Search results for: parameter uncertainty

Authors: B. Sellami, M. Belloufi

Abstract:

Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new two-parameter family of conjugate gradient methods for unconstrained optimization. The two-parameter family of methods not only includes the already existing three practical nonlinear conjugate gradient methods, but also has other family of conjugate gradient methods as subfamily. The two-parameter family of methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for the two-parameter family of methods. The numerical results show that this method is efficient for the given test problems. In addition, the methods related to this family are uniformly discussed.

Keywords: unconstrained optimization, conjugate gradient method, line search, global convergence

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Authors: Vahid Tabrizi, Reza GHasemi, Ahmadreza Vali

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This paper presents robust nonlinear control law for a quadrotor UAV using fast terminal sliding mode control. Fast terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Then, in reaching phase for removing chattering and producing smooth control signal, continuous approximation idea is used. Simulation results show that the proposed algorithm is robust against parameter uncertainty and has better performance than conventional sliding mode for controlling a quadrotor UAV.

Keywords: quadrotor UAV, fast terminal sliding mode, second order sliding mode t

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Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

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After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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Authors: Sergio Haram Sarmiento, Arcady Ponosov

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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara

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In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.

Keywords: stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.

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Authors: Suparman Suparman

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A white noise in autoregressive (AR) model is often assumed to be normally distributed. In application, the white noise usually do not follows a normal distribution. This paper aims to estimate a parameter of AR model that has a exponential white noise. A Bayesian method is adopted. A prior distribution of the parameter of AR model is selected and then this prior distribution is combined with a likelihood function of data to get a posterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model is estimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC) is adopted. A result is a estimation of the parameter AR model can be simultaneously calculated.

Keywords: autoregressive (AR) model, exponential white Noise, bayesian, reversible jump Markov Chain Monte Carlo (MCMC)

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Authors: Sara Kanzi, Izzet Sakalli

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The effect of Lorentz symmetry breaking (LSB) on the Hawking radiation of Schwarzschild-like black hole found in the bumblebee gravity model (SBHBGM) is studied in the framework of quantum gravity. To this end, we consider Hawking radiation spin-0 (bosons) and spin-12particles (fermions), which go in and out through the event horizon of the SBHBGM. We use the modified Klein-Gordon and Dirac equations, which are obtained from the generalized uncertainty principle (GUP) to show how Hawking radiation is affected by the GUP and LSB. In particular, we reveal that independent of the spin of the emitted particles, GUP causes a change in the Hawking temperature of the SBHBGM. Furthermore, we compute the semi-analytic greybody factors (for both bosons and fermions) of the SBHBGM. Thus, we reveal that LSB is effective on the greybody factor of the SBHBGM such that its redundancy decreases the value of the greybody factor. Our findings are graphically depicted.

Keywords: bumblebee gravity model, Hawking radiation, generalized uncertainty principle, Lorentz symmetry breaking

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Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

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Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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Authors: H. R. Fazlollahi

Abstract:

Dark Energy origin is unknown and so describing this mysterious component in large scale structure needs to manipulate our theories in general relativity. Although in most models, dark energy arises from extra terms through modifying Einstein-Hilbert action, maybe its origin traces back to fundamental aspects of ground energy of space-time given in quantum mechanics. Hence, diluting space-time in general relativity with quantum mechanics properties leads to the Karolyhazy relation corresponding energy density of quantum fluctuations of space-time. Through generalized uncertainty principle and an eye to Karolyhazy approach in this study we extend energy density of quantum fluctuations of space-time. Also, the application of this idea is considered in late time evolution and we have shown how extra term in generalized uncertainty principle plays as a plausible interaction term role in suggested model.

Keywords: generalized uncertainty principle, karolyhazy approach, agegraphic dark energy, cosmology

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Authors: Elzbieta Babula, Juhyun Park

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Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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Authors: Arash Heydarian Pashakhanlou

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The security dilemma is one of the key concepts in International Relations (IR), and the numerous engagements with it have created a great deal of confusion regarding its essence. That is why this article seeks to dissect the security dilemma and rebuild it from its foundational core. In doing so, the present study highlights that the security dilemma requires interaction among actors that seek to protect themselves from other's capacity for harm under the condition of uncertainty to operate. In this constellation, actors are confronted with the dilemma of motives, power, and action, which they seek to resolve by acquiring information regarding their opponents. The relationship between the parties is shaped by the harm-uncertainty index (HUI) consisting of geographical distance, MAD, and joint democracy that determines the intensity of the security dilemma. These elements define the unified theory of the security dilemma (UTSD) developed here. UTSD challenges the prevailing view that the security dilemma is a unidimensional paradoxical concept, regulated by the offense-defense balance and differentiation that only occurs in anarchic settings with tragic outcomes and is equivalent to the spiral model.

Keywords: security dilemma, revisionism, status quo, anarchy, uncertainty, tragedy, spiral, deterrence

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Authors: Junyoung Kim, Shangwha Cha, Soomee Kang, Jake S. Byun

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This study shows the effect of parameter controls for livestock manure composting in waste recycling process for the development of a new design of a microorganism-oriented- composting system. Based on the preliminary studies, only the temperature control by changing mechanical mixing can reduce microorganisms’ biodegradability from 3 to 6 months to 15 days, saving the consumption of energy and manual labor. The final degree of fermentation in just 5 days of composting increased to ‘3’ comparing the compost standard level ‘4’ in Korea, others standards were all satisfied. This result shows that the controlling the optimum microorganism parameter using an ICT device connected to mixing condition can increase the effectiveness of fermentation system and reduce odor to nearly zero, and lead to upgrade the composting method than the conventional

Keywords: manure composting, odor removal, parameter control, waste recycling

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Authors: Johannes Gantner, Michael Held, Matthias Fischer

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The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Mohamed Noureldin, Jinkoo Kim

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The sensitivity of the seismic response parameters to the uncertain modeling variables of pile-founded fixed steel jacket platforms are investigated using tornado diagram, first-order second-moment, and static pushover analysis techniques. The effects of both aleatory and epistemic uncertainty on seismic response parameters have been investigated for an existing offshore platform. The sources of uncertainty considered in the present study are categorized into three different categories: the uncertainties associated with the soil-pile modeling parameters in clay soil, the platform jacket structure modeling parameters, and the uncertainties related to ground motion excitations. It has been found that the variability in parameters such as yield strength or pile bearing capacity has almost no effect on the seismic response parameters considered, whereas the global structural response is highly affected by the ground motion uncertainty. Also, some uncertainty in soil-pile property such as soil-pile friction capacity has a significant impact on the response parameters and should be carefully modeled. Based on the results, it is highlighted that which uncertain parameters should be considered carefully and which can be assumed with reasonable engineering judgment during the early structural design stage of fixed steel jacket platforms.

Keywords: fixed jacket offshore platform, pile-soil structure interaction, sensitivity analysis

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Authors: H. Niranjan, S. Sivasankaran, Zailan Siri

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This study investigates mixed convection heat transfer about a thin vertical plate in the presence of magnetohydrodynamic (MHD) and heat transfer effects in the porous medium. The fluid is assumed to be steady, laminar, incompressible and in two-dimensional flow. The nonlinear coupled parabolic partial differential equations governing the flow are transformed into the non-similar boundary layer equations, which are then solved numerically using the shooting method. The effects of the conjugate heat transfer parameter, the porous medium parameter, the permeability parameter, the mixed convection parameter, the magnetic parameter, and the thermal radiation on the velocity and temperature profiles as well as on the local skin friction and local heat transfer are presented and analyzed. The validity of the methodology and analysis is checked by comparing the results obtained for some specific cases with those available in the literature. The various parameters on local skin friction, heat and mass transfer rates are presented in tabular form.

Keywords: MHD, porous medium, soret/dufour, stagnation-point

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Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

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Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: Autcha Araveeporn

Abstract:

This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov chain Monte Carlo method, maximum likelihood method, normal distribution

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Authors: Abdolsalam Ghaderi

Abstract:

In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: location-routing problem, robust optimization, stochastic programming, variable neighborhood search

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Authors: Seyyed Feisal Asbaghian Namin, Reza Pilafkan, Mahmood Kaffash Irzarahimi

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TThis paper considers vibration of single-layered graphene sheets using molecular dynamics (MD) and nonlocal elasticity theory. Based on the MD simulations, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), an open source software, is used to obtain fundamental frequencies. On the other hand, governing equations are derived using nonlocal elasticity and first order shear deformation theory (FSDT) and solved using generalized differential quadrature method (GDQ). The small-scale effect is applied in governing equations of motion by nonlocal parameter. The effect of different side lengths, boundary conditions and nonlocal parameter are inspected for aforementioned methods. Results are obtained from MD simulations is compared with those of the nonlocal elasticity theory to calculate appropriate values for the nonlocal parameter. The nonlocal parameter value is suggested for graphene sheets with various boundary conditions. Furthermore, it is shown that the nonlocal elasticity approach using classical plate theory (CLPT) assumptions overestimates the natural frequencies.

Keywords: graphene sheets, molecular dynamics simulations, fundamental frequencies, nonlocal elasticity theory, nonlocal parameter

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Authors: Pavel Borodkin, Nikolay Khrennikov, Azamat Gazetdinov

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The problem of ensuring of VVER type reactor equipment integrity is now most actual in connection with justification of safety of the NPP Units and extension of their service life to 60 years and more. First of all, it concerns old units with VVER-440 and VVER-1000. The justification of the VVER equipment integrity depends on the reliability of estimation of the degree of the equipment damage. One of the mandatory requirements, providing the reliability of such estimation, and also evaluation of VVER equipment lifetime, is the monitoring of equipment radiation loading parameters. In this connection, there is a problem of justification of such normative parameters, used for an estimation of the pressure vessel metal embrittlement, as the fluence and fluence rate (FR) of fast neutrons above 0.5 MeV. From the point of view of regulatory practice, a comparison of displacement per atom (DPA) and fast neutron fluence (FNF) above 0.5 MeV has a practical concern. In accordance with the Russian regulatory rules, neutron fluence F(E > 0.5 MeV) is a radiation exposure parameter used in steel embrittlement prediction under neutron irradiation. However, the DPA parameter is a more physically legitimate quantity of neutron damage of Fe based materials. If DPA distribution in reactor structures is more conservative as neutron fluence, this case should attract the attention of the regulatory authority. The purpose of this work was to show what radiation load parameters (fluence, DPA) on all VVER equipment should be under control, and give the reasonable estimations of such parameters in the volume of all equipment. The second task is to give the conservative estimation of each parameter including its uncertainty. Results of recently received investigations allow to test the conservatism of calculational predictions, and, as it has been shown in the paper, combination of ex-vessel measured data with calculated ones allows to assess unpredicted uncertainties which are results of specific unique features of individual equipment for VVER reactor. Some results of calculational-experimental investigations are presented in this paper.

Keywords: equipment integrity, fluence, displacement per atom, nuclear power plant, neutron activation measurements, neutron transport calculations

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Authors: Tomas Menard

Abstract:

The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: A. M. Abd-Elfattah, M. H. Abu-Moussa

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In this paper, the estimation of stress-strength parameter R = P(Y < X) is considered when X; Y the strength and stress respectively are two independent random variables of Burr Type XII distribution. The samples taken for X and Y are progressively censoring of type II. The maximum likelihood estimator (MLE) of R is obtained when the common parameter is unknown. But when the common parameter is known the MLE, uniformly minimum variance unbiased estimator (UMVUE) and the Bayes estimator of R = P(Y < X) are obtained. The exact condence interval of R based on MLE is obtained. The performance of the proposed estimators is compared using the computer simulation.

Keywords: Burr Type XII distribution, progressive type-II censoring, stress-strength model, unbiased estimator, maximum-likelihood estimator, uniformly minimum variance unbiased estimator, confidence intervals, Bayes estimator

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Authors: Saied Farham-Nia, Alireza Ghaffari-Hadigheh

Abstract:

Game theory is a mathematical tool to study the behaviors of a rational and strategic decision-makers, that analyze existing equilibrium in interest conflict situation and provides an appropriate mechanisms for cooperation between two or more player. Game theory is applicable for any strategic and interest conflict situation in politics, management and economics, sociology and etc. Real worlds’ decisions are usually made in the state of indeterminacy and the players often are lack of the information about the other players’ payoffs or even his own, which leads to the games in uncertain environments. When historical data for decision parameters distribution estimation is unavailable, we may have no choice but to use expertise belief degree, which represents the strength with that we believe the event will happen. To deal with belief degrees, we have use uncertainty theory which is introduced and developed by Liu based on normality, duality, subadditivity and product axioms to modeling personal belief degree. As we know, the personal belief degree heavily depends on the personal knowledge concerning the event and when personal knowledge changes, cause changes in the belief degree too. Uncertainty theory not only theoretically is self-consistent but also is the best among other theories for modeling belief degree on practical problem. In this attempt, we primarily reintroduced Expected Utility Function in uncertainty environment according to uncertainty theory axioms to extract payoffs. Then, we employed Nash Equilibrium to investigate the solutions. For more practical issues, Stackelberg leader-follower Game and Bertrand Game, as a benchmark models are discussed. Compared to existing articles in the similar topics, the game models and solution concepts introduced in this article can be a framework for problems in an uncertain competitive situation based on experienced expert’s belief degree.

Keywords: game theory, uncertainty theory, belief degree, uncertain expected value, Nash equilibrium

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Authors: H. Ashrafi, S. Ebrahimi, H. Kamalzadeh

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With the development of business competition, it is important for healthcare providers to improve their service qualities. In order to improve service quality of a clinic, four important dimensions are defined: tangibles, responsiveness, empathy, and reliability. Moreover, there are several service stages in hospitals such as financial screening and examination. One of the most challenging limitations for improving service quality is budget which impressively affects the service quality. In this paper, we present an approach to address budget uncertainty and provide guidelines for service resource allocation. In this paper, a service quality improvement approach is proposed which can be adopted to multistage service processes to improve service quality, while controlling the costs. A multi-objective function based on the importance of each area and dimension is defined to link operational variables to service quality dimensions. The results demonstrate that our approach is not ultra-conservative and it shows the actual condition very well. Moreover, it is shown that different strategies can affect the number of employees in different stages.

Keywords: allocation, budget uncertainty, healthcare resource, service quality assessment, robust optimization

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Authors: Mouhoubi Nedjima, Sassi Boudemagh Souad

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In this paper, we will try to demonstrate the importance of the project approach in the urban to deal with uncertainty, the importance of the involvement of all stakeholders in the urban project process and that the absence of an actor can lead to project failure but also the importance of the urban project management. These points are handled through the following questions: Does the urban adhere to the theory of complexity? Does the project approach bring hope and solution to make urban planning "sustainable"? How converging visions of actors for the same project? Is the management of urban project the solution to support the urban project approach?

Keywords: strategic planning, project, urban project stakeholders, management

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Authors: T. Yuri, M. Zagloel, Inaki M. Hakim, Tegu Bintang Nugraha

Abstract:

In an era of customer centricity, automotive parts manufacturer in Indonesia must be able to keep up with the uncertainty and fluctuation of consumer demand. Flexible Manufacturing System (FMS) is a strategy to react to predicted and unpredicted changes of demand in automotive industry. This research is about flexible mixed model assembly line design through Value Stream Mapping (VSM) and Line Balancing in mixed model assembly line prior to simulation. It uses value stream mapping to identify and reduce waste while finding the best position to add or reduce manpower. Line balancing is conducted to minimize or maximize production rate while increasing assembly line productivity and efficiency. Results of this research is a recommendation of standard work combination for specifics demand scenario which can enhance assembly line efficiency and productivity.

Keywords: automotive industry, demand uncertainty, flexible assembly system, line balancing, value stream mapping

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Authors: L. Yettou

Abstract:

In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models , level density, level density a-parameter., Empire code, Talys code.

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Authors: Min Fang, Jiaxi Yang

Abstract:

Monetary policy could be less effective at stimulating investment during periods of elevated volatility than during normal times. In this paper, we argue that elevated volatility leads to a decrease in extensive margin investment incentive so that nominal stimulus generates less aggregate investment. To do this, we first empirically document that high volatility weakens firms’ investment responses to monetary stimulus. Such effects depend on the lumpiness nature of the firm-level investment. The findings are that the channel exists for all of the physical investment, innovation investment, and organization investment.

Keywords: investment, irreversibility, volatility, uncertainty, firm heterogeneity, monetary policy

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