Search for dissertations about: "Information classification method"

Showing result 1 - 5 of 241 swedish dissertations containing the words Information classification method.

  1. 1. Supporting Information Security Management : Developing a Method for Information Classification

    Author : Erik Bergström; Rose-Mharie Åhlfeldt; Fredrik Karlsson; Eva Söderström; Steven Furnell; Högskolan i Skövde; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; information classification; Information security management; Information security management systems; Information classification method; INF303 Informationssäkerhet; INF303 Information Security; Information Systems; Informationssystem IS ;

    Abstract : In the highly digitalised world in which we live today, information and information systems have become critical assets to organisations, and hence need to be safeguarded accordingly. In order to implement and work with information security in a structured way, an Information Security Management System (ISMS) can be implemented. READ MORE

  2. 2. Detection and Classification in Electrocardiac Signals

    Author : Magnus Åström; Institutionen för elektro- och informationsteknik; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Signalbehandling; Signal processing; morphology classification; QRS detection; ischemia; body position changes; electrogram; ECG; electrocardiogram; clustering; classification; Detection; sensing;

    Abstract : Signal processing can be used to condition medical signals to facilitate their interpretation, and to extract clinically important information. The purpose of the present doctoral thesis is to put forward solutions to certain problems encountered in the processing of electrocardiac signals. READ MORE

  3. 3. Studies in Semantic Modeling of Real-World Objects using Perceptual Anchoring

    Author : Andreas Persson; Amy Loutfi; Alessandro Saffiotti; Severin Lemaignan; Örebro universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Perceptual Anchoring; Semantic World Modeling; Sensor-Driven Acquisition of Data; Object Recognition; Object Classification; Symbol Grounding; Probabilistic Object Tracking;

    Abstract : Autonomous agents, situated in real-world scenarios, need to maintain consonance between the perceived world (through sensory capabilities) and their internal representation of the world in the form of symbolic knowledge. An approach for modeling such representations of objects is through the concept of perceptual anchoring, which, by definition, handles the problem of creating and maintaining, in time and space, the correspondence between symbols and sensor data that refer to the same physical object in the external world. READ MORE

  4. 4. Perceptually motivated speech recognition and mispronunciation detection

    Author : Christos Koniaris; Olov Engwall; Martin Cooke; KTH; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; feature extraction; feature selection; auditory models; MFCCs; speech recognition; distortion measures; perturbation analysis; psychoacoustics; human perception; sensitivity matrix; pronunciation error detection; phoneme; second language; perceptual assessment;

    Abstract : This doctoral thesis is the result of a research effort performed in two fields of speech technology, i.e., speech recognition and mispronunciation detection. Although the two areas are clearly distinguishable, the proposed approaches share a common hypothesis based on psychoacoustic processing of speech signals. READ MORE

  5. 5. Components of Embodied Visual Object Recognition : Object Perception and Learning on a Robotic Platform

    Author : Marcus Wallenberg; Per-Erik Forssén; Mårten Björkman; Linköpings universitet; []

    Abstract : Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. READ MORE