Time-domain Dielectric Spectroscopy of Carboxymethylcellulose

Práce se zabývá dielektrickou relaxační spektroskopií karboxymetylcelulózy v časové oblasti. V rámci experimentálních prací bylo navrženo a postupně dále vyvíjeno měřicí pracoviště umožňující záznam časového průběhu vybíjecích proudů dielektrik, jeho zpracování a analýzu. Předmětem měření byla karboxymetylcelulóza, což je jednoduchý polysacharid používaný v širokém spektru aplikací, mezi jiným i v biomedicínském inženýrství. Studium vlastností karboxymetylcelulózy si vyžádalo vytvoření vlastního experimentálního zařízení, v němž byly ošetřeny stabilizace vzorku před měřením, jeho nabíjení i vybíjení v definovaných časových intervalech, přepínání mezi jednotlivými režimy, záznam měření, úpravy a zpracování naměřených signálů až po Fourierovu transformaci do frekvenční oblasti. Frekvenční průběh komplexní permitivity či jeho imaginární část, získaný Fourierovou transformací průběhu vybíjecího proudu dielektrika v časové oblasti, se pak označuje jako dielektrické spektrum. Vzhledem k tomu, že měření probíhala na velice nízkých úrovních měřeného signálu (pod 10-12 A), nejednalo se o právě jednoduchou záležitost. V rámci práce tak bylo nutné studovat a řešit otázky zemnění, šumu a citlivosti k různým vnějším vlivům. Hlavním těžištěm práce je matematické zpracování šumu přítomného ve vybíjecím proudu, tedy operace s původními získanými signály v časové oblasti směřující v podstatě k číslicové filtraci zaznamenaných dielektrických dat. Na to navazujícím cílem práce je objasnit dielektrické parametry zkoumaného vzorku karboxymetylcelulózy v co nejširším spektru frekvencí. Nedílnou součást práce tvoří výběr a aplikace metody převodu upraveného signálu do frekvenční oblasti. Měření včetně experimentální části i zpracování měřených dat bylo provedeno na Ústavu fyziky FEKT VUT Brno. Pro účely měření byl používán elektrometr Keithley 617, měřicí most HP 4284A a kryogenický systém Janis CCS-400-204. Výsledky měření byly doplněny měřením provedeným na V. katedře experimentální fyziky Přírodovědecké fakulty University Augsburg.The dissertation deals with the time-domain dielectric relaxation spectroscopy of carboxymethylcellulose. The main attention was paid to the experimental part of research, mainly to the design and subsequent development of an experimental setup for the measurement of discharge currents and for their processing and analysis. The subject of the measurement is carboxymethylcellulose (CMC), which is a simple polysaccharide used in wide range of applications, among else also in biomedical engineering. The study of CMC properties has required the development of a new experimental set-up of original design, which includes the equilibration (short-circuiting) of a sample before the measurement, charging and discharging at defined time intervals, switching between these two modes, recording of measurement, adjustments and processing of measured signals up to Fourier transformation into the frequency domain and, finally, calculation of complex permittivity of the sample. The frequency dependence of complex permittivity or its imaginary part, obtained by Fourier transformation of discharge current in time domain, is then referred to as the dielectric spectrum. In view of the fact that current measurements were done at very low levels of measured signal (below 10-12 A) the whole measurement was no easy matter. The framework of the work also necessitated studies and subsequent resolution of problems associated with shielding, grounding, presence of noise and sensitivity to various ambient influences. The research work focused on a reliable and trustworthy measurement of very low discharge currents and, subsequently, mathematical processing of noise present in them, i.e., operations with the original, experimentally established signal in time domain, leading in principle to a digital filtration of measured dielectric data. A further pursued objective is the explanation of dielectric parameters of tested carboxymethylcellulose sample in the widest possible frequency spectrum. The integral part of the research was the selection and application of the method for the transformation of the adjusted signal to the frequency domain. The experimental works, including data processing, were carried out in the Department of Physics, Brno FEEC BUT. Measurements were done with Keithley 617 Electrometer, HP4284A Frequency Analyzer and Janis CCS-400-204 cryogenic system. The results were completed with results obtained at the V Department of Experimental Physics, Centre for Electronic Correlations and Magnetism, University of Augsburg, Germany.

Employee Attrition System Prediction using Random Forest Classifier

Despite rising unemployment, most job coverage of the COVID-19 outbreak has concentrated on layoffs. Employees have been fired for reasons related to the epidemic, which has been a less prominent issue. COVID-19 is still doing damage to the country\u27s economy. Companies are in the midst of a recession, so they are beginning to fire off unproductive employees. Making critical decisions like laying off employees or cutting an employee\u27s compensation is a challenging undertaking that must be done with extreme attention and accuracy. Adding negligence would harm the employee\u27s career and the company\u27s image in the industry. In this paper, we have predicted employee attrition using Logistic Regression, Random Forest, and Decision Tree techniques. Random Forest Classifier has outperformed other algorithms in this work. After using different machine learning techniques, we can say that Random Forest gives the best performance with a recall of 70%, and also, we have found Precision, Accuracy, and F1- Score

Predicting Accurate Heart Attacks Using Logistic Regression

A heart attack is one of the leading causes of death today. According to a large data population used as a training set for the algorithm for machine learning, classification is a technique for predicting the target class from input data. A difficulty in clinical data analytics is predicting heart attacks with greater precision. The focal point of this work is to analyze the heart attack dataset (Kaggle repository) to find a Machine learning classifier technique that predicts if a person is prone to a heart attack with maximum accuracy based on various health factors. The efficacy of the three classifiers, namely Logistic Regression, Random Forest, and Decision Tree, is demonstrated for predicting heart attack. This work compares the three classification algorithms among various factors. Logistic Regression outperforms all for predicting the values from the dataset accurately

Clinical study of primary caesarean section in multiparous women in a tertiary care hospital

Background: The objective of this study was to find the incidence and indications of primary caesarean section in parous women and evaluate the maternal and perinatal outcomes there from.Methods: Prospective study of primary caesarean sections in parous women at our institute from June 2013 to May 2014 was done. Age, indications and the maternal as well as perinatal outcomes were analyzed. Data was expressed as number and percentage.Results: Out of 1124 caesarean deliveries, 68 primary caesareans in parous women were done.  The most common age group was 21-30 years. The majority of parous women who underwent primary caesarean section, were para 2. Booked cases constituted the maximum number of such women at 97.1 % (n=66). In parous women undergoing primary caesarean section, the number of spontaneous onset of labour was significantly more than those undergoing induction of labour. The most common indication for caesarean section in this group of patients was fetal distress. There was no neonatal mortality or adverse maternal outcome.Conclusions: Fetal distress was the most common indication for primary caesarean section in the parous woman, although malpresentation also contributed significant numbers. Primary caesarean sections in women with previous vaginal deliveries, were not associated with any significant neonatal or maternal complications

Variation of Roughness in a Non-Prismatic Converging Compound Channel

For the management of rivers and floodplains, it is important to understand the behavior of flows within compound channels. Flooding situation in rivers is a complex phenomenon which affects the livelihood and economic condition of the region. The modeling of such flow is of primary importance for river engineers and scientists to work in this field. As a result of topographic changes along the open channels, designing the converging compound channel is important. Fluvial flows are strongly influenced by geometric complexity and large overall uncertainty on every single measurable property, such as roughness or velocity distribution on different sectional parameters like width ratio, aspect ratio and hydraulic parameter such as relative depth. Flow structure in non-prismatic compound channel is more complex than straight channels due to 3-dimentional nature of flow. The usual practice in one dimensional analysis is to select a value of n depending on the channel surface roughness and take it as uniform for the entire surface for all depths of flow. The influences of all the parameters are assumed to be lumped into a single value of n. The roughness of the main channel was determined by measuring the velocity of water flowing along the main channel. Patra (1999), Patra and Kar (2000), and Pang (1998) have shown that Manning’s n coefficient not only denotes the roughness characteristics of a channel but also the energy loss in the flow. The coefficients for Chezy’s and Darcy-Weisbach friction factors from in bank flow to over bank flow are found to be in line with the behavior of Manning’s n. The larger the value of n, the higher is the loss of energy within the flow. Although much research has been done on Mannings n, for straight channels, very little has been done concerning the roughness values for non-prismatic compound channels. In this paper, an experimental investigation of a non-prismatic compound channel having converging flood plains is investigated. Five sections with different cross-sections along the longitudinal direction of the non-prismatic channel are analysed to scrutinize the change in the value of Manning’s n along the path of the channel