Evolutionary support vector machines and their application for classification

We propose a novel learning technique for classification as result of the hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the classification task as in support vector machines but use evolutionary algorithms to solve the optimization problem of determining the decision function. They can acquire the coefficients of the separating hyperplane, which is often not possible within classical techniques. More important, ESVMs obtain the coefficients directly from the evolutionary algorithm and can refer them at any point during a run. The concept is furthermore extended to handle large amounts of data, a problem frequently occurring e.g. in spam mail detection, one of our test cases. Evolutionary support vector machines are validated on this and three other real-world classification tasks; obtained results show the promise of this new technique

Multi-Phonon γ\gamma-Vibrational Bands and the Triaxial Projected Shell Model

We present a fully quantum-mechanical, microscopic, unified treatment of ground-state band and multi-phonon $\gamma$-vibrational bands using shell model diagonalization with the triaxial projected shell model. The results agree very well with data on the g- and $\gamma$-band spectra in $^{156-170}$Er, as well as with recently measured $4^+$ 2-phonon $\gamma$-bandhead energies in $^{166}$Er and $^{168}$Er. Multi-phonon $\gamma$-excitation energies are predicted.Comment: 4 pages, 4 figures, submitted to Phys. Lett.

Landscape evolution, post-LGM surface denudation and soil weathering processes from Dickinson Park mire, Wind River Range, Wyoming (USA)

At mid-latitudes, the transition from the Pleistocene to the Holocene was characterised by distinct and partially abrupt climatic changes. Also during the Holocene, climatic perturbations, with sometimes cold-dry conditions, have occurred. How land surfaces and soil development processes in high-mountains respond to these climatic oscillations is so far only poorly known. We traced the responses of surfaces in the alpine settings of the Wind River Range (Wyoming, US) by using a large mire as natural archive. This enabled us to reconstruct environmental conditions and ecosystem changes during the Holocene in this montane area. Although adjacent moraine deposits display 10Be exposure ages from the Last Glacial Maximum up to MIS16 or even older, the accessible sediment deposits covered only the Holocene (via radiocarbon dating). By applying a geoforensic approach and deriving sedimentation rates, major climatic signals were detected. A higher deposition (and consequently erosion) rate and thus a higher rate of geomorphic activity was measured for the known cold periods 9.4–10.2 ka BP, 4.2 ka BP and 2.5 ka BP. During the LIA, especially rapid aggradation of organic matter organic matter took place here. Rates of chemical weathering and soil formation seem to have been relatively low until about 5–6 ka BP but have since increased during the Late Holocene. This would fit previous observations of increasing moisture conditions after the mid-Holocene aridity period. In contrast to several other studies, no clear signs of major disturbances (erosion, weathering) during the 8.2 ka event could be observed. Together with the low levels of chemical weathering found here, we do not see any evidence that the climate was more humid during this period. Compared to previous findings, more humid conditions seemed to have returned earlier, i.e. about 5 kyr BP. In general, this landscape displayed a patchy pattern of reaction to environmental changes, as all events were not recorded in each mire profile

Cooperative Evolution of Rules for Classification

A new learning technique based on cooperative coevo-lution is proposed for tackling classification problems. For each possible outcome of the classification task, a popu-lation of if-then rules, all having that certain class as the conclusion part, is evolved. Cooperation between rules ap-pears in the evaluation stage, when complete sets of rules are formed with the purpose of measuring their classifica-tion accuracy on the training data. In the end of the evolu-tion process, a complete set of rules is extracted by selecting a rule from each of the final populations. It is then applied to the test data. Some interesting results were obtained from experiments conducted on Fisher’s iris benchmark problem. 1

Coevolution For Classification

A data mining field with daily, and sometimes even vital, practical applications, classification has been addressed by many powerful paradigms, among which evolutionary algorithms (EAs) play a successful role. Nevertheless, as evolutionary computation (EC) progresses, there appear new possibilities of developing simpler and yet robust classification techniques. The aim of this paper is hence to put forward a novel evolutionary classification framework which embodies two contradictory prototypes coming from the state-of-the-art field of coevolution and which has proven to be a viable alternative. Coevolution between individuals assumes two opposite interactions: cooperative and competitive. Analogously, coevolution for classification assumes two possible and opposed manners of solving the task. Within both approaches, the solution of a classification problem is regarded as a set of IFTHEN conjunctive rules in first order logic. As a consequence, learning will be driven either by the cooperation between rules towards a complete and accurate rule set or by the competition between rules and training samples in the direction of extensive and hard testing on each side. The paper is organized as follows. The next section introduces a general point of view upon classification. Section three brings an overview on coevolution: The cooperative and competitive archetypes are outlined and explained. Section four describes the proposed manner of approaching classification from the cooperative side, while section five presents the application of the competitive counterpart. Experiments on three data sets, two benchmark and one real-world, are depicted in section six and the paper closes with the concluding remarks

Dynamic Resource Provisioning in Grid Environments

Batch schedulers commonly used to manage access to parallel computing clusters are not typically configured to enable easy configuration of application-specific scheduling policies. In addition, their sophisticated scheduling algorithms can be relatively expensive to execute. Thus, for example, applications that require the rapid execution of many small tasks often do not perform well. It has been proposed that these problems be overcome by separating the two tasks of provisioning and scheduling. This paper focuses on resource provisioning, the various allocation and de-allocation policies, and how dynamic and adaptive provisioning can be in light of varying workloads. We couple the proposed dynamic resource provisioning (DRP) with an existing system, Falkon, which is used for the scheduling of tasks to the provisioned resources. We describe the DRP architecture and implementation, and present performance results for both microbenchmarks and applications. Microbenchmarks show that DRP can allocate resources on the order of 10s of seconds across multiple Grid sites and can reduce average queue wait times by up to 95 % (effectively yielding queue wait times within 3 % of ideal); furthermore, applications (executed by the Swift parallel programming system) reduce end-to-end run time of up to 90 % for large-scale astronomy and medical applications, relative to versions that execute tasks via separate scheduler submissions

Landscape evolution, post-LGM surface denudation and soil weathering processes from Dickinson Park mire, Wind River Range, Wyoming (USA)

At mid-latitudes, the transition from the Pleistocene to the Holocene was characterised by distinct and partially abrupt climatic changes. Also during the Holocene, climatic perturbations, with sometimes cold-dry conditions, have occurred. How land surfaces and soil development processes in high-mountains respond to these climatic oscillations is so far only poorly known. We traced the responses of surfaces in the alpine settings of the Wind River Range (Wyoming, US) by using a large mire as natural archive. This enabled us to reconstruct environmental conditions and ecosystem changes during the Holocene in this montane area. Although adjacent moraine deposits display 10Be exposure ages from the Last Glacial Maximum up to MIS16 or even older, the accessible sediment deposits covered only the Holocene (via radiocarbon dating). By applying a geoforensic approach and deriving sedimentation rates, major climatic signals were detected. A higher deposition (and consequently erosion) rate and thus a higher rate of geomorphic activity was measured for the known cold periods 9.4–10.2 ka BP, 4.2 ka BP and 2.5 ka BP. During the LIA, especially rapid aggradation of organic matter organic matter took place here. Rates of chemical weathering and soil formation seem to have been relatively low until about 5–6 ka BP but have since increased during the Late Holocene. This would fit previous observations of increasing moisture conditions after the mid-Holocene aridity period. In contrast to several other studies, no clear signs of major disturbances (erosion, weathering) during the 8.2 ka event could be observed. Together with the low levels of chemical weathering found here, we do not see any evidence that the climate was more humid during this period. Compared to previous findings, more humid conditions seemed to have returned earlier, i.e. about 5 kyr BP. In general, this landscape displayed a patchy pattern of reaction to environmental changes, as all events were not recorded in each mire profile.ISSN:0169-555xISSN:1872-695