This paper presents a new approach to robustness analysis in multi-objective optimization problems aimed at obtaining the most robust Pareto front solutions and distributing the solutions along the most robust regions of the optimal Pareto set. A new set of test problems accounting for the different types of robustness cases is presented in this study. Non-dominated solutions are classified according to their degree of robustness and are distributed along the Pareto front according to specific algorithm parameter values. Verification of the proposed method is carried out using the developed test problems and artificial and real world benchmark test problems present in the literature. 相似文献
The alarm pheromone system ofLeptoglossus zonatus (Dallas) adults was shown to be composed of hexyl acetate, hexanol, hexanal, and hexanoic acid. Single components tested in the field elicited dispersive behavior of over 70% of adults. 2-(E)-Hexenal, found in the secretion of nymphs, but not in the exudates of adults, was also active against adults. In addition, first-instar nymphs responded to the four components of the alarm pheromone of adults as well as to 2-(E)-hexenal, a component of their own alarm pheromone system. Adults and nymphs possess different alarm pheromone systems, which are not specific to their own life stage. That hemipteran alarm pheromone systems are not species-specific was supported by the fact that both adult and nymphL. zonatus responded to butanoic acid, an alarm pheromone of Alydidae, which was not found in this Coreidae species. 相似文献
The “River Disease” (RD), a disorder impacting honeybee colonies located close to waterways with abundant riparian vegetation (including Sebastiania schottiana, Euphorbiaceae), kills newly hatched larvae. Forager bees from RD-affected colonies collect honeydew excretions from Epormenis cestri (Hemiptera: Flatidae), a planthopper feeding on trees of S. schottiana. First-instar honeybee larvae fed with this honeydew died. Thus, we postulated that the nectars of RD-affected colonies had a natural toxin coming from either E. cestri or S. schottiana. An untargeted metabolomics characterization of fresh nectars extracts from colonies with and without RD allowed to pinpoint xanthoxylin as one of the chemicals present in higher amounts in nectar from RD-affected colonies than in nectars from healthy colonies. Besides, xanthoxylin was also found in the aerial parts of S. schottiana and the honeydew excreted by E. cestri feeding on this tree. A larva feeding assay where xanthoxylin-enriched diets were offered to 1st instar larvae showed that larvae died in the same proportion as larvae did when offered enriched diets with nectars from RD-colonies. These findings demonstrate that a xenobiotic can mimic the RD syndrome in honeybee larvae and provide evidence of an interspecific flow of xanthoxylin among three trophic levels. Further, our results give information that can be considered when implementing measures to control this honeybee disease.
This paper presents Latency-Energy Minimization Medium Access (LEMMA), a new TDMA-based MAC protocol for Wireless Sensor Networks (WSNs), specially suited to extend the lifetime of networks supporting alarm-driven, delay-sensitive applications characterized by convergecast traffic patterns and sporadic traffic generation. Its cascading time-slot assignment scheme conciliates low end-to-end latency with a low duty-cycle, while supporting multi-sink WSN topologies. Unlike most of the current solutions, LEMMA’s time-slot allocation protocol makes decisions based on the interference actually experienced by the nodes, instead of following the simple but potentially ineffective n-hop approach. Simulation results are presented to demonstrate the ineffectiveness of the n-hop time-slot allocation in comparison with LEMMA, as well as to evaluate the performance of LEMMA against L-MAC, T-MAC and Low Power Listening. The results show that under the target scenario conditions, LEMMA presents lower interference between assigned time-slots and lower end-to-end latency, while matching its best contender in terms of energy-efficiency. 相似文献
The present work addresses the problem of structural damage identification built on the statistical inversion approach. Here, the damage state of the structure is continuously described by a cohesion parameter, which is spatially discretized by the finite element method. The inverse problem of damage identification is then posed as the determination of the posterior probability densities of the nodal cohesion parameters. The Markov Chain Monte Carlo method, implemented with the Metropolis–Hastings algorithm, is considered in order to approximate the posterior probabilities by drawing samples from the desired joint posterior probability density function. With this approach, prior information on the sought parameters can be used and the uncertainty concerning the known values of the material properties can be quantified in the estimation of the cohesion parameters. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. The damage identification and assessment are performed considering time domain response data. Different damage scenarios and noise levels were addressed, demonstrating the feasibility of the proposed approach. 相似文献
This paper presents two new approaches for constructing an ensemble of neural networks (NN) using coevolution and the artificial
immune system (AIS). These approaches are extensions of the CLONal Selection Algorithm for building ENSembles (CLONENS) algorithm.
An explicit diversity promotion technique was added to CLONENS and a novel coevolutionary approach to build neural ensembles
is introduced, whereby two populations representing the gates and the individual NN are coevolved. The former population is
responsible for defining the ensemble size and selecting the members of the ensemble. This population is evolved using the
differential evolution algorithm. The latter population supplies the best individuals for building the ensemble, which is
evolved by AIS. Results show that it is possible to automatically define the ensemble size being also possible to find smaller
ensembles with good generalization performance on the tested benchmark regression problems. More interestingly, the use of
the diversity measure during the evolutionary process did not necessarily improve generalization. In this case, diverse ensembles
may be found using only implicit diversity promotion techniques. 相似文献
Increasingly, new regulations are governing organizations and their information systems. Individuals responsible for ensuring legal compliance and accountability currently lack sufficient guidance and support to manage their legal obligations within relevant information systems. While software controls provide assurances that business processes adhere to specific requirements, such as those derived from government regulations, there is little support to manage these requirements and their relationships to various policies and regulations. We propose a requirements management framework that enables executives, business managers, software developers and auditors to distribute legal obligations across business units and/or personnel with different roles and technical capabilities. This framework improves accountability by integrating traceability throughout the policy and requirements lifecycle. We illustrate the framework within the context of a concrete healthcare scenario in which obligations incurred from the Health Insurance Portability and Accountability Act (HIPAA) are delegated and refined into software requirements. Additionally, we show how auditing mechanisms can be integrated into the framework and how auditors can certify that specific chains of delegation and refinement decisions comply with government regulations. 相似文献