OpenRaiser/Intern-Atlas huggingface dataset:
On Secure Distributed Data Storage Under Repair Dynamics
Venue: arXiv cs.IT 2010
Year: 2010

We address the problem of securing distributed storage systems against passive eavesdroppers that can observe a limited number of storage nodes. An important aspect of these systems is node failures over time, which demand a repair mechanism aimed at maintaining a targeted high level of system reliability. If an eavesdropper observes a node that is added to the system to replace a failed node, it will have access to all the data downloaded during repair, which can potentially compromise the entire information in the system. We are interested in determining the secrecy capacity of distributed storage systems under repair dynamics, i.e., the maximum amount of data that can be securely stored and made available to a legitimate user without revealing any information to any eavesdropper. We derive a general upper bound on the secrecy capacity and show that this bound is tight for the bandwidth-limited regime which is of importance in scenarios such as peer-to-peer distributed storage systems. We also provide a simple explicit code construction that achieves the capacity for this regime.
Model Selection with the Loss Rank Principle
Venue: arXiv cs.LG 2010
Year: 2010

A key issue in statistics and machine learning is to automatically select the "right" model complexity, e.g., the number of neighbors to be averaged over in k nearest neighbor (kNN) regression or the polynomial degree in regression with polynomials. We suggest a novel principle - the Loss Rank Principle (LoRP) - for model selection in regression and classification. It is based on the loss rank, which counts how many other (fictitious) data would be fitted better. LoRP selects the model that has minimal loss rank. Unlike most penalized maximum likelihood variants (AIC, BIC, MDL), LoRP depends only on the regression functions and the loss function. It works without a stochastic noise model, and is directly applicable to any non-parametric regressor, like kNN.
Information embedding meets distributed control
Venue: arXiv cs.IT 2010
Year: 2010

We consider the problem of information embedding where the encoder modifies a white Gaussian host signal in a power-constrained manner to encode the message, and the decoder recovers both the embedded message and the modified host signal. This extends the recent work of Sumszyk and Steinberg to the continuous-alphabet Gaussian setting. We show that a dirty-paper-coding based strategy achieves the optimal rate for perfect recovery of the modified host and the message. We also provide bounds for the extension wherein the modified host signal is recovered only to within a specified distortion. When specialized to the zero-rate case, our results provide the tightest known lower bounds on the asymptotic costs for the vector version of a famous open problem in distributed control -- the Witsenhausen counterexample. Using this bound, we characterize the asymptotically optimal costs for the vector Witsenhausen problem numerically to within a factor of 1.3 for all problem parameters, improving on the earlier best known bound of 2.
Zigzags in Turing machines
Venue: arXiv cs.FL 2010
Year: 2010

We study one-head machines through symbolic and topological dynamics. In particular, a subshift is associated to the subshift, and we are interested in its complexity in terms of realtime recognition. We emphasize the class of one-head machines whose subshift can be recognized by a deterministic pushdown automaton. We prove that this class corresponds to particular restrictions on the head movement, and to equicontinuity in associated dynamical systems.
The Grid[Way] Job Template Manager, a tool for parameter sweeping
Venue: arXiv cs.DC 2010
Year: 2010

Parameter sweeping is a widely used algorithmic technique in computational science. It is specially suited for high-throughput computing since the jobs evaluating the parameter space are loosely coupled or independent. A tool that integrates the modeling of a parameter study with the control of jobs in a distributed architecture is presented. The main task is to facilitate the creation and deletion of job templates, which are the elements describing the jobs to be run. Extra functionality relies upon the GridWay Metascheduler, acting as the middleware layer for job submission and control. It supports interesting features like multi-dimensional sweeping space, wildcarding of parameters, functional evaluation of ranges, value-skipping and job template automatic indexation. The use of this tool increases the reliability of the parameter sweep study thanks to the systematic bookkeping of job templates and respective job statuses. Furthermore, it simplifies the porting of the target application to the grid reducing the required amount of time and effort.
FIFO anomaly is unbounded
Venue: arXiv cs.OS 2010
Year: 2010

Virtual memory of computers is usually implemented by demand paging. For some page replacement algorithms the number of page faults may increase as the number of page frames increases. Belady, Nelson and Shedler constructed reference strings for which page replacement algorithm FIFO produces near twice more page faults in a larger memory than in a smaller one. They formulated the conjecture that 2 is a general bound. We prove that this ratio can be arbitrarily large.
Using Coloured Petri Nets for design of parallel raytracing environment
Venue: arXiv cs.DC 2010
Year: 2010

This paper deals with the parallel raytracing part of virtual-reality system PROLAND, developed at the home institution of authors. It describes an actual implementation of the raytracing part and introduces a Coloured Petri Nets model of the implementation. The model is used for an evaluation of the implementation by means of simulation-based performance analysis and also forms the basis for future improvements of its parallelization strategy.
Secured Cryptographic Key Generation From Multimodal Biometrics: Feature Level Fusion of Fingerprint and Iris
Venue: arXiv cs.CR 2010
Year: 2010

Human users have a tough time remembering long cryptographic keys. Hence, researchers, for so long, have been examining ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to generate strong and repeatable cryptographic keys. Our objective is to incorporate the volatility of the user's biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the user's biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic key generation so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. Initially, the features, minutiae points and texture properties are extracted from the fingerprint and iris images respectively. Subsequently, the extracted features are fused together at the feature level to construct the multi-biometric template. Finally, a 256-bit secure cryptographic key is generated from the multi-biometric template. For experimentation, we have employed the fingerprint images obtained from publicly available sources and the iris images from CASIA Iris Database. The experimental results demonstrate the effectiveness of the proposed approach.
Comments on "Routh Stability Criterion"
Venue: arXiv cs.NA 2010
Year: 2010

In this note, we have shown special case on Routh stability criterion, which is not discussed, in previous literature. This idea can be useful in computer science applications.
Multi-objective Geometric Programming Problem With Weighted Mean Method
Venue: arXiv cs.NA 2010
Year: 2010

Geometric programming is an important class of optimization problems that enable practitioners to model a large variety of real-world applications, mostly in the field of engineering design. In many real life optimization problem multi-objective programming plays a vital role in socio-economical and industrial optimizing problems. In this paper we have discussed the basic concepts and principle of multiple objective optimization problems and developed geometric programming (GP) technique to solve this optimization problem using weighted method to obtain the non-inferior solutions.
Formal Concept Analysis for Information Retrieval
Venue: arXiv cs.IR 2010
Year: 2010

In this paper we describe a mechanism to improve Information Retrieval (IR) on the web. The method is based on Formal Concepts Analysis (FCA) that it is makes semantical relations during the queries, and allows a reorganizing, in the shape of a lattice of concepts, the answers provided by a search engine. We proposed for the IR an incremental algorithm based on Galois lattice. This algorithm allows a formal clustering of the data sources, and the results which it turns over are classified by order of relevance. The control of relevance is exploited in clustering, we improved the result by using ontology in field of image processing, and reformulating the user queries which make it possible to give more relevant documents.
Information Fusion in the Immune System
Venue: arXiv cs.AI 2010
Year: 2010

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial Immune Systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has show how AISs which use multi-level information sources as input data can be used to build effective algorithms for real time computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs
An Entry Point for Formal Methods: Specification and Analysis of Event Logs
Venue: arXiv cs.SE 2010
Year: 2010

Formal specification languages have long languished, due to the grave scalability problems faced by complete verification methods. Runtime verification promises to use formal specifications to automate part of the more scalable art of testing, but has not been widely applied to real systems, and often falters due to the cost and complexity of instrumentation for online monitoring. In this paper we discuss work in progress to apply an event-based specification system to the logging mechanism of the Mars Science Laboratory mission at JPL. By focusing on log analysis, we exploit the "instrumentation" already implemented and required for communicating with the spacecraft. We argue that this work both shows a practical method for using formal specifications in testing and opens interesting research avenues, including a challenging specification learning problem.
Privacy Issues of the W3C Geolocation API
Venue: arXiv cs.CY 2010
Year: 2010

The W3C's Geolocation API may rapidly standardize the transmission of location information on the Web, but, in dealing with such sensitive information, it also raises serious privacy concerns. We analyze the manner and extent to which the current W3C Geolocation API provides mechanisms to support privacy. We propose a privacy framework for the consideration of location information and use it to evaluate the W3C Geolocation API, both the specification and its use in the wild, and recommend some modifications to the API as a result of our analysis.
Nonlinear Filter Based Image Denoising Using AMF Approach
Venue: arXiv cs.CV 2010
Year: 2010

This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Median (CWM) filter has got a better average performance over the median filter [8]. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach by overcoming the existing problem, the proposed new scheme (AMF) Adaptive Median Filter has been simulated along with the standard ones and various performance measures have been compared.
Localization Technologies for Indoor Human Tracking
Venue: arXiv cs.NI 2010
Year: 2010

The proliferation of wireless localization technologies provides a promising future for serving human beings in indoor scenarios. Their applications include real-time tracking, activity recognition, health care, navigation, emergence detection, and target-of-interest monitoring, among others. Additionally, indoor localization technologies address the inefficiency of GPS (Global Positioning System) inside buildings. Since people spend most of their time in indoor environments, indoor tracking service is in great public demand. Based on this observation, this paper aims to provide a better understanding of state-of-the-art technologies and stimulate new research efforts in this field. For these purposes, existing localization technologies that can be used for tracking individuals in indoor environments are reviewed, along with some further discussions.
The zero exemplar distance problem
Venue: arXiv cs.CC 2010
Year: 2010

Given two genomes with duplicate genes, \textsc{Zero Exemplar Distance} is the problem of deciding whether the two genomes can be reduced to the same genome without duplicate genes by deleting all but one copy of each gene in each genome. Blin, Fertin, Sikora, and Vialette recently proved that \textsc{Zero Exemplar Distance} for monochromosomal genomes is NP-hard even if each gene appears at most two times in each genome, thereby settling an important open question on genome rearrangement in the exemplar model. In this paper, we give a very simple alternative proof of this result. We also study the problem \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order, and prove the analogous result that it is also NP-hard even if each gene appears at most two times in each genome. For the positive direction, we show that both variants of \textsc{Zero Exemplar Distance} admit polynomial-time algorithms if each gene appears exactly once in one genome and at least once in the other genome. In addition, we present a polynomial-time algorithm for the related problem \textsc{Exemplar Longest Common Subsequence} in the special case that each mandatory symbol appears exactly once in one input sequence and at least once in the other input sequence. This answers an open question of Bonizzoni et al. We also show that \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order is fixed-parameter tractable if the parameter is the maximum number of chromosomes in each genome.
Rivals for the crown: Reply to Opthof and Leydesdorff
Venue: arXiv cs.DL 2010
Year: 2010

We reply to the criticism of Opthof and Leydesdorff [arXiv:1002.2769] on the way in which our institute applies journal and field normalizations to citation counts. We point out why we believe most of the criticism is unjustified, but we also indicate where we think Opthof and Leydesdorff raise a valid point.
QoS Routing in Smart Grid
Venue: arXiv cs.IT 2010
Year: 2010

Smart grid is an emerging technology which is able to control the power load via price signaling. The communication between the power supplier and power customers is a key issue in smart grid. Performance degradation like delay or outage may cause significant impact on the stability of the pricing based control and thus the reward of smart grid. Therefore, a QoS mechanism is proposed for the communication system in smart grid, which incorporates the derivation of QoS requirement and applies QoS routing in the communication network. For deriving the QoS requirement, the dynamics of power load and the load-price mapping are studied. The corresponding impacts of different QoS metrics like delay are analyzed. Then, the QoS is derived via an optimization problem that maximizes the total revenue. Based on the derived QoS requirement, a simple greedy QoS routing algorithm is proposed for the requirement of high speed routing in smart grid. It is also proven that the proposed greedy algorithm is a $K$-approximation. Numerical simulation shows that the proposed mechanism and algorithm can effectively derive and secure the communication QoS in smart grid.
Towards a new crown indicator: Some theoretical considerations
Venue: arXiv cs.DL 2010
Year: 2010

The crown indicator is a well-known bibliometric indicator of research performance developed by our institute. The indicator aims to normalize citation counts for differences among fields. We critically examine the theoretical basis of the normalization mechanism applied in the crown indicator. We also make a comparison with an alternative normalization mechanism. The alternative mechanism turns out to have more satisfactory properties than the mechanism applied in the crown indicator. In particular, the alternative mechanism has a so-called consistency property. The mechanism applied in the crown indicator lacks this important property. As a consequence of our findings, we are currently moving towards a new crown indicator, which relies on the alternative normalization mechanism.
The C Object System: Using C as a High-Level Object-Oriented Language
Venue: arXiv cs.PL 2010
Year: 2010

The C Object System (Cos) is a small C library which implements high-level concepts available in Clos, Objc and other object-oriented programming languages: uniform object model (class, meta-class and property-metaclass), generic functions, multi-methods, delegation, properties, exceptions, contracts and closures. Cos relies on the programmable capabilities of the C programming language to extend its syntax and to implement the aforementioned concepts as first-class objects. Cos aims at satisfying several general principles like simplicity, extensibility, reusability, efficiency and portability which are rarely met in a single programming language. Its design is tuned to provide efficient and portable implementation of message multi-dispatch and message multi-forwarding which are the heart of code extensibility and reusability. With COS features in hand, software should become as flexible and extensible as with scripting languages and as efficient and portable as expected with C programming. Likewise, Cos concepts should significantly simplify adaptive and aspect-oriented programming as well as distributed and service-oriented computing
An Educative Brain-Computer Interface
Venue: arXiv cs.HC 2010
Year: 2010

In this paper we will describe all necessary parts of Brain-Computer Interface (BCI), such as source of signals, hardware, software, analysis, architectures of complete system. We also will go along various applications of BCI, view some subject fields and their specifics. After preface we will consider the main point of this work-concepts of using BCI in education. Represented direction of BCI development has not been reported prior. In this work a computer system, currently being elaborated in author's laboratory, will be specified. A purpose of it is to determine a degree of clearness of studied information for certain user according to their indications of brain electrical signals. On the basis of this information the system is able to find an optimal approach to interact with each single user. Feedback individualization leads to learning effectiveness increasing. Stated investigations will be supplemented by author's analytical reasoning on the nature of thinking process.
Classified Ads Harvesting Agent and Notification System
Venue: arXiv cs.IR 2010
Year: 2010

The shift from an information society to a knowledge society require rapid information harvesting, reliable search and instantaneous on demand delivery. Information extraction agents are used to explore and collect data available from Web, in order to effectively exploit such data for business purposes, such as automatic news filtering, advertisement or product searching and price comparing. In this paper, we develop a real-time automatic harvesting agent for adverts posted on Servihoo web portal and an SMS-based notification system. It uses the URL of the web portal and the object model, i.e., the fields of interests and a set of rules written using the HTML parsing functions to extract latest adverts information. The extraction engine executes the extraction rules and stores the information in a database to be processed for automatic notification. This intelligent system helps to tremendously save time. It also enables users or potential product buyers to react more quickly to changes and newly posted sales adverts, paving the way to real-time best buy deals.
A Systematic Framework for the Construction of Optimal Complete Complementary Codes
Venue: arXiv cs.IT 2010
Year: 2010

The complete complementary code (CCC) is a sequence family with ideal correlation sums which was proposed by Suehiro and Hatori. Numerous literatures show its applications to direct-spread code-division multiple access (DS-CDMA) systems for inter-channel interference (ICI)-free communication with improved spectral efficiency. In this paper, we propose a systematic framework for the construction of CCCs based on $N$-shift cross-orthogonal sequence families ($N$-CO-SFs). We show theoretical bounds on the size of $N$-CO-SFs and CCCs, and give a set of four algorithms for their generation and extension. The algorithms are optimal in the sense that the size of resulted sequence families achieves theoretical bounds and, with the algorithms, we can construct an optimal CCC consisting of sequences whose lengths are not only almost arbitrary but even variable between sequence families. We also discuss the family size, alphabet size, and lengths of constructible CCCs based on the proposed algorithms.
Near-Optimal Evasion of Convex-Inducing Classifiers
Venue: arXiv cs.LG 2010
Year: 2010

Classifiers are often used to detect miscreant activities. We study how an adversary can efficiently query a classifier to elicit information that allows the adversary to evade detection at near-minimal cost. We generalize results of Lowd and Meek (2005) to convex-inducing classifiers. We present algorithms that construct undetected instances of near-minimal cost using only polynomially many queries in the dimension of the space and without reverse engineering the decision boundary.