OpenRaiser/Intern-Atlas huggingface dataset:
Cyclic Association Rules Mining under Constraints
Venue: arXiv cs.DB 2012
Year: 2012

Several researchers have explored the temporal aspect of association rules mining. In this paper, we focus on the cyclic association rules, in order to discover correlations among items characterized by regular cyclic variation overtime. The overview of the state of the art has revealed the drawbacks of proposed algorithm literatures, namely the excessive number of generated rules which are not meeting the expert's expectations. To overcome these restrictions, we have introduced our approach dedicated to generate the cyclic association rules under constraints through a new method called Constraint-Based Cyclic Association Rules CBCAR. The carried out experiments underline the usefulness and the performance of our new approach.
Low Complexity Differentiating Adaptive Erasure Codes for Multimedia Wireless Broadcast
Venue: arXiv cs.IT 2012
Year: 2012

Based on the erasure channel FEC model as defined in multimedia wireless broadcast standards, we illustrate how doping mechanisms included in the design of erasure coding and decoding may improve the scalability of the packet throughput, decrease overall latency and potentially differentiate among classes of multimedia subscribers regardless of their signal quality. We describe decoding mechanisms that allow for linear complexity and give complexity bounds when feedback is available. We show that elaborate coding schemes which include pre-coding stages are inferior to simple Ideal Soliton based rateless codes, combined with the proposed two-phase decoder. The simplicity of this scheme and the availability of tight bounds on latency given pre-allocated radio resources makes it a practical and efficient design solution.
Hybrid Data Mining Technique for Knowledge Discovery from Engineering Materials' Data sets
Venue: arXiv cs.DB 2012
Year: 2012

Studying materials informatics from a data mining perspective can be beneficial for manufacturing and other industrial engineering applications. Predictive data mining technique and machine learning algorithm are combined to design a knowledge discovery system for the selection of engineering materials that meet the design specifications. Predictive method-Naive Bayesian classifier and Machine learning Algorithm - Pearson correlation coefficient method were implemented respectively for materials classification and selection. The knowledge extracted from the engineering materials data sets is proposed for effective decision making in advanced engineering materials design applications.
Writing Reusable Digital Geometry Algorithms in a Generic Image Processing Framework
Venue: arXiv cs.MS 2012
Year: 2012

Digital Geometry software should reflect the generality of the underlying mathe- matics: mapping the latter to the former requires genericity. By designing generic solutions, one can effectively reuse digital geometry data structures and algorithms. We propose an image processing framework focused on the Generic Programming paradigm in which an algorithm on the paper can be turned into a single code, written once and usable with various input types. This approach enables users to design and implement new methods at a lower cost, try cross-domain experiments and help generalize results
Memoryless Near-Collisions, Revisited
Venue: arXiv cs.CR 2012
Year: 2012

In this paper we discuss the problem of generically finding near-collisions for cryptographic hash functions in a memoryless way. A common approach is to truncate several output bits of the hash function and to look for collisions of this modified function. In two recent papers, an enhancement to this approach was introduced which is based on classical cycle-finding techniques and covering codes. This paper investigates two aspects of the problem of memoryless near-collisions. Firstly, we give a full treatment of the trade-off between the number of truncated bits and the success-probability of the truncation based approach. Secondly, we demonstrate the limits of cycle-finding methods for finding near-collisions by showing that, opposed to the collision case, a memoryless variant cannot match the query-complexity of the "memory-full" birthday-like near-collision finding method.
An Efficient Color Face Verification Based on 2-Directional 2-Dimensional Feature Extraction
Venue: arXiv cs.CV 2012
Year: 2012

A novel and uniform framework for face verification is presented in this paper. First of all, a 2-directional 2-dimensional feature extraction method is adopted to extract client-specific template - 2D discrimant projection matrix. Then the face skin color information is utilized as an additive feature to enhance decision making strategy that makes use of not only 2D grey feature but also 2D skin color feature. A fusion decision of both is applied to experiment the performance on the XM2VTS database according to Lausanne protocol. Experimental results show that the framework achieves high verification accuracy and verification speed.
Stemmer for Serbian language
Venue: arXiv cs.CL 2012
Year: 2012

In linguistic morphology and information retrieval, stemming is the process for reducing inflected (or sometimes derived) words to their stem, base or root form; generally a written word form. In this work is presented suffix stripping stemmer for Serbian language, one of the highly inflectional languages.
Performance Evaluation of Hierarchical Publish-Subscribe Monitoring Architecture for Service-Oriented Applications
Venue: arXiv cs.DC 2012
Year: 2012

Contemporary high-performance service-oriented applications demand a performance efficient run-time monitoring. In this paper, we analyze a hierarchical publish-subscribe architecture for monitoring service-oriented applications. The analyzed architecture is based on a tree topology and publish-subscribe communication model for aggregation of distributed monitoring data. In order to satisfy interoperability and platform independence of service-orientation, monitoring reports are represented as XML documents. Since XML formatting introduces a significant processing and network load, we analyze the performance of monitoring architecture with respect to the number of monitored nodes, the load of system machines, and the overall latency of the monitoring system.
Controllable-choice Message Sequence Graphs
Venue: arXiv cs.LO 2012
Year: 2012

We focus on the realizability problem of Message Sequence Graphs (MSG), i.e. the problem whether a given MSG specification is correctly distributable among parallel components communicating via messages. This fundamental problem of MSG is known to be undecidable. We introduce a well motivated restricted class of MSG, so called controllable-choice MSG, and show that all its models are realizable and moreover it is decidable whether a given MSG model is a member of this class. In more detail, this class of MSG specifications admits a deadlock-free realization by overloading existing messages with additional bounded control data. We also show that the presented class is the largest known subclass of MSG that allows for deadlock-free realization.
Delay-Optimal Data Forwarding in Vehicular Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

Vehicular Sensor Network (VSN) is emerging as a new solution for monitoring urban environments such as Intelligent Transportation Systems and air pollution. One of the crucial factors that determine the service quality of urban monitoring applications is the delivery delay of sensing data packets in the VSN. In this paper, we study the problem of routing data packets with minimum delay in the VSN, by exploiting i) vehicle traffic statistics, ii) anycast routing and iii) knowledge of future trajectories of vehicles such as buses. We first introduce a novel road network graph model that incorporates the three factors into the routing metric. We then characterize the packet delay on each edge as a function of the vehicle density, speed and the length of the edge. Based on the network model and delay function, we formulate the packet routing problem as a Markov Decision Process (MDP) and develop an optimal routing policy by solving the MDP. Evaluations using real vehicle traces in a city show that our routing policy significantly improves the delay performance compared to existing routing protocols.
Application of Fuzzy Mathematics to Speech-to-Text Conversion by Elimination of Paralinguistic Content
Venue: arXiv cs.AI 2012
Year: 2012

For the past few decades, man has been trying to create an intelligent computer which can talk and respond like he can. The task of creating a system that can talk like a human being is the primary objective of Automatic Speech Recognition. Various Speech Recognition techniques have been developed in theory and have been applied in practice. This paper discusses the problems that have been encountered in developing Speech Recognition, the techniques that have been applied to automate the task, and a representation of the core problems of present day Speech Recognition by using Fuzzy Mathematics.
Strong Secrecy for Multiple Access Channels
Venue: arXiv cs.IT 2012
Year: 2012

We show strongly secret achievable rate regions for two different wiretap multiple-access channel coding problems. In the first problem, each encoder has a private message and both together have a common message to transmit. The encoders have entropy-limited access to common randomness. If no common randomness is available, then the achievable region derived here does not allow for the secret transmission of a common message. The second coding problem assumes that the encoders do not have a common message nor access to common randomness. However, they may have a conferencing link over which they may iteratively exchange rate-limited information. This can be used to form a common message and common randomness to reduce the second coding problem to the first one. We give the example of a channel where the achievable region equals zero without conferencing or common randomness and where conferencing establishes the possibility of secret message transmission. Both coding problems describe practically relevant networks which need to be secured against eavesdropping attacks.
One-side Energy costs of the RBO receiver
Venue: arXiv cs.DS 2012
Year: 2012

Let $n = 2^k$ be the length of the broadcast cycle of the RBO broadcast scheduling protocol (see [arXiv:1108.5095] and [arXiv:1201.3318]). Let $lb$ and $ub$ be the variables of the RBO receiver as defined in [ arXiv:1201.3318 ]. We show that the number of changes of $lb$ (the "left-side energy") is not greater than $k + 1$. We also show that the number of changes of $rb$ (the "right-side energy") is not greater than $k + 2$. Thus the "extra energy" (defined in [arXiv:1201.3318]) is bounded by $2 k + 3$. This updates the previous bound from [arXiv:1201.3318], which was $4 k + 2$.
Counting inequivalent monotone Boolean functions
Venue: arXiv cs.DS 2012
Year: 2012

Monotone Boolean functions (MBFs) are Boolean functions $f: {0,1}^n \rightarrow {0,1}$ satisfying the monotonicity condition $x \leq y \Rightarrow f(x) \leq f(y)$ for any $x,y \in {0,1}^n$. The number of MBFs in n variables is known as the $n$th Dedekind number. It is a longstanding computational challenge to determine these numbers exactly - these values are only known for $n$ at most 8. Two monotone Boolean functions are inequivalent if one can be obtained from the other by renaming the variables. The number of inequivalent MBFs in $n$ variables was known only for up to $n = 6$. In this paper we propose a strategy to count inequivalent MBF's by breaking the calculation into parts based on the profiles of these functions. As a result we are able to compute the number of inequivalent MBFs in 7 variables. The number obtained is 490013148.
Coding and System Design for Quantize-Map-and-Forward Relaying
Venue: arXiv cs.IT 2012
Year: 2012

In this paper we develop a low-complexity coding scheme and system design framework for the half duplex relay channel based on the Quantize-Map-and-Forward (QMF) relay- ing scheme. The proposed framework allows linear complexity operations at all network terminals. We propose the use of binary LDPC codes for encoding at the source and LDGM codes for mapping at the relay. We express joint decoding at the destination as a belief propagation algorithm over a factor graph. This graph has the LDPC and LDGM codes as subgraphs connected via probabilistic constraints that model the QMF relay operations. We show that this coding framework extends naturally to the high SNR regime using bit interleaved coded modulation (BICM). We develop density evolution analysis tools for this factor graph and demonstrate the design of practical codes for the half-duplex relay channel that perform within 1dB of information theoretic QMF threshold.
Capacity of Gaussian Channels with Duty Cycle and Power Constraints
Venue: arXiv cs.IT 2012
Year: 2012

In many wireless communication systems, radios are subject to a duty cycle constraint, that is, a radio only actively transmits signals over a fraction of the time. For example, it is desirable to have a small duty cycle in some low power systems; a half-duplex radio cannot keep transmitting if it wishes to receive useful signals; and a cognitive radio needs to listen and detect primary users frequently. This work studies the capacity of scalar discrete-time Gaussian channels subject to duty cycle constraint as well as average transmit power constraint. An idealized duty cycle constraint is first studied, which can be regarded as a requirement on the minimum fraction of nontransmissions or zero symbols in each codeword. A unique discrete input distribution is shown to achieve the channel capacity. In many situations, numerically optimized on-off signaling can achieve much higher rate than Gaussian signaling over a deterministic transmission schedule. This is in part because the positions of nontransmissions in a codeword can convey information. Furthermore, a more realistic duty cycle constraint is studied, where the extra cost of transitions between transmissions and nontransmissions due to pulse shaping is accounted for. The capacity-achieving input is no longer independent over time and is hard to compute. A lower bound of the achievable rate as a function of the input distribution is shown to be maximized by a first-order Markov input process, the distribution of which is also discrete and can be computed efficiently. The results in this paper suggest that, under various duty cycle constraints, departing from the usual paradigm of intermittent packet transmissions may yield substantial gain.
Pseudo-random Aloha for Enhanced Collision-recovery in RFID
Venue: arXiv cs.NI 2012
Year: 2012

In this letter we motivate the need to revisit the MAC protocol used in Gen2 RFID system in order to leverage receiver structures with Collision Recovery capabilities at the PHY layer. To this end we propose to consider a simple variant of the Framed Slotted Aloha with pseudo-random (deterministic) slot selection as opposite to the classical random selection. Pseudo-random access allows naturally to implement Inter-frame Successive Interference Cancellation (ISIC) without changing the PHY modulation and coding format of legacy RFID standard. By means of simulations we show that ISIC can bring 20-25% gain in throughput with respect to traditional intra-frame SIC. Besides that, we elaborate on the potential of leveraging pseudo-random access protocols in combination with advanced PHY techniques in the context of RFID applications.
Counting common substrings effectively
Venue: arXiv cs.DS 2012
Year: 2012

This article presents effective (dynamic) algorithm for solving a problem of counting the number of substrings of given string which are also substrings of second string. Presented algorithm can be used for example for quick calculation of strings similarity measure using generalized $n$-gram method (Niewiadomski measure), which are shown. Correctness and complexity analyses are included. ----- W artykule przedstawiono efektywny (dynamiczny) algorytm wyznaczający miarę podobieństwa wyrazów za pomocą uogólnionej metody $n$-gramów (miary Niewiadomskiego). Uzasadniono także poprawność działania algorytmu i oszacowano jego złożoność obliczeniową.
A Novel Image Encryption Using an Integration Technique of Blocks Rotation Based on the Magic Cube and the AES Algorithm
Venue: arXiv cs.CR 2012
Year: 2012

In recent years, several encryption algorithms have been proposed to protect digital images from cryptographic attacks. These encryption algorithms typically use a relatively small key space and therefore, provide safe, especially if they are of a dimension. In this paper proposes an encryption algorithm for a new image protection scheme based on the rotation of the faces of a Magic Cube. The original image is divided into six sub-images and these sub-images are divided amongst a number of blocks and attached to the faces of a Magic Cube. The faces are then scrambled using rotation of the Magic Cube. Then the rotated image is fed to the AES algorithm which is applied to the pixels of the image to encrypt the scrambled image. Finally, experimental results and security analysis show that the proposed image encryption scheme not only encrypts the picture to achieve perfect hiding, but the algorithm can also withstand exhaustive, statistical and differential attacks.
Sparse Signal Recovery from Quadratic Measurements via Convex Programming
Venue: arXiv cs.IT 2012
Year: 2012

In this paper we consider a system of quadratic equations |<z_j, x>|^2 = b_j, j = 1, ..., m, where x in R^n is unknown while normal random vectors z_j in R_n and quadratic measurements b_j in R are known. The system is assumed to be underdetermined, i.e., m < n. We prove that if there exists a sparse solution x, i.e., at most k components of x are non-zero, then by solving a convex optimization program, we can solve for x up to a multiplicative constant with high probability, provided that k <= O((m/log n)^(1/2)). On the other hand, we prove that k <= O(log n (m)^(1/2)) is necessary for a class of naive convex relaxations to be exact.
Dynamic Resource Management in Clouds: A Probabilistic Approach
Venue: arXiv cs.NI 2012
Year: 2012

Dynamic resource management has become an active area of research in the Cloud Computing paradigm. Cost of resources varies significantly depending on configuration for using them. Hence efficient management of resources is of prime interest to both Cloud Providers and Cloud Users. In this work we suggest a probabilistic resource provisioning approach that can be exploited as the input of a dynamic resource management scheme. Using a Video on Demand use case to justify our claims, we propose an analytical model inspired from standard models developed for epidemiology spreading, to represent sudden and intense workload variations. We show that the resulting model verifies a Large Deviation Principle that statistically characterizes extreme rare events, such as the ones produced by "buzz/flash crowd effects" that may cause workload overflow in the VoD context. This analysis provides valuable insight on expectable abnormal behaviors of systems. We exploit the information obtained using the Large Deviation Principle for the proposed Video on Demand use-case for defining policies (Service Level Agreements). We believe these policies for elastic resource provisioning and usage may be of some interest to all stakeholders in the emerging context of cloud networking
Efficient Refreshing Protocol for Leakage-Resilient Storage Based on the Inner-Product Extractor
Venue: arXiv cs.CR 2012
Year: 2012

A recent trend in cryptography is to protect data and computation against various side-channel attacks. Dziembowski and Faust (TCC 2012) have proposed a general way to protect arbitrary circuits against any continual leakage assuming that: (i) the memory is divided into the parts, which leaks independently (ii) the leakage in each observation is bounded (iii) the circuit has an access to a leak-free component, which samples random orthogonal vectors. The pivotal element of their construction is a protocol for refreshing the so-called Leakage-Resilient Storage (LRS). In this note, we present a more efficient and simpler protocol for refreshing LRS under the same assumptions. Our solution needs O(n) operations to fully refresh the secret (in comparison to Ω(n^2) for a protocol of Dziembowski and Faust), where n is a security parameter that describes the maximal amount of leakage in each invocation of the refreshing procedure
Formal Definition of AI
Venue: arXiv cs.AI 2012
Year: 2012

A definition of Artificial Intelligence was proposed in [1] but this definition was not absolutely formal at least because the word "Human" was used. In this paper we will formalize the definition from [1]. The biggest problem in this definition was that the level of intelligence of AI is compared to the intelligence of a human being. In order to change this we will introduce some parameters to which AI will depend. One of this parameters will be the level of intelligence and we will define one AI to each level of intelligence. We assume that for some level of intelligence the respective AI will be more intelligent than a human being. Nevertheless, we cannot say which is this level because we cannot calculate its exact value.
The Future of Neural Networks
Venue: arXiv cs.NE 2012
Year: 2012

The paper describes some recent developments in neural networks and discusses the applicability of neural networks in the development of a machine that mimics the human brain. The paper mentions a new architecture, the pulsed neural network that is being considered as the next generation of neural networks. The paper also explores the use of memristors in the development of a brain-like computer called the MoNETA. A new model, multi/infinite dimensional neural networks, are a recent development in the area of advanced neural networks. The paper concludes that the need of neural networks in the development of human-like technology is essential and may be non-expendable for it.
Locating Disruptions on Internet Paths through End-to-End Measurements
Venue: arXiv cs.NI 2012
Year: 2012

In backbone networks carrying heavy traffic loads, unwanted and unusual end-to-end delay changes can happen, though possibly rarely. In order to understand and manage the network to potentially avoid such abrupt changes, it is crucial and challenging to locate where in the network lies the cause of such delays so that some corresponding actions may be taken. To tackle this challenge, the present paper proposes a simple and novel approach. The proposed approach relies only on end-to-end measurements, unlike literature approaches that often require a distributed and possibly complicated monitoring / measurement infrastructure. Here, the key idea of the proposed approach is to make use of compressed sensing theory to estimate delays on each hop between the two nodes where end-to-end delay measurement is conducted, and infer critical hops that contribute to the abrupt delay increases. To demonstrate its effectiveness, the proposed approach is applied to a real network. The results are encouraging, showing that the proposed approach is able to locate the hops that have the most significant impact on or contribute the most to abrupt increases on the end-to-end delay.