Search results for: optimal volume

Authors: Taejung Lho, Jonghwan Lee

Abstract:

Most of the photovoltaic (PV) module manufacturers have recently interested in reducing the manufacturing cost. One of available solution is the use of the thin photovoltaic cell because of reducing of raw material cost. Thin PV cells, however, are damaged large deformation which causes possible microcracks inside PV cell, leading to failure problem. In this paper, deformation characteristics by heat conduction in soldering process of PV cells are analyzed through ANSYS software tool. They have been tested for different PV cell thickness and soldering temperature profile. Accordingly optimal soldering process to minimize the deformation of PV cell has been suggested.

Keywords: photovoltaic (PV) cell, infrared(IR) lamp soldering, optimal soldering temperature profile, deformation, temperature distribution, 3D scanner, ANSYS

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Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer

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Authors: M. Wendeker, K. Siadkowska, P. Magryta, Z. Czyz, K. Skiba

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In the paper environmental impact analysis the optimal Diesel engine for a light helicopter was performed. The paper consist an answer to the question of what the optimal Diesel engine for a light helicopter is, taking into consideration its expected performance and design capacity. The use of turbocharged engine with self-ignition and an electronic control system can substantially reduce the negative impact on the environment by decreasing toxic substance emission, fuel consumption and therefore carbon dioxide emission. In order to establish the environmental benefits of the diesel engine technologies, mathematical models were created, providing additional insight on the environmental impact and performance of a classic turboshaft and an advanced diesel engine light helicopter, incorporating technology developments.

Keywords: diesel engine, helicopter, simulation, environmental impact

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Authors: Mohan L. Jayatiake, Judd Storrs, Jing-Huei Lee

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The optimal MRI resolution relies on a homogeneous magnetic field. However, local susceptibility variations can lead to field inhomogeneities that cause artifacts such as image distortion and signal loss. The effects of local susceptibility variation notoriously increase with magnetic field strength. Active shimming improves homogeneity by applying corrective fields generated from shim coils, but requires calculation of optimal current for each shim coil. FASTMAP (fast automatic shimming technique by mapping along projections) is an effective technique for finding optimal currents works well at high-field, but is restricted to shimming spherical regions of interest. The 3D gradient-echo pulse sequence was modified to reduce sensitivity to eddy currents and used to obtain susceptibility field maps at 4T. Measured fields were projected onto first-and second-order spherical harmonic functions corresponding to shim hardware. A spherical phantom was used to calibrate the shim currents. Susceptibility maps of a volunteer’s brain with and without FASTMAP shimming were obtained. Simulations indicate that optimal shim currents derived from the field map may provide better overall shimming of the human brain.

Keywords: shimming, high-field, active, passive

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Authors: Gaspar J. Machado, Stéphane Clain, Raphael Loubère

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The goal of the present work is to numerically study steady-state nonlinear hyperbolic equations in the context of the finite volume framework. We will consider the unidimensional Burgers' equation as the reference case for the scalar situation and the unidimensional Euler equations for the vectorial situation. We consider two approaches to solve the nonlinear equations: a time marching algorithm and a direct steady-state approach. We first develop the necessary and sufficient conditions to obtain the existence and unicity of the solution. We treat regular examples and solutions with a steady shock and to provide very-high-order finite volume approximations we implement a method based on the MOOD technology (Multi-dimensional Optimal Order Detection). The main ingredient consists in using an 'a posteriori' limiting strategy to eliminate non physical oscillations deriving from the Gibbs phenomenon while keeping a high accuracy for the smooth part.

Keywords: Euler equations, finite volume, MOOD, steady-state

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Authors: Saba Fahham, Supak Ngamsom, Suchaya Damrongsri

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Objective: The objective is to determine the optimal threshold of Romexis software for the airway volume and minimum cross-section area (MCA) analysis using Image J as a gold standard. Materials and Methods: A total of ten cone-beam computed tomography (CBCT) images were collected. The airway volume and MCA of each patient were analyzed using the automatic airway segmentation function in the CBCT DICOM viewer (Romexis). Airway volume and MCA measurements were conducted on each CBCT sagittal view with fifteen different threshold values from the Romexis software, Ranging from 300 to 1000. Duplicate DICOM files, in axial view, were imported into Image J for concurrent airway volume and MCA analysis as the gold standard. The airway volume and MCA measured from Romexis and Image J were compared using a t-test with Bonferroni correction, and statistical significance was set at p<0.003. Results: Concerning airway volume, thresholds of 600 to 850 as well as 1000, exhibited results that were not significantly distinct from those obtained through Image J. Regarding MCA, employing thresholds from 400 to 850 within Romexis Viewer showed no variance from Image J. Notably, within the threshold range of 600 to 850, there were no statistically significant differences observed in both airway volume and MCA analyses, in comparison to Image J. Conclusion: This study demonstrated that the utilization of Planmeca Romexis Viewer 6.4.3.3 within threshold range of 600 to 850 yields airway volume and MCA measurements that exhibit no statistically significant variance in comparison to measurements obtained through Image J. This outcome holds implications for diagnosing upper airway obstructions and post-orthodontic surgical monitoring.

Keywords: airway analysis, airway segmentation, cone beam computed tomography, threshold

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Authors: Imen Dhaou

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This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets.

Keywords: CVaR, Dow Jones Islamic index, GJR-GARCH-EVT-pair copula, portfolio optimization

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Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

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Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

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The Markov Decision Process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, dynamic programming, Monte Carlo simulation, periodic replacement, Weibull distribution

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Authors: El Hassene Osmani, Mounir Haddou, Naceurdine Bensalem

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In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach.

Keywords: complementarity problem, IPOPT, Lagrange multipliers, mathematical programming, optimal control, smoothing methods, variationally inequalities

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Authors: Leila Jafari, Viliam Makis

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In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand

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Authors: Piyakajornkul T., Noppiboon S., Hochareon L., Kitsubun P.

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Nowadays, DNA vaccines become an interesting subject in the third vaccine generation. The platform of DNA vaccines production has been developed and its downstream process becomes challenging due to the quality of the products in terms of purity and percentage of supercoiled DNA. To overcome these challenges, tangential flow filtration (TFF), which is involved in the purification process, could be used since it provides effective separation of impurity prior to performing further purification steps. However, operating conditions of TFF is varied based on several factors such as sizes of target particle and impurities, a concentration of solution as well as a concentration polarization on the membrane surface. In this study, pVAX1/lacZ was used as a model of TFF optimization in order to prevent a concentration polarization that can lead to the membrane fouling and also minimize a diafiltration volume while maintaining the maximum permeate flux resulting in proper operating times and buffer volume. By using trans membrane pressure (TMP) excursion method, feed flow rates and TMP were varied. The results showed a correlation of permeate flux with TMP where the maximum volume concentration factor reached 2.5 times of the initial volume when feed flow rate and TMP were 7 liters/m²/min and 1 bar, respectively. It was optimal operating conditions before TFF system undergone pressure independent regime. In addition, the diafiltration volume was 14 times of the concentrated volume prior to performing a further anion chromatography process.

Keywords: concentration polarization, DNA vaccines, optimization, permeate flux, pressure dependent, tangential flow filtration (TFF), trans membrane pressure (TMP)

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Authors: Ahmed Ouammi

Abstract:

This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance.

Keywords: decision support systems, electric power grid, optimization, wind energy

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Authors: Christian Rathgeber, Franz Winkler, Xiaoyu Kang, Steffen Müller

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In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results.

Keywords: trajectory planning, direct method, indirect method, highly automated driving

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Authors: Mohamed Anouar Razgallah

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This paper examines in the context of a one-period model the impact of background risk on the optimal secondary prevention. We conduct our study based on various configurations of the background risk. We intend to show that in most cases the level of secondary prevention effort varied after the introduction of background risk, however, in very few cases this level remains constant.

Keywords: secondary prevention, primary prevention, background risk, ecomomics

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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: Yuanhao Gao, Pin Lin, Kees Weijer

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In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

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Authors: Trung Le Thanh

Abstract:

Bored piles are always the optimal solution for high-rise building foundations. They have many advantages, such as large diameter, large pile length and construction in all different geological conditions. However, due to construction characteristics, the load-bearing capacity of bored piles is not optimal because wall friction is reduced due to poor contact between the pile and the surrounding soil. Therefore, grouting technology along the pile body helps improve the load-bearing capacity of bored piles significantly through increasing the skin resistance of the pile and surrounding soil. The improvement of pile skin resistance depends on the parameters of grouting technology, especially grouting volume, mortar viscosity, mortar strength,... and different geological conditions. Studies show that the technology of grouting piles on sandy soil is more effective than on clay. This article presents an experimental model to determine the load-bearing capacity of bored piles with a diameter of 400 mm and a length of 3 m on sand with different slurry volume in Tan Uyen city, Binh Duong province. On that basis, analyze the correlation between the increase in load-bearing capacity of bored piles without and with shaft grouting pile. Research results show that the wall resistance of shaft grouted piles increases 2-3 times compared to piles without grouting, and the pile's load-bearing capacity increases significantly. The article's research provides scientific value for consulting work on the design of bored piles when grouted along the pile body.

Keywords: bored pile, shaft grouting, bearing capacity, pile shaft resistance

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Authors: M. F. F. Ab Rashid, A. N. Mohd Rose, N. M. Z. Nik Mohamed, W. S. Wan Harun, S. A. Che Ghani

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Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm.

Keywords: traveling salesman problem, sequencing, genetic algorithm, precedence constraint

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Authors: D. De-León-Escobedo, D. J. Delgado-Hernández, S. Pérez

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A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF<1. As the main hazard is the rainfall on the area, statistics of rainfall intensity and duration are considered and modeled with an exponential distribution. The expected life-cycle cost is assessed by considering a monetary value on the slope failure consequences. Alternative mitigation measures are simulated, and the formulation is used to get the measures driving to the optimal one (minimum life-cycle costs). For the example, the optimal mitigation measure is the reduction on the slope inclination angle.

Keywords: expected life-cycle cost, failure probability, slopes failure, storms

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Authors: Kevin Spencer G. Anglim, Zhenyu Zhang, Qingbin Gao

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Reusable launch vehicles (RLVs) present a more environmentally-friendly approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimum-fuel optimal trajectories using principles from optimal control theory and particle swarm optimization (PSO). This problem is formulated as a minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for studies on the Moon or on Mars. Rather than optimizing the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. The PSO method is verified in a one-dimensional comparison study, and it is then applied to the two-dimensional cases, the results of which are illustrated.

Keywords: minimum-fuel optimal trajectory, particle swarm optimization, reusable rocket, SpaceX

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

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Authors: Wen Liang Chang

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In this study, the optimal replacement time and number of preventive maintenance (PM) actions were investigated for a second-hand device. Suppose that a user intends to use a second-hand device for manufacturing products, and that the device is replaced with a new one. Any device failure is rectified through minimal repair, thereby incurring a fixed repair cost to the user. If the new device fails within the FRW period, minimal repair is performed at no cost to the user. After the FRW expires, a failed device is repaired and the cost of repair is incurred by the user. In this study, two profit models were developed, and the optimal replacement time and number of PM actions were determined to maximize profits. Finally, the influence of the optimal replacement time and number of PM actions were elaborated on, using numerical examples.

Keywords: second-hand device, preventive maintenance, replacement time, device failure

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Authors: Virgil Miranda, Gissele Mosqueda, Pablo Delgado, Yimesker Yihun

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Muscular fatigue affects the muscle activation that is needed for producing the desired clinical outcome. Integrating optimal muscle relaxation periods into a variety of health care rehabilitation protocols is important to maximize the efficiency of the therapy. In this study, four muscle relaxation periods (30, 60, 90, and 120 seconds) and their effectiveness in producing consistent muscle activation of the muscle biceps brachii between sets of elbow flexion and extension task was investigated among a sample of 10 subjects with no disabilities. The same resting periods were then utilized in a controlled exoskeleton-based exercise for a sample size of 5 subjects and have shown similar results. On average, the muscle activity of the biceps brachii decreased by 0.3% when rested for 30 seconds, and it increased by 1.25%, 0.76%, and 0.82% when using muscle relaxation periods of 60, 90, and 120 seconds, respectively. The preliminary results suggest that a muscle relaxation period of about 60 seconds is needed for optimal continuous muscle activation within rehabilitation regimens. Robot-based rehabilitation is good to produce repetitive tasks with the right intensity, and knowing the optimal resting period will make the automation more effective.

Keywords: rest intervals, muscle biceps brachii, robot rehabilitation, muscle fatigue

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Authors: Ghazaleh Monazami Tehrani, Zhamak Monazami Tehrani, Raziyeh Hadavand

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Optimal site selection for temporary housing is one of the most important issues in crisis management. In this research, district six of Tehran city with high frequency and geographical distribution of earthquakes has been selected as a case study for positioning temporary housing after a probable earthquake. For achieving this goal this study tries to identify and evaluate distribution of location according to some standards such as compatible and incompatible urban land uses with utility of GIS and AHP. The results of this study show the most susceptible parts of this region in the center. According to the maps, north eastern part of Kordestan, Shaheed Gomnam intersection possesses the highest pixels value in terms of areal extent, therefore these places are recommended as an optimum site location for construction of emergency evacuation base.

Keywords: optimal site selection, temporary housing , crisis management, AHP, GIS

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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

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Authors: Muhammad Danish Khan, Imran Naeem, Mudassar Imran

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In this article, we study time-space Fractional Advection-Dispersion (FADE) equation and time-space Fractional Whitham-Broer-Kaup (FWBK) equation that have a significant role in hydrology. We introduce suitable transformations to convert fractional order derivatives to integer order derivatives and as a result these equations transform into Partial Differential Equations (PDEs). Then the Lie symmetries and corresponding optimal systems of the resulting PDEs are derived. The symmetry reductions and exact independent solutions based on optimal system are investigated which constitute the exact solutions of original fractional differential equations.

Keywords: modified Riemann-Liouville fractional derivative, lie-symmetries, optimal system, invariant solutions

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Authors: Wafa' Alsharafat, Suhila Farhan Abu-Owida

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Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimization methods used to solve Travel salesman Problem (TSP). The feasibility of GA in finding a TSP solution is dependent on GA operators; encoding method, population size, termination criteria, in general. In specific, crossover and its probability play a significant role in finding possible solutions for Symmetric TSP (STSP). In addition, the crossover should be determined and enhanced in term reaching optimal or at least near optimal. In this paper, we spot the light on using a modified crossover method called modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of a parameter value in solving the TSP, a set comparative analysis conducted on different crossover methods values.

Keywords: genetic algorithm, crossover, mutation, TSP

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Authors: Slim Amami

Abstract:

A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

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Authors: Engy Adel Mohamed, Yasser Gamal-Eldin Hegazy

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This paper presents a firefly based algorithm for optimal sizing and allocation of distributed generators for profit maximization. Distributed generators in the proposed algorithm are of photovoltaic and combined heat and power technologies. Combined heat and power distributed generators are modeled as voltage controlled nodes while photovoltaic distributed generators are modeled as constant power nodes. The proposed algorithm is implemented in MATLAB environment and tested the unbalanced IEEE 37-node feeder. The results show the effectiveness of the proposed algorithm in optimal selection of distributed generators size and site in order to maximize the total system profit.

Keywords: distributed generators, firefly algorithm, IEEE 37-node feeder, profit maximization

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