OpenRaiser/Intern-Atlas huggingface dataset:
Improving Physical Layer Secrecy Using Full-Duplex Jamming Receivers
Venue: arXiv cs.IT 2013
Year: 2013

This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy performance as the system is interference-limited. In the literature, assuming that the receiver operates in half duplex (HD) mode, the aforementioned problem has been addressed via use of cooperating nodes who act as jammers to confound the eavesdropper. This paper investigates an alternative solution, which assumes the availability of a full duplex (FD) receiver. In particular, while receiving data, the receiver transmits jamming noise to degrade the eavesdropper channel. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. For the case in which global channel state information is available, we aim to design the optimal jamming covariance matrix that maximizes the secrecy rate and mitigates loop interference associated with the FD operation. We consider both fixed and optimal linear receiver design at the destination, and show that the optimal jamming covariance matrix is rank-1, and can be found via an efficient 1-D search. For the case in which only statistical information on the eavesdropper channel is available, the optimal power allocation is studied in terms of ergodic and outage secrecy rates. Simulation results verify the analysis and demonstrate substantial performance gain over conventional HD operation at the destination.
X- problem of value three
Venue: arXiv cs.DM 2013
Year: 2013

The X-problem of number 3 for one dimension and related observations are discussed
Balancing indivisible real-valued loads in arbitrary networks
Venue: arXiv cs.DC 2013
Year: 2013

In parallel computing, a problem is divided into a set of smaller tasks that are distributed across multiple processing elements. Balancing the load of the processing elements is key to achieving good performance and scalability. If the computational costs of the individual tasks vary over time in an unpredictable way, dynamic load balancing aims at migrating them between processing elements so as to maintain load balance. During dynamic load balancing, the tasks amount to indivisible work packets with a real-valued cost. For this case of indivisible, real- valued loads, we analyze the balancing circuit model, a local dynamic load-balancing scheme that does not require global communication. We extend previous analyses to the present case and provide a probabilistic bound for the achievable load balance. Based on an analogy with the offline balls-into-bins problem, we further propose a novel algorithm for dynamic balancing of indivisible, real-valued loads. We benchmark the proposed algorithm in numerical experiments and compare it with the classical greedy algorithm, both in terms of solution quality and communication cost. We find that the increased communication cost of the proposed algorithm is compensated by a higher solution quality, leading on average to about an order of magnitude gain in overall performance.
Braess's Paradox in Wireless Networks: The Danger of Improved Technology
Venue: arXiv cs.GT 2013
Year: 2013

When comparing new wireless technologies, it is common to consider the effect that they have on the capacity of the network (defined as the maximum number of simultaneously satisfiable links). For example, it has been shown that giving receivers the ability to do interference cancellation, or allowing transmitters to use power control, never decreases the capacity and can in certain cases increase it by $Ω(\log (Δ\cdot P_{\max}))$, where $Δ$ is the ratio of the longest link length to the smallest transmitter-receiver distance and $P_{\max}$ is the maximum transmission power. But there is no reason to expect the optimal capacity to be realized in practice, particularly since maximizing the capacity is known to be NP-hard. In reality, we would expect links to behave as self-interested agents, and thus when introducing a new technology it makes more sense to compare the values reached at game-theoretic equilibria than the optimum values. In this paper we initiate this line of work by comparing various notions of equilibria (particularly Nash equilibria and no-regret behavior) when using a supposedly "better" technology. We show a version of Braess's Paradox for all of them: in certain networks, upgrading technology can actually make the equilibria \emph{worse}, despite an increase in the capacity. We construct instances where this decrease is a constant factor for power control, interference cancellation, and improvements in the SINR threshold ($β$), and is $Ω(\log Δ)$ when power control is combined with interference cancellation. However, we show that these examples are basically tight: the decrease is at most O(1) for power control, interference cancellation, and improved $β$, and is at most $O(\log Δ)$ when power control is combined with interference cancellation.
Leadership without Leaders? Starters and Followers in Online Collective Action
Venue: arXiv cs.CY 2013
Year: 2013

The Internet has been ascribed a prominent role in collective action, particularly with widespread use of social media. But most mobilisations fail. We investigate the characteristics of those few mobilisations that succeed and hypothesise that the presence of 'starters' with low thresholds for joining will determine whether a mobilisation achieves success, as suggested by threshold models. We use experimental data from public good games to identify personality types associated with willingness to start in collective action. We find a significant association between both extraversion and internal locus of control, and willingness to start, while agreeableness is associated with a tendency to follow. Rounds without at least a minimum level of extraversion among the participants are unlikely to be funded, providing some support for the hypothesis.
Text Compression using Abstract Numeration System on a Regular Language
Venue: arXiv cs.FL 2013
Year: 2013

An abstract numeration system (ANS) is a numeration system that provides a one-to-one correspondence between the natural numbers and a regular language. In this paper, we define an ANS-based compression as an extension of this correspondence. In addition, we show the following results: 1) an average compression ratio is computable from a language, 2) an ANS-based compression runs in sublinear time with respect to the length of the input string, and 3) an ANS-based compression can be extended to block-based compression using a factorial language.
Sparse Dictionary-based Attributes for Action Recognition and Summarization
Venue: arXiv cs.CV 2013
Year: 2013

We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective function for learning a sparse dictionary of action attributes. The objective function maximizes the mutual information between what has been learned and what remains to be learned in terms of appearance information and class distribution for each dictionary atom. We propose a Gaussian Process (GP) model for sparse representation to optimize the dictionary objective function. The sparse coding property allows a kernel with compact support in GP to realize a very efficient dictionary learning process. Hence we can describe an action video by a set of compact and discriminative action attributes. More importantly, we can recognize modeled action categories in a sparse feature space, which can be generalized to unseen and unmodeled action categories. Experimental results demonstrate the effectiveness of our approach in action recognition and summarization.
Blind-date Conversation Joining
Venue: arXiv cs.SE 2013
Year: 2013

We focus on a form of joining conversations among multiple parties in service-oriented applications where a client may asynchronously join an existing conversation without need to know in advance any information about it. More specifically, we show how the correlation mechanism provided by orchestration languages enables a form of conversation joining that is completely transparent to clients and that we call 'blind-date joining'. We provide an implementation of this strategy by using the standard orchestration language WS-BPEL. We then present its formal semantics by resorting to COWS, a process calculus specifically designed for modelling service-oriented applications. We illustrate our approach by means of a simple, but realistic, case study from the online games domain.
Amending Choreographies
Venue: arXiv cs.PL 2013
Year: 2013

Choreographies are global descriptions of system behaviors, from which the local behavior of each endpoint entity can be obtained automatically through projection. To guarantee that its projection is correct, i.e. it has the same behaviors of the original choreography, a choreography usually has to respect some coherency conditions. This restricts the set of choreographies that can be projected. In this paper, we present a transformation for amending choreographies that do not respect common syntactic conditions for projection correctness. Specifically, our transformation automatically reduces the amount of concurrency, and it infers and adds hidden communications that make the resulting choreography respect the desired conditions, while preserving its behavior.
Managing Schema Evolution in NoSQL Data Stores
Venue: arXiv cs.DB 2013
Year: 2013

NoSQL data stores are commonly schema-less, providing no means for globally defining or managing the schema. While this offers great flexibility in early stages of application development, developers soon can experience the heavy burden of dealing with increasingly heterogeneous data. This paper targets schema evolution for NoSQL data stores, the complex task of adapting and changing the implicit structure of the data stored. We discuss the recommendations of the developer community on handling schema changes, and introduce a simple, declarative schema evolution language. With our language, software developers and architects can systematically manage the evolution of their production data and perform typical schema maintenance tasks. We further provide a holistic NoSQL database programming language to define the semantics of our schema evolution language. Our solution does not require any modifications to the NoSQL data store, treating the data store as a black box. Thus, we want to address application developers that use NoSQL systems
Data Center Cost Optimization Via Workload Modulation Under Real-World Electricity Pricing
Venue: arXiv cs.SY 2013
Year: 2013

We formulate optimization problems to study how data centers might modulate their power demands for cost-effective operation taking into account three key complex features exhibited by real-world electricity pricing schemes: (i) time-varying prices (e.g., time-of-day pricing, spot pricing, or higher energy prices during coincident peaks) and (ii) separate charge for peak power consumption. Our focus is on demand modulation at the granularity of an entire data center or a large part of it. For computational tractability reasons, we work with a fluid model for power demands which we imagine can be modulated using two abstract knobs of demand dropping and demand delaying (each with its associated penalties or costs). Given many data center workloads and electric prices can be effectively predicted using statistical modeling techniques, we devise a stochastic dynamic program (SDP) that can leverage such predictive models. Since the SDP can be computationally infeasible in many real platforms, we devise approximations for it. We also devise fully online algorithms that might be useful for scenarios with poor power demand or utility price predictability. For one of our online algorithms, we prove a competitive ratio of 2-1/n. Finally, using empirical evaluation with both real-world and synthetic power demands and real-world prices, we demonstrate the efficacy of our techniques. As two salient empirically-gained insights: (i) demand delaying is more effective than demand dropping regarding to peak shaving (e.g., 10.74% cost saving with only delaying vs. 1.45% with only dropping for Google workload) and (ii) workloads tend to have different cost saving potential under various electricity tariffs (e.g., 16.97% cost saving under peak-based tariff vs. 1.55% under time-varying pricing tariff for Facebook workload).
Zero-error Slepian-Wolf Coding of Confined Correlated Sources with Deviation Symmetry
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, we use linear codes to study zero-error Slepian-Wolf coding of a set of sources with deviation symmetry, where the sources are generalization of the Hamming sources over an arbitrary field. We extend our previous codes, Generalized Hamming Codes for Multiple Sources, to Matrix Partition Codes and use the latter to efficiently compress the target sources. We further show that every perfect or linear-optimal code is a Matrix Partition Code. We also present some conditions when Matrix Partition Codes are perfect and/or linear-optimal. Detail discussions of Matrix Partition Codes on Hamming sources are given at last as examples.
Performance comparison of IEEE 802.11g and IEEE 802.11n in the presence of interference from 802.15.4 networks
Venue: arXiv cs.NI 2013
Year: 2013

In this paper we compare the packet error rate (PER) and maximum throughput of IEEE 802.11n and IEEE 802.11g under interference from IEEE 802.15.4 by using MATLAB to simulate the IEEE PHY for 802.11n and 802.11g networks.
Compressive Sampling for Remote Control Systems
Venue: arXiv cs.SY 2013
Year: 2013

In remote control, efficient compression or representation of control signals is essential to send them through rate-limited channels. For this purpose, we propose an approach of sparse control signal representation using the compressive sampling technique. The problem of obtaining sparse representation is formulated by cardinality-constrained L2 optimization of the control performance, which is reducible to L1-L2 optimization. The low rate random sampling employed in the proposed method based on the compressive sampling, in addition to the fact that the L1-L2 optimization can be effectively solved by a fast iteration method, enables us to generate the sparse control signal with reduced computational complexity, which is preferable in remote control systems where computation delays seriously degrade the performance. We give a theoretical result for control performance analysis based on the notion of restricted isometry property (RIP). An example is shown to illustrate the effectiveness of the proposed approach via numerical experiments.
Stratified Labelings for Abstract Argumentation
Venue: arXiv cs.AI 2013
Year: 2013

We introduce stratified labelings as a novel semantical approach to abstract argumentation frameworks. Compared to standard labelings, stratified labelings provide a more fine-grained assessment of the controversiality of arguments using ranks instead of the usual labels in, out, and undecided. We relate the framework of stratified labelings to conditional logic and, in particular, to the System Z ranking functions.
Context Specific Event Model For News Articles
Venue: arXiv cs.CL 2013
Year: 2013

We present a new context based event indexing and event ranking model for News Articles. The context event clusters formed from the UNL Graphs uses the modified scoring scheme for segmenting events which is followed by clustering of events. From the context clusters obtained three models are developed- Identification of Main and Sub events; Event Indexing and Event Ranking. Based on the properties considered from the UNL Graphs for the modified scoring main events and sub events associated with main-events are identified. The temporal details obtained from the context cluster are stored using hashmap data structure. The temporal details are place-where the event took; person-who involved in that event; time-when the event took place. Based on the information collected from the context clusters three indices are generated- Time index, Person index, and Place index. This index gives complete details about every event obtained from context clusters. A new scoring scheme is introduced for ranking the events. The scoring scheme for event ranking gives weight-age based on the priority level of the events. The priority level includes the occurrence of the event in the title of the document, event frequency, and inverse document frequency of the events.
Performance Limits and Practical Decoding of Interleaved Reed-Solomon Polar Concatenated Codes
Venue: arXiv cs.IT 2013
Year: 2013

A scheme for concatenating the recently invented polar codes with non-binary MDS codes, as Reed-Solomon codes, is considered. By concatenating binary polar codes with interleaved Reed-Solomon codes, we prove that the proposed concatenation scheme captures the capacity-achieving property of polar codes, while having a significantly better error-decay rate. We show that for any $ε> 0$, and total frame length $N$, the parameters of the scheme can be set such that the frame error probability is less than $2^{-N^{1-ε}}$, while the scheme is still capacity achieving. This improves upon $2^{-N^{0.5-ε}}$, the frame error probability of Arikan's polar codes. The proposed concatenated polar codes and Arikan's polar codes are also compared for transmission over channels with erasure bursts. We provide a sufficient condition on the length of erasure burst which guarantees failure of the polar decoder. On the other hand, it is shown that the parameters of the concatenated polar code can be set in such a way that the capacity-achieving properties of polar codes are preserved. We also propose decoding algorithms for concatenated polar codes, which significantly improve the error-rate performance at finite block lengths while preserving the low decoding complexity.
Designing a Pattern Language For Surviving Earthquakes
Venue: arXiv cs.CY 2013
Year: 2013

In this paper, we proposed the Survival Language, a pattern language to support survival when a catastrophic earthquake occurs. This proposal comes from the problem that the tragedies of earthquakes are repeated, because knowledge and wisdom on how to prepare for an earthquake and what to do during an earthquake have not been passed down sufficiently. This paper presented the four patterns of the Survival Language: "Daily Use of Reserves," "Life over Furniture," "Evacuation Initiator," and "Kick Signal." In addition, we described that the Survival Language is created and used by collaborations because a pattern language has been a tool for collaboration since it was presented by Christopher Alexander.
Intensional view of General Single Processor Operating Systems
Venue: arXiv cs.OS 2013
Year: 2013

Operating systems are currently viewed ostensively. As a result they mean different things to different people. The ostensive character makes it is hard to understand OSes formally. An intensional view can enable better formal work, and also offer constructive support for some important problems, e.g. OS architecture. This work argues for an intensional view of operating systems. It proposes to overcome the current ostensive view by defining an OS based on formal models of computation, and also introduces some principles. Together these are used to develop a framework of algorithms of single processor OS structure using an approach similar to function level programming. In this abridged paper we illustrate the essential approach, discuss some advantages and limitations and point out some future possibilities.
Pattern recognition issues on anisotropic smoothed particle hydrodynamics
Venue: arXiv cs.AI 2013
Year: 2013

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.
Global Life Patterns: A Methodology for Designing a Personal Global Life
Venue: arXiv cs.CY 2013
Year: 2013

In this paper, we propose the Global Life Patterns, a methodology to support people to maintain individuality and design their own actions in respect to the "globalizing" society - a Global Life. Today, globalization requires each person to maintain individuality in respect to Globalization. Because methods to acquire such ability are tacit, a clarified methodology to live a Global Life is needed.This methodology is based on the format of a Pattern Language - specifically, this methodology is in the format of the Pattern Language 3.0 (Iba, 2012).
Pricing Ad Slots with Consecutive Multi-unit Demand
Venue: arXiv cs.GT 2013
Year: 2013

We consider the optimal pricing problem for a model of the rich media advertisement market, as well as other related applications. In this market, there are multiple buyers (advertisers), and items (slots) that are arranged in a line such as a banner on a website. Each buyer desires a particular number of {\em consecutive} slots and has a per-unit-quality value $v_i$ (dependent on the ad only) while each slot $j$ has a quality $q_j$ (dependent on the position only such as click-through rate in position auctions). Hence, the valuation of the buyer $i$ for item $j$ is $v_iq_j$. We want to decide the allocations and the prices in order to maximize the total revenue of the market maker. A key difference from the traditional position auction is the advertiser's requirement of a fixed number of consecutive slots. Consecutive slots may be needed for a large size rich media ad. We study three major pricing mechanisms, the Bayesian pricing model, the maximum revenue market equilibrium model and an envy-free solution model. Under the Bayesian model, we design a polynomial time computable truthful mechanism which is optimum in revenue. For the market equilibrium paradigm, we find a polynomial time algorithm to obtain the maximum revenue market equilibrium solution. In envy-free settings, an optimal solution is presented when the buyers have the same demand for the number of consecutive slots. We conduct a simulation that compares the revenues from the above schemes and gives convincing results.