Search for dissertations about: "Data Science"

Showing result 1 - 5 of 5915 swedish dissertations containing the words Data Science.

  1. 1. Lock-free Concurrent Search

    University dissertation from ; Chalmers tekniska högskola; Gothenburg

    Author : Bapi Chatterjee; [2017]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Wait-free; Help-aware; Non-blocking; Concurrency; Linearizability; Lock-based; Lock-free-kD-tree; Amortized Complexity; Data Structure; Binary Search Tree; Blocking; Search; Concurrent; kD-tree; Linked-list; Lock-free; Range Search; Language-portable; Help-optimal; Nearest Neighbour Search; Linearizable; Synchronization;

    Abstract : The contemporary computers typically consist of multiple computing cores with high compute power. Such computers make excellent concurrent asynchronous shared memory system. READ MORE

  2. 2. Dynamic Adaptations of Synchronization Granularity in Concurrent Data Structures

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Kjell Winblad; Uppsala universitet.; Uppsala universitet.; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; concurrent data structures; contention adapting; range queries; lock-freedom; adaptivity; linearizability; ordered sets; maps; key-value stores; concurrent priority queues; relaxed concurrent data structures; locks; delegation locking; Computer Science; Datavetenskap;

    Abstract : The multicore revolution means that programmers have many cores at their disposal in everything from phones to large server systems. Concurrent data structures are needed to make good use of all the cores. Designing a concurrent data structure that performs well across many different scenarios is a difficult task. READ MORE

  3. 3. Health Data Representation and (In)visibility

    University dissertation from Stockholm : KTH Royal Institute of Technology

    Author : Pedro Sanches; KTH.; Networks and Analytics lab. Decisions; [2015]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : För att förstå hälsodata krävs sammanhang. Jag visar hur detta kan erhållas, genom två fallstudier: en om självövervakning, med fokus på representation av kroppsdata, samt en om massövervakning, med fokus på representation av populationer. READ MORE

  4. 4. Hierarchical Concurrent Systems from a Model-Oriented perspective

    University dissertation from Department of Computer Science, Lund University

    Author : Daniel Einarson; Lunds universitet.; Lund University.; Högskolan Kristianstad.; [2002]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; control; systems; numerical analysis; Computer science; Distributed Systems; Hierarchical Systems; Object-Orientation; Model-Orientation; Datalogi; numerisk analys; system; kontroll; Systems engineering; computer technology; Data- och systemvetenskap; TECHNOLOGY Information technology Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap;

    Abstract : Real world systems are normally considered as hierarchically organized, for example, we see those as hierarchies of systems including subsystems. Examples on this can be seen in organizations where people act in environments and carry within themselves their own internal subsystem of thinking processes. READ MORE

  5. 5. Utilizing Diversity and Performance Measures for Ensemble Creation

    University dissertation from Örebro universitet

    Author : Tuve Löfström; Högskolan i Skövde.; Högskolan i Skövde.; Högskolan i Borås.; [2009]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TECHNOLOGY Information technology Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap; Teknik; Technology; Ensemble Learning; Machine Learning; Diversity; Artificial Neural Networks; Data Mining; Information Fusion; ensemble learning; machine learning; diversity; artificial neural networks; information fusion; Computer Science; data mining;

    Abstract : An ensemble is a composite model, aggregating multiple base models into one predictive model. An ensemble prediction, consequently, is a function of all included base models. Both theory and a wealth of empirical studies have established that ensembles are generally more accurate than single predictive models. READ MORE