7,605 research outputs found

    Inductive queries for a drug designing robot scientist

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    It is increasingly clear that machine learning algorithms need to be integrated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that are being performed. In this chapter, we summarise several key challenges in achieving this integration of machine learning and data mining algorithms in methods for the discovery of Quantitative Structure Activity Relationships (QSARs). We introduce the concept of a robot scientist, in which all steps of the discovery process are automated; we discuss the representation of molecular data such that knowledge discovery tools can analyse it, and we discuss the adaptation of machine learning and data mining algorithms to guide QSAR experiments

    Private Real Estate Investment Analysis within a One-Shot Decision Framework

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    Land development is a typical one-shot decision for private investors due to the huge investment expense and the fear of substantial loss. In this paper, a private real estate investment problem is analyzed within a one-shot decision framework, which is used for a situation where a decision is made only once. The one-shot decision framework involves two steps. The first is to identify which state of nature should be focused for each alternative. The second is to evaluate alternatives by using the focused states of nature. In a one-shot decision framework, the behavior of different types of private investors, such as normal, active, passive and more easily satisfied ones, are examined. The analysis provides insights into personal real estate investment and important policy implications in the regulation of urban land development.Private real estate investment; Possibility theory; One-shot decision; Focus points

    Technological and design aspects of the processing of composites and nanocomposites. Volume III

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    Processing of composites and nanocomposites materials constitutes nowadays an important area of research given the growing interest by these types of materials due to its singular properties, namely in what concerns technological and design aspects. This monography presents the developments taking place in the framework of the NEWEX project during the fourth year of its duration, which is a sequence of other two previous monographies. The main objective of the NEWEX project entitled “Investigation and development of a new generation of machines for the processing of composite and nanocomposites materials” is the exchange of researchers from the institutions participating in the project. Another important objective consists in develop permanent international and inter-sector collaboration between academic research centres (Lublin University of Technology, Technical University of Kosice, University of Minho) and industrial organizations (Zamak-Mercator LLC and SEZ-Krompachy a.s., Dirmeta UAB). The contents of this book reflects the work done within the NEWEX project. It starts by presenting the results obtained concerning new concepts for the extruder parts studied and the manufacturing of those extruder parts. Then, some approaches for modelling and optimizing and to study experimentally the process are described, which includes mixing analysis and monitoring. Finally, a practical and state-of-theart application of the extrusion is identified, namely 3D printing. It is expected that the nine chapters of this monography be useful to the industry of plastics processing and for scientific organisations dealing with technologies and processing of polymer composites and nanocomposites

    Combining link and content-based information in a Bayesian inference model for entity search

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    An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework. A flexible query model is supported capable to reason with the availability of simple semantics in querie

    Models of Speed Discrimination

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    The prime purpose of this project was to investigate various theoretical issues concerning the integration of information across visual space. To date, most of the research efforts in the study of the visual system seem to have been focused in two almost non-overlaping directions. One research focus has been the low level perception as studied by psychophysics. The other focus has been the study of high level vision exemplified by the study of object perception. Most of the effort in psychophysics has been devoted to the search for the fundamental "features" of perception. The general idea is that the most peripheral processes of the visual system decompose the input into features that are then used for classification and recognition. The experimental and theoretical focus has been on finding and describing these analyzers that decompose images into useful components. Various models are then compared to the physiological measurements performed on neurons in the sensory systems. In the study of higher level perception, the work has been focused on the representation of objects and on the connections between various physical effects and object perception. In this category we find the perception of 3D from a variety of physical measurements including motion, shading and other physical phenomena. With few exceptions, there seem to be very limited development of theories describing how the visual system might combine the output of the analyzers to form the representation of visual objects. Therefore, the processes underlying the integration of information over space represent critical aspects of vision system. The understanding of these processes will have implications on our expectations for the underlying physiological mechanisms, as well as for our models of the internal representation for visual percepts. In this project, we explored several mechanisms related to spatial summation, attention, and eye movements. The project comprised three components: 1. Modeling visual search for the detection of speed deviation. 2. Perception of moving objects. 3. Exploring the role of eye movements in various visual tasks
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