A new repair-replace strategy for items sold with a two-dimensional warranty

For repairable items, the manufacturer has the option to either repair or replace a failed item that is returned under warranty. In this paper, we look at a new warranty servicing strategy for items sold with two-dimensional warranty where the failed item is replaced by a new one when it fails for the first time in a specified region of the warranty and all other failures are repaired minimally. The region is characterised by two parameters and we derive the optimal values for these to minimise the total expected warranty servicing cost. We compare the results with other repair-replace strategies reported in the literature. (C) 2003 Elsevier Ltd. All rights reserved.

General gaussian priors for improved generalisation

We explore the dependence of performance measures, such as the generalization error and generalization consistency, on the structure and the parameterization of the prior on `rules', instanced here by the noisy linear perceptron. Using a statistical mechanics framework, we show how one may assign values to the parameters of a model for a `rule' on the basis of data instancing the rule. Information about the data, such as input distribution, noise distribution and other `rule' characteristics may be embedded in the form of general gaussian priors for improving net performance. We examine explicitly two types of general gaussian priors which are useful in some simple cases. We calculate the optimal values for the parameters of these priors and show their effect in modifying the most probable, MAP, values for the rules.

A new rapidly absorbed paracetamol tablet containing sodium bicarbonate. II. Dissolution studies and in vitro/in vivo correlation

The objective of this study was to compare the in vitro dissolution profile of a new rapidly absorbed paracetamol tablet containing sodium bicarbonate (PS) with that of a conventional paracetamol tablet (P), and to relate these by deconvolution and mapping to in vivo release. The dissolution methods used include the standard procedure described in the USP monograph for paracetamol tablets, employing buffer at pH5.8 or 0.05 M HCl at stirrer speeds between 10 and 50 rpm. The mapping process was developed and implemented in Microsoft Excel® worksheets that iteratively calculated the optimal values of scale and shape factors which linked in vivo time to in vitro time. The in vitro-in vivo correlation (IVIVC) was carried out simultaneously for both formulations to produce common mapping factors. The USP method, using buffer at pH5.8, demonstrated no difference between the two products. However, using an acidic medium the rate of dissolution of P but not of PS decreased with decreasing stirrer speed. A significant correlation (r=0.773; p<.00001) was established between in vivo release and in vitro dissolution using the profiles obtained with 0.05 M HCl and a stirrer speed of 30 rpm. The scale factor for optimal simultaneous IVIVC in the fasting state was 2.54 and the shape factor was 0.16; corresponding values for mapping in the fed state were 3.37 and 0.13 (implying a larger in vitro-in vivo time difference but reduced shape difference in the fed state). The current IVIVC explains, in part, the observed in vivo variability of the two products. The approach to mapping may also be extended to different batches of these products, to predict the impact of any changes of in vitro dissolution on in vivo release and plasma drug concentration-time profiles.

Performance of downlink massive MIMO in Ricean fading channels with ZF precoder

We investigate the achievable sum rate and energy efficiency of zero-forcing precoded downlink massive multiple-input multiple-output systems in Ricean fading channels. A simple and accurate approximation of the average sum rate is presented, which is valid for a system with arbitrary rank channel means. Based on this expression, the optimal power allocation strategy maximizing the average sum rate is derived. Moreover, considering a general power consumption model, the energy efficiency of the system with rank-1 channel means is characterized. Specifically, the impact of key system parameters, such as the number of users N, the number of BS antennas M, Ricean factor K and the signal-to-noise ratio (SNR) ρ are studied, and closed-form expressions for the optimal ρ and M maximizing the energy efficiency are derived. Our findings show that the optimal power allocation scheme follows the water filling principle, and it can substantially enhance the average sum rate in the presence of strong line-of-sight effect in the low SNR regime. In addition, we demonstrate that the Ricean factor K has significant impact on the optimal values of M, N and ρ.

Large-scale prediction of seagrass distribution: the case of Cymodocea nodosa (Mediterranean-Atlantic)

Understanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. We model the environmental niche of Cymodocea nodosa using a combination of environmental variables and landscape metrics to examine factors defining its distribution and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 ºC to 26.4 ºC and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 m and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems.

A natural extension of the classical envelope theorem in vector differential programming

The aim of this paper is to extend the classical envelope theorem from scalar to vector differential programming. The obtained result allows us to measure the quantitative behaviour of a certain set of optimal values (not necessarily a singleton) characterized to become minimum when the objective function is composed with a positive function, according to changes of any of the parameters which appear in the constraints. We show that the sensitivity of the program depends on a Lagrange multiplier and its sensitivity.

Bayesian Linear Regression for estimation of the Fractal Dimension of the Cerebral Cortex

The cerebral cortex presents self-similarity in a proper interval of spatial scales, a property typical of natural objects exhibiting fractal geometry. Its complexity therefore can be characterized by the value of its fractal dimension (FD). In the computation of this metric, it has usually been employed a frequentist approach to probability, with point estimator methods yielding only the optimal values of the FD. In our study, we aimed at retrieving a more complete evaluation of the FD by utilizing a Bayesian model for the linear regression analysis of the box-counting algorithm. We used T1-weighted MRI data of 86 healthy subjects (age 44.2 ± 17.1 years, mean ± standard deviation, 48% males) in order to gain insights into the confidence of our measure and investigate the relationship between mean Bayesian FD and age. Our approach yielded a stronger and significant (P < .001) correlation between mean Bayesian FD and age as compared to the previous implementation. Thus, our results make us suppose that the Bayesian FD is a more truthful estimation for the fractal dimension of the cerebral cortex compared to the frequentist FD.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Non-timber values and the optimal forest rotation: An application to the southern forest of Tasmania

The present paper examines the optimal use of a site containing standing timber, taking account of both timber and non-timber values. Using a site in the southern forest of Tasmania for illustrative purposes, it calculates the relationships between age of stand, extent of timber and non-timber values and optimal cutting age. It finds that, for a stand with moderate potential environmental benefits, there is a period of its life during which it is optimal to log. This segment narrows, and eventually disappears, as potential environmental benefits increase.

Doehlert Design-desirability Function Multi-criteria Optimal Separation Of 17 Phenolic Compounds From Extra-virgin Olive Oil By Capillary Zone Electrophoresis.

In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.

Optimal fermentation conditions for maximizing the ethanol production by Kluyveromyces fragilis from cheese whey powder

Cheese whey powder (CWP) is an attractive raw material for ethanol production since it is a dried and concentrated form of CW and contains lactose in addition to nitrogen, phosphate and other essential nutrients. In the present work, deproteinized CWP was utilized as fermentation medium for ethanol production by Kluyveromyces fragilis. The individual and combined effects of initial lactose concentration (50-150 kg m(-3)), temperature (25-35 degrees C) and inoculum concentration (1-3 kg m(-3)) were investigated through a 2(3) full-factorial central composite design, and the optimal conditions for maximizing the ethanol production were determined. According to the statistical analysis, in the studied range of values, only the initial lactose concentration had a significant effect on ethanol production, resulting in higher product formation as the initial substrate concentration was increased. Assays with initial lactose concentration varying from 150 to 250 kg m(-3) were thus performed and revealed that the use of 200 kg m(-3) initial lactose concentration, inoculum concentration of 1 kg m(-3) and temperature of 35 degrees C were the best conditions for maximizing the ethanol production from CWP solution. Under these conditions, 80.95 kg m(-3) of ethanol was obtained after 44 h of fermentation. (C) 2011 Elsevier Ltd. All rights reserved.

Optimal conditions for the wetting balance test

Wetting balance tests of copper sheets submerged in tin solder baths were carried out in a completely automatic wetting balance. Wetting curves were examined for three different values of sheet thickness and four different solder bath temperatures. Most of the wetting curves showed a distorted shape relative to that of a standard curve, preventing calculation of important wetting parameters, such as the wetting rate and the wetting force. The wetting tests showed that the distortion increased for a thicker sheet thickness and a lower solder bath temperature, being the result of solder bath solidification around the submerged sheet substrate. (C) 2008 Elsevier B.V. All rights reserved.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

Evaluation of IMRT and VMAT techniques with and without flattening filter using pareto optimal fronts

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.