| |
|
Prostatic cancer and possibilities of prediction of early success of radical prostatectomy
Svačina, Jakub ; Hanuš, Tomáš (advisor) ; Zachoval, Roman (referee)
Classification of adenocarcinoma prostatae is very important for the treatment. I have described the disease, its treatment and classification in the introduction. I have analysed a sample of 52 patients from the Urological Clinic of General Faculty Hospital. Simple statistics was used for comparing and analysing of relation of preoperative classification and postoperative development of PSA. I have compared preoperative and operative Gleason's score. Preoperative Gleason score underscores the operative score. PSA decrease is significantly higher in patients with high initial PSA and in patients with classification T2N0M0. PSA one month after surgery does not differ in patients with classification T1C and T2 and it does not correlate with the preoperative characteristics of patients. The decrease of PSA is perhaps dependent only on the surgical treatment. Effect of operation cannot be predicted by Gleason score and by age. These results are valid only for patients undergoing radical prostractomy
|
|
Statistical Classification by means of generalized linear models
Sladká, Vladimíra ; Mrázková, Eva (referee) ; Michálek, Jaroslav (advisor)
The goal of this thesis is introduce the theory of generalized linear models, namely probit and logit model. This models are especially used for medical data processing. In our concrete case these mentioned models are applied to data file obtained in teaching hospital Brno. The aim is statically analyzed immune response of child patients in dependence of twelve selected types of genes and find out which combinations of these genes influence septic state of patients.
|
|
Packet Classification Algorithms
Puš, Viktor ; Lhotka,, Ladislav (referee) ; Dvořák, Václav (advisor)
Tato práce se zabývá klasifikací paketů v počítačových sítích. Klasifikace paketů je klíčovou úlohou mnoha síťových zařízení, především paketových filtrů - firewallů. Práce se tedy týká oblasti počítačové bezpečnosti. Práce je zaměřena na vysokorychlostní sítě s přenosovou rychlostí 100 Gb/s a více. V těchto případech nelze použít pro klasifikaci obecné procesory, které svým výkonem zdaleka nevyhovují požadavkům na rychlost. Proto se využívají specializované technické prostředky, především obvody ASIC a FPGA. Neméně důležitý je také samotný algoritmus klasifikace. Existuje mnoho algoritmů klasifikace paketů předpokládajících hardwarovou implementaci, přesto však tyto přístupy nejsou připraveny pro velmi rychlé sítě. Dizertační práce se proto zabývá návrhem nových algoritmů klasifikace paketů se zaměřením na vysokorychlostní implementaci ve specializovaném hardware. Je navržen algoritmus, který dělí problém klasifikace na jednodušší podproblémy. Prvním krokem je operace vyhledání nejdelšího shodného prefixu, používaná také při směrování paketů v IP sítích. Tato práce předpokládá využití některého existujícího přístupu, neboť již byly prezentovány algoritmy s dostatečnou rychlostí. Následujícím krokem je mapování nalezených prefixů na číslo pravidla. V této části práce přináší vylepšení využitím na míru vytvořené hashovací funkce. Díky použití hashovací funkce lze mapování provést v konstantním čase a využít při tom pouze jednu paměť s úzkým datovým rozhraním. Rychlost tohoto algoritmu lze určit analyticky a nezávisí na počtu pravidel ani na charakteru síťového provozu. S využitím dostupných součástek lze dosáhnout propustnosti 266 milionů paketů za sekundu. Následující tři algoritmy uvedené v této práci snižují paměťové nároky prvního algoritmu, aniž by ovlivňovaly rychlost. Druhý algoritmus snižuje velikost paměti o 11 % až 96 % v závislosti na sadě pravidel. Nevýhodu nízké stability odstraňuje třetí algoritmus, který v porovnání s prvním zmenšuje paměťové nároky o 31 % až 84 %. Čtvrtý algoritmus kombinuje třetí algoritmus se starším přístupem a díky využití několika technik zmenšuje paměťové nároky o 73 % až 99 %.
|
|
Classification analysis
Rensová, Dita ; Juríček, Jozef (referee) ; Kalina, Jan (advisor)
Xazev pracc: Kiasifikacni analy/a Autor: Dita. Rensova Kak'dra: Katedra. pravdepodobnost i a ma.tema.ticke statist iky Vedouci ba.kalarske prace: Ur.rer.nat. Ja.n Kaliua e-mail vedoucfho; kalina n-karlin.inff.cuni.c7 Al)stvakt: V toto pnici sc- zabvvame modely klasifikacm analyzy. Popiseme jednotliva klasiiikacni pravidla, a son\islosti mexi niini. Nejprve sc zaniefhne na modely line-arm a kvadraticke klasifikaee pru pripad dvou sknpin. kterr dak1 xobccninu: na, linearni a. kvadi'at.icke inodcly pro pn'pad kla,sifikae.e do vice skupin. Pole so bndeine /abyvat pra\xlepodobnosti s[>a.tnc klasifikaeo nrcit(''ho objektu do sknpiny a.mettxlami, jak Into pravdepodobnost odhad- nont. Dale se zmhn'nie o vyu/iti diskriniinacnieh skc'irii pri kiasifikaei a so- ziianiune se s modoloni logist.ieke kla.sifika.ee. Na zaver pfetlvedi^iuj ponzitf nekt.erych vy!)ranyeli modclii na, konkn'M nieli dateeh / oborn lesnictvi. Klieova slova: Lincarni klasifikace. kvadraticka klasilikacc, lo^ist.icka klasi- fikace. diskrhninacc a klasifikace Title: Cla.ssifica.t ion analysis Author; Uita Hensova Depaituiont,: Department ol Probability and Mathematical Statistics Supervisor: IJr.rer.nat. .Jan Kalina Supervisor's e-mail address: kalina:(i;karhn.mfl.cuni.c/ Abstract.: In the- present work we study methods for classification analysis....
|
|
The effect of the operator on the accuracy of the estimates of lean meat share in pigs
Jiravová, Renata ; Šprysl, Michal (advisor) ; Libor , Libor (referee)
The aim of the study followed the determination of operator error, ie repeatability, or influence of the measuring point on the accuracy of the estimate of lean meat share (LMP). It was a FOM-SFK instrument measured at prescribed locations the backfat thickness, muscle depth, and thus their LMP in their carcass realization in SEUROP system. For this purpose a total of 71 hybrid pigs (Dan-Bred) were measured at the Velvary slaughterhouse. In order to determine the error from incorrectly determined place of measurement, the following six classification insertions were done per one animal, thus 1. 2nd -- 3rd last rib 7 cm off the midline (right point), 2. 2nd -- 3rd last rib 7 cm off the midline (repeat in the same hole), 3. 2nd -- 3rd last rib 1 cm caudal to the right point, 4. 2nd -- 3rd last rib 1 cm cranial to the right point, 5. 3rd -- 4th last rib 1 cm medial to the right point, 6. 1st --2nd last rib 1 cm lateral to the right point. Measurements were performed on the carcass that insertion 2 should be identical with insertion 1, insertions 3 and 4 were moved 1 cm off insertion 1 in the cranial or caudal direction and insertions 5 and 6 were moved by 1 rib from insertion 1 in the cranial or caudal direction respectively. Classification was held by FOM instrument, for further comparison also by ZP method. For the above classifications following regression equations were used. For: - FOM y= 81,8909+0,2006*M+14,1911*ln S, kde M=MLLT depth, S =backfat thickness, - ZP y= 76,6722--1,0485*M+0,00794*M2--0,002884*S2+9,0151*ln (M/S), kde M = MLLT depth, S= backfat thickness. Calculation and comparison of the results was performed by statistical program SAS Propriety Software Release 6.04, differences were tested by analysis of variance. Based on the results we can say that a given hypothesis was confirmed. Also, in the realization of slaughter pigs in SEUROP system can be stated that - by invasive technique FOM - precise LMP determination of the carcass is a function of the need for precise determination of the puncture site of operator, - accuracy of the backfat thickness as well as LMP estimate is affected by repeated punctures, - more reliably is measured the backfat thickness with repeated injection than the muscle depth due to its possible deformation, - inaccuracy of repeated measurements (repeatability) will not significantly affect the carcass classification into classes at the slaughterhouse; any errors will occur to the detriment of the supplier, - the injection shift 1 rib cranially respectively caudally affect the overall carcass classification more than shift the injection 1 cm medially or laterally away from the spine, - in the case of an unsuccessful measurement the best is to repeat the puncture or the second puncture shift 1 cm caudal or repeat puncture between the 2nd and the 3rd thoracic vertebra 1 cm towards the spine, - non-invasive technique ZP, compared to FOM, underestimates the LMP estimate by about 1,4%.
|
|
Analysis of coffee sales in selected hotels in Prague
Veverka, Libor ; Kopecká, Lenka (advisor) ; Svoboda, Roman (referee)
In this thesis the sale of coffee in selected hotels in Prague will be analysed, based on information obtained in the drink menus of these hotels.
The theoretical part consists of three main parts, namely The market and the market mechanism, Classification by type of prepared coffee drinks and The classification of hotels into five classes.
The first part, called The market and the market mechanism, explains market and its functioning, perfect and imperfect competition between companies and, in the end also imperfections of the market. The second part of Classification by types of prepared coffee drinks discusses the ingredients and the proper preparation of a wide range of coffee drinks. The third and last part of the theoretical part called The classification of hotels into five classes, points out the basic limit points for dividing hotels into each of these categories.
In the second part, which is called The actual work representations of hotels in the Czech Republic, in Prague are examined and compared. There is also a list of the selected hotels in Prague, which are taken into account in the analysis, comparison and subsequent assessment of results.
In the conclusion, the difference in prices of offered coffee drinks in randomly selected hotels in Prague is assessed from two points of view. The first is examining the differences in prices between classes of hotels and the second one is examining differences in prices inside the particular classes.
|
|
Classification of dense shaped refractory products - Part 4: Special products
Kotora, J. ; Korsa, B. ; Krupičková, A. ; Kunc, J. ; Kutzendorfer, J. ; Lvová, H. ; Muller, P. ; Novotný, M. ; Stoklasa, Jaroslav ; Ševčík, F. ; Tomšů, F.
|
|
Insulating refractory products - Part 2: Classification of products (ISO 2245:1990 modified)
Kotora, J. ; Korsa, B. ; Krupičková, A. ; Kunc, J. ; Kutzendorfer, J. ; Lvová, H. ; Muller, P. ; Novotný, M. ; Stoklasa, Jaroslav ; Ševčík, F. ; Tomšů, F.
|
|
Classification of dense shaped refractory products - Part 1: Alumina-silica products
Kotora, J. ; Korsa, B. ; Krupičková, A. ; Kunc, J. ; Kutzendorfer, J. ; Lvová, H. ; Muller, P. ; Novotný, M. ; Stoklasa, Jaroslav ; Ševčík, F. ; Tomšů, F.
|
guest ::
