OpenRaiser/Intern-Atlas huggingface dataset:
Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid
Venue: arXiv cs.SY 2013
Year: 2013

In this paper, we model energy use in commercial buildings using empirical data captured through sMAP, a campus building data portal at UC Berkeley. We conduct at-scale experiments in a newly constructed building on campus. By modulating the supply duct static pressure (SDSP) for the main supply air duct, we induce a response on the main supply fan and determine how much ancillary power flexibility can be provided by a typical commercial building. We show that the consequent intermittent fluctuations in the air mass flow into the building does not influence the building climate in a human-noticeable way. We estimate that at least 4 GW of regulation reserve is readily available only through commercial buildings in the US. Based on predictions this value will reach to 5.6 GW in 2035. We also show how thermal slack can be leveraged to provide an ancillary service to deal with transient frequency fluctuations in the grid. We consider a simplified model of the grid power system with time varying demand and generation and present a simple control scheme to direct the ancillary service power flow from buildings to improve on the classical automatic generation control (AGC)-based approach. Simulation results are provided to show the effectiveness of the proposed methodology for enhancing grid frequency regulation.
On Using Complex Event Processing for Dynamic Demand Response Optimization in Microgrid
Venue: arXiv cs.DC 2013
Year: 2013

Demand-side load reduction is a key benefit of Smart Grids. However, existing demand response optimization (DR) programs fail to effectively leverage the near-realtime information available from smart meters and Building Area Networks to respond dynamically to changing energy use profiles. We investigate the use of semantic Complex Event Processing (CEP) patterns to model and detect dynamic situations in a campus microgrid to facilitate adaptive DR. Our focus is on demand-side management rather than supply-side constraints. Continuous data from information sources like smart meters and building sensors are abstracted as event streams. Event patterns for situations that assist with DR are detected from them. Specifically, we offer a taxonomy of event patterns that can guide operators to define situations of interest and we illustrate its efficacy for DR by applying these patterns on realtime events in the USC Campus microgrid using our CEP framework
Battery Placement on Performance of VAR Controls
Venue: arXiv cs.SY 2013
Year: 2013

Battery's role in the development of smart grid is gaining greater attention as an energy storage device that can be integrated with a Photovoltaic (PV) cell in the distribution circuit. As more PVs are connected to the system, real power injection to the distribution can cause fluctuation in the voltage. Due to the rapid fluctuation of the voltage, a more advanced volt-ampere reactive (VAR) power control scheme on a fast time scale is used to minimize the voltage deviation on the distribution. Employing both global and local dynamic VAR control schemes in our previous work, we show the effects of battery placement on the performance of VAR controls in the example of a single branch radial distribution circuit. Simulations verify that having battery placement at the rear in the distribution circuit can provide smaller voltage variations and higher energy savings than front battery placement when used with dynamic VAR control algorithms.
The Effects of GQM+Strategies on Organizational Alignment
Venue: arXiv cs.SE 2013
Year: 2013

The increasing role of software for developing products and services requires that organizations align their software-related activities with high-level business goals. In practice, this alignment is very difficult and only little systematic support is available. GQM+Strategies is a method that aims at aligning organizational goals, strategies, and measurements at all levels of an organization in a seamless way. This article describes a case study of applying GQM+Strategies in a globally op- erating industrial R&D organization developing special-purpose device products for B2B customers. The study analyzes how GQM+Strategies has helped clarify and harmonize the goal set of the organization. Results of the study indicate improved alignment and integration of different goals. In addition, the method helped to make the initially informal goal-setting more transparent and consequently enabled revising it while new, more important goals were discovered and comprehended. Moreover, several elements affecting the achievement of goals as well as impediments were identified.
Intelligent Agent for Prediction in E- Negotiation: An Approach
Venue: arXiv cs.MA 2013
Year: 2013

With the proliferation of web technologies it becomes more and more important to make the traditional negotiation pricing mechanism automated and intelligent. The behaviour of software agents which negotiate on behalf of humans is determined by their tactics in the form of decision functions. Prediction of partners behaviour in negotiation has been an active research direction in recent years as it will improve the utility gain for the adaptive negotiation agent and also achieve the agreement much quicker or look after much higher benefits. In this paper we review the various negotiation methods and the existing architecture. Although negotiation is practically very complex activity to automate without human intervention we have proposed architecture for predicting the opponents behaviour which will take into consideration various factors which affect the process of negotiation. The basic concept is that the information about negotiators, their individual actions and dynamics can be used by software agents equipped with adaptive capabilities to learn from past negotiations and assist in selecting appropriate negotiation tactics.
Commune: Shared Ownership in an Agnostic Cloud
Venue: arXiv cs.CR 2013
Year: 2013

Although cloud storage platforms promise a convenient way for users to share files and engage in collaborations, they require all files to have a single owner who unilaterally makes access control decisions. Existing clouds are, thus, agnostic to shared ownership. This can be a significant limitation in many collaborations because one owner can, for example, delete files and revoke access without consulting the other collaborators. In this paper, we first formally define a notion of shared ownership within a file access control model. We then propose a solution, called Commune, to the problem of distributively enforcing shared ownership in agnostic clouds, so that access grants require the support of a pre-arranged threshold of owners. Commune can be used in existing clouds without requiring any modifications to the platforms. We analyze the security of our solution and evaluate its scalability and performance by means of an implementation integrated with Amazon S3.
Modeling the Time-varying Subjective Quality of HTTP Video Streams with Rate Adaptations
Venue: arXiv cs.MM 2013
Year: 2013

Newly developed HTTP-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' Quality of Experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer-duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for on-line TVSQ prediction in HTTP based streaming.
Wavelet Transform-Based Analysis of QRS complex in ECG Signals
Venue: arXiv cs.CE 2013
Year: 2013

In the present paper we have reported a wavelet based time-frequency multiresolution analysis of an ECG signal. The ECG (electrocardiogram), which records hearts electrical activity, is able to provide with useful information about the type of Cardiac disorders suffered by the patient depending upon the deviations from normal ECG signal pattern. We have plotted the coefficients of continuous wavelet transform using Morlet wavelet. We used different ECG signal available at MIT-BIH database and performed a comparative study. We demonstrated that the coefficient at a particular scale represents the presence of QRS signal very efficiently irrespective of the type or intensity of noise, presence of unusually high amplitude of peaks other than QRS peaks and Base line drift errors. We believe that the current studies can enlighten the path towards development of very lucid and time efficient algorithms for identifying and representing the QRS complexes that can be done with normal computers and processors.
Universal Codes from Switching Strategies
Venue: arXiv cs.IT 2013
Year: 2013

We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical ontributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.
XQuery Streaming by Forest Transducers
Venue: arXiv cs.DB 2013
Year: 2013

Streaming of XML transformations is a challenging task and only very few systems support streaming. Research approaches generally define custom fragments of XQuery and XPath that are amenable to streaming, and then design custom algorithms for each fragment. These languages have several shortcomings. Here we take a more principles approach to the problem of streaming XQuery-based transformations. We start with an elegant transducer model for which many static analysis problems are well-understood: the Macro Forest Transducer (MFT). We show that a large fragment of XQuery can be translated into MFTs --- indeed, a fragment of XQuery, that can express important features that are missing from other XQuery stream engines, such as GCX: our fragment of XQuery supports XPath predicates and let-statements. We then rely on a streaming execution engine for MFTs, one which uses a well-founded set of optimizations from functional programming, such as strictness analysis and deforestation. Our prototype achieves time and memory efficiency comparable to the fastest known engine for XQuery streaming, GCX. This is surprising because our engine relies on the OCaml built in garbage collector and does not use any specialized buffer management, while GCX's efficiency is due to clever and explicit buffer management.
DoF Analysis of the K-user MISO Broadcast Channel with Alternating CSIT
Venue: arXiv cs.IT 2013
Year: 2013

We consider a $K$-user multiple-input single-output (MISO) broadcast channel (BC) where the channel state information (CSI) of user $i(i=1,2,\ldots,K)$ may be either perfect (P), delayed (D) or not known (N) at the transmitter with probabilities $λ_P^i$, $λ_D^i$ and $λ_N^i$, respectively. In this channel, according to the three possible CSIT for each user, joint CSIT of the $K$ users could have at most $3^K$ realizations. Although the results by Tandon et al. show that the Degrees of Freedom (DoF) region for the two user MISO BC with symmetric marginal probabilities (i.e., $λ_Q^i=λ_Q \forall i\in \{1,2,\ldots,K\}, Q\in \{P,D,N\}$) depends only on the marginal probabilities, we show that this interesting result does not hold in general when the number of users is more than two. In other words, the DoF region is a function of the \textit{CSIT pattern}, or equivalently, all the joint probabilities. In this paper, given the marginal probabilities of CSIT, we derive an outer bound for the DoF region of the $K$-user MISO BC. Subsequently, the achievability of these outer bounds are considered in certain scenarios. Finally, we show the dependence of the DoF region on the joint probabilities.
Efficient XML Keyword Search based on DAG-Compression
Venue: arXiv cs.DB 2013
Year: 2013

In contrast to XML query languages as e.g. XPath which require knowledge on the query language as well as on the document structure, keyword search is open to anybody. As the size of XML sources grows rapidly, the need for efficient search indices on XML data that support keyword search increases. In this paper, we present an approach of XML keyword search which is based on the DAG of the XML data, where repeated substructures are considered only once, and therefore, have to be searched only once. As our performance evaluation shows, this DAG-based extension of the set intersection search algorithm[1], [2], can lead to search times that are on large documents more than twice as fast as the search times of the XML-based approach. Additionally, we utilize a smaller index, i.e., we consume less main memory to compute the results.
Spreading huge free software without internet connection, via self-replicating USB keys
Venue: arXiv cs.OH 2013
Year: 2013

We describe and discuss an affordable way to spread huge software without relying on internet connection, via the use of self-replicating live USB keys.
Pairwise Comparisons Simplified
Venue: arXiv cs.DM 2013
Year: 2013

This study examines the notion of generators of a pairwise comparisons matrix. Such approach decreases the number of pairwise comparisons from $n\cdot (n-1)$ to $n-1$. An algorithm of reconstructing of the PC matrix from its set of generators is presented.
Multi-agent based protection system for distribution system with DG
Venue: arXiv cs.MA 2013
Year: 2013

This paper introduces the basic structure of multi-agent based protection system for distribution system with DGs. The entire system consists of intelligent agents and communication system. Intelligent agents can be divided into three layers, the bottom layer, the middle layer and the upper layer. The design of the agent in different layer is analyzed in detail. Communication system is the bridge of multi-agent system (MAS). The transmission mode, selective communication and other principles are discussed to improve the transmission efficiency. Finally, some evaluations are proposed, which provides the design of MAS with reference.
Want a Good Answer? Ask a Good Question First!
Venue: arXiv cs.DB 2013
Year: 2013

Community Question Answering (CQA) websites have become valuable repositories which host a massive volume of human knowledge. To maximize the utility of such knowledge, it is essential to evaluate the quality of an existing question or answer, especially soon after it is posted on the CQA website. In this paper, we study the problem of inferring the quality of questions and answers through a case study of a software CQA (Stack Overflow). Our key finding is that the quality of an answer is strongly positively correlated with that of its question. Armed with this observation, we propose a family of algorithms to jointly predict the quality of questions and answers, for both quantifying numerical quality scores and differentiating the high-quality questions/answers from those of low quality. We conduct extensive experimental evaluations to demonstrate the effectiveness and efficiency of our methods.
Good, Better, Best! - Unbeatable Protocols for Consensus and Set Consensus
Venue: arXiv cs.DC 2013
Year: 2013

While the very first consensus protocols for the synchronous model were designed to match the worst-case lower bound, deciding in exactly t+1 rounds in all runs, it was soon realized that they could be strictly improved upon by early stopping protocols. These dominate the first ones, by always deciding in at most t+1 rounds, but often much faster. A protocol is unbeatable if it can't be strictly dominated. Unbeatability is often a much more suitable notion of optimality for distributed protocols than worst-case performance. Using a knowledge-based analysis, this paper studies unbeatability for both consensus and k-set consensus. We present unbeatable solutions to non-uniform consensus and k-set consensus, and uniform consensus in synchronous message-passing contexts with crash failures. The k-set consensus problem is much more technically challenging than consensus, and its analysis has triggered the development of the topological approach to distributed computing. Worst-case lower bounds for this problem have required either techniques based on algebraic topology, or reduction-based proofs. Our proof of unbeatability is purely combinatorial, and is a direct, albeit nontrivial, generalization of the one for consensus. We also present an alternative topological unbeatability proof that allows to understand the connection between the connectivity of protocol complexes and the decision time of processes. For the synchronous model, only solutions to the uniform variant of k-set consensus have been offered. Based on our unbeatable protocols for uniform consensus and for non-uniform k-set consensus, we present a uniform k-set consensus protocol that strictly dominates all known solutions to this problem in the synchronous model.
Image forgery detection based on the fusion of machine learning and block-matching methods
Venue: arXiv cs.CV 2013
Year: 2013

Dense local descriptors and machine learning have been used with success in several applications, like classification of textures, steganalysis, and forgery detection. We develop a new image forgery detector building upon some descriptors recently proposed in the steganalysis field suitably merging some of such descriptors, and optimizing a SVM classifier on the available training set. Despite the very good performance, very small forgeries are hardly ever detected because they contribute very little to the descriptors. Therefore we also develop a simple, but extremely specific, copy-move detector based on region matching and fuse decisions so as to reduce the missing detection rate. Overall results appear to be extremely encouraging.
Distributed Power Loss Minimization in Residential Micro Grids: a Communications Perspective
Venue: arXiv cs.OH 2013
Year: 2013

The constantly increasing number of power generation devices based on renewables is calling for a transition from the centralized control of electrical distribution grids to a distributed control scenario. In this context, distributed generators (DGs) are exploited to achieve other objectives beyond supporting loads, such as the minimization of the power losses along the distribution lines. The aim of this work is that of designing a full-fledged system that extends existing state of the art algorithms for the distributed minimization of power losses. We take into account practical aspects such as the design of a communication and coordination protocol that is resilient to link failures and manages channel access, message delivery and DG coordination. Thus, we analyze the performance of the resulting optimization and communication scheme in terms of power loss reduction, reduction of aggregate power demand, convergence rate and resilience to communication link failures. After that, we discuss the results of a thorough simulation campaign, obtained using topologies generated through a statistical approach that has been validated in previous research, by also assessing the performance deviation with respect to localized schemes, where the DGs are operated independently. Our results reveal that the convergence and stability performance of the selected algorithms vary greatly. However, configurations exist for which convergence is possible within five to ten communication steps and, when just 30% of the nodes are DGs, the aggregate power demand is roughly halved. Also, some of the considered approaches are quite robust against link failures as they still provide gains with respect to the localized solutions for failure rates as high as 50%.
Improved Optimal and Approximate Power Graph Compression for Clearer Visualisation of Dense Graphs
Venue: arXiv cs.CG 2013
Year: 2013

Drawings of highly connected (dense) graphs can be very difficult to read. Power Graph Analysis offers an alternate way to draw a graph in which sets of nodes with common neighbours are shown grouped into modules. An edge connected to the module then implies a connection to each member of the module. Thus, the entire graph may be represented with much less clutter and without loss of detail. A recent experimental study has shown that such lossless compression of dense graphs makes it easier to follow paths. However, computing optimal power graphs is difficult. In this paper, we show that computing the optimal power-graph with only one module is NP-hard and therefore likely NP-hard in the general case. We give an ILP model for power graph computation and discuss why ILP and CP techniques are poorly suited to the problem. Instead, we are able to find optimal solutions much more quickly using a custom search method. We also show how to restrict this type of search to allow only limited back-tracking to provide a heuristic that has better speed and better results than previously known heuristics.
Infinite Horizon Optimal Impulsive Control Theory with Application to Internet Congestion Control
Venue: arXiv cs.NI 2013
Year: 2013

We develop Bellman equation based approach for infinite time horizon optimal impulsive control problems. Both discounted and time average criteria are considered. We establish very general and at the same time natural conditions under which a canonical control triplet produces an optimal feedback policy. Then, we apply our general results for Internet congestion control providing a convenient setting for the design of active queue management algorithms. In particular, our general theoretical results suggest a simple threshold-based active queue management scheme which takes into account the main parameters of the transmission control protocol.
Real-time High Resolution Fusion of Depth Maps on GPU
Venue: arXiv cs.GR 2013
Year: 2013

A system for live high quality surface reconstruction using a single moving depth camera on a commodity hardware is presented. High accuracy and real-time frame rate is achieved by utilizing graphics hardware computing capabilities via OpenCL and by using sparse data structure for volumetric surface representation. Depth sensor pose is estimated by combining serial texture registration algorithm with iterative closest points algorithm (ICP) aligning obtained depth map to the estimated scene model. Aligned surface is then fused into the scene. Kalman filter is used to improve fusion quality. Truncated signed distance function (TSDF) stored as block-based sparse buffer is used to represent surface. Use of sparse data structure greatly increases accuracy of scanned surfaces and maximum scanning area. Traditional GPU implementation of volumetric rendering and fusion algorithms were modified to exploit sparsity to achieve desired performance. Incorporation of texture registration for sensor pose estimation and Kalman filter for measurement integration improved accuracy and robustness of scanning process.