1000 resultados para Process drifts


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Considering the staggering benefits of high-performance schools, it seems an obvious choice to “go green.” High-performance schools offer an exceptionally cost-effective means to enhance student learning, using on average 33 percent less energy than conventionally designed schools, and provide substantial health gains, including reduced respiratory problems and absenteeism. According to the 2006 study, Greening America's Schools, Costs and Benefits, co-sponsored by the American Institute of Architects (AIA) and Capital E, a green building consulting firm, high-performance lighting is a key element of healthy learning environments, contributing to improved test scores, reduced off-task behavior, and higher achievement among students. Few argue this point more convincingly than architect Heinz Rudolf, of Portland-Oregon-based Boora Architects, who has designed sustainable schools for more than 80 school districts in Oregon, Washington, Colorado, and Wyoming, and has pioneered the high-performance school movement. Boora's recently completed project, the Baker Prairie Middle School in Canby, Oregon is one of the most sustainable K-12 facilities in the state, and illustrates Rudolf's progressive and research-intensive approach to school design.

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This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

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Acoustic emission (AE) energy, instead of amplitude, associated with each of the event is used to estimate the fracture process zone (FPZ) size. A steep increase in the cumulative AE energy of the events with respect to time is correlated with the formation of FPZ. Based on the AE energy released during these events and the locations of the events, FPZ size is obtained. The size-independent fracture energy is computed using the expressions given in the boundary effect model by least squares method since over-determined system of equations are obtained when data from several specimens are used. Instead of least squares method a different method is suggested in which the transition ligament length, measured from the plot of histograms of AE events plotted over the un-cracked ligament, is used directly to obtain size-independent fracture energy. The fracture energy thus calculated seems to be size-independent.

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Structural, optical and magnetic studies of Co-doped ZnO have been carried out for bulk as well as thin films. The magnetic studies revealed the superparamagnetic nature for low-temperature synthesized samples, indicating the presence of cobalt metallic clusters, and this is supported by the optical studies. For the high-temperature sintered samples one obtains paramagnetism. The optical studies reveal the presence of Co2+ ions in the tetrahedral sites indicating proper doping. Interestingly, the films deposited by laser ablation from the paramagnetic target showed room temperature ferromagnetism. It appears that the magnetic nature of this system is process dependent.

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A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65mn gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of Response. Surface Methodology (RSM) using Design of Experiments (DOE) and Least Squares Method (LSM), are employed to generate a "hybrid model" for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by atleast 6X on a normalized basis, against worst case design.

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Two acceptor containing polyimides PDI and NDI carrying pyromellitic diimide units and 1,4,5,8-naphthalene tetracarboxy diimide units, respectively, along with hexa(oxyethylene) (EO6) segments as linkers, were prepared from the corresponding dianhydrides and diamines. These polyimides were made to fold by interaction with specifically designed folding agents containing a dialkoxynaphtha-lene (DAN) donor linked to a carboxylic acid group. The alkali-metal counter-ion of the donor carboxylic acid upon complexation with the EO6 segment brings the DAN unit in the right location to induce a charge-transfer complex formation with acceptor units in the polymer backbone. This two-point interaction between the folding agent and the polymer backbone leads to a folding of the polymer chain, which was readily monitored by NMR titrations. The effect of various parameters, such as structures of the folding agent and polymer, and the solvent composition, on the folding propensities of the polymer was studied.

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Product success is substantially influenced by satisfaction of knowledge needs of designers, and many tools and methods have been proposed to support these needs. However, adoption of these methods in industry is minimal. This may be due to an inadequate understanding of the knowledge needs of designers in industry. This research attempts to develop a better understanding of these needs by undertaking descriptive studies in an industry. We propose a taxonomy of knowledge, and evaluate this by analyzing the questions asked by the designers involved in the study during their interactions. Using the taxonomy, we converted the questions asked into a generic form. The generic questions provide an understanding about what knowledge must be captured during design, and what its structure should be.

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Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.

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This paper probes how two small foundries in Belgaum, Karnataka State, India, have achieved technological innovations successfully based on their technological capability and customer needs, enabling them to sail through the competitive environment. This study brought out that technically qualified entrepreneurs of both the foundries have carried out technological innovations, mainly due to their self-motivation and self-efforts. Changing product designs, as desired or directed by the customers, cost reduction, quality improvement and import substitution through reverse engineering are the characteristics of these technological innovations. These incremental innovations have enabled the entrepreneurs of the two foundries to enhance competitiveness, grow in the domestic market and penetrate the international market and grow in size over time.

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This paper probes how two small foundries in Belgaum, Karnataka State, India, have achieved technological innovations successfully based on their technological capability and customer needs, enabling them to sail through the competitive environment. This study brought out that technically qualified entrepreneurs of both the foundries have carried out technological innovations, mainly due to their self-motivation and self-efforts. Changing product designs, as desired or directed by the customers, cost reduction, quality improvement and import substitution through reverse engineering are the characteristics of these technological innovations. These incremental innovations have enabled the entrepreneurs of the two foundries to enhance competitiveness, grow in the domestic market and penetrate the international market and grow in size over time.

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In the present work, a numerical study is performed to predict the effect of process parameters on transport phenomena during solidification of aluminium alloy A356 in the presence of electromagnetic stirring. A set of single-phase governing equations of mass, momentum, energy and species conservation is used to represent the solidification process and the associated fluid flow, heat and mass transfer. In the model, the electromagnetic forces are incorporated using an analytical solution of Maxwell equation in the momentum conservation equations and the slurry rheology during solidification is represented using an experimentally determined variable viscosity function. Finally, the set of governing equations is solved for various process conditions using a pressure based finite volume technique, along with an enthalpy based phase change algorithm. In present work, the effect of stirring intensity and cooling rate are considered. It is found that increasing stirring intensity results in increase of slurry velocity and corresponding increase in the fraction of solid in the slurry. In addition, the increasing stirring intensity results uniform distribution of species and fraction of solid in the slurry. It is also found from the simulation that the distribution of solid fraction and species is dependent on cooling rate conditions. At low cooling rate, the fragmentation of dendrites from the solid/liquid interface is more.

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Crystalline Bi5NbO10 nanoparticles have been achieved through a modified sol–gel process using a mixture of ethylenediamine and ethanolamine as a solvent. The Bi5NbO10 nanoparticles were characterized by X-ray diffraction (XRD), differential scanning calorimetry/thermogravimetry (DSC/TG), Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM) and Raman spectroscopy. The results showed that well-dispersed 5–60 nm Bi5NbO10 nanoparticles were prepared through heat-treating the precursor at 650 °C and the high density pellets were obtained at temperatures lower than those commonly employed. The frequency and temperature dependence of the dielectric constant and the electrical conductivity of the Bi5NbO10 solid solutions were investigated in the 0.1 Hz to 1 MHz frequency range. Two distinct relaxation mechanisms were observed in the plots of dielectric loss and the imaginary part of impedance (Z″) versus frequency in the temperature range of 200–350 °C. The dielectric constant and the loss in the low frequency regime were electrode dependent. The ionic conductivity of Bi5NbO10 solid solutions at 700 °C is 2.86 Ω−1 m−1 which is in same order of magnitude for Y2O3-stabilized ZrO2 ceramics at same temperature. These results suggest that Bi5NbO10 is a promising material for an oxygen ion conductor.