OpenRaiser/Intern-Atlas huggingface dataset:
Robust Adaptive Beamforming Algorithms Based on the Constrained Constant Modulus Criterion
Venue: arXiv cs.IT 2013
Year: 2013

We present a robust adaptive beamforming algorithm based on the worst-case criterion and the constrained constant modulus approach, which exploits the constant modulus property of the desired signal. Similarly to the existing worst-case beamformer with the minimum variance design, the problem can be reformulated as a second-order cone (SOC) program and solved with interior point methods. An analysis of the optimization problem is carried out and conditions are obtained for enforcing its convexity and for adjusting its parameters. Furthermore, low-complexity robust adaptive beamforming algorithms based on the modified conjugate gradient (MCG) and an alternating optimization strategy are proposed. The proposed low-complexity algorithms can compute the existing worst-case constrained minimum variance (WC-CMV) and the proposed worst-case constrained constant modulus (WC-CCM) designs with a quadratic cost in the number of parameters. Simulations show that the proposed WC-CCM algorithm performs better than existing robust beamforming algorithms. Moreover, the numerical results also show that the performances of the proposed low-complexity algorithms are equivalent or better than that of existing robust algorithms, whereas the complexity is more than an order of magnitude lower.
An Overview on 3GPP Device-to-Device Proximity Services
Venue: arXiv cs.NI 2013
Year: 2013

Device-to-device (D2D) communication will likely be added to LTE in 3GPP Release 12. In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled LTE devices can also become competitive for fallback public safety networks, that must function when cellular networks are not available, or fail. Introducing D2D poses many challenges and risks to the long-standing cellular architecture, which is centered around the base station. We provide an overview on D2D standardization activities in 3GPP, identify outstanding technical challenges, draw lessons from initial evaluation studies, and summarize "best practices" in the design of a D2D-enabled air interface for LTE-based cellular networks.
Optimal Routing and Scheduling of Charge for Electric Vehicles: Case Study
Venue: arXiv cs.SY 2013
Year: 2013

In Colombia, there is an increasing interest about improving public transportation. One of the proposed strategies in that way is the use battery electric vehicles (BEVs). One of the new challenges is the BEVs routing problem, which is subjected to the traditional issues of the routing problems, and must also consider the particularities of autonomy, charge and battery degradation of the BEVs. In this work, a scheme that coordinates the routing, scheduling of charge and operating costs of BEVs is proposed. The simplified operating costs have been modeled considering both charging fees and battery degradation. A case study is presented, in order to illustrate the proposed methodology. The given case considers an airport shuttle service scenario, in which energy consumption of the BEVs is estimated based on experimentally measured driving patterns.
Managing and Analysing Software Product Line Requirements
Venue: arXiv cs.SE 2013
Year: 2013

Modelling software product line (SPL) features plays a crucial role to a successful development of SPL. Feature diagram is one of the widely used notations to model SPL variants. However, there is a lack of precisely defined formal notations for representing and verifying such models. This paper presents an approach that we adopt to model SPL variants by using UML and subsequently verify them by using first-order logic. UML provides an overall modelling view of the system. First-order logic provides a precise and rigorous interpretation of the feature diagrams. We model variants and their dependencies by using propositional connectives and build logical expressions. These expressions are then validated by the Alloy verification tool. The analysis and verification process is illustrated by using Computer Aided Dispatch (CAD) system.
Modern Summation Methods for Loop Integrals in Quantum Field Theory: The Packages Sigma, EvaluateMultiSums and SumProduction
Venue: arXiv cs.SC 2013
Year: 2013

A large class of Feynman integrals, like e.g., two-point parameter integrals with at most one mass and containing local operator insertions, can be transformed to multi-sums over hypergeometric expressions. In this survey article we present a difference field approach for symbolic summation that enables one to simplify such definite nested sums to indefinite nested sums. In particular, the simplification is given -if possible- in terms of harmonic sums, generalized harmonic sums, cyclotomic harmonic sums or binomial sums. Special emphasis is put on the developed packages Sigma, EvaluateMultiSums and SumProduction that assist in the task to perform these simplifications completely automatically for huge input expressions.
Group Sparse Beamforming for Green Cloud-RAN
Venue: arXiv cs.IT 2013
Year: 2013

A cloud radio access network (Cloud-RAN) is a network architecture that holds the promise of meeting the explosive growth of mobile data traffic. In this architecture, all the baseband signal processing is shifted to a single baseband unit (BBU) pool, which enables efficient resource allocation and interference management. Meanwhile, conventional powerful base stations can be replaced by low-cost low-power remote radio heads (RRHs), producing a green and low-cost infrastructure. However, as all the RRHs need to be connected to the BBU pool through optical transport links, the transport network power consumption becomes significant. In this paper, we propose a new framework to design a green Cloud-RAN, which is formulated as a joint RRH selection and power minimization beamforming problem. To efficiently solve this problem, we first propose a greedy selection algorithm, which is shown to provide near- optimal performance. To further reduce the complexity, a novel group sparse beamforming method is proposed by inducing the group-sparsity of beamformers using the weighted $\ell_1/\ell_2$-norm minimization, where the group sparsity pattern indicates those RRHs that can be switched off. Simulation results will show that the proposed algorithms significantly reduce the network power consumption and demonstrate the importance of considering the transport link power consumption.
Surface Registration Using Genetic Algorithm in Reduced Search Space
Venue: arXiv cs.CV 2013
Year: 2013

Surface registration is a technique that is used in various areas such as object recognition and 3D model reconstruction. Problem of surface registration can be analyzed as an optimization problem of seeking a rigid motion between two different views. Genetic algorithms can be used for solving this optimization problem, both for obtaining the robust parameter estimation and for its fine-tuning. The main drawback of genetic algorithms is that they are time consuming which makes them unsuitable for online applications. Modern acquisition systems enable the implementation of the solutions that would immediately give the information on the rotational angles between the different views, thus reducing the dimension of the optimization problem. The paper gives an analysis of the genetic algorithm implemented in the conditions when the rotation matrix is known and a comparison of these results with results when this information is not available.
Countering Wrapping Attack on XML Signature in SOAP Message for Cloud Computing
Venue: arXiv cs.CR 2013
Year: 2013

It is known that the exchange of information between web applications is done by means of the SOAP protocol. Securing this protocol is obviously a vital issue for any computer network. However, when it comes to cloud computing systems, the sensitivity of this issue rises, as the clients of system, release their data to the cloud. XML signature is employed to secure SOAP messages. However, there are also some weak points that have been identified, named as XML signature wrapping attacks, which have been categorized into four major groups; Simple Ancestry Context Attack, Optional element context attacks, Sibling Value Context Attack, Sibling Order Context. In this paper, two existing methods, for referencing the signed part of SOAP Message, named as ID referencing and XPath method, are analyzed and examined. In addition, a new method is proposed and tested, to secure the SOAP message. In the new method, the XML any signature wrapping attack is prevented by employing the concept of XML digital signature on the SOAP message. The results of conducted experiments show that the proposed method is approximately three times faster than the XPath method and even a little faster than ID.
Improving the Quality of MT Output using Novel Name Entity Translation Scheme
Venue: arXiv cs.CL 2013
Year: 2013

This paper presents a novel approach to machine translation by combining the state of art name entity translation scheme. Improper translation of name entities lapse the quality of machine translated output. In this work, name entities are transliterated by using statistical rule based approach. This paper describes the translation and transliteration of name entities from English to Punjabi. We have experimented on four types of name entities which are: Proper names, Location names, Organization names and miscellaneous. Various rules for the purpose of syllabification have been constructed. Transliteration of name entities is accomplished with the help of Probability calculation. N-Gram probabilities for the extracted syllables have been calculated using statistical machine translation toolkit MOSES.
Learning Lambek grammars from proof frames
Venue: arXiv cs.LG 2013
Year: 2013

In addition to their limpid interface with semantics, categorial grammars enjoy another important property: learnability. This was first noticed by Buskowsky and Penn and further studied by Kanazawa, for Bar-Hillel categorial grammars. What about Lambek categorial grammars? In a previous paper we showed that product free Lambek grammars where learnable from structured sentences, the structures being incomplete natural deductions. These grammars were shown to be unlearnable from strings by Foret and Le Nir. In the present paper we show that Lambek grammars, possibly with product, are learnable from proof frames that are incomplete proof nets. After a short reminder on grammatical inference à la Gold, we provide an algorithm that learns Lambek grammars with product from proof frames and we prove its convergence. We do so for 1-valued also known as rigid Lambek grammars with product, since standard techniques can extend our result to $k$-valued grammars. Because of the correspondence between cut-free proof nets and normal natural deductions, our initial result on product free Lambek grammars can be recovered. We are sad to dedicate the present paper to Philippe Darondeau, with whom we started to study such questions in Rennes at the beginning of the millennium, and who passed away prematurely. We are glad to dedicate the present paper to Jim Lambek for his 90 birthday: he is the living proof that research is an eternal learning process.
Rule Based Stemmer in Urdu
Venue: arXiv cs.CL 2013
Year: 2013

Urdu is a combination of several languages like Arabic, Hindi, English, Turkish, Sanskrit etc. It has a complex and rich morphology. This is the reason why not much work has been done in Urdu language processing. Stemming is used to convert a word into its respective root form. In stemming, we separate the suffix and prefix from the word. It is useful in search engines, natural language processing and word processing, spell checkers, word parsing, word frequency and count studies. This paper presents a rule based stemmer for Urdu. The stemmer that we have discussed here is used in information retrieval. We have also evaluated our results by verifying it with a human expert.
Decentralized Measurement Feedback Stabilization of Large-scale Systems via Control Vector Lyapunov Functions
Venue: arXiv cs.SY 2013
Year: 2013

This paper studies the problem of decentralized measurement feedback stabilization of nonlinear interconnected systems. As a natural extension of the recent development on control vector Lyapunov functions, the notion of output control vector Lyapunov function (OCVLF) is introduced for investigating decentralized measurement feedback stabilization problems. Sufficient conditions on (local) stabilizability are discussed which are based on the proposed notion of OCVLF. It is shown that a decentralized controller for a nonlinear interconnected system can be constructed using these conditions under an additional vector dissipation-like condition. To illustrate the proposed method, two examples are given.
Games and Culture: Using Online-gaming Data to Cluster Chinese Regional Cultures
Venue: arXiv cs.CY 2013
Year: 2013

To identify cluster of societies and cultures is not easy in subject to the availability of data. In this study, we propose a novel method to cluster Chinese regional cultures. Using geotagged online-gaming data of Chinese internet users playing online card and board games with regional features, 336 Chinese cities are grouped into 17 clusters. The distribution of clustering units shows great geographical proximity when the boundary of the clusters coincides well with the geographical boundary of provinces.
Upper-Expectation Bisimilarity and Real-valued Modal Logics
Venue: arXiv cs.LO 2013
Year: 2013

Several notions of bisimulation relations for probabilistic non-deterministic transition systems have been considered in the literature. We consider a novel testing-based behavioral equivalence called upper-expectation bisimilarity and develop its theory using standard results from linear algebra and functional analysis. We show that, for a wide class of systems, our new notion coincides with Segala's convex bisimilarity. We develop logical characterizations in terms of expressive probabilistic modal mu-calculi and a novel real-valued modal logic. We prove that upper-expectation bisimilarity is a congruence for the wide family of process algebras specified following the probabilistic GSOS rule format.
RoboRun: A gamification approach to control flow learning for young students with TouchDevelop
Venue: arXiv cs.CY 2013
Year: 2013

This demo paper introduces young students to writing code in a touch enabled interactive maze game. Problem-based learning is given a gamified approach to learning, while simultaneously introducing the TouchDevelop platform to build basic first control flow algorithms and to learn about ordering and loops in conditional statements.
Janus II: a new generation application-driven computer for spin-system simulations
Venue: arXiv cs.AR 2013
Year: 2013

This paper describes the architecture, the development and the implementation of Janus II, a new generation application-driven number cruncher optimized for Monte Carlo simulations of spin systems (mainly spin glasses). This domain of computational physics is a recognized grand challenge of high-performance computing: the resources necessary to study in detail theoretical models that can make contact with experimental data are by far beyond those available using commodity computer systems. On the other hand, several specific features of the associated algorithms suggest that unconventional computer architectures, which can be implemented with available electronics technologies, may lead to order of magnitude increases in performance, reducing to acceptable values on human scales the time needed to carry out simulation campaigns that would take centuries on commercially available machines. Janus II is one such machine, recently developed and commissioned, that builds upon and improves on the successful JANUS machine, which has been used for physics since 2008 and is still in operation today. This paper describes in detail the motivations behind the project, the computational requirements, the architecture and the implementation of this new machine and compares its expected performances with those of currently available commercial systems.
Evolution of choices over time: The U.S. Presidential election 2012 and the NY City Mayoral Election, 2013
Venue: arXiv cs.OH 2013
Year: 2013

We conducted surveys before and after the 2012 U.S. Presidential election and prior to the NY City Mayoral election in 2013. The surveys were done using Amazon Turk. This poster describes the results of our analysis of the surveys and predicts the winner of the NY City Mayoral Election.
Vectorized OpenCL implementation of numerical integration for higher order finite elements
Venue: arXiv cs.MS 2013
Year: 2013

In our work we analyze computational aspects of the problem of numerical integration in finite element calculations and consider an OpenCL implementation of related algorithms for processors with wide vector registers. As a platform for testing the implementation we choose the PowerXCell processor, being an example of the Cell Broadband Engine (CellBE) architecture. Although the processor is considered old for today's standards (its design dates back to year 2001), we investigate its performance due to two features that it shares with recent Xeon Phi family of coprocessors: wide vector units and relatively slow connection of computing cores with main global memory. The performed analysis of parallelization options can also be used for designing numerical integration algorithms for other processors with vector registers, such as contemporary x86 microprocessors.
Spatially Scalable Compressed Image Sensing with Hybrid Transform and Inter-layer Prediction Model
Venue: arXiv cs.IT 2013
Year: 2013

Compressive imaging is an emerging application of compressed sensing, devoted to acquisition, encoding and reconstruction of images using random projections as measurements. In this paper we propose a novel method to provide a scalable encoding of an image acquired by means of compressed sensing techniques. Two bit-streams are generated to provide two distinct quality levels: a low-resolution base layer and full-resolution enhancement layer. In the proposed method we exploit a fast preview of the image at the encoder in order to perform inter-layer prediction and encode the prediction residuals only. The proposed method successfully provides resolution and quality scalability with modest complexity and it provides gains in the quality of the reconstructed images with respect to separate encoding of the quality layers. Remarkably, we also show that the scheme can also provide significant gains with respect to a direct, non-scalable system, thus accomplishing two features at once: scalability and improved reconstruction performance.
The Novel Approach of Adaptive Twin Probability for Genetic Algorithm
Venue: arXiv cs.NE 2013
Year: 2013

The performance of GA is measured and analyzed in terms of its performance parameters against variations in its genetic operators and associated parameters. Since last four decades huge numbers of researchers have been working on the performance of GA and its enhancement. This earlier research work on analyzing the performance of GA enforces the need to further investigate the exploration and exploitation characteristics and observe its impact on the behavior and overall performance of GA. This paper introduces the novel approach of adaptive twin probability associated with the advanced twin operator that enhances the performance of GA. The design of the advanced twin operator is extrapolated from the twin offspring birth due to single ovulation in natural genetic systems as mentioned in the earlier works. The twin probability of this operator is adaptively varied based on the fitness of best individual thereby relieving the GA user from statically defining its value. This novel approach of adaptive twin probability is experimented and tested on the standard benchmark optimization test functions. The experimental results show the increased accuracy in terms of the best individual and reduced convergence time.
Learning ambiguous functions by neural networks
Venue: arXiv cs.NE 2013
Year: 2013

It is not, in general, possible to have access to all variables that determine the behavior of a system. Having identified a number of variables whose values can be accessed, there may still be hidden variables which influence the dynamics of the system. The result is model ambiguity in the sense that, for the same (or very similar) input values, different objective outputs should have been obtained. In addition, the degree of ambiguity may vary widely across the whole range of input values. Thus, to evaluate the accuracy of a model it is of utmost importance to create a method to obtain the degree of reliability of each output result. In this paper we present such a scheme composed of two coupled artificial neural networks: the first one being responsible for outputting the predicted value, whereas the other evaluates the reliability of the output, which is learned from the error values of the first one. As an illustration, the scheme is applied to a model for tracking slopes in a straw chamber and to a credit scoring model.
The Relevance of Proofs of the Rationality of Probability Theory to Automated Reasoning and Cognitive Models
Venue: arXiv cs.AI 2013
Year: 2013

A number of well-known theorems, such as Cox's theorem and de Finetti's theorem. prove that any model of reasoning with uncertain information that satisfies specified conditions of "rationality" must satisfy the axioms of probability theory. I argue here that these theorems do not in themselves demonstrate that probabilistic models are in fact suitable for any specific task in automated reasoning or plausible for cognitive models. First, the theorems only establish that there exists some probabilistic model; they do not establish that there exists a useful probabilistic model, i.e. one with a tractably small number of numerical parameters and a large number of independence assumptions. Second, there are in general many different probabilistic models for a given situation, many of which may be far more irrational, in the usual sense of the term, than a model that violates the axioms of probability theory. I illustrate this second point with an extended examples of two tasks of induction, of a similar structure, where the reasonable probabilistic models are very different.
Massive MU-MIMO Downlink TDD Systems with Linear Precoding and Downlink Pilots
Venue: arXiv cs.IT 2013
Year: 2013

We consider a massive MU-MIMO downlink time-division duplex system where a base station (BS) equipped with many antennas serves several single-antenna users in the same time-frequency resource. We assume that the BS uses linear precoding for the transmission. To reliably decode the signals transmitted from the BS, each user should have an estimate of its channel. In this work, we consider an efficient channel estimation scheme to acquire CSI at each user, called beamforming training scheme. With the beamforming training scheme, the BS precodes the pilot sequences and forwards to all users. Then, based on the received pilots, each user uses minimum mean-square error channel estimation to estimate the effective channel gains. The channel estimation overhead of this scheme does not depend on the number of BS antennas, and is only proportional to the number of users. We then derive a lower bound on the capacity for maximum-ratio transmission and zero-forcing precoding techniques which enables us to evaluate the spectral efficiency taking into account the spectral efficiency loss associated with the transmission of the downlink pilots. Comparing with previous work where each user uses only the statistical channel properties to decode the transmitted signals, we see that the proposed beamforming training scheme is preferable for moderate and low-mobility environments.