22,114 research outputs found
Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets.
Re-sampling methods to solve class imbalance problems have shown to improve classification accuracy by mitigating the bias introduced by differences in class size. However, it is possible that a model which uses a specific re-sampling technique prior to Artificial neural networks (ANN) training may not be suitable for aid in classifying varied datasets from the healthcare industry. Five healthcare-related datasets were used across three re-sampling conditions: under-sampling, over-sampling and combi-sampling. Within each condition, different algorithmic approaches were applied to the dataset and the results were statistically analysed for a significant difference in ANN performance. The combi-sampling condition showed that four out of the five datasets did not show significant consistency for the optimal re-sampling technique between the f1-score and Area Under the Receiver Operating Characteristic Curve performance evaluation methods. Contrarily, the over-sampling and under-sampling condition showed all five datasets put forward the same optimal algorithmic approach across performance evaluation methods. Furthermore, the optimal combi-sampling technique (under-, over-sampling and convergence point), were found to be consistent across evaluation measures in only two of the five datasets. This study exemplifies how discrete ANN performances on datasets from the same industry can occur in two ways: how the same re-sampling technique can generate varying ANN performance on different datasets, and how different re-sampling techniques can generate varying ANN performance on the same dataset
Modelling uncertainties for measurements of the H → γγ Channel with the ATLAS Detector at the LHC
The Higgs boson to diphoton (H → γγ) branching ratio is only 0.227 %, but this
final state has yielded some of the most precise measurements of the particle. As
measurements of the Higgs boson become increasingly precise, greater import is
placed on the factors that constitute the uncertainty. Reducing the effects of these
uncertainties requires an understanding of their causes. The research presented
in this thesis aims to illuminate how uncertainties on simulation modelling are
determined and proffers novel techniques in deriving them.
The upgrade of the FastCaloSim tool is described, used for simulating events in
the ATLAS calorimeter at a rate far exceeding the nominal detector simulation,
Geant4. The integration of a method that allows the toolbox to emulate the
accordion geometry of the liquid argon calorimeters is detailed. This tool allows
for the production of larger samples while using significantly fewer computing
resources.
A measurement of the total Higgs boson production cross-section multiplied
by the diphoton branching ratio (σ × Bγγ) is presented, where this value was
determined to be (σ × Bγγ)obs = 127 ± 7 (stat.) ± 7 (syst.) fb, within agreement
with the Standard Model prediction. The signal and background shape modelling
is described, and the contribution of the background modelling uncertainty to the
total uncertainty ranges from 18–2.4 %, depending on the Higgs boson production
mechanism.
A method for estimating the number of events in a Monte Carlo background
sample required to model the shape is detailed. It was found that the size of
the nominal γγ background events sample required a multiplicative increase by
a factor of 3.60 to adequately model the background with a confidence level of
68 %, or a factor of 7.20 for a confidence level of 95 %. Based on this estimate,
0.5 billion additional simulated events were produced, substantially reducing the
background modelling uncertainty.
A technique is detailed for emulating the effects of Monte Carlo event generator
differences using multivariate reweighting. The technique is used to estimate the
event generator uncertainty on the signal modelling of tHqb events, improving the
reliability of estimating the tHqb production cross-section. Then this multivariate
reweighting technique is used to estimate the generator modelling uncertainties
on background V γγ samples for the first time. The estimated uncertainties were
found to be covered by the currently assumed background modelling uncertainty
Exploring the effects of spinal cord stimulation for freezing of gait in parkinsonian patients
Dopaminergic replacement therapies (e.g. levodopa) provide limited to no response for axial motor symptoms including gait dysfunction and freezing of gait (FOG) in Parkinson’s disease (PD) and Richardson’s syndrome progressive supranuclear palsy (PSP-RS) patients. Dopaminergic-resistant FOG may be a sensorimotor processing issue that does not involve basal ganglia (nigrostriatal) impairment. Recent studies suggest that spinal cord stimulation (SCS) has positive yet variable effects for dopaminergic-resistant gait and FOG in parkinsonian patients. Further studies investigating the mechanism of SCS, optimal stimulation parameters, and longevity of effects for alleviating FOG are warranted. The hypothesis of the research described in this thesis is that mid-thoracic, dorsal SCS effectively reduces FOG by modulating the sensory processing system in gait and may have a dopaminergic effect in individuals with FOG. The primary objective was to understand the relationship between FOG reduction, improvements in upper limb visual-motor performance, modulation of cortical activity and striatal dopaminergic innervation in 7 PD participants. FOG reduction was associated with changes in upper limb reaction time, speed and accuracy measured using robotic target reaching choice tasks. Modulation of resting-state, sensorimotor cortical activity, recorded using electroencephalography, was significantly associated with FOG reduction while participants were OFF-levodopa. Thus, SCS may alleviate FOG by modulating cortical activity associated with motor planning and sensory perception. Changes to striatal dopaminergic innervation, measured using a dopamine transporter marker, were associated with visual-motor performance improvements. Axial and appendicular motor features may be mediated by non-dopaminergic and dopaminergic pathways, respectively. The secondary objective was to demonstrate the short- and long-term effects of SCS for alleviating dopaminergic-resistant FOG and gait dysfunction in 5 PD and 3 PSP-RS participants without back/leg pain. SCS programming was individualized based on which setting best improved gait and/or FOG responses per participant using objective gait analysis. Significant improvements in stride velocity, step length and reduced FOG frequency were observed in all PD participants with up to 3-years of SCS. Similar gait and FOG improvements were observed in all PSP-RS participants up to 6-months. SCS is a promising therapeutic option for parkinsonian patients with FOG by possibly influencing cortical and subcortical structures involved in locomotion physiology
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Reliable Decision-Making with Imprecise Models
The rapid growth in the deployment of autonomous systems across various sectors has generated considerable interest in how these systems can operate reliably in large, stochastic, and unstructured environments. Despite recent advances in artificial intelligence and machine learning, it is challenging to assure that autonomous systems will operate reliably in the open world. One of the causes of unreliable behavior is the impreciseness of the model used for decision-making. Due to the practical challenges in data collection and precise model specification, autonomous systems often operate based on models that do not represent all the details in the environment. Even if the system has access to a comprehensive decision-making model that accounts for all the details in the environment and all possible scenarios the agent may encounter, it may be intractable to solve this complex model optimally. Consequently, this complex, high fidelity model may be simplified to accelerate planning, introducing imprecision. Reasoning with such imprecise models affects the reliability of autonomous systems. A system\u27s actions may sometimes produce unexpected, undesirable consequences, which are often identified after deployment. How can we design autonomous systems that can operate reliably in the presence of uncertainty and model imprecision?
This dissertation presents solutions to address three classes of model imprecision in a Markov decision process, along with an analysis of the conditions under which bounded-performance can be guaranteed. First, an adaptive outcome selection approach is introduced to devise risk-aware reduced models of the environment that efficiently balance the trade-off between model simplicity and fidelity, to accelerate planning in resource-constrained settings. Second, a framework that extends stochastic shortest path framework to problems with imperfect information about the goal state during planning is introduced, along with two solution approaches to solve this problem. Finally, two complementary solution approaches are presented to minimize the negative side effects of agent actions. The techniques presented in this dissertation enable an autonomous system to detect and mitigate undesirable behavior, without redesigning the model entirely
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Quantitative Character and the Composite Account of Phenomenal Content
I advance an account of quantitative character, a species of phenomenal character that presents as an intensity (cf. a quality) and includes experience dimensions such as loudness, pain intensity, and visual pop-out. I employ psychological and neuroscientific evidence to demonstrate that quantitative characters are best explained by attentional processing, and hence that they do not represent external qualities. Nonetheless, the proposed account of quantitative character is conceived as a compliment to the reductive intentionalist strategy toward qualitative states; I argue that an account of perceptual experience that combines a tracking account of qualitative character with my functionalist proposal of quantitative character permits replies to some notoriously difficult problems for tracking representationalism without sacrificing its chief virtues
The applied psychology of addictive orientations : studies in a 12-step treatment context.
The clinical data for the studies was collected at The PROMIS Recovery Centre, a Minnesota Model treatmentc entre for addictions,w hich encouragesth e membership and use of the 12 step Anonymous Fellowships, and is abstinence based. The area of addiction is contextualised in a review chapter which focuses on research relating to the phenomenon of cross addiction. A study examining the concept of "addictive orientations" in male and female addicts is described, which develops a study conductedb y StephensonM, aggi, Lefever, & Morojele (1995). This presents study found a four factor solution which appeared to be subdivisions of the previously found Hedonism and Nurturance factors. Self orientated nurturance (both food dimensions, shopping and caffeine), Other orientated nurturance (both compulsive helping dimensions and work), Sensation seeking hedonism (Drugs, prescription drugs, nicotine and marginally alcohol), and Power related hedonism (Both relationship dimensions, sex and gambling. This concept of "addictive orientations" is further explored in a non-clinical population, where again a four factor solution was found, very similar to that in the clinical population. This was thought to indicate that in terms of addictive orientation a pattern already exists in this non-clinical population and that consideration should be given to why this is the case. These orientations are examined in terms of gender differences. It is suggested that the differences between genders reflect power-related role relationships between the sexes. In order to further elaborate the significance and meaning behind these orientations, the next two chapters look at the contribution of personality variables and how addictive orientations relate to psychiatric symptomatology. Personality variables were differentially, and to a considerable extent predictably involved with the four factors for both males and females.Conscientiousness as positively associated with "Other orientated Nurturance" and negatively associated with "Sensation seeking hedonism" (particularly for men). Neuroticism had a particularly strong association with the "Self orientated Nurturance" factor in the female population. More than twice the symptomatology variance was explained by the factor scores for females than it was for males. The most important factorial predictors for psychiatric symptomatology were the "Power related hedonism" factor for males, and "Self oriented nurturance" for females. The results are discussed from theoretical and treatment perspectives
Differences in external match load metrics between professional and semi-professional football players
This study aimed to investigate the differences in external match load between professional and semi-professional footballers, and also aimed to investigate whether periods of fixture congestion throughout the season had an effect on the external match load of players at either the professional or semi-professional level. This study consisted of data from 51 football players, 21 professional and 30 semi-professional footballers, playing in the 2019/2020 football season. The data collected was obtained via MEMS (microelectromechanical systems) devices, which measured the players’ total distance, high-speed distance, accelerations, decelerations and player load. Once the external match load data was quantified, a comparison between playing levels took place using a univariate ANOVA. A two-way repeated measures ANOVA was used to examine if significant differences existed in external match load variables across player performance level (2 levels) and time of the season (3 levels) during periods of time when teams experienced fixture congestion. This study found that professional players travelled significantly greater distances in a 90 minute match (10.93 ± 2.46 vs 9.02 ± 1.56 km respectively; P<0.001). No differences in high-speed distance were observed between playing level (P=0.70), whereas semiprofessional players recorded significantly greater player load value than the professional players (88.6 ± 12.2 vs 68.8 ± 18.9% respectively; P<0.001). Periods of fixture congestion were not found to significantly affect any of the match load variables at either playing level despite the time of the season. In conclusion, neither playing level was found to exhibit a superior level of external match load. The other major finding of this thesis was that fixture congestion did not affect match load. Further research is required to quantify and compare the external match load at the non-elite professional and semi-professional level of football, as these levels of football are largely ignored in this field of literature
Modular peptide binders – development of a predictive technology as alternative for reagent antibodies
Current biomedical research and diagnostics critically depend on detection agents for specific recognition and quantification of protein molecules. Monoclonal antibodies have been used for this purpose over decades and facilitated numerous biological and biomedical investigations. Recently, however, it has become apparent that many commercial reagent antibodies lack specificity or do not recognize their target at all. Thus, synthetic alternatives are needed whose complex designs are facilitated by multidisciplinary approaches incorporating experimental protein engineering with computational modeling. Here, we review the status of such an engineering endeavor based on the modular armadillo repeat protein scaffold and discuss challenges in its implementation
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Effect of Prior Plastic Strain on the High Temperature Creep Deformation and Damage Response of Type 316H Stainless Steel
Creep damage in ductile alloys is associated with creep deformation, crack growth and starts with the nucleation and growth of cavities. Under sustained high temperature and stress conditions, growing cavities can start to coalesce leading to microcracking and ultimate failure of a component. This mechanism can limit the lifetime of power plant components operating at high temperature. Many engineering components enter service in a cold-worked or prestrained condition as a result of manufacturing processes such as bending, forging, welding etc. Such pre-conditioning alters the creep resistance of the material significantly. Its effect on the creep deformation properties of a structure during service, and creep damage response can be advantageous for some materials but disadvantageous for others. Hence it is crucial to understand the effects of prior plastic strain when assessing the lifetime and safety of power plant components, for example in the context of nuclear power generation. The research set out in this thesis aims to examine the effect of prior plastic strain on subsequent creep deformation behaviour and development of damage in AISI Type 316H austenitic stainless steel, a material widely used in the fleet of Advanced Gas Cooled reactors operated by EDF Energy in the UK.
A novel cylindrical hourglass-shaped test specimen was designed for the research where a constant applied load provided a variation in uniaxial stress and associated creep strain rate along the hourglass gauge length. A further innovation in this PhD work involved exploiting the potential of 3D digital image correlation (3D-DIC) for measuring spatially resolved creep deformation along the hourglass gauge section over long duration creep tests at a high temperature of 550â—¦C. The scope of testing included load-controlled creep tests carried out on 5 samples where 0, 4, 8, 12 and 16% of prior tensile plastic strain was introduced at room temperature. The prestraining was carried out on cylindrical samples before the hourglass shape was machined, ensuring a uniform level of prior plastic strain was present along the gauge section prior to creep experiments. It was found that prior plastic strain increased the creep resistance of the as-received material. Increasing plastic strain decreased the creep strain rate and creep ductility. On the other hand, it resulted in an increase in time to failure.
After creep failure at the maximum stress location, small-angle neutron scattering (SANS) was utilised to investigate changes in creep cavitational damage as a function of applied stress, level of creep strain and prior plastic strain at room temperature. Two sets of experiments were performed using the D11 instrument at the ILL reactor source (France) and the SANS2D instrument at the ISIS spallation source (UK). Very similar scattering results were obtained from the two instruments. Furthermore, SANS data from the instruments were analysed using two independent analysis routes; a maximum entropy method (MAXE) and a Monte Carlo algorithm (McSAS). Since SANS is an indirect method for measuring creep cavitation, the microstructure of the specimens was also investigated using qualitative scanning electron microscopy (SEM) in order to interpret and verify the SANS cavitation observations. The SANS investigations revealed a strong correlation between the volume fraction and number density of creep cavities with applied stress and creep strain. Furthermore, an increasing number density of small creep cavities as a function of prior plastic strain was observed and verified by qualitative SEM studies. This is new evidence that prior plastic strain, induced at room temperature, introduces specific cavitational damage in Type 316H stainless steel. The macroscopic damage calculation based on the stress modified ductility exhaustion model revealed that the majority of damage for the series of prestrained specimens is caused by plastic hole growth as a consequence of inducing prior plastic strain rather than due to creep related diffusion processes
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