Sökning: "Heterogeneous Cluster"

Visar resultat 1 - 5 av 22 uppsatser innehållade orden Heterogeneous Cluster.

  1. 1. Deterministic Performance on Kubernetes

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Chetan Kandya; [2023]
    Nyckelord :Kubernetes; Deterministic Performance; Core Isolation; IDO; Intent Driven Orchestration; CRI-RM; Docker; Cloud Optimization;

    Sammanfattning : With the exponential growth of virtualization and cloud computing over the last decade, many companies in the telecommunications sector have started their journey towards cloud migration by exchanging a lot of specialized hardware for virtualized solutions. With more and more applications running in a cloud environment, it became essential to run these applications on heterogeneous systems with shared underlying hardware and software resources. LÄS MER

  2. 2. An Application of Cluster Analysis in Identifying and Evaluating Prognostic Subgroups for Therapy-Related Acute Myeloid Leukemia

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Stefanie Antonilli; [2022]
    Nyckelord :AML; lymphoma; heterogeneous data; cluster analysis; k-prototypes algorithm;

    Sammanfattning : Treatment for lymphoma with alkylating therapy is known to increase the risk of secondary malignancies such as Acute Myeloid Leukemia (AML), although the risk is not fully understood. This study investigates the characteristics of AML that arise after lymphoma treatment in contrastto AML cases without a prior lymphoma. LÄS MER

  3. 3. Data-driven asthma phenotypes fail to accommodate personalized follow-up strategies in primary care

    Master-uppsats, Örebro universitet/Institutionen för medicinska vetenskaper

    Författare :Carolin Wingefors; [2022]
    Nyckelord :asthma phenotypes; cluster analysis; asthma control; exacerbations; follow-up.;

    Sammanfattning : Introduction Asthma is a common and heterogeneous disease in primary care. Asthma phenotypes are recognisable clusters of for example clinical characteristics. Current asthma symptoms and previous exacerbations are used to assess the level of asthma control. Asthma control is used clinically to plan follow-up strategies. LÄS MER

  4. 4. Machine Learning personalizationfor hypotension prediction

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Clara Escorihuela Altaba; [2022]
    Nyckelord :Arterial blood pressure; Hypotension prediction; Machine learning personal- ization; Domain adaptation; Data grouping; Arteriellt blodtryck; Börutsägelse av hypotoni; Personaliserad maskininlär- ning; Domänanpassning; Datagruppering.;

    Sammanfattning : Perioperative hypotension (PH), commonly a side effect of anesthesia,is one of the main mortality causes during the 30 posterior days of asurgical procedure. Novel research lines propose combining machinelearning algorithms with the Arterial Blood Pressure (ABP) waveform tonotify healthcare professionals about the onset of a hypotensive event withtime advance and prevent its occurrence. LÄS MER

  5. 5. Federated Learning in Large Scale Networks : Exploring Hierarchical Federated Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Henrik Eriksson; [2020]
    Nyckelord :Federated learning; personalization; time series forecasting; clustering; hierarchical federated learning; model interpolation; Mapper; HierFAvg; base stations; non-IID; LSTM; Federerad inlärning; tidsserieprognostisering; personalisering; kluster; hierarkisk federerad inlärning; modellinterpolation; Mapper; HierFAvg; basstationer;

    Sammanfattning : Federated learning faces a challenge when dealing with highly heterogeneous data and it can sometimes be inadequate to adopt an approach where a single model is trained for usage at all nodes in the network. Different approaches have been investigated to succumb this issue such as adapting the trained model to each node and clustering the nodes in the network and train a different model for each cluster where the data is less heterogeneous. LÄS MER