Modern systems produce a great amount of information and cues from which human operators must take action. On one hand, these complex systems can place a high demand on an operator's cognitive load, potentially overwhelming them and causing poor performance. On the other hand, some systems utilize extensive automation to accommodate their complexity; this can cause an operator to become complacent and inattentive, which again leads to deteriorated performance (Wilson, Russell, 2003a; Wilson, Russell, 2003b). An ideal human-machine interface would be one that optimizes the functional state of the operator, preventing overload while not permitting complacency, thus resulting in improved system performance. An operator's functional state (OFS) is the momentary ability of an operator to meet task demands with their cognitive resources. A high OFS indicates that an operator is vigilant and aware, with ample cognitive resources to achieve satisfactory performance. A low OFS, however, indicates a non-optimal cognitive load, either too much or too little, resulting in sub-par system performance (Wilson, Russell, 1999). With the ability to measure and detect changes in OFS in real-time, a closed-loop system between the operator and machine could optimize OFS through the dynamic allocation of tasks. For instance, if the system detects the operator is in cognitive overload, it can automate certain tasks allowing them to better focus on salient information. Conversely, if the system detects under-vigilance, it can allocate tasks back to the manual control of the operator. In essence, this system operates to "dynamically match task demands to [an] operator's momentary cognitive state", thereby achieving optimal OFS (Wilson, Russell, 2007). This concept is termed adaptive aiding and has been the subject of much research, with recent emphasis on accurately assessing OFS in real-time. OFS is commonly measured indirectly, like using overt performance metrics on tasks; if performance is declining, a low OFS is assumed. Another indirect measure is the subjective estimate of mental workload, where an operator narrates his/her perceived functional state while performing tasks (Wilson, Russell, 2007). Unfortunately, indirect measures of OFS are often infeasible in operational settings; performance metrics are difficult to construct for highly-automated complex systems, and subjective workload estimates are often inaccurate and intrusive (Wilson, Russell, 2007; Prinzel et al., 2000; Smith et al., 2001). OFS can be more directly measured via psychophysiological signals such as electroencephalogram (EEG) and electrooculography (EOG). Current research has demonstrated these signals' ability to respond to changing cognitive load and to measure OFS (Wilson, Fisher, 1991; Wilson, Fisher, 1995; Gevins et al., 1997; Gevins et al., 1998; Byrne, Parasuraman, 1996). Moreover, psychophysiological signals are continuously available and can be obtained in a non-intrusive manner, pre-requisite for their use in operational environments. The objective of this study is to advance schemes which detect change in OFS by monitoring psychophysiological signals in real-time. Reviews on similar methods can be found in, e.g., Wilson and Russell (2003a) and Wilson and Russell (2007). Many of these methods employ pattern recognition to classify mental workload into one of several discrete categories. For instance, given an experiment with easy, medium and hard tasks, and assuming the tasks induce varying degrees of mental workload on a subject, these methods classify which task is being performed for each epoch of psychophysiological data. The most common classifiers are artificial neural networks (ANN) and multivariate statistical techniques such as stepwise discriminant analysis (SWDA). ANNs have proved especially effective at classifying OFS as they account for the non-linear and higher order relationships often present in EEG/EOG data; they routinely achieve classification accuracy greater than 80%. However, the discrete output of these classification schemes is not conducive to real-time change detection. They accurately classify OFS, but they do not indicate when OFS has changed; the change points remain ambiguous and left to subjective interpretation. Thus, the present study introduces several online algorithms which objectively determine change in OFS via real-time psychophysiological signals. The following chapters describe the dataset evaluated, discuss the statistical properties of psychophysiological signals, and detail various algorithms which utilize these signals to detect real-time changes in OFS. The results of the algorithms are presented along with a discussion. Finally, the study is concluded with a comparison of each method and recommendations for future application.

Complex industrial processes are represented by data that are well known to be multiscaled due to the variety of events that occur in a process at different time and frequency localizations. Wavelet based multiscale analysis approaches provide an excellent means to examine these events. However, the scope of the existing wavelet based methods in the fields of statistical applications, such as process monitoring and defect identification are still limited. Recent literature contains several wavelet decomposition based multiscale process monitoring approaches including many real life process monitoring applications, such as tool-life monitoring, bearing defect monitoring, and monitoring of ultra-precision processes such as chemical mechanical planarization (CMP) in wafer fabrication. However, all of the above mentioned wavelet based methodologies are offline and depend on the visual observations of the wavelet coefficients and details. The offline analysis paradigm was imposed by the high computation needs of the multiscale analysis, whereas the visual observation based approach was necessitated by the lack of statistical means to identify undesirable events. One of the most recent multiscale application, that deals with detecting delamination in CMP, addressed the need for online analysis by developing a moving window based approach to reduce computation time. This research presents 1) development of a fully online multiscale analysis approach where the speed of wavelet based analysis of the data matches the rate of data generation, 2) development of a statistical tool based on Sequential Probability Ratio Test (SPRT) to detect events of interest, and 3) development of an approach to display the analysis results through real time graphs for ease of process supervisory decision making. The developed methodologies are programmed using MATLAB 6.5 and implemented on several data sets obtained from metal and oxide CMP of wafer fabrication. The results and analysis are presented.

This research addressed the design and implementation of a polynomial-complexity deadlock avoidance controller for a flexible manufacturing cell modeled using Colored Petri Nets. The cell model is robust to changes in the part types to be manufactured in the system and is automatically generated using the interaction of the resources in the cell and the technological capabilities of the machines. The model also captures dynamic routing flexibility options. The framework introduced separates the cell model from the control logic allowing the system designer to implement and test various control algorithms using the same cell model. The controller adopts the neighborhood deadlock avoidance policy to resolve deadlocks and control the resource allocation decisions within the system. The evaluation of the performance of systems controlled by not maximally permissive algorithms is important in determining the applicability of the control algorithms. There are many polynomial time deadlock avoidance algorithms proposed for the control of general resource allocation systems. However, the permissiveness of these algorithms is not quantified and the applicability of these algorithms in terms of effective resource utilization remains unanswered. The performance of automated manufacturing cells controlled using the neighborhood deadlock avoidance policy is benchmarked by comparing its performance with other control policies.

The increasing application of cryptographic algorithms to ensure secure communications across virtual networks has led to an ever-growing demand for high performance hardware implementations of the encryption/decryption methods. The inevitable inclusion of the cryptographic algorithms in network communications has led to the development of several encryption standards, one of the prominent ones among which, is the Rijndael, the Advanced Encryption Standard. Rijndael was chosen as the Advanced Encryption Standard (AES) by the National Institute of Standard and Technology (NIST), in October 2000, as a replacement for the Data Encryption Standard (DES). This thesis presents the architecture for the VLSI implementation of the Rijndael, the Advanced Encryption Standard algorithm. Rijndael is an iterated, symmetric block cipher with a variable key length and block length. The block length is fixed at 128 bits by the AES standard [4]. The key length can be designed for 128,192 or 256 bits. The VLSI implementation, presented in this thesis, is based on a feed-back logic and allows a key length specification of 128-bits. The present architecture is implemented in the Electronic Code Book(ECB) mode of operation. The proposed architecture is further optimized for area through resource-sharing between the encryption and decryption modules. The architecture includes a Key-Scheduler module for the forward-key and reverse-key scheduling during encryption and decryption respectively. The subkeys, required for each round of the Rijndael algorithm, are generated in real-time by the Key-Scheduler module by expanding the initial secret key. The proposed architecture is designed using the Custom-Design Layout methodology with the Cadence Virtuoso tools and tested using the Avanti Hspice and the Nanosim CAD tools. Successful implementation of the algorithm using iterativearchitecture resulted in a throughput of 232 Mbits/sec on a 0.35[mu] CMOS technology. Using 0.35[mu] CMOS technology, implementation of the algorithm using pipelining architecture resulted in a throughput of 1.83 Gbits/sec. The performance of this implementation is compared with similar architectures reported in the literature.

Ziel dieser Arbeit ist es ein besseres Verständinis der molekularen Prozesse der Melanomentstehung und Tumorprogression zu gewinnen. Hierfür wurde ein Tiermodell transgener Medakas (Oryzias latipes) verwendet, welche als stabiles Transgen das Konstrukt mitf::xmrk besitzen. Diese Fische entwickelten Pigmentzelltumore, welche für eine Microarrayanalyse herangezogen wurden. Aus diesem Microarraydatensatz wurden 11 Gene ausgewählt, welche in dieser Arbeit näher untersucht wurden. Beobachtungen haben ergeben, dass sich bei transgenen Medakas, welche Xmrk exprimieren, verschiedene pigmentierte Hauttumore entwickeln. Diese Tumore wurden je nach ihrem verschiedenen Histiotyp klassifiziert und untersucht. Um einen Eindruck zu gewinnen, wie Xmrk die Transkription verschiedener Gene, welche in der Krebsentstehung und –progression eine wichtige Rolle spielen, beeinflusst, wurden pigmentierte Hauttumore transgener Medakas, so wie zu Vergleichszwecken hyperpigmentierte Haut transgener Medakas und Lymphome und gesunde Organe von Wildtyp-Medakas, untersucht. Mit Hilfe von Real-time-PCR’s wurden die folgenden Gene untersucht: G6PC, GAMT, GM2A, MAPK3, NID1, SLC24A5, SPP1, PDIA4, RASL11B, TACC2 und ZFAND5. Dabei konnte festgestellt werden, dass die Expression der Gene GM2A, MAPK3, NID1, PDIA4, RASL11B, SLC24A5 und ZFAND5 von Xmrk beeinflusst wird, während dies für die Gene G6PC, GAMT, SPP1 und TACC2 nicht zutrifft. Im Vergleich zu gesunder Haut werden GM2A, MAPK3, PDIA4, RASL11B, SLC24A5 und ZFAND5 in Tumoren höher exprimiert. Die Gene G6PC, GAMT, NID1, SPP1 und TACC2 werden dagegen verglichen mit gesunder Haut unverändert oder niedriger exprimiert. Die Bedeutung der erhöhten Genexpression lässt sich in vielen Fällen zurzeit nur theoretisch erfassen. Eine höhere Expression von SLC24A5 beispielsweise lässt vermuten, dass ein Zusammenhang zwischen der Melaninproduktion und der Zellproliferation besteht. Die Überexpression von GM2A weist dagegen auf eine Rolle von GM2A als Tumormarker hin. Dahingegen scheint die erniedrigte Expression von GAMT und G6PC Auskunft über den veränderten Stoffwechsel in Tumoren zu geben. Um diese Ergebnisse zu bestätigen und zu entschlüsseln wie genau Xmrk die Expression der getesteten Gene beeinflusst, sind allerdings noch weitere funktionelle Studien nötig. Generell kommt man zu dem Schluss, dass die Genexpression sich in jedem Tumor unterscheidet. Daher scheint jeder Tumor seinen eigenen Evolutionsweg zu beschreiten. / Target of this work is to get a better understanding in melanomagenesis and tumorprogression. Therefore a model of transgenic medakas (Oryzias latipes) was used, wich had the construct mitf::Xmrk as a stable, integrated transgen. Those fishes developed pigmentcelltumors that, wich where used in a microarrayanalysis. Of the results of this microarray 11 genes where chosen and analysed in this study. Those transgenic medakas which got xmrk injected, but without a tumorsuppresorgen, developed various pigmented kinds of skin cancer. Those tumors were analysed equally to their histiotyps. To get an idea, how Xmrk effects the transcription of several genes, which play an important role in tumor development and progression, pigmented skin cancer of transgenic medakas and for comparison, hyper pigmented skin of transgenic medakas and also lymphoma and healthy organs where tested. The following genes where tested by real-time-PCR: G6PC, GAMT, GM2A, MAPK3, NID1, SLC24A5, SPP1, PDIA4, RASL11B, TACC2 and ZFAND5. It was noticed that the expression of the genes GM2A, MAPK3, NID1, PDIA4, RASL11B, SLC24A5 und ZFAND5 gets modified by Xmrk. In contrast the genes G6PC, GAMT, SPP1 and TACC2 didn't. In comparison to healthy skin GM2A, MAPK3, PDIA4, RASL11B, SLC24A5 and ZFAND5 got higher expressed in tumors. Indeed the expression level of the genes G6PC, GAMT, NID1, SPP1 and TACC2 is the same or even lower than in healthy skin. The meaning of the higher gen expression can currently just be theoretically conceived. The higher expression of SLC24A5 for example leads to guess that there is a link between the production of melanin and cell proliferation. The overexpression of GM2A shows that GM2A plays maybe a role as an tumor marker. However the lower expression of G6PC and GAMT gets references about the metabolism in cancer. To fix this results and get an better understanding how Xmrk affects the expression of this genes, additional funktional studies are necessary. The result is that gene expression differs in each tumor. A common conclusion is not possible. It appears that each tumor goes its own evolutionary way.

Un des freins à la commercialisation de masse de la pile à combustible et notamment de la technologie à membrane échangeuse de proton vient de sa faible durée de vie due à la difficulté de contrôler le système sous certaines conditions. Pour pallier à ce problème, l’élaboration d’un modèle mathématique précis de la pile à combustible à membrane échangeuse de protons permettant d’observer les variables internes et l'état de la pile à combustible au cours de son fonctionnement permettrait le développement de la stratégie de contrôle du système.Cette thèse propose d’élaborer un modèle dynamique multi-physique complet pour la pile à combustible à membrane échangeuse de protons. Le modèle proposé couvre les domaines multi-physiques pour les caractéristiques électriques, fluidiques et thermiques. Dans ces deux derniers domaines, les phénomènes transitoires sont notamment pris en compte dans le modèle proposé, tels que les comportements dynamiques de la teneur en eau de la membrane de la pile et la température. Par conséquent, ce modèle peut être utilisé pour analyser les effets de couplage des variables dynamiques entre différents domaines physiques.Grace à ce modèle ainsi définit, un second modèle multi-physique bidimensionnel plus détaillé est également présenté. Le modèle proposé couvre les domaines électriques et fluidiques avec une approche de modélisation 2-D innovante. Les distributions spatiales de quantité physique dans le domaine électrique peuvent ainsi être obtenues. Par conséquent, ce modèle 2-D PEMFC peut être utilisé pour étudier les influences des paramètres de modélisation sur la prédiction de performance multidimensionnelle locale. Une étude expérimentale est effectuée pour valider le modèle 2-D proposé avec une pile commerciale PEMFC Ballard NEXA de 1,2 kW.Dans un second chapitre, une analyse des phénomènes dynamiques est réalisée en fonction du modèle dynamique multidisciplinaire développé en s’appuyant sur la méthode RGA (gain relatif) pour diverses variables d'entrée de contrôle, afin d'analyser quantitativement les effets de couplage dans différents domaines physiques. L’étude s’intéresse entre autre aux interactions de la teneur en eau et de la température de la membrane. L'analyse de couplage présentée dans cette thèse peut aider les ingénieurs à concevoir et à optimiser les stratégies de contrôle des piles à combustible, en particulier pour la gestion de l'eau et de la chaleur dans les systèmes de piles à combustible.Une deuxième analyse portant sur la sensibilité aux paramètres de l'étude est effectuée sur la base du modèle multidisciplinaire bidimensionnel développé. Ces résultats d'analyse de sensibilité globale fournissent des informations utiles pour la compréhension de la dégradation, le réglage des paramètres et la simplification du modèle des piles à combustible.Dans un troisième temps, le modèle proposé se décline dans un algorithme de résolution mathématique en temps réel basé sur un algorithme de matrice tri diagonal efficace (TDMA). Les résultats expérimentaux démontrent les possibilités pratiques du modèle 2-D proposé pour le contrôle en temps réel avancé des systèmes de pile à combustible avec un temps de calcul de la boucle de contrôle de l'ordre de la milliseconde. Le temps d'exécution du modèle peut être quadruplé par rapport aux algorithme séquentiels présent dans la littérature; garantissant ainsi des décisions et des actions de contrôle rapide. / Before mass commercialization of proton exchange membrane fuel cell, the research on the design of appropriate control strategies and auxiliaries need to be done for achieving proton exchange membrane fuel cell (PEMFC) optimal working modes. An accurate mathematical PEMFC model can be used to observe the internal variables and state of fuel cell during its operation, and could further greatly help the system control strategy development.A comprehensive multi-physical dynamic model for PEMFC is developed in chapter I. The proposed model covers multi-physical domains for electric, fluidic and thermal features. Particularly, the transient phenomena in both fluidic and thermal domain are simultaneously considered in the proposed model, such as the dynamic behaviors of fuel cell membrane water content and temperature. Therefore, this model can be used to analyze the coupling effects of dynamic variables among different physical domains.Based on the developed multi-physical PEMFC model, a full two-dimensional multi-physical model is further presented. The proposed model covers electrical and fluidic domains with an innovative 2-D modeling approach. In order to accurately describe the characteristics of reactant gas convection in the channels and diffusion through the gas diffusion layer, the gas pressure drop in the serpentine pipeline is comprehensively analyzed by fully taking the geometric form of flow field into consideration, such as the reactant gas pressure drop due to the pipeline sharp and U-bends. Based on the developed 2-D fluidic domain modeling results, spatial physical quantity distributions in electrical domain can be further obtained. Therefore, this 2-D PEMFC model can be use to study the influences of modeling parameters on the local multi-dimensional performance prediction. The simulation and experimental test are then performed to validate the proposed 2-D model with a commercial Ballard NEXA 1.2 kW PEMFC stack.In chapter II, analyses of dynamic phenomena step responses are conducted based on the developed multi-physical dynamic PEMFC model using the relative gain array (RGA) method for various control input variables, in order to quantitatively analyze the coupling effects in different physical domains, such as the interactions of membrane water content and temperature. Based on the calculated values of relative gain array, the proposed model can be considered as a fuel cell MIMO system, which could be divided into two independent control sub-systems by minimizing parameter coupling effects between each other. Due to the closely coupled parameters in the proposed first control sub-system, a decoupling control method is recommended to achieve optimized control results. The coupling analysis presented in this thesis can help engineers to design and optimize the fuel cell control strategies, especially for the water and thermal management in fuel cell systems.

Le but du rendu stylisé est de produire un rendud'une scène 3D dans le style visuel particuliervoulu par un artiste.Cela nécessite de reproduire automatiquementsur ordinateur certaines caractéristiquesd'illustrations traditionnelles: par exemple,la façon dont un artiste représente les ombres et lalumière, les contours des objets, ou bien les coupsde pinceau qui ont servi à créer une peinture.Les problématiques du rendu stylisé sont pertinentesdans des domaines comme la réalisation de films d'animation 3Dou le jeu vidéo, où les studios cherchent de plus en plus à se démarquerpar des styles visuels originaux.Dans cette thèse, nous explorons des techniques destylisation qui peuvent s'intégrer dans des pipelinesde rendu temps-réel existants, et nous proposons deux contributions.La première est un outil de création de modèles d'illuminationstylisés pour des objets 3D.La conception de ces modèles est complexe et coûteuse en temps,car ils doivent produire un résultat cohérentsous une multitude d'angles de vue et d'éclairages.Nous proposons une méthode qui facilite la créationde modèles d'illumination pour le rendu stylisé,en les décomposant en sous-modèles plus simples à manipuler.Notre seconde contribution est un pipeline de rendude scènes 3D dans un style peinture,qui utilise une combinaison de bruits procéduraux 3Det de filtrage en espace écran.Des techniques de filtrage d'image ont déjà été proposéespour styliser des images ou des vidéos:le but de ce travail est d'utiliser ces filtres pourstyliser des scènes 3D tout en gardant la cohérence du mouvement.Cependant, directement appliquer un filtreen espace écran produit des défauts visuels au niveau dessilhouettes des objets.Nous proposons une méthode qui permet d'assurer la cohérence du mouvement,en guidant les filtres d'images avec des informations sur la géométrie extraites de G-buffers, et qui élimine les défauts aux silhouettes. / The goal of stylized rendering is to render 3D scenes in the visual style intended by an artist.This often entails reproducing, with some degree of automation,the visual features typically found in 2D illustrationsthat constitute the "style" of an artist.Examples of these features include the depiction of light and shade,the representation of the contours of objects,or the strokes on a canvas that make a painting.This field is relevant today in domains such as computer-generated animation orvideo games, where studios seek to differentiate themselveswith styles that deviate from photorealism.In this thesis, we explore stylization techniques that can be easilyinserted into existing real-time rendering pipelines, and propose two novel techniques in this domain.Our first contribution is a workflow that aims to facilitatethe design of complex stylized shading models for 3D objects.Designing a stylized shading model that follows artistic constraintsand stays consistent under a variety of lightingconditions and viewpoints is a difficult and time-consuming process.Specialized shading models intended for stylization existbut are still limited in the range of appearances and behaviors they can reproduce.We propose a way to build and experiment with complex shading modelsby combining several simple shading behaviors using a layered approach,which allows a more intuitive and efficient exploration of the design space of shading models.In our second contribution, we present a pipeline to render 3D scenes in painterly styles,simulating the appearance of brush strokes,using a combination of procedural noise andlocal image filtering in screen-space.Image filtering techniques can achieve a wide range of stylized effects on 2D pictures and video:our goal is to use those existing filtering techniques to stylize 3D scenes,in a way that is coherent with the underlying animation or camera movement.This is not a trivial process, as naive approaches to filtering in screen-spacecan introduce visual inconsistencies around the silhouette of objects.The proposed method ensures motion coherence by guiding filters with informationfrom G-buffers, and ensures a coherent stylization of silhouettes in a generic way.

The scientific studies associated with material engineering and device miniaturization are the core concepts for future technology innovation. The exploring and tailoring of material properties of amorphous magnetic microwires, recently, have revealed remarkable high sensitive magnetic field sensitivity down to the picoTesla regime at room temperature. This superior magnetometer is highly promising for active sensing and real-time monitoring building block for modern industrial devices and healthcare applications. The low-field, high sensitivity regime of the GMI response over a wide frequency range (1 MHz - 1 GHz) in the Co-rich melt-extracted microwires was optimized through novel Joule annealing methods (single- and multi-step current annealing techniques). Optimization of current value through multi-step current annealing (MSA) from 20 mA to 100 mA for 10 minutes is the key to improving the GMI ratio, and its field sensitivity up to 760% and 925%/Oe at f ≈ 20 MHz. The respective GMI ratio and field sensitivity are 1.75 times and 17.92 times higher than those of the as-prepared counterpart. The employment of the MSA technique successfully enhances the surface domain structures of the Co-rich microwires. This alternative tailoring method is suitable for improving the GMI sensitivity for a small field detection. The high sensitive response of the GMI to a weak magnetic field is highly promising for biomedical sensing applications. Real-time monitoring of position, motion, and rotation of a non-stationary object is crucial for product packaging, conveying, tracking, and safety compliance in industrial applications. The effectiveness of current sensing technology is limited by sensing distance and messy environments. A new class of high-frequency GMI-based sensor was designed and fabricated using the optimal Co-rich microwire. The impedance spectrum from the optimal sensing element showed a high GMI ratio and high field sensitivity response at low magnetic fields. The GMI sensor based longitudinal effect was found to be more sensitive than the commercially available Gaussmeters. The practical utility of the high sensitivity of the miniaturized sensor at weak magnetic fields for far-off distance monitoring of position, speed and gear rotating was demonstrated. This GMI-based sensor is highly promising for real-time position detection, oscillatory motion monitoring, and predictive failure of a rotating gear for industrial applications. Monitoring the rate of respiration and its pattern is crucial to assessing an individual’s health or progression of an illness, creating a pressing need for fast, reliable and cost-effective monitors. A new sensor based on a magnetic coil, which is made of Co-rich melt-extracted microwire for the detection of small magnetic fields was fabricated. The 3 mm diameter coil is wound from a Co-rich magnetic microwire. Unlike some typical solenoids, the MMC is sensitive to small magnetic fields due to a significant change in impedance attributed to the high-frequency giant magneto-impedance (GMI) effect. An application of the MMC sensor for the detection of a position-varying source of a small magnetic field (~0.01 – 10 Oe) in real-time bio-mechanical movement monitoring in human was demonstrated. This newly developed MMC magneto-LC resonance technology is highly promising for active respiratory motion monitoring, eye movement detection and other biomedical field sensing applications.

No description available.

The emergence of MNAzymes (Multi-component nucleic acid enzymes) provides a new approach for detection of target analytes in various applications. In this thesis, three novel MNAzyme-based methodologies were developed to expand the range of the applications of MNAzymes. MNAzymes can be coupled with DNA or RNA ligands called aptamers to generate an apta-MNAzyme system, which can be used for the detection of non-nucleic target analytes such as small molecules and proteins. Direct detection using apta-MNAzyme system is performed in a format, which was isothermal, fluorescent, rapid, and requires no protein enzymes. Apta-MNAzymes can be coupled with a signal amplification cascade to increase the sensitivity of the reaction. Another MNAzyme-based methodology termed truncated MNAzyme arm system was developed to discriminate the presence of a single base mismatch of two closely related sequences. The system employs a partzyme with a truncated sensor arm and a stabiliser oligonucleotide that binds adjacently to the truncated sensor arm to stabilise the active MNAzyme structure. Truncated MNAzyme real-time PCR system is capable of discriminating the presence of a single base mismatch in a target DNA with high specificity and sensitivity (down to approximately 10 gene copies). The generic nature of the system enables simultaneous detection of three SNP targets in a multiplex format. MNAzymes was also investigated with various strategies to discriminate DNA sequences that are either methylated or unmethylated. In this thesis, bisulphite-treated DNA samples present in as low as 0.032 % of methylated DNA in a background of unmethylated DNA were discriminated using MNAzyme real-time methylation specific PCR (MSP) system. Furthermore, the presence of 5-methylcytosines in a target sequence increases the melting temperature of the duplex DNA. This was exploited further to directly discriminate DNA methylation status of target sequences using the truncated MNAzyme arm system without the need for bisulphite modification. Findings in this thesis have broadened the scope of MNAzymes as versatile tools for many possible applications and flexible alternative to the current technologies.