legal problems have been growing. In the legal enforcement, the judges have authority to interpret the laws. Authority and freedom are the source of corruption by the courts in Indonesia. Therefore, it should be built the conceptual framework to interpret the transplanted laws as the legal basis in deciding the cases. This article describes legal development based on interpretation of transplanted law in Indonesia by using the Indonesian Supervisory Commission for Business Competition (KPPU) decisions between 2000 and 2010 as the object of the research. The study was using law as a system theory and theories of legal interpretation especially the static and dynamic interpretations. The research showed that the KPPU interpreted the concept that exists in the Competition Law by using static and dynamic interpretation. Static interpretation was used to interpret the legal concepts based on two grounds, minute of meeting during law making process and the definitions that have been recognized in the Indonesian legal system. Dynamic interpretation was used when the KPPU developing the definition of the legal concepts. The general purpose of the law and the theories of the basis of the law were the conceptual framework in using dynamic interpretation. There are two recommendations in this article. Firstly, interpreting the laws by the judges should be based on the correct conceptual framework. Secondly, the technique of interpreting the laws would be the method of controlling the judges.

Keywords: legal interpretation, legal transplant, competition law, KPPU

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: Young Sik Kim, Tae Kwon Ha

Abstract:

High strength Fe-36Ni-base Invar alloys containing Al contents up to 0.3 weight per cent were cast into ingots and thermodynamic equilibrium during solidification has been investigated in this study. From the thermodynamic simulation using Thermo-Calc®, it has been revealed that equilibrium phases which can be formed are two kinds of MC-type precipitates, MoC, and M2C carbides. The mu phase was also expected to form by addition of aluminum. Microstructure observation revealed the coarse precipitates in the as-cast ingots, which was non-equilibrium phase and could be resolved by the successive heat treatment. With increasing Al contents up to 0.3 wt.%, tensile strength of Invar alloy increased as 1400MPa after cold rolling and thermal expansion coefficient increased significantly. Cold rolling appeared to dramatically decrease thermal expansion coefficient.

Keywords: Invar alloy, transition metals, phase equilibrium, aging behavior, microstructure, hardness

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Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

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Authors: Sie Long Kek, Wah June Leong, Kok Lay Teo

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Linear quadratic Gaussian model is a standard mathematical model for the stochastic optimal control problem. The combination of the linear quadratic estimation and the linear quadratic regulator allows the state estimation and the optimal control policy to be designed separately. This is known as the separation principle. In this paper, an efficient computational method is proposed to solve the linear quadratic Gaussian problem. In our approach, the Hamiltonian function is defined, and the necessary conditions are derived. In addition to this, the output error is defined and the least-square optimization problem is introduced. By determining the first-order necessary condition, the gradient of the sum squares of output error is established. On this point of view, the stochastic approximation approach is employed such that the optimal control policy is updated. Within a given tolerance, the iteration procedure would be stopped and the optimal solution of the linear-quadratic Gaussian problem is obtained. For illustration, an example of the linear-quadratic Gaussian problem is studied. The result shows the efficiency of the approach proposed. In conclusion, the applicability of the approach proposed for solving the linear quadratic Gaussian problem is highly demonstrated.

Keywords: iteration procedure, least squares solution, linear quadratic Gaussian, output error, stochastic approximation

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Authors: Kun Huang

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This paper investigates whether the combination of local and stochastic volatility models can be calibrated exactly to any arbitrage-free implied volatility surface of European option. The risk neutral Brownian Bridge density is applied for calibration of the leverage function of our Hybrid model. Furthermore, the tails of marginal risk neutral density are generated by Generalized Extreme Value distribution in order to capture the properties of asset returns. The local volatility is generated from the arbitrage-free implied volatility surface using stochastic volatility inspired parameterization.

Keywords: arbitrage free implied volatility, calibration, extreme value distribution, hybrid model, local volatility, risk-neutral density, stochastic volatility

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Authors: Zubier Arfan, Paul Johnson

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The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model.

Keywords: market-making, market-microsctrucure, stochastic volatility, quantitative trading

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Authors: T. G. Kassem, A. K. Adunchezor, J. P. Chollom

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This paper describes a mathematical model developed to predict the dynamics of Hepatitis B virus (HBV) infection and to evaluate the potential impact of vaccination and treatment on its dynamics. We used a compartmental model expressed by a set of differential equations based on the characteristic of HBV transmission. With these, we find the threshold quantity R0, then find the local asymptotic stability of disease free equilibrium and endemic equilibrium. Furthermore, we find the global stability of the disease free and endemic equilibrium.

Keywords: hepatitis B virus, epidemiology, vaccination, mathematical model

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Ipek Kivanc, Demet Ozgur-Unluakin

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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.

Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes

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Authors: Joao Teotonio Manzi

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Reversibility, irreversibility, equilibrium and steady-state that play a central role in the thermodynamic analysis of processes arising in the context of reactive systems are discussed in this article. Such concepts have generated substantial doubts, even among the most experienced researchers, and engineers, because from the literature, conclusive or definitive statements cannot be extracted. Concepts such as the time-reversibility of irreversible processes seem paradoxical, requiring further analysis. Equilibrium and reversibility, which appear to be of the same nature, have also been re-examined in the light of maximum entropy. The goal of this paper is to revisit and explore these concepts based on classical thermodynamics in order to have a better understanding them due to their impacts on technological advances, as a result, to generate an optimal procedure for designing, monitoring, and engineering optimization. Furthermore, an effective graphic procedure for dimensioning a Plug Flow Reactor has been provided. Thus, to meet the needs of chemical engineering from a simple conceptual analysis but with significant practical effects, a macroscopic approach is taken so as to integrate the different parts of this paper.

Keywords: reversibility, equilibrium, steady-state, thermodynamics, reactive system

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Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

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Authors: Amir Azaron

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In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: decentralized, optimal control, output, singular perturb

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Authors: A. A. Ahmadi, A. R. Pishevar, M. Nili

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As the test gas in a gun tunnel is non-isentropically compressed and heated by a light weight piston. Here, first consideration is the optimum piston weight. Although various aspects of the influence of piston weight on gun tunnel performance have been studied, it is not possible to decide from the existing literature what piston weight is required for optimum performance in various conditions. The technique whereby the piston is rapidly brought to rest at the end of the gun tunnel barrel, and the resulted peak pressure is equal in magnitude to the final equilibrium pressure, is called the equilibrium piston technique. The equilibrium piston technique was developed to estimate the equilibrium piston mass; but this technique cannot give an appropriate estimate for the optimum piston weight. In the present work, a gun tunnel with diameter of 3 in. is described and its performance is investigated numerically to obtain the effect of piston and its weight. Numerical results in the present work are in very good agreement with experimental results. Significant influence of the existence of a piston is shown by comparing the gun tunnel results with results of a conventional shock tunnel in the same dimension and same initial condition. In gun tunnel, an increase of around 250% in running time is gained relative to shock tunnel. Also, Numerical results show that equilibrium piston technique is not a good way to estimate suitable piston weight and there will be a lighter piston which can increase running time of the gun tunnel around 60%.

Keywords: gun tunnel, hypersonic flow, piston, shock tunnel

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Authors: Abeer Amayri, Akif A. Bulgak

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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

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Authors: Seok Hong Min, Tae Kwon Ha

Abstract:

High strength Fe-36Ni-base Invar alloys containing Al contents up to 0.3 weight percent were cast into ingots and thermodynamic equilibrium during solidification has been investigated in this study. From the thermodynamic simulation using Thermo-Calc®, it has been revealed that equilibrium phases which can be formed are two kinds of MC-type precipitates, MoC, and M2C carbides. The mu phase was also expected to form by addition of aluminum. Microstructure observation revealed the coarse precipitates in the as-cast ingots, which was non-equilibrium phase and could be resolved by the successive heat treatment. With increasing Al contents up to 0.3 wt.%, tensile strength of Invar alloy increased as 1400MPa after cold rolling and thermal expansion coefficient increased significantly. Cold rolling appeared to dramatically decrease thermal expansion coefficient.

Keywords: invar alloy, aluminum, phase equilibrium, thermal expansion coefficient, microstructure, tensile properties

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Authors: I .Ait El Harch, K. Outaaoui, Y. El Foutayeni

Abstract:

This study aims to deepen the understanding and optimize fishing activity in Morocco by holistically integrating biological and economic aspects. We develop a biological equilibrium model in which these competing species present their natural growth by logistic equations, taking into account density and competition between them. The integration of human intervention adds a realistic dimension to our model. A company specifically targets the three species, thus influencing population dynamics according to their fishing activities. The aim of this work is to determine the fishing effort that maximizes the company’s profit, taking into account the constraints associated with conserving ecosystem equilibrium.

Keywords: bioeconomical modeling, optimization techniques, linear complementarity problem LCP, biological equilibrium, maximizing profits

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Song Ni, Junxiang Xu

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This paper concerns quasi-periodic perturbations with parameters of 2-dimensional degenerate systems. If the equilibrium point of the unperturbed system is elliptic-type degenerate. Assume that the perturbation is real analytic quasi-periodic with diophantine frequency. Without imposing any assumption on the perturbation, we can use a path of equilibrium points to tackle with the Melnikov non-resonance condition, then by the Leray-Schauder Continuation Theorem and the Kolmogorov-Arnold-Moser technique, it is proved that the equation has a small response solution for many sufficiently small parameters.

Keywords: quasi-periodic systems, KAM-iteration, degenerate equilibrium point, response solution

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Authors: Alakija Temitope Olufunmilayo, Akinyemi, Yagba Joy

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Hepatitis is the inflammation of the liver tissue that can cause whiteness of the eyes (Jaundice), lack of appetite, vomiting, tiredness, abdominal pain, diarrhea. Hepatitis is acute if it resolves within 6 months and chronic if it last longer than 6 months. Acute hepatitis can resolve on its own, lead to chronic hepatitis or rarely result in acute liver failure. Chronic hepatitis may lead to scarring of the liver (Cirrhosis), liver failure and liver cancer. Modelling Hepatitis B may become necessary in order to reduce its spread. So, dynamic SIR model can be used. This model consists of a system of three coupled non-linear ordinary differential equation which does not have an explicit formula solution. It is an epidemiological model used to predict the dynamics of infectious disease by categorizing the population into three possible compartments. In this study, a five-compartment dynamic model of Hepatitis B disease was proposed and developed by adding control measure of sensitizing the public called awareness. All the mathematical and statistical formulation of the model, especially the general equilibrium of the model, was derived, including the nonlinear least square estimators. The initial parameters of the model were derived using nonlinear least square embedded in R code. The result study shows that the proportion of Hepatitis B patient in the study population is 1.4 per 1,000,000 populations. The estimated Hepatitis B induced death rate is 0.0108, meaning that 1.08% of the infected individuals die of the disease. The reproduction number of Hepatitis B diseases in Nigeria is 6.0, meaning that one individual can infect more than 6.0 people. The effect of sensitizing the public on the basic reproduction number is significant as the reproduction number is reduced. The study therefore recommends that programme should be designed by government and non-governmental organization to sensitize the entire Nigeria population in order to reduce cases of Hepatitis B disease among the citizens.

Keywords: hepatitis B, modelling, non-linear ordinary differential equation, sihar model, sensitization

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Authors: Bo Kampmann Walther

Abstract:

This essay provides an in-depth interpretation of the ancient Babylonian origin narrative, The Enuma Elish, through the lens of game theory. It examines the strategic interactions among the deities in the myth as if they were players in a game, focusing on understanding the dynamics of conflict, cooperation, and equilibrium within the narrative. The pivotal game theory concept known as Nash Equilibrium is given prominent consideration, but saddle points and optimal strategies will also be employed to uncover the decision-making processes of the divine figures, particularly in the cosmic battle for supremacy. This analysis demonstrates that the ancient narrative, beyond its mythological content, illustrates timeless principles of strategic behavior in the pursuit of game success.

Keywords: Enuma Elish, game theory, Nash Equilibrium, Babylonian mythology, strategic interaction

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Authors: Kannapha Amaruchkul

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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

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Authors: Ji Chan Kim, Seok Hong Min, Tae Kwon Ha

Abstract:

The effect of Yttrium addition on the microstructure and mechanical properties of Sn-Zn eutectic alloy, which has been attracting intensive focus as a Pb-free solder material, was investigated in this study. Phase equilibrium has been calculated by using FactSage® to evaluate the composition and fraction of equilibrium intermetallic compounds and construct a phase diagram. In the case of Sn-8.8 Zn eutectic alloy, the as-cast microstructure was typical lamellar. With addition of 0.25 wt. %Y, a large amount of pro-eutectic phases have been observed and various YZnx intermetallic compounds were expected to successively form during cooling. Hardness of Sn-8.8 Zn alloy was not affected by Y-addition and both alloys could be rolled by 90% at room temperature.

Keywords: lead-free solder, zn-al-sn alloy, phase equilibrium, rolling, microstructure, hardness

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Authors: A. D. Susanti, W. B. Sediawan, S. K. Wirawan, Budhijanto, Ritmaleni

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Rice bran oil contains significant amounts of oryzanol, a natural antioxidant that considered has higher antioxidant activity than vitamin E (tocopherol). Oryzanol reviewed has several health properties and interested in pharmacy, nutrition, and cosmetics. For practical usage, isolation and purification would be necessary due to the low concentration of oryzanol in crude rice bran oil (0.9-2.9%). Batch chromatography has proved as a promising process for the oryzanol recovery, but productivity was still low and scale-up processes of industrial interest have not yet been described. In order to improve productivity of batch chromatography, a continuous chromatography design namely Simulated Moving Bed (SMB) concept have been proposed. The SMB concept has interested for continuous commercial scale separation of binary system (oryzanol and rice bran oil), and rice bran oil still obtained as side product. Design of SMB chromatography for oryzanol separation requires quantification of its equilibrium. In this study, equilibrium of oryzanol separation conducted in batch adsorption using silica as the adsorbent and n-hexane/acetone (9:1) as the eluent. Three isotherm models, namely the Henry, Langmuir, and Freundlich equations, have been applied and modified for the experimental data to establish appropriate correlation for each sample. It turned out that the model quantitatively describe the equilibrium experimental data and will directed for design of SMB chromatography.

Keywords: adsorption, equilibrium, oryzanol, rice bran oil, simulated moving bed

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Authors: Gordon Newlove Asamoah

Abstract:

This study’s objective is to determine the impact of the African Continental Free Trade Area (AfCFTA) on Ghana using computable general equilibrium (CGE) modelling. The trade data for the simulation was drawn from the standard GTAP database version 10. The study estimated the Ad valorem equivalent (AVE) of Non-Tariff Measures (NTMs) for the Ghanaian sectors which were used for the analysis. Simulations were performed to remove import tariffs and export taxes for 90% of the tariff lines as well as 50% of the NTMs for all the AfCFTA participating countries. The NTMs' reduction was simulated using these two mechanisms: iceberg costs, also known as import augmenting technological change (AMS), and exporter costs (AXS). The study finds that removing the tariffs and NTMs in the AfCFTA regions has a positive impact on Ghana’s GDP, export and import volumes, terms of trade and welfare as measured by the equivalent variations. However, Ghana recorded a deficit of US$4766.69 million as a trade balance due to its high importation bills. This is not by chance, as Ghana is an importer of high-value-added goods but an exporter of basic agricultural raw materials with low export earnings. The study also finds much larger positive impacts for the AfCFTA regions for both importers and exporters when the NTMs that work as iceberg costs and export costs are reduced. It further finds that by reducing the export cost that increases the cost of intermediate inputs, trade among the AfCFTA regions (intra-AfCFTA trade) is enhanced.

Keywords: impact, AfCFTA, NTMs, Ghana, CGE

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Authors: Trevor C. Brown, David J. Miron

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Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

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Authors: Liang Liu, Xiaopeng Luo

Abstract:

In this paper, we propose an accelerated stochastic gradient method with momentum. The momentum term is the weighted average of generated gradients, and the weights decay inverse proportionally with the iteration times. Stochastic gradient descent with momentum (SGDM) uses weights that decay exponentially with the iteration times to generate the momentum term. Using exponential decay weights, variants of SGDM with inexplicable and complicated formats have been proposed to achieve better performance. However, the momentum update rules of our method are as simple as that of SGDM. We provide theoretical convergence analyses, which show both the exponential decay weights and our inverse proportional decay weights can limit the variance of the parameter moving directly to a region. Experimental results show that our method works well with many practical problems and outperforms SGDM.

Keywords: exponential decay rate weight, gradient descent, inverse proportional decay rate weight, momentum

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

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We have conducted the optimal synthesis of root-mean-squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous-time.

Keywords: mathematical expectation, filtration, anomalous noise, memory

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Authors: Koe Han Beng, Khoo Boo Cheong

Abstract:

The rising interest of stepped hull design has been led by the demand of more efficient high-speed boat. At the same time, the need of accurate prediction method for stepped planing hull is getting more important. By understanding the flow at high Froude number is the key in designing a practical step hull, the study surrounding stepped hull has been done mainly in the towing tank which is time-consuming and costly for initial design phase. Here the feasibility of predicting hydrodynamics of high-speed planing hull both with and without step using computational fluid dynamics (CFD) with the volume of fluid (VOF) methodology is studied in this work. First the flow around the prismatic body is analyzed, the force generated and its center of pressure are compared with available experimental and empirical data from the literature. The wake behind the transom on the keel line as well as the quarter beam buttock line are then compared with the available data, this is important since the afterbody flow of stepped hull is subjected from the wake of the forebody. Finally the calm water performance prediction of a conventional planing hull and its stepped version is then analyzed. Overset mesh methodology is employed in solving the dynamic equilibrium of the hull. The resistance, trim, and heave are then compared with the experimental data. The resistance is found to be predicted well and the dynamic equilibrium solved by the numerical method is deemed to be acceptable. This means that computational fluid dynamics will be very useful in further study on the complex flow around stepped hull and its potential usage in the design phase.

Keywords: planing hulls, stepped hulls, wake shape, numerical simulation, hydrodynamics

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