OpenRaiser/Intern-Atlas huggingface dataset:
Kinetic $k$-Semi-Yao Graph and its Applications
Venue: arXiv cs.CG 2014
Year: 2014

This paper introduces a new proximity graph, called the $k$-Semi-Yao graph ($k$-SYG), on a set $P$ of points in $\mathbb{R}^d$, which is a supergraph of the $k$-nearest neighbor graph ($k$-NNG) of $P$. We provide a kinetic data structure (KDS) to maintain the $k$-SYG on moving points, where the trajectory of each point is a polynomial function whose degree is bounded by some constant. Our technique gives the first KDS for the theta graph (\ie, $1$-SYG) in $\mathbb{R}^d$. It generalizes and improves on previous work on maintaining the theta graph in $\mathbb{R}^2$. As an application, we use the kinetic $k$-SYG to provide the first KDS for maintenance of all the $k$-nearest neighbors in $\mathbb{R}^d$, for any $k\geq 1$. Previous works considered the $k=1$ case only. Our KDS for all the $1$-nearest neighbors is deterministic. The best previous KDS for all the $1$-nearest neighbors in $ \mathbb{R}^d$ is randomized. Our structure and analysis are simpler and improve on this work for the $k=1$ case. We also provide a KDS for all the $(1+ε)$-nearest neighbors, which in fact gives better performance than previous KDS's for maintenance of all the exact $1$-nearest neighbors. As another application, we present the first KDS for answering reverse $k$-nearest neighbor queries on moving points in $ \mathbb{R}^d$, for any $k\geq 1$.
Simulation leagues: Enabling replicable and robust investigation of complex robotic systems
Venue: arXiv cs.RO 2014
Year: 2014

Physically-realistic simulated environments are powerful platforms for enabling measurable, replicable and statistically-robust investigation of complex robotic systems. Such environments are epitomised by the RoboCup simulation leagues, which have been successfully utilised to conduct massively-parallel experiments in topics including: optimisation of bipedal locomotion, self-localisation from noisy perception data and planning complex multi-agent strategies without direct agent-to-agent communication. Many of these systems are later transferred to physical robots, making the simulation leagues invaluable well-beyond the scope of simulated soccer matches. In this study, we provide an overview of the RoboCup simulation leagues and describe their properties as they pertain to replicable and robust robotics research. To demonstrate their utility directly, we leverage the ability to run parallelised experiments to evaluate different competition formats (e.g. round robin) for the RoboCup 2D simulation league. Our results demonstrate that a previously-proposed hybrid format minimises fluctuations from 'true' (statistically-significant) team performance rankings within the time constraints of the RoboCup world finals. Our experimental analysis would be impossible with physical robots alone, and we encourage other researchers to explore the potential for enriching their experimental pipelines with simulated components, both to minimise experimental costsand enable others to replicate and expand upon their results in a hardware-independent manner.
Image Enhancement Using a Generalization of Homographic Function
Venue: arXiv cs.CV 2014
Year: 2014

This paper presents a new method of gray level image enhancement, based on point transforms. In order to define the transform function, it was used a generalization of the homographic function.
Jamming Based on an Ephemeral Key to Obtain Everlasting Security in Wireless Environments
Venue: arXiv cs.CR 2014
Year: 2014

Secure communication over a wiretap channel is considered in the disadvantaged wireless environment, where the eavesdropper channel is (possibly much) better than the main channel. We present a method to exploit inherent vulnerabilities of the eavesdropper's receiver to obtain everlasting secrecy. Based on an ephemeral cryptographic key pre-shared between the transmitter Alice and the intended recipient Bob, a random jamming signal is added to each symbol. Bob can subtract the jamming signal before recording the signal, while the eavesdropper Eve is forced to perform these non-commutative operations in the opposite order. Thus, information-theoretic secrecy can be obtained, hence achieving the goal of converting the vulnerable "cheap" cryptographic secret key bits into "valuable" information-theoretic (i.e. everlasting) secure bits. We evaluate the achievable secrecy rates for different settings, and show that, even when the eavesdropper has perfect access to the output of the transmitter (albeit through an imperfect analog-to-digital converter), the method can still achieve a positive secrecy rate. Next we consider a wideband system, where Alice and Bob perform frequency hopping in addition to adding the random jamming to the signal, and we show the utility of such an approach even in the face of substantial eavesdropper hardware capabilities.
Visual Concept Ontology for Image Annotations
Venue: arXiv cs.IR 2014
Year: 2014

In spite of the development of content-based data management, text-based searching remains the primary means of multimedia retrieval in many areas. Automatic creation of text metadata is thus a crucial tool for increasing the findability of multimedia objects. Search-based annotation tools try to provide content-descriptive keywords by exploiting web data, which are easily available but unstructured and noisy. Such data need to be analyzed with the help of semantic resources that provide knowledge about objects and relationships in a given domain. In this paper, we focus on the task of general-purpose image annotation and present the VCO, a new ontology of visual concepts developed as a part of image annotation framework. The ontology is linked with the WordNet lexical database, so the annotation tools can easily integrate information from both these resources.
Technical Report: Finger Replacement Schemes for RAKE Receivers in the Soft Handover Region with Multiple BSs over I.N.D. Fading Channels
Venue: arXiv cs.IT 2014
Year: 2014

A new finger replacement technique which is applicable for RAKE receivers in the soft handover (SHO) region has been proposed and studied in [1], [2] under the ideal assumption that the fading is both independent and identically distributed from path to path. To supplement our previous work, we present a general comprehensive framework for the performance assessment of the proposed finger replacement schemes operating over independent and non-identically distributed (i.n.d.) faded paths. To accomplish this object, we derive new closed-form expressions for the target key statistics which are composed of i.n.d. exponential random variables. With these new expressions, the performance analysis of various wireless communication systems over more practical environments can be possible.
A Robust and Efficient Detection Algorithm for The Photon-Counting Free-Space Optical System
Venue: arXiv cs.IT 2014
Year: 2014

We propose a Viterbi-type trellis-search algorithm to implement the FSO photon-counting sequence receiver proposed in [1] more efficiently and a selective-store strategy to overcome the error floor problem observed therein.
Design, Implementation and Simulation of a Cloud Computing System for Enhancing Real-time Video Services by using VANET and Onboard Navigation Systems
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we propose a design for novel and experimental cloud computing systems. The proposed system aims at enhancing computational, communicational and annalistic capabilities of road navigation services by merging several independent technologies, namely vision-based embedded navigation systems, prominent Cloud Computing Systems (CCSs) and Vehicular Ad-hoc NETwork (VANET). This work presents our initial investigations by describing the design of a global generic system. The designed system has been experimented with various scenarios of video-based road services. Moreover, the associated architecture has been implemented on a small-scale simulator of an in-vehicle embedded system. The implemented architecture has been experimented in the case of a simulated road service to aid the police agency. The goal of this service is to recognize and track searched individuals and vehicles in a real-time monitoring system remotely connected to moving cars. The presented work demonstrates the potential of our system for efficiently enhancing and diversifying real-time video services in road environments.
Improving Observability of Stochastic Complex Networks under the Supervision of Cognitive Dynamic Systems
Venue: arXiv cs.SY 2014
Year: 2014

Much has been said about observability in system theory and control; however, it has been recently that observability in complex networks has seriously attracted the attention of researchers. This paper examines the state-of-the-art and discusses some issues raised due to "complexity" and "stochasticity". These unresolved issues call for a new practical methodology. For stochastic systems, a degree of observability may be defined and the observability problem is not a binary (i.e., yes-no) question anymore. Here, we propose to employ a goal-seeking system to play a supervisory role in the network. Hence, improving the degree of observability would be a valid objective for the supervisory system. Towards this goal, the supervisor dynamically optimizes the observation process by reconfiguring the sensory parts in the network. A cognitive dynamic system is suggested as a proper choice for the supervisory system. In this framework, the network itself is viewed as the environment with which the cognitive dynamic system interacts. Computer experiments confirm the potential of the proposed approach for addressing some of the issues raised in networks due to complexity and stochasticity.
Iterative LMMSE Channel Estimation, Multiuser Detection, and Decoding via Spatial Coupling
Venue: arXiv cs.IT 2014
Year: 2014

Spatial coupling is utilized to improve the performance of iterative channel estimation, multiuser detection, and decoding for multiple-input multiple-input (MIMO) bit-interleaved coded modulation (BICM). Coupling is applied to both coding and BICM---the encoder uses a protograph-based spatially-coupled low-density parity-check (SC LDPC) code. Spatially and temporally coupled (STC) BICM is proposed to enable iterative channel estimation via coupling. Linear minimum mean-squared error (LMMSE) estimation is applied for both channel estimation and detection to reduce the complexity. Tractable density evolution (DE) equations are derived to analyze the convergence property of iterative receivers in the large-system limit, via a tool developed in statistical physics---replica method. The DE analysis implies that the STC BICM can improve the performance of iterative channel estimation especially for higher-order modulation. Numerical simulations show that the STC BICM can provide a significant gain of the performance at high signal-to-noise ratios for 64 quadrature amplitude modulation (QAM), as well as an improvement in the decoding threshold, compared to conventional BICM.
Exact recovery of non-uniform splines from the projection onto spaces of algebraic polynomials
Venue: arXiv cs.IT 2014
Year: 2014

In this work we consider the problem of recovering non-uniform splines from their projection onto spaces of algebraic polynomials. We show that under a certain Chebyshev-type separation condition on its knots, a spline whose inner-products with a polynomial basis and boundary conditions are known, can be recovered using Total Variation norm minimization. The proof of the uniqueness of the solution uses the method of `dual' interpolating polynomials and is based on \cite{SR}, where the theory was developed for trigonometric polynomials. We also show results for the multivariate case.
Discovering and Predicting Temporal Patterns of WiFi-interactive Social Populations
Venue: arXiv cs.SI 2014
Year: 2014

Extensive efforts have been devoted to characterizing the rich connectivity patterns among the nodes (components) of such complex networks (systems), and in the course of development of research in this area, people have been prompted to address on a fundamental question: How does the fascinating yet complex topological features of a network affect or determine the collective behavior and performance of the networked system? While elegant attempts to address this core issue have been made, for example, from the viewpoints of synchronization, epidemics, evolutionary cooperation, and the control of complex networks, theoretically or empirically, this widely concerned key question still remains open in the newly emergent field of network science. Such fruitful advances also push the desire to understand (mobile) social networks and characterize human social populations with the interdependent collective dynamics as well as the behavioral patterns. Nowadays, a great deal of digital technologies are unobtrusively embedded into the physical world of human daily activities, which offer unparalleled opportunities to explosively digitize human physical interactions, who is contacting with whom at what time. Such powerful technologies include the Bluetooth, the active Radio Frequency Identification (RFID) technology, wireless sensors and, more close to our interest in this paper, the WiFi technology. As a snapshot of the modern society, a university is in the coverage of WiFi signals, where the WiFi system records the digital access logs of the authorized WiFi users when they access the campus wireless services. Such WiFi access records, as the indirect proxy data, work as the effective proxy of a large-scale population's social interactions.
Distributed Decision Trees
Venue: arXiv cs.LG 2014
Year: 2014

Recently proposed budding tree is a decision tree algorithm in which every node is part internal node and part leaf. This allows representing every decision tree in a continuous parameter space, and therefore a budding tree can be jointly trained with backpropagation, like a neural network. Even though this continuity allows it to be used in hierarchical representation learning, the learned representations are local: Activation makes a soft selection among all root-to-leaf paths in a tree. In this work we extend the budding tree and propose the distributed tree where the children use different and independent splits and hence multiple paths in a tree can be traversed at the same time. This ability to combine multiple paths gives the power of a distributed representation, as in a traditional perceptron layer. We show that distributed trees perform comparably or better than budding and traditional hard trees on classification and regression tasks.
Py3DFreeHandUS: a library for voxel-array reconstruction using Ultrasonography and attitude sensors
Venue: arXiv cs.CV 2014
Year: 2014

In medical imaging, there is a growing interest to provide real-time images with good quality for large anatomical structures. To cope with this issue, we developed a library that allows to replace, for some specific clinical applications, more robust systems such as Computer Tomography (CT) and Magnetic Resonance Imaging (MRI). Our python library Py3DFreeHandUS is a package for processing data acquired simultaneously by ultra-sonographic systems (US) and marker-based optoelectronic systems. In particular, US data enables to visualize subcutaneous body structures, whereas the optoelectronic system is able to collect the 3D position in space for reflective objects, that are called markers. By combining these two measurement devices, it is possible to reconstruct the real 3D morphology of body structures such as muscles, for relevant clinical implications. In the present research work, the different steps which allow to obtain a relevant 3D data set as well as the procedures for calibrating the systems and for determining the quality of the reconstruction.
Existential Second-Order Logic Over Graphs: A Complete Complexity-Theoretic Classification
Venue: arXiv cs.LO 2014
Year: 2014

Descriptive complexity theory aims at inferring a problem's computational complexity from the syntactic complexity of its description. A cornerstone of this theory is Fagin's Theorem, by which a graph property is expressible in existential second-order logic (ESO logic) if, and only if, it is in NP. A natural question, from the theory's point of view, is which syntactic fragments of ESO logic also still characterize NP. Research on this question has culminated in a dichotomy result by Gottlob, Kolatis, and Schwentick: for each possible quantifier prefix of an ESO formula, the resulting prefix class either contains an NP-complete problem or is contained in P. However, the exact complexity of the prefix classes inside P remained elusive. In the present paper, we clear up the picture by showing that for each prefix class of ESO logic, its reduction closure under first-order reductions is either FO, L, NL, or NP. For undirected, self-loop-free graphs two containment results are especially challenging to prove: containment in L for the prefix $\exists R_1 \cdots \exists R_n \forall x \exists y$ and containment in FO for the prefix $\exists M \forall x \exists y$ for monadic $M$. The complex argument by Gottlob, Kolatis, and Schwentick concerning polynomial time needs to be carefully reexamined and either combined with the logspace version of Courcelle's Theorem or directly improved to first-order computations. A different challenge is posed by formulas with the prefix $\exists M \forall x\forall y$: We show that they express special constraint satisfaction problems that lie in L.
pyFRET: A Python Library for Single Molecule Fluorescence Data Analysis
Venue: arXiv cs.CE 2014
Year: 2014

Single molecule Förster resonance energy transfer (smFRET) is a powerful experimental technique for studying the properties of individual biological molecules in solution. However, as adoption of smFRET techniques becomes more widespread, the lack of available software, whether open source or commercial, for data analysis, is becoming a significant issue. Here, we present pyFRET, an open source Python package for the analysis of data from single-molecule fluorescence experiments from freely diffusing biomolecules. The package provides methods for the complete analysis of a smFRET dataset, from burst selection and denoising, through data visualisation and model fitting. We provide support for both continuous excitation and alternating laser excitation (ALEX) data analysis. pyFRET is available as a package downloadable from the Python Package Index (PyPI) under the open source three-clause BSD licence, together with links to extensive documentation and tutorials, including example usage and test data. Additional documentation including tutorials is hosted independently on ReadTheDocs. The code is available from the free hosting site Bitbucket. Through distribution of this software, we hope to lower the barrier for the adoption of smFRET experiments by other research groups and we encourage others to contribute modules for specific analysis needs.
Enhancing SfePy with Isogeometric Analysis
Venue: arXiv cs.MS 2014
Year: 2014

In the paper a recent enhancement to the open source package SfePy (Simple Finite Elements in Python, http://sfepy.org) is introduced, namely the addition of another numerical discretization scheme, the isogeometric analysis, to the original implementation based on the nowadays standard and well-established numerical solution technique, the finite element method. The isogeometric removes the need of the solution domain approximation by a piece-wise polygonal domain covered by the finite element mesh, and allows approximation of unknown fields with a higher smoothness then the finite element method, which can be advantageous in many applications. Basic numerical examples illustrating the implementation and use of the isogeometric analysis in SfePy are shown.
Towards a Consistent, Sound and Complete Conceptual Knowledge
Venue: arXiv cs.AI 2014
Year: 2014

Knowledge is only good if it is sound, consistent and complete. The same holds true for conceptual knowledge, which holds knowledge about concepts and its association. Conceptual knowledge no matter what format they are represented in, must be consistent, sound and complete in order to realise its practical use. This paper discusses consistency, soundness and completeness in the ambit of conceptual knowledge and the need to consider these factors as fundamental to the development of conceptual knowledge.
Simplified firefly algorithm for 2D image key-points search
Venue: arXiv cs.NE 2014
Year: 2014

In order to identify an object, human eyes firstly search the field of view for points or areas which have particular properties. These properties are used to recognise an image or an object. Then this process could be taken as a model to develop computer algorithms for images identification. This paper proposes the idea of applying the simplified firefly algorithm to search for key-areas in 2D images. For a set of input test images the proposed version of firefly algorithm has been examined. Research results are presented and discussed to show the efficiency of this evolutionary computation method.
A la Carte - Learning Fast Kernels
Venue: arXiv cs.LG 2014
Year: 2014

Kernel methods have great promise for learning rich statistical representations of large modern datasets. However, compared to neural networks, kernel methods have been perceived as lacking in scalability and flexibility. We introduce a family of fast, flexible, lightly parametrized and general purpose kernel learning methods, derived from Fastfood basis function expansions. We provide mechanisms to learn the properties of groups of spectral frequencies in these expansions, which require only O(mlogd) time and O(m) memory, for m basis functions and d input dimensions. We show that the proposed methods can learn a wide class of kernels, outperforming the alternatives in accuracy, speed, and memory consumption.
Cauchy Principal Component Analysis
Venue: arXiv cs.LG 2014
Year: 2014

Principal Component Analysis (PCA) has wide applications in machine learning, text mining and computer vision. Classical PCA based on a Gaussian noise model is fragile to noise of large magnitude. Laplace noise assumption based PCA methods cannot deal with dense noise effectively. In this paper, we propose Cauchy Principal Component Analysis (Cauchy PCA), a very simple yet effective PCA method which is robust to various types of noise. We utilize Cauchy distribution to model noise and derive Cauchy PCA under the maximum likelihood estimation (MLE) framework with low rank constraint. Our method can robustly estimate the low rank matrix regardless of whether noise is large or small, dense or sparse. We analyze the robustness of Cauchy PCA from a robust statistics view and present an efficient singular value projection optimization method. Experimental results on both simulated data and real applications demonstrate the robustness of Cauchy PCA to various noise patterns.