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Title: Harmonic Order Parameters for Characterizing Complex Particle Morphologies |
Abstract: Order parameters based on spherical harmonics and Fourier coefficients already play a significant role in condensed matter research in the context of systems of spherical or point particles. Here, we extend these types of order parameter to more complex shapes, such as those encountered in nanoscale self-asse... |
Title: How I won the "Chess Ratings - Elo vs the Rest of the World" Competition |
Abstract: This article discusses in detail the rating system that won the kaggle competition "Chess Ratings: Elo vs the rest of the world". The competition provided a historical dataset of outcomes for chess games, and aimed to discover whether novel approaches can predict the outcomes of future games, more accurately ... |
Title: Pathways of Distinction Analysis: a new technique for multi-SNP analysis of GWAS data |
Abstract: Genome-wide association studies have become increasingly common due to advances in technology and have permitted the identification of differences in single nucleotide polymorphism (SNP) alleles that are associated with diseases. However, while typical GWAS analysis techniques treat markers individually, comp... |
Title: Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes |
Abstract: Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from which, with homophily as a guiding principle, inferences could be made about the underlying similarities. How... |
Title: Automatic Estimation of the Exposure to Lateral Collision in Signalized Intersections using Video Sensors |
Abstract: Intersections constitute one of the most dangerous elements in road systems. Traffic signals remain the most common way to control traffic at high-volume intersections and offer many opportunities to apply intelligent transportation systems to make traffic more efficient and safe. This paper describes an auto... |
Title: Input Parameters Optimization in Swarm DS-CDMA Multiuser Detectors |
Abstract: In this paper, the uplink direct sequence code division multiple access (DS-CDMA) multiuser detection problem (MuD) is studied into heuristic perspective, named particle swarm optimization (PSO). Regarding different system improvements for future technologies, such as high-order modulation and diversity explo... |
Title: Approximate tail probabilities of the maximum of a chi-square field on multi-dimensional lattice points and their applications to detection of loci interactions |
Abstract: Define a chi-square random field on a multi-dimensional lattice points index set with a direct-product covariance structure, and consider the distribution of the maximum of this random field. We provide two approximate formulas for the upper tail probability of the distribution based on nonlinear renewal theo... |
Title: Calibration Using Matrix Completion with Application to Ultrasound Tomography |
Abstract: We study the calibration process in circular ultrasound tomography devices where the sensor positions deviate from the circumference of a perfect circle. This problem arises in a variety of applications in signal processing ranging from breast imaging to sensor network localization. We introduce a novel metho... |
Title: Regularized Least-Mean-Square Algorithms |
Abstract: We consider adaptive system identification problems with convex constraints and propose a family of regularized Least-Mean-Square (LMS) algorithms. We show that with a properly selected regularization parameter the regularized LMS provably dominates its conventional counterpart in terms of mean square deviati... |
Title: Texture feature extraction in the spatial-frequency domain for content-based image retrieval |
Abstract: The advent of large scale multimedia databases has led to great challenges in content-based image retrieval (CBIR). Even though CBIR is considered an emerging field of research, however it constitutes a strong background for new methodologies and systems implementations. Therefore, many research contributions... |
Title: Exploring Grid Polygons Online |
Abstract: We investigate the exploration problem of a short-sighted mobile robot moving in an unknown cellular room. To explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified cell adjacent to the room's ou... |
Title: Matrix Insertion-Deletion Systems |
Abstract: In this article, we consider for the first time the operations of insertion and deletion working in a matrix controlled manner. We show that, similarly as in the case of context-free productions, the computational power is strictly increased when using a matrix control: computational completeness can be obtai... |
Title: Exploring Simple Triangular and Hexagonal Grid Polygons Online |
Abstract: We investigate the online exploration problem (aka covering) of a short-sighted mobile robot moving in an unknown cellular environment with hexagons and triangles as types of cells. To explore a cell, the robot must enter it. Once inside, the robot knows which of the 3 or 6 adjacent cells exist and which are ... |
Title: Computationally Efficient Modulation Level Classification Based on Probability Distribution Distance Functions |
Abstract: We present a novel modulation level classification (MLC) method based on probability distribution distance functions. The proposed method uses modified Kuiper and Kolmogorov-Smirnov distances to achieve low computational complexity and outperforms the state of the art methods based on cumulants and goodness-o... |
Title: Forward Smoothing using Sequential Monte Carlo |
Abstract: Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation of additive functionals recursively. Essentially, it is an online or forward-only implementation of a forward... |
Title: Ordinal Risk-Group Classification |
Abstract: Most classification methods provide either a prediction of class membership or an assessment of class membership probability. In the case of two-group classification the predicted probability can be described as "risk" of belonging to a "special" class . When the required output is a set of ordinal-risk group... |
Title: Ontology-based Queries over Cancer Data |
Abstract: The ever-increasing amount of data in biomedical research, and in cancer research in particular, needs to be managed to support efficient data access, exchange and integration. Existing software infrastructures, such caGrid, support access to distributed information annotated with a domain ontology. However, ... |
Title: Mining Multi-Level Frequent Itemsets under Constraints |
Abstract: Mining association rules is a task of data mining, which extracts knowledge in the form of significant implication relation of useful items (objects) from a database. Mining multilevel association rules uses concept hierarchies, also called taxonomies and defined as relations of type 'is-a' between objects, t... |
Title: Symmetry Breaking with Polynomial Delay |
Abstract: A conservative class of constraint satisfaction problems CSPs is a class for which membership is preserved under arbitrary domain reductions. Many well-known tractable classes of CSPs are conservative. It is well known that lexleader constraints may significantly reduce the number of solutions by excluding sy... |
Title: The Ethics of Robotics |
Abstract: The three laws of Robotics first appeared together in Isaac Asimov's story 'Runaround' after being mentioned in some form or the other in previous works by Asimov. These three laws commonly known as the three laws of robotics are the earliest forms of depiction for the needs of ethics in Robotics. In simplist... |
Title: Looking for plausibility |
Abstract: In the interpretation of experimental data, one is actually looking for plausible explanations. We look for a measure of plausibility, with which we can compare different possible explanations, and which can be combined when there are different sets of data. This is contrasted to the conventional measure for ... |
Title: Software Effort Estimation with Ridge Regression and Evolutionary Attribute Selection |
Abstract: Software cost estimation is one of the prerequisite managerial activities carried out at the software development initiation stages and also repeated throughout the whole software life-cycle so that amendments to the total cost are made. In software cost estimation typically, a selection of project attributes... |
Title: DD-EbA: An algorithm for determining the number of neighbors in cost estimation by analogy using distance distributions |
Abstract: Case Based Reasoning and particularly Estimation by Analogy, has been used in a number of problem-solving areas, such as cost estimation. Conventional methods, despite the lack of a sound criterion for choosing nearest projects, were based on estimation using a fixed and predetermined number of neighbors from... |
Title: Neural Network Influence in Group Technology: A Chronological Survey and Critical Analysis |
Abstract: This article portrays a chronological review of the influence of Artificial Neural Network in group technology applications in the vicinity of Cellular Manufacturing Systems. The research trend is identified and the evolvement is captured through a critical analysis of the literature accessible from the very ... |
Title: SAPFOCS: a metaheuristic based approach to part family formation problems in group technology |
Abstract: This article deals with Part family formation problem which is believed to be moderately complicated to be solved in polynomial time in the vicinity of Group Technology (GT). In the past literature researchers investigated that the part family formation techniques are principally based on production flow anal... |
Title: On Elementary Loops of Logic Programs |
Abstract: Using the notion of an elementary loop, Gebser and Schaub refined the theorem on loop formulas due to Lin and Zhao by considering loop formulas of elementary loops only. In this article, we reformulate their definition of an elementary loop, extend it to disjunctive programs, and study several properties of e... |
Title: Affine-invariant diffusion geometry for the analysis of deformable 3D shapes |
Abstract: We introduce an (equi-)affine invariant diffusion geometry by which surfaces that go through squeeze and shear transformations can still be properly analyzed. The definition of an affine invariant metric enables us to construct an invariant Laplacian from which local and global geometric structures are extrac... |
Title: Affine-invariant geodesic geometry of deformable 3D shapes |
Abstract: Natural objects can be subject to various transformations yet still preserve properties that we refer to as invariants. Here, we use definitions of affine invariant arclength for surfaces in R^3 in order to extend the set of existing non-rigid shape analysis tools. In fact, we show that by re-defining the sur... |
Title: Extending Binary Qualitative Direction Calculi with a Granular Distance Concept: Hidden Feature Attachment |
Abstract: In this paper we introduce a method for extending binary qualitative direction calculi with adjustable granularity like OPRAm or the star calculus with a granular distance concept. This method is similar to the concept of extending points with an internal reference direction to get oriented points which are t... |
Title: Annotated English |
Abstract: This document presents Annotated English, a system of diacritical symbols which turns English pronunciation into a precise and unambiguous process. The annotations are defined and located in such a way that the original English text is not altered (not even a letter), thus allowing for a consistent reading an... |
Title: Learning a Representation of a Believable Virtual Character's Environment with an Imitation Algorithm |
Abstract: In video games, virtual characters' decision systems often use a simplified representation of the world. To increase both their autonomy and believability we want those characters to be able to learn this representation from human players. We propose to use a model called growing neural gas to learn by imitat... |
Title: Large-scale interval and point estimates from an empirical Bayes extension of confidence posteriors |
Abstract: The proposed approach extends the confidence posterior distribution to the semi-parametric empirical Bayes setting. Whereas the Bayesian posterior is defined in terms of a prior distribution conditional on the observed data, the confidence posterior is defined such that the probability that the parameter valu... |
Title: Truncated Stochastic Approximation with Moving Bounds: Convergence |
Abstract: In this paper we propose a wide class of truncated stochastic approximation procedures with moving random bounds. While we believe that the proposed class of procedures will find its way to a wider range of applications, the main motivation is to accommodate applications to parametric statistical estimation t... |
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