The vast majority of data mining algorithms require the setting of many input parameters. The dangers of working with parameter-laden algorithms are twofold. First, incorrect settings may cause an algorithm to fail in finding the true patterns. Second, a perhaps more insidious problem is that the algorithm may report spurious patterns that do not really exist, or greatly overestimate the significance of the reported patterns. This is especially likely when the user fails to understand the role of parameters in the data mining 100 E. Keogh et al.process. Data mining algorithms should have as few parameters as possible. A parameter-light algorithm would limit our ability to impose our prejudices, expectations, and presumptions on the problem at hand, and would let the data itself speak to us. In this work, we show that recent results in bioinformatics, learning, and computational theory hold great promise for a parameter-light data-mining paradigm. The results are strongly connected to Kolmogorov complexity theory. However, as a practical matter, they can be implemented using any off-the-shelf compression algorithm with the addition of just a dozen lines of code. We will show that this approach is competitive or superior to many of the state-of-the-art approaches in anomaly/interestingness detection, classification, and clustering with empirical tests on time series/DNA/text/XML/video datasets. As a further evidence of the advantages of our method, we will demonstrate its effectiveness to solve a real world classification problem in recommending printing services and products.
The late Mesozoic through early Cenozoic is an interval of significant biologic turnover and ecologic reorganization within marine assemblages, but the timing and causes of these changes remain poorly understood. Here, we quantify the pattern and timing of shifts in the diversity (richness and evenness) and ecology of local (i.e., sample level) mollusk-dominated assemblages during this critical interval using field-collected and published data sets from the U.S. Gulf Coastal Plain. We test whether the biologic and ecologic patterns observed primarily at the global level during this time are also expressed at the local level, and whether the end-Cretaceous (K/Pg) mass extinction and recovery moderated these trends. To explore whether environment had any effect on these patterns, we examine data from shallow subtidal and offshore settings.Assemblages from both settings recovered to pre-extinction diversity levels rapidly, in less than 7 million years. Following initial recovery, diversity remained unchanged in both settings. The trajectory of ecological restructuring was distinct for each setting in the wake of the K/Pg extinction. In offshore assemblages, the abundance and number of predatory carnivorous taxa dramatically increased, and surficial sessile suspension feeders were replaced by more active suspension feeders. In contrast, shallow subtidal assemblages did not experience ecological reorganization following the K/Pg extinction. The distinct ecological patterns displayed in each environment follow onshore-offshore patterns of innovation, whereby evolutionary novelties first appear in onshore settings relative to offshore habitats. Increased predation pressure may explain the significant ecological restructuring of offshore assemblages, whereby the explosive radiation of predators drove changes in their prey. Habitat-specific ecological restructuring, and its occurrence solely during the recovery interval, implies that disturbance and incumbency were also key in mediating these ecological changes.
The concept of coordinated stasis, manifest as a pattern of long intervals of concurrent taxonomic and ecologic persistence separated by comparatively abrupt periods of biotic change, has been challenged in recent studies that claim a lack of prolonged persistence of taxa and associations. A key problem has been the difficulty of distinguishing faunal change owing to localized, short-term environmental fluctuation or patchiness from that indicating regionally pervasive, long-term evolutionary or ecological change. Here, we use an extensive database from the Middle Devonian Hamilton Group of the Appalachian Basin to test for taxonomic and ecologic persistence within this ecological-evolutionary subunit, a succession of purported relative stability. Replicate samples collected from many localities and stratigraphic horizons over a wide geographic area allow us to address the effects of small-scale environmental variation and localized faunal patchiness while exploring basin-scale variation in faunal composition within and between the formations of the Hamilton Group.Observed stratigraphic distributions of fossils are consistent with a scenario in which all taxa are present from bottom to top of the Hamilton Group, and absences result only from sampling failure. Although small-scale variation in faunal composition indeed does occur, there is no more variation among formations than occurs within them. Assemblages from different formations, whether they are defined by taxonomic or ecologic composition, are statistically indistinguishable according to several independent metrics, including ANOSIM and a maximum likelihood estimation that evaluates stratigraphic turnover using Bayesian “Information Criterion.” Simulated data sets indicate that test results are most consistent with species-level extinction of 2.6% per Myr within the Hamilton Group, far lower than the Givetian rate of 11.5% per Myr generic extinction derived from a global database. Such faunal persistence over the ~5.5 Myr encompassed by this unit is consistent with the pattern of coordinated stasis. Earlier studies showing greater amounts of temporal turnover in Hamilton Group faunas are likely influenced by their smaller geographic scale of analysis, suggesting that regional studies done elsewhere may yield similar results.
Nanotechnology is the new industrial revolution of the 21st Century as the various processes lead to radical improvements in medicine, manufacturing, energy production, land remediation, information technology and many other everyday products and applications. With this revolution however, there are undoubted concerns for health, safety and the environment which arise from the unique nature of materials and processes at the nanometre scale.The in vitro assays used in the screening strategy are all validated, internationally accepted protocols and provide a useful indication of potential toxicity of a chemical as a result of effects on various toxicological endpoints such as local site of contact (dermal) irritation, general cytotoxicity and mutagenicity.The initial in vitro screening strategy described in this paper to investigate the potential health implications, if any, which may arise following exposure to one specific application of nanoparticulate cerium oxide used as a diesel fuel borne catalyst, reflects a precautionary approach and the results will inform judgement on how best to proceed to ensure safe use.
The OpenHaptics™ toolkit is a haptics library developed by SensAble Technologies, Inc®. It is patterned after the OpenGL® API, making it familiar to graphics programmers and facilitating integration with existing OpenGL applications. OpenHaptics is composed of two layers: Haptic Device API (HDAPI) and Haptic Library API (HLAPI). HDAPI provides low-level access to the haptic device. HLAPI provides advanced haptic rendering capability. HDAPI and HLAPI are built on top of the PHANTOM® Device Drivers (PDD), the device drivers for PHANTOM series of haptic devices.
In light of the ongoing debate over the value of the equity risk premium, its increasing use in the regulatory setting, and the impact of dividend imputation on the premium, this paper presents a timely new look at the historical equity risk premium in Australia, and provides an improved understanding of the historical record. We document concerns about data quality that become increasingly important the further back in time one looks. In particular, there are sufficient question marks over the quality of data prior to 1958 to warrant any estimates based thereon to be treated with caution. Accordingly, we present a new set of estimates of the historical equity risk premium corresponding to periods of increasing data quality but of decreasing sample size. Relative to bonds (bills), the equity premium has averaged 6.3 per cent (6.8 per cent) per annum over 1958-2005, which is a period of relatively good data quality. Together with other results in the paper, the findings reveal a historical estimate that is substantially less than widely cited historical studies would otherwise indicate. We reconcile prior evidence through documenting a dividend adjustment that has typically been overlooked. We also provide estimates that incorporate an adjustment for imputation credits. Copyright (c) The Authors.
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