Second IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings

The following topics are dealt with: data acquisition systems; intelligent measurement systems; artificial intelligence; cyber security; distributed computing; virtual instrumentation; data mining; artificial neural networks; data analysis; signal processing; image processing; data compression; problem solving View full abstract»

The rapid growth of powerful single-chip microcomputers for monitoring and data acquisition applications permits nowadays the design of advanced measuring systems. We present an advanced on-line monitoring configuration in order to improve the performance and extend the lifetime of ultrasonic transducers by applying an automated testing and calibration technique. The operation of this instrumentat... View full abstract»

We describe solutions, how to improve a quality of basic testing methods to be possible to use them for dynamic testing high-resolution/middle speed AD converters and AD modules. The following methods are described: an application of low-distortion band pass filters, a digital correction of a known distortion of a testing signal, an application of a two-tone (or multitone) signal, an application o... View full abstract»

The a priory poor known and complex measurement objects have to be served by the multiplex instrumentation which allows adopting it's next sampling program to the current object situation. Such task may be realized by a little bit more intellectualized system with capability of object behavior analyzing and self programming View full abstract»

We present the results on the design, production and preliminary experimental testing of the multichannel magnetocardiography (MCG) device. Such a supersensitive device is intended for examination of the patients with cardiology diseases and investigation of the electrophysiological processes in a human heart and in Ukraine was developed for the first time. Device possesses 8 channels including 4 ... View full abstract»

We present a complete description and evaluation of the features of a novel method for the instruction-level energy consumption measurement and the corresponding modeling approach for embedded microprocessors. According to the proposed method the base and inter-instruction energy costs of the ARM7 embedded processor as well as the energy cost due to different values in the instruction parameters a... View full abstract»

We discuss analytic procedures for evaluating the availability of parallel computer systems comprised of P processors with N tasks subject to failures and repairs. In addition, we argue, via analytic and numeric examples, that not incorporating the task-stream into the model is an inadequate approach for evaluating system performance View full abstract»

Previous code compression research on embedded systems was based on typical RISC instruction code. THUMB from ARM Ltd is a compacted 16-bits instruction set showing a great code density than its original 32-bits ARM instruction. Our research shows that THUMB code is compressible and a further 10-15% code size reduction on THUMB code can be expected using our proposed new architecture - code compre... View full abstract»

Cluster rendering systems often take a sort-first, sort-last, or a hybrid of these two approaches because it is generally assumed that the hardware pipeline cannot be split between the geometric and rasterization stages. These approaches often limit the scalability of the system because they introduce either load balancing problems or high contention for the communication network. We propose a nov... View full abstract»

The Bluetooth radio multipath, fading indoor channel with additive white Gaussian noise (AWGN), was evaluated by simulation using a component-based architecture to model the physical layer. The communication model included forward error correction (FEC) and automatic repeat request (ARQ) schemes. The observed bit error rate (BER) versus signal:noise ratio (SNR) using AWGN and a statistical channel... View full abstract»

We consider the creation of intelligent solving machines and the arrangement of parallel programming in intelligent distributed multiprocessor systems based on them. There are some proposed main concepts. A system is designed for programming in the C+Graph high-level language. The ideology proposed can be considered as an efficient development of structural high-level language interpretation when ... View full abstract»

We have addressed the problem of observability of power systems from the point of view of topological observability and using genetic algorithms for its determination. The objective is to find a way to determine if a system is observable by establishing if a spanning tree of the system that verifies certain properties with regards to the use of available measurements can be obtained. To this end w... View full abstract»

We propose a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA algorithm) o... View full abstract»

Decision making is done in many application areas. Still most studies are done in such fields as economy and production planning. In methodologies used there exists more variation. We review the decision concepts discussed in the literature. Also some decision models by the author are commented. The field and practise in decision science is summarized. Although decision support systems are the fin... View full abstract»

We describe experiments with machine learning algorithms (ID3, C4.5, Bagged-C4.5, Boosted-C4.5 and Naive Bayes) and an algorithm made on the basis of a combination of genetic algorithms (GA) and ID3. To perform the experiments, the latter algorithm is implemented as an extension of the MLC++ library of Stanford University. The behaviour of the algorithm is tested using 24 databases including the d... View full abstract»

Decision making is mostly based on decision concepts and decision models built in decision support systems. Type of decision problem determines application. We present a conceptual decision model that utilises rule-based methodologies, numerical algorithms and procedures, statistical methodologies including distributions, and visual support. Selection of used decision concepts is based on case-bas... View full abstract»

The estimation of the regulation work periodicity of the risk technical systems is an extremely important moment for its technical service. Many scientific publications concern this problem but most of them deal with a service process for an infinite technical exploitation period. A solution of the problem for a limited interval of technical exploitation is suggested. A reliability model of the ob... View full abstract»

An ad-hoc sensor network is a set of sensor nodes that communicate by sending messages over wireless link either directly to destination node or indirectly over a sequence of nodes. Sensor networks are often formed by ad-hoc deployment and utilized for information gathering and processing. Since design sensors are small inexpensive devices it can be expected that wireless networks of thousands or ... View full abstract»

Main reliability characteristics of unrestorable symmetric computing systems ramified to level 2 and with ageing ramified elements are examined. Expressions for the failure probability, the failure frequency and the failure rate are worked out in the cases when the reliability of ageing output elements is circumscribed by the Rayleigh distribution or by the Weibull distribution View full abstract»

The chromatography separation of two chemical species (c₁ and c₂) that transform into each other with first-order kinetic as they pass through a Langmuir isotherm reactor is governed by a concrete system of nonlinear hyperbolic equations. We study the problem of existence and uniqueness of wave type solutions of such system (usually called simple stat... View full abstract»

We propose an incomplete Cholesky factorization for the solution of large positive definite systems of equations and for the solution of large-scale trust region sub-problems. The factorization is based on the two-parameter (m,p)-drop-tolerance strategy for insignificant elements in the incomplete factor matrix. The factorization proposed essentially reduces the negative processes of irregular dis... View full abstract»

We discuss the neural network approach for computing of Lyapunov spectrum using one dimensional time series from unknown dynamical system. Such an approach is based on the reconstruction of attractor dynamics and applying of multilayer perceptron (MLP) for forecasting the next state of dynamical system from the previous one. It allows for evaluating the Lyapunov spectrum of unknown dynamical syste... View full abstract»

The analysis of turbulent flow signals irregularly sampled by a laser Doppler velocimeter is assessed by means of ANNs. This technique has been proven to correctly predict the time evolution of turbulent signals. We are taking advantage of this ability to obtain models of unevenly sampled signals and thus be able to reconstruct and resample them at a regular pace in order to allow for their conven... View full abstract»

We simulate an associative memory model using spiking neurons. Those models in which we specify interaction among McCulloch-Pitts neurons by a Hebbian-like learning algorithm, for example, already exist. The Hopfield model is one of these examples. Though we have still many unknown issues in the Hopfield model of associative memory, we have some inevitable drawbacks as well, such as small storage ... View full abstract»

To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. In contrast to the ordinary approach of utilising all neural networks available to make a committee decision, we propose creating adaptive committees, which are specific for each input data point. A prediction network is used to identify classification neural networks to be fused for ... View full abstract»