OpenRaiser/Intern-Atlas huggingface dataset:
Adaptive Electricity Scheduling in Microgrids
Venue: arXiv cs.SY 2013
Year: 2013

Microgrid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity (QoSE). Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The microgrid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, i.e., QoSE, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macrogrid. The problem is formulated as a constrained stochastic programming problem. The Lyapunov optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm since it does not require any statistics and future knowledge of the electricity supply, demand and price processes. We derive several "hard" performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling algorithm.
Follow the Leader If You Can, Hedge If You Must
Venue: arXiv cs.LG 2013
Year: 2013

Follow-the-Leader (FTL) is an intuitive sequential prediction strategy that guarantees constant regret in the stochastic setting, but has terrible performance for worst-case data. Other hedging strategies have better worst-case guarantees but may perform much worse than FTL if the data are not maximally adversarial. We introduce the FlipFlop algorithm, which is the first method that provably combines the best of both worlds. As part of our construction, we develop AdaHedge, which is a new way of dynamically tuning the learning rate in Hedge without using the doubling trick. AdaHedge refines a method by Cesa-Bianchi, Mansour and Stoltz (2007), yielding slightly improved worst-case guarantees. By interleaving AdaHedge and FTL, the FlipFlop algorithm achieves regret within a constant factor of the FTL regret, without sacrificing AdaHedge's worst-case guarantees. AdaHedge and FlipFlop do not need to know the range of the losses in advance; moreover, unlike earlier methods, both have the intuitive property that the issued weights are invariant under rescaling and translation of the losses. The losses are also allowed to be negative, in which case they may be interpreted as gains.
On the Low SNR Capacity of Maximum Ratio Combining over Rician Fading Channels with Full Channel State Information
Venue: arXiv cs.IT 2013
Year: 2013

In this letter, we study the ergodic capacity of a maximum ratio combining (MRC) Rician fading channel with full channel state information (CSI) at the transmitter and at the receiver. We focus on the low Signal-to-Noise Ratio (SNR) regime and we show that the capacity scales as (L Omega/(K+L)) SNR log(1/SNR), where Omega is the expected channel gain per branch, K is the Rician fading factor, and L is the number of diversity branches. We show that one-bit CSI feedback at the transmitter is enough to achieve this capacity using an on-off power control scheme. Our framework can be seen as a generalization of recently established results regarding the fading-channels capacity characterization in the low-SNR regime.
From EGEE OPerations Portal towards EGI OPerations Portal
Venue: arXiv cs.SE 2013
Year: 2013

EGEE to EGI structure based on NGIs evolution induces a large move from the operations that will rely on a sustainable and largely decentralized model. One of the key evolutions for the challenge in the regionalisation relies in the scalability and the flexibility required regarding information source types and information handling. For 5 years, we have developed and maintained a standard-based component that allows us to address both theses issues. This open-source tool, named Lavoisier, has been a critical success factor for the operations dashboard, one of the Operations Portal main features. Indeed, it enables coherent efficient and reliable data handling which is customizable and scalable, as Lavoisier is an extensible service designed to provide a unified view of data collected from multiple heterogeneous data sources. Data views are represented and accessed as XML documents through standard languages such as XSLT, XPath. Moreover, scalability and reliability are enforced by a caching mechanism adaptable to specific data sources and use-cases. We will namely expose how the concept and the implementation enable clear roles separation between plug-in developer, service configuration administrator or end-user. Also, maintainability of the portal code has increased dramatically as the latter is now independent from the data sources technology or from the cache management policies. Finally, integration of data has recently been simplified as the service administrator proceeds now through web interfaces
International Collaboration in Science: The Global Map and the Network
Venue: arXiv cs.DL 2013
Year: 2013

The network of international co-authorship relations has been dominated by certain European nations and the USA, but this network is rapidly expanding at the global level. Between 40 and 50 countries appear in the center of the international network in 2011, and almost all (201) nations are nowadays involved in international collaboration. In this brief communication, we present both a global map with the functionality of a Google Map (zooming, etc.) and network maps based on normalized relations. These maps reveal complementary aspects of the network. International collaboration in the generation of knowledge claims (that is, the context of discovery) changes the structural layering of the sciences. Previously, validation was at the global level and discovery more dependent on local contexts. This changing relationship between the geographical and intellectual dimensions of the sciences also has implications for national science policies.
Moment-Matching Polynomials
Venue: arXiv cs.CC 2013
Year: 2013

We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem and deviate significantly from known Fourier-based methods, which require the underlying distribution to have some product structure. Our main application is the first polynomial-time algorithm for agnostically learning any function of a constant number of halfspaces with respect to any log-concave distribution (for any constant accuracy parameter). This result was not known even for the case of learning the intersection of two halfspaces without noise. Additionally, we show that in the "smoothed-analysis" setting, the above results hold with respect to distributions that have sub-exponential tails, a property satisfied by many natural and well-studied distributions in machine learning. Given that our algorithms can be implemented using Support Vector Machines (SVMs) with a polynomial kernel, these results give a rigorous theoretical explanation as to why many kernel methods work so well in practice.
Static Analysis for Regular Expression Denial-of-Service Attacks
Venue: arXiv cs.PL 2013
Year: 2013

Regular expressions are a concise yet expressive language for expressing patterns. For instance, in networked software, they are used for input validation and intrusion detection. Yet some widely deployed regular expression matchers based on backtracking are themselves vulnerable to denial-of-service attacks, since their runtime can be exponential for certain input strings. This paper presents a static analysis for detecting such vulnerable regular expressions. The running time of the analysis compares favourably with tools based on fuzzing, that is, randomly generating inputs and measuring how long matching them takes. Unlike fuzzers, the analysis pinpoints the source of the vulnerability and generates possible malicious inputs for programmers to use in security testing. Moreover, the analysis has a firm theoretical foundation in abstract machines. Testing the analysis on two large repositories of regular expressions shows that the analysis is able to find significant numbers of vulnerable regular expressions in a matter of seconds.
Comparative Studies on Decentralized Multiloop PID Controller Design Using Evolutionary Algorithms
Venue: arXiv cs.SY 2013
Year: 2013

Decentralized PID controllers have been designed in this paper for simultaneous tracking of individual process variables in multivariable systems under step reference input. The controller design framework takes into account the minimization of a weighted sum of Integral of Time multiplied Squared Error (ITSE) and Integral of Squared Controller Output (ISCO) so as to balance the overall tracking errors for the process variables and required variation in the corresponding manipulated variables. Decentralized PID gains are tuned using three popular Evolutionary Algorithms (EAs) viz. Genetic Algorithm (GA), Evolutionary Strategy (ES) and Cultural Algorithm (CA). Credible simulation comparisons have been reported for four benchmark 2x2 multivariable processes.
Knowledge Sharing: A Model
Venue: arXiv cs.SI 2013
Year: 2013

We know anything because we learn about it, there is anything we ever share about it, but now a lot of media that can represent how it happened as infrastructure of the knowledge sharing. This paper aims to introduce a model for understanding a problem in knowledge sharing based on interaction.
Analysis of Influence of Internet Retail Service Quality (IRSQ) to Consumer Online Shopping Satisfaction at www.kebanaran.com
Venue: arXiv cs.CY 2013
Year: 2013

The purpose of this research was to determine the influence of Internet Retail Service Quality (IRSQ) (website performance, access, security, sensation, and information) to the satisfaction www.kebanaran.com online shoppers. The method of analysis used was path analysis. Based on the research results influence IRSQ variables (performance, access, sensation, and information security), performance variables (X1), access (X2) and sensation (X3) had no significant effect on satisfaction (Y). It showsthat the online shopping website www.kebanaran.com already apply standard terms online stores in general, such as membership, has a return policy, a unique craft product offerings, the choice of language, the choice of currency, the chatroom facility, the product ctalogue about images from different angles and so forth, so that consumers be sure to purchase products through the online shopping website www.kebanaran.com. Security variable (X4) and information (X5) has a significant effect on satisfaction (Y). This shows that security is applied and the importance of information for consumers such as information availability, quality productsinformation, accurate product information is essential so that consumers do not hesitate to deal transaction use online shopping website www.kebanaran.com. Keyword: Service Quality, Satisfaction, Online Shop
CA4IOT Context Awareness for Internet of Things
Venue: arXiv cs.SE 2013
Year: 2013

Internet of Things (IoT) will connect billions of sensors deployed around the world together. This will create an ideal opportunity to build a sensing-as-a-service platform. Due to large number of sensor deployments, there would be number of sensors that can be used to sense and collect similar information. Further, due to advances in sensor hardware technology, new methods and measurements will be introduced continuously. In the IoT paradigm, selecting the most appropriate sensors which can provide relevant sensor data to address the problems at hand among billions of possibilities would be a challenge for both technical and non-technical users. In this paper, we propose the Context Awareness for Internet of Things (CA4IOT) architecture to help users by automating the task of selecting the sensors according to the problems/tasks at hand. We focus on automated configuration of filtering, fusion and reasoning mechanisms that can be applied to the collected sensor data streams using selected sensors. Our objective is to allow the users to submit their problems, so our proposed architecture understands them and produces more comprehensive and meaningful information than the raw sensor data streams generated by individual sensors.
Regularized Zero-Forcing Interference Alignment for the Two-Cell MIMO Interfering Broadcast Channel
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, we propose transceiver design strategies for the two-cell multiple-input multiple-output (MIMO) interfering broadcast channel where inter-cell interference (ICI) exists in addition to interuser interference (IUI). We first formulate the generalized zero-forcing interference alignment (ZF-IA) method based on the alignment of IUI and ICI in multi-dimensional subspace. We then devise a minimum weighted-mean-square-error (WMSE) method based on regularizing the precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing weighted-sum-rate-maximizing transceiver, our method does not require an iterative calculation of the optimal weights. Because of this, the proposed scheme, while not designed specifically to maximize the sum rate, is computationally efficient and achieves a faster convergence compared to the known weighted-sum-rate maximizing scheme. Through analysis and simulation, we show the effectiveness of the proposed regularized ZF-IA scheme.
SPARC - Sorted ASP with Consistency Restoring Rules
Venue: arXiv cs.PL 2013
Year: 2013

This is a preliminary report on the work aimed at making CR-Prolog -- a version of ASP with consistency restoring rules -- more suitable for use in teaching and large applications. First we describe a sorted version of CR-Prolog called SPARC. Second, we translate a basic version of the CR-Prolog into the language of DLV and compare the performance with the state of the art CR-Prolog solver. The results form the foundation for future more efficient and user friendly implementation of SPARC and shed some light on the relationship between two useful knowledge representation constructs: consistency restoring rules and weak constraints of DLV.
Eliminating Unfounded Set Checking for HEX-Programs
Venue: arXiv cs.LO 2013
Year: 2013

HEX-programs are an extension of the Answer Set Programming (ASP) paradigm incorporating external means of computation into the declarative programming language through so-called external atoms. Their semantics is defined in terms of minimal models of the Faber-Leone-Pfeifer (FLP) reduct. Developing native solvers for HEX-programs based on an appropriate notion of unfounded sets has been subject to recent research for reasons of efficiency. Although this has lead to an improvement over naive minimality checking using the FLP reduct, testing for foundedness remains a computationally expensive task. In this work we improve on HEX-program evaluation in this respect by identifying a syntactic class of programs, that can be efficiently recognized and allows to entirely skip the foundedness check. Moreover, we develop criteria for decomposing a program into components, such that the search for unfounded sets can be restricted. Observing that our results apply to many HEX-program applications provides analytic evidence for the significance and effectiveness of our approach, which is complemented by a brief discussion of preliminary experimental validation.
Two New Definitions of Stable Models of Logic Programs with Generalized Quantifiers
Venue: arXiv cs.LO 2013
Year: 2013

We present alternative definitions of the first-order stable model semantics and its extension to incorporate generalized quantifiers by referring to the familiar notion of a reduct instead of referring to the SM operator in the original definitions. Also, we extend the FLP stable model semantics to allow generalized quantifiers by referring to an operator that is similar to the $\sm$ operator. For a reasonable syntactic class of logic programs, we show that the two stable model semantics of generalized quantifiers are interchangeable.
Extending FO(ID) with Knowledge Producing Definitions: Preliminary Results
Venue: arXiv cs.LO 2013
Year: 2013

Previous research into the relation between ASP and classical logic has identified at least two different ways in which the former extends the latter. First, ASP program typically contain sets of rules that can be naturally interpreted as inductive definitions, and the language FO(ID) has shown that such inductive definitions can elegantly be added to classical logic in a modular way. Second, there is of course also the well-known epistemic component of ASP, which was mainly emphasized in the early papers on stable model semantics. To investigate whether this kind of knowledge can also, and in a similarly modular way, be added to classical logic, the language of Ordered Epistemic Logic was presented in recent work. However, this logic views the epistemic component as entirely separate from the inductive definition component, thus ignoring any possible interplay between the two. In this paper, we present a language that extends the inductive definition construct found in FO(ID) with an epistemic component, making such interplay possible. The eventual goal of this work is to discover whether it is really appropriate to view the epistemic component and the inductive definition component of ASP as two separate extensions of classical logic, or whether there is also something of importance in the combination of the two.
Is it ever safe to vote strategically?
Venue: arXiv cs.GT 2013
Year: 2013

There are many situations in which mis-coordinated strategic voting can leave strategic voters worse off than they would have been had they not tried to strategize. We analyse the simplest of such scenarios, in which the set of strategic voters all have the same sincere preferences and all cast the same strategic vote, while all other voters vote sincerely. Most mis-coordinations in this framework can be classified as instances of either strategic overshooting (too many voted strategically) or strategic undershooting (too few). If mis-coordination can result in strategic voters ending up worse off than they would have been had they all just voted sincerely, we call the relevant strategic vote unsafe. We show that under every onto and non-dictatorial social choice rule there exist circumstances where a voter has an incentive to cast a safe strategic vote. We extend the Gibbard-Satterthwaite Theorem by proving that every onto and non-dictatorial social choice rule can be individually manipulated by a voter casting a safe strategic vote.
Fuzzy Soft Set Based Classification for Gene Expression Data
Venue: arXiv cs.AI 2013
Year: 2013

Classification is one of the major issues in Data Mining Research fields. The classification problems in medical area often classify medical dataset based on the result of medical diagnosis or description of medical treatment by the medical practitioner. This research work discusses the classification process of Gene Expression data for three different cancers which are breast cancer, lung cancer and leukemia cancer with two classes which are cancerous stage and non cancerous stage. We have applied a fuzzy soft set similarity based classifier to enhance the accuracy to predict the stages among cancer genes and the informative genes are selected by using Entopy filtering.
Causal graph-based video segmentation
Venue: arXiv cs.CV 2013
Year: 2013

Numerous approaches in image processing and computer vision are making use of super-pixels as a pre-processing step. Among the different methods producing such over-segmentation of an image, the graph-based approach of Felzenszwalb and Huttenlocher is broadly employed. One of its interesting properties is that the regions are computed in a greedy manner in quasi-linear time. The algorithm may be trivially extended to video segmentation by considering a video as a 3D volume, however, this can not be the case for causal segmentation, when subsequent frames are unknown. We propose an efficient video segmentation approach that computes temporally consistent pixels in a causal manner, filling the need for causal and real time applications.
On Max-SINR Receiver for HMT System over Doubly Dispersive Channel
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, a novel receiver for Hexagonal Multicarrier Transmission (HMT) system based on the maximizing Signal-to-Interference-plus-Noise Ratio (Max-SINR) criterion is proposed. Theoretical analyses show that there is a timing offset between the prototype pulses of the proposed Max-SINR receiver and the traditional projection receiver. Meanwhile, the timing offset should be matched to the channel scattering factor of the doubly dispersive (DD) channel. The closed form timing offset expressions of the prototype pulse for Max-SINR HMT receiver over DD channel with different channel scattering functions are derived. Simulation results show that the proposed Max-SINR receiver outperforms traditional projection scheme and obtains an approximation to the theoretical upper bound SINR performance. Consistent with the SINR performance improvement, the bit error rate (BER) performance of HMT system has also been further improved by using the proposed Max-SINR receiver. Meanwhile, the SINR performance of the proposed Max-SINR receiver is robust to the channel delay spread estimation errors.
Analytical model for mobile user connectivity in coexisting femtocell/macrocell networks
Venue: arXiv cs.NI 2013
Year: 2013

In this paper we investigate the performance of mobile user connectivity in femtocell/macrocell networks. The femto user equipment (FUE) can connect to femto access point (FAP) with low communication range rather than higher communication range to macro base station (MBS). Furthermore, in such emerging networks, the spatial reuse of resources is permissible and the transmission range can be decreased, then the probability of connectivity is high. Thereby in this study, we propose a tractable analytical model for the connectivity probability based on communication range and the mobility of mobile users in femtocell/macrocell networks. Further, we study the interplays between outage probability and spectral efficiency in such networks. Numerical results demonstrate the effectiveness of computing the connectivity probability in femtocell/macrocell networks.
Stability and Cost Optimization in Controlled Random Walks Using Scheduling Fields
Venue: arXiv cs.SY 2013
Year: 2013

The control of large queueing networks is a notoriously difficult problem. Recently, an interesting new policy design framework for the control problem called h-MaxWeight has been proposed: h-MaxWeight is a natural generalization of the famous MaxWeight policy where instead of the quadratic any other surrogate value function can be applied. Stability of the policy is then achieved through a perturbation technique. However, stability crucially depends on parameter choice which has to be adapted in simulations. In this paper we use a different technique where the required perturbations can be directly implemented in the weight domain, which we call a scheduling field then. Specifically, we derive the theoretical arsenal that guarantees universal stability while still operating close to the underlying cost criterion. Simulation examples suggest that the new approach to policy synthesis can even provide significantly higher gains irrespective of any further assumptions on the network model or parameter choice.