A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.

Medieval knights amid the gum-trees : the experience of European heritage tourism in south-east Queensland, Australia

This paper is interested in the way in which the heritage of another place, time, and culture is repurposed for popular consumption in an experience economy, as well as the way in which the visitors experience their own past and the past of others. We trace the processes of engagement, education and nostalgia that occur when the European heritage is presented in a postcolonial context and an Australian environment. The information presented includes the results of qualitative and quantitative research conducted at the Abbey Museum over the December-Jan. period of 2012-13.

Evolutionary Perspectives

The standard approach to industrial economics starts with the industry’s basic conditions, then runs through the structure–conduct–performance paradigm of industrial organization, and finally considers government regulation and policy. Most creative industries segments have been studied in this way, for example in Albarran (2002) and Caves (2000). These approaches use standard economic analysis to explain the particular properties and characteristics of a specific industrial sector. The overview presented here is different again. It focuses on the creative industries and examines their economic effect, specifically their contribution to economic evolu -tion. This is an evolutionary systems approach to industrial analysis, where we seek to understand how a sector fits into a broader system of production, consumption, technology, trade and institutions. The evolutionary approach focuses on innovation, economic growth and endogenous transformation. So, rather than using economics to explain static or industrial-organization features of the creative industries, we are using an open systems view of the creative industries to explain dynamic ‘Schumpeterian’ features of the broader economy. The creative industries are drivers of economic transformation through their role in the origination of new ideas, in consumer adoption, and in facilitating the institutional embedding of new ideas into the economic order. This is not a novel idea, as economists have long understood that particular activities are drivers of economic growth and development, for example research and development, and also that particular sectors are instrumental to this process, for example high-technology sectors. What is new is the argument that cultural and creative sectors are also a key part of this process of economic evolution. We will review the case for that claim, and outline purported mechanisms. We will also consider why policy settings in the creative industries should be more in line with innovation and growth policy than with industry policy.

Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Design methodologies and architectures of hardware-based evolutionary algorithms for aerospace optimisation applications on FPGAS

This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospace platforms and providing effective performance speedups over traditional methods.

Managed livestock grazing is compatible with the maintenance of plant diversity in semidesert grasslands

Even when no baseline data are available, the impacts of 150 years of livestock grazing on natural grasslands can be assessed using a combined approach of grazing manipulation and regional-scale assessment of the flora. Here, we demonstrate the efficacy of this method across 18 sites in the semidesert Mitchell grasslands of northeastern Australia. Fifteen-year-old exclosures (ungrazed and macropod grazed) revealed that the dominant perennial grasses in the genus Astrebla do not respond negatively to grazing disturbance typical of commercial pastoralism. Neutral, positive, intermediate, and negative responses to grazing disturbance were recorded amongst plant species with no single life-form group associated with any response type. Only one exotic species, Cenchrus ciliaris, was recorded at low frequency. The strongest negative response was from a native annual grass, Chionachne hubbardiana, an example of a species that is highly sensitive to grazing disturbance. Herbarium records revealed only scant evidence that species with a negative response to grazing have declined through the period of commercial pastoralism. A regional analysis identified 14 from a total of 433 plant species in the regional flora that may be rare and potentially threatened by grazing disturbance. However, a targeted survey precluded grazing as a cause of decline for seven of these based on low palatability and positive responses to grazing and other disturbance. Our findings suggest that livestock grazing of semidesert grasslands with a short evolutionary history of ungulate grazing has altered plant composition, but has not caused declines in the dominant perennial grasses or in species richness as predicted by the preceding literature. The biggest impact of commercial pastoralism is the spread of woody leguminous trees that can transform grassland to thorny shrubland. The conservation of plant biodiversity is largely compatible with commercial pastoralism provided these woody weeds are controlled, but reserves strategically positioned within water remote areas are necessary to protect grazing-sensitive species. This study demonstrates that a combination of experimental studies and regional surveys can be used to understand anthropogenic impacts on natural ecosystems where reference habitat is not available.

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Part 3. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 3.) Practical application to the design and optimisation of UAV systems

These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.

Genetic and phenotypic evidence supports evolutionary divergence of the American flamingo (Phoenicopterus ruber) population in the Galapagos islands

The Galapagos archipelago is characterized by a high degree of endemism across many taxa, linked to the archpelago's oceanic origin and distance from other colonizing land masses. A population of ~ 500 American Flamingos (Phoenicopterus ruber) resides in Galapagos, which is thought to share an historical origin with the American Flamingo currently found in the Caribbean region. Genetic and phenotypic parameters in American Flamingos from Galapagos and from the Caribbean were investigated. Microsatellite and microchondrial DNA markers data showed that the American Flamingo population in Galapagos differs genetically from that in the Caribbean. American Flamingos in Galapagos form a clade which differs by a single common nucleotide substitution from American Flamingos in the Caribbean. The genetic differentiation is also evident from nuclear DNA in that microsatellite data reveal a number of private alleles for the American Flamingo in Galapagos. Analysis of skeletal measurements showed that American Flamingos in Galapagos are smaller than those in the Caribbean primarily due to shorter tarsus length, and differences in body shape sexual dimorphism. American Flamingo eggs from Galapagos have smaller linear dimensions and volumes than those from the Caribbean. The findings are consistent with reproductive isolation of American Flamingo population in Galapagos.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

Rescaling clustering trees using impact ratios for robust hierarchical speaker clustering

We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

Not drowning, (hand)waving? Molecular phylogenetics, biogeography and evolutionary tempo of the ‘Gondwanan’ midge Stictocladius Edwards (Diptera: Chironomidae)

Many insect clades, especially within the Diptera (true flies), have been considered classically ‘Gondwanan’, with an inference that distributions derive from vicariance of the southern continents. Assessing the role that vicariance has played in the evolution of austral taxa requires testing the location and tempo of diversification and speciation against the well-established predictions of fragmentation of the ancient super-continent. Several early (anecdotal) hypotheses that current austral distributions originate from the breakup of Gondwana derive from studies of taxa within the family Chironomidae (non-biting midges). With the advent of molecular phylogenetics and biogeographic analytical software, these studies have been revisited and expanded to test such conclusions better. Here we studied the midge genus Stictocladius Edwards, from the subfamily Orthocladiinae, which contains austral-distributed clades that match vicariance-based expectations. We resolve several issues of systematic relationships among morphological species and reveal cryptic diversity within many taxa. Time-calibrated phylogenetic relationships among taxa accorded partially with the predicted tempo from geology. For these apparently vagile insects, vicariance-dated patterns persist for South America and Australia. However, as often found, divergence time estimates for New Zealand at c. 50 mya post-date separation of Zealandia from Antarctica and the remainder of Gondwana, but predate the proposed Oligocene ‘drowning’ of these islands. We detail other such ‘anomalous’ dates and suggest a single common explanation rather than stochastic processes. This could involve synchronous establishment following recovery from ‘drowning’ and/or deleteriously warming associated with the mid-Eocene climatic optimum (hence ‘waving’, which refers to cycles of drowning events) plus new availability of topography providing of cool running waters, or all these factors in combination. Alternatively a vicariance explanation remains available, given the uncertain duration of connectivity of Zealandia to Australia–Antarctic–South America via the Lord Howe and Norfolk ridges into the Eocene.

Selection procedures for module discovery : exploring evolutionary algorithms for cognitive science

Evolutionary algorithms are playing an increasingly important role as search methods in cognitive science domains. In this study, methodological issues in the use of evolutionary algorithms were investigated via simulations in which procedures were systematically varied to modify the selection pressures on populations of evolving agents. Traditional roulette wheel, tournament, and variations of these selection algorithms were compared on the “needle-in-a-haystack” problem developed by Hinton and Nowlan in their 1987 study of the Baldwin effect. The task is an important one for cognitive science, as it demonstrates the power of learning as a local search technique in smoothing a fitness landscape that lacks gradient information. One aspect that has continued to foster interest in the problem is the observation of residual learning ability in simulated populations even after long periods of time. Effective evolutionary algorithms balance their search effort between broad exploration of the search space and in-depth exploitation of promising solutions already found. Issues discussed include the differential effects of rank and proportional selection, the tradeoff between migration of populations towards good solutions and maintenance of diversity, and the development of measures that illustrate how each selection algorithm affects the search process over generations. We show that both roulette wheel and tournament algorithms can be modified to appropriately balance search between exploration and exploitation, and effectively eliminate residual learning in this problem.