OpenRaiser/Intern-Atlas huggingface dataset:
Strong Secrecy in Wireless Network Coding Systems with M-QAM Modulators
Venue: arXiv cs.CR 2014
Year: 2014

We investigate the possibility of developing physical layer network coding (PNC) schemes with embedded strong secrecy based on standard QAM modulators. The proposed scheme employs a triple binning approach at the QAM front-end of the wireless PNC encoders. A constructive example of a strong secrecy encoder is presented when a BPSK and an 8-PAM modulator are employed at the wireless transmitters and generalized to arbitrary M-QAM modulators, assuming channel inversion is attainable at the first cycle of the transmission. Our preliminary investigations demonstrate the potential of using such techniques to increase the throughput while in parallel not compromise the confidentiality of the exchanged data.
Modelling an Aircraft Landing System in Event-B (Full Report)
Venue: arXiv cs.SE 2014
Year: 2014

The failure of hardware or software in a critical system can lead to loss of lives. The design errors can be main source of the failures that can be introduced during system development process. Formal techniques are an alternative approach to verify the correctness of critical systems, overcoming limitations of the traditional validation techniques such as simulation and testing. The increasing complexity and failure rate brings new challenges in the area of verification and validation of avionic systems. Since the reliability of the software cannot be quantified, the \textit{correct by construction} approach can implement a reliable system. Refinement plays a major role to build a large system incrementally from an abstract specification to a concrete system. This paper contributes as a stepwise formal development of the landing system of an aircraft. The formal models include the complex behaviour, temporal behaviour and sequence of operations of the landing gear system. The models are formalized in Event-B modelling language, which supports stepwise refinement. This case study is considered as a benchmark for techniques and tools dedicated to the verification of behavioural properties of systems. The report is the full version of a paper published for the ABZ 2014 Case Study. is
Higher-Order Quantum-Inspired Genetic Algorithms
Venue: arXiv cs.NE 2014
Year: 2014

This paper presents a theory and an empirical evaluation of Higher-Order Quantum-Inspired Genetic Algorithms. Fundamental notions of the theory have been introduced, and a novel Order-2 Quantum-Inspired Genetic Algorithm (QIGA2) has been presented. Contrary to all QIGA algorithms which represent quantum genes as independent qubits, in higher-order QIGAs quantum registers are used to represent genes strings which allows modelling of genes relations using quantum phenomena. Performance comparison has been conducted on a benchmark of 20 deceptive combinatorial optimization problems. It has been presented that using higher quantum orders is beneficial for genetic algorithm efficiency, and the new QIGA2 algorithm outperforms the old QIGA algorithm which was tuned in highly compute intensive metaoptimization process.
On the Capacity of CSI Based Transmission Link Selection in Decode-and-Forward Cooperative System
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we study the problem of best transmission link selection in a decode-and-forward (DF) cooperative system from capacity point of view. The transmission link can be a cooperative (via a relay) or direct link between the source and destination nodes. In a two-hop DF system with multiple relays and a direct link in between the source and destination, the transmission link selection can be performed based on full or partial channel state information (CSI) of all links involved in cooperation. We derive analytical ergodic capacity of full and partial CSI based path selection schemes in the DF cooperative system. Further, the full and partial CSI based link selection schemes are compared with help of these expressions.
HT-Paxos: High Throughput State-Machine Replication Protocol for Large Clustered Data Centers
Venue: arXiv cs.DC 2014
Year: 2014

Paxos is a prominent theory of state machine replication. Recent data intensive Systems those implement state machine replication generally require high throughput. Earlier versions of Paxos as few of them are classical Paxos, fast Paxos and generalized Paxos have a major focus on fault tolerance and latency but lacking in terms of throughput and scalability. A major reason for this is the heavyweight leader. Through offloading the leader, we can further increase throughput of the system. Ring Paxos, Multi Ring Paxos and S-Paxos are few prominent attempts in this direction for clustered data centers. In this paper, we are proposing HT-Paxos, a variant of Paxos that one is the best suitable for any large clustered data center. HT-Paxos further offloads the leader very significantly and hence increases the throughput and scalability of the system. While at the same time, among high throughput state-machine replication protocols, HT-Paxos provides reasonably low latency and response time.
Dynamic Checking of Safe Concurrent Memory Access using Shared Ownership
Venue: arXiv cs.DC 2014
Year: 2014

In shared-memory concurrent programming, shared resources can be protected using synchronization mechanisms such as monitors or channels. The connection between these mechanisms and the resources they protect is, however, only given implicitly; this makes it difficult both for programmers to apply the mechanisms correctly and for compilers to check that resources are properly protected. This paper presents a mechanism to automatically check that shared memory is accessed properly, using a methodology called shared ownership. In contrast to traditional ownership, shared ownership offers more flexibility by permitting multiple owners of a resource. On the basis of this methodology, we define an abstract model of resource access that provides operations to manage data dependencies, as well as sharing and transfer of access privileges. The model is rigorously defined using a formal semantics, and shown to be free from data races. This property can be used to detect unsafe memory accesses when simulating the model together with the execution of a program. The expressiveness and efficiency of the approach is demonstrated on a variety of programs using common synchronization mechanisms.
Inverse Graphics with Probabilistic CAD Models
Venue: arXiv cs.CV 2014
Year: 2014

Recently, multiple formulations of vision problems as probabilistic inversions of generative models based on computer graphics have been proposed. However, applications to 3D perception from natural images have focused on low-dimensional latent scenes, due to challenges in both modeling and inference. Accounting for the enormous variability in 3D object shape and 2D appearance via realistic generative models seems intractable, as does inverting even simple versions of the many-to-many computations that link 3D scenes to 2D images. This paper proposes and evaluates an approach that addresses key aspects of both these challenges. We show that it is possible to solve challenging, real-world 3D vision problems by approximate inference in generative models for images based on rendering the outputs of probabilistic CAD (PCAD) programs. Our PCAD object geometry priors generate deformable 3D meshes corresponding to plausible objects and apply affine transformations to place them in a scene. Image likelihoods are based on similarity in a feature space based on standard mid-level image representations from the vision literature. Our inference algorithm integrates single-site and locally blocked Metropolis-Hastings proposals, Hamiltonian Monte Carlo and discriminative data-driven proposals learned from training data generated from our models. We apply this approach to 3D human pose estimation and object shape reconstruction from single images, achieving quantitative and qualitative performance improvements over state-of-the-art baselines.
Cross Layer Provision of Future Cellular Networks
Venue: arXiv cs.IT 2014
Year: 2014

To cope with the growing demand for wireless data and to extend service coverage, future 5G networks will increasingly rely on the use of low powered nodes to support massive connectivity in diverse set of applications and services [1]. To this end, virtualized and mass-scale cloud architectures are proposed as promising technologies for 5G in which all the nodes are connected via a backhaul network and managed centrally by such cloud centers. The significant computing power made available by the cloud technologies has enabled the implementation of sophisticated signal processing algorithms, especially by way of parallel processing, for both interference management and network provision. The latter two are among the major signal processing tasks for 5G due to increased level of frequency sharing, node density, interference and network congestion. This article outlines several theoretical and practical aspects of joint interference management and network provisioning for future 5G networks. A cross-layer optimization framework is proposed for joint user admission, user-base station association, power control, user grouping, transceiver design as well as routing and flow control. We show that many of these cross-layer tasks can be treated in a unified way and implemented in a parallel manner using an efficient algorithmic framework called WMMSE (Weighted MMSE). Some recent developments in this area are highlighted and future research directions are identified.
The Smart Shower
Venue: arXiv cs.CY 2014
Year: 2014

The smart shower is an intelligent device that saves the water during the shower. It uses the indicator lamps that inform the user of the amount of the water. Like the traffic signal it has three sets of lamps, green, yellow and red, each indicating the amount of time spent. This device brain is the Siemens Logo PLC.
A Robust Low-Complexity MIMO Detector for Rank 4 LTE/LTE-A Systems
Venue: arXiv cs.IT 2014
Year: 2014

This paper deals with MIMO detection for rank 4 LTE systems. The paper revolves around a previously known detector [1, by Inkyu Lee, TCOM'2010] which we shall refer to as RCSMLD (Reduced-Constellation-Size-Maximum-Likelihood-Detector). However, a direct application of the scheme in [1, by Inkyu Lee, TCOM'2010] to LTE/LTE-A rank 4 test cases results in unsatisfactory performance. The first contribution of the paper is to introduce several modifications that can jointly be applied to the basic RCSMLD scheme which, taken together, result in excellent performance. Our second contribution is the development of a highly efficient hardware structure for RCSMLD that allows for an implementation with very few multiplications.
Analyzing Cryptographic Algorithms for Secure Cloud Network
Venue: arXiv cs.DC 2014
Year: 2014

Pay as per usage concept of Cloud computing has brought revolutionary changes in the information technology world.
Parameter Synthesis for Cardiac Cell Hybrid Models Using Delta-Decisions
Venue: arXiv cs.LO 2014
Year: 2014

A central problem in systems biology is to identify parameter values such that a biological model satisfies some behavioral constraints (\eg, time series). In this paper we focus on parameter synthesis for hybrid (continuous/discrete) models, as many biological systems can possess multiple operational modes with specific continuous dynamics in each mode. These biological systems are naturally modeled as hybrid automata, most often with nonlinear continuous dynamics. However, hybrid automata are notoriously hard to analyze --- even simple reachability for hybrid systems with linear differential dynamics is an undecidable problem. In this paper we present a parameter synthesis framework based on $δ$-complete decision procedures that sidesteps undecidability. We demonstrate our method on two highly nonlinear hybrid models of the cardiac cell action potential. The results show that our parameter synthesis framework is convenient and efficient, and it enabled us to select a suitable model to study and identify crucial parameter ranges related to cardiac disorders.
Differentially Private Multi-party Computation: Optimality of Non-Interactive Randomized Response
Venue: arXiv cs.CR 2014
Year: 2014

We study the problem of interactive function computation by multiple parties possessing a single bit each in a differential privacy setting (i.e., there remains an uncertainty in any specific party's bit even when given the transcript of the interactions and all the other parties' bits). Each party is interested in computing a function, which could differ from party to party, and there could be a central observer interested in computing a separate function. Performance at each party and the central observer is measured via the accuracy of the function computed. We allow for an arbitrary cost function to measure the distortion between the true and the computed function value. Our main result is the exact optimality of a simple non-interactive protocol: each party randomizes (sufficiently) and publishes its own bit. In other words, non-interactive randomized response is exactly optimal. Each party and the central observer then separately compute their respective function to maximize the appropriate notion of their accuracy measure. The optimality is very general: it holds for all types of functions, heterogeneous privacy conditions on the parties, all types of cost metrics, and both average and worst-case (over the inputs) measures of accuracy. Finally, the optimality result is simultaneous, in terms of maximizing accuracy at each of the parties and the central observer.
WordRep: A Benchmark for Research on Learning Word Representations
Venue: arXiv cs.CL 2014
Year: 2014

WordRep is a benchmark collection for the research on learning distributed word representations (or word embeddings), released by Microsoft Research. In this paper, we describe the details of the WordRep collection and show how to use it in different types of machine learning research related to word embedding. Specifically, we describe how the evaluation tasks in WordRep are selected, how the data are sampled, and how the evaluation tool is built. We then compare several state-of-the-art word representations on WordRep, report their evaluation performance, and make discussions on the results. After that, we discuss new potential research topics that can be supported by WordRep, in addition to algorithm comparison. We hope that this paper can help people gain deeper understanding of WordRep, and enable more interesting research on learning distributed word representations and related topics.
Synthesis from Probabilistic Components
Venue: arXiv cs.LO 2014
Year: 2014

Synthesis is the automatic construction of a system from its specification. In classical synthesis algorithms, it is always assumed that the system is "constructed from scratch" rather than composed from reusable components. This, of course, rarely happens in real life, where almost every non-trivial commercial software system relies heavily on using libraries of reusable components. Furthermore, other contexts, such as web-service orchestration, can be modeled as synthesis of a system from a library of components. Recently, Lustig and Vardi introduced dataflow and control-flow synthesis from libraries of reusable components. They proved that dataflow synthesis is undecidable, while control-flow synthesis is decidable. In this work, we consider the problem of control-flow synthesis from libraries of probabilistic components . We show that this more general problem is also decidable.
L1 Control Theoretic Smoothing Splines
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we propose control theoretic smoothing splines with L1 optimality for reducing the number of parameters that describes the fitted curve as well as removing outlier data. A control theoretic spline is a smoothing spline that is generated as an output of a given linear dynamical system. Conventional design requires exactly the same number of base functions as given data, and the result is not robust against outliers. To solve these problems, we propose to use L1 optimality, that is, we use the L1 norm for the regularization term and/or the empirical risk term. The optimization is described by a convex optimization, which can be efficiently solved via a numerical optimization software. A numerical example shows the effectiveness of the proposed method.
An Approach for Controlling Faults in Wireless Sensor Networks Using Clustering
Venue: arXiv cs.NI 2014
Year: 2014

Fault control and tolerance in wireless sensor network is a challenging problem because of limited energy, bandwidth, and computational complexity. While facing numerous threats these severely resource constrained nodes are responsible for data collection, data processing, localization, time synchronization aggregation and data forwarding. One of the effective approaches to control and tolerate these threats is through clustering. In this paper we present a new method called Efficient Fault Control Mechanism for fault controlling in wireless sensor networks based on clustering and cluster-head selection. Simulation results show Efficient Fault Control Mechanism has better performance over state of art methods.
Secret message capacity of a line network
Venue: arXiv cs.IT 2014
Year: 2014

We investigate the problem of information theoretically secure communication in a line network with erasure channels and state feedback. We consider a spectrum of cases for the private randomness that intermediate nodes can generate, ranging from having intermediate nodes generate unlimited private randomness, to having intermediate nodes generate no private randomness, and all cases in between. We characterize the secret message capacity when either only one of the channels is eavesdropped or all of the channels are eavesdropped, and we develop polynomial time algorithms that achieve these capacities. We also give an outer bound for the case where an arbitrary number of channels is eavesdropped. Our work is the first to characterize the secrecy capacity of a network of arbitrary size, with imperfect channels and feedback. As a side result, we derive the secret key and secret message capacity of an one-hop network, when the source has limited randomness.
Lower Bounds on the Critical Density in the Hard Disk Model via Optimized Metrics
Venue: arXiv cs.CC 2014
Year: 2014

We prove a new lower bound on the critical density $ρ_c$ of the hard disk model, i.e., the density below which it is possible to efficiently sample random configurations of $n$ non-overlapping disks in a unit torus. We use a classic Markov chain which moves one disk at a time, but with an improved path coupling analysis. Our main tool is an optimized metric on neighboring pairs of configurations, i.e., configurations that differ in the position of a single disk: we define a metric that depends on the difference in these positions, and which approaches zero continuously as they coincide. This improves the previous lower bound $ρ_c \ge 1/8$ to $ρ_c \ge 0.154$.
Obstructions of Turkish Public Organizations Getting ISO/IEC 27001 Certified
Venue: arXiv cs.CY 2014
Year: 2014

In this paper; a comparison has been made among the Articles contained in the ISO/IEC 27001 Standard and the Articles of the Civil Servants Law No 657, which should essentially be complied with by the personnel employed within the bodies of public institutions in Turkey; and efforts have been made in order to emphasize the consistent Articles; and in addition, the matters, which should be paid attention by the public institutions indenting to obtain the ISO/IEC 27001 certificate for the Articles of the Civil Servants Law No 657 which are not consistent with the ISO/IEC 27001 certification process, have been mentioned. Furthermore, solution offers have been presented in order to ensure that the mentioned Articles become consistent with the ISO/IEC 27001 certification process.
Meteorological time series forecasting with pruned multi-layer perceptron and 2-stage Levenberg-Marquardt method
Venue: arXiv cs.NE 2014
Year: 2014

A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where "all" configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). These two tasks must be repeated depending on the knowledge of each new problem studied, making the process, long, laborious and not systematically robust. In this paper a pruning process is proposed. This method allows, during the training phase, to carry out an inputs selecting method activating (or not) inter-nodes connections in order to verify if forecasting is improved. We propose to use iteratively the popular damped least-squares method to activate inputs and neurons. A first pass is applied to 10% of the learning sample to determine weights significantly different from 0 and delete other. Then a classical batch process based on LMA is used with the new MLP. The validation is done using 25 measured meteorological TS and cross-comparing the prediction results of the classical LMA and the 2-stage LMA.
Performance Estimation of 2*4 MIMO-MC-CDMA Using Convolution Code in Different Modulation Technique using ZF Detection Scheme
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we estimate the performance of 2*4 MIMO-MC-CDMA system using convolution code in MATLAB which highly reduces BER. MC-CDMA (Multi Carrier Code Division for Multiple Access) is a multiuser and multiple access system which is formed by the combination of OFDM and CDMA and convolution encoding scheme is used in encoder of CDMA as FEC (Forward Error Correction) code to reduce BER (Bit Error Rate). MC-CDMA system is a multicarrier system in which single wideband frequency selective carrier is converted into parallel narrowband flat fading multiple sub-carriers to optimize the performance of system. Now this system further improved by combination of 2*4 MIMO (Multiple Input Multiple Output) system which utilizes ZF (Zero Forcing) decoder at the receiver to reduce BER and also half rate convolutionally encoded Alamouti STBC (Space Time Block Code) block code as transmit diversity of MIMO for multiple transmission of data through multiple transmit antenna. Main advantage of using MIMO-MC-CDMA using convolution code is to reduce the complexity of system and to reduce BER with increased gain. In this paper we analyze system performance in different modulation schemes like, QPSK, 8PSK, 8QAM, 16QAM, 32QAM and 64QAM in Rayleigh fading channel using MATLAB.
On Codes Over $\mathbb{Z}_{p^{s}}$ with the Extended Lee Weight
Venue: arXiv cs.IT 2014
Year: 2014

We consider codes over $\mathbb{Z}_{p^s}$ with the extended Lee weight. We find Singleton bounds with respect to this weight and define MLDS and MLDR codes accordingly. We also consider the kernels of these codes and the notion of independence of vectors in this space. We investigate the linearity and duality of the Gray images of codes over $\mathbb{Z}_{p^s}$.
Négociation de spectre dans les réseaux de radio cognitive
Venue: arXiv cs.MA 2014
Year: 2014

In this report, we propose a technique using negotiation based on multi-agent system (MAS) in the context of cognitive radio network (CRN). The agents are particularly suited to provide responsive solutions to complex problems such as the negotiation of the spectrum in CRN. We have implemented our proposed solution with JADE (Java Agent Development Framework) and we have also evaluate the proposed solution to show its interest.