Economic Control of Quality of Manufactured Product.

Polyphasic taxonomy, a consensus approach to bacterial systematics.

Brucellosis remains a major zoonosis worldwide Although many countries have eradicated Brucella abortus from cattle, in some areas Brucella melitensis has emerged as a cause of infection in this species as well as in sheep and goats Despite vaccination campaigns with the Rev 1 strain, B melitensis remains the principal cause of human brucellosis Brucella suis is also emerging as an agent of infection in cattle, thus extending its opportunities to infect humans The recent isolation of distinctive strains of Brucella from marine mammals has extended its ecologic range Molecular genetic studies have demonstrated phylogenetic affiliation to Agrobacterium, Phyllobacterium, Ochrobactrum, and Rhizobium Polymerase chain reaction and gene probe development may provide more effective typing methods Pathogenicity is related to production of lipopolysaccharides containing a poly N-formyl perosamine O chain, CuZn superoxide dismutase, erythrlose phosphate dehydrogenase, stress-induced proteins related to intracellular survival, and adenine and guanine monophosphate inhibitors of phagocyte functions Protective immunity is conferred by antibody to lipopolysaccharide and T-cell-mediated macrophage activation triggered by protein antigens Diagnosis still centers on isolation of the organism and serologic test results, especially enzyme immunoassay, which is replacing other methods Polymerase chain reaction is also under evaluation Therapy is based on tetracyclines with or without rifampicin, aminoglycosides, or quinolones No satisfactory vaccines against human brucellosis are available, although attenuated purE mutants appear promising

/pdf/brucellosis-an-overview-14k0fkto7f.pdf

Brucellosis: an overview.

Project scheduling under uncertainty: survey and research potentials

http://web.nchu.edu.tw/pweb/users/arborfish/lesson/8682.pdf

A survey of variants and extensions of the resource-constrained project scheduling problem

It is well-known that well managed and controlled projects are more likely to be delivered on time and within budget. The construction of a (resource-feasible) baseline schedule and the follow-up during execution are primary contributors to the success or failure of a project. Earned value management systems have been set up to deal with the complex task of controlling and adjusting the baseline project schedule during execution. Although earned value systems have been proven to provide reliable estimates for the follow-up of cost performance, they often fail to predict the total duration of the project. In this chapter, results of a large simulation study to evaluate the forecast accuracy of earned value based predictive metrics are presented. No detailed mathematical calculations are presented in the chapter, but instead an overview from a project life cycle point-of-view is presented. Details can be found at the end of the chapter (key terms and their definitions) or in the references cited throughout this chapter.

Static and dynamic determinants of earned value based time forecast accuracy

Activity-based costing (ABC) as well as other cost accounting systems provide accurate costs only under stringent conditions. However, we know little about the nature, level, and bias of costing errors. This paper reports the results of a simulation study of a two-stage costing system that provides the following main insights: 1) partial improvement in the costing system usually increases the overall accuracy of reported product costs except in certain cases identified in this paper where errors have an offsetting effect, most notably when there is aggregation error on the activity cost pools and measurement error on the resource drivers; 2) the impact of Stage II costing errors on overall accuracy is stronger than that of Stage I errors, so any system refinements should focus on Stage II; and 3) the introduction of aggregation and measurement errors usually results in relatively more products being under- than overcosted, with high amounts of overcosting for a few "big-ticket" (large dollar size) products, and small amounts of undercosting for a larger number of less expensive (small dollar size) products.

A simulation analysis of interactions among errors in costing system design

Well placement planning is one of the challenging issues in any field development plan. Reservoir engineers always confront the problem that which point of the field should be drilled to achieve the highest recovery factor and/or maximum sweep efficiency. In this paper, we use Reservoir Opportunity Index (ROI) as a spatial measure of productivity potential for greenfields, which hybridizes the reservoir static properties, and for brownfields, ROI is replaced by Dynamic Measure (DM), which takes into account the current dynamic properties in addition to static properties. The purpose of using these criteria is to diminish the search region of optimization algorithms and as a consequence, reduce the computational time and cost of optimization, which are the main challenges in well placement optimization problems. However, considering the significant subsurface uncertainty, a probabilistic definition of ROI (SROI) or DM (SDM) is needed, since there exists an infinite number of possible distribution maps of static and/or dynamic properties. To build SROI or SDM maps, the k -means clustering technique is used to extract a limited number of characteristic realizations that can reasonably span the uncertainties. In addition, to determine the optimum number of clustered realizations, Higher-Order Singular Value Decomposition (HOSVD) method is applied which can also compress the data for large models in a lower-dimensional space. Additionally, we introduce the multiscale spatial density of ROI or DM (D2 ROI and D2 DM), which can distinguish between regions of high SROI (or SDM) in arbitrary neighborhood windows from the local SROI (or SDM) maxima with low values in the vicinity. Generally, we develop and implement a new systematic approach for well placement optimization for both green and brownfields on a synthetic reservoir model. This approach relies on the utilization of multi-scale maps of SROI and SDM to improve the initial guess for optimization algorithm. Narrowing down the search region for optimization algorithm can substantially speed up the convergence and hence the computational cost would be reduced by a factor of 4.

Generalized Multi-Scale Stochastic Reservoir Opportunity Index for enhanced well placement optimization under uncertainty in green and brownfields

The idea of maximizing the net present value of the cash flows of a project has gained increasing attention over the past decades. Several solution procedures have been presented in the literature to cope with these financial aspects of project management. In this paper we compare three solution procedures for the unconstrained project scheduling problem with discounted cash flows. Each activity of this unconstrained project scheduling problem has a known deterministic cash flow which can be negative, zero or positive. Progress payments and cash outflows occur at the completion of activities. The objective is to schedule the activities subject to the precedence constraints and a fixed deadline in order to maximize the net present value. We compare two recursive search algorithms and a first-order steepest ascent approach for project scheduling problems where both minimal and maximal time-lags between the activities are considered. All procedures exploit the idea that positive cash flows should be scheduled as early as possible while negative cash flows should be scheduled as late as possible within the precedence constraints. The procedures have been coded in Visual C++, version 6.0 under Windows 2000 and have been validated on well-known problem sets.

https://lirias.kuleuven.be/bitstream/123456789/118487/1/OR_0030.pdf

A validation of procedures for maximizing the net present value of a project

Time-cost tradeoffs have been extensively studied in the literature since the development of the critical path method. Recently, the discrete version of the problem formulation has been extended to various practical assumptions, and solved with both exact and heuristic optimisation procedures, as described in Vanhoucke and Debels (J Sched 10:311–326, 2007).In this chapter, an overview is given of four variants of the discrete time-cost tradeoff problem and a newly developed electromagnetic meta-heuristic (EM) algorithm to solve these problems is presented. We extend the standard electromagnetic meta-heuristic with problem specific features and investigate the influence of various EM parameters on the solution quality. We test the new meta-heuristic on a benchmark set from the literature and present extensive computational results.

Mario Vanhoucke

Papers

Static and dynamic determinants of earned value based time forecast accuracy

A simulation analysis of interactions among errors in costing system design

Generalized Multi-Scale Stochastic Reservoir Opportunity Index for enhanced well placement optimization under uncertainty in green and brownfields

A validation of procedures for maximizing the net present value of a project

Generalized Discrete Time-Cost Tradeoff Problems