OpenRaiser/Intern-Atlas huggingface dataset:
On the Secrecy of Interference-Limited Networks under Composite Fading Channels
Venue: arXiv cs.IT 2014
Year: 2014

This paper deals with the secrecy capacity of the radio channel in interference-limited regime. We assume that interferers are uniformly scattered over the network area according to a Point Poisson Process and the channel model consists of path-loss, log-normal shadowing and Nakagami-m fading. Both the probability of non-zero secrecy capacity and the secrecy outage probability are then derived in closed-form expressions using tools of stochastic geometry and higher-order statistics. Our numerical results show how the secrecy metrics are affected by the disposition of the desired receiver, the eavesdropper and the legitimate transmitter.
Distributed Discovery Clients for Spectrum Allocation
Venue: arXiv cs.NI 2014
Year: 2014

By using a distributed P2P system where the agents reside in in microprocessors already present in most radio nodes like Wi-Fi access points, base stations, TVs connected to Internet etc, these agents can discover other agents over the back-haul network. As a result, client node lists (similar to neighbor lists used in 3GPP) are created. An alternative is to use a centralized database. Why this best is done by distributed agents is discussed in this paper along with security considerations. Examples of other applications which will benefit from this system is also presented.
Optimal Radio Resource Allocation for Hybrid Traffic in Cellular Networks: Traffic Analysis and Implementation
Venue: arXiv cs.NI 2014
Year: 2014

In part I of this paper, a distributed and a centralized architecture for an optimal radio resource allocation aware of the traffic delay-tolerance nature, user subscription type, and application usage variations were developed. In the current article, a transmission overhead analysis of the aforementioned distributed and a centralized architectures is investigated and it is proved that the centralized scheme endures a significantly lower transmission overhead than does the distributed approach. Furthermore, the lower bounds of the transmission overhead for both the centralized and the distributed architectures are derived. Moreover, a sensitivity analysis of the resource allocation procedures of the aforesaid centralized and distributed architectures to the changes in the number of users in the system is presented. Besides, a sensitivity analysis of the centralized and distributed approaches to the temporal changes in application usages are investigated. Ultimately, the transmission overhead and sensitivity relevant statements are verified through appropriate simulations. And last but not the least, a real-world implementation of the resource allocation methods developed in Part I is provided.
Benchmarking DataStax Enterprise/Cassandra with HiBench
Venue: arXiv cs.DC 2014
Year: 2014

This report evaluates the new analytical capabilities of DataStax Enterprise (DSE) [1] through the use of standard Hadoop workloads. In particular, we run experiments with CPU and I/O bound micro-benchmarks as well as OLAP-style analytical query workloads. The performed tests should show that DSE is capable of successfully executing Hadoop applications without the need to adapt them for the underlying Cassandra distributed storage system [2]. Due to the Cassandra File System (CFS) [3], which supports the Hadoop Distributed File System API, Hadoop stack applications should seamlessly run in DSE. The report is structured as follows: Section 2 provides a brief description of the technologies involved in our study. An overview of our used hardware and software components of the experimental environment is given in Section 3. Our benchmark methodology is defined in Section 4. The performed experiments together with the evaluation of the results are presented in Section 5. Finally, Section 6 concludes with lessons learned.
Definition of Visual Speech Element and Research on a Method of Extracting Feature Vector for Korean Lip-Reading
Venue: arXiv cs.CL 2014
Year: 2014

In this paper, we defined the viseme (visual speech element) and described about the method of extracting visual feature vector. We defined the 10 visemes based on vowel by analyzing of Korean utterance and proposed the method of extracting the 20-dimensional visual feature vector, combination of static features and dynamic features. Lastly, we took an experiment in recognizing words based on 3-viseme HMM and evaluated the efficiency.
Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning
Venue: arXiv cs.CL 2014
Year: 2014

This paper aims to explore the effect of prior disambiguation on neural network- based compositional models, with the hope that better semantic representations for text compounds can be produced. We disambiguate the input word vectors before they are fed into a compositional deep net. A series of evaluations shows the positive effect of prior disambiguation for such deep models.
Near-Optimal Linear Precoding with Low Complexity for Massive MIMO
Venue: arXiv cs.IT 2014
Year: 2014

Linear precoding techniques can achieve near- optimal capacity due to the special channel property in down- link massive MIMO systems, but involve high complexity since complicated matrix inversion of large size is required. In this paper, we propose a low-complexity linear precoding scheme based on the Gauss-Seidel (GS) method. The proposed scheme can achieve the capacity-approaching performance of the classical linear precoding schemes in an iterative way without complicated matrix inversion, which can reduce the overall complexity by one order of magnitude. The performance guarantee of the proposed GS-based precoding is analyzed from the following three aspects. At first, we prove that GS-based precoding satisfies the transmit power constraint. Then, we prove that GS-based precoding enjoys a faster convergence rate than the recently proposed Neumann-based precoding. At last, the convergence rate achieved by GS-based precoding is quantified, which reveals that GS-based precoding converges faster with the increasing number of BS antennas. To further accelerate the convergence rate and reduce the complexity, we propose a zone-based initial solution to GS-based precoding, which is much closer to the final solution than the traditional initial solution. Simulation results demonstrate that the proposed scheme outperforms Neumann- based precoding, and achieves the exact capacity-approaching performance of the classical linear precoding schemes with only a small number of iterations both in Rayleigh fading channels and spatially correlated channels.
ROSS User's Guide and Reference Manual (Version 1.0)
Venue: arXiv cs.AI 2014
Year: 2014

The ROSS method is a new approach in the area of knowledge representation that is useful for many artificial intelligence and natural language understanding representation and reasoning tasks. (ROSS stands for "Representation", "Ontology", "Structure", "Star" language). ROSS is a physical symbol-based representational scheme. ROSS provides a complex model for the declarative representation of physical structure and for the representation of processes and causality. From the metaphysical perspective, the ROSS view of external reality involves a 4D model, wherein discrete single-time-point unit-sized locations with states are the basis for all objects, processes and aspects that can be modeled. ROSS includes a language called "Star" for the specification of ontology classes. The ROSS method also includes a formal scheme called the "instance model". Instance models are used in the area of natural language meaning representation to represent situations. This document is an in-depth specification of the ROSS method.
Cycle slipping in nonlinear circuits under periodic nonlinearities and time delays
Venue: arXiv cs.SY 2014
Year: 2014

Phase-locked loops (PLL), Costas loops and other synchronizing circuits are featured by the presence of a nonlinear phase detector, described by a periodic nonlinearity. In general, nonlinearities can cause complex behavior of the system such multi-stability and chaos. However, even phase locking may be guaranteed under any initial conditions, the transient behavior of the circuit can be unsatisfactory due to the cycle slipping. Growth of the phase error caused by cycle slipping is undesirable, leading e.g. to demodulation and decoding errors. This makes the problem of estimating the phase error oscillations and number of slipped cycles in nonlinear PLL-based circuits extremely important for modern telecommunications. Most mathematical results in this direction, available in the literature, examine the probability density of the phase error and expected number of slipped cycles under stochastic noise in the signal. At the same time, cycle slipping occurs also in deterministic systems with periodic nonlinearities, depending on the initial conditions, properties of the linear part and the periodic nonlinearity and other factors such as delays in the loop. In the present paper we give analytic estimates for the number of slipped cycles in PLL-based systems, governed by integro-differential equations, allowing to capture effects of high-order dynamics, discrete and distributed delays. We also consider the effects of singular small parameter perturbations on the cycle slipping behavior.
Differential Distributed Space-Time Coding with Imperfect Synchronization in Frequency-Selective Channels
Venue: arXiv cs.IT 2014
Year: 2014

Differential distributed space-time coding (D-DSTC) is a cooperative transmission technique that can improve diversity in wireless relay networks in the absence of channel information. Conventionally, it is assumed that channels are flat-fading and relays are perfectly synchronized at the symbol level. However, due to the delay spread in broadband systems and the distributed nature of relay networks, these assumptions may be violated. Hence, inter-symbol interference (ISI) may appear. This paper proposes a new differential encoding and decoding process for D-DSTC systems with multiple relays over slow frequency-selective fading channels with imperfect synchronization. The proposed method overcomes the ISI caused by frequency-selectivity and is robust against synchronization errors while not requiring any channel information at the relays and destination. Moreover, the maximum possible diversity with a decoding complexity similar to that of the conventional D-DSTC is attained. Simulation results are provided to show the performance of the proposed method in various scenarios.
Hierarchical and Matrix Structures in a Large Organizational Email Network: Visualization and Modeling Approaches
Venue: arXiv cs.SI 2014
Year: 2014

This paper presents findings from a study of the email network of a large scientific research organization, focusing on methods for visualizing and modeling organizational hierarchies within large, complex network datasets. In the first part of the paper, we find that visualization and interpretation of complex organizational network data is facilitated by integration of network data with information on formal organizational divisions and levels. By aggregating and visualizing email traffic between organizational units at various levels, we derive several insights into how large subdivisions of the organization interact with each other and with outside organizations. Our analysis shows that line and program management interactions in this organization systematically deviate from the idealized pattern of interaction prescribed by "matrix management." In the second part of the paper, we propose a power law model for predicting degree distribution of organizational email traffic based on hierarchical relationships between managers and employees. This model considers the influence of global email announcements sent from managers to all employees under their supervision, and the role support staff play in generating email traffic, acting as agents for managers. We also analyze patterns in email traffic volume over the course of a work week.
Probabilistic Modeling and Simulation of Transmission Line Temperatures under Fluctuating Power Flows
Venue: arXiv cs.SY 2014
Year: 2014

Increasing shares of fluctuating renewable energy sources induce higher and higher power flow variability at the transmission level. The question arises as to what extent existing networks can absorb additional fluctuating power injection without exceeding thermal limits. At the same time, the resulting power flow characteristics call for revisiting classical approaches to line temperature prediction. This paper presents a probabilistic modeling and simulation methodology for estimating the occurrence of critical line temperatures in the presence of fluctuating power flows. Cumbersome integration of the dynamic thermal equations at each Monte Carlo simulation trial is sped up by a specific algorithm that makes use of a variance reduction technique adapted from the telecommunications field. The substantial reduction in computational time allows estimations closer to real time, relevant to short-term operational assessments. A case study performed on a single line model provides fundamental insights into the probability of hitting critical line temperatures under given power flow fluctuations. A transmission system application shows how the proposed method can be used for a fast yet accurate operational assessment.
Automatic Synthesis of Test Cases to Identify Software Redundancy
Venue: arXiv cs.SE 2014
Year: 2014

Software system can include redundant implementation elements, such as, different methods that can produce indistinguishable results. This type of redundancy is called intrinsic if it is already available in the software, although not intentionally planned. Redundancy can be a key element to increase the reliability of a system. Some fault tolerance and self-healing techniques exploit the redundancy to avoid failures at runtime. Unfortunately, inferring which operations are equivalent manually can be expensive and error prone. A technique proposed in previous work allows to automatically synthesizes method sequences that are equivalent to a target method. However this technique needs an execution scenario to work. Currently, this execution scenario is generated manually that is expensive and makes the technique hard to use. This paper proposes a technique to generate execution scenarios for a target method for which we are searching equivalent sequences. The experimental results obtained on the Java class Stack show that the proposed approach correctly generates execution scenarios within reasonable execution time. Besides, the execution scenarios generated allow to maximize the effectiveness of the technique described above.
Some Notes on Constructions of Binary Sequences with Optimal Autocorrelation
Venue: arXiv cs.IT 2014
Year: 2014

Constructions of binary sequences with low autocorrelation are considered in the paper. Based on recent progresses about this topic, several more general constructions of binary sequences with optimal autocorrelations and other low autocorrelations are presented.
The Complexity of DC-Switching Problems
Venue: arXiv cs.CC 2014
Year: 2014

This report provides a comprehensive complexity study of line switching in the Linear DC model for the feasibility problem and the optimization problems of maximizing the load that can be served (maximum switching flow, MSF) and minimizing generation cost (optimal transmission switching, OTS). Our results show that these problems are NP-complete and that there is no fully polynomial-time approximation scheme for planar networks with a maximum-node degree of 3. Additionally, we demonstrate that the problems are still NP-hard if we restrict the network structure to cacti with a maximum degree of 3. We also show that the optimization problems can not be approximated within any constant factor.
Deterministic Broadcasting and Random Linear Network Coding in Mobile Ad Hoc Networks
Venue: arXiv cs.NI 2014
Year: 2014

Network coding has been successfully used in the past for efficient broadcasting in wireless multi-hop networks. Two coding approaches are suitable for mobile networks; Random Linear Network Coding (RLNC) and XOR-based coding. In this work, we make the observation that RLNC provides increased resilience to packet losses compared to XOR-based coding. We develop an analytical model that justifies our intuition. However, the model also reveals that combining RLNC with probabilistic forwarding, which is the approach taken in the literature, may significantly impact RLNC's performance. Therefore, we take the novel approach to combine RLNC with a deterministic broadcasting algorithm in order to prune transmissions. More specifically, we propose a Connected Dominating Set (CDS) based algorithm that works in synergy with RLNC on the "packet generation level". Since managing packet generations is a key issue in RLNC, we propose a distributed scheme, which is also suitable for mobile environments and does not compromise the coding efficiency. We show that the proposed algorithm outperforms XOR-based as well as RLNC-based schemes even when global knowledge is used for managing packet generations.
An Institution for Simple UML State Machines
Venue: arXiv cs.SE 2014
Year: 2014

We present an institution for UML state machines without hierarchical states. The interaction with UML class diagrams is handled via institutions for guards and actions, which provide dynamic components of states (such as valuations of attributes) but abstract away from details of class diagrams. We also study a notion of interleaving product, which captures the interaction of several state machines. The interleaving product construction is the basis for a semantics of composite structure diagrams, which can be used to specify the interaction of state machines. This work is part of a larger effort to build a framework for formal software development with UML, based on a heterogeneous approach using institutions.
Feedback Solution to Optimal Switching Problems with Switching Cost
Venue: arXiv cs.SY 2014
Year: 2014

The problem of optimal switching between nonlinear autonomous subsystems is investigated in this study where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to utilization of different modes. The mode sequence is unspecified and a switching cost term is used in the cost function for penalizing each switching. It is shown that once a switching cost is incorporated, the optimal cost-to-go function depends on the already active subsystem, i.e., the subsystem which was engaged in the previous time step. Afterwards, an approximate dynamic programming based method is developed which provides an approximation of the optimal solution to the problem in a feedback form and for different initial conditions. Finally, the performance of the method is analyzed through numerical examples.
Sparsity Exploiting Erasure Coding for Resilient Storage and Efficient I/O Access in Delta based Versioning Systems
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we study the problem of storing reliably an archive of versioned data. Specifically, we focus on systems where the differences (deltas) between subsequent versions rather than the whole objects are stored - a typical model for storing versioned data. For reliability, we propose erasure encoding techniques that exploit the sparsity of information in the deltas while storing them reliably in a distributed back-end storage system, resulting in improved I/O read performance to retrieve the whole versioned archive. Along with the basic techniques, we propose a few optimization heuristics, and evaluate the techniques' efficacy analytically and with numerical simulations.
Learning nonparametric differential equations with operator-valued kernels and gradient matching
Venue: arXiv cs.LG 2014
Year: 2014

Modeling dynamical systems with ordinary differential equations implies a mechanistic view of the process underlying the dynamics. However in many cases, this knowledge is not available. To overcome this issue, we introduce a general framework for nonparametric ODE models using penalized regression in Reproducing Kernel Hilbert Spaces (RKHS) based on operator-valued kernels. Moreover, we extend the scope of gradient matching approaches to nonparametric ODE. A smooth estimate of the solution ODE is built to provide an approximation of the derivative of the ODE solution which is in turn used to learn the nonparametric ODE model. This approach benefits from the flexibility of penalized regression in RKHS allowing for ridge or (structured) sparse regression as well. Very good results are shown on 3 different ODE systems.
An Experimental Study Towards Understanding Data Delivery Performance Over a WSN Link
Venue: arXiv cs.NI 2014
Year: 2014

The performance of a wireless sensor network (WSN) depends fundamentally on how its various parameters are configured under different link quality conditions. Surprisingly, even though WSNs have been extensively researched, there still lacks an in-depth understanding on how parameter configurations affect, in particular jointly, the performance under different link quality conditions. To fill the gap, this paper presents an extensive experimental study on the performance of a wireless sensor network link, where measurement data of more than 200 million packets were collected. Different from existing work, we consider major parameters from different layers together and measure their joint effects on key performance metrics under an extensive set of parameter configurations. Based on the large amount of measurement data, we investigate the impacts of these parameters and their joint configurations on the performance, introduce empirical models to theoretically reason the impacts, discuss implications of the obtained results, and suggest practical guidelines for parameter configurations. Through these, a comprehensive overview of parameter configuration impacts on the erformance is provided, which provides new insights on wireless link performance in WSNs.
Hostile Intent Enumeration using Soft Computing Techniques
Venue: arXiv cs.OH 2014
Year: 2014

In any tactical scenario, the successful quantification and triangulation of potential hostile elements is instrumental to minimize any casualties which might be incurred. The most commonly deployed infrastructures to cater to this have mostly been surveillance systems which only extract some data pertaining to the targets of interest in the area of observation and convey the information to the human operators. Accordingly, with the ever increasing rate at which warfare tactics are evolving, there has been a growing need for smarter solutions to this problem of hostile intent enumeration. Recently, a number of developments have been made to ameliorate the efficacy and the certitude with which this task is performed. This paper discusses two of the most prominent approaches which address this problem and posits the outline of a novel solution which seeks to address the shortcomings faced by the existing approaches.
Threshold Logic Computing: Memristive-CMOS Circuits for Fast Fourier Transform and Vedic Multiplication
Venue: arXiv cs.ET 2014
Year: 2014

Brain inspired circuits can provide an alternative solution to implement computing architectures taking advantage of fault tolerance and generalisation ability of logic gates. In this brief, we advance over the memristive threshold circuit configuration consisting of memristive averaging circuit in combination with operational amplifier and/or CMOS inverters in application to realizing complex computing circuits. The developed memristive threshold logic gates are used for designing FFT and multiplication circuits useful for modern microprocessors. Overall, the proposed threshold logic outperforms previous memristive-CMOS logic cells on every aspect, however, indicate a lower chip area, lower THD, and controllable leakage power, but a higher power dissipation with respect to CMOS logic.