Prompt engineering is the craft of designing prompts in order to get desired answers from language models such as ChatGPT. This thesis investigates how ChatGPT, specifically GPT-4, can be used to detect plagiarism in simple programming exercises. We used a dataset containing seven different original solutions for programming tasks. Every programming task also contained solutions that were plagiarizing the original as well as solutions that did not plagiarize the original. After testing various different prompts on a subset of the dataset, four different prompts were tested on the majority of the dataset. Three of the prompts produced unreliable results to the point that simply guessing whether or not the task solutions were plagiarized would have frequently been more accurate. The fourth prompt was more accurate although still not accurate enough for it to be recommended to use ChatGPT in order to identify plagiarism. / Promptkonstruktion (prompt engineering) är konsten att skapa instruktioner som ger bästa möjliga svar från språkmodeller (language models) såsom ChatGPT. Denna avhandling undersöker hur ChatGPT kan användas för att upptäcka plagiat i enkla programmeringsuppgifter. Vi använde ett dataset som innehåller sju olika originallösningar på enkla programmeringsuppgifter. Varje programmeringsuppgift har plagierade lösningar som löser samma uppgift och icke-plagierade lösningar som också löser samma uppgift. Efter att ha testat olika instruktioner med ChatGPT på en liten delmängd av datasetet, testades fyra olika instruktioner på majoriteten av datasetet. Tre av instruktionerna gav opålitliga resultat till den grad att det ofta skulle gett ett bättre resultat att gissa om lösningarna var plagierade eller inte. Den fjärde instruktionen gav bättre resultat, men fortfarande inte tillräckligt bra för att rekommendera att använda ChatGPT för att identifiera plagiat.

Das Prompt Gamma-Ray Timing (PGT) ist eine vielversprechende Methode für die in vivo Reichweite-Verifikation in der Protonentherapie. Dabei wird mit unkollimierten Szintillationsdetektoren die Zeit-Verteilung prompter Gammastrahlung, in der die Protonenreichweite enthalten ist, gemessen. In dieser Arbeit wurden PGT-Spektren einer Bestrahlung eines Plastikphantoms mit verschiedenen Dicken an Luftkavitäten analysiert. Neben der Optimierung der Datenverarbeitung wurden Methoden für die Selektion statistischer Parameter implementiert und die resultierenden linearen Modelle mit denen der bisher verwendeten Parameter verglichen. Zusätzlich wurde der Einfluss der Spotakkumulation und die Energieabhängigkeit der Modelle untersucht. Nachdem die Datenverarbeitung optimiert werden konnte, zeigte der Vergleich der Modelle eine deutlich bessere Vorhersage der neu entwickelten Modelle (R2 > 0;5) im Vergleich zu den bisher verwendeten Modellen (R2 < 0;1), wobei eine weitere Verbesserung durch die Akkumulation von Spots erreicht werden konnte (R2 > 0;9). Weiterhin zeigte die Parameterselektion eine deutlich bessere Vorhersagekraft der energiespezifischen (RMSE < 1;8 mm) gegenüber den energieunabhängigen Modellen (RMSE > 3 mm). Die gewonnenen Erkenntnisse leisten einen wesentlichen Beitrag zur klinischen Implementierung der PGT-Methode. / Prompt Gamma-Ray Timing (PGT) is a promising method for in vivo range verification in proton therapy. The distribution of prompt gamma radiation, in which the proton range is encoded, is measured in a time-resolved manner with uncollimated scintillation detectors. In this work, PGT spectra acquired during irradiation of a plastic phantom with air cavities of different thicknesses were analyzed. In addition to the optimization of the data processing, methods for parameter selection were implemented and the resulting linear models were compared with those of previously used parameters. In addition, the influence of a spot accumulation and the energy dependency of the models were examined. After the data preprocessing could be optimized, the newly developed models showed a strongly improved predictive power (R2 > 0;5) compared to the previously used models (R2 < 0;1) and a further improvement could be achieved by the accumulation of spots (R2 > 0;9). In addition the parameter selection showed better predictive power of the energy-specific models (RMSE < 1;8 mm) compared to the energy-independent models (RMSE > 3 mm). The knowledge gained can contribute to the clinical implementation of the PGT method.

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Current research indicates that the inability to spontaneously communicate needs or wants may result in the acquisition of unconventional forms of requesting such as aggression and tantrums. This in turn limits the amount of access that students with autism have to neurotypical peers and social environments. The purpose of this study was to investigate the effect of using a stimulus control transfer procedure on the acquisition of spontaneous mands. Four school-aged children with autism, two boys and two girls, participated in the study. A multiple baseline design across participants was utilized to demonstrate a functional relation between the stimulus control transfer procedures and the rate of spontaneous mands. Measurement variables included the frequency of spontaneous versus multiply-controlled mands during discrete trial training on a variety of verbal operants. Effectiveness of the intervention was analyzed through visual analysis and the magnitude of effect was assessed through effect size. Visual analysis indicated that three of the four participants learned to spontaneously mand for items out of view and demonstrated generalization across targets, staff and environments. The effect size for three participants were large (d = 1.94; d = 2.2; and d = 1.4), whereas the outcome of intervention for one participant (d = 0.98) indicated moderate effect. The overall (d = 1.15) outcome demonstrated a large effect of the intervention on the rate of mands. Based on the results of this study, it is recommended that early and intensive behavior intervention programs for children with autism incorporate this type of procedure for socially significant outcomes.

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<p>This thesis describes the development of a method to measure <em>in vivo</em> gadolinium (Gd) content by prompt gamma neutron activation analysis (PGNAA). PGNAA is a quantitative measurement technique that is completely non-invasive. Gadolinium has the highest thermal neutron capture cross section of all the stable elements. Gadolinium-based contrast agents are widely used in magnetic resonance imaging (MRI). The primary intention of this work is to quantify <em>in vivo</em> Gd retention to investigate the potential toxicity of these agents. This study involves the optimization of the McMaster University ²³⁸Pu/Be PGNAA facility for Gd measurements. Monte Carlo simulations were performed in parallel with the experimental work using MCNP version 5. Excellent agreement has been demonstrated between the Monte Carlo model of the system and the experimental measurements (both sensitivity and dosimetry). The initial study on the sensitivity of Gd demonstrated the feasibility of the measurement system. The Monte Carlo dosimetry simulations and experimental survey measurements demonstrated consistently that the radiation exposures for a single measurement were quite low, with an effective dose rate of 1.1 µSv/hr for a leg muscle measurement, 74 µSv/hr for a kidney measurement, and 48 µSv/hr for a liver measurement. The initial studies confirmed the Gd measurement feasibility which ultimately led to an <em>in vivo</em> pilot study on 10 healthy volunteers. The pilot study was successful with 9 out of 10 volunteers having measureable Gd in muscle above the <em>in vivo</em> detection limit of 0.58 ppm within 1 hour of administration, and the remaining participant had detectable Gd 196 minutes post administration. The concentrations measured ranged from 6.9 to 56 uncertainties different from zero. The system has been validated in humans and can now be used in future studies of short or long-term retention of Gd after contrast administration in at risk populations, such as those with reduced kidney function, patients with multiple exposures over the treatment period, and patients who are prescribed higher dosages. In addition, experiments and simulations were extended to another high neutron absorbing element, samarium (Sm).</p> / Doctor of Philosophy (PhD)

This project sought to evaluate the effects of video prompting in combination with backwards chaining to increase proficiency of tying shoe-laces using a changing criterion design. Two children, one diagnosed with Autism Spectrum Disorder (ASD) and one neurotypical were invited to participate in this study. Following baseline, shoe-tying prompt videos and backwards chaining were used to teach shoe-tying. Video prompting plus backwards chaining increased the typically developing participant’s proficiency with performing a larger percentage of steps of the targeted skill independently following intervention. However, the participant with ASD was unable to meet criterion and the study was terminated for him due to challenging behavior. These results indicate that the combination of point-of-view video prompts along with backwards chaining can be effective in teaching children to tie their shoelaces. These results also indicate that children with ASD may need additional supports with this intervention to reach acquisition criterion. Parents reported satisfaction both with the procedures undertaken and with the outcomes of the intervention. / Applied Behavioral Analysis

Comparative anatomical studies of diverse plant species are vital for the understanding of changes in gene functions such as those involved in solute transport and hormone signaling in plant roots. The state-of-the-art method for confocal image analysis called PlantSeg utilized U-Net for cell wall segmentation. U-Net is a neural network model that requires training with a large amount of manually labeled confocal images and lacks generalizability. In this research, we test a foundation model called the Segment Anything Model (SAM) to evaluate its zero-shot learning capability and whether prompt engineering can reduce the effort and time consumed in dataset annotation, facilitating a semi-automated training process. Our proposed method improved the detection rate of cells and reduced the error rate as compared to state-of-the-art segmentation tools. We also estimated the IoU scores between the proposed method and PlantSeg to reveal the trade-off between accuracy and detection rate for different quality of data. By addressing the challenges specific to confocal images, our approach offers a robust solution for studying plant structure. Our findings demonstrated the efficiency of SAM in confocal image segmentation, showcasing its adaptability and performance as compared to existing tools. Overall, our research highlights the potential of foundation models like SAM in specialized domains and underscores the importance of tailored approaches for achieving accurate semantic segmentation in confocal imaging. / Master of Science / Studying different plant species' anatomy is crucial for understanding how genes work, especially those related to moving substances and signaling in plant roots. Scientists often use advanced techniques like confocal microscopy to examine plant tissues in detail. Traditional techniques like PlantSeg in automatically segmenting plant cells require a lot of computational resources and manual effort in preparing the dataset and training the model. In this study, we develop a novel technique using Segment-Anything-Model that could learn to identify cells without needing as much training data. We found that SAM performed better than other methods, detecting cells more accurately and making fewer mistakes. By comparing SAM with PlantSeg, we could see how well they worked with different types of images. Our results show that SAM is a reliable option for studying plant structures using confocal imaging. This research highlights the importance of using tailored approaches like SAM to get accurate results from complex images, offering a promising solution for plant scientists.

No / Trade credit terms offer firms contractual solutions to informational asymmetries between buyers and sellers. The credit period permits buyers to reduce uncertainty concerning product quality prior to payment, while the seller can reduce uncertainty concerning buyer payment intentions by prescribing payment before/on delivery or through two¿part payment terms and other mechanisms. Variation in trade credit terms also offers firms price discriminating opportunities. This study, drawing on the responses of 700 large firms in the US, UK and Australia, explores trade credit terms through the twin objectives of reducing information asymmetries and discriminatory pricing. Support is found for both theories.