Detection of pitting corrosion in steel using image processing

This paper presents an image processing based detection method for detecting pitting corrosion in steel structures. High Dynamic Range (HDR) imaging has been carried out in this regard to demonstrate the effectiveness of such relatively inexpensive techniques that are of immense benefit to Non – Destructive – Tesing (NDT) community. The pitting corrosion of a steel sample in marine environment is successfully detected in this paper using the proposed methodology. It is observed, that the proposed method has a definite potential to be applied to a wider range of applications.

Development of a novel probe integrated with a micro-structured impedance sensor for the detection of breast cancer

The work described in this thesis focuses on the development of an innovative bioimpedance device for the detection of breast cancer using electrical impedance as the detection method. The ability for clinicians to detect and treat cancerous lesions as early as possible results in improved patient outcomes and can reduce the severity of the treatment the patient has to undergo. Therefore, new technology and devices are continually required to improve the specificity and sensitivity of the accepted detection methods. The gold standard for breast cancer detection is digital x-ray mammography but it has some significant downsides associated with it. The development of an adjunct technology to aid in the detection of breast cancers could represent a significant patient and economic benefit. In this project silicon substrates were pattern with two gold microelectrodes that allowed electrical impedance measurements to be recorded from intact tissue structures. These probes were tested and characterised using a range of in vitro and ex vivo experiments. The end application of this novel sensor device was in a first-in-human clinical trial. The initial results of this study showed that the silicon impedance device was capable of differentiating between normal and abnormal (benign and cancerous) breast tissue. The mean separation between the two tissue types 4,340 Ω with p < 0.001. The cancer type and grade at the site of the probe recordings was confirmed histologically and correlated with the electrical impedance measurements to determine if the different subtypes of cancer could each be differentiated. The results presented in this thesis showed that the novel impedance device demonstrated excellent electrochemical recording potential; was biocompatible with the growth of cultured cell lines and was capable of differentiating between intact biological tissues. The results outlined in this thesis demonstrate the potential feasibility of using electrical impedance for the differentiation of biological tissue samples. The novelty of this thesis is in the development of a new method of tissue determination with an application in breast cancer detection.

Ex vivo culture of patient tissue and examination of gene delivery

Gene therapy has emerged as a realistic prospect for the treatment of cancer due to its potential for selective tumour cell targeting. The greatest challenge gene delivery vectors face is the ability to safely and efficiently deliver genes into target cells. The overall objectives of this thesis are to evaluate the efficacy of various gene delivery methods in a clinically relevant tumour model and to also investigate potential strategies for tumour selective delivery. We began with the development of a tumour slice model system using patient waste tissue. This model involves the use of fresh human tumour tissue, cut into thin slices and maintained ex vivo and is universally applicable to gene delivery methods, using a real-time luminescence detection method to assess gene delivery. The nature of the ex vivo culture system permitted examination of specific physiological variables, the influence of intratumoural factors and tissue specific effects on vector expression. Adenoviral vectors under the control of the human CXCR4 promoter demonstrated a 'tumour on' and 'normal off' expression profile when compared with the ubiquitously active CMV promoter when tested in patient tumour tissue. In addition, we developed an ex vivo system of changing oxygenation using the hypoxia inducer, cobalt, to mimic the transient hypoxic conditions found in solid tumours. We found that Adenoviral transgene expression was robust in the cycling hypoxic conditions relevant to solid tumours and re-oxygenation of chronically hypoxic tissue enhanced transgene expression. Finally, we demonstrated an AAV-based tumour targeting strategy using a tumour-selective promoter allowing for the efficient targeting of AAV vectors to cancer cells and the sparing of normal tissue in both murine metastatic liver tumours models and patient tissue. The thesis highlights the importance of indepth preclinical assessment of novel therapeutics and may serve as a platform for further testing of novel gene delivery approaches.

Synthesis, characterisation and applications of group IV nanocrystals

Group IV materials such as silicon nanocrystals (Si NCs) and carbon quantum dots (CQDs) have received great attention as new functional materials with unique physical/chemical properties that are not found in the bulk material. This thesis reports the synthesis and characterisation of both types of nanocrystal and their application as fluorescence probes for the detection of metal ions. In chapter 2, a simple method is described for the size controlled synthesis of Si NCs within inverse micelles having well defined core diameters ranging from 2 to 6 nm using inert atmospheric synthetic methods. In addition, ligands with different molecular structures were utilised to reduce inter-nanocrystal attraction forces and improve the stability of the NC dispersions in water and a variety of organic solvents. Regulation of the Si NCs size is achieved by variation of the surfactants and addition rates, resulting high quality NCs with standard deviations (σ = Δd/d) of less than 10 %. Large scale production of highly mondisperse Si NC was also successfully demonstrated. In chapter 3, a simple solution phase synthesis of size monodisperse carbon quantum dots (CQDs) using a room temperature microemulsion strategy is demonstrated. The CQDs are synthesized in reverse micelles via the reduction of carbon tetrachloride using a hydride reducing agent. CQDs may be functionalised with covalently attached alkyl or amine monolayers, rendering the CQDs dispersible in wide range of polar or non-polar solvents. Regulation of the CQDs size was achieved by utilizing hydride reducing agents of different strengths. The CQDs possess a high photoluminescence quantum yield in the visible region and exhibit excellent photostability. In chapter 4, a simple and rapid assay for detection of Fe3+ ions was developed, based on quenching of the strong blue-green Si NC photoluminescence. The detection method showed a high selectivity, with only Fe3+ resulting in strong quenching of the fluorescence signal. No quenching of the fluorescence signal was induced by Fe2+ ions, allowing for solution phase discrimination between the same ion in different charge states. The optimised sensor system showed a sensitive detection range from 25- 900 μM and a limit of detection of 20.8 μM

Phase estimation receiver for full-field detection: a novel receiver structure for electronic dispersion compensation of metropolitan area networks

The development of ultra high speed (~20 Gsamples/s) analogue to digital converters (ADCs), and the delayed deployment of 40 Gbit/s transmission due to the economic downturn, has stimulated the investigation of digital signal processing (DSP) techniques for compensation of optical transmission impairments. In the future, DSP will offer an entire suite of tools to compensate for optical impairments and facilitate the use of advanced modulation formats. Chromatic dispersion is a very significant impairment for high speed optical transmission. This thesis investigates a novel electronic method of dispersion compensation which allows for cost-effective accurate detection of the amplitude and phase of the optical field into the radio frequency domain. The first electronic dispersion compensation (EDC) schemes accessed only the amplitude information using square law detection and achieved an increase in transmission distances. This thesis presents a method by using a frequency sensitive filter to estimate the phase of the received optical field and, in conjunction with the amplitude information, the entire field can be digitised using ADCs. This allows DSP technologies to take the next step in optical communications without requiring complex coherent detection. This is of particular of interest in metropolitan area networks. The full-field receiver investigated requires only an additional asymmetrical Mach-Zehnder interferometer and balanced photodiode to achieve a 50% increase in EDC reach compared to amplitude only detection.

Automatic detection of learner-style for adaptive eLearning

The advent of modern wireless technologies has seen a shift in focus towards the design and development of educational systems for deployment through mobile devices. The use of mobile phones, tablets and Personal Digital Assistants (PDAs) is steadily growing across the educational sector as a whole. Mobile learning (mLearning) systems developed for deployment on such devices hold great significance for the future of education. However, mLearning systems must be built around the particular learner’s needs based on both their motivation to learn and subsequent learning outcomes. This thesis investigates how biometric technologies, in particular accelerometer and eye-tracking technologies, could effectively be employed within the development of mobile learning systems to facilitate the needs of individual learners. The creation of personalised learning environments must enable the achievement of improved learning outcomes for users, particularly at an individual level. Therefore consideration is given to individual learning-style differences within the electronic learning (eLearning) space. The overall area of eLearning is considered and areas such as biometric technology and educational psychology are explored for the development of personalised educational systems. This thesis explains the basis of the author’s hypotheses and presents the results of several studies carried out throughout the PhD research period. These results show that both accelerometer and eye-tracking technologies can be employed as an Human Computer Interaction (HCI) method in the detection of student learning-styles to facilitate the provision of automatically adapted eLearning spaces. Finally the author provides recommendations for developers in the creation of adaptive mobile learning systems through the employment of biometric technology as a user interaction tool within mLearning applications. Further research paths are identified and a roadmap for future of research in this area is defined.

Visualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiation

Ribosome profiling (ribo-seq) is a recently developed technique that provides genomewide information on protein synthesis (GWIPS) in vivo. The high resolution of ribo-seq is one of the exciting properties of this technique. In Chapter 2, I present a computational method that utilises the sub-codon precision and triplet periodicity of ribosome profiling data to detect transitions in the translated reading frame. Application of this method to ribosome profiling data generated for human HeLa cells allowed us to detect several human genes where the same genomic segment is translated in more than one reading frame. Since the initial publication of the ribosome profiling technique in 2009, there has been a proliferation of studies that have used the technique to explore various questions with respect to translation. A review of the many uses and adaptations of the technique is provided in Chapter 1. Indeed, owing to the increasing popularity of the technique and the growing number of published ribosome profiling datasets, we have developed GWIPS-viz (http://gwips.ucc.ie), a ribo-seq dedicated genome browser. Details on the development of the browser and its usage are provided in Chapter 3. One of the surprising findings of ribosome profiling of initiating ribosomes carried out in 3 independent studies, was the widespread use of non-AUG codons as translation initiation start sites in mammals. Although initiation at non-AUG codons in mammals has been documented for some time, the extent of non-AUG initiation reported by these ribo-seq studies was unexpected. In Chapter 4, I present an approach for estimating the strength of initiating codons based on the leaky scanning model of translation initiation. Application of this approach to ribo-seq data illustrates that initiation at non-AUG codons is inefficient compared to initiation at AUG codons. In addition, our approach provides a probability of initiation score for each start site that allows its strength of initiation to be evaluated.

Learning to drive: from hazard detection to hazard handling

Hazard perception has been found to correlate with crash involvement, and has thus been suggested as the most likely source of any skill gap between novice and experienced drivers. The most commonly used method for measuring hazard perception is to evaluate the perception-reaction time to filmed traffic events. It can be argued that this method lacks ecological validity and may be of limited value in predicting the actions drivers’ will take to hazards encountered. The first two studies of this thesis compare novice and experienced drivers’ performance on a hazard detection test, requiring discrete button press responses, with their behaviour in a more dynamic driving environment, requiring hazard handling ability. Results indicate that the hazard handling test is more successful at identifying experience-related differences in response time to hazards. Hazard detection test scores were strongly related to performance on a driver theory test, implying that traditional hazard perception tests may be focusing more on declarative knowledge of driving than on the procedural knowledge required to successfully avoid hazards while driving. One in five Irish drivers crash within a year of passing their driving test. This suggests that the current driver training system does not fully prepare drivers for the dangers they will encounter. Thus, the third and fourth studies in this thesis focus on the development of two simulator-based training regimes. In the third study participants receive intensive training on the molar elements of driving i.e. speed and distance evaluation. The fourth study focuses on training higher order situation awareness skills, including perception, comprehension and projection. Results indicate significant improvement in aspects of speed, distance and situation awareness across training days. However, neither training programme leads to significant improvements in hazard handling performance, highlighting the difficulties of applying learning to situations not previously encountered.

Application of signal detection methods to fisheries management

The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.

Highly sensitive surface enhanced Raman scattering (SERS) detection platforms formed by large area self-assembled Au nanorod arrays

This thesis explores a new method to fabricate SERS detection platforms formed by large area self-assembled Au nanorod arrays. For the fabrication of these new SERS platforms a new droplet deposition method for the self-assembly of Au nanorods was developed. The method, based in the controlled evaporation of organic suspensions of Au nanorods, was used for the fabrication of horizontal and vertical arrays of Au nanorods over large areas (100μm2). The fabricated nanorods arrays showed a high degree of order measured by SEM and optical microscopy over mm2 areas, but unfortunately they detached from the support when immersed in any analyte solutions. In order to improve adhesion of arrays to the support and clean off residual organic matter, we introduced an additional stamping process. The stamping process allows the immobilization of the arrays on different flexible and rigid substrates, whose feasibility as SERS platforms were tested satisfactory with the model molecule 4ABT. Following the feasibility study, the substrates were used for the detection of the food contaminant Crystal Violet and the drug analogue Benzocaine as examples of recognition of health menaces in real field applications.