Student EEICT 2021

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    Modeling Of Multiple Electrode System For Inhomogeneity Detection
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021) Mancl, Vlastimil
    Capacitive sensing gained on popularity through the last decades. From proximity sensorsthrough humidity measurement to touch screen matrices. Capacitive sensing offers reliability,simplicity, and low financial cost. One of the crucial parts of the capacity sensor is the setup of theelectrodes. The behavior of such setup is often needed to be known before application. Due to thecomplex nature of electrostatic arrays, the precise analytic solution is often unavailable so the othermeans to gain solution is needed. This paper focuses on using the simulation for modeling of multipleelectrode setup, which could be used for measuring inhomogeneity in an otherwise homogeneousdielectric. The paper describes the problem of sharp edges. The description of the sensing depth of aplanar capacitor is also included. Three simulations were created to prove initial assumptions.
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    Influence Of Piezoelectric Material Properties On Impedance Characteristic And Improvements Of Calibration Equipment
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021) Krejčí, Jakub
    This paper deals with finite element simulations of impedance characteristics piezoelecticelements utilized in sensors of acoustic emission (AE). Coefficients of piezoelectric material arechanged to evaluate the sensitivity to their variation in case they are not known precisely, so to whichextent can they influence the sensitivity of the sensor. Result showed sensitivity on coefficient inc-matrix, mainly to coefficients c11 and c13. Second investigated topic is issue with test stand for calibrationof AE sensors, where output of force sensor was affected by parasite signal. By contactlessmeasurement with laser interferometer was discovered the parasite signal is caused by mechanic ofthe system and it is no threat for the measuring chain.
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    In-Bed Posture Classification
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021) Husák, Michal
    The growing trend of the population age contributes to the accumulation of patients insocial facilities and in-home care, which leads to growing chronic diseases. Modern systems try toimprove the effectiveness of health care interventions. Our work aims to create a widely applicableplatform that combines the measurement of in-bed position with another’s negative states. All thesephysical influences are mainly the cause of chronic tissue damage (pressure ulcers). Processing ofthe pressure distribution on the bed is a more dimension problem. The mentioned data are multimodal.Therefore, we used the machine learning (ML) method to obtain the properties.
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    Techniques For Avoiding Model Overfitting On Small Dataset
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021) Kratochvila, Lukas
    Building a deep learning model based on small dataset is difficult, even impossible. Toavoiding overfitting, we must constrain model, which we train. Techniques as data augmentation,regularization or data normalization could be crucial. We have created a benchmark with a simpleCNN image classifier in order to find the best techniques. As a result, we compare different types ofdata augmentation and weights regularization and data normalization on a small dataset.
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    Comparison Of Methods For Impulse Response Computation
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2021) Karsky, Vilem
    This paper deals with obtaining impulse responses from integer order and fractional ordertransfer functions. There are shown three method how to compute inverse Laplace transform. The firstmethod is based on Mittag-Leffler functions, the second method is formed on generalized Laguerrefunctions and the third method lays on Fourier transform. These methods are also compared on twoexamples.