OpenRaiser/Intern-Atlas huggingface dataset:
Optimizing Service Differentiation Scheme with Sized-based Queue Management in DiffServ Networks
Venue: arXiv cs.NI 2012
Year: 2012

In this paper we introduced Modified Sized-based Queue Management as a dropping scheme that aims to fairly prioritize and allocate more service to VoIP traffic over bulk data like FTP as the former one usually has small packet size with less impact to the network congestion. In the same time, we want to guarantee that this prioritization is fair enough for both traffic types. On the other hand we study the total link delay over the congestive link with the attempt to alleviate this congestion as much as possible at the by function of early congestion notification. Our M-SQM scheme has been evaluated with NS2 experiments to measure the packets received from both and total link-delay for different traffic. The performance evaluation results of M-SQM have been validated and graphically compared with the performance of other three legacy AQMs (RED, RIO, and PI). It is depicted that our M-SQM outperformed these AQMs in providing QoS level of service differentiation.
Compiling Relational Database Schemata into Probabilistic Graphical Models
Venue: arXiv cs.AI 2012
Year: 2012

Instead of requiring a domain expert to specify the probabilistic dependencies of the data, in this work we present an approach that uses the relational DB schema to automatically construct a Bayesian graphical model for a database. This resulting model contains customized distributions for columns, latent variables that cluster the data, and factors that reflect and represent the foreign key links. Experiments demonstrate the accuracy of the model and the scalability of inference on synthetic and real-world data.
Spectral properties of Google matrix of Wikipedia and other networks
Venue: arXiv cs.IR 2012
Year: 2012

We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between PageRank and CheiRank vectors distinguishes different organizations of information flow on BBC and Le Monde web sites.
Making Early Predictions of the Accuracy of Machine Learning Applications
Venue: arXiv cs.LG 2012
Year: 2012

The accuracy of machine learning systems is a widely studied research topic. Established techniques such as cross-validation predict the accuracy on unseen data of the classifier produced by applying a given learning method to a given training data set. However, they do not predict whether incurring the cost of obtaining more data and undergoing further training will lead to higher accuracy. In this paper we investigate techniques for making such early predictions. We note that when a machine learning algorithm is presented with a training set the classifier produced, and hence its error, will depend on the characteristics of the algorithm, on training set's size, and also on its specific composition. In particular we hypothesise that if a number of classifiers are produced, and their observed error is decomposed into bias and variance terms, then although these components may behave differently, their behaviour may be predictable. We test our hypothesis by building models that, given a measurement taken from the classifier created from a limited number of samples, predict the values that would be measured from the classifier produced when the full data set is presented. We create separate models for bias, variance and total error. Our models are built from the results of applying ten different machine learning algorithms to a range of data sets, and tested with "unseen" algorithms and datasets. We analyse the results for various numbers of initial training samples, and total dataset sizes. Results show that our predictions are very highly correlated with the values observed after undertaking the extra training. Finally we consider the more complex case where an ensemble of heterogeneous classifiers is trained, and show how we can accurately estimate an upper bound on the accuracy achievable after further training.
Integrated Green Cloud Computing Architecture
Venue: arXiv cs.DC 2012
Year: 2012

Arbitrary usage of cloud computing, either private or public, can lead to uneconomical energy consumption in data processing, storage and communication. Hence, green cloud computing solutions aim not only to save energy but also reduce operational costs and carbon footprints on the environment. In this paper, an Integrated Green Cloud Architecture (IGCA) is proposed that comprises of a client-oriented Green Cloud Middleware to assist managers in better overseeing and configuring their overall access to cloud services in the greenest or most energy-efficient way. Decision making, whether to use local machine processing, private or public clouds, is smartly handled by the middleware using predefined system specifications such as service level agreement (SLA), Quality of service (QoS), equipment specifications and job description provided by IT department. Analytical model is used to show the feasibility to achieve efficient energy consumption while choosing between local, private and public Cloud service provider (CSP).
Autonomous Navigation by Robust Scan Matching Technique
Venue: arXiv cs.CV 2012
Year: 2012

For effective autonomous navigation,estimation of the pose of the robot is essential at every sampling time. For computing an accurate estimation,odometric error needs to be reduced with the help of data from external sensor. In this work, a technique has been developed for accurate pose estimation of mobile robot by using Laser Range data. The technique is robust to noisy data, which may contain considerable amount of outliers. A grey image is formed from laser range data and the key points from this image are extracted by Harris corner detector. The matching of the key points from consecutive data sets have been done while outliers have been rejected by RANSAC method. Robot state is measured by the correspondence between the two sets of keypoints. Finally, optimal robot state is estimated by Extended Kalman Filter. The technique has been applied to an operational robot in the laboratory environment to show the robustness of the technique in presence of noisy sensor data. The performance of this new technique has been compared with that of conventional ICP method. Through this method, effective and accurate navigation has been achieved even in presence of substantial noise in the sensor data at the cost of a small amount of additional computational complexity.
Automatic Detection of Texture Defects Using Texture-Periodicity and Gabor Wavelets
Venue: arXiv cs.CV 2012
Year: 2012

In this paper, we propose a machine vision algorithm for automatically detecting defects in textures belonging to 16 out of 17 wallpaper groups using texture-periodicity and a family of Gabor wavelets. Input defective images are subjected to Gabor wavelet transformation in multi-scales and multi-orientations and a resultant image is obtained in L2 norm. The resultant image is split into several periodic blocks and energy of each block is used as a feature space to automatically identify defective and defect-free blocks using Ward's hierarchical clustering. Experiments on defective fabric images of three major wallpaper groups, namely, pmm, p2 and p4m, show that the proposed method is robust in finding fabric defects without human intervention and can be used for automatic defect detection in fabric industries.
A simple method for decision making in robocup soccer simulation 3d environment
Venue: arXiv cs.AI 2012
Year: 2012

In this paper new hierarchical hybrid fuzzy-crisp methods for decision making and action selection of an agent in soccer simulation 3D environment are presented. First, the skills of an agent are introduced, implemented and classified in two layers, the basicskills and the highlevel skills. In the second layer, a twophase mechanism for decision making is introduced. In phase one, some useful methods are implemented which check the agent's situation for performing required skills. In the next phase, the team str ategy, team for mation, agent's role and the agent's positioning system are introduced. A fuzzy logical approach is employed to recognize the team strategy and further more to tell the player the best position to move. At last, we comprised our implemented algor ithm in the Robocup Soccer Simulation 3D environment and results showed th eefficiency of the introduced methodology.
Modeling for Control of Symmetric Aerial Vehicles Subjected to Aerodynamic Forces
Venue: arXiv cs.SY 2012
Year: 2012

This paper participates in the development of a unified approach to the control of aerial vehicles with extended flight envelopes. More precisely, modeling for control purposes of a class of thrust-propelled aerial vehicles subjected to lift and drag aerodynamic forces is addressed assuming a rotational symmetry of the vehicle's shape about the thrust force axis. A condition upon aerodynamic characteristics that allows one to recast the control problem into the simpler case of a spherical vehicle is pointed out. Beside showing how to adapt nonlinear controllers developed for this latter case, the paper extends a previous work by the authors in two directions. First, the 3D case is addressed whereas only motions in a single vertical plane was considered. Secondly, the family of models of aerodynamic forces for which the aforementioned transformation holds is enlarged.
A Change Support Model for Distributed Collaborative Work
Venue: arXiv cs.SE 2012
Year: 2012

Distributed collaborative software development tends to make artifacts and decisions inconsistent and uncertain. We try to solve this problem by providing an information repository to reflect the state of works precisely, by managing the states of artifacts/products made through collaborative work, and the states of decisions made through communications. In this paper, we propose models and a tool to construct the artifact-related part of the information repository, and explain the way to use the repository to resolve inconsistencies caused by concurrent changes of artifacts. We first show the model and the tool to generate the dependency relationships among UML model elements as content of the information repository. Next, we present the model and the method to generate change support workflows from the information repository. These workflows give us the way to efficiently modify the change-related artifacts for each change request. Finally, we define inconsistency patterns that enable us to be aware of the possibility of inconsistency occurrences. By combining this mechanism with version control systems, we can make changes safely. Our models and tool are useful in the maintenance phase to perform changes safely and efficiently.
Toward Intelligent Biped-Humanoids Gaits Generation
Venue: arXiv cs.RO 2012
Year: 2012

In this chapter we will highlight our experimental studies on natural human walking analysis and introduce a biologically inspired design for simple bipedal locomotion system of humanoid robots. Inspiration comes directly from human walking analysis and human muscles mechanism and control. A hybrid algorithm for walking gaits generation is then proposed as an innovative alternative to classically used kinematics and dynamic equations solving, the gaits include knee, ankle and hip trajectories. The proposed algorithm is an intelligent evolutionary based on particle swarm optimization paradigm. This proposal can be used for small size humanoid robots, with a knee an ankle and a hip and at least six Degrees of Freedom (DOF).
On Structured Realizability and Stabilizability of Linear Systems
Venue: arXiv cs.SY 2012
Year: 2012

We study the notion of structured realizability for linear systems defined over graphs. A stabilizable and detectable realization is structured if the state-space matrices inherit the sparsity pattern of the adjacency matrix of the associated graph. In this paper, we demonstrate that not every structured transfer matrix has a structured realization and we reveal the practical meaning of this fact. We also uncover a close connection between the structured realizability of a plant and whether the plant can be stabilized by a structured controller. In particular, we show that a structured stabilizing controller can only exist when the plant admits a structured realization. Finally, we give a parameterization of all structured stabilizing controllers and show that they always have structured realizations.
A direct solver with reutilization of previously-computed LU factorizations for h-adaptive finite element grids with point singularities
Venue: arXiv cs.NA 2012
Year: 2012

This paper describes a direct solver algorithm for a sequence of finite element meshes that are h-refined towards one or several point singularities. For such a sequence of grids, the solver delivers linear computational cost O(N) in terms of CPU time and memory with respect to the number of unknowns N. The linear computational cost is achieved by utilizing the recursive structure provided by the sequence of h-adaptive grids with a special construction of the elimination tree that allows for reutilization of previously computed partial LU factorizations over the entire unrefined part of the computational mesh. The reutilization technique reduces the computational cost of the entire sequence of h-refined grids from O(N^2) down to O(N). Theoretical estimates are illustrated with numerical results on two- and three-dimensional model problems exhibiting one or several point singularities.
Secondary Access to Spectrum with SINR Requirements Through Constraint Transformation
Venue: arXiv cs.NI 2012
Year: 2012

In this paper we investigate the problem of allocating spectrum among radio nodes under SINR requirements. This problem is of special interest in dynamic spectrum access networks where topology and spectral resources differ with time and location. The problem is to determine the number of radio nodes that can transmit simultaneously while still achieving their SINR requirements and then decide which channels these nodes should transmit on. Previous work have shown how this can be done for a large spectrum pool where nodes allocate multiple channels from that pool which renders a linear programming approach feasible when the pool is large enough. In this paper we extend their work by considering arbitrary individual pool sizes and allow nodes to only transmit on one channel. Due to the accumulative nature of interference this problem is a non-convex integer problem which is NP-hard. However, we introduce a constraint transformation that transforms the problem to a binary quadratic constraint problem. Although this problem is still NP-hard, well known heuristic algorithms for solving this problem are known in the literature. We implement a heuristic algorithm based on Lagrange relaxation which bounds the solution value of the heuristic to the optimal value of the constraint transformed problem. Simulation results show that this approach provides solutions within an average gap of 10% of solutions obtained by a genetic algorithm for the original non-convex integer problem.
Recapitulation of Web Services based on Tree Structure
Venue: arXiv cs.SE 2012
Year: 2012

The Recapitulation of Web service is an approach for the effective integration of distributed, heterogeneous and autonomous applications to build more Structured and value added services. Web services selection algorithms are required to find and select the best services. A QoS is a benchmark to select the best service for the task of composition. The importance of the web services selection algorithm is to maximize the QoS of the web services recapitulation using complex service provider's (CSP) QoS requirement parameters. This paper have discussed about different Web service Service-offers. We have classified the CSP's requirements defined on the QoS and Service-offers based on its structure. We have proposed a tree structure to represent the CSP's requirement to be defined based on the multiple QoS properties.
Improved Channel Estimation Methods based on PN sequence for TDS-OFDM
Venue: arXiv cs.IT 2012
Year: 2012

An accurate channel estimation is crucial for the novel time domain synchronous orthogonal frequency-division multiplexing (TDS-OFDM) scheme in which pseudo noise (PN) sequences serve as both guard intervals (GI) for OFDM data symbols and training sequences for synchronization/channel estimation. This paper studies the channel estimation method based on the cross-correlation of PN sequences. A theoretical analysis of this estimator is conducted and several improved estimators are then proposed to reduce the estimation error floor encountered by the PN-correlation-based estimator. It is shown through mathematical derivations and simulations that the new estimators approach or even achieve the Cramer-Rao bound.
Automated verification of termination certificates
Venue: arXiv cs.LO 2012
Year: 2012

In order to increase user confidence, many automated theorem provers provide certificates that can be independently verified. In this paper, we report on our progress in developing a standalone tool for checking the correctness of certificates for the termination of term rewrite systems, and formally proving its correctness in the proof assistant Coq. To this end, we use the extraction mechanism of Coq and the library on rewriting theory and termination called CoLoR.
Robust Face Recognition using Local Illumination Normalization and Discriminant Feature Point Selection
Venue: arXiv cs.LG 2012
Year: 2012

Face recognition systems must be robust to the variation of various factors such as facial expression, illumination, head pose and aging. Especially, the robustness against illumination variation is one of the most important problems to be solved for the practical use of face recognition systems. Gabor wavelet is widely used in face detection and recognition because it gives the possibility to simulate the function of human visual system. In this paper, we propose a method for extracting Gabor wavelet features which is stable under the variation of local illumination and show experiment results demonstrating its effectiveness.
Multi-layered Social Networks
Venue: arXiv cs.SI 2012
Year: 2012

It is quite obvious that in the real world, more than one kind of relationship can exist between two actors and that those ties can be so intertwined that it is impossible to analyse them separately [Fienberg 85], [Minor 83], [Szell 10]. Social networks with more than one type of relation are not a completely new concept [Wasserman 94] but they were analysed mainly at the small scale, e.g. in [McPherson 01], [Padgett 93], and [Entwisle 07]. Just like in the case of regular single-layered social network there is no widely accepted definition or even common name. At the beginning such networks have been called multiplex network [Haythornthwaite 99], [Monge 03]. The term is derived from communications theory which defines multiplex as combining multiple signals into one in such way that it is possible to separate them if needed [Hamill 06]. Recently, the area of multi-layered social network has started attracting more and more attention in research conducted within different domains [Kazienko 11a], [Szell 10], [Rodriguez 07], [Rodriguez 09], and the meaning of multiplex network has expanded and covers not only social relationships but any kind of connection, e.g. based on geography, occupation, kinship, hobbies, etc. [Abraham 12]. This essay aims to summarize existing knowledge about one concept which has many different names i.e. the concept of Multi-layered Social Network also known as Layered social network, Multi-relational social network, Multidimensional social network, Multiplex social network
Upgrading Ambiguous Signs in QPNs
Venue: arXiv cs.AI 2012
Year: 2012

WA qualitative probabilistic network models the probabilistic relationships between its variables by means of signs. Non-monotonic influences have associated an ambiguous sign. These ambiguous signs typically lead to uninformative results upon inference. A non-monotonic influence can, however, be associated with a, more informative, sign that indicates its effect in the current state of the network. To capture this effect, we introduce the concept of situational sign. Furthermore, if the network converts to a state in which all variables that provoke the non-monotonicity have been observed, a non-monotonic influence reduces to a monotonic influence. We study the persistence and propagation of situational signs upon inference and give a method to establish the sign of a reduced influence.
On Triangulating Dynamic Graphical Models
Venue: arXiv cs.AI 2012
Year: 2012

This paper introduces new methodology to triangulate dynamic Bayesian networks (DBNs) and dynamic graphical models (DGMs). While most methods to triangulate such networks use some form of constrained elimination scheme based on properties of the underlying directed graph, we find it useful to view triangulation and elimination using properties only of the resulting undirected graph, obtained after the moralization step. We first briefly introduce the Graphical model toolkit (GMTK) and its notion of dynamic graphical models, one that slightly extends the standard notion of a DBN. We next introduce the 'boundary algorithm', a method to find the best boundary between partitions in a dynamic model. We find that using this algorithm, the notions of forward- and backward-interface become moot - namely, the size and fill-in of the best forward- and backward- interface are identical. Moreover, we observe that finding a good partition boundary allows for constrained elimination orders (and therefore graph triangulations) that are not possible using standard slice-by-slice constrained eliminations. More interestingly, with certain boundaries it is possible to obtain constrained elimination schemes that lie outside the space of possible triangulations using only unconstrained elimination. Lastly, we report triangulation results on invented graphs, standard DBNs from the literature, novel DBNs used in speech recognition research systems, and also random graphs. Using a number of different triangulation quality measures (max clique size, state-space, etc.), we find that with our boundary algorithm the triangulation quality can dramatically improve.
A possibilistic handling of partially ordered information
Venue: arXiv cs.AI 2012
Year: 2012

In a standard possibilistic logic, prioritized information are encoded by means of weighted knowledge base. This paper proposes an extension of possibilistic logic for dealing with partially ordered information. We Show that all basic notions of standard possibilitic logic (sumbsumption, syntactic and semantic inference, etc.) have natural couterparts when dealing with partially ordered information. We also propose an algorithm which computes possibilistic conclusions of a partial knowledge base of a partially ordered knowlege base.
Value Elimination: Bayesian Inference via Backtracking Search
Venue: arXiv cs.AI 2012
Year: 2012

Backtracking search is a powerful algorithmic paradigm that can be used to solve many problems. It is in a certain sense the dual of variable elimination; but on many problems, e.g., SAT, it is vastly superior to variable elimination in practice. Motivated by this we investigate the application of backtracking search to the problem of Bayesian inference (Bayes). We show that natural generalizations of known techniques allow backtracking search to achieve performance guarantees similar to standard algorithms for Bayes, and that there exist problems on which backtracking can in fact do much better. We also demonstrate that these ideas can be applied to implement a Bayesian inference engine whose performance is competitive with standard algorithms. Since backtracking search can very naturally take advantage of context specific structure, the potential exists for performance superior to standard algorithms on many problems.