OpenRaiser/Intern-Atlas huggingface dataset:
Composing and Factoring Generalized Green's Operators and Ordinary Boundary Problems
Venue: arXiv cs.SC 2013
Year: 2013

We consider solution operators of linear ordinary boundary problems with "too many" boundary conditions, which are not always solvable. These generalized Green's operators are a certain kind of generalized inverses of differential operators. We answer the question when the product of two generalized Green's operators is again a generalized Green's operator for the product of the corresponding differential operators and which boundary problem it solves. Moreover, we show that---provided a factorization of the underlying differential operator---a generalized boundary problem can be factored into lower order problems corresponding to a factorization of the respective Green's operators. We illustrate our results by examples using the Maple package IntDiffOp, where the presented algorithms are implemented.
On the Capacity of Multiple Access and Broadcast Fading Channels with Full Channel State Information at Low SNR
Venue: arXiv cs.IT 2013
Year: 2013

We study the throughput capacity region of the Gaussian multi-access (MAC) fading channel with perfect channel state information (CSI) at the receiver and at the transmitters, at low power regime. We show that it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points. More specifically, we show that at low power regime, the boundary surface of the capacity region shrinks to a single point corresponding to the sum rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Inspired by this result, we propose an on-off scheme, compute its achievable rate, and show that this scheme achieves single user capacity bounds of the MAC channel for a wide class of fading channels at asymptotically low power regime. We argue that this class of fading encompasses all known wireless channels for which the capacity region of the MAC channel has even a simpler expression in terms of users' average power constraints only. Using the duality of Gaussian MAC and broadcast channels (BC), we deduce a simple characterization of the BC capacity region at low power regime and show that for a class of fading channels (including Rayleigh fading), time-sharing is asymptotically optimal.
Translating Specifications in a Dependently Typed Lambda Calculus into a Predicate Logic Form
Venue: arXiv cs.LO 2013
Year: 2013

Dependently typed lambda calculi such as the Edinburgh Logical Framework (LF) are a popular means for encoding rule-based specifications concerning formal syntactic objects. In these frameworks, relations over terms representing formal objects are naturally captured by making use of the dependent structure of types. We consider here the meaning-preserving translation of specifications written in this style into a predicate logic over simply typed λ-terms. Such a translation can provide the basis for efficient implementation and sophisticated capabilities for reasoning about specifications. We start with a previously described translation of LF specifications to formulas in the logic of higher-order hereditary Harrop (hohh) formulas. We show how this translation can be improved by recognizing and eliminating redundant type checking information contained in it. This benefits both the clarity of translated formulas, and reduces the effort which must be spent on type checking during execution. To allow this translation to be used to execute LF specifications, we describe an inverse transformation from hohh terms to LF expressions; thus computations can be carried out using the translated form and the results can then be exported back into LF. Execution based on LF specifications may also involve some forms of type reconstruction. We discuss the possibility of supporting such a capability using the translation under some reasonable restrictions on the structure of specifications.
An optimally concentrated Gabor transform for localized time-frequency components
Venue: arXiv cs.NA 2013
Year: 2013

Gabor analysis is one of the most common instances of time-frequency signal analysis. Choosing a suitable window for the Gabor transform of a signal is often a challenge for practical applications, in particular in audio signal processing. Many time-frequency (TF) patterns of different shapes may be present in a signal and they can not all be sparsely represented in the same spectrogram. We propose several algorithms, which provide optimal windows for a user-selected TF pattern with respect to different concentration criteria. We base our optimization algorithm on $l^p$-norms as measure of TF spreading. For a given number of sampling points in the TF plane we also propose optimal lattices to be used with the obtained windows. We illustrate the potentiality of the method on selected numerical examples.
Speech animation using electromagnetic articulography as motion capture data
Venue: arXiv cs.HC 2013
Year: 2013

Electromagnetic articulography (EMA) captures the position and orientation of a number of markers, attached to the articulators, during speech. As such, it performs the same function for speech that conventional motion capture does for full-body movements acquired with optical modalities, a long-time staple technique of the animation industry. In this paper, EMA data is processed from a motion-capture perspective and applied to the visualization of an existing multimodal corpus of articulatory data, creating a kinematic 3D model of the tongue and teeth by adapting a conventional motion capture based animation paradigm. This is accomplished using off-the-shelf, open-source software. Such an animated model can then be easily integrated into multimedia applications as a digital asset, allowing the analysis of speech production in an intuitive and accessible manner. The processing of the EMA data, its co-registration with 3D data from vocal tract magnetic resonance imaging (MRI) and dental scans, and the modeling workflow are presented in detail, and several issues discussed.
A Meta-heuristically Approach of the Spatial Assignment Problem of Human Resources in Multi-sites Enterprise
Venue: arXiv cs.AI 2013
Year: 2013

The aim of this work is to present a meta-heuristically approach of the spatial assignment problem of human resources in multi-sites enterprise. Usually, this problem consists to move employees from one site to another based on one or more criteria. Our goal in this new approach is to improve the quality of service and performance of all sites with maximizing an objective function under some managers imposed constraints. The formulation presented here of this problem coincides perfectly with a Combinatorial Optimization Problem (COP) which is in the most cases NP-hard to solve optimally. To avoid this difficulty, we have opted to use a meta-heuristic popular method, which is the genetic algorithm, to solve this problem in concrete cases. The results obtained have shown the effectiveness of our approach, which remains until now very costly in time. But the reduction of the time can be obtained by different ways that we plan to do in the next work.
Thread-Based Obfuscation through Control-Flow Mangling
Venue: arXiv cs.CR 2013
Year: 2013

The increasing use of cloud computing and remote execution have made program security especially important. Code obfuscation has been proposed to make the understanding of programs more complicated to attackers. In this paper, we exploit multi-core processing to substantially increase the complexity of programs, making reverse engineering more complicated. We propose a novel method that automatically partitions any serial thread into an arbitrary number of parallel threads, at the basic-block level. The method generates new control-flow graphs, preserving the blocks' serial successor relations and guaranteeing that one basic-block is active at a time using guards. The method generates m^n different combinations for m threads and n basic-blocks, significantly complicating the execution state. We provide a correctness proof for the algorithm and implement the algorithm in the LLVM compilation framework.
Structure-preserving color transformations using Laplacian commutativity
Venue: arXiv cs.CV 2013
Year: 2013

Mappings between color spaces are ubiquitous in image processing problems such as gamut mapping, decolorization, and image optimization for color-blind people. Simple color transformations often result in information loss and ambiguities (for example, when mapping from RGB to grayscale), and one wishes to find an image-specific transformation that would preserve as much as possible the structure of the original image in the target color space. In this paper, we propose Laplacian colormaps, a generic framework for structure-preserving color transformations between images. We use the image Laplacian to capture the structural information, and show that if the color transformation between two images preserves the structure, the respective Laplacians have similar eigenvectors, or in other words, are approximately jointly diagonalizable. Employing the relation between joint diagonalizability and commutativity of matrices, we use Laplacians commutativity as a criterion of color mapping quality and minimize it w.r.t. the parameters of a color transformation to achieve optimal structure preservation. We show numerous applications of our approach, including color-to-gray conversion, gamut mapping, multispectral image fusion, and image optimization for color deficient viewers.
A Technique for Efficiently Managing SRAM-NVM Hybrid Cache
Venue: arXiv cs.AR 2013
Year: 2013

In this paper, we present a SRAM-PCM hybrid cache design, along with a cache replacement policy, named dead fast block (DFB) to manage the hybrid cache. This design aims to leverage the best features of both SRAM and PCM devices. Compared to a PCM-only cache, the hybrid cache with DFB policy provides superior results on all relevant evaluation metrics, viz. cache lifetime, performance and energy efficiency. Also, use of DFB policy for managing the hybrid cache provides better results compared to LRU replacement policy on all the evaluation metrics.
A systematic comparison of supervised classifiers
Venue: arXiv cs.LG 2013
Year: 2013

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration.
A Linear-Time and Space Algorithm for Optimal Traffic Signal Durations at an Intersection
Venue: arXiv cs.DS 2013
Year: 2013

Finding an optimal solution of signal traffic control durations is a computationally intensive task. It is typically O(T3) in time, and O(T2) in space, where T is the length of the control interval in discrete time steps. In this paper, we propose a linear time and space algorithm for the same problem. The algorithm provides for an efficient dynamic programming formulation of the state space, the prunes non-optimal states, early on. The paper proves the correctness of the algorithm and provides an initial experimental validation.
Non-linear Task-Space Disturbance Observer for Position Regulation of Redundant Robot Arms against Perturbations in 3D Environments
Venue: arXiv cs.RO 2013
Year: 2013

Many day-to-day activities require the dexterous manipulation of a redundant humanoid arm in complex 3D environments. However, position regulation of such robot arm systems becomes very difficult in presence of non-linear uncertainties in the system. Also, perturbations exist due to various unwanted interactions with obstacles for clumsy environments in which obstacle avoidance is not possible, and this makes position regulation even more difficult. This report proposes a non-linear task-space disturbance observer by virtue of which position regulation of such robotic systems can be achieved in spite of such perturbations and uncertainties. Simulations are conducted using a 7-DOF redundant robot arm system to show the effectiveness of the proposed method. These results are then compared with the case of a conventional mass-damper based task-space disturbance observer to show the enhancement in performance using the developed concept. This proposed method is then applied to a controller which exhibits human-like motion characteristics for reaching a target. Arbitrary perturbations in the form of interactions with obstacles are introduced in its path. Results show that the robot end-effector successfully continues to move in its path of a human-like quasi-straight trajectory even if the joint trajectories deviated by a considerable amount due to the perturbations. These results are also compared with that of the unperturbed motion of the robot which further prove the significance of the developed scheme.
An Adaptive Amoeba Algorithm for Shortest Path Tree Computation in Dynamic Graphs
Venue: arXiv cs.NE 2013
Year: 2013

This paper presents an adaptive amoeba algorithm to address the shortest path tree (SPT) problem in dynamic graphs. In dynamic graphs, the edge weight updates consists of three categories: edge weight increases, edge weight decreases, the mixture of them. Existing work on this problem solve this issue through analyzing the nodes influenced by the edge weight updates and recompute these affected vertices. However, when the network becomes big, the process will become complex. The proposed method can overcome the disadvantages of the existing approaches. The most important feature of this algorithm is its adaptivity. When the edge weight changes, the proposed algorithm can recognize the affected vertices and reconstruct them spontaneously. To evaluate the proposed adaptive amoeba algorithm, we compare it with the Label Setting algorithm and Bellman-Ford algorithm. The comparison results demonstrate the effectiveness of the proposed method.
Accurate curve fits of IAPWS data for high-pressure, high-temperature single-phase liquid water based on the stiffened gas equation of state
Venue: arXiv cs.CE 2013
Year: 2013

We present a series of optimal (in the sense of least-squares) curve fits for the stiffened gas equation of state for single-phase liquid water. At high pressures and (subcritical) temperatures, the parameters produced by these curve fits are found to have very small relative errors: less than $1\%$ in the pressure model, and less than $2\%$ in the temperature model. At low pressures and temperatures, especially near the liquid-vapor transition line, the error in the curve fits increases rapidly. The smallest pressure value for which curve fits are reported in the present work is 25 MPa, high enough to ensure that the fluid remains a single-phase liquid up to the maximum subcritical temperature of approximately 647K.
Observation of large-scale multi-agent based simulations
Venue: arXiv cs.MA 2013
Year: 2013

The computational cost of large-scale multi-agent based simulations (MABS) can be extremely important, especially if simulations have to be monitored for validation purposes. In this paper, two methods, based on self-observation and statistical survey theory, are introduced in order to optimize the computation of observations in MABS. An empirical comparison of the computational cost of these methods is performed on a toy problem.
Resource Allocation for Network-Integrated Device-to-Device Communications Using Smart Relays
Venue: arXiv cs.NI 2013
Year: 2013

With increasing number of autonomous heterogeneous devices in future mobile networks, an efficient resource allocation scheme is required to maximize network throughput and achieve higher spectral efficiency. In this paper, performance of network-integrated device-to-device (D2D) communication is investigated where D2D traffic is carried through relay nodes. An optimization problem is formulated for allocating radio resources to maximize end-to-end rate as well as conversing QoS requirements for cellular and D2D user equipment under total power constraint. Numerical results show that there is a distance threshold beyond which relay-assisted D2D communication significantly improves network performance when compared to direct communication between D2D peers.
FiWi Access Networks Based on Next-Generation PON and Gigabit-Class WLAN Technologies: A Capacity and Delay Analysis (Extended Version)
Venue: arXiv cs.IT 2013
Year: 2013

Current Gigabit-class passive optical networks (PONs) evolve into next-generation PONs, whereby high-speed 10+ Gb/s time division multiplexing (TDM) and long-reach wavelength-broadcasting/routing wavelength division multiplexing (WDM) PONs are promising near-term candidates. On the other hand, next-generation wireless local area networks (WLANs) based on frame aggregation techniques will leverage physical layer enhancements, giving rise to Gigabit-class very high throughput (VHT) WLANs. In this paper, we develop an analytical framework for evaluating the capacity and delay performance of a wide range of routing algorithms in converged fiber-wireless (FiWi) broadband access networks based on different next-generation PONs and a Gigabit-class multi-radio multi-channel WLAN-mesh front-end. Our framework is very flexible and incorporates arbitrary frame size distributions, traffic matrices, optical/wireless propagation delays, data rates, and fiber faults. We verify the accuracy of our probabilistic analysis by means of simulation for the wireless and wireless-optical-wireless operation modes of various FiWi network architectures under peer-to-peer, upstream, uniform, and nonuniform traffic scenarios. The results indicate that our proposed optimized FiWi routing algorithm (OFRA) outperforms minimum (wireless) hop and delay routing in terms of throughput for balanced and unbalanced traffic loads, at the expense of a slightly increased mean delay at small to medium traffic loads.
Motivation for hyperlink creation using inter-page relationships
Venue: arXiv cs.DL 2013
Year: 2013

Using raw hyperlink counts for webometrics research has been shown to be unreliable and researchers have looked for alternatives. One alternative is classifying hyperlinks in a website based on the motivation behind the hyperlink creation. The method used for this type of classification involves manually visiting a webpage and then classifying individual links on the webpage. This is time consuming, making it infeasible for large scale studies. This paper speeds up the classification of hyperlinks in UK academic websites by using a machine learning technique, decision tree induction, to group web pages found in UK academic websites into one of eight categories and then infer the motivation for the creation of a hyperlink in a webpage based on the linking pattern of the category the webpage belongs to.
Using Robust PCA to estimate regional characteristics of language use from geo-tagged Twitter messages
Venue: arXiv cs.CL 2013
Year: 2013

Principal component analysis (PCA) and related techniques have been successfully employed in natural language processing. Text mining applications in the age of the online social media (OSM) face new challenges due to properties specific to these use cases (e.g. spelling issues specific to texts posted by users, the presence of spammers and bots, service announcements, etc.). In this paper, we employ a Robust PCA technique to separate typical outliers and highly localized topics from the low-dimensional structure present in language use in online social networks. Our focus is on identifying geospatial features among the messages posted by the users of the Twitter microblogging service. Using a dataset which consists of over 200 million geolocated tweets collected over the course of a year, we investigate whether the information present in word usage frequencies can be used to identify regional features of language use and topics of interest. Using the PCA pursuit method, we are able to identify important low-dimensional features, which constitute smoothly varying functions of the geographic location.
Toward a New Approach for Modeling Dependability of Data Warehouse System
Venue: arXiv cs.DB 2013
Year: 2013

The sustainability of any Data Warehouse System (DWS) is closely correlated with user satisfaction. Therefore, analysts, designers and developers focused more on achieving all its functionality, without considering others kinds of requirement such as dependability s aspects. Moreover, these latter are often considered as properties of the system that will must be checked and corrected once the project is completed. The practice of "fix it later" can cause the obsolescence of the entire Data Warehouse System. Therefore, it requires the adoption of a methodology that will ensure the integration of aspects of dependability since the early stages of project DWS. In this paper, we first define the concepts related to dependability of DWS. Then we present our approach inspired from the MDA (Model Driven Architecture) approach to model dependability s aspects namely: availability, reliability, maintainability and security, taking into account their interaction.
Face Recognition via Globality-Locality Preserving Projections
Venue: arXiv cs.CV 2013
Year: 2013

We present an improved Locality Preserving Projections (LPP) method, named Gloablity-Locality Preserving Projections (GLPP), to preserve both the global and local geometric structures of data. In our approach, an additional constraint of the geometry of classes is imposed to the objective function of conventional LPP for respecting some more global manifold structures. Moreover, we formulate a two-dimensional extension of GLPP (2D-GLPP) as an example to show how to extend GLPP with some other statistical techniques. We apply our works to face recognition on four popular face databases, namely ORL, Yale, FERET and LFW-A databases, and extensive experimental results demonstrate that the considered global manifold information can significantly improve the performance of LPP and the proposed face recognition methods outperform the state-of-the-arts.