Communications inspired linear discriminant analysis

We study the problem of supervised linear dimensionality reduction, taking an information-theoretic viewpoint. The linear projection matrix is designed by maximizing the mutual information between the projected signal and the class label. By harnessing a recent theoretical result on the gradient of mutual information, the above optimization problem can be solved directly using gradient descent, without requiring simplification of the objective function. Theoretical analysis and empirical comparison are made between the proposed method and two closely related methods, and comparisons are also made with a method in which Rényi entropy is used to define the mutual information (in this case the gradient may be computed simply, under a special parameter setting). Relative to these alternative approaches, the proposed method achieves promising results on real datasets. Copyright 2012 by the author(s)/owner(s).

Evaluating Stakeholder Engagement in North Carolina Sea Grant’s Strategic Planning Process

In order to develop a strategic plan that will guide their priorities and resource allocation for 2018-2021, North Carolina Sea Grant has implemented a multi-stage process designed to increase stakeholder engagement and to better assess and serve the coastal priorities of North Carolinians. This project explores strengths and potential areas for improvement within NC Sea Grant’s planning process with a specific focus on maximizing stakeholder engagement. By interviewing staff, observing focus groups, and creating a survey instrument for public distribution, we developed a set of recommendations highlighting the ways that NC Sea Grant can better facilitate inclusion of stakeholder, public, and staff input in its strategic planning process, such as holding some stakeholder events outside of typical business hours and discussing ways to incorporate diversity into the strategic plan.

Preemptive scheduling on uniform parallel machines with controllable job processing times

In this paper, we provide a unified approach to solving preemptive scheduling problems with uniform parallel machines and controllable processing times. We demonstrate that a single criterion problem of minimizing total compression cost subject to the constraint that all due dates should be met can be formulated in terms of maximizing a linear function over a generalized polymatroid. This justifies applicability of the greedy approach and allows us to develop fast algorithms for solving the problem with arbitrary release and due dates as well as its special case with zero release dates and a common due date. For the bicriteria counterpart of the latter problem we develop an efficient algorithm that constructs the trade-off curve for minimizing the compression cost and the makespan.

Sistema integrado para empresas de construcción en Cusco

Actualmente las empresas requieren estrategias innovadoras, que permitan gestionar de forma integral, optimizando los recursos y maximizando los resultados. Siendo el objetivo del presente trabajo de investigación, diseñar un instrumento de gestión integral (gestión de la calidad, ambiental, seguridad y salud ocupacional) para el sector construcción en Cusco. Se realizó un análisis actual de la actividad de construcción, se planteó a diferencia de otras propuestas, el diseño que inicia con el diagnóstico, planificación, organización, ejecución, supervisión y optimización del sistema integral. Los resultados están expresados en el diagnóstico de los 3 sistemas, información clave, para el planteamiento y propuesta de las etapas posteriores; estructurando el planteamiento de los subprogramas basados en el diagnóstico integral, para finalmente determinar los lineamientos estratégicos, de implementación, evaluación y verificación del sistema, teniendo en cuenta la norma ISO 9001: 2008, ISO 14001:2004 y OSHAS 18001:2007; así como la legislación vigente para el Perú.

Independent particle descriptions of tunneling using the many-body quantum transport approach

Currents across thin insulators are commonly taken as single electrons moving across classically forbidden regions; this independent particle picture is well-known to describe most tunneling phenomena. Examining quantum transport from a different perspective, i.e., by explicit treatment of electron-electron interactions, we evaluate different single particle approximations with specific application to tunneling in metal-molecule-metal junctions. We find maximizing the overlap of a Slater determinant composed of single-particle states to the many-body current-carrying state is more important than energy minimization for defining single-particle approximations in a system with open boundary conditions. Thus the most suitable single particle effective potential is not one commonly in use by electronic structure methods, such as the Hartree-Fock or Kohn-Sham approximations.

MISEP method for postnonlinear blind source separation

In this letter, a standard postnonlinear blind source separation algorithm is proposed, based on the MISEP method, which is widely used in linear and nonlinear independent component analysis. To best suit a wide class of postnonlinear mixtures, we adapt the MISEP method to incorporate a priori information of the mixtures. In particular, a group of three-layered perceptrons and a linear network are used as the unmixing system to separate sources in the postnonlinear mixtures, and another group of three-layered perceptron is used as the auxiliary network. The learning algorithm for the unmixing system is then obtained by maximizing the output entropy of the auxiliary network. The proposed method is applied to postnonlinear blind source separation of both simulation signals and real speech signals, and the experimental results demonstrate its effectiveness and efficiency in comparison with existing methods.

The less amorous Gammarus: predation risk affects mating decisions in Gammarus duebeni (Amphipoda)

We examined the trade-off between the behaviours associated with predator avoidance and mate acquisition in the mate-guarding amphipod crustacean Gammarus duebeni. We used laboratory experiments to investigate the impact of olfactory predator cues on activity, mate choice and mate-guarding behaviour of males and females. Pair formation declined under perceived risk of predation, reflecting reduced activity of both males and females and hence a reduced likelihood of encountering a mate. We also observed a reduction in the choosiness of both males and females. Under increased perceived predation risk, assessment of the female by the male was more likely to be followed by pair formation, and males showed a nonsignificant trend towards reduced discrimination in favour of large females and were less tenacious in their pair bond when they paired during exposure to predator cues. Females also showed less resistance behaviour, suggesting that both males and females trade off the costs of maximizing current reproductive success against the benefits of predator avoidance for survival and reproduction in the future. We discuss the implications of such context-dependent mating behaviours for ecological interactions between species and suggest that predators, via the effects of perceived predation risk on mate choice and mate guarding in the prey species, induce trait-mediated indirect effects with the potential to influence population dynamics and community structure. (C) 2008 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Genuine multipartite nonlocality of entangled thermal states

We assess quantum nonlocality of multiparty entangled thermal states by studying, quantitatively, both tripartite and quadripartite states belonging to the Greenberger-Horne-Zeilinger, W, and linear cluster-state classes and showing violation of relevant Bell-like inequalities. We discuss the conditions for maximizing the degree of violation against the local thermal character of the states and the inefficiency of the detection apparatuses. We demonstrate that such classes of multipartite entangled states can be made to last quite significantly, notwithstanding adverse operating conditions. This opens up the possibility for coherent exploitation of multipartite quantum channels made out of entangled thermal states. Our study is accompanied by a detailed description of possible generation schemes for the states analyzed.

Methodological considerations in reserve system selection: a case study of Malagasy Lemurs.

Although data quality and weighting decisions impact the outputs of reserve selection algorithms, these factors have not been closely studied. We examine these methodological issues in the use of reserve selection algorithms by comparing: (1) quality of input data and (2) use of different weighting methods for prioritizing among species. In 2003, the government of Madagascar, a global biodiversity hotspot, committed to tripling the size of its protected area network to protect 10% of the country’s total land area. We apply the Zonation reserve selection algorithm to distribution data for 52 lemur species to identify priority areas for the expansion of Madagascar’s reserve network. We assess the similarity of the areas selected, as well as the proportions of lemur ranges protected in the resulting areas when different forms of input data were used: extent of occurrence versus refined extent of occurrence. Low overlap between the areas selected suggests that refined extent of occurrence data are highly desirable, and to best protect lemur species, we recommend refining extent of occurrence ranges using habitat and altitude limitations. Reserve areas were also selected for protection based on three different species weighting schemes, resulting in marked variation in proportional representation of species among the IUCN Red List of Threatened Species extinction risk categories. This result demonstrates that assignment of species weights influences whether a reserve network prioritizes maximizing overall species protection or maximizing protection of the most threatened species.

Capacity and resource allocation of cooperative MIMO in ad hoc networks

Cooperative MIMO (Multiple Input–Multiple Output) allows multiple nodes share their antennas to emulate antenna arrays and transmit or receive cooperatively. It has the ability to increase the capacity for future wireless communication systems and it is particularly suited for ad hoc networks. In this study, based on the transmission procedure of a typical cooperative MIMO system, we first analyze the capacity of single-hop cooperative MIMO systems, and then we derive the optimal resource allocation strategy to maximize the end-to-end capacity in multi-hop cooperative MIMO systems. The study shows three implications. First, only when the intra-cluster channel is better than the inter-cluster channel, cooperative MIMO results in a capacity increment. Second, for a given scenario there is an optimal number of cooperative nodes. For instance, in our study an optimal deployment of three cooperative nodes achieve a capacity increment of 2 bps/Hz when compared with direct transmission. Third, an optimal resource allocation strategy plays a significant role in maximizing end-to-end capacity in multi-hop cooperative MIMO systems. Numerical results show that when optimal resource allocation is applied we achieve more than 20% end-to-end capacity increment in average when compared with an equal resource allocation strategy.

Promoting Health Behaviour Change in the Cardiac Patient

The importance of giving patients advice in relation to positive health behaviour change geared towards maximizing physical health must not be overlooked and is an important role of the cardiac nurse in contemporary health care. However, over-reliance on offering advice can often be counter-productive and less likely to achieve effective change. Patients are more likely to make positive health behaviour changes when they self-generate their own solutions to the health issues and problems that they face. In this article, the authors encourage cardiac nurses to embrace a less directive and more facilitative approach to patient health behaviour change in light of the mounting evidence that exists to the effectiveness of motivational interviewing techniques.

A hybrid metaheuristic approach to the university course timetabling problem

This paper describes the development of a novel metaheuristic that combines an electromagnetic-like mechanism (EM) and the great deluge algorithm (GD) for the University course timetabling problem. This well-known timetabling problem assigns lectures to specific numbers of timeslots and rooms maximizing the overall quality of the timetable while taking various constraints into account. EM is a population-based stochastic global optimization algorithm that is based on the theory of physics, simulating attraction and repulsion of sample points in moving toward optimality. GD is a local search procedure that allows worse solutions to be accepted based on some given upper boundary or ‘level’. In this paper, the dynamic force calculated from the attraction-repulsion mechanism is used as a decreasing rate to update the ‘level’ within the search process. The proposed method has been applied to a range of benchmark university course timetabling test problems from the literature. Moreover, the viability of the method has been tested by comparing its results with other reported results from the literature, demonstrating that the method is able to produce improved solutions to those currently published. We believe this is due to the combination of both approaches and the ability of the resultant algorithm to converge all solutions at every search process.

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.

Single mating in orchid bees (Euglossa, Apinae): implications for mate choice and social evolution

Neotropical orchid bees (Euglossini) are conspicuously different from other corbiculate bees (Apinae) in their lack of advanced sociality and in male use of acquired odors (fragrances) as pheromone-analogues. In both contexts, orchid bee mating systems, in particular the number of males a female mates with, are of great interest but are currently unknown. To assess female mating frequency in the genus Euglossa, we obtained nests from three species in Mexico and Panama and genotyped mothers and their brood at microsatellite DNA loci. In 26 out of 29 nests, genotypes of female brood were fully consistent with being descended from a singly mated mother. In nests with more than one adult female present, those adult females were frequently related, with genotypes being consistent with full sister-sister (r = 0.75) or mother-daughter (r = 0.5) relationships. Thus, our genetic data support the notions of female philopatry and nest-reuse in the genus Euglossa. Theoretically, single mating should promote the evolution of eusociality by maximizing the relatedness among individuals in a nest. However, in Euglossini this genetic incentive has not led to the formation of eusocial colonies as in other corbiculate bees, presumably due to differing ecological or physiological selective regimes. Finally, monandry in orchid bees is in agreement with the theory that females select a single best mate based on the male fragrance phenotype, which may contain information on male age, cognitive ability, and competitive strength.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.