Search for dissertations about: "Continuous data"

Showing result 1 - 5 of 1190 swedish dissertations containing the words Continuous data.

  2. 1. Parallel Data Streaming Analytics in the Context of Internet of Things

    Author : Hannaneh Najdataei; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; clustering; stream continuous data processing; edge computing; Internet of Things; parallelism; elasticity; data analysis; fog computing; scalability;

    Abstract : We are living in an increasingly connected world, where the ubiquitously sensing technologies enable inter-connection of physical objects, as part of Internet of Things (IoT), and provide continuous massive amount of data. As this growth soars, benefits and challenges come together, which requires development of right tools in order to extract valuable information from data. READ MORE

  4. 2. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

    Author : Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

    Abstract : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. READ MORE

  5. 3. Scalable and Reliable Data Stream Processing

    Author : Paris Carbone; Seif Haridi; Peter Pietzuch; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; distributed systems; stream processing; data management; databases; distributed computing; data processing; fault tolerance; database optimisation; programming systems; data science; data analytics; computer science; Informations- och kommunikationsteknik; Information and Communication Technology;

    Abstract : Data-stream management systems have for long been considered as a promising architecture for fast data management. The stream processing paradigm poses an attractive means of declaring persistent application logic coupled with state over evolving data. READ MORE

  6. 4. Mining Evolving and Heterogeneous Data : Cluster-based Analysis Techniques

    Author : Vishnu Manasa Devagiri; Veselka Boeva; Niklas Lavesson; Shehroz Khan; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Domain Adaptation; Evolving Clustering; Heterogeneous Data; Multi-View Clustering; Streaming Data; Computer Science; Datavetenskap;

    Abstract : A large amount of data is generated from fields like IoT, smart monitoring applications, etc., raising demand for suitable data analysis and mining techniques. READ MORE

  7. 5. Improving the Performance of Machine Learning-based Methods for Continuous Integration by Handling Noise

    Author : Khaled Al-Sabbagh; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Continuous Integration; Noise in software programs; Noise-handling; Software regression testing; Code change requests; Build prediction;

    Abstract : Background: Modern software development companies are increasingly implementing continuous integration (CI) practices to meet market demands for delivering high-quality features. The availability of data from CI systems presents an opportunity for these companies to leverage machine learning to create methods for optimizing the CI process. READ MORE