87,655 research outputs found
Computer Aided Aroma Design. I. Molecular knowledge framework
Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and when their odour quality are definitely subjective whereas their odour intensity are partly subjective as stated in Rossitier’s review (1996). In part I, provided that classification rules like those presented in part II exist to assess the odour quality, the CAAD methodology presented proceeds with a multilevel approach matched by a versatile and novel molecular framework. It can distinguish the infinitesimal chemical structure differences, like in isomers, that are responsible for different odour quality and intensity. Besides, its chemical graph concepts are well suited for genetic algorithm sampling techniques used for an efficient screening of large molecules such as aroma. Finally, an input/output XML format based on the aggregation of CML and ThermoML enables to store the molecular classes but also any subjective or objective property values computed during the CAAD process
Probing-Based Preprocessing Techniques for Propositional Satisfiability
Preprocessing is an often used approach for solving hard instances of propositional satisfiability (SAT). Preprocessing can be used for reducing the number of variables and for drastically modifying the set of clauses, either by eliminating irrelevant clauses or by inferring new clauses. Over the years, a large number of formula manipulation techniques has been proposed, that in some situations have allowed solving instances not otherwise solvable with stateof -the-art SAT solvers. This paper proposes probing-based preprocessing, an integrated approach for preprocessing propositional formulas, that for the first time integrates in a single algorithm most of the existing formula manipulation techniques. Moreover, the new unified framework can be used to develop new techniques. Preliminary experimental results illustrate that probing-based preprocessing can be effectively used as a preprocessing tool in state-of-theart SAT solvers
Eligibility Propagation to Speed up Time Hopping for Reinforcement Learning
A mechanism called Eligibility Propagation is proposed to speed up the Time
Hopping technique used for faster Reinforcement Learning in simulations.
Eligibility Propagation provides for Time Hopping similar abilities to what
eligibility traces provide for conventional Reinforcement Learning. It
propagates values from one state to all of its temporal predecessors using a
state transitions graph. Experiments on a simulated biped crawling robot
confirm that Eligibility Propagation accelerates the learning process more than
3 times.Comment: 7 page
RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation
This paper proposes RUR53: an Unmanned Ground Vehicle able to autonomously
navigate through, identify, and reach areas of interest; and there recognize,
localize, and manipulate work tools to perform complex manipulation tasks. The
proposed contribution includes a modular software architecture where each
module solves specific sub-tasks and that can be easily enlarged to satisfy new
requirements. Included indoor and outdoor tests demonstrate the capability of
the proposed system to autonomously detect a target object (a panel) and
precisely dock in front of it while avoiding obstacles. They show it can
autonomously recognize and manipulate target work tools (i.e., wrenches and
valve stems) to accomplish complex tasks (i.e., use a wrench to rotate a valve
stem). A specific case study is described where the proposed modular
architecture lets easy switch to a semi-teleoperated mode. The paper
exhaustively describes description of both the hardware and software setup of
RUR53, its performance when tests at the 2017 Mohamed Bin Zayed International
Robotics Challenge, and the lessons we learned when participating at this
competition, where we ranked third in the Gran Challenge in collaboration with
the Czech Technical University in Prague, the University of Pennsylvania, and
the University of Lincoln (UK).Comment: This article has been accepted for publication in Advanced Robotics,
published by Taylor & Franci
Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval
We summarize math search engines and search interfaces produced by the
Document and Pattern Recognition Lab in recent years, and in particular the min
math search interface and the Tangent search engine. Source code for both
systems are publicly available. "The Masses" refers to our emphasis on creating
systems for mathematical non-experts, who may be looking to define unfamiliar
notation, or browse documents based on the visual appearance of formulae rather
than their mathematical semantics.Comment: Paper for Invited Talk at 2015 Conference on Intelligent Computer
Mathematics (July, Washington DC
Towards a Holistic Integration of Spreadsheets with Databases: A Scalable Storage Engine for Presentational Data Management
Spreadsheet software is the tool of choice for interactive ad-hoc data
management, with adoption by billions of users. However, spreadsheets are not
scalable, unlike database systems. On the other hand, database systems, while
highly scalable, do not support interactivity as a first-class primitive. We
are developing DataSpread, to holistically integrate spreadsheets as a
front-end interface with databases as a back-end datastore, providing
scalability to spreadsheets, and interactivity to databases, an integration we
term presentational data management (PDM). In this paper, we make a first step
towards this vision: developing a storage engine for PDM, studying how to
flexibly represent spreadsheet data within a database and how to support and
maintain access by position. We first conduct an extensive survey of
spreadsheet use to motivate our functional requirements for a storage engine
for PDM. We develop a natural set of mechanisms for flexibly representing
spreadsheet data and demonstrate that identifying the optimal representation is
NP-Hard; however, we develop an efficient approach to identify the optimal
representation from an important and intuitive subclass of representations. We
extend our mechanisms with positional access mechanisms that don't suffer from
cascading update issues, leading to constant time access and modification
performance. We evaluate these representations on a workload of typical
spreadsheets and spreadsheet operations, providing up to 20% reduction in
storage, and up to 50% reduction in formula evaluation time
Can Computer Algebra be Liberated from its Algebraic Yoke ?
So far, the scope of computer algebra has been needlessly restricted to exact
algebraic methods. Its possible extension to approximate analytical methods is
discussed. The entangled roles of functional analysis and symbolic programming,
especially the functional and transformational paradigms, are put forward. In
the future, algebraic algorithms could constitute the core of extended symbolic
manipulation systems including primitives for symbolic approximations.Comment: 8 pages, 2-column presentation, 2 figure
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