A multiple hill climbing approach to software module clustering

Automated software module clustering is important for maintenance of legacy systems written in a 'monolithic format' with inadequate module boundaries. Even where systems were originally designed with suitable module boundaries, structure tends to degrade as the system evolves, making re-modularization worthwhile. This paper focuses upon search-based approaches to the automated module clustering problem, where hitherto, the local search approach of hill climbing has been found to be most successful. In the paper we show that results from a set of multiple hill climbs can be combined to locate good 'building blocks' for subsequent searches. Building blocks are formed by identifying the common features in a selection of best hill climbs. This process reduces the search space, while simultaneously 'hard wiring' parts of the solution. The paper reports the results of an empirical study that show that the multiple hill climbing approach does indeed guide the search to higher peaks in subsequent executions. The paper also investigates the relationship between the improved results and the system size

Approaches to Active Tourism in the Urals and in Perm Krai

Located in the south of Ural, Perm Krai, apart from mineral resources and well-developed industry, can boast vast areas that lend themselves to active and qualified tourism, with the quality of an amateur sport. The development of these forms of tourism often requires large expenditure needed for adjusting the space to various types of activity. It also requires a correlation between a given character of the space and the preferred form of tourism, which often leads to environmental conflicts between the development of tourism and nature protection. The article presents the most important elements of the tourism potential in Perm Krai, as well as the sports tourism development perspectives in the context of real and potential environmental conflicts

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available.Comment: arXiv admin note: text overlap with arXiv:1101.5184 by other author

Phylogenetic Trees and Their Analysis

Determining the best possible evolutionary history, the lowest-cost phylogenetic tree, to fit a given set of taxa and character sequences using maximum parsimony is an active area of research due to its underlying importance in understanding biological processes. As several steps in this process are NP-Hard when using popular, biologically-motivated optimality criteria, significant amounts of resources are dedicated to both both heuristics and to making exact methods more computationally tractable. We examine both phylogenetic data and the structure of the search space in order to suggest methods to reduce the number of possible trees that must be examined to find an exact solution for any given set of taxa and associated character data. Our work on four related problems combines theoretical insight with empirical study to improve searching of the tree space. First, we show that there is a Hamiltonian path through tree space for the most common tree metrics, answering Bryant\u27s Challenge for the minimal such path. We next examine the topology of the search space under various metrics, showing that some metrics have local maxima and minima even with perfect data, while some others do not. We further characterize conditions for which sequences simulated under the Jukes-Cantor model of evolution yield well-behaved search spaces. Next, we reduce the search space needed for an exact solution by splitting the set of characters into mutually-incompatible subsets of compatible characters, building trees based on the perfect phylogenies implied by these sets, and then searching in the neighborhoods of these trees. We validate this work empirically. Finally, we compare two approaches to the generalized tree alignment problem, or GTAP: Sequence alignment followed by tree search vs. Direct Optimization, on both biological and simulated data

Morphology of the fertile leaves of the lomariopsidaceae, with special reference to the venation

Fertile pinnae of thirty-one species of the eight genera of Lomariopsidaceae studied have the lamina variously reduced, in some cases to narrow wings on either side of the midrib. The lamina is either broad, thin, and with the venation conspicuous on the surface, or narrow, fleshy, and with hidden venation. The mesophyll is undifferentiated and consists of thin-walled parenchyma which possesses collapsible walls in some species. Intercellular air spaces are inconspicuous in most species. The epidermal cells are usually thin-walled, chlorophyllous and dorsiventrally flattened. The midrib has two or three vascular strands which unite into one in the anterior half of the lamina. Distinct sclerenchyma tissue is absent: a few layers of thick-walled hypodermal cells occur in the midrib region in some. Venation of the fertile pinna is almost similar to that of the sterile pinnae in Bolbitis and Lomagramma (both reticulate), and in Egenolfia, Elaphoglossum and Thysanosoria (all free-veined). The fertile pinnae of Arthrobotrya, Lomariopsis and Teratophyllum usually possess a reticulate venation, though the sterile pinnae are free-veined. A set of special veins supplying the sporangia is found in addition to the 'normal' venation in many species except Elaphoglossum and Thysanosoria. The special venation is variously developed in the different species of each genus; it consists of a set of veins close to the lower epidermis of the lamina and connected to the 'normal' veins at intervals: in some cases the special veins form extensive reticulations independent of the 'normal' venation. The two sets of veins are at different planes, one above the other. The special venation is not connected directly to the midrib and often has a longitudinal vein running parallel to the midrib on either side. In all genera, except Thysanosoria which has discrete sori restricted to the vein tips, sporangia are acrostichoid in distribution. They are of the common leptosporangiate type. The sporangial stalk is slender and long in all, except Lomagramma and Lomariopsis in which it is short and stout. The stalk is three cells thick, the third row developed secondarily as a protrusion of the basal wall cell of the capsule in continuation of the stomium. Distinct paraphyses are absent, except in Arthrobotrya, Lomagramma and Teratophyllum. The spores are bilateral, monolete and ranging in size from 22 × 33 μ(Bolbitis spp., Elaphoglossum spp.) to 90 × 125 μ(Lomariopsis intermedia). The exine is smooth except in Lomagramma, Thysanosoria (both granulose) and Lomariopsis spp. (spinulose). Lomagramma and Thysanosoria are perine-less; all others are perinate, with the perine bearing characteristic reticulate ornamentation in all except Bolbitis and Elaphoglossum

The Value of Moderate Obsession: Insights from a New Model of Organizational Search

This study presents a new model of search on a “rugged landscape,” which employs modeling techniques from fractal geometry rather than the now-familiar NK modeling technique. In our simulations,firms search locally in a two-dimensional fitness landscape, choosing moves in a way that responds both to local payoff considerations and to a more global sense of opportunity represented by a firm-specific “preferred direction.” The latter concept provides a very simple device for introducing cognitive or motivational considerations into the formal account of search behavior, alongside payoff considerations. After describing the objectives and the structure of the model, we report a first experiment which explores how the ruggedness of the landscape affects the interplay of local payoff and cognitive considerations (preferred direction) in search. We show that an intermediate search strategy, combining the guidance of local search with a moderate level of non-local “obsession,” is distinctly advantageous in searching a rugged landscape. We also explore the effects of other considerations, including the objective validity of the preferred direction and the degree of dispersion of firm strategies. We conclude by noting available features of the model that are not exercised in this experiment. Given the inherent flexibility of the model, the range of questions that might potentially be explored is extremely large.Rugged Landscapes; Local Search; Cognition; Obsession; Fractal Geometry

Analysis of Touring Cyclists: Impacts, Needs and Opportunities for Montana

The purpose of this study was to understand the niche market of touring cyclists and to examine the potential for cycle tourism in the state of Montana. Results indicate a strong potential for cycle tourism in the state of Montana. Multi-day cyclists are generally satisfied while in Montana, but improvements are needed. Touring cyclists fit directly in line with Montana’s geotourism marketing brand pillars