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Assisting physicians in the auscultation of the patients by providing cost effective, automatic and accurate signal processing module for the heart event detection and recognition is of importance. We suggest that the segmentation of time-frequency representation image of one-dimensional phonocardiogram signals (PCGs) could be effective for observing possible abnormal heart events. The fact that frequency...
Accurate spleen segmentation in abdominal MRI images is one of the most important steps for computer aided spleen pathology diagnosis. The first and essential step for the diagnosis is the automatic spleen segmentation that is still an open problem. In this paper, we have proposed a new automatic algorithm for spleen area extraction in abdominal MRI images. The algorithm is fully automatic and contains...
Load prediction is a necessity in a deregulated electrical energy sector. It is important financially and technically. In order to cope with nonlinear and non stationary character of a load signal, an efficient adaptive predictor should be employed. Also, power utilities manage load information as a complex-valued signal. To this cause, performance of a class of complex-valued gradient descent (GD)...
Energy consumption predictions are essential and are required in the studies of capacity expansion, energy supply strategy, capital investment, revenue analysis and market research management. In the recent years artificial neural networks (ANN) have attracted much attention and many interesting ANN applications have been reported in power system areas, due to their computational speed, their ability...
Paper deals with application of online rotor broken bar fault detection via artificial neural networks. Fault can be detected by monitoring abnormalities of the spectrum amplitudes at certain frequencies in the motor current spectrum. These discriminative features are used for training of feed-forward backpropagation artificial neural network. Trained network is capable to successfully classify induction...
This work presents the technical aspects for the development of a firmware for a Nd:YAG laser based ophthalmic surgery microscope. The software designed for a Microchip® PIC18F4550 microcontroller interfaces the electronic blocks of the device and allows the calibration of the laser energy attenuator. This paper mainly describes the experimental setup and presents the experimental data for an innovative...
Wireless mesh networks (WMN) represent a type of mobile ad-hoc networks. These networks are very important in providing the Internet access to fixed and mobile terminal equipment. The main problem in WMNs (regarding to mesh routers and mesh clients) is a routing protocol, especially because it has to enable the access to network for both mesh and conventional clients. Access to Internet for wireless...
Advancements in digital electronics and signal processing algorithms for various purposes generated the possibility and need for designing artificial neural networks in hardware. The selected platform, FPGA, enables fulfillment of their demands and provides comfortable work and test environment. This paper presents development cycle and specifics for implementation of high speed Hamming artificial...
Two modern concepts implemented for forecasting based on reduced time series are contrasted. Results obtained by use of artificial neural nets (ANNs), already discussed at this conference, are compared with the ones obtained by implementation of the so called Grey theory or Grey Model (GM). Particularly, feed-forward accommodated for prediction (FFAP) and time controlled recurrent (TCR) ANNs are used...
Feed-forward artificial neural networks (ANNs) have been applied to the diagnosis of mixed-mode electronic circuit. In order to tackle the circuit complexity and to reduce the number of test points hierarchical approach to the diagnosis generation was implemented with two levels of decision: the system level and the circuit level. For every level, using the simulation-before-test (SBT) approach, fault...
This paper addresses the problem of vowels recognition in patients after total laryngectomy using combined visual and acoustic features. The linear prediction coefficients were estimated from speech signal using weighted recursive least squares algorithm. Ten cross-sectional areas of vocal tract model were calculated. Face expression parameters related to the spoken vowel were extracted from video...
This paper presents investigation on speech recognition classification performance when using different standard neural networks structures as a classifier. Those cases include usage of a Feed-forward Neural Network (NN) with back propagation algorithm and a Radial Basis Functions (RBF) Neural Network.
In this paper we present a method for optimization of spatial selectivity of multi-pad electrode during transcutaneous Functional Electrical Stimulation (FES). The presented method is based on measurement of individual muscle twitches using Micro-Electro-Mechanical Systems (MEMS) accelerometers positioned on hand, while stimulating with low frequency electrical stimulation via pads within multi-pad...
This paper focuses on grid performance optimization in large scale workflow applications with an intelligent workflow scheduling mechanism. Utility Management Systems (UMS) are managing very large numbers of workflows with very high resource requirements. This paper proposes a UMS scheduling architecture which dynamically executes a scheduling algorithm using near real-time feedback about the current...
This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.
Due to high penetration of wind generation in modern power systems, the influence of wind power production over the efficient operation of the power system is increasingly complex. Hence, an increasing interest is shown by different actors in the wind energy market to develop and enhance existent forecasting methods for power generated by wind farms. This paper presents the experience with wind power...
This paper proposes novel approach in coding single phonemes based on mel-frequency cepstral coefficients (MFCC) in order to simplify the neural network used to recognize those phonemes. The efficiency and effectiveness of proposed algorithm are demonstrated for both male and female speakers.
We present the method for classifying kinematical data required for control of a rehabilitation robot for upper extremities. The classification to two cases (success, no-success) was analyzed by two methods: Bayes estimation and artificial neural network (ANN). The results are presented for an example being envisioned for rehabilitation: playing the Wii bowling with the specially constructed pantograph...
Summary form only given. The contemporary robotics technology is broadening its applications from factory to more general-purpose applications in domestic and public use, e.g., partner to the elderly, rehabilitations, search and rescue, etc. If robotics technology is to be successful in such complex, unstructured, dynamic environments with high level of uncertainties, it will need to meet new levels...
The genetic code is analyzed as one of the major natural codes, which as such can reveal the deeper principles of optimal coding. The analysis is based on a discovery that the symmetrical architecture of genetic code and the nucleon number of its constituents - the free canonical amino acids and bases, are strictly determined by the prime number with a cycling digit property -037. A detailed derivation...
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