Měření silových účinků el. proudu

Import 03/11/2016Bachelor thesis deals with force effects of electric currents that arise in the profiled busbars. The first part is dismantled theory of the origin of these forces. The basic principles of these forces and the theory of strain gauges. The second section describes the implementation of practical part of the whole scheme further measurements and members that I will use. This calculation and verification of the calculations, comparing the measured values. The last part is made exemplary laboratory task for future measurements younger students.Bakalárska práca sa zaoberá silovými účinkami elektrického prúdu, ktoré vznikajú v profilovaných prípojniciach. V prvej časti je rozobratá teória vzniku týchto síl. Základné princípy týchto síl a aj teória o tenzometrií. V druhej časti je popísaná realizácia praktickej časti, ďalej schéma celého merania a členov ktoré budem používať. K tomu aj výpočet a overenie výpočtov porovnaním s nameranými hodnotami. V poslednej časti je zhotovená vzorová laboratórna úloha pre budúce merania mladšími študentmi.410 - Katedra elektroenergetikyvýborn

Methodology for measurement of parameters of luminaires by spectroradiometer and goniophotometer

Táto diplomová práca je zameraná na riešenie problematiky merania svietidiel. Keďže svietidiel je na trhu obrovské množstvo a dnešným trendom je vyrábať svietidlá so zdrojom LED, zamerám sa na tento smer. V práci sa budem zaoberať problematikou LED osvetlenia vozidla, kde sú kladené na svietidlo určité požiadavky. Budem sa taktiež zaoberať problematikou merania a návrhom vhodnej metódy merania svietidiel pomocou spektroradiometra a goniofotometra. Svietidlo sa podrobí jasovej analýze. Výsledky z meraní porovnám na základe medzinárodných noriem pre automotive.This diploma thesis is focused on solving problems of luminaire measurement. Since there is a huge amount of light on the market and today's trend is to produce LED lamps, I will focus on that direction. In my work I will deal with the issue of LED lighting of the vehicle where certain requirements are placed on the luminaire. I will also deal with the measurement and design of a suitable method of measuring luminaires using a spectroradiometer and a goniophotometer. The lamp is subjected to luminance analysis. The results from measurements are compared on the basis of international automotive standards.410 - Katedra elektroenergetikyvelmi dobř

Agent-Based Model of the Spectrum Auctions with Sensing Imperfections in Dynamic Spectrum Access Networks

Cognitive radio (CR) is the underlying platform for the application of dynamic spectrum access (DSA) networks. Although the auction theory and spectrum trading mechanisms have been discussed in the CR related works, their joint techno-economic impact on the efficiency of distributed CR networks has not been researched yet. In this paper we assume heterogeneous primary channels with network availability statistics unknown to each secondary user (SU) terminal. In order to detect the idle primary user (PU) network channels, the SU terminals trigger regularly the spectrum sensing mechanism and make the cooperative decision regarding the channel status at the fusion center. The imperfections of the spectrum mechanism create the possibility of the channel collision, resulting in the existence of the risk (in terms of user collision) in the network. The spectrum trading within SU network is governed by the application of the sealed-bid first-price auction, which takes into account the channel valuation as well as the statistical probability of the risk existence. In order to maximize the long-term payoff, the SU terminals take an advantage of the reinforcement comparison strategy. The results demonstrate that in the investigated model, total revenue and total payoff of the SU operator (auctioneer) and SU terminals (bidders) are characterized by the existence of the global optimum, thus there exists the optimal sensing time guaranteeing the optimum economic factors for both SU operator and SU terminals

Randomized double-blind, placebo-controlled multicenter phase III study of prevention of irinotecan-induced diarrhea by a probiotic mixture containing Bifidobacterium BB-12®Lactobacillus rhamnosus LGG® in colorectal cancer patients

BackgroundThe incidence of irinotecan-induced diarrhea varies between 60-90%, by which the incidence of severe diarrhea is 20-40%. The objective of this phase III trial was to determine the effectiveness of the probiotic mixture containing Bifidobacterium, BB-12® and Lactobacillus rhamnosus, LGG® in the prophylaxis of irinotecan-induced diarrhea in metastatic colorectal cancer patients due to a reduction in the activity of intestinal beta-D-glucuronidase.MethodsFrom March 2016 to May 2022, a total of 242 patients with colorectal cancer starting a new line of irinotecan-based therapy were registered to the study in 11 cancer centers in Slovakia. Patients were randomized in a ratio 1:1 to probiotic formula vs. placebo that was administered for 6 weeks. Each capsule of Probio-Tec® BG-Vcap-6.5 contained 2.7x109 colony-forming units (CFU) of 2 lyophilized probiotic strains Bifidobacterium, BB-12® (50%) and Lactobacillus rhamnosus GG, LGG® (50%).ResultsAdministration of probiotics compared to placebo was not associated with a significant reduction of grade 3/4 diarrhea (placebo arm 11.8% vs. probiotic arm 7.9%, p=0.38). Neither the overall incidence of diarrhea (46.2% vs. 41.2%, p=0.51) nor the incidence of enterocolitis (3.4% vs. 0.9%, p=0.37) was different in the placebo vs. probiotic arm. Subgroup analysis revealed that patients with colostomy had higher incidence of any diarrhea and grade 3/4 diarrhea in the placebo arm compared to the probiotic arm (48.5% vs. 22.2%, p=0.06 and 15.2% vs. 0%, p=0.06, respectively). Moreover, patients on probiotic arm had significantly better diarrhea-free survival (HR = 0.41, 95%CI 0.18 – 0.95, p=0.05) and needed less loperamide (p=0.01) compared to patients on placebo arm. We did not observe any infection caused by probiotic strains used in this study.ConclusionThis study failed to achieve its primary endpoint, and results suggest a lack of benefit of administered probiotic formula for the prevention of irinotecan-induced diarrhea. However, subgroup analysis suggests a possible benefit in patients with colostomy

CSVO: Clustered Sparse Voxel Octrees—A Hierarchical Data Structure for Geometry Representation of Voxelized 3D Scenes

When representing the geometry of voxelized three-dimensional scenes (especially if they have been voxelized to high resolutions) in a naive—uncompressed—form, one may end up using vast amounts of data. These can easily attack the available memory capacity of the graphics card, the operating memory or even secondary storage of computer. A viable solution to this problem is to use domain-specific hierarchical data structures, based on octant trees or directed acyclic graphs, which, among other advantages, provide a compact binary representation that can thus be considered to be their compressed encoding. These data structures include—inter alia—sparse voxel octrees, sparse voxel directed acyclic graphs and symmetry-aware sparse voxel directed acyclic graphs. The paper deals with the proposal of a new domain-specific hierarchical data structure: the clustered sparse voxel octrees. It is designed to represent the geometry of voxelized three-dimensional scenes and can be constructed using the out-of-core algorithm proposed in the paper. The advantage of the presented data structure is in its compact binary representation, achieved by omitting a significant number of pointers to child nodes (82.55% in case of Angel Lucy model in 1283 voxels resolution) and by using a wider range of child node pointer lengths, including 8b, 16b and 32b. We achieved from 6.57 to 6.82 times more compact encoding, compared to sparse voxel octrees, whose all node components were 32b aligned, and from 4.11 to 4.27 times more compact encoding, when not all node components were 32b aligned

MLMD—A Malware-Detecting Antivirus Tool Based on the XGBoost Machine Learning Algorithm

This paper focuses on training machine learning models using the XGBoost and extremely randomized trees algorithms on two datasets obtained using static and dynamic analysis of real malicious and benign samples. We then compare their success rates—both mutually and with other algorithms, such as the random forest, the decision tree, the support vector machine, and the naïve Bayes algorithms, which we compared in our previous work on the same datasets. The best performing classification models, using the XGBoost algorithm, achieved 91.9% detection accuracy and 98.2% sensitivity, 0.853 AUC, and 0.949 F1 score on the static analysis dataset, and 96.4% accuracy and 98.5% sensitivity, 0.940 AUC, and 0.977 F1 score on the dynamic analysis dataset. Then, we exported the best performing machine learning models and used them in our proposed MLMD program, automating the process of static and dynamic analysis and allowing the trained models to be used for classification on new samples