In this paper, the Incremental Conductance maximum power point tracking (MPPT) algorithm is evaluated using an experimental setup consisting of two 75W photovoltaic (PV) panels connected in series. Humusoft MF 634 board is used to obtain and produce signals. The model was tested under changing solar irradiance conditions, and the acquired results show that it is able to respond to these changes appropriately.

In this paper, two approaches are evaluated using the Full Error Detection and Correction (FEDC) method for a pipelined structure. The approaches are referred to as Full Duplication with Comparison...

Assessment of skeletal maturity is typical strategy applied in clinical pediatrics today. The main goal of a Bone Age Assessment (BAA) is to determine endocrinology and growth disorders by comparing the bone and chronological age of the patient. Several methods are developed to determine skeletal maturity, but Greulich-Pyle and Tanner-Whitehouse represent the two most common methods that involve left hand and wrist radiographs. However, these methods are extremely time-dependent and rely on an experienced radiologist, who further evaluates bone age using hand atlas as a reference. In this paper, VGG-16 and ResNet50 are two Deep Convolutional Neural Network (DCNN) models applied with ImageNet pre-trained weights in order to estimate correct bone age and achieve high accuracy of gender prediction using public RSNA dataset that includes 12611 radiographs. The experimental results show month discrepancy of approximately eight months and 82% accuracy during the process of gender classification.

Abstract The process of experimental identification refers to a challenging task since most of the closed-loop identification methods depend on some existing knowledge of the controlled object. Although various identification methods have been described and implemented in the past, the common issue refers to the use of nonlinear equipment such as relays that may cause an undesirable error and consequently affect the accuracy of the controlled object. The main aim of this research is to conduct experimental verification of a novel approach to linear system identification in the closed-loop feedback system. The novel approach represents an extension to the Ziegler-Nichols experiment performed in the closed-loop feedback system, but without using any additional equipment. One servomechanism composed of two motors is used as an object of identification where data acquisition is performed using a dSPACE embedded module allowing real-time reading of measurement results. The conducted experiment succeeds in locating a representative number of points in the Nyquist plot bringing only damped oscillations. Finally, the considered motor is identified as a first-order object due to the dynamic of available mechanical as well as electrical subsystems.

The regulation of functions such as respiratory or heart rate in human body as well as the control of motor movements are under the control of nervous system. As these actions and correlated tasks are directly influenced by the brain, the brain monitoring gives the possibility to differentiate the tasks, enabling at the same time the prediction of further actions. In this contribution, publicly available electroencephalography (EEG) datasets are analyzed with respect to the detection of epileptic seizure occurrence and BCI-related actions (here: cued motor imagery). For these purposes, timefrequency- based feature extraction alongside different classification methods is used. To perform the classification, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are utilized and compared with previously obtained results. The feasibility of particular features for the detection of epileptic seizures and BCI-related tasks is discussed. Four different feature vectors per analyzed problem are identified. Acceptable accuracy of classification using ANN- and SVMbased classifiers is achieved using identified feature vectors.

Abstract Purpose of this paper is to present the project that will use artificial intelligence and features of Altera FPGA board to imitate human. This problem was solved by using Cleverbot Google API and Altera FPGA board which has Linux system installed to run backend of our application. Frontend input and output peripherals will be used to read input from user and to present output to user. We present an implementation which has all the necessary features to be used for treating social anxiety disorder by simulating real human interaction by effectively employing such algorithms and system.

Abstract: Regarding the fact that the industrial robot PUMA 560 is one of the robots with the best mathematical description of its kinematics, it found the new application in the research laboratories for educational purposes. For that reason there is a need to design new controllers which would be compatible with the contemporary CAD tools used for robot movement programming in a graphic manner. Basically, new controllers can be divided into two groups: PC-based and with embedded computer. It is well established that PC computers are known for their unreliability and sensitivity to computer viruses and the suggestion is that the stated shortcomings should be overcome by the use of FPGA based embedded computers. In this paper is suggested FPGA based controller which has to answer the following requirement of the hypothesis: realisation of the robot controller based on FPGA chip (single chip) which contributes the system availability and safety while answering all the functional, safety and economical requirements. The new controller will enable the use of advance CAD tools which is one of the aims of the research.

Abstract This paper is a description of universal block created for the purpose of simplifying realization of control structure for anthropomorphous robots on FPGA chip. Block is realized in Matlab with installed DSP Builder used for programming Altera FPGA chips with FPGA Real Time Toolbox. In the paper are also provided prerequisites and control structure for robot PUMA 560, as well as simulation results of the chosen algorithm realized in Matlab with Robotics Toolbox. In the end of the paper are provided experimental results verified on robot PUMA 560. Matching between experimental and simulation results validates the concept of the realized controller hardware and universal block.