OpenRaiser/Intern-Atlas huggingface dataset:
Emergence of wave patterns on Kadanoff Sandpiles
Venue: arXiv cs.DM 2013
Year: 2013

Emergence is a concept that is easy to exhibit, but very hard to formally handle. This paper is about cubic sand grains moving around on nicely packed columns in one dimension (the physical sandpile is two dimensional, but the support of sand columns is one dimensional). The Kadanoff Sandpile Model is a discrete dynamical system describing the evolution of a finite number of stacked grains --as they would fall from an hourglass-- to a stable configuration (fixed point). Grains move according to the repeated application of a simple local rule until reaching a fixed point. The main interest of the model relies in the difficulty of understanding its behavior, despite the simplicity of the rule. In this paper we prove the emergence of wave patterns periodically repeated on fixed points. Remarkably, those regular patterns do not cover the entire fixed point, but eventually emerge from a seemingly highly disordered segment. The proof technique we set up associates arguments of linear algebra and combinatorics, which interestingly allow to formally state the emergence of regular patterns without requiring a precise understanding of the chaotic initial segment's dynamic.
Elementos de ingeniería de explotación de la información: réplica y algunos trazos sobre teoría informática
Venue: arXiv cs.IT 2013
Year: 2013

A reply to the commentaries of Yana (2013), and some jots on information theory.
Autonomous Quantum Perceptron Neural Network
Venue: arXiv cs.NE 2013
Year: 2013

Recently, with the rapid development of technology, there are a lot of applications require to achieve low-cost learning. However the computational power of classical artificial neural networks, they are not capable to provide low-cost learning. In contrast, quantum neural networks may be representing a good computational alternate to classical neural network approaches, based on the computational power of quantum bit (qubit) over the classical bit. In this paper we present a new computational approach to the quantum perceptron neural network can achieve learning in low-cost computation. The proposed approach has only one neuron can construct self-adaptive activation operators capable to accomplish the learning process in a limited number of iterations and, thereby, reduce the overall computational cost. The proposed approach is capable to construct its own set of activation operators to be applied widely in both quantum and classical applications to overcome the linearity limitation of classical perceptron. The computational power of the proposed approach is illustrated via solving variety of problems where promising and comparable results are given.
Post-Quantum Cryptography: Code-based Signatures
Venue: arXiv cs.CR 2013
Year: 2013

This survey provides a comparative overview of code-based signature schemes with respect to security and performance. Furthermore, we explicitly describe serveral code-based signature schemes with additional properties such as identity-based, threshold ring and blind signatures.
Uniqueness Conditions for A Class of l0-Minimization Problems
Venue: arXiv cs.IT 2013
Year: 2013

We consider a class of l0-minimization problems, which is to search for the partial sparsest solution to an underdetermined linear system with additional constraints. We introduce several concepts, including lp-induced norm (0 < p < 1), maximal scaled spark and scaled mutual coherence, to develop several new uniqueness conditions for the partial sparsest solution to this class of l0-minimization problems. A further improvement of some of these uniqueness criteria have been also achieved through the so-called concepts such as maximal scaled (sub)coherence rank.
Virtual Reality: A Definition History - A Personal Essay
Venue: arXiv cs.HC 2013
Year: 2013

This essay, written in 1998 by an active participant in both virtual reality development and the virtual reality definition debate, discusses the definition of the phrase "Virtual Reality" (VR). I start with history from a personal perspective, concentrating on the debate between the "Virtual Reality" and "Virtual Environment" labels in the late 1980's and early 1990's. Definitions of VR based on specific technologies are shown to be unsatisfactory. I propose the following definition of VR, based on the striking effects of a good VR system: "Virtual Reality is the use of computer technology to create the effect of an interactive three-dimensional world in which the objects have a sense of spatial presence." The justification for this definition is discussed in detail, and is favorably compared with the dictionary definitions of "virtual" and "reality". The implications of this definition for virtual reality technology are briefly examined.
An improved Branch-and-cut code for the maximum balanced subgraph of a signed graph
Venue: arXiv cs.DM 2013
Year: 2013

The Maximum Balanced Subgraph Problem (MBSP) is the problem of finding a subgraph of a signed graph that is balanced and maximizes the cardinality of its vertex set. We are interested in the exact solution of the problem: an improved version of a branch-and-cut algorithm is proposed. Extensive computational experiments are carried out on a set of instances from three applications previously discussed in the literature as well as on a set of random instances.
Teleoperation System Using Past Image Records Considering Narrow Communication Band
Venue: arXiv cs.RO 2013
Year: 2013

Teleoperation is necessary when the robot is applied to real missions, for example surveillance, search and rescue. We proposed teleoperation system using past image records (SPIR). SPIR virtually generates the bird's-eye view image by overlaying the CG model of the robot at the corresponding current position on the background image which is captured from the camera mounted on the robot at a past time. The problem for SPIR is that the communication bandwidth is often narrow in some teleoperation tasks. In this case, the candidates of background image of SPIR are few and the position of the robot is often delayed. In this study, we propose zoom function for insufficiency of candidates of the background image and additional interpolation lines for the delay of the position data of the robot. To evaluate proposed system, an outdoor experiments are carried out. The outdoor experiment is conducted on a training course of a driving school.
On the number of proper $k$-colorings in an $n$-gon
Venue: arXiv cs.DM 2013
Year: 2013

We define an $n$-gon to be any convex polygon with $n$ vertices. Let $V$ represent the set of vertices of the polygon. A proper $k$-coloring refers to a function, $f$ : $V$ $\rightarrow$ $\{1, 2, 3, ... k\}$, such that for any two vertices $u$ and $v$, if $f(u) = f(v)$, $u$ is not adjacent to $v$. The purpose of this paper is to develop a recursive algorithm to compute the number of proper $k$-colorings in an $n$-gon. The proposed algorithm can easily be solved to obtain the explicit expression. This matches the explicit expression obtained from the popular conventional solutions, which confirms the correctness of the proposed algorithm. Often, for huge values of $n$ and $k$, it becomes impractical to display the output numbers, which would consist of thousands of digits. We report the answer modulo a certain number. In such situations, the proposed algorithm is observed to run slightly faster than the conventional recursive algorithm.
Technical Report: A New Multi-Device Wireless Power Transfer Scheme Using an Intermediate Energy Storage Circuit
Venue: arXiv cs.OH 2013
Year: 2013

A new multi-device wireless power transfer scheme that reduces the overall charging time is presented. The proposed scheme employs the intermediated energy storage (IES) circuit which consists of a constant power driving circuit and a super-capacitor. By utilizing the characteristic of high power density of the super-capacitor, the receiver can receive and store the energy in short duration and supply to the battery for long time. This enables the overlap of charging duration between all receivers. As a result, the overall charging time can be reduced.
Weyl-Heisenberg Spaces for Robust Orthogonal Frequency Division Multiplexing
Venue: arXiv cs.IT 2013
Year: 2013

Design of Weyl-Heisenberg sets of waveforms for robust orthogonal frequency division multiplex- ing (OFDM) has been the subject of a considerable volume of work. In this paper, a complete parameterization of orthogonal Weyl-Heisenberg sets and their corresponding biorthogonal sets is given. Several examples of Weyl-Heisenberg sets designed using this parameterization are pre- sented, which in simulations show a high potential for enabling OFDM robust to frequency offset, timing mismatch, and narrow-band interference.
A Functional Approach to Standard Binary Heaps
Venue: arXiv cs.DS 2013
Year: 2013

This paper describes a new and purely functional implementation technique of binary heaps. A binary heap is a tree-based data structure that implements priority queue operations (insert, remove, minimum/maximum) and guarantees at worst logarithmic running time for them. Approaches and ideas described in this paper present a simple and asymptotically optimal implementation of immutable binary heap.
Finite Horizon Online Lazy Scheduling with Energy Harvesting Transmitters over Fading Channels
Venue: arXiv cs.IT 2013
Year: 2013

Lazy scheduling, i.e. setting transmit power and rate in response to data traffic as low as possible so as to satisfy delay constraints, is a known method for energy efficient transmission.This paper addresses an online lazy scheduling problem over finite time-slotted transmission window and introduces low-complexity heuristics which attain near-optimal performance.Particularly, this paper generalizes lazy scheduling problem for energy harvesting systems to deal with packet arrival, energy harvesting and time-varying channel processes simultaneously. The time-slotted formulation of the problem and depiction of its offline optimal solution provide explicit expressions allowing to derive good online policies and algorithms.
Analysis of MIMO Systems used in planning a 4G-WiMAX Network in Ghana
Venue: arXiv cs.IT 2013
Year: 2013

With the increasing demand for mobile data services, Broadband Wireless Access (BWA) is emerging as one of the fastest growing areas within mobile communications. Innovative wireless communication systems, such as WiMAX, are expected to offer highly reliable broadband radio access in order to meet the increasing demands of emerging high speed data and multimedia services. In Ghana, deployment of WiMAX technology has recently begun. Planning these high capacity networks in the presence of multiple interferences in order to achieve the aim of enabling users enjoy cheap and reliable internet services is a critical design issue. This paper has used a deterministic approach for simulating the Bit-Error-Rate (BER) of initial MIMO antenna configurations which were considered in deploying a high capacity 4G-WiMAX network in Ghana. The radiation pattern of the antenna used in the deploying the network has been simulated with Genex-Unet and NEC and results presented. An adaptive 4x4 MIMO antenna configuration with optimally suppressed sidelobes has been suggested for future network deployment since the adaptive 2x2 MIMO antenna configuration, which was used in the initial network deployment provides poor estimates for average BER performance as compared to 4x4 antenna configuration which seem less affected in the presence of multiple interferers.
Locating Multiple Ultrasound Targets in Chorus
Venue: arXiv cs.IT 2013
Year: 2013

Ranging by Time of Arrival (TOA) of Narrow-band ultrasound (NBU) has been widely used by many locating systems for its characteristics of low cost and high accuracy. However, because it is hard to support code division multiple access in narrowband signal, to track multiple targets, existing NBU-based locating systems generally need to assign exclusive time slot to each target to avoid the signal conflicts. Because the propagation speed of ultrasound is slow in air, dividing exclusive time slots on a single channel causes the location updating rate for each target rather low, leading to unsatisfied tracking performances as the number of targets increases. In this paper, we investigated a new multiple target locating method using NBU, called UltraChorus, which is to locate multiple targets while allowing them sending NBU signals simultaneously, i.e., in chorus mode. It can dramatically increase the location updating rate. In particular, we investigated by both experiments and theoretical analysis on the necessary and sufficient conditions for resolving the conflicts of multiple NBU signals on a single channel, which is referred as the conditions for chorus ranging and chorus locating. To tackle the difficulty caused by the anonymity of the measured distances, we further developed consistent position generation algorithm and probabilistic particle filter algorithm}to label the distances by sources, to generate reasonable location estimations, and to disambiguate the motion trajectories of the multiple concurrent targets based on the anonymous distance measurements. Extensive evaluations by both simulation and testbed were carried out, which verified the effectiveness of our proposed theories and algorithms.
Dual Layer Textual Message Cryptosystem with Randomized Sequence of Symmetric Key
Venue: arXiv cs.CR 2013
Year: 2013

This paper introduces a new concept of textual message encryption and decryption through a pool of randomized symmetric key and the dual layer cryptosystem with the concept of visual cryptography and steganography. A textual message is converted into two image slides, and the images are encrypted through two different randomized sequences of symmetric key. The decryption is done in the reverse way. The encrypted images are decrypted by those two symmetric keys. The decrypted image slides are merged together and converted into textual message. Here the image sharing is done through the concept of visual cryptography and the textual message to image conversion is done through the concept of steganography.
Codebook based Audio Feature Representation for Music Information Retrieval
Venue: arXiv cs.IR 2013
Year: 2013

Digital music has become prolific in the web in recent decades. Automated recommendation systems are essential for users to discover music they love and for artists to reach appropriate audience. When manual annotations and user preference data is lacking (e.g. for new artists) these systems must rely on \emph{content based} methods. Besides powerful machine learning tools for classification and retrieval, a key component for successful recommendation is the \emph{audio content representation}. Good representations should capture informative musical patterns in the audio signal of songs. These representations should be concise, to enable efficient (low storage, easy indexing, fast search) management of huge music repositories, and should also be easy and fast to compute, to enable real-time interaction with a user supplying new songs to the system. Before designing new audio features, we explore the usage of traditional local features, while adding a stage of encoding with a pre-computed \emph{codebook} and a stage of pooling to get compact vectorial representations. We experiment with different encoding methods, namely \emph{the LASSO}, \emph{vector quantization (VQ)} and \emph{cosine similarity (CS)}. We evaluate the representations' quality in two music information retrieval applications: query-by-tag and query-by-example. Our results show that concise representations can be used for successful performance in both applications. We recommend using top-$τ$ VQ encoding, which consistently performs well in both applications, and requires much less computation time than the LASSO.
Bar 1-Visibility Graphs and their relation to other Nearly Planar Graphs
Venue: arXiv cs.DS 2013
Year: 2013

A graph is called a strong (resp. weak) bar 1-visibility graph if its vertices can be represented as horizontal segments (bars) in the plane so that its edges are all (resp. a subset of) the pairs of vertices whose bars have a $ε$-thick vertical line connecting them that intersects at most one other bar. We explore the relation among weak (resp. strong) bar 1-visibility graphs and other nearly planar graph classes. In particular, we study their relation to 1-planar graphs, which have a drawing with at most one crossing per edge; quasi-planar graphs, which have a drawing with no three mutually crossing edges; the squares of planar 1-flow networks, which are upward digraphs with in- or out-degree at most one. Our main results are that 1-planar graphs and the (undirected) squares of planar 1-flow networks are weak bar 1-visibility graphs and that these are quasi-planar graphs.
Playing Atari with Deep Reinforcement Learning
Venue: arXiv cs.LG 2013
Year: 2013

We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards. We apply our method to seven Atari 2600 games from the Arcade Learning Environment, with no adjustment of the architecture or learning algorithm. We find that it outperforms all previous approaches on six of the games and surpasses a human expert on three of them.
An Introduction to Socially Connected Machines: Characteristics and Applications
Venue: arXiv cs.SI 2013
Year: 2013

Due to the development of information and communication technologies, it is difficult to handle the billions of connected machines. In this paper, to cope with the problem, we introduce machine social networks, where they freely follow each other and share common interests with their neighbors. We classify characteristics and describe required functionalities of socially connected machines. We also illustrate two examples; a twit-bot and maze scenario.
Support for Error Tolerance in the Real-Time Transport Protocol
Venue: arXiv cs.NI 2013
Year: 2013

Streaming applications often tolerate bit errors in their received data well. This is contrasted by the enforcement of correctness of the packet headers and payload by network protocols. We investigate a solution for the Real-time Transport Protocol (RTP) that is tolerant to errors by accepting erroneous data. It passes potentially corrupted stream data payloads to the codecs. If errors occur in the header, our solution recovers from these by leveraging the known state and expected header values for each stream. The solution is fully receiver-based and incrementally deployable, and as such requires neither support from the sender nor changes to the RTP specification. Evaluations show that our header error recovery scheme can recover from almost all errors, with virtually no erroneous recoveries, up to bit error rates of about 10%.
Developing a model of evacuation after an earthquake in Lebanon
Venue: arXiv cs.MA 2013
Year: 2013

This article describes the development of an agent-based model (AMEL, Agent-based Model for Earthquake evacuation in Lebanon) that aims at simulating the movement of pedestrians shortly after an earthquake. The GAMA platform was chosen to implement the model. AMEL is applied to a real case study, a district of the city of Beirut, Lebanon, which potentially could be stricken by a M7 earthquake. The objective of the model is to reproduce real life mobility behaviours that have been gathered through a survey in Beirut and to test different future scenarios, which may help the local authorities to target information campaigns.
Succinct representation of labeled trees
Venue: arXiv cs.DS 2013
Year: 2013

We give a representation for labeled ordered trees that supports labeled queries such as finding the i-th ancestor of a node with a given label. Our representation is succinct, namely the redundancy is small-o of the optimal space for storing the tree. This improves the representation of He et al. which is succinct unless the entropy of the labels is small.
Aspartame: Solving Constraint Satisfaction Problems with Answer Set Programming
Venue: arXiv cs.AI 2013
Year: 2013

Encoding finite linear CSPs as Boolean formulas and solving them by using modern SAT solvers has proven to be highly effective, as exemplified by the award-winning sugar system. We here develop an alternative approach based on ASP. This allows us to use first-order encodings providing us with a high degree of flexibility for easy experimentation with different implementations. The resulting system aspartame re-uses parts of sugar for parsing and normalizing CSPs. The obtained set of facts is then combined with an ASP encoding that can be grounded and solved by off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting aspartame and sugar.
A System for Interactive Query Answering with Answer Set Programming
Venue: arXiv cs.AI 2013
Year: 2013

Reactive answer set programming has paved the way for incorporating online information into operative solving processes. Although this technology was originally devised for dealing with data streams in dynamic environments, like assisted living and cognitive robotics, it can likewise be used to incorporate facts, rules, or queries provided by a user. As a result, we present the design and implementation of a system for interactive query answering with reactive answer set programming. Our system quontroller is based on the reactive solver oclingo and implemented as a dedicated front-end. We describe its functionality and implementation, and we illustrate its features by some selected use cases.
Learned versus Hand-Designed Feature Representations for 3d Agglomeration
Venue: arXiv cs.CV 2013
Year: 2013

For image recognition and labeling tasks, recent results suggest that machine learning methods that rely on manually specified feature representations may be outperformed by methods that automatically derive feature representations based on the data. Yet for problems that involve analysis of 3d objects, such as mesh segmentation, shape retrieval, or neuron fragment agglomeration, there remains a strong reliance on hand-designed feature descriptors. In this paper, we evaluate a large set of hand-designed 3d feature descriptors alongside features learned from the raw data using both end-to-end and unsupervised learning techniques, in the context of agglomeration of 3d neuron fragments. By combining unsupervised learning techniques with a novel dynamic pooling scheme, we show how pure learning-based methods are for the first time competitive with hand-designed 3d shape descriptors. We investigate data augmentation strategies for dramatically increasing the size of the training set, and show how combining both learned and hand-designed features leads to the highest accuracy.
Large-Scale Paralleled Sparse Principal Component Analysis
Venue: arXiv cs.MS 2013
Year: 2013

Principal component analysis (PCA) is a statistical technique commonly used in multivariate data analysis. However, PCA can be difficult to interpret and explain since the principal components (PCs) are linear combinations of the original variables. Sparse PCA (SPCA) aims to balance statistical fidelity and interpretability by approximating sparse PCs whose projections capture the maximal variance of original data. In this paper we present an efficient and paralleled method of SPCA using graphics processing units (GPUs), which can process large blocks of data in parallel. Specifically, we construct parallel implementations of the four optimization formulations of the generalized power method of SPCA (GP-SPCA), one of the most efficient and effective SPCA approaches, on a GPU. The parallel GPU implementation of GP-SPCA (using CUBLAS) is up to eleven times faster than the corresponding CPU implementation (using CBLAS), and up to 107 times faster than a MatLab implementation. Extensive comparative experiments in several real-world datasets confirm that SPCA offers a practical advantage.