OpenRaiser/Intern-Atlas huggingface dataset:
Two channel paraunitary filter banks based on linear canonical transform
Venue: arXiv cs.IT 2009
Year: 2009

In this paper a two channel paraunitary filter bank is proposed, which is based on linear canonical transform, instead of discrete Fourier transform. Input-output relation for such a filter bank are derived in terms of polyphase matrices and modulation matrices. It is shown that like conventional filter banks, the LCT based paraunitary filter banks need only one filter to be designed and rest of the filters can be obtained from it. It is also shown that LCT based paraunitary filter banks can be designed by using conventional power-symmetric filter design in Fourier domain.
Extending WS-Security to Implement Security Protocols for Web Services
Venue: arXiv cs.CR 2009
Year: 2009

Web services use tokens provided by the WS-Security standard to implement security protocols. We propose several extensions to the WS-Security standard, including name types, key and random number extensions. The extensions are used to implement existing protocols such as ISO9798, Kerberos or BAN-Lowe. The advantages of using these implementations rather than the existing, binary ones, are inherited from the advantages of using Web service technologies, such as extensibility and end-to-end security across multiple environments that do not support a connection-based communication.
RIOT: I/O-Efficient Numerical Computing without SQL
Venue: arXiv cs.DB 2009
Year: 2009

R is a numerical computing environment that is widely popular for statistical data analysis. Like many such environments, R performs poorly for large datasets whose sizes exceed that of physical memory. We present our vision of RIOT (R with I/O Transparency), a system that makes R programs I/O-efficient in a way transparent to the users. We describe our experience with RIOT-DB, an initial prototype that uses a relational database system as a backend. Despite the overhead and inadequacy of generic database systems in handling array data and numerical computation, RIOT-DB significantly outperforms R in many large-data scenarios, thanks to a suite of high-level, inter-operation optimizations that integrate seamlessly into R. While many techniques in RIOT are inspired by databases (and, for RIOT-DB, realized by a database system), RIOT users are insulated from anything database related. Compared with previous approaches that require users to learn new languages and rewrite their programs to interface with a database, RIOT will, we believe, be easier to adopt by the majority of the R users.
Unbundling Transaction Services in the Cloud
Venue: arXiv cs.DB 2009
Year: 2009

The traditional architecture for a DBMS engine has the recovery, concurrency control and access method code tightly bound together in a storage engine for records. We propose a different approach, where the storage engine is factored into two layers (each of which might have multiple heterogeneous instances). A Transactional Component (TC) works at a logical level only: it knows about transactions and their "logical" concurrency control and undo/redo recovery, but it does not know about page layout, B-trees etc. A Data Component (DC) knows about the physical storage structure. It supports a record oriented interface that provides atomic operations, but it does not know about transactions. Providing atomic record operations may itself involve DC-local concurrency control and recovery, which can be implemented using system transactions. The interaction of the mechanisms in TC and DC leads to multi-level redo (unlike the repeat history paradigm for redo in integrated engines). This refactoring of the system architecture could allow easier deployment of application-specific physical structures and may also be helpful to exploit multi-core hardware. Particularly promising is its potential to enable flexible transactions in cloud database deployments. We describe the necessary principles for unbundled recovery, and discuss implementation issues.
Heterogeneity in Distributed Live Streaming: Blessing or Curse?
Venue: arXiv cs.NI 2009
Year: 2009

Distributed live streaming has brought a lot of interest in the past few years. In the homogeneous case (all nodes having the same capacity), many algorithms have been proposed, which have been proven almost optimal or optimal. On the other hand, the performance of heterogeneous systems is not completely understood yet. In this paper, we investigate the impact of heterogeneity on the achievable delay of chunk-based live streaming systems. We propose several models for taking the atomicity of a chunk into account. For all these models, when considering the transmission of a single chunk, heterogeneity is indeed a ``blessing'', in the sense that the achievable delay is always faster than an equivalent homogeneous system. But for a stream of chunks, we show that it can be a ``curse'': there is systems where the achievable delay can be arbitrary greater compared to equivalent homogeneous systems. However, if the system is slightly bandwidth-overprovisioned, optimal single chunk diffusion schemes can be adapted to a stream of chunks, leading to near-optimal, faster than homogeneous systems, heterogeneous live streaming systems.
Randomized Sensor Selection in Sequential Hypothesis Testing
Venue: arXiv cs.IT 2009
Year: 2009

We consider the problem of sensor selection for time-optimal detection of a hypothesis. We consider a group of sensors transmitting their observations to a fusion center. The fusion center considers the output of only one randomly chosen sensor at the time, and performs a sequential hypothesis test. We consider the class of sequential tests which are easy to implement, asymptotically optimal, and computationally amenable. For three distinct performance metrics, we show that, for a generic set of sensors and binary hypothesis, the fusion center needs to consider at most two sensors. We also show that for the case of multiple hypothesis, the optimal policy needs at most as many sensors to be observed as the number of underlying hypotheses.
Paired Comparisons-based Interactive Differential Evolution
Venue: arXiv cs.AI 2009
Year: 2009

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals each other but compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed one is superior to others from both user interface and convergence performance points of view.
MESURE Tool to benchmark Java Card platforms
Venue: arXiv cs.SE 2009
Year: 2009

The advent of the Java Card standard has been a major turning point in smart card technology. With the growing acceptance of this standard, understanding the performance behavior of these platforms is becoming crucial. To meet this need, we present in this paper a novel benchmarking framework to test and evaluate the performance of Java Card platforms. MESURE tool is the first framework which accuracy and effectiveness are independent from the particular Java Card platform tested and CAD used.
Slicing: A New Approach to Privacy Preserving Data Publishing
Venue: arXiv cs.DB 2009
Year: 2009

Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that generalization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. In this paper, we present a novel technique called slicing, which partitions the data both horizontally and vertically. We show that slicing preserves better data utility than generalization and can be used for membership disclosure protection. Another important advantage of slicing is that it can handle high-dimensional data. We show how slicing can be used for attribute disclosure protection and develop an efficient algorithm for computing the sliced data that obey the l-diversity requirement. Our workload experiments confirm that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute. Our experiments also demonstrate that slicing can be used to prevent membership disclosure.
Random Sampling Using Shannon Interpolation and Poisson Summation Formulae
Venue: arXiv cs.IT 2009
Year: 2009

This report mainly focused on the basic concepts and the recovery methods for the random sampling. The recovery methods involve the orthogonal matching pursuit algorithm and the gradient-based total variation strategy. In particular, a fast and efficient observation matrix filling technique was implemented by the classic Shannon interpolation and Poisson summation formulae. The numerical results for the trigonometric signal, the Gaussian-modulated sinusoidal pulse, and the square wave were demonstrated and discussed. The work may give some help for future work in theoretical study and practical implementation of the random sampling.
Simulation of Resource Usage in Parallel Evolutionary Peptide Optimization using JavaSpaces Technology
Venue: arXiv cs.DC 2009
Year: 2009

Peptide Optimization is a highly complex problem and it takes very long time of computation. This optimization process uses many software applications in a cluster running GNU/Linux Operating System that perform special tasks. The application to organize the whole optimization process had been already developed, namely SEPP (System for Evolutionary Pareto Optimization of Peptides/Polymers). A single peptide optimization takes a lot of computation time to produce a certain number of individuals. However, it can be accelerated by increasing the degree of parallelism as well as the number of nodes (processors) in the cluster. In this master thesis, I build a model simulating the interplay of the programs so that the usage of each resource (processor) can be determined and also the approximated time needed for the overall optimization process. There are two Evolutionary Algorithms that could be used in the optimization, namely Generation-based and Steady-state Evolutionary Algorithm. The results of each Evolutionary Algorithm are shown based on the simulations. Moreover, the results are also compared by using different parameters (the degree of parallelism and the number of processors) in the simulation to give an overview of the advantages and the disadvantages of the algorithms in terms of computation time and resource usage. The model is built up using JavaSpaces Technology.
Self-Partial and Dynamic Reconfiguration Implementation for AES using FPGA
Venue: arXiv cs.CR 2009
Year: 2009

This paper addresses efficient hardware/software implementation approaches for the AES (Advanced Encryption Standard) algorithm and describes the design and performance testing algorithm for embedded system. Also, with the spread of reconfigurable hardware such as FPGAs (Field Programmable Gate Array) embedded cryptographic hardware became cost-effective. Nevertheless, it is worthy to note that nowadays, even hardwired cryptographic algorithms are not so safe. From another side, the self-reconfiguring platform is reported that enables an FPGA to dynamically reconfigure itself under the control of an embedded microprocessor. Hardware acceleration significantly increases the performance of embedded systems built on programmable logic. Allowing a FPGA-based MicroBlaze processor to self-select the coprocessors uses can help reduce area requirements and increase a system's versatility. The architecture proposed in this paper is an optimal hardware implementation algorithm and takes dynamic partially reconfigurable of FPGA. This implementation is good solution to preserve confidentiality and accessibility to the information in the numeric communication.
Implementation of Rule Based Algorithm for Sandhi-Vicheda Of Compound Hindi Words
Venue: arXiv cs.CL 2009
Year: 2009

Sandhi means to join two or more words to coin new word. Sandhi literally means `putting together' or combining (of sounds), It denotes all combinatory sound-changes effected (spontaneously) for ease of pronunciation. Sandhi-vicheda describes [5] the process by which one letter (whether single or cojoined) is broken to form two words. Part of the broken letter remains as the last letter of the first word and part of the letter forms the first letter of the next letter. Sandhi- Vicheda is an easy and interesting way that can give entirely new dimension that add new way to traditional approach to Hindi Teaching. In this paper using the Rule based algorithm we have reported an accuracy of 60-80% depending upon the number of rules to be implemented.
Pavideoge: A Metadata Markup Video Structure in Video Search Engine
Venue: arXiv cs.IR 2009
Year: 2009

In this paper, we study the problems of video processing in video search engine. Video has now become a very important kind of data in Internet; while searching for video is still a challenging task due to the inner properties of video: requiring enormous storage space, being independent, expressing information hiddenly. To handle the properties of video more effectively, in this paper, we propose a new video processing method in video search engine. In detail, the core of the new video processing method is creating pavideoge--a new data type, which contains the video advantages and webpage advantages. The pavideoge has four attributes: real link, videorank, text information and playnum. Each of them combines video's properties with webpage's. Video search engine based on the pavideoge can retrieve video more effectively. The experiment results show the encouraging performance of our approach. Based on the pavideoge, our video search engine can retrieve more precise videos in comparsion with previous related work.
A progression ring for interfaces of instruction sequences, threads, and services
Venue: arXiv cs.PL 2009
Year: 2009

We define focus-method interfaces and some connections between such interfaces and instruction sequences, giving rise to instruction sequence components. We provide a flexible and practical notation for interfaces using an abstract datatype specification comparable to that of basic process algebra with deadlock. The structures thus defined are called progression rings. We also define thread and service components. Two types of composition of instruction sequences or threads and services (called `use' and `apply') are lifted to the level of components.
A new efficient k-out-of-n Oblivious Transfer protocol
Venue: arXiv cs.CR 2009
Year: 2009

This paper presents a new efficient protocol for k-out-of-n oblivious transfer which is a generalization of Parakh's 1-out-of-2 oblivious transfer protocol based on Diffie-Hellman key exchange. In the proposed protocol, the parties involved generate Diffie-Hellman keys obliviously and then use them for oblivious transfer of secrets.
Compressive Sensing Based Opportunistic Protocol for Throughput Improvement in Wireless Networks
Venue: arXiv cs.IT 2009
Year: 2009

A key feature in the design of any MAC protocol is the throughput it can provide. In wireless networks, the channel of a user is not fixed but varies randomly. Thus, in order to maximize the throughput of the MAC protocol at any given time, only users with large channel gains should be allowed to transmit. In this paper, compressive sensing based opportunistic protocol for throughput improvement in wireless networks is proposed. The protocol is based on the traditional protocol of R-ALOHA which allows users to compete for channel access before reserving the channel to the best user. We use compressive sensing to find the best user, and show that the proposed protocol requires less time for reservation and so it outperforms other schemes proposed in literature. This makes the protocol particularly suitable for enhancing R-ALOHA in fast fading environments. We consider both analog and digital versions of the protocol where the channel gains sent by the user are analog and digital, respectively.
The quantitative side of the Repertory Grid Technique: some concerns
Venue: arXiv cs.HC 2009
Year: 2009

User experience (UX) evaluation is gaining increased interest lately, both from academia and industry. In this paper we argue that UX evaluation needs to fulfill two important requirements: scalability, i.e. the ability to provide useful feedback in different stages of the design, and diversity, i.e. the ability to reflect the di-versity of opinions that may exist in different users. We promote the use of the Repertory Grid Technique as a promising UX evaluation technique and discuss some of our concerns regarding the quantitative side of its use.
Compressed Sensing with Probabilistic Measurements: A Group Testing Solution
Venue: arXiv cs.IT 2009
Year: 2009

Detection of defective members of large populations has been widely studied in the statistics community under the name "group testing", a problem which dates back to World War II when it was suggested for syphilis screening. There the main interest is to identify a small number of infected people among a large population using collective samples. In viral epidemics, one way to acquire collective samples is by sending agents inside the population. While in classical group testing, it is assumed that the sampling procedure is fully known to the reconstruction algorithm, in this work we assume that the decoder possesses only partial knowledge about the sampling process. This assumption is justified by observing the fact that in a viral sickness, there is a chance that an agent remains healthy despite having contact with an infected person. Therefore, the reconstruction method has to cope with two different types of uncertainty; namely, identification of the infected population and the partially unknown sampling procedure. In this work, by using a natural probabilistic model for "viral infections", we design non-adaptive sampling procedures that allow successful identification of the infected population with overwhelming probability 1-o(1). We propose both probabilistic and explicit design procedures that require a "small" number of agents to single out the infected individuals. More precisely, for a contamination probability p, the number of agents required by the probabilistic and explicit designs for identification of up to k infected members is bounded by m = O(k^2 (log n)/p^2) and m = O(k^2 (log n)^2 /p^2), respectively. In both cases, a simple decoder is able to successfully identify the infected population in time O(mn).
Randomized Algorithms for Large scale SVMs
Venue: arXiv cs.LG 2009
Year: 2009

We propose a randomized algorithm for training Support vector machines(SVMs) on large datasets. By using ideas from Random projections we show that the combinatorial dimension of SVMs is $O({log} n)$ with high probability. This estimate of combinatorial dimension is used to derive an iterative algorithm, called RandSVM, which at each step calls an existing solver to train SVMs on a randomly chosen subset of size $O({log} n)$. The algorithm has probabilistic guarantees and is capable of training SVMs with Kernels for both classification and regression problems. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up existing SVM learners, without loss of accuracy.
Analytical Models for Energy Consumption in Infrastructure WLAN STAs Carrying TCP Traffic
Venue: arXiv cs.NI 2009
Year: 2009

We develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fraction of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than just using CAM. For short file downloads we compute the number of file downloads that can be completed with given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. In contrast to earlier work on analytical modeling of PSM, our models that capture the details of the interactions between the 802.11 MAC in PSM and certain aspects of TCP.
Stiffness Analysis Of Multi-Chain Parallel Robotic Systems
Venue: arXiv cs.RO 2009
Year: 2009

The paper presents a new stiffness modelling method for multi-chain parallel robotic manipulators with flexible links and compliant actuating joints. In contrast to other works, the method involves a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations, which allows computing the stiffness matrix for singular postures and to take into account influence of the external forces. The advantages of the developed technique are confirmed by application examples, which deal with stiffness analysis of a parallel manipulator of the Orthoglide family
A Numerical Algorithm for Zero Counting. II: Distance to Ill-posedness and Smoothed Analysis
Venue: arXiv cs.NA 2009
Year: 2009

We show a Condition Number Theorem for the condition number of zero counting for real polynomial systems. That is, we show that this condition number equals the inverse of the normalized distance to the set of ill-posed systems (i.e., those having multiple real zeros). As a consequence, a smoothed analysis of this condition number follows.
Breaking the 2^n-Barrier for Irredundance: A Parameterized Route to Solving Exact Puzzles
Venue: arXiv cs.DS 2009
Year: 2009

The lower and the upper irredundance numbers of a graph $G$, denoted $ir(G)$ and $IR(G)$ respectively, are conceptually linked to domination and independence numbers and have numerous relations to other graph parameters. It is a long-standing open question whether determining these numbers for a graph $G$ on $n$ vertices admits exact algorithms running in time less than the trivial $Ω(2^n)$ enumeration barrier. We solve these open problems by devising parameterized algorithms for the dual of the natural parameterizations of the problems with running times faster than $O^*(4^{k})$. For example, we present an algorithm running in time $O^*(3.069^{k})$ for determining whether $IR(G)$ is at least $n-k$. Although the corresponding problem has been known to be in FPT by kernelization techniques, this paper offers the first parameterized algorithms with an exponential dependency on the parameter in the running time. Additionally, our work also appears to be the first example of a parameterized approach leading to a solution to a problem in exponential time algorithmics where the natural interpretation as an exact exponential-time algorithm fails.