OpenRaiser/Intern-Atlas huggingface dataset:
MotàMot project: conversion of a French-Khmer published dictionary for building a multilingual lexical system
Venue: arXiv cs.CL 2014
Year: 2014

Economic issues related to the information processing techniques are very important. The development of such technologies is a major asset for developing countries like Cambodia and Laos, and emerging ones like Vietnam, Malaysia and Thailand. The MotAMot project aims to computerize an under-resourced language: Khmer, spoken mainly in Cambodia. The main goal of the project is the development of a multilingual lexical system targeted for Khmer. The macrostructure is a pivot one with each word sense of each language linked to a pivot axi. The microstructure comes from a simplification of the explanatory and combinatory dictionary. The lexical system has been initialized with data coming mainly from the conversion of the French-Khmer bilingual dictionary of Denis Richer from Word to XML format. The French part was completed with pronunciation and parts-of-speech coming from the FeM French-english-Malay dictionary. The Khmer headwords noted in IPA in the Richer dictionary were converted to Khmer writing with OpenFST, a finite state transducer tool. The resulting resource is available online for lookup, editing, download and remote programming via a REST API on a Jibiki platform.
Distance-bounding facing both mafia and distance frauds: Technical report*
Venue: arXiv cs.CR 2014
Year: 2014

Contactless technologies such as RFID, NFC, and sensor networks are vulnerable to mafia and distance frauds. Both frauds aim at passing an authentication protocol by cheating on the actual distance between the prover and the verifier. To cope these security issues, distance-bounding protocols have been designed. However, none of the current proposals simultaneously resists to these two frauds without requiring additional memory and computation. The situation is even worse considering that just a few distance-bounding protocols are able to deal with the inherent background noise on the communication channels. This article introduces a noise-resilient distance-bounding protocol that resists to both mafia and distance frauds. The security of the protocol is analyzed with respect to these two frauds in both scenarios, namely noisy and noiseless channels. Analytical expressions for the adversary's success probabilities are provided, and are illustrated by experimental results. The analysis, performed in an already existing framework for fairness reasons, demonstrates the undeniable advantage of the introduced lightweight design over the previous proposals.
Learning to Generate Networks
Venue: arXiv cs.LG 2014
Year: 2014

We investigate the problem of learning to generate complex networks from data. Specifically, we consider whether deep belief networks, dependency networks, and members of the exponential random graph family can learn to generate networks whose complex behavior is consistent with a set of input examples. We find that the deep model is able to capture the complex behavior of small networks, but that no model is able capture this behavior for networks with more than a handful of nodes.
Performance Guarantees for ReProCS -- Correlated Low-Rank Matrix Entries Case
Venue: arXiv cs.IT 2014
Year: 2014

Online or recursive robust PCA can be posed as a problem of recovering a sparse vector, $S_t$, and a dense vector, $L_t$, which lies in a slowly changing low-dimensional subspace, from $M_t:= S_t + L_t$ on-the-fly as new data comes in. For initialization, it is assumed that an accurate knowledge of the subspace in which $L_0$ lies is available. In recent works, Qiu et al proposed and analyzed a novel solution to this problem called recursive projected compressed sensing or ReProCS. In this work, we relax one limiting assumption of Qiu et al's result. Their work required that the $L_t$'s be mutually independent over time. However this is not a practical assumption, e.g., in the video application, $L_t$ is the background image sequence and one would expect it to be correlated over time. In this work we relax this and allow the $L_t$'s to follow an autoregressive model. We are able to show that under mild assumptions and under a denseness assumption on the unestimated part of the changed subspace, with high probability (w.h.p.), ReProCS can exactly recover the support set of $S_t$ at all times; the reconstruction errors of both $S_t$ and $L_t$ are upper bounded by a time invariant and small value; and the subspace recovery error decays to a small value within a finite delay of a subspace change time. Because the last assumption depends on an algorithm estimate, this result cannot be interpreted as a correctness result but only a useful step towards it.
Low-complexity video encoder for smart eyes based on underdetermined blind signal separation
Venue: arXiv cs.MM 2014
Year: 2014

This paper presents a low complexity video coding method based on Underdetermined Blind Signal Separation (UBSS). The detailed coding framework is designed. Three key techniques are proposed to enhance the compression ratio and the quality of the decoded frames. The experiments validate that the proposed method costs 30ms encoding time less than DISCOVER. The simulation shows that this new method can save 50% energy compared with H.264.
Compositional Reasoning for Explicit Resource Management in Channel-Based Concurrency
Venue: arXiv cs.LO 2014
Year: 2014

We define a pi-calculus variant with a costed semantics where channels are treated as resources that must explicitly be allocated before they are used and can be deallocated when no longer required. We use a substructural type system tracking permission transfer to construct coinductive proof techniques for comparing behaviour and resource usage efficiency of concurrent processes. We establish full abstraction results between our coinductive definitions and a contextual behavioural preorder describing a notion of process efficiency w.r.t. its management of resources. We also justify these definitions and respective proof techniques through numerous examples and a case study comparing two concurrent implementations of an extensible buffer.
A Study of Local Binary Pattern Method for Facial Expression Detection
Venue: arXiv cs.CV 2014
Year: 2014

Face detection is a basic task for expression recognition. The reliability of face detection & face recognition approach has a major role on the performance and usability of the entire system. There are several ways to undergo face detection & recognition. We can use Image Processing Operations, various classifiers, filters or virtual machines for the former. Various strategies are being available for Facial Expression Detection. The field of facial expression detection can have various applications along with its importance & can be interacted between human being & computer. Many few options are available to identify a face in an image in accurate & efficient manner. Local Binary Pattern (LBP) based texture algorithms have gained popularity in these years. LBP is an effective approach to have facial expression recognition & is a feature-based approach.
A review over the applicability of image entropy in analyses of remote sensing datasets
Venue: arXiv cs.CV 2014
Year: 2014

Entropy is the measure of uncertainty in any data and is adopted for maximisation of mutual information in many remote sensing operations. The availability of wide entropy variations motivated us for an investigation over the suitability preference of these versions to specific operations.
A Bi-clustering Framework for Consensus Problems
Venue: arXiv cs.CV 2014
Year: 2014

We consider grouping as a general characterization for problems such as clustering, community detection in networks, and multiple parametric model estimation. We are interested in merging solutions from different grouping algorithms, distilling all their good qualities into a consensus solution. In this paper, we propose a bi-clustering framework and perspective for reaching consensus in such grouping problems. In particular, this is the first time that the task of finding/fitting multiple parametric models to a dataset is formally posed as a consensus problem. We highlight the equivalence of these tasks and establish the connection with the computational Gestalt program, that seeks to provide a psychologically-inspired detection theory for visual events. We also present a simple but powerful bi-clustering algorithm, specially tuned to the nature of the problem we address, though general enough to handle many different instances inscribed within our characterization. The presentation is accompanied with diverse and extensive experimental results in clustering, community detection, and multiple parametric model estimation in image processing applications.
An Effective Evolutionary Clustering Algorithm: Hepatitis C Case Study
Venue: arXiv cs.NE 2014
Year: 2014

Clustering analysis plays an important role in scientific research and commercial application. K-means algorithm is a widely used partition method in clustering. However, it is known that the K-means algorithm may get stuck at suboptimal solutions, depending on the choice of the initial cluster centers. In this article, we propose a technique to handle large scale data, which can select initial clustering center purposefully using Genetic algorithms (GAs), reduce the sensitivity to isolated point, avoid dissevering big cluster, and overcome deflexion of data in some degree that caused by the disproportion in data partitioning owing to adoption of multi-sampling. We applied our method to some public datasets these show the advantages of the proposed approach for example Hepatitis C dataset that has been taken from the machine learning warehouse of University of California. Our aim is to evaluate hepatitis dataset. In order to evaluate this dataset we did some preprocessing operation, the reason to preprocessing is to summarize the data in the best and suitable way for our algorithm. Missing values of the instances are adjusted using local mean method.
Metrics for BPEL Process Reusability Analysis in a Workflow System
Venue: arXiv cs.SE 2014
Year: 2014

This work proposes a quantitative metric to analyze potential reusability of a BPEL (Business Process Execution Language) Process. The approach is based on Description and Logic Mismatch Probability of a BPEL Process that will be reused within potential contexts. The mismatch probabilities have been consolidated to a metric formula for quantifying the probability of potential reuse of BPEL processes. An initial empirical evaluation suggests that the proposed metric properly predict potential reusability of BPEL processes. According to the experiment, there exists a significant statistical correlation between results of the metric and the experts judgements. This indicates a predictive dependency between the proposed metric and potential reusability of BPEL processes as a measuring stick for this phenomena. If future studies ascertain these findings by replicating this experiment, the practical implications of such a metric are early detection of the design flaws and aiding architects to judge various design alternatives.
Py-oopsi: the python implementation of the fast-oopsi algorithm
Venue: arXiv cs.CE 2014
Year: 2014

Fast-oopsi was developed by Joshua Vogelstein in 2009, which is now widely used to extract neuron spike activities from calcium fluorescence signals. Here, we propose detailed implementation of the fast-oopsi algorithm in python programming language. Some corrections are also made to the original fast-oopsi paper.
Grid-based Search Technique for Massive Academic Publications
Venue: arXiv cs.DC 2014
Year: 2014

The numerical size of academic publications that are being published in recent years had grown rapidly. Accessing and searching massive academic publications that are distributed over several locations need large amount of computing resources to increase the system performance. Therefore, many grid-based search techniques were proposed to provide flexible methods for searching the distributed extensive data. This paper proposes search technique that is capable of searching the extensive publications by utilizing grid computing technology. The search technique is implemented as interconnected grid services to offer a mechanism to access different data locations. The experimental result shows that the grid-based search technique has enhanced the performance of the search.
An improved accelerated frame slotted aloha (afsa) algorithm for tag collision in rfid
Venue: arXiv cs.NI 2014
Year: 2014

The efficiency of tag identification in an RFID system can be low down due to the tag collision problems. the tag collision problem occurs when a reader try to read multiple tags in an interrogation zone. as a result the reader does not identify the tag correctly. that causes a loss of information or data interference. to solve such kind of issues a series of aloha based algorithm and binary search algorithm have beed proposed. the most simple popular and good giving performance algorithm are aloha based anti-collision algorithms. in this paper we present a new variation in accelerated slotted aloha afsa. our proposed algorithm by using the bitmaps and avoids wastages in bit times due to idleness and collided slots reduce the tag reading time. the simulation result shows that afsa can significantly reduce the average tag reading time with respect to the base protocols and achieve high tag reading rates under both static and mobile setting.
Public Auditing and Data Dynamics for Storage Security in Cloud Computing
Venue: arXiv cs.CR 2014
Year: 2014

Cloud computing has been envisioned as the next generation architecture of IT Enterprise. Using Cloud Storage,users can remotely store their data and enjoy the on demand high quality applications and services from a shared pool of configurable computing resources, without the burden local copy data storage and maintenance. It moves the application of software data stored to the centralized large data centers, where the management of the data stored services may not be completely trusted. There are many new security challenges and the problems taken into account for ensuring the integrity of data storage in Cloud Computing. In particular, we consider the task of allowing a third party auditor (TPA) to perform verifies the integrity of the dynamic data stored in the cloud.
Étude des dimensions spécifiques du contexte dans un système de filtrage d'informations
Venue: arXiv cs.IR 2014
Year: 2014

In the context of business information systems, e-commerce and access to knowledge, the relevance of the information provided to use is a key fact to the success of information systems. Therefore the quality of access is determined by access to the right information at the right time, at the right place. In this context, it is important to consider the users needs when access to information and his contextual situation in order to provide relevant information, tailored to their needs and context use. In what follows we describe the prelude to a project that tries to combine all of these needs to improve information systems.
Differentially positive systems
Venue: arXiv cs.SY 2014
Year: 2014

The paper introduces and studies differentially positive systems, that is, systems whose linearization along an arbitrary trajectory is positive. A generalization of Perron Frobenius theory is developed in this differential framework to show that the property induces a (conal) order that strongly constrains the asymptotic behavior of solutions. The results illustrate that behaviors constrained by local order properties extend beyond the well-studied class of linear positive systems and monotone systems, which both require a constant cone field and a linear state space.
Traffic Driven Resource Allocation in Heterogenous Wireless Networks
Venue: arXiv cs.IT 2014
Year: 2014

Most work on wireless network resource allocation use physical layer performance such as sum rate and outage probability as the figure of merit. These metrics may not reflect the true user QoS in future heterogenous networks (HetNets) with many small cells, due to large traffic variations in overlapping cells with complicated interference conditions. This paper studies the spectrum allocation problem in HetNets using the average packet sojourn time as the performance metric. To be specific, in a HetNet with $K$ base terminal stations (BTS's), we determine the optimal partition of the spectrum into $2^K$ possible spectrum sharing combinations. We use an interactive queueing model to characterize the flow level performance, where the service rates are decided by the spectrum partition. The spectrum allocation problem is formulated using a conservative approximation, which makes the optimization problem convex. We prove that in the optimal solution the spectrum is divided into at most $K$ pieces. A numerical algorithm is provided to solve the spectrum allocation problem on a slow timescale with aggregate traffic and service information. Simulation results show that the proposed solution achieves significant gains compared to both orthogonal and full spectrum reuse allocations with moderate to heavy traffic.
Classical automata on promise problems
Venue: arXiv cs.FL 2014
Year: 2014

Promise problems were mainly studied in quantum automata theory. Here we focus on state complexity of classical automata for promise problems. First, it was known that there is a family of unary promise problems solvable by quantum automata by using a single qubit, but the number of states required by corresponding one-way deterministic automata cannot be bounded by a constant. For this family, we show that even two-way nondeterminism does not help to save a single state. By comparing this with the corresponding state complexity of alternating machines, we then get a tight exponential gap between two-way nondeterministic and one-way alternating automata solving unary promise problems. Second, despite of the existing quadratic gap between Las Vegas realtime probabilistic automata and one-way deterministic automata for language recognition, we show that, by turning to promise problems, the tight gap becomes exponential. Last, we show that the situation is different for one-way probabilistic automata with two-sided bounded-error. We present a family of unary promise problems that is very easy for these machines; solvable with only two states, but the number of states in two-way alternating or any simpler automata is not limited by a constant. Moreover, we show that one-way bounded-error probabilistic automata can solve promise problems not solvable at all by any other classical model.
Optimality Theory as a Framework for Lexical Acquisition
Venue: arXiv cs.CL 2014
Year: 2014

This paper re-investigates a lexical acquisition system initially developed for French.We show that, interestingly, the architecture of the system reproduces and implements the main components of Optimality Theory. However, we formulate the hypothesis that some of its limitations are mainly due to a poor representation of the constraints used. Finally, we show how a better representation of the constraints used would yield better results.
Assessing Educational Research -- An Information Service for Monitoring a Heterogeneous Research Field
Venue: arXiv cs.DL 2014
Year: 2014

The paper presents a web prototype that visualises different characteristics of research projects in the heterogeneous domain of educational research. The concept of the application derives from the project "Monitoring Educational Research" (MoBi) that aims at identifying and implementing indicators that adequately describe structural properties and dynamics of the research field. The prototype enables users to visualise data regarding different indicators, e.g. "research activity", "funding", "qualification project", "disciplinary area". Since the application is based on Semantic MediaWikitechnology it furthermore provides an easily accessible opportunity to collaboratively work on a database of research projects. Users can jointly and in a semantically controlled way enter metadata on research projects which are the basis for the computation and visualisation of indicators.
When Politicians Talk: Assessing Online Conversational Practices of Political Parties on Twitter
Venue: arXiv cs.SI 2014
Year: 2014

Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different - mostly qualitative - aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties.
Disk-based genome sequencing data compression
Venue: arXiv cs.DS 2014
Year: 2014

Motivation: High-coverage sequencing data have significant, yet hard to exploit, redundancy. Most FASTQ compressors cannot efficiently compress the DNA stream of large datasets, since the redundancy between overlapping reads cannot be easily captured in the (relatively small) main memory. More interesting solutions for this problem are disk-based~(Yanovsky, 2011; Cox et al., 2012), where the better of these two, from Cox~{\it et al.}~(2012), is based on the Burrows--Wheeler transform (BWT) and achieves 0.518 bits per base for a 134.0 Gb human genome sequencing collection with almost 45-fold coverage. Results: We propose ORCOM (Overlapping Reads COmpression with Minimizers), a compression algorithm dedicated to sequencing reads (DNA only). Our method makes use of a conceptually simple and easily parallelizable idea of minimizers, to obtain 0.317 bits per base as the compression ratio, allowing to fit the 134.0 Gb dataset into only 5.31 GB of space. Availability: http://sun.aei.polsl.pl/orcom under a free license.
Sparsity-Aware Filtered-X Affine Projection Algorithms for Active Noise Control
Venue: arXiv cs.SD 2014
Year: 2014

This paper describes a novel technique for promoting sparsity in the modified filtered-x algorithms required for active noise control. The proposed algorithms are based on recent techniques incorporating approximations to the \ell_0-norm in the cost functions that are used to derive adaptive filtering algorithms. In particular, zero-attracting and reweighted zero-attracting filtered-x adaptive algorithms are developed and considered for active noise control problems. The results of simulations indicate that the proposed techniques improve the convergence of the existing modified algorithm in the case where the primary and secondary paths exhibit a degree of sparsity.