864 resultados para Production Inventory Model with Switching Time
Resumo:
The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.
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A newly developed and validated constitutive model that accounts for primary compression and time-dependent mechanical creep and biodegradation is used for parametric study to investigate the effects of model parameters on the predicted settlement of municipal solid waste (MSW) with time. The model enables the prediction of stress strain response and yield surfaces for three components of settlement: primary compression, mechanical creep, and biodegradation. The MSW parameters investigated include compression index, coefficient of earth pressure at-rest, overconsolidation ratio, and biodegradation parameters of MSW. A comparison of the predicted settlements for typical MSW landfill conditions showed significant differences in time-settlement response depending on the selected model input parameters. The effect of lift thickness of MSW on predicted settlement is also investigated. Overall, the study shows that the variation in the model parameters can lead to significantly different results; therefore, the model parameter values should be carefully selected to predict landfill settlements accurately. It is shown that the proposed model captures the time settlement response which is in general agreement with the results obtained from the other two reported models having similar features. (C) 2011 Elsevier Ltd. All rights reserved.
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A fluctuating-force model is developed for representing the effect of the turbulent fluid velocity fluctuations on the particle phase in a turbulent gas–solid suspension in the limit of high Stokes number, where the particle relaxation time is large compared with the correlation time for the fluid velocity fluctuations. In the model, a fluctuating force is incorporated in the equation of motion for the particles, and the force distribution is assumed to be an anisotropic Gaussian white noise. It is shown that this is equivalent to incorporating a diffusion term in the Boltzmann equation for the particle velocity distribution functions. The variance of the force distribution, or equivalently the diffusion coefficient in the Boltzmann equation, is related to the time correlation functions for the fluid velocity fluctuations. The fluctuating-force model is applied to the specific case of a Couette flow of a turbulent particle–gas suspension, for which both the fluid and particle velocity distributions were evaluated using direct numerical simulations by Goswami & Kumaran (2010). It is found that the fluctuating-force simulation is able to quantitatively predict the concentration, mean velocity profiles and the mean square velocities, both at relatively low volume fractions, where the viscous relaxation time is small compared with the time between collisions, and at higher volume fractions, where the time between collisions is small compared with the viscous relaxation time. The simulations are also able to predict the velocity distributions in the centre of the Couette, even in cases in which the velocity distribution is very different from a Gaussian distribution.
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We address the problem of local-polynomial modeling of smooth time-varying signals with unknown functional form, in the presence of additive noise. The problem formulation is in the time domain and the polynomial coefficients are estimated in the pointwise minimum mean square error (PMMSE) sense. The choice of the window length for local modeling introduces a bias-variance tradeoff, which we solve optimally by using the intersection-of-confidence-intervals (ICI) technique. The combination of the local polynomial model and the ICI technique gives rise to an adaptive signal model equipped with a time-varying PMMSE-optimal window length whose performance is superior to that obtained by using a fixed window length. We also evaluate the sensitivity of the ICI technique with respect to the confidence interval width. Simulation results on electrocardiogram (ECG) signals show that at 0dB signal-to-noise ratio (SNR), one can achieve about 12dB improvement in SNR. Monte-Carlo performance analysis shows that the performance is comparable to the basic wavelet techniques. For 0 dB SNR, the adaptive window technique yields about 2-3dB higher SNR than wavelet regression techniques and for SNRs greater than 12dB, the wavelet techniques yield about 2dB higher SNR.
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Estimation of creep and shrinkage are critical in order to compute loss of prestress with time in order to compute leak tightness and assess safety margins available in containment structures of nuclear power plants. Short-term creep and shrinkage experiments have been conducted using in-house test facilities developed specifically for the present research program on 35 and 45 MPa normal concrete and 25 MPa heavy density concrete. The extensive experimental program for creep, has cylinders subject to sustained levels of load typically for several days duration (till negligible strain increase with time is observed in the creep specimen), to provide the total creep strain versus time curves for the two normal density concrete grades and one heavy density concrete grade at different load levels, different ages at loading, and at different relative humidity’s. Shrinkage studies on prism specimen for concrete of the same mix grades are also being studied. In the first instance, creep and shrinkage prediction models reported in the literature has been used to predict the creep and shrinkage levels in subsequent experimental data with acceptable accuracy. While macro-scale short experiments and analytical model development to estimate time dependent deformation under sustained loads over long term, accounting for the composite rheology through the influence of parameters such as the characteristic strength, age of concrete at loading, relative humidity, temperature, mix proportion (cement: fine aggregate: coarse aggregate: water) and volume to surface ratio and the associated uncertainties in these variables form one part of the study, it is widely believed that strength, early age rheology, creep and shrinkage are affected by the material properties at the nano-scale that are not well established. In order to understand and improve cement and concrete properties, investigation of the nanostructure of the composite and how it relates to the local mechanical properties is being undertaken. While results of creep and shrinkage obtained at macro-scale and their predictions through rheological modeling are satisfactory, the nano and micro indenting experimental and analytical studies are presently underway. Computational mechanics based models for creep and shrinkage in concrete must necessarily account for numerous parameters that impact their short and long term response. A Kelvin type model with several elements representing the influence of various factors that impact the behaviour is under development. The immediate short term deformation (elastic response), effects of relative humidity and temperature, volume to surface ratio, water cement ratio and aggregate cement ratio, load levels and age of concrete at loading are parameters accounted for in this model. Inputs to this model, such as the pore structure and mechanical properties at micro/nano scale have been taken from scanning electron microscopy and micro/nano-indenting of the sample specimen.
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Various logical formalisms with the freeze quantifier have been recently considered to model computer systems even though this is a powerful mechanism that often leads to undecidability. In this paper, we study a linear-time temporal logic with past-time operators such that the freeze operator is only used to express that some value from an infinite set is repeated in the future or in the past. Such a restriction has been inspired by a recent work on spatio-temporal logics. We show decidability of finitary and infinitary satisfiability by reduction into the verification of temporal properties in Petri nets. This is a surprising result since the logic is closed under negation, contains future-time and past-time temporal operators and can express the nonce property and its negation. These ingredients are known to lead to undecidability with a more liberal use of the freeze quantifier.
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The synthesis of dsRNA is analyzed using a pathway model with amplifications caused by the aberrant RNAs. The transgene influx rate is assumed time-decaying considering the fact that the number of transgenes can not be infinite. The dynamics of the transgene induced RNA silencing is investigated using a system of coupled nonautonomous ordinary nonlinear differential equations which describe the model phenomenologically. The silencing phenomena are detected after a period of transcription. Important contributions of certain parameters are discussed with several numerical examples.
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Antiferroelectric materials (example: lead zirconate and modified lead zirconate stannate), in which a field-induced ferroelectric phase transition is feasible due to a small free energy difference between the ferroelectric and the antiferroelectric phases, are proven to be very good candidates for applications involving actuation and high charge storage devices. The property of reverse switching from the field-induced ferroelectric to antiferroelectric phases is studied as a function of temperature, applied electric field, and sample thickness in antiferroelectric lead zirconate thin films deposited by pulsed excimer laser ablation. The maximum released charge density was 22 μC/cm2 from a stored charge density of 36 μC/cm2 in a 0.55 μ thick lead zirconate thin film. This indicated that more than 60% of the stored charge could be released in less than 7 ns at room temperature for a field of 200 kV/cm. The content of net released charge was found to increase with increasing field strength, whereas with increasing temperature the released charge was found to decrease. Thickness-dependent studies on lead zirconate thin films showed that size effects relating to extrinsic and intrinsic pinning mechanisms controlled the released and induced charges through the intrinsic switching time. These results proved that antiferroelectric PZ thin films could be utilized in high-speed charge decoupling capacitors in microelectronics applications.
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To find the approximate stability limit on the forward gain in control systems with small time delay, this note suggests approximating the exponential in the characteristic equation by the first few terms of its series and using the Routh–Hurwitz criterion. This approximation avoids all the time-consuming graphical work and gives a somewhat pessimistic maximum bound for the gain constant.
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The time delay to the firing of a triggered vacuum gap (t.v.g.) containing barium titanate in the trigger gap is investigated as a function of the main gap voltage, main gap length, trigger pulse duration, trigger current and trigger voltage. The time delay decreases steadily with increasing trigger current and trigger voltage until it reaches saturation. The effect of varying the main gap length and voltage on the time delay is not strong. Before `conditioning�¿ the t.v.g. two groups of time delays, long (>100�¿s) and short (<10�¿s), are simultaneously observed when a large number of trials are conducted. After conditioning, only the group of short time delays are present. This is attributed to the marked reduction of the resistance of the trigger gap across the surface of the solid dielectric resulting directly from the conditioning effect.
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This paper is concerned with the optimal flow control of an ATM switching element in a broadband-integrated services digital network. We model the switching element as a stochastic fluid flow system with a finite buffer, a constant output rate server, and a Gaussian process to characterize the input, which is a heterogeneous set of traffic sources. The fluid level should be maintained between two levels namely b1 and b2 with b1
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A terrestrial biosphere model with dynamic vegetation capability, Integrated Biosphere Simulator (IBIS2), coupled to the NCAR Community Atmosphere Model (CAM2) is used to investigate the multiple climate-forest equilibrium states of the climate system. A 1000-year control simulation and another 1000-year land cover change simulation that consisted of global deforestation for 100 years followed by re-growth of forests for the subsequent 900 years were performed. After several centuries of interactive climate-vegetation dynamics, the land cover change simulation converged to essentially the same climate state as the control simulation. However, the climate system takes about a millennium to reach the control forest state. In the absence of deep ocean feedbacks in our model, the millennial time scale for converging to the original climate state is dictated by long time scales of the vegetation dynamics in the northern high latitudes. Our idealized modeling study suggests that the equilibrium state reached after complete global deforestation followed by re-growth of forests is unlikely to be distinguishable from the control climate. The real world, however, could have multiple climate-forest states since our modeling study is unlikely to have represented all the essential ecological processes (e. g. altered fire regimes, seed sources and seedling establishment dynamics) for the reestablishment of major biomes.
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Motivated by experiments on Josephson junction arrays, and cold atoms in an optical lattice in a synthetic magnetic field, we study the ``fully frustrated'' Bose-Hubbard model with half a magnetic flux quantum per plaquette. We obtain the phase diagram of this model on a two-leg ladder at integer filling via the density matrix renormalization group approach, complemented by Monte Carlo simulations on an effective classical XY model. The ground state at intermediate correlations is consistently shown to be a chiral Mott insulator (CMI) with a gap to all excitations and staggered loop currents which spontaneously break time-reversal symmetry. We characterize the CMI state as a vortex supersolid or an indirect exciton condensate, and discuss various experimental implications.
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Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying fading. By explicitly accounting for practical constraints imposed by the next-generation wireless standards such as training, packetization and antenna switching time, we propose a single receive AS method for time-varying fading channels. The method exploits the low training overhead and accuracy possible from the use of discrete prolate spheroidal (DPS) sequences based reduced rank subspace projection techniques. It only requires knowledge of the Doppler bandwidth, and does not require detailed correlation knowledge. Closed-form expressions for the channel prediction and estimation error as well as symbol error probability (SEP) of M-ary phase-shift keying (MPSK) for symbol-by-symbol receive AS are also derived. It is shown that the proposed AS scheme, after accounting for the practical limitations mentioned above, outperforms the ideal conventional single-input single-output (SISO) system with perfect CSI and no AS at the receiver and AS with conventional estimation based on complex exponential basis functions.
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We interpret the recent discovery of a 125 GeV Higgs-like state in the context of a two-Higgs-doublet model with a heavy fourth sequential generation of fermions, in which one Higgs doublet couples only to the fourth-generation fermions, while the second doublet couples to the lighter fermions of the first three families. This model is designed to accommodate the apparent heaviness of the fourth-generation fermions and to effectively address the low-energy phenomenology of a dynamical electroweak-symmetry-breaking scenario. The physical Higgs states of the model are, therefore, viewed as composites primarily of the fourth-generation fermions. We find that the lightest Higgs, h, is a good candidate for the recently discovered 125 GeV spin-zero particle, when tan beta similar to O(1), for typical fourth-generation fermion masses of M-4G = 400-600 GeV, and with a large t-t' mixing in the right-handed quark sector. This, in turn, leads to BR(t' -> th) similar to O(1), which drastically changes the t' decay pattern. We also find that, based on the current Higgs data, this two-Higgs-doublet model generically predicts an enhanced production rate (compared to the Standard Model) in the pp -> h -> tau tau channel, and reduced rates in the VV -> h -> gamma gamma and p (p) over bar /pp -> V -> hV -> Vbb channels. Finally, the heavier CP-even Higgs is excluded by the current data up to m(H) similar to 500 GeV, while the pseudoscalar state, A, can be as light as 130 GeV. These heavier Higgs states and the expected deviations from the Standard Model din some of the Higgs production channels can be further excluded or discovered with more data.