Highly comparative feature-based time-series classification

A highly comparative, feature-based approach to time series classification is introduced that uses an extensive database of algorithms to extract thousands of interpretable features from time series. These features are derived from across the scientific time-series analysis literature, and include summaries of time series in terms of their correlation structure, distribution, entropy, stationarity, scaling properties, and fits to a range of time-series models. After computing thousands of features for each time series in a training set, those that are most informative of the class structure are selected using greedy forward feature selection with a linear classifier. The resulting feature-based classifiers automatically learn the differences between classes using a reduced number of time-series properties, and circumvent the need to calculate distances between time series. Representing time series in this way results in orders of magnitude of dimensionality reduction, allowing the method to perform well on very large datasets containing long time series or time series of different lengths. For many of the datasets studied, classification performance exceeded that of conventional instance-based classifiers, including one nearest neighbor classifiers using Euclidean distances and dynamic time warping and, most importantly, the features selected provide an understanding of the properties of the dataset, insight that can guide further scientific investigation

Semiconductor devices and methods

A method of forming a semiconductor device includes the following steps: providing a plurality of semiconductor layers; providing means for coupling signals to and/or from layers of the device; providing a quantum well disposed between adjacent layers of the device; and providing a layer of quantum dots disposed in one of the adjacent layers, and spaced from the quantum well, whereby carriers can tunnel in either direction between the quantum well and the quantum dots.Board of Regents, University of Texas Syste

The Implicit Value of Irrigation Through Parcel Level Hedonic Price Modeling

This paper relies on data associated 2,100 agricultural land sale transactions across two major Nebraska Watersheds (the Republican and Central Platte) over the 2000 to 2008 time period. The sales were spatially referenced (digitized into a GIS) in order to quantify and geo-spatially predict and map the implicit values of irrigation through the use of hedonic price modeling. Marginal implicit prices vary substantially across subwatersheds (natural resource districts), and the contribution of irrigation to sale prices is directly related to the extent to dependency of production agriculture on irrigation. This information is now currently being used to evaluate the economic efficiency of recent irrigation retirement programs and to help ensure that current and future retirement programs are cost-effective through targeting that retires irrigation land with the greatest hydrologic impact on water resources for the lowest cost.Farm Management, Production Economics, Resource /Energy Economics and Policy,

Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information

The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation

Sequence effects in categorization of simple perceptual stimuli

Categorization research typically assumes that the cognitive system has access to a (more or less noisy) representation of the absolute magnitudes of the properties of stimuli and that this information is used in reaching a categorization decision. However, research on identification of simple perceptual stimuli suggests that people have very poor representations of absolute magnitude information and that judgments about absolute magnitude are strongly influenced by preceding material. The experiments presented here investigate such sequence effects in categorization tasks. Strong sequence effects were found. Classification of a borderline stimulus was more accurate when preceded by a distant member of the opposite category than by a distant member of the same category. It is argued that this category contrast effect cannot be accounted for by extant exemplar or decision-bound models of categorization. The effect suggests the use of relative magnitude information in categorization. A memory and contrast model illustrates how relative magnitude information may be used in categorization

Information Retention by Stringy Black Holes

Building upon our previous work on two-dimensional stringy black holes and its extension to spherically-symmetric four-dimensional stringy black holes, we show how the latter retain information. A key r\^ole is played by an infinite-dimensional $W_\infty$ symmetry that preserves the area of an isolated black-hole horizon and hence its entropy. The exactly-marginal conformal world-sheet operator representing a massless stringy particle interacting with the black hole necessarily includes a contribution from $W_\infty$ generators in its vertex function. This admixture manifests the transfer of information between the string black hole and external particles. We discuss different manifestations of $W_\infty$ symmetry in black-hole physics and the connections between them.Comment: 29 pages, 18th International Conference From the Planck Scale to the Electroweak Scale, 25-29 May 2015, Ioannina, Greece; Updated version, contains a new subsection 5.4 on the relationship between Hawking radiation and W-infinity symmetries with additional reference

Bryophytes of Uganda : 1., BBS Tropical Bryology Group expeditions, 1996-1998 ; introduction and collecting sites

The British Bryological Society Tropical Bryology Group (TBG) undertook three expeditions to Uganda, in Jan-Feb 1996, Jan-Feb 1997 and June-Jul 1998. Collections were made from 134 sites, mainly from national parks and forest reserves in western and southern Uganda