Usually when modeling a real process the effects of nonlinearities must be taken into account. A road traffic sector is one such process. Considering it from a macroscopic point of view, the sector is modeled both as ...
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Usually when modeling a real process the effects of nonlinearities must be taken into account. A road traffic sector is one such process. Considering it from a macroscopic point of view, the sector is modeled both as a nonlinear and as a linearized process. An 110 model is proposed and a RST control algorithm is used to ensure the imposed performances for the closed loop system. The robustness of the system is obtained by determining the modulus margin and based upon it the admissible nonlinearities are analyzed in order to determine the limits between which the system maintains its stability.
The problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data, is considered. It is shown how several competing Kalman-type parameter ...
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The problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data, is considered. It is shown how several competing Kalman-type parameter smoothers, differing in smoothness constraints and memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing bandwidth to the unknown, and possibly time-varying, rate of nonstationarity of the identified system. It also allows one to account for parameter jumps and for the distribution of measurement noise.
The paper presents a method for estimation of converter drive parameters. This estimation encompassed three types of drives, i.e. a static Scherbius drive, a drive with a brushless direct current (BLDC) motor and a dr...
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The paper presents a method for estimation of converter drive parameters. This estimation encompassed three types of drives, i.e. a static Scherbius drive, a drive with a brushless direct current (BLDC) motor and a drive with a voltage inverter. For drive modelling and parameter estimation, the author implemented original programmes written in FORTRAN. As well as these, the paper describes an objective function applied for the estimation. The author also compares gradient and gradientless methods, which are applied for minimization of the objective function. Finally, the author explains the estimation results for example drives, focusing on the coincidence of theoretical and empirical waveforms. The abovementioned procedure led to the general rule, which facilitates estimation efficiency.
The paper provides a case study on the wireless circuit for the purpose of the EGG (Electrogastrography) signal acquisition. The authors present an amplifier based on the ADS1298, wireless communication module (Blueto...
The paper provides a case study on the wireless circuit for the purpose of the EGG (Electrogastrography) signal acquisition. The authors present an amplifier based on the ADS1298, wireless communication module (Bluetooth) and the microprocessor unit which have been recently built. The system is currently under examination but the outcome is very promising because the amplifier input is fed with the pure signal, i.e. no high/low pass filter is applied, that is a novelty. The system presented in this paper could be helpful in diagnosis gastric disorders in noninvasive way. It could determine patients with unexplained nausea, vomiting and other dyspeptic symptoms. The unit is under clinical trials tests and preliminary evaluation indicates acceptance by medical staff. Additional advantages are the relatively low cost of manufacture and the possibility of application remotely (pervasive computing).
This paper describes a method for medical images annotation based on the SURF descriptor and the SVM classifier. For the features extraction a Fast-Hessian detector was used. The feature matching was performed with a ...
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This paper describes a method for medical images annotation based on the SURF descriptor and the SVM classifier. For the features extraction a Fast-Hessian detector was used. The feature matching was performed with a SVM with a quadratic kernel. The testing of the developed system was performed using a subset of the IRMA radiographic images. The results provided with the SURF descriptor are compared with the ones obtained using the SIFT descriptor with SVM classification. Applying the SURF descriptor resulted in improved classification of lung images with an accuracy over 96%. The research shows that the SURF is a potentially strong tool to be applied in the field of medical image annotation. Together with the SVM classification it may construct an efficient system for automatic medical image retrieval and annotation.
The main goal of this paper is to inform the reader about new directions in cloud computing, referring to performance, availability and, especially, security. We describe modern capabilities that any cloud provider sh...
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The main goal of this paper is to inform the reader about new directions in cloud computing, referring to performance, availability and, especially, security. We describe modern capabilities that any cloud provider should support, together with a cryptographic side of future cloud services -(fully) homomorphic encryption. We also focus on how to integrate the latest in our current cloud computing environment.
Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous...
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Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous optimization exist but DASA seems to be very efficient for the class of highdimension real-parameters optimization problems, becoming a competitor to more classical methods such as Particle Swarm Optimization (PSO). The PSO is a meta-heuristic which is also inspired from insects' life as ACO. Even both methods use a population of entities, the memory of PSO is larger as those of DASA. DASA uses just one current solution around which the population search and the difference that generated last improvement. PSO stores the previous best position and velocity of every particle. This paper attempts to examine if an elitist version of DASA has at least the same effectiveness (finding the true global solution) as PSO, but with significantly better efficiency (less function evaluation). The performance comparison of DASA and PSO is implemented using a set of six test functions well known for their difficulty.
The nature of wireless communication protocols used in automotive industry (eg. TPMS - Tire Pressure Monitoring System, RKE Remote Key-less Entry or PEPS- Passive Entry & Passive Start) and fact, that transmission...
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The nature of wireless communication protocols used in automotive industry (eg. TPMS - Tire Pressure Monitoring System, RKE Remote Key-less Entry or PEPS- Passive Entry & Passive Start) and fact, that transmission between remote sensor and main controller has to be received and correctly decoded, require sophisticated receiver systems. Complexity of systems installed in modern vehicles and variety of multiple conditions cause that verification and validation is the most difficult step of whole design process. Especially important part, that must be carefully checked, is behavior of a system in case of incorrect transmission. These false conditions should be repetitive, exact and comprehensive. Usage of Software Defined Radio (SDR) technique makes posible to fulfill all mentioned above requirements. This article describes utilization of SDR modeling with GNURadio to achieve flexible and very powerful Verification Platform for one-way automotive communication protocols. Description is focused on TPMS module however our solution works well for other protocols such as PEPS, RKE and similar.
The commonly used approach to avoid the effects of a critical situation in an industrial plant is a limited strategy. The paper describes the implementation of a defect classifier on a Waste Water Treatment Plant as a...
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The commonly used approach to avoid the effects of a critical situation in an industrial plant is a limited strategy. The paper describes the implementation of a defect classifier on a Waste Water Treatment Plant as a means of achieving early warning and devising proper response to a critical situation. According to the IEC 61511/ISA 84 process safety standards, the process risk has to be reduced to a tolerable level as set by the plant owner.
An important issue in the analysis of two-dimensional electrophoresis images is the detection and quantification of protein spots. The main challenges in the segmentation of 2DGE images are to separate overlapping pro...
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