Four proteins exhibiting different rates of denaturation or precipitation with increasing cooking temperature from 63 to 73°C for beef and 67 to 79°C for pork were selected for developing a ratio model and incorporating the results into a mathematical expression. Monoclonal antibodies (Mabs) against lactate dehydrogenase isozyme 5 (LDH-5), bovine serum albumin (BSA), porcine enolase, and bovine myoglobin were developed for use in a sandwich enzyme-linked immunosorbent assay (ELISA) to simultaneously investigate changes in protein concentration with incremental increases in temperature. Four groups of mice were immunized separately with commercially available or purified protein (LDH-5, BSA, enolase, or myoglobin). After reporting ample blood serum titers, spleen cells were harvested and fused with SP2 myeloma tumor cells using an electro fusion cell manipulator. Hybridoma containing wells were screened against their respective protein to isolate hybridomas secreting protein specific Mabs. Tissue culture flask produced Mabs were used initially in sandwich ELISA assay testing. Mabs were tested against ground beef and pork cooked to instantaneous endpoint temperatures (EPTs). A 6 g section removed from the geometric center of each sample was homogenized in phosphate buffer, centrifuged, and a 1 ml aliquot collected for analysis. Microtiter plates were coated with goat anti-mouse IgG antibody (2 mg/ml) to act as a capture antibody for the protein specific monoclonal antibody concentrated from cell culture supernatant. Serial diluted muscle (beef or pork) extract (10 ml) from each EPT was applied to a microtiter plate. A protein A/G purified polyclonal antibody (Pab) was applied, followed by a goat anti-rabbit IgG peroxidase conjugated antibody. Concentration was determined by comparison to a standard curve. After multiple cell fusions, 24, 29, 66, and 12 cell lines secreting protein specific Mabs against LDH-5, BSA, enolase, and myoglobin, respectively, were produced. Six Mabs against LDH-5 reported R2 values > 0.9 indicating high specificity and affinity for LDH-5. Sandwich ELISA assays development with Mabs against BSA, enolase, and myoglobin was not as successful. Mouse ascites produced Mabs against BSA, enolase, and myoglobin were also unsuccessful when used in a sandwich ELISA. However, preliminary data suggested a multiple antigen ratio model still remained a viable option.

Highly correlated electron materials are systems in which many new states of matter can emerge. A particular situation which favours the formation of exotic phases of the electron liquid in complex materials is that where a quantum critical point (QCP) is present in the phase diagram. Neighbouring regions in parameter space reveal unusual physical properties, described as non-Fermi liquid behaviour. One of the important problems in quantum criticality is to find out how the Fermi surface (FS) of a material evolves near a QCP. The traditional method for studying the FS of materials is the de Haas van Alphen effect (dHvA). A quantum critical end point (QCEP) has been reported in the highly correlated metal Sr₃Ru₂O₇, which is tuned using a magnetic field high enough to perform the dHvA experiment. It moreover features a new emergent phase in the vicinity of the QCEP, a nematic type of electron ordering. The subject of this thesis is the study of the FS of Sr₃Ru₂O₇ using the dHvA effect. Three aspects were explored. The first was the determination of the FS at fields both above and below that where the QCEP arises. The second was the search for quantum oscillations inside the nematic phase. The third was a reinvestigation of the behaviour of the quasiparticle effective masses near the FS. In collaboration with angle resolved photoemission spectroscopy experimentalists, a complete robust model for the FS of Sr₃Ru₂O₇ at zero fields was determined. Moreover, the new measurements of the quasiparticle masses revealed that no mass enhancements exist anywhere around the QCEP, in contradiction with previous specific heat data and measurements of the A coefficient of the power law of the resistivity. Finally, we report dHvA oscillations inside the nematic phase, and the temperature dependence of their amplitude suggests strongly that the carriers consist of Landau quasiparticles.

Typical surface preparation consists of exposure to cleaning chemical to remove contaminants followed by rinsing with ultra-pure water which is followed by drying. Large quantities of water, various chemicals, and energy are used during rinsing and drying processes. Currently there is no in-situ metrology available to determine the cleanliness of micro- and nano-structures as these processes are taking place. This is a major technology gap and leads to over use of resources and adversely affects the throughput.Surface preparation of patterned wafers by batch processing becomes a major challenge as semiconductor fabrication moves deeper in submicron technology nodes. Many fabs have already employed single wafer tools. The main roadblock for single-wafer tools is their lower throughput. This obstacle is eased by introduction of multi chamber tools. To reduce cycle time and resource utilization during rinse and dry processes without sacrificing surface cleanliness and throughput, in-situ metrology is developed and used to compare typical single wafer spinning tools with immersion tools for rinsing of patterned wafers. This novel metrology technology includes both hardware for an in-situ measurement and software for process data analysis. Successful incorporation of this metrology will eliminate dependency on external analysis techniques such as Inductively Coupled Mass Spectroscopy (ICPMS), Scanning Electron Microscope (SEM), and Tunneling Electron Microscope (TEM), and will lead to fast response time.In this study the electro-chemical residue sensor (ECRS) was incorporated in a lab scale single-wafer spinning and single- wafer immersion tool. The ECRS was used to monitor dynamics of rinsing of various cleans such as ammonium peroxide mixture (APM), hydrochloric peroxide mixture (HPM), and sulfuric peroxide mixture (SPM). It was observed that different cleaning chemicals impact the subsequent rinse not only through adsorption and desorption but also through surface charge. The results are analyzed by using a comprehensive process model which takes into account various transport mechanisms such as adsorption, desorption, diffusion, convection, and surface charge. This novel metrology can be used at very low concentration with very high accuracy. It is used to study the effect of the key process parameters such as flow rate, spin rate, temperature, and chemical concentration.

The use of solar cells for energy production has indeed a bright future. Reduction of cost for fabrication along with increased efficiency are key features for a market boom, both achieved as a result of increased knowledge of the technology. Especially the thin film solar cell technology with absorbers made of Cu(In,Ga)Se2 (CIGS) is promising since it has proven high power conversion efficiency in combination with a true potential for low cost fabrication. In this thesis different recipes for fabrication of the Cu(In,Ga)Se2 absorber layer have been studied. The deposition technique used has been co-evaporation from elemental sources. For all depositions the substrate has been heated to a constant temperature of 500 ºC in order for the growing absorber to form a chalcopyrite phase, necessary for the photovoltaic functionality. The selenium has been evaporated such to always be in excess during depositions whereas the metal ratio Cu/(In+Ga) has been varied according to different recipes but always to be less than one at the end of the process. In the work emphasis has been on the radiative properties of the CIGS film during growth. The substrate heater has been temperature controlled to maintain the constant set temperature of the substrate, regardless of varying emitted power caused by changing surface emissivity. Depending on the growth conditions the emissivity of the growing film is changing, leading to a readable variation in the electrical power to the substrate heater. Since the thermal radiation from the substrate during growth has been of central focus, this has been studied in detail. For this reason the substrate has been treated as an optical stack composed of glass/Mo/Cu(In,Ga)Se2/CuxSe which determine the thermally radiated power by its emissivity. An optical model has been adopted to simulate the emissivity of the stack. In order to use the model, the optical constants for Cu(In,Ga)Se2 and CuxSe have been derived for the wavelength interval 2 μm to 20 μm. The simulation of the emissivity of the stack during CIGS growth agreed well with what has been seen for actual growth. Features of the OP-signal could hereby be explained as a result of film thickness of Cu(In,Ga)Se2 and CuxSe respectively. This is an important knowledge for an efficient fabrication in large scale.

A Mandarin speech recognition system for addresses based on MFCC, hidden Markov model (HMM) and Viterbi algorithm is proposed in this thesis. HMM is a doubly stochastic process describing the ways of pronunciation by recording the state transitions according to the time-varing properties of the speech signal. In order to simplify the system design and reduce the computational cost, the mono-syllable structure information in Mandarin is used by incorporating both mono-syllable recognizor and HMM for our system. For the speaker-dependent case, Mandarin address inputting can be accomplished within 60 seconds and 98% correct identification rate can be achieved in the laboratory environment.

A Mandarin speech recognition system for addresses in Taiwan, based on end-point detection, MFCC and HMM, is proposed and implemented in this thesis. It includes both phrase and monosyllable recognition tasks. For the phrase recognition part, we select the initial candidates before the final recognition stage to tremendously reduce the computational time. On the other side, for the monosyllable recognition part, we further refine the recognition details to improve the correct rate under easily confused circumstances. The final system can achieve 85% correct identification rate, and the address recognition can be completed within 2 seconds in the laboratory environment for speaker-dependent case.

Australia has a crop research system with higher research intensity than exists internationally. Motivated to improve R&D policy in Canada, this dissertation focuses on the Australian End Point Royalty (EPR) system for wheat and addresses four principal questions: (1) How was the Australian system created and how does it work? (2) How do public, producer and private ownership of breeding programs affect the pricing of varieties? (3) How do EPR rates affect wheat variety adoption? (4) Finally, how would uniform EPR rates, similar to those used in France, affect variety selection, total production and revenue if used in the Australian market? In addressing the first question I use existing literature and interviews with prominent personnel in the Australian wheat breeding system, including management of InterGrain, AGT, DAFWA, GRDC and others. Interviews were conducted during field study in Australia in 2011. In addressing the second question I employ a horizontal location model to analyze three game theoretic scenarios of a two firm oligopoly market with private, public and producer owned-breeding companies. The results show public and producer ownership of one of the wheat breeding programs reduces price level relative to private only ownership. I derive a novel result showing that when competing with private firms who must price above marginal cost, the public firm should also price above marginal cost in order to maximize total industry surplus. In addressing the third question I develop and estimate an econometric wheat variety adoption model for Western Australia. I find EPR rates have a negative inelastic, statistically significant impact on the adoption of varieties. Finally, in addressing the last question, I use the econometric model to simulate the adoption of Australian wheat varieties, given a counterfactual of revenue neutral uniform EPR rates. The uniform EPR rates speed up both the adoption and dis-adoption of varieties, thereby increasing weighted average yield and total production. The value of the increase in value of production exceeds the revenue for breeders under varying EPR rates, suggesting uniform EPR system may be an attractive alternative to varying EPR rates.

Metamorphism is a technique that mutates the binary code using different obfuscations. It is difficult to write a new metamorphic malware and in general malware writers reuse old malware. To hide detection the malware writers change the obfuscations (syntax) more than the behavior (semantic) of such a new malware. On this assumption and motivation, this thesis presents a new framework named MARD for Metamorphic Malware Analysis and Real-Time Detection. We also introduce a new intermediate language named MAIL (Malware Analysis Intermediate Language). Each MAIL statement is assigned a pattern that can be used to annotate a control flow graph for pattern matching to analyse and detect metamorphic malware. MARD uses MAIL to achieve platform independence, automation and optimizations for metamorphic malware analysis and detection. As part of the new framework, to build a behavioral signature and detect metamorphic malware in real-time, we propose two novel techniques, named ACFG (Annotated Control Flow Graph) and SWOD-CFWeight (Sliding Window of Difference and Control Flow Weight). Unlike other techniques, ACFG provides a faster matching of CFGs, without compromising detection accuracy; it can handle malware with smaller CFGs, and contains more information and hence provides more accuracy than a CFG. SWOD-CFWeight mitigates and addresses key issues in current techniques, related to the change of the frequencies of opcodes, such as the use of different compilers, compiler optimizations, operating systems and obfuscations. The size of SWOD can change, which gives anti-malware tool developers the ability to select appropriate parameter values to further optimize malware detection. CFWeight captures the control flow semantics of a program to an extent that helps detect metamorphic malware in real-time. Experimental evaluation of the two proposed techniques, using an existing dataset, achieved detection rates in the range 94% - 99.6% and false positive rates in the range 0.93% - 12.44%. Compared to ACFG, SWOD-CFWeight significantly improves the detection time, and is suitable to be used where the time for malware detection is more important as in real-time (practical) anti-malware applications. / Graduate / 0984 / alam_shahid@yahoo.com

Fermentation processes play an integral role in the manufacture of pharmaceutical products. The Quality by Design initiative, combined with Process Analytical Technologies, aims to facilitate the consistent production of high quality products in the most efficient and economical way. The ability to estimate and control product quality from these processes is essential in achieving this aim. Large historical datasets are commonplace in the pharmaceutical industry and multivariate methods based on PCA and PLS have been successfully used in a wide range of applications to extract useful information from such datasets. This thesis has focused on the development and application of novel multivariate methods to the estimation and control of product quality from a number of processes. The document is divided into four main categories. Firstly, the related literature and inherent mathematical techniques are summarised. Following this, the three main technical areas of work are presented. The first of these relates to the development of a novel method for estimating the quality of products from a proprietary process using PCA. The ability to estimate product quality is useful for identifying production steps that are potentially problematic and also increases process efficiency by ensuring that any defective products are detected before they undergo any further processing. The proposed method is simple and robust and has been applied to two separate case studies, the results of which demonstrate the efficacy of the technique. The second area of work concentrates on the development of a novel method of identifying the operational phases of batch fermentation processes and is based on PCA and associated statistics. Knowledge of the operational phases of a process can be beneficial from a monitoring and control perspective and allows a process to be divided into phases that can be approximated by a linear model. The devised methodology is applied to two separate fermentation processes and results show the capability of the proposed method. The third area of work focuses on undertaking a performance evaluation of two multivariate algorithms, PLS and EPLS, in controlling the end-point product yield of fermentation processes. Control of end-point product quality is of crucial importance in many manufacturing industries, such as the pharmaceutical industry. Developing a controller based on historical and identification process data is attractive due to the simplicity of modelling and the increasing availability of process data. The methodology is applied to two case studies and performance evaluated. From both a prediction and control perspective, it is seen that EPLS outperforms PLS, which is important if modelling data is limited.

The effects of NaCl (1 and 2%), added-water (AW; 30 and 40%), milk protein hydrolysate (MPH; 1, 2 and 3%), and end-point cooking temperature (EPT; 71.1 and 76.7 C) were examined. Regardless of the formulation, all turkey-beef frankfurters contained less than 0.4% fat. As levels of NaCl in the formula increased, the frankfurters had lower (P< 0.05) penetration values (total energy and peak force) but higher shear stress and shear strain. In addition, higher salt levels resulted in lower cooking loss, moisture content, protein content, and darker frankfurters. Increasing AW level reduced (P<0.05) penetration values (total energy and peak force), shear stress, shear modulus, and hardness but increased cohesiveness. Higher levels of AW not only resulted in higher (P<0.05) moisture content but also resulted in higher cooking loss and purge loss. Higher AW products were lighter (P<0.05) in color and less red. Increasing the amount of MPH increased (P<0.05) shear stress and shear modulus but lowered shear strain. Higher MPH reduced cooking loss and produced (P<0.05) darker, more yellow, and less red frankfurters. Higher EPT increased (P<0.05) cooking loss, shear stress, and shear modulus but decreased penetration values (total energy and peak force), shear strain, and cohesiveness. Higher EPT produced lighter (P<0.05) colored frankfurters. There were some two and three-way independent variable interactions (P<0.05) for shear stress, shear strain, and cohesiveness. Of the four independent variables evaluated, AW and EPT most influenced textural properties. By using various combinations of these four independent variables, meat processors would have the ability to improve the quality characteristics of fat-free frankfurters. / Master of Science