860 resultados para two-stage sampling


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The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.

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Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to he stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase H and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail. Copyright (C) 2008 John Wiley & Sons, Ltd.

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Aims: Certain milk factors may promote the growth of a gastrointestinal microflora predominated by bifidobacteria and may aid in overcoming enteric infections. This may explain why breast-fed infants experience fewer intestinal infections than their formula-fed counterparts. The effect of formula supplementation with two such factors was investigated in this study. Methods and Results: Infant faecal specimens were used to ferment formulae supplemented with glycomacropeptide (GMP) and alpha-lactalbumin (alpha-la) in a two-stage compound continuous culture model. At steady state, all fermenter vessels were inoculated with 5 ml of 0.1 M phosphate-buffered saline (pH 7.2) containing 10(8) CFU ml(-1) of either enteropathogenic Escherichia coli 2348/69 (O127:H6) or Salmonella serotype Typhimurium (DSMZ 5569). Bacteriology was determined by independent fluorescence in situ hybridization. Vessels that contained breast milk (BM), as well as alpha-la and GMP supplemented formula had stable total counts of bifidobacteria while lactobacilli increased significantly only in vessels with breast milk. Bacteroides, clostridia and E. coli decreased significantly in all three groups prior to pathogen addition. Escherichia coli counts decreased in vessels containing BM and alpha-la while Salmonella decreased significantly in all vessels containing BM, alpha-la and GMP. Acetate was the predominant acid. Significance and Impact of the Study: Supplementation of infant formulae with appropriate milk proteins may be useful in mimicking the beneficial bacteriological effects of breast milk.

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This paper considers two-stage iterative processes for solving the linear system $Af = b$. The outer iteration is defined by $Mf^{k + 1} = Nf^k + b$, where $M$ is a nonsingular matrix such that $M - N = A$. At each stage $f^{k + 1} $ is computed approximately using an inner iteration process to solve $Mv = Nf^k + b$ for $v$. At the $k$th outer iteration, $p_k $ inner iterations are performed. It is shown that this procedure converges if $p_k \geqq P$ for some $P$ provided that the inner iteration is convergent and that the outer process would converge if $f^{k + 1} $ were determined exactly at every step. Convergence is also proved under more specialized conditions, and for the procedure where $p_k = p$ for all $k$, an estimate for $p$ is obtained which optimizes the convergence rate. Examples are given for systems arising from the numerical solution of elliptic partial differential equations and numerical results are presented.

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Certain milk factors can promote the growth of a host-friendly gastrointestinal microflora. This may explain why breast-fed infants experience fewer intestinal infections than their formula-fed counterparts. The effect of formula supplementation with two such factors was investigated in this study. Infant faecal specimens were used to ferment formulas supplemented with glycomacropeptide and α-lactalbumin in a two-stage compound continuous culture model. Bacteriology was determined by fluorescence in situ hybridisation. Vessels that contained breast milk as well as α-lactalbumin and glycomacropeptide had stable counts of bifidobacteria while lactobacilli increased significantly only in vessels with breast milk. Bacteroides, clostridia and Escherichia coli decreased significantly in all runs. Acetate was the principal acid found along with high amounts of propionate and lactate. Supplementation of infant formulas with appropriate milk proteins may be useful in simulating the beneficial bacteriological effects of breast milk.

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Most CRM work focuses on consumer applications. This paper addresses the operational adoption issues facing the organisation deploying CRM practices. There are a plethora of challenges facing organisations when adopting CRM. Previous research is limited to either examining the CRM adoption process at an individual/employees level or an organisational level. Hence, in this paper the myriad of organisational, marketing and technical antecedents that seem to impinge upon employee perceptions and organisational implementation of CRM are structured in a two-stage model. Using a stratified sample of ten organisations across four sectors, seven hypotheses are tested on data collected from 301 practitioners. A two-stage model is analysed using structural equation modelling. Findings reveal that CRM implementation relates to employee perceptions of CRM. This paper deepens our understanding of organisational practices to adopt CRM, so as an organisation properly profits from the expected benefits of CRM.

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The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

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This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty or weighting parameters for its initialization.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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When the (X) over bar chart is in use, samples are regularly taken from the process, and their means are plotted on the chart. In some cases, it is too expensive to obtain the X values, but not the values of a correlated variable Y. This paper presents a model for the economic design of a two-stage control chart, that is. a control chart based on both performance (X) and surrogate (Y) variables. The process is monitored by the surrogate variable until it signals an out-of-control behavior, and then a switch is made to the (X) over bar chart. The (X) over bar chart is built with central, warning. and action regions. If an X sample mean falls in the central region, the process surveillance returns to the (Y) over bar chart. Otherwise. The process remains under the (X) over bar chart's surveillance until an (X) over bar sample mean falls outside the control limits. The search for an assignable cause is undertaken when the performance variable signals an out-of-control behavior. In this way, the two variables, are used in an alternating fashion. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A study is performed to examine the economic advantages of using performance and surrogate variables. (C) 2003 Elsevier B.V. All rights reserved.

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This paper investigates the most desirable configuration of a two-stage nonlinear vibration isolation system, in which the isolators contain hardening geometric stiffness nonlinearity and linear viscous damping. The force transmissibility of the system is used as the measure of the effectiveness of the isolation system. The hardening nonlinearity is achieved by placing horizontal springs onto the suspended and intermediate masses, which are supported by vertical springs. It is found that nonlinearity in the upper stage has very little effect and thus serves little purpose. The nonlinearity in the lower stage, however, has a profound effect, and can significantly improve the effectiveness of the isolation system. Further, it is found that it is desirable to have high damping in the upper stage and very low damping in the lower stage. © 2012 Elsevier Ltd.

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Linear single-stage vibration isolation systems have a limitation on their performance, which can be overcome passively by using linear two-stage isolations systems. It has been demonstrated by several researchers that linear single-stage isolation systems can be improved upon by using nonlinear stiffness elements, especially for low-frequency vibrations. In this paper, an investigation is conducted into whether the same improvements can be made to a linear two-stage isolation system using the same methodology for both force and base excitation. The benefits of incorporating geometric stiffness nonlinearity in both upper and lower stages are studied. It is found that there are beneficial effects of using nonlinearity in the stiffness in both stages for both types of excitation. Further, it is found that this nonlinearity causes the transmissibility at the lower resonance frequency to bend to the right, but the transmissibility at the higher resonance frequency is not affected in the same way. Generally, it is found that a nonlinear two-stage system has superior isolation performance compared to that of a linear two-stage isolator.