OpenRaiser/Intern-Atlas huggingface dataset:
Source-Channel Coding and Separation for Generalized Communication Systems
Venue: arXiv cs.IT 2009
Year: 2009

We consider transmission of stationary and ergodic sources over non-ergodic composite channels with channel state information at the receiver (CSIR). Previously we introduced alternate capacity definitions to Shannon capacity, including the capacity versus outage and the expected capacity. These generalized definitions relax the constraint of Shannon capacity that all transmitted information must be decoded at the receiver. In this work alternate end-to-end distortion metrics such as the distortion versus outage and the expected distortion are introduced to relax the constraint that a single distortion level has to be maintained for all channel states. For transmission of stationary and ergodic sources over stationary and ergodic channels, the classical Shannon separation theorem enables separate design of source and channel codes and guarantees optimal performance. For generalized communication systems, we show that different end-to-end distortion metrics lead to different conclusions about separation optimality even for the same source and channel models.
Toward Understanding Friendship in Online Social Networks
Venue: arXiv cs.CY 2009
Year: 2009

All major on-line social networks, such as MySpace, Facebook, LiveJournal, and Orkut, are built around the concept of friendship. It is not uncommon for a social network participant to have over 100 friends. A natural question arises: are they all real friends of hers, or does she mean something different when she calls them "friends?" Speaking in other words, what is the relationship between off-line (real, traditional) friendship and its on-line (virtual) namesake? In this paper, we use sociological data to suggest that there is a significant difference between the concepts of virtual and real friendships. We further investigate the structure of on-line friendship and observe that it follows the Pareto (or double Pareto) distribution and is subject to age stratification but not to gender segregation. We introduce the concept of digital personality that quantifies the willingness of a social network participant to engage in virtual friendships.
ScALPEL: A Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring
Venue: arXiv cs.DC 2009
Year: 2009

As supercomputers continue to grow in scale and capabilities, it is becoming increasingly difficult to isolate processor and system level causes of performance degradation. Over the last several years, a significant number of performance analysis and monitoring tools have been built/proposed. However, these tools suffer from several important shortcomings, particularly in distributed environments. In this paper we present ScALPEL, a Scalable Adaptive Lightweight Performance Evaluation Library for application performance monitoring at the functional level. Our approach provides several distinct advantages. First, ScALPEL is portable across a wide variety of architectures, and its ability to selectively monitor functions presents low run-time overhead, enabling its use for large-scale production applications. Second, it is run-time configurable, enabling both dynamic selection of functions to profile as well as events of interest on a per function basis. Third, our approach is transparent in that it requires no source code modifications. Finally, ScALPEL is implemented as a pluggable unit by reusing existing performance monitoring frameworks such as Perfmon and PAPI and extending them to support both sequential and MPI applications.
Workflow Patterns in Process Modeling
Venue: arXiv cs.SE 2009
Year: 2009

This paper proposes an introduction to one of the newest modelling methods, an executable model based on workflows. We present the terminology for some basic workflow patterns, as described in the Workflow Management Coalition Terminology and Glossary.
Improved identity-based identification using correcting codes
Venue: arXiv cs.CR 2009
Year: 2009

In this paper, a new identity-based identification scheme based on error-correcting codes is proposed. Two well known code-based schemes are combined : the signature scheme by Courtois, Finiasz and Sendrier and an identification scheme by Stern. A proof of security for the scheme in the Random Oracle Model is given.
Spectral Efficiency Optimized Adaptive Transmission for Cognitive Radios in an Interference Channel
Venue: arXiv cs.IT 2009
Year: 2009

In this paper, we consider a primary and a cognitive user transmitting over a wireless fading interference channel. The primary user transmits with a constant power and utilizes an adaptive modulation and coding (AMC) scheme satisfying a bit error rate requirement. We propose a link adaptation scheme to maximize the average spectral efficiency of the cognitive radio, while a minimum required spectral efficiency for the primary user is provisioned. The resulting problem is constrained to also satisfy a bit error rate requirement and a power constraint for the cognitive link. The AMC mode selection and power control at the cognitive transmitter is optimized based on the scaled signal to noise plus interference ratio feedback of both links. The problem is then cast as a nonlinear discrete optimization problem for which a fast and efficient suboptimum solution is presented. We also present a scheme with rate adaption and a constant power. An important characteristic of the proposed schemes is that no negotiation between the users is required. Comparisons with underlay and interweave approaches to cognitive radio with adaptive transmission demonstrate the efficiency of the proposed solutions.
Heaps Simplified
Venue: arXiv cs.DS 2009
Year: 2009

The heap is a basic data structure used in a wide variety of applications, including shortest path and minimum spanning tree algorithms. In this paper we explore the design space of comparison-based, amortized-efficient heap implementations. From a consideration of dynamic single-elimination tournaments, we obtain the binomial queue, a classical heap implementation, in a simple and natural way. We give four equivalent ways of representing heaps arising from tournaments, and we obtain two new variants of binomial queues, a one-tree version and a one-pass version. We extend the one-pass version to support key decrease operations, obtaining the {\em rank-pairing heap}, or {\em rp-heap}. Rank-pairing heaps combine the performance guarantees of Fibonacci heaps with simplicity approaching that of pairing heaps. Like pairing heaps, rank-pairing heaps consist of trees of arbitrary structure, but these trees are combined by rank, not by list position, and rank changes, but not structural changes, cascade during key decrease operations.
Optimal Interdiction of Unreactive Markovian Evaders
Venue: arXiv cs.DM 2009
Year: 2009

The interdiction problem arises in a variety of areas including military logistics, infectious disease control, and counter-terrorism. In the typical formulation of network interdiction, the task of the interdictor is to find a set of edges in a weighted network such that the removal of those edges would maximally increase the cost to an evader of traveling on a path through the network. Our work is motivated by cases in which the evader has incomplete information about the network or lacks planning time or computational power, e.g. when authorities set up roadblocks to catch bank robbers, the criminals do not know all the roadblock locations or the best path to use for their escape. We introduce a model of network interdiction in which the motion of one or more evaders is described by Markov processes and the evaders are assumed not to react to interdiction decisions. The interdiction objective is to find an edge set of size B, that maximizes the probability of capturing the evaders. We prove that similar to the standard least-cost formulation for deterministic motion this interdiction problem is also NP-hard. But unlike that problem our interdiction problem is submodular and the optimal solution can be approximated within 1-1/e using a greedy algorithm. Additionally, we exploit submodularity through a priority evaluation strategy that eliminates the linear complexity scaling in the number of network edges and speeds up the solution by orders of magnitude. Taken together the results bring closer the goal of finding realistic solutions to the interdiction problem on global-scale networks.
Faith in the Algorithm, Part 1: Beyond the Turing Test
Venue: arXiv cs.CY 2009
Year: 2009

Since the Turing test was first proposed by Alan Turing in 1950, the primary goal of artificial intelligence has been predicated on the ability for computers to imitate human behavior. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution to intelligence. Another goal for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification. This article surveys various systems that contribute to the advancement of human and social intelligence.
How to Play Unique Games on Expanders
Venue: arXiv cs.DS 2009
Year: 2009

In this note we improve a recent result by Arora, Khot, Kolla, Steurer, Tulsiani, and Vishnoi on solving the Unique Games problem on expanders. Given a $(1-\varepsilon)$-satisfiable instance of Unique Games with the constraint graph $G$, our algorithm finds an assignment satisfying at least a $1- C \varepsilon/h_G$ fraction of all constraints if $\varepsilon < c λ_G$ where $h_G$ is the edge expansion of $G$, $λ_G$ is the second smallest eigenvalue of the Laplacian of $G$, and $C$ and $c$ are some absolute constants.
De-amortized Cuckoo Hashing: Provable Worst-Case Performance and Experimental Results
Venue: arXiv cs.DS 2009
Year: 2009

Cuckoo hashing is a highly practical dynamic dictionary: it provides amortized constant insertion time, worst case constant deletion time and lookup time, and good memory utilization. However, with a noticeable probability during the insertion of n elements some insertion requires Ω(log n) time. Whereas such an amortized guarantee may be suitable for some applications, in other applications (such as high-performance routing) this is highly undesirable. Recently, Kirsch and Mitzenmacher (Allerton '07) proposed a de-amortization of cuckoo hashing using various queueing techniques that preserve its attractive properties. Kirsch and Mitzenmacher demonstrated a significant improvement to the worst case performance of cuckoo hashing via experimental results, but they left open the problem of constructing a scheme with provable properties. In this work we follow Kirsch and Mitzenmacher and present a de-amortization of cuckoo hashing that provably guarantees constant worst case operations. Specifically, for any sequence of polynomially many operations, with overwhelming probability over the randomness of the initialization phase, each operation is performed in constant time. Our theoretical analysis and experimental results indicate that the scheme is highly efficient, and provides a practical alternative to the only other known dynamic dictionary with such worst case guarantees, due to Dietzfelbinger and Meyer auf der Heide (ICALP '90).
Breaking Value Symmetry
Venue: arXiv cs.AI 2009
Year: 2009

Symmetry is an important factor in solving many constraint satisfaction problems. One common type of symmetry is when we have symmetric values. In a recent series of papers, we have studied methods to break value symmetries. Our results identify computational limits on eliminating value symmetry. For instance, we prove that pruning all symmetric values is NP-hard in general. Nevertheless, experiments show that much value symmetry can be broken in practice. These results may be useful to researchers in planning, scheduling and other areas as value symmetry occurs in many different domains.
Teacher's Evaluation - a Component of Quality Assessment System
Venue: arXiv cs.CY 2009
Year: 2009

One of the most important activities to increase the importance and the responsibility of the higher education is the quality management, assessment and evaluation. Starting from 2006, a national mechanism was created in Romania and all the educational institutions have to apply a concrete algorithm to ensure the internal evaluation, the external evaluation and, the most important, to increase the quality of the educational process. This paper presents the implementation of the quality assessment in "Tibiscus" University of Timisoara, particularly at the Faculty of Computers and Applied Computer Science.
Leveraging Discarded Samples for Tighter Estimation of Multiple-Set Aggregates
Venue: arXiv cs.DB 2009
Year: 2009

Many datasets such as market basket data, text or hypertext documents, and sensor observations recorded in different locations or time periods, are modeled as a collection of sets over a ground set of keys. We are interested in basic aggregates such as the weight or selectivity of keys that satisfy some selection predicate defined over keys' attributes and membership in particular sets. This general formulation includes basic aggregates such as the Jaccard coefficient, Hamming distance, and association rules. On massive data sets, exact computation can be inefficient or infeasible. Sketches based on coordinated random samples are classic summaries that support approximate query processing. Queries are resolved by generating a sketch (sample) of the union of sets used in the predicate from the sketches these sets and then applying an estimator to this union-sketch. We derive novel tighter (unbiased) estimators that leverage sampled keys that are present in the union of applicable sketches but excluded from the union sketch. We establish analytically that our estimators dominate estimators applied to the union-sketch for {\em all queries and data sets}. Empirical evaluation on synthetic and real data reveals that on typical applications we can expect a 25%-4 fold reduction in estimation error.
Compressive Sensing Using Low Density Frames
Venue: arXiv cs.IT 2009
Year: 2009

We consider the compressive sensing of a sparse or compressible signal ${\bf x} \in {\mathbb R}^M$. We explicitly construct a class of measurement matrices, referred to as the low density frames, and develop decoding algorithms that produce an accurate estimate $\hat{\bf x}$ even in the presence of additive noise. Low density frames are sparse matrices and have small storage requirements. Our decoding algorithms for these frames have $O(M)$ complexity. Simulation results are provided, demonstrating that our approach significantly outperforms state-of-the-art recovery algorithms for numerous cases of interest. In particular, for Gaussian sparse signals and Gaussian noise, we are within 2 dB range of the theoretical lower bound in most cases.
Resource Allocation for Multiple Concurrent In-Network Stream-Processing Applications
Venue: arXiv cs.DC 2009
Year: 2009

This paper investigates the operator mapping problem for in-network stream-processing applications. In-network stream-processing amounts to applying one or more trees of operators in steady-state, to multiple data objects that are continuously updated at different locations in the network. The goal is to compute some final data at some desired rate. Different operator trees may share common subtrees. Therefore, it may be possible to reuse some intermediate results in different application trees. The first contribution of this work is to provide complexity results for different instances of the basic problem, as well as integer linear program formulations of various problem instances. The second second contribution is the design of several polynomial-time heuristics. One of the primary objectives of these heuristics is to reuse intermediate results shared by multiple applications. Our quantitative comparisons of these heuristics in simulation demonstrates the importance of choosing appropriate processors for operator mapping. It also allow us to identify a heuristic that achieves good results in practice.
Modeling the Experience of Emotion
Venue: arXiv cs.AI 2009
Year: 2009

Affective computing has proven to be a viable field of research comprised of a large number of multidisciplinary researchers resulting in work that is widely published. The majority of this work consists of computational models of emotion recognition, computational modeling of causal factors of emotion and emotion expression through rendered and robotic faces. A smaller part is concerned with modeling the effects of emotion, formal modeling of cognitive appraisal theory and models of emergent emotions. Part of the motivation for affective computing as a field is to better understand emotional processes through computational modeling. One of the four major topics in affective computing is computers that have emotions (the others are recognizing, expressing and understanding emotions). A critical and neglected aspect of having emotions is the experience of emotion (Barrett, Mesquita, Ochsner, and Gross, 2007): what does the content of an emotional episode look like, how does this content change over time and when do we call the episode emotional. Few modeling efforts have these topics as primary focus. The launch of a journal on synthetic emotions should motivate research initiatives in this direction, and this research should have a measurable impact on emotion research in psychology. I show that a good way to do so is to investigate the psychological core of what an emotion is: an experience. I present ideas on how the experience of emotion could be modeled and provide evidence that several computational models of emotion are already addressing the issue.
Tagging multimedia stimuli with ontologies
Venue: arXiv cs.AI 2009
Year: 2009

Successful management of emotional stimuli is a pivotal issue concerning Affective Computing (AC) and the related research. As a subfield of Artificial Intelligence, AC is concerned not only with the design of computer systems and the accompanying hardware that can recognize, interpret, and process human emotions, but also with the development of systems that can trigger human emotional response in an ordered and controlled manner. This requires the maximum attainable precision and efficiency in the extraction of data from emotionally annotated databases While these databases do use keywords or tags for description of the semantic content, they do not provide either the necessary flexibility or leverage needed to efficiently extract the pertinent emotional content. Therefore, to this extent we propose an introduction of ontologies as a new paradigm for description of emotionally annotated data. The ability to select and sequence data based on their semantic attributes is vital for any study involving metadata, semantics and ontological sorting like the Semantic Web or the Social Semantic Desktop, and the approach described in the paper facilitates reuse in these areas as well.
Artificial table testing dynamically adaptive systems
Venue: arXiv cs.SE 2009
Year: 2009

Dynamically Adaptive Systems (DAS) are systems that modify their behavior and structure in response to changes in their surrounding environment. Critical mission systems increasingly incorporate adaptation and response to the environment; examples include disaster relief and space exploration systems. These systems can be decomposed in two parts: the adaptation policy that specifies how the system must react according to the environmental changes and the set of possible variants to reconfigure the system. A major challenge for testing these systems is the combinatorial explosions of variants and envi-ronment conditions to which the system must react. In this paper we focus on testing the adaption policy and propose a strategy for the selection of envi-ronmental variations that can reveal faults in the policy. Artificial Shaking Table Testing (ASTT) is a strategy inspired by shaking table testing (STT), a technique widely used in civil engineering to evaluate building's structural re-sistance to seismic events. ASTT makes use of artificial earthquakes that simu-late violent changes in the environmental conditions and stresses the system adaptation capability. We model the generation of artificial earthquakes as a search problem in which the goal is to optimize different types of envi-ronmental variations.
How do Wireless Chains Behave? The Impact of MAC Interactions
Venue: arXiv cs.NI 2009
Year: 2009

In a Multi-hop Wireless Networks (MHWN), packets are routed between source and destination using a chain of intermediate nodes; chains are a fundamental communication structure in MHWNs whose behavior must be understood to enable building effective protocols. The behavior of chains is determined by a number of complex and interdependent processes that arise as the sources of different chain hops compete to transmit their packets on the shared medium. In this paper, we show that MAC level interactions play the primary role in determining the behavior of chains. We evaluate the types of chains that occur based on the MAC interactions between different links using realistic propagation and packet forwarding models. We discover that the presence of destructive interactions, due to different forms of hidden terminals, does not impact the throughput of an isolated chain significantly. However, due to the increased number of retransmissions required, the amount of bandwidth consumed is significantly higher in chains exhibiting destructive interactions, substantially influencing the overall network performance. These results are validated by testbed experiments. We finally study how different types of chains interfere with each other and discover that well behaved chains in terms of self-interference are more resilient to interference from other chains.
Footprints in Local Reasoning
Venue: arXiv cs.SE 2009
Year: 2009

Local reasoning about programs exploits the natural local behaviour common in programs by focussing on the footprint - that part of the resource accessed by the program. We address the problem of formally characterising and analysing the footprint notion for abstract local functions introduced by Calcagno, O Hearn and Yang. With our definition, we prove that the footprints are the only essential elements required for a complete specification of a local function. We formalise the notion of small specifications in local reasoning and show that for well-founded resource models, a smallest specification always exists that only includes the footprints, and also present results for the non-well-founded case. Finally, we use this theory of footprints to investigate the conditions under which the footprints correspond to the smallest safe states. We present a new model of RAM in which, unlike the standard model, the footprints of every program correspond to the smallest safe states, and we also identify a general condition on the primitive commands of a programming language which guarantees this property for arbitrary models.
Stochastic Constraint Programming: A Scenario-Based Approach
Venue: arXiv cs.AI 2009
Year: 2009

To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contain both decision variables, which we can set, and stochastic variables, which follow a discrete probability distribution. We provide a semantics for stochastic constraint programs based on scenario trees. Using this semantics, we can compile stochastic constraint programs down into conventional (non-stochastic) constraint programs. This allows us to exploit the full power of existing constraint solvers. We have implemented this framework for decision making under uncertainty in stochastic OPL, a language which is based on the OPL constraint modelling language [Hentenryck et al., 1999]. To illustrate the potential of this framework, we model a wide range of problems in areas as diverse as portfolio diversification, agricultural planning and production/inventory management.