Software systems are becoming increasingly complex, with developers frequentlyutilizing numerous dependencies. In this landscape, accurate tracking and understanding of dependencies within JavaScript and TypeScript codebases are vital formaintaining software security and quality. However, there exists a gap in how existing vulnerability scanning tools, such as Dependabot, convey information aboutthe usage of these dependencies. This study addresses the problem of providing amore comprehensive dependency usage overview, a topic critical to aiding developers in securing their software systems. To bridge this gap, a custom pipeline wasimplemented to supplement Dependabot, extracting the dependencies identified asvulnerable and providing specific information about their usage within a repository.The results highlight the pros and cons of this approach, showing an improvement inthe understanding of dependency usage. The effort opens a pathway towards moresecure software systems.

Software companies spend a lot of resources on debugging, a process where previous solutions can help in solving current problems. The bug tickets, containing this information, are often time-consuming to read. To minimize the time spent on debugging and to make sure that the knowledge from prior solutions is kept in the company, an evaluation was made to see if summaries could make this process more efficient. Abstractive and extractive summarization models were tested for this task and fine-tuning of the bert-extractive-summarizer was performed. The model-generated summaries were compared in terms of perceived quality, speed, similarity to each other, and summarization length. The average description summary contained part of the description needed and the found solution was either well documented or did not answer the problem at all. The fine-tuned extractive model and the abstractive model BART provided good conditions for generating summaries containing all the information needed. / Vid mjukvaruutveckling går mycket resurser åt till felsökning, en process där tidigare lösningar kan hjälpa till att lösa aktuella problem. Det är ofta tidskrävande att läsa felrapporterna som innehåller denna information. För att minimera tiden som läggs på felsökning och säkerställa att kunskap från tidigare lösningar bevaras inom företaget, utvärderades om sammanfattningar skulle kunna effektivisera detta. Abstrakta och extraherande sammanfattningsmodeller testades för uppgiften och en finjustering av bert-extractive- summarizer gjordes. De genererade sammanfattningarna jämfördes i avseende på upplevd kvalitet, genereringshastighet, likhet mellan varandra och sammanfattningslängd. Den genomsnittliga sammanfattningen innehöll delar av den viktigaste informationen och den föreslagna lösningen var antingen väldokumenterad eller besvarade inte problembeskrivningen alls. Den finjusterade BERT och den abstrakta modellen BART visade goda förutsättningar för att generera sammanfattningar innehållande all den viktigaste informationen.

One of the state-of-the-art highlights of deep learning in the past ten years is the introduction of generative adversarial networks (GANs), which had achieved great success in their ability to generate images comparable to real photos with minimum human intervention. These networks can generalise to a multitude of desired outputs, especially in image-to-image problems and image syntheses. This thesis proposes a computer graphics pipeline for 3D rendering by utilising generative adversarial networks (GANs). This thesis is motivated by regression models and convolutional neural networks (ConvNets) such as U-Net architectures, which can be directed to generate realistic global illumination effects, by using a semi-supervised GANs model (Pix2pix) that is comprised of PatchGAN and conditional GAN which is then accompanied by a U-Net structure. Pix2pix had been chosen for this thesis for its ability for training as well as the quality of the output images. It is also different from other forms of GANs by utilising colour labels, which enables further control and consistency of the geometries that comprises the output image. The series of experiments were carried out with laboratory created image sets, to pursue the possibility of which deep learning and generative adversarial networks can lend a hand to enhance the pipeline and speed up the 3D rendering process. First, ConvNet is applied in combination with Support Vector Machine (SVM) in order to pair 3D objects with their corresponding shadows, which can be applied in Augmenter Reality (AR) scenarios. Second, a GANs approach is presented to generate shadows for non-shadowed 3D models, which can also be beneficial in AR scenarios. Third, the possibility of generating high quality renders of image sequences from low polygon density 3D models using GANs. Finally, the possibility to enhance visual coherence of the output image sequences of GAN by utilising multi-colour labels. The results of the adopted GANs model were able to generate realistic outputs comparable to the lab generated 3D rendered ground-truth and control group output images with plausible scores on PSNR and SSIM similarity index metrices.

No description available.

No description available.

No description available.

No description available.

No description available.

[pt] Na exploração de campos offshore, é frequente a necessidade transportar óleo e gás por dutos de produção ou de transferência que percorrem grandes distâncias no leito submarino. Em relação aos gasodutos, podem ocorrer a formação de condensado ao longo desses, o que afeta drasticamente a capacidade de entrega e a modalidade operacional, sendo a remoção do condensado realizada por pigs. Além disso, devido a existência de condições extremas como baixas temperaturas e altas pressões, pode ocorrer a formação de plug de hidrato nos gasodutos. Nesse caso, são previstas operações especiais para a remoção do plug de hidrato, onde, durante o procedimento, pode ser gerado condensado. Dessa forma, é importante que essas operações sejam simuladas durante a fase de projeto e de operação para avaliar a efetividade dos procedimentos e os valores das variáveis de processo de forma a garantir a segurança operacional do sistema. O objetivo deste estudo é investigar numericamente o processo de deslocamento de pigs e de plugs de hidrato ao longo de tubulações, na presença de condensado. A formação de condensado é obtida através de um modelo de equilíbrio de fases, que utiliza a equação de Peng-Robinson para o cálculo das propriedades termodinâmicas para ambas as fases. O escoamento bifásico é modelado como unidimensional. A solução das equações de conservação de massa, quantidade de movimento linear e energia, acopladas ao balanço de forças para prever o deslocamento do pig/plug são resolvidas utilizando o método numérico de diferenças finitas. A modelagem do escoamento e do modelo termodinâmico, englobando o equilíbrio de fases e as propriedades termodinâmicas, foram validadas com soluções analíticas e dados da literatura. Estudos de casos de deslocamento de pig e de plug de hidrato na presença de condensado foram realizados e os resultados obtidos foram bastante satisfatórios, permitindo concluir que os modelos desenvolvidos podem ser utilizados para a análise e previsão das operações de passagem de pig e de remoção de plugs de hidrato na presença de condensado. / [en] In offshore oilfield exploration, gas is often transported through long-distance transfer pipelines or production pipelines on the seabed. Along the pipeline, condensate may be formed, which dramatically affect the delivery capacity and the operational mode, requiring condensate removal employing pigs. Further, due to the presence of extreme conditions encountered in these pipelines, such as low temperatures and high pressures, hydrate plug can also be formed inside the gas pipelines. In this case, special procedures are foreseen to remove the hydrate plug, during which condensate may be generated. Thus, it is essential that these operations should be simulated throughout the design and operation stages to evaluate the efficacy of these procedures and the process variable values in order to guarantee the system s operational safety. The purpose of this study is to investigate numerically the process of displacement of pigs and hydrate plugs along pipelines, in the presence of condensate. The condensate formation is obtained through a phase behavior model (FLASH), which employs the Peng-Robinson equation to calculate the thermodynamic properties for both phases. Two-phase flow is modeled as one-dimensional. The conservation equations of mass, linear momentum and energy, coupled with the force balance to predict the displacement of the pig/plug are solved, using the numerical method of finite differences. The flow and thermodynamic models were validated with analytical solutions and literature data. The validation of the thermodynamic model included the phase equilibrium and thermodynamic properties. Case studies of displacement of pig and hydrate plug in the presence of condensate were performed and the results obtained were very satisfactory, allowing to conclude that the developed models can be used for the analysis and prediction of the pigging operations and removal of hydrate plugs in the presence of condensate.

Yes / Research with prisoners’ families is limited in the context of learning difficulties/disabilities (LD) and autism spectrum. Life-story interviews with mothers reveal an extended period of emotional and practical care labour, as the continuous engagement with their son’s education and experiences of physical and emotional abuse are explored. Prior to their son’s incarceration, mothers spoke of stigma and barriers to support throughout their childrearing, as well as limited or absent preventative/positive care practices. Subsequently prisons and locked wards seem to feature as a progression. Mothers have experienced abuse; physical and/or emotional, as well as lives that convey accounts of failure. Not their failure, but that of the systems. A care ethics model of disability assists an analysis of the narratives where care-less spaces are identified. Interrelated experiences merging emotional responses to extended mothering, the external forces of disabilism and destructive systems, lead to proposing a rehumanising of care practices within for example, education and the criminal justice system. / The Leverhume Trust (RF-2016-613\8)