The diethyl ether-extracted organic compounds of 155 samples of unifloral grade New Zealand kamahi and honeydew honeys, and New Zealand and Norwegian erica honeys, together with a series of active and inactive manuka honeys were analysed using combined gas chromatography/mass spectrometry. It was found that Kamahi honey is characterized by the presence of 2,6-dimethylocta-3,7-diene-2,6-diol, meliracemoic acid, and kamahines A-C and these compounds were typically present at average levels of 31, 14, and 73 mg/kg of honey, respectively. 2,6-Dimethylocta-3,7-diene-2,6-diol was isolated and the structure of this compound was defined using one- and two-dimensional NMR analyses. The only recognizably distinct peak present in the honeydew honey profile was indole acetic acid. In this honey, a relatively low to moderate level of indole acetic acid, ranging from 0.9 to 9.1 mg/kg honey was detected. In the New Zealand erica honey samples, ericinic acid, isoericinic acid isomers (average levels 363 and 34 mg/kg respectively), trans,cis and trans,trans-abscisic acid isomers (average levels 302 and 224 mg/kg respectively) and benzoic acid (average level 6950 mg/kg) were identified as floral marker compounds. Ericinic acid was isolated and the structure of this acid was defined using one-and two-dimensional NMR analyses. Low levels of ericinic and isoericinic acids (average levels of 1.1 and 0.32 mg/kg respectively) were detected in the Norwegian erica-rich honeys. The results presented here indicate that ericinic and isoericinic acids are likely to be universally present in erica honeys at levels which may range from as low as 1 mg/kg or less, as found in some Norwegian samples, to more than 100 mg/kg in some New Zealand samples. Two groups, namely a fingerprint pattern which characterized active manuka honeys, and a fingerprint pattern that characterized inactive manuka honeys were identified. Some substances contributing to the GCMS profile were found as marker compounds for the presence of unidentified substances responsible for the UMF activity. A statistically significant correlation was found between a small set of marker compounds (i.e. phenylacetic acid, 2-methoxyacetophenone, 2-methoxybenzoic, phenyllactic, octanedioic, cis-cinnamic, trans-cinnamic, nonanedioic, 4-methoxyphenyllactic and decanedioic acids and methyl syringate) and UMF activity of manuka honey. The best-fit marker compound regression equation (R = 0.92) was obtained for a set of pooled 30 moderate to high activity (UMF gt 14.1) samples. It was shown that the marker compound regression equation is capable of predicting the approximate UMF activity in both active and inactive manuka and kanuka honey samples. The leaf oil profiles of manuka (L. scoparium) plants that yielded active and inactive manuka honeys were characterized using an adaption of the micro-scale extraction and GC/FID or GC/MS, technique developed by Brophy et al. (1989). Six major groups of volatile (steam distillable) compounds (monoterpenes, sesquiterpene hydrocarbons, oxygenated sesquiterpenes [excluding eudesmols], eudesmols, triketones, and nor-triketones) and 3 groups of non-volatile or semi-volatile compounds (flavonoids, grandiflorone and nor-grandiflorone) were recognized in the leaf oil components. The active manuka honeys do not appear to be derived uniquely, or predominantly, from a single leaf oil chemotype.

This thesis deals with the detection of Uniform Marker Fields and the position of a camera in a space. The steps of the UMF detection, the Windows Phone 8 platform, DirectX working and the concept of augmented reality are described in the thesis. Implementation and design of the demo application together with the whole architecture of the project is described in the thesis. The result of the thesis is an application using the UMF detector and plotting a 3D object into a scene. Finally the application is tested and evaluated.

Tato práce stručně popisuje moderní metody v rozšířené realitě a dále se zabývá generováním a detekcí Uniform Marker Fields. Hlavním cílem je zlepšovat markery známé jako Unifrom Checker-Board Marker Fields. Toho je dosaženo několika vylepšeními návrhu těchto markerů. Mezi hlavní patří využití širší barevné palety, zaměření na podobnost s vybraným obrázkem a změna tvaru modulů. Výsledný algoritmus byl navržen ke generování právě takových markerů. Výstupem jsou esteticky vypadající markery, které umožňují spolehlivou detekci i v případě výrazného překrytí nebo za špatných světelných podmínek.

Tato práce popisuje systém pro sledování obrazovky počítače v reálném čase a určení pozice uživatelova pohledu na tuto obrazovku s využitím dat z eye-trackovacích brýlí a Uniform Marker Fields. Vytvořený systém lokalizuje obrazovku počítače ve snímcích z kamery umístěné na eye-trackeru snímající scénu před uživatelem. V této scéně je detekován marker zobrazený na monitoru počítače. Po jeho úspěšné detekci je marker skryt a ke sledování pozice obrazovky jsou dále využívány významné body detekované ve snímku z kamery ležící na obrazovce, případně z celého snímku. Pokud sledování významných bodů selže, marker je znovu zobrazen a systém je znovu inicializován pomocí detekovaného markeru. Aby byl marker pro uživatele co nejméně nápadný a obtěžující, jsou využity data z eye-trackeru k tomu, aby byl marker zobrazen co nejdále od oblasti uživatelova zájmu. Pro vyhodnocení výkonu a přesnosti vytvořeného systému a rušivosti markeru pro uživatele bylo provedeno několik experimentů a testování s uživateli.

Uncertainty analysis is crucial to any thorough analysis of an engineering system. Traditional uncertainty analysis can be a tedious task involving numerous steps that can be error prone if conducted by hand. If conducted with the aid of a computer, these tasks can be computationally expensive. In either case, the process is quite rigid. If a parameter of the system is modified or the system configuration is changed, the entire uncertainty analysis process must be conducted again giving more opportunities for calculation errors or computation time. Modular uncertainty analysis provides a method to overcome all these obstacles of traditional uncertainty analysis. The modular technique is well suited for computation by a computer which makes the process somewhat automatic after the initial setup and computation errors are reduced. The modular technique implements matrix operations to conduct the analysis. This in turns makes the process more efficient than traditional methods because computers are well suited for matrix operations. Since the modular technique implements matrix operations, the method is adaptable to system parameter or configuration modifications. The modular technique also lends itself to quickly calculating other uncertainty analysis parameters such as the uncertainty magnification factor, and the uncertainty percent contribution. This dissertation will focuson the modular technique, the extension of the technique in the form the uncertainty magnification factor and uncertainty percent contribution, and the application of the modular technique to different type of energy systems. The modular technique is applied to an internal combustion engine with a bottoming organic Rankine cycle system, a combined heat and power system, and a heating, ventilation, and air conditioning system. The results show that the modular technique is well suited to evaluate complex engineering systems. The modular technique is also shown to perform well when system parameters or configurations are modified.