OpenRaiser/Intern-Atlas huggingface dataset:
An UHF RFID Energy-Harvesting System Enhanced by a DC-DC Charge Pump in Silicon-on-Insulator Technology
Venue: arXiv cs.OH 2013
Year: 2013

An RF-DC converter enhanced by a DC-DC voltage booster in silicon-on-insulator technology for UHF radio frequency identification (RFID) energy harvesting is presented in this letter. When the received RF power level is -14 dBm or higher, the system, fabricated on an FR4 substrate using off-the-shelf low-cost discrete components and connected to a flexible dipole antenna, is able to produce 2.4-V DC voltage to power general-purpose electronic devices. As a simple proof of concept,a device comprising microcontroller, temperature sensor, and EEPROM is considered in this work. The experimental results demonstrate the capability of the system to autonomously perform temperature data logging up to a distance of 5 m from a conventional UHF RFID reader used as an RF energy source.
Reliable Reception of Wireless Metering Data with Protocol Coding
Venue: arXiv cs.NI 2013
Year: 2013

Stationary collectors reading wireless, battery powered smart meters, often operate in harsh channel conditions to cut network installation cost to a minimum, challenging the individual link to each meter. The desired performance measure is reliable reception of at least some data from as many as possible meters, rather than increasing the fraction of received packets from one meter. As a first step for improving reliable reception, and motivated by the recent revision of Wireless M-Bus, we propose the use of a deterministic packet transmission interval to group packets from the same meter. We derive the probability of falsely pairing packets from different senders in the simple case of no channel errors, and show through simulation and data from an experimental deployment the probability of false pairing with channel errors. The pairing is an essential step towards recovery of metering data from as many as possible meters under harsh channel conditions. From the experiment we find that more than 15% of all conducted pairings are between two erroneous packets, which sets an upper bound on the number of additional meters that can be reliably recovered.
ATLAS: Adaptive Topology- and Load-Aware Scheduling
Venue: arXiv cs.NI 2013
Year: 2013

The largest strength of contention-based MAC protocols is simultaneously the largest weakness of their scheduled counterparts: the ability to adapt to changes in network conditions. For scheduling to be competitive in mobile wireless networks, continuous adaptation must be addressed. We propose ATLAS, an Adaptive Topology- and Load-Aware Scheduling protocol to address this problem. In ATLAS, each node employs a random schedule achieving its persistence, the fraction of time a node is permitted to transmit, that is computed in a topology and load dependent manner. A distributed auction (REACT) piggybacks offers and claims onto existing network traffic to compute a lexicographic max-min channel allocation. A node's persistence p is related to its allocation. Its schedule achieving p is updated where and when needed, without waiting for a frame boundary.We study how ATLAS adapts to controlled changes in topology and load. Our results show that ATLAS adapts to most network changes in less than 0.1s, with about 20% relative error, scaling with network size. We further study ATLAS in more dynamic networks showing that it keeps up with changes in topology and load sufficient for TCP to sustain multi-hop flows, a struggle in IEEE 802.11 networks. The stable performance of ATLAS supports the design of higher-layer services that inform, and are informed by, the underlying communication network.
Optimal Frame Transmission for Scalable Video with Hierarchical Prediction Structure
Venue: arXiv cs.MM 2013
Year: 2013

An optimal frame transmission scheme is presented for streaming scalable video over a link with limited capacity. The objective is to select a transmission sequence of frames and their transmission schedule such that the overall video quality is maximized. The problem is solved for two general classes of hierarchical prediction structures, which include as a special case the popular dyadic structure. Based on a new characterization of the interdependence among frames in terms of trees, structural properties of an optimal transmission schedule are derived. These properties lead to the development of a jointly optimal frame selection and scheduling algorithm, which has computational complexity that is quadratic in the number of frames. Simulation results show that the optimal scheme substantially outperforms three existing alternatives.
A Nonlinear Constrained Optimization Framework for Comfortable and Customizable Motion Planning of Nonholonomic Mobile Robots - Part II
Venue: arXiv cs.RO 2013
Year: 2013

In this series of papers, we present a motion planning framework for planning comfortable and customizable motion of nonholonomic mobile robots such as intelligent wheelchairs and autonomous cars. In Part I, we presented the mathematical foundation of our framework, where we model motion discomfort as a weighted cost functional and define comfortable motion planning as a nonlinear constrained optimization problem of computing trajectories that minimize this discomfort given the appropriate boundary conditions and constraints. In this paper, we discretize the infinite-dimensional optimization problem using conforming finite elements. We describe shape functions to handle different kinds of boundary conditions and the choice of unknowns to obtain a sparse Hessian matrix. We also describe in detail how any trajectory computation problem can have infinitely many locally optimal solutions and our method of handling them. Additionally, since we have a nonlinear and constrained problem, computation of high quality initial guesses is crucial for efficient solution. We show how to compute them.
Social Network Games with Obligatory Product Selection
Venue: arXiv cs.GT 2013
Year: 2013

Recently, Apt and Markakis introduced a model for product adoption in social networks with multiple products, where the agents, influenced by their neighbours, can adopt one out of several alternatives (products). To analyze these networks we introduce social network games in which product adoption is obligatory. We show that when the underlying graph is a simple cycle, there is a polynomial time algorithm allowing us to determine whether the game has a Nash equilibrium. In contrast, in the arbitrary case this problem is NP-complete. We also show that the problem of determining whether the game is weakly acyclic is co-NP hard. Using these games we analyze various types of paradoxes that can arise in the considered networks. One of them corresponds to the well-known Braess paradox in congestion games. In particular, we show that social networks exist with the property that by adding an additional product to a specific node, the choices of the nodes will unavoidably evolve in such a way that everybody is strictly worse off.
A Comparison of Random Forests and Ferns on Recognition of Instruments in Jazz Recordings
Venue: arXiv cs.LG 2013
Year: 2013

In this paper, we first apply random ferns for classification of real music recordings of a jazz band. No initial segmentation of audio data is assumed, i.e., no onset, offset, nor pitch data are needed. The notion of random ferns is described in the paper, to familiarize the reader with this classification algorithm, which was introduced quite recently and applied so far in image recognition tasks. The performance of random ferns is compared with random forests for the same data. The results of experiments are presented in the paper, and conclusions are drawn.
Distributed Power Control Network and Green Building Test-bed for Demand Response in Smart Grid
Venue: arXiv cs.SY 2013
Year: 2013

It is known that demand and supply power balancing is an essential method to operate power delivery system and prevent blackouts caused by power shortage. In this paper, we focus on the implementation of demand response strategy to save power during peak hours by using Smart Grid. It is obviously impractical with centralized power control network to realize the real-time control performance, where a single central controller measures the huge metering data and sends control command back to all customers. For that purpose, we propose a new architecture of hierarchical distributed power control network which is scalable regardless of the network size. The sub-controllers are introduced to partition the large system into smaller distributed clusters where low-latency local feedback power control loops are conducted to guarantee control stability. Furthermore, sub-controllers are stacked up in an hierarchical manner such that data are fed back layer-by-layer in the inbound while in the outbound control responses are decentralized in each local sub-controller for realizing the global objectives. Numerical simulations in a realistic scenario of up to 5000 consumers show the effectiveness of the proposed scheme to achieve a desired 10% peak power saving by using off-the-shelf wireless devices with IEEE802.15.4g standard. In addition, a small scale power control system for green building test-bed is implemented to demonstrate the potential use of the proposed scheme for power saving in real life.
A Game Theory Interpretation for Multiple Access in Cognitive Radio Networks with Random Number of Secondary Users
Venue: arXiv cs.GT 2013
Year: 2013

In this paper a new multiple access algorithm for cognitive radio networks based on game theory is presented. We address the problem of a multiple access system where the number of users and their types are unknown. In order to do this, the framework is modelled as a non-cooperative Poisson game in which all the players are unaware of the total number of devices participating (population uncertainty). We propose a scheme where failed attempts to transmit (collisions) are penalized. In terms of this, we calculate the optimum penalization in mixed strategies. The proposed scheme conveys to a Nash equilibrium where a maximum in the possible throughput is achieved.
Investigating Deletion in Wikipedia
Venue: arXiv cs.CY 2013
Year: 2013

Several hundred Wikipedia articles are deleted every day because they lack sufficient significance to be included in the encyclopedia. We collect a dataset of deleted articles and analyze them to determine whether or not the deletions were justified. We find evidence to support the hypothesis that many deletions are carried out correctly, but also find that a large number were done very quickly. Based on our conclusions, we make some recommendations to reduce the number of non-significant pages and simultaneously improve retention of new editors.
System error of project ETONN and EIAS
Venue: arXiv cs.SE 2013
Year: 2013

Detected a system error of the project ETONN&EIAS.NET, which consists in the use of the developers EIAS.NET the Windows operating system in the software EIAS.NET, which in accordance with the requirements of the specification for the project EIAS.NET should provide information exchange in real time . It is concluded that it is impossible to meet the requirement specification for the project EIAS.NET about providing work ETONN/ETNaSP with the support of EIAS / EIAS.NET in real time, providing the use of the Windows operating system in the software EIAS.NET.
Pure Price of Anarchy for Generalized Second Price Auction
Venue: arXiv cs.GT 2013
Year: 2013

The Generalized Second Price auction (GSP) has been widely used by search engines to sell ad slots. Previous studies have shown that the pure Price Of Anarchy (POA) of GSP is 1.25 when there are two ad slots and 1.259 when three ad slots. For the cases with more than three ad slots, however, only some untight upper bounds of the pure POA were obtained. In this work, we improve previous results in two aspects: (1) We prove that the pure POA for GSP is 1.259 when there are four ad slots, and (2) We show that the pure POA for GSP with more than four ad slots is also 1.259 given the bidders are ranked according to a particular permutation.
Loss-resilient Coding of Texture and Depth for Free-viewpoint Video Conferencing
Venue: arXiv cs.MM 2013
Year: 2013

Free-viewpoint video conferencing allows a participant to observe the remote 3D scene from any freely chosen viewpoint. An intermediate virtual viewpoint image is commonly synthesized using two pairs of transmitted texture and depth maps from two neighboring captured viewpoints via depth-image-based rendering (DIBR). To maintain high quality of synthesized images, it is imperative to contain the adverse effects of network packet losses that may arise during texture and depth video transmission. Towards this end, we develop an integrated approach that exploits the representation redundancy inherent in the multiple streamed videos a voxel in the 3D scene visible to two captured views is sampled and coded twice in the two views. In particular, at the receiver we first develop an error concealment strategy that adaptively blends corresponding pixels in the two captured views during DIBR, so that pixels from the more reliable transmitted view are weighted more heavily. We then couple it with a sender-side optimization of reference picture selection (RPS) during real-time video coding, so that blocks containing samples of voxels that are visible in both views are more error-resiliently coded in one view only, given adaptive blending will erase errors in the other view. Further, synthesized view distortion sensitivities to texture versus depth errors are analyzed, so that relative importance of texture and depth code blocks can be computed for system-wide RPS optimization. Experimental results show that the proposed scheme can outperform the use of a traditional feedback channel by up to 0.82 dB on average at 8% packet loss rate, and by as much as 3 dB for particular frames.
Optimal Scheduling for Energy Harvesting Transmitters with Hybrid Energy Storage
Venue: arXiv cs.IT 2013
Year: 2013

We consider data transmission with an energy harvesting transmitter which has a hybrid energy storage unit composed of a perfectly efficient super-capacitor (SC) and an inefficient battery. The SC has finite space for energy storage while the battery has unlimited space. The transmitter can choose to store the harvested energy in the SC or in the battery. The energy is drained from the SC and the battery simultaneously. In this setting, we consider the offline throughput maximization problem by a deadline over a point-to-point channel. In contrast to previous works, the hybrid energy storage model with finite and unlimited storage capacities imposes a generalized set of constraints on the transmission policy. As such, we show that the solution generalizes that for a single battery and is obtained by applying directional water-filling algorithm multiple times.
Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs
Venue: arXiv cs.AI 2013
Year: 2013

The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem. The model has a variety of real life applications; however, empirical studies of the model are not available in the literature, except in a few isolated instances. In this paper, we develop efficient heuristic algorithms based on tabu search, very large scale neighborhood (VLSN) search, and a hybrid algorithm that integrates the two. The computational study establishes that effective integration of simple tabu search with VLSN search results in superior outcomes, and suggests the value of such an integration in other settings. Complexity analysis and implementation details are provided along with conclusions drawn from experimental analysis. In addition, we obtain solutions better than the best previously known for almost all medium and large size benchmark instances.
Algebraic Net Class Rewriting Systems, Syntax and Semantics for Knowledge Representation and Automated Problem Solving
Venue: arXiv cs.AI 2013
Year: 2013

The intention of the present study is to establish general framework for automated problem solving by approaching the task universal algebraically introducing knowledge as realizations of generalized free algebra based nets, graphs with gluing forms connecting in- and out-edges to nodes. Nets are caused to undergo transformations in conceptual level by type wise differentiated intervening net rewriting systems dispersing problems to abstract parts, matching being determined by substitution relations. Achieved sets of conceptual nets constitute congruent classes. New results are obtained within construction of problem solving systems where solution algorithms are derived parallel with other candidates applied to the same net classes. By applying parallel transducer paths consisting of net rewriting systems to net classes congruent quotient algebras are established and the manifested class rewriting comprises all solution candidates whenever produced nets are in anticipated languages liable to acceptance of net automata.
Computing with and without arbitrary large numbers
Venue: arXiv cs.CC 2013
Year: 2013

In the study of random access machines (RAMs) it has been shown that the availability of an extra input integer, having no special properties other than being sufficiently large, is enough to reduce the computational complexity of some problems. However, this has only been shown so far for specific problems. We provide a characterization of the power of such extra inputs for general problems. To do so, we first correct a classical result by Simon and Szegedy (1992) as well as one by Simon (1981). In the former we show mistakes in the proof and correct these by an entirely new construction, with no great change to the results. In the latter, the original proof direction stands with only minor modifications, but the new results are far stronger than those of Simon (1981). In both cases, the new constructions provide the theoretical tools required to characterize the power of arbitrary large numbers.
Decoding by Sampling - Part II: Derandomization and Soft-output Decoding
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, a derandomized algorithm for sampling decoding is proposed to achieve near-optimal performance in lattice decoding. By setting a probability threshold to sample candidates, the whole sampling procedure becomes deterministic, which brings considerable performance improvement and complexity reduction over to the randomized sampling. Moreover, the upper bound on the sample size K, which corresponds to near-maximum likelihood (ML) performance, is derived. We also find that the proposed algorithm can be used as an efficient tool to implement soft-output decoding in multiple-input multiple-output (MIMO) systems. An upper bound of the sphere radius R in list sphere decoding (LSD) is derived. Based on it, we demonstrate that the derandomized sampling algorithm is capable of achieving near-maximum a posteriori (MAP) performance. Simulation results show that near-optimum performance can be achieved by a moderate size K in both lattice decoding and soft-output decoding.
Towards a semantic and statistical selection of association rules
Venue: arXiv cs.DB 2013
Year: 2013

The increasing growth of databases raises an urgent need for more accurate methods to better understand the stored data. In this scope, association rules were extensively used for the analysis and the comprehension of huge amounts of data. However, the number of generated rules is too large to be efficiently analyzed and explored in any further process. Association rules selection is a classical topic to address this issue, yet, new innovated approaches are required in order to provide help to decision makers. Hence, many interesting- ness measures have been defined to statistically evaluate and filter the association rules. However, these measures present two major problems. On the one hand, they do not allow eliminating irrelevant rules, on the other hand, their abun- dance leads to the heterogeneity of the evaluation results which leads to confusion in decision making. In this paper, we propose a two-winged approach to select statistically in- teresting and semantically incomparable rules. Our statis- tical selection helps discovering interesting association rules without favoring or excluding any measure. The semantic comparability helps to decide if the considered association rules are semantically related i.e comparable. The outcomes of our experiments on real datasets show promising results in terms of reduction in the number of rules.
Homomorphic Encryption: Theory & Applications
Venue: arXiv cs.CR 2013
Year: 2013

The goal of this chapter is to present a survey of homomorphic encryption techniques and their applications. After a detailed discussion on the introduction and motivation of the chapter, we present some basic concepts of cryptography. The fundamental theories of homomorphic encryption are then discussed with suitable examples. The chapter then provides a survey of some of the classical homomorphic encryption schemes existing in the current literature. Various applications and salient properties of homomorphic encryption schemes are then discussed in detail. The chapter then introduces the most important and recent research direction in the filed - fully homomorphic encryption. A significant number of propositions on fully homomorphic encryption is then discussed. Finally, the chapter concludes by outlining some emerging research trends in this exicting field of cryptography.
Optimal Groupon Allocations
Venue: arXiv cs.GT 2013
Year: 2013

Group-buying websites represented by Groupon.com are very popular in electronic commerce and online shopping nowadays. They have multiple slots to provide deals with significant discounts to their visitors every day. The current user traffic allocation mostly relies on human decisions. We study the problem of automatically allocating the user traffic of a group-buying website to different deals to maximize the total revenue and refer to it as the Group-buying Allocation Problem (\GAP). The key challenge of \GAP\ is how to handle the tipping point (lower bound) and the purchase limit (upper bound) of each deal. We formulate \GAP\ as a knapsack-like problem with variable-sized items and majorization constraints. Our main results for \GAP\ can be summarized as follows. (1) We first show that for a special case of \GAP, in which the lower bound equals the upper bound for each deal, there is a simple dynamic programming-based algorithm that can find an optimal allocation in pseudo-polynomial time. (2) The general case of \GAP\ is much more difficult than the special case. To solve the problem, we first discover several structural properties of the optimal allocation, and then design a two-layer dynamic programming-based algorithm leveraging those properties. This algorithm can find an optimal allocation in pseudo-polynomial time. (3) We convert the two-layer dynamic programming based algorithm to a fully polynomial time approximation scheme (FPTAS), using the technique developed in \cite{ibarra1975fast}, combined with some careful modifications of the dynamic programs. Besides these results, we further investigate some natural generalizations of \GAP, and propose effective algorithms.
Questions related to Bitcoin and other Informational Money
Venue: arXiv cs.CY 2013
Year: 2013

A collection of questions about Bitcoin and its hypothetical relatives Bitguilder and Bitpenny is formulated. These questions concern technical issues about protocols, security issues, issues about the formalizations of informational monies in various contexts, and issues about forms of use and misuse. Some questions are formulated in the more general setting of informational monies and near-monies. We also formulate questions about legal, psychological, and ethical aspects of informational money. Finally we formulate a number of questions concerning the economical merits of and outlooks for Bitcoin.