10,060 research outputs found
Venn diagram showing overlap of differentially expressed genes following exposure to 2 and 4 mg/mL KCOH.
No full textVenn diagram showing overlap of differentially expressed genes following exposure to 2 and 4 mg/mL KCOH.</p
Metadata Representations for Queryable ML Model Zoos
No full textMachine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that are useful for reporting, auditing, reproducibility, and interpretability purposes. The metatada is currently not standardised; its expressivity is limited; and there is no interoperable way to store and query it. Consequently, model search, reuse, comparison, and composition are hindered. In this paper, we advocate for standardized ML model metadata representation and management, proposing a toolkit supported to help practitioners manage and query that metadata.Web Information SystemsHuman-Centred Artificial Intelligenc
A Manifesto of Nodalism
No full textThis paper proposes the notion of Nodalism as a means describing contemporary culture and of understanding my own creative practice in electronic music composition. It draws on theories and ideas from Kirby, Bauman, Bourriaud, Deleuze, Guatarri, and Gochenour, to demonstrate how networks of ideas or connectionist neural models of cognitive behaviour can be used to contextualize, understand and become a creative tool for the creation of contemporary electronic music
Optimizing ML Inference Queries Under Constraints
No full textThe proliferation of pre-trained ML models in public Web-based model zoos facilitates the engineering of ML pipelines to address complex inference queries over datasets and streams of unstructured content. Constructing optimal plan for a query is hard, especially when constraints (e.g. accuracy or execution time) must be taken into consideration, and the complexity of the inference query increases. To address this issue, we propose a method for optimizing ML inference queries that selects the most suitable ML models to use, as well as the order in which those models are executed. We formally define the constraint-based ML inference query optimization problem, formulate it as a Mixed Integer Programming (MIP) problem, and develop an optimizer that maximizes accuracy given constraints. This optimizer is capable of navigating a large search space to identify optimal query plans on various model zoos.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information SystemsHuman-Centred Artificial Intelligenc
Building a generalisable ML pipeline at ING
No full textAdvances in data science have caused an increase in the use of Artificial Intelligence (AI), specifically Machine Learning (ML), throughout various fields. Not only in research but in the industry as well, has ML been receiving increasing amounts of interest. Many companies rely on ML models to increase the efficiency of existing processes or offer new services and products. The industry, however, is facing several additional challenges compared to the academic context. One of those challenges is applying the Development Operations (DevOps) model to an ML application, also referred to as MLOps. This thesis sets out to find the specific challenges that practitioners encounter while operationalising ML models. To do so, we perform a single-case case study on an ML pipeline built by the Trade & Communication Surveillance team at the ING bank. This case study consists of conducting a set of interviews and performing a manual code inspection of the pipeline. The team faces challenges ranging from having insufficient time for operationalising each ML project individually to operating in the highlyregulated fintech context. Their pipeline is able to deploy a single ML model but it does not generalise well to other projects. We present the first version of an application that mitigates these challenges. The application is able to deploy ML models to the development environment at ING and can be operated by data scientists to reduce the effort of operationalising an ML model. Computer Science | Software Technolog
'Project smells' - Experiences in Analysing the Software Quality of ML Projects with mllint
No full textMachine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes, it is only a small piece of the software quality puzzle, especially in the case of ML projects given their additional challenges and lower degree of Software Engineering (SE) experience in the data scientists that develop them. We introduce the novel concept of project smells which consider deficits in project management as a more holistic perspective on software quality in ML projects. An open-source static analysis tool mllint was also implemented to help detect and mitigate these. Our research evaluates this novel concept of project smells in the industrial context of ING, a global bank and large software- and data-intensive organisation. We also investigate the perceived importance of these project smells for proof-of-concept versus production-ready ML projects, as well as the perceived obstructions and benefits to using static analysis tools such as mllint. Our findings indicate a need for context-aware static analysis tools, that fit the needs of the project at its current stage of development, while requiring minimal configuration effort from the user. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Software EngineeringSoftware Technolog
Audiomobiles, Sculptures and Conundrums
No full textRoberto Gerhard was a pioneer of electronic music in England creating a number of substantial concert, theatre and radio works from as early as 1954. Gerhard’s electronic music is one of the richest repositories for understanding the development of the composer’s late compositional technique. Apart from the Symphony no.3, ‘Collages’, none of Gerhard’s electronic music is published. This paper will discuss aspects of Gerhard’s electronic music, focusing on Audiomobiles (1958-59) and Sculptures (1963)
Studies to predict and reduce anastomotic leak following colorectal surgery
No full textIntroduction Anastomotic leak (AL) is the most significant complication of colorectal surgery with huge impact on morbidity, mortality and quality of life. This thesis aimed to investigate the evidence to predict AL following colorectal surgery and how an education based quality improvement intervention to reduce AL risk could 1) effect change and 2) demonstrate how surgical practice can be improved using an education tool. Objectives The thesis objectives were to undertake: 1. A systematic review of pre- and intraoperative anastomotic leak prediction scores (ALPS); 2. An international, batched, cluster randomised trial of an education based, quality improvement intervention (QII) to reduce AL following right colectomy (EAGLE); 3. A process evaluation of EAGLE involving fully integrated mixed methods (FIMM) to explore feasibility, motivation and the barriers and enablers to implementation. Methods The following methods were used: Objective 1: a systematic review of ALPS. Objective 2: an international, batched, incomplete, stepped wedge, cluster randomised, education based, hospital-level, QII trial to reduce AL after right colectomy where the primary objective was to reduce AL by 30% relative risk. Objective 3: a prospective, parallel process evaluation of EAGLE using a FIMM study design including study of technical feasibility for the novel study design, education evaluation, content analysis and thematic framework analysis of semi-structured interview data to evaluate motivating factors, barriers and enablers for change. Results Thirty-one ALPS and six validation studies were identified using only pre- and intraoperative risk factors for AL. No ALPS were free of significant risk of bias or issues with either performance scores, validation or applicability to promote adoption in clinical practice. EAGLE randomised 373 unique clusters into one of three study sequences in 16 batches over three years. 2143 learners completed the EAGLE e-modules with a high conversion rate from login to completion (77.3%). The EAGLE primary outcome was based on 3039 patients from 352 clusters in 64 countries. EAGLE did not significantly reduce AL rate following the QII however a subgroup analysis showed a reduction in AL at hospitals with the highest team engagement (proportion of surgeons to complete e-modules). Feasibility studies showed the batched design reduced the sample size, optimised statistical efficiency; allowed sequential site on-boarding to accelerate trial progress; and was resistant to the impact of the Covid-19 trial suspension. The incomplete aspect of the study design caused some confusion among collaborators and complexity of work for the central team. Key barriers to implementing change reported by collaborators were attitudinal barriers, practical obstacles and the competing demands of high clinical workloads. Establishment of a community of practice and a culture that fosters learning, improvement and research were important enablers. Conclusion AL remains a devastating complication for patients and surgeons. Authors of future prediction models should validate existing ALPS, and design and report any new models in accordance with guidance to reduce risk of bias. Education based international QIIs can achieve high levels of engagement in a multidisciplinary operating theatre setting, with variable implementation. The EAGLE study did not achieve the 30% relative risk reduction in AL that was intended however this study indicates that whole team focus on perioperative optimisation and engagement with best evidence, may be more important than checklist type exercises in improving patient outcomes. The EAGLE study design is feasible: the batched feature is advantageous, but the incomplete aspect is likely not worth the additional administrative effort in future studies. Attitudinal barriers limit implementation that limits the reach of the QII to target patients. Implementation is most likely in the presence of good teamwork, in departments that foster learning, improvement and research
Music for classical guitar by South African composers : a historical survey, notes on selected works and a general catalogue
No full textIncludes abstract.Includes bibliographical references (leaves 296-309).This is the first comprehensive investigation of music for, or including, the classical guitar by South African composers. The focus of this research has been, firstly, to uncover as much of the repertoire as possible, and, secondly, to collate, study, catalogue and report on the information. A brief historical survey of the guitar in South Africa provides the context within which this study was conducted. The primary sources of quantitative data collection were through the archival catalogues of the South African Music Rights Organisation and through personal contact with guitarists, composers and guitar teachers. Other sources consulted were publishers, broadcasting corporations, recording companies, libraries and the internet. The body of the dissertation comprises biographical sketches, background notes, analyses and technical notes on 17 selected solo and chamber works dating from 1947 to 2007 by some of South Africa's most prominent composers and guitaristcomposers. The repertoire ranges in style from the traditional and ethnically inspired to the experimental and abstract. As this is an empirical survey, each selected entry includes details on instrumentation, duration, level of difficulty, number of pages, scordatura, commissions or requests, sources or publishers, premières and recordings. A biography of each composer is provided as well as background notes which offer an overview of the selected work. The notes discuss historical, cultural, musical and extra-musical influences, and frequently include references to interview material. The commentaries on the selected works, with musical examples, include an analytical component describing structure, form, stylistic and compositional elements, while the technical observations include performance suggestions and a grading for each work
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