991 resultados para penalty-based aggregation functions


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In multicriteria decision problems many values must be assigned, such as the importance of the different criteria and the values of the alternatives with respect to subjective criteria. Since these assignments are approximate, it is very important to analyze the sensitivity of results when small modifications of the assignments are made. When solving a multicriteria decision problem, it is desirable to choose a decision function that leads to a solution as stable as possible. We propose here a method based on genetic programming that produces better decision functions than the commonly used ones. The theoretical expectations are validated by case studies. © 2003 Elsevier B.V. All rights reserved.

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In order to study the effect of washcoat composition on lean NOx trap (LNT) aging characteristics, fully formulated monolithic LNT catalysts containing varying amounts of La-stabilized CeO2 (5 wt% La2O3) or CeO2-ZrO2 (Ce:Zr = 70:30) were subjected to accelerated aging on a bench reactor. Subsequent catalyst evaluation revealed that aging resulted in deterioration of the NOx storage, NOx release and NOx reduction functions, whereas the observation of lean phase NO2 slip for all of the aged catalysts indicated that LNT performance was not limited by the kinetics of NO oxidation. After aging, all of the catalysts showed increased selectivity to NH3 in the temperature range 250–450 °C. TEM, H2 chemisorption, XPS and elemental analysis data revealed two main changes which can explain the degradation in LNT performance. First, residual sulfur in the catalysts, present as BaSO4, decreased catalyst NOx storage capacity. Second, sintering of the precious metals in the washcoat was observed, which can be expected to decrease the rate of NOx reduction. Additionally, sintering is hypothesized to result in segregation of the precious metal and Ba phases, resulting in less efficient NOx spillover from Pt to Ba during NOx adsorption, as well as decreased rates of reductant spillover from Pt to Ba and reverse NOx spillover during catalyst regeneration. Spectacular improvement in LNT durability was observed for catalysts containing CeO2 or CeO2-ZrO2 relative to their non-ceria containing analog. This was attributed to (i) the ability of ceria to participate in NOx storage/reduction as a supplement to the main Ba NOx storage component; (ii) the fact that Pt and CeO2(-ZrO2) are not subject to phase segregation; and (iii) the ability of ceria to trap sulfur, resulting in decreased sulfur accumulation on the Ba component.

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The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

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A synchronization scheme for a two-channel phase sensitive amplifier is implemented based on the injection-locking of single InP quantum-dash mode-locked laser. Error free performance with penalty <1 dB is demonstrated for both channels. © 2011 Optical Society of America.

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An injection-locking-based pump recovery system for phase-sensitively amplified links is proposed and studied experimentally. Measurements with 10 Gbaud DQPSK signals show penalty-free recovery of 0.8 GHz FWHM bandwidth pump with 63 dB overall amplification. © 2012 OSA.

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Logic based Pattern Recognition extends the well known similarity models, where the distance measure is the base instrument for recognition. Initial part (1) of current publication in iTECH-06 reduces the logic based recognition models to the reduced disjunctive normal forms of partially defined Boolean functions. This step appears as a way to alternative pattern recognition instruments through combining metric and logic hypotheses and features, leading to studies of logic forms, hypotheses, hierarchies of hypotheses and effective algorithmic solutions. Current part (2) provides probabilistic conclusions on effective recognition by logic means in a model environment of binary attributes.

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The first motivation for this note is to obtain a general version of the following result: let E be a Banach space and f : E → R be a differentiable function, bounded below and satisfying the Palais-Smale condition; then, f is coercive, i.e., f(x) goes to infinity as ||x|| goes to infinity. In recent years, many variants and extensions of this result appeared, see [3], [5], [6], [9], [14], [18], [19] and the references therein. A general result of this type was given in [3, Theorem 5.1] for a lower semicontinuous function defined on a Banach space, through an approach based on an abstract notion of subdifferential operator, and taking into account the “smoothness” of the Banach space. Here, we give (Theorem 1) an extension in a metric setting, based on the notion of slope from [11] and coercivity is considered in a generalized sense, inspired by [9]; our result allows to recover, for example, the coercivity result of [19], where a weakened version of the Palais-Smale condition is used. Our main tool (Proposition 1) is a consequence of Ekeland’s variational principle extending [12, Corollary 3.4], and deals with a function f which is, in some sense, the “uniform” Γ-limit of a sequence of functions.

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The problem of decision functions quality in pattern recognition is considered. An overview of the approaches to the solution of this problem is given. Within the Bayesian framework, we suggest an approach based on the Bayesian interval estimates of quality on a finite set of events.

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* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

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* The work is supported by RFBR, grant 04-01-00858-a.

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* Supported by INTAS 2000-626, INTAS YSF 03-55-1969, INTAS INNO 182, and TIC 2003-09319-c03-03.

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* Work is partially supported by the Lithuanian State Science and Studies Foundation.

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There is a proliferation of categorization schemes in the scientific literature that have mostly been developed from psychologists’ understanding of the nature of linguistic interactions. This has a led to problems in defining question types used by interviewers. Based on the principle that the overarching purpose of an interview is to elicit information and that questions can function both as actions in their own right and as vehicles for other actions, a Conversational Analysis approach was used to analyse a small number of police interviews. The analysis produced a different categorization of question types and, in particular, the conversational turns fell into two functional types: (i) Topic Initiation Questions and (ii) Topic Facilitation Questions. We argue that forensic interviewing requires a switch of focus from the ‘words’ used by interviewers in question types to the ‘function’ of conversational turns within interviews.

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In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

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Mathematics Subject Classification: Primary 30C40