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In this article we present the prototype of a framework capable of producing, with linear complexity, uniformly random XML documents with respect to a given RELAX NG grammar. The generation relies on powerful combinatorial methods together with numerical and symbolic resolution of polynomial systems.
This paper is concerned with the problem of designing computationally efficient Generalized Comb Filters (GCF). Basically, GCF filters are anti-aliasing filters that guarantee superior performance in terms of selectivity and quantization noise rejection compared to classical comb filters, when used as decimation filters in multistage architectures. Upon employing a partial polyphase (PP) architecture proposed in a companion paper, we develop a sensitivity analysis in order to investigate the effects of the coefficients' quantization on the frequency response of the designed filters. We show that the sensitivity of the filter response to errors in the coefficients is dependent on the particular split of the decimation factor between the two sub-filters constituting the PP architecture. The sensitivity analysis is then used for developing a fixed-point implementation of a sample filter from the class of GCF filters, used as reference filter throughout the paper. Finally, we present computer simulations in order to evaluate the performance of the designed fixed-point filters.
In this paper an extension of the sparse decomposition problem is considered and an algorithm for solving it is presented. In this extension, it is known that one of the shifted versions of a signal s (not necessarily the original signal itself) has a sparse representation on an overcomplete dictionary, and we are looking for the sparsest representation among the representations of all the shifted versions of s. Then, the proposed algorithm finds simultaneously the amount of the required shift, and the sparse representation. Experimental results emphasize on the performance of our algorithm.
Side-channel attacks are efficient attacks against cryptographic devices. They use only quantities observable from outside, such as the duration and the power consumption. Attacks against synchronous devices using electric observations are facilitated by the fact that all transitions occur simultaneously with some global clock signal. Asynchronous control remove this synchronization and therefore makes it more difficult for the attacker to insulate \emph{interesting intervals}. In addition the coding of data in an asynchronous circuit is inherently more difficult to attack. This article describes the Programmable Logic Block of an asynchronous FPGA resistant against \emph{side-channel attacks}. Additionally it can implement different styles of asynchronous control and of data representation.
Dynamic voltage scaling (DVS) is one of the most effective techniques for reducing energy consumption in embedded and real-time systems. However, traditional DVS algorithms have inherent limitations on their capability in energy saving since they rarely take into account the actual application requirements and often exploit fixed timing constraints of real-time tasks. Taking advantage of application adaptation, an enhanced energy-aware feedback scheduling (EEAFS) scheme is proposed, which integrates feedback scheduling with DVS. To achieve further reduction in energy consumption over pure DVS while not jeopardizing the quality of control, the sampling period of each control loop is adapted to its actual control performance, thus exploring flexible timing constraints on control tasks. Extensive simulation results are given to demonstrate the effectiveness of EEAFS under different scenarios. Compared with the optimal pure DVS scheme, EEAFS saves much more energy while yielding comparable control performance.
Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.
Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better performance than their integer order counterparts. Controller synthesis is based on required peak overshoot and rise time specifications. The characteristic equation is minimized to obtain an optimum set of controller parameters. Results show that this design method can effectively tune the parameters of the fractional order controller.
System identification is a necessity in control theory. Classical control theory usually considers processes with integer order transfer functions. Real processes are usually of fractional order as opposed to the ideal integral order models. A simple and elegant scheme is presented for approximation of such a real world fractional order process by an ideal integral order model. A population of integral order process models is generated and updated by PSO technique, the fitness function being the sum of squared deviations from the set of observations obtained from the actual fractional order process. Results show that the proposed scheme offers a high degree of accuracy.
System identification refers to estimation of process parameters and is a necessity in control theory. Physical systems usually have varying parameters. For such processes, accurate identification is particularly important. Online identification schemes are also needed for designing adaptive controllers. Real processes are usually of fractional order as opposed to the ideal integral order models. In this paper, we propose a simple and elegant scheme of estimating the parameters for such a fractional order process. A population of process models is generated and updated by particle swarm optimization (PSO) technique, the fitness function being the sum of squared deviations from the actual set of observations. Results show that the proposed scheme offers a high degree of accuracy even when the observations are corrupted to a significant degree. Additional schemes to improve the accuracy still further are also proposed and analyzed.
The Proportional-Integral-Derivative Controller is widely used in industries for process control applications. Fractional-order PID controllers are known to outperform their integer-order counterparts. In this paper, we propose a new technique of fractional-order PID controller synthesis based on peak overshoot and rise-time specifications. Our approach is to construct an objective function, the optimization of which yields a possible solution to the design problem. This objective function is optimized using two popular bio-inspired stochastic search algorithms, namely Particle Swarm Optimization and Differential Evolution. With the help of a suitable example, the superiority of the designed fractional-order PID controller to an integer-order PID controller is affirmed and a comparative study of the efficacy of the two above algorithms in solving the optimization problem is also presented.
Particle swarm optimization (PSO) is extensively used for real parameter optimization in diverse fields of study. This paper describes an application of PSO to the problem of designing a fractional-order proportional-integral-derivative (FOPID) controller whose parameters comprise proportionality constant, integral constant, derivative constant, integral order (lambda) and derivative order (delta). The presence of five optimizable parameters makes the task of designing a FOPID controller more challenging than conventional PID controller design. Our design method focuses on minimizing the Integral Time Absolute Error (ITAE) criterion. The digital realization of the deigned system utilizes the Tustin operator-based continued fraction expansion scheme. We carry out a simulation that illustrates the effectiveness of the proposed approach especially for realizing fractional-order plants. This paper also attempts to study the behavior of fractional PID controller vis-a-vis that of its integer order counterpart and demonstrates the superiority of the former to the latter.
An adaptive voting algorithm for digital media was introduced in this study. Availability was improved by incoherence scoring in voting mechanism of Multi-Modular Redundancy. Regulation parameters give the algorithm flexibility of adjusting priorities in decision process. Proposed adaptive voting algorithm was shown to be more aware of fault status of redundant modules
An algorithm to generate the locus of a circle using the intersection points of straight lines is proposed. The pixels on the circle are plotted independent of one another and the operations involved in finding the locus of the circle from the intersection of straight lines are parallelizable. Integer only arithmetic and algorithmic optimizations are used for speedup. The proposed algorithm makes use of an envelope to form a parabolic arc which is consequent transformed into a circle. The use of parabolic arcs for the transformation results in higher pixel errors as the radius of the circle to be drawn increases. At its current state, the algorithm presented may be suitable only for generating circles for string art.
Information and Communication Technologies (ICT) has practically penetrated into all spheres of life. Therefore a closer look at the impact of ICT in public financial management and performance is highly justified. Public finance is defined as a field of economics concerned with paying for collective or governmental activities, and with the administration and design of those activities. Activities will be viewed as services or more precisely as public services. We believe that there is need to consider performance from the perspective of effective performance and the perceived performance. In fact the real or effective performance might not correspond to the perceived performance. A service can be considered from the perspective of the decision-maker, who in our case could be a government or a collectivity. ICT can be employed in the three phases that concern the decision-maker: design, implementation and evaluation. The beneficiaries of a service can employ ICT in any of the three phases - awareness, exploitation and assessment - for guarantying a high level of efficiency. Each phase in the environment of a service will be presented as well as illustrations of how ICT can be employed in order to improve the end-result of each one of them. We believe that a high efficiency of each phase will produce a high global efficiency. It should be noted however that the effectiveness of any system is highly dependent on the human engagement in the system. Therefore, the impact of ICT in public financial management will be felt only if the decision-makers and the end-users of the services engage themselves in the success of the system. Instead of giving a catalog of services, the focus has been on the model (or methodology) to adopt in designing services for which ICT could enhance the implementation.
In this paper we study several variations of the \emph{pancake flipping problem}, which is also well known as the problem of \emph{sorting by prefix reversals}. We consider the variations in the sorting process by adding with prefix reversals other similar operations such as prefix transpositions and prefix transreversals. These type of sorting problems have applications in interconnection networks and computational biology. We first study the problem of sorting unsigned permutations by prefix reversals and prefix transpositions and present a 3-approximation algorithm for this problem. Then we give a 2-approximation algorithm for sorting by prefix reversals and prefix transreversals. We also provide a 3-approximation algorithm for sorting by prefix reversals and prefix transpositions where the operations are always applied at the unsorted suffix of the permutation. We further analyze the problem in more practical way and show quantitatively how approximation ratios of our algorithms improve with the increase of number of prefix reversals applied by optimal algorithms. Finally, we present experimental results to support our analysis.
Still and multi-media images are subject to transformations for compression, steganographic embedding and digital watermarking. In a major program of activities we are engaged in the modeling, design and analysis of digital content. Statistical and pattern classification techniques should be combined with understanding of run length, transform coding techniques, and also encryption techniques.
In this study, we introduced a probabilistic voter, regarding symbol probabilities in decision process besides majority consensus. Conventional majority voter is independent of functionality of redundant modules. In our study, proposed probabilistic voter is designed corresponding to functionality of the redundant module. We tested probabilistic voter for 3 and 5 redundant modules with random transient errors inserted the wires and it was seen from simulation results that Multi-Modular Redundancy (M-MR) with Probabilistic Voting (PV) had been shown better availability performance than conventional majority voter.
Adopting the scientific method a theoretical model is proposed as foundation for information science and technology, extending the existing theory of signaling: a fact f becomes known in a physical system only following the success of a test f, tests performed primarily by human sensors and applied to (physical) phenomena within which further tests may be performed. Tests are phenomena and classify phenomena. A phenomenon occupies both time and space, facts and inferences having physical counterparts which are phenomena of specified classes. Identifiers such as f are conventional, assigned by humans; a fact (f', f'') reports the success of a test of generic class f', the outcome f'' of the reported application classifying the successful test in more detail. Facts then exist only within structures of a form dictated by constraints on the structural design of tests. The model explains why responses of real time systems are not uniquely predictable and why restrictions, on concurrency in performing inferences within them, are needed. Improved methods, based on the model and applicable throughout the software life-cycle, are summarised in the paper. No report of similar work has been found in the literature.