Lifelogging is a process of collecting rich source of information about daily life of people. In this paper, we introduce the problem of sentiment analysis in egocentric events focusing on the moments that compose the...
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Learning motor skills for robots is a hard task. In particular, a high number of degrees-of-freedom in the robot can pose serious challenges to existing reinforcement learning methods, since it leads to a high-dimensi...
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The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately ...
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Recognizing faces is a difficult problem due to the generally similar shape of faces combined with the considerable variability in images of the same face under different viewing conditions. In this paper we consider ...
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In this paper, we consider the Hamiltonian alternating path problem for graphs, multigraphs, and digraphs. We describe an approach to solve the problem. This approach is based on constructing logical models for the pr...
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In this paper, we consider the Hamiltonian alternating path problem for graphs, multigraphs, and digraphs. We describe an approach to solve the problem. This approach is based on constructing logical models for the problem. We use logical models for the Hamiltonian alternating path problem to solve the Hamiltonian path problem and the planning a typical working day for indoor service robots problem. Also, we use these models for Bennett's model of cytogenetics, automatic generation of recognition modules, and algebraic data.
Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA ...
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Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA and protein sequences. Structure comparison for RNA and for protein sequences has become a central computational problem bearing many challenging computerscience questions. The longest arc-preserving common subsequence problem has been introduced as a framework for studying the similarity of arc-annotated sequences. It is a sound and meaningful mathematical formalization of comparing the secondary structures of molecular sequences. In this paper, we consider two special cases of the longest arc-preserving common subsequence problem, efragment LAPCS (unlimited, plain), c-fragment LAPCS (unlimited, unlimited). In particular, we consider a parameterized version of the 1-fragment LAPCS (unlimited, plain) problem, parameterized by the length l of the desired subsequence. We show W[1]-completeness of the problem. Also, we describe an approach to solve c-fragment LAPCS (unlimited, unlimited). This approach is based on constructing logical models for the problem.
A large number of landmarks selection techniques has been proposed. However, finding optimal solutions requires to solve some hard problems. In this paper, we consider the P- minimum overlapping region decomposition p...
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A large number of landmarks selection techniques has been proposed. However, finding optimal solutions requires to solve some hard problems. In this paper, we consider the P- minimum overlapping region decomposition problem that was proposed for landmarks selection. This problem is NP-complete. We describe an approach to solve the problem optimally. This approach is based on an explicit reduction from the problem to the satisfiability problem. Also, we consider some greedy algorithms for solution of the problem.
作者：
Gorbenko, AnnaUral Federal University
Department of Intelligent Systems Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia
The problem of the longest common subsequence is a classical distance measure for strings. There have been several attempts to accommodate longest common subsequences along with some other distance measures. There are...
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The problem of the longest common subsequence is a classical distance measure for strings. There have been several attempts to accommodate longest common subsequences along with some other distance measures. There are a large number of different variants of the problem. In this paper, we consider the constrained longest common subsequence problem for two strings and arbitrary number of constraints. In particular, we consider an explicit reduction from the problem to the satisfiability problem and present experimental results for different satisfiability algorithms. It should be noted that different regularities in experimentally obtained data reveal important information about the underlying physical system. In this paper, we consider the problem of systematic monitoring of passenger flows. In particular, we use constrained longest common subsequences for tracking the image features.
A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. How...
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A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques.
作者：
Gorbenko, AnnaUral Federal University
Department of Intelligent Systems and Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia
Different regularities can be used to identify the sequence among other sequences. Regularities allow us to infer an information about the evolution of the sequence. Tandem repeats are the most frequent in the genomes...
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Different regularities can be used to identify the sequence among other sequences. Regularities allow us to infer an information about the evolution of the sequence. Tandem repeats are the most frequent in the genomes of eukaryotes. Extraction of regularities is a widely studied problem. However, searching for exact tandem repeats can be too restrictive. So, a natural extension of the repetition is to allow errors. In this paper, we consider the approximate period problem. In particular, we consider an explicit reduction from the approximate period problem to the satisfiability problem and present experimental results for different satisfiability algorithms. Also, we consider the approximate period problem for sequences of motor primitives of robots. In particular, we use the approximate period problem to obtain some meta-parameters that adapt the global motion behavior. We try to use such metaparameters for learning to generalize motor primitives to a different behavior by trial and error without re-learning the task.
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