Search for dissertations about: "linear regression"

Showing result 21 - 25 of 482 swedish dissertations containing the words linear regression.

  2. 21. Analysis of Retroreflection and other Properties of Road Signs

    Author : Roxan Saleh; Hasan Fleyeh; Darko Babić; Högskolan Dalarna; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Road traffic signs; retroreflective sheeting material; night-time visibility; supervised machine learning; principal component analysis; prediction; linear regression;

    Abstract : Road traffic signs provide regulatory, warning, guidance, and other important information to road users to prevent hazards and road accidents. Therefore, the traffic signs must be detectable, legible, and visible both in day and nighttime to fulfill their purpose. The nighttime visibility is critical to safe driving on the roads at night. READ MORE

  4. 22. A Study of Critical Variables in the Anxiety of Schizophrenics by means of a Structured Clinical Interview and a Percept-genetic Experiment

    Author : Dan Anders Palmquist; Institutionen för psykologi; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Psychology; Factor-analysi; Cluster-analysis; Structured Interview; Subliminal verbal stimulation; Gestalting ability; Regression; Disintegration; Subliminal perception; Psychopathology; Cognitive maturity; Affects; Anxiety; Schizophrenia Perception; Percept-genetics; Psykologi; Regression;

    Abstract : Presented to 42 schizophrenic patients and 19 normals, by means of a percept-genetic technique, two motifs of mother and infant in close interaction (feeding and nursing) . The motifs were tagged, by subliminal presentation, with aggressive resp. "healing" sentences, in a balanced design. No effects of this tagging were discernible. READ MORE

  5. 23. Cervical dysplasia and cervical cancer in pregnancy: diagnosis and outcome

    Author : Cecilia Kärrberg; Göteborgs universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Cervical dysplasia; cervical cancer; pregnancy; colposcopic scoring system; regression; persistence; progression; HPV DNA test; HPV mRNA E6 E7 test; p16INK4a;

    Abstract : ABSTRACT:Cervical cancer is one of the most common types of cancer that is diagnosed during pregnancy. The primary aim in investigation of atypical cervical cytology during pregnancy is to exclude cancer so that further treatment of the lesion can be postponed until after delivery. READ MORE

  6. 24. Development and evaluation of methods for control and modelling of multiple-input multiple-output systems

    Author : Fredrik Bengtsson; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Input-output scaling; Modeling; Fiber length; Tensile Index; Hold-input; Decentralized control; Gramian based measures; Delays; LQG control; TMP; Uncertain data sets; Unreliable communication links; MIMO systems; Control configuration selection; Linear regression; Freeness; Shives; CTMP;

    Abstract : In control, a common type of system is the multiple-input multiple-output (MIMO) system, where the same input may affect multiple outputs, or conversely, the same output is affected by multiple inputs. In this thesis two methods for controlling MIMO systems are examined, namely linear quadratic Gaussian (LQG) control and decentralized control, and some of the difficulties associated with them. READ MORE

  7. 25. Generalization under Model Mismatch and Distributed Learning

    Author : Martin Hellkvist; Ayca Özcelikkale; Anders Ahlén; Martin Jaggi; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine learning; Signal processing; Generalization error; Training error; Double-descent; Double descent; Distributed learning; Distributed optimization; Learning over networks; Model mismatch; Model misspecification; Fake features; Missing features; linear regression; regularization; Machine learning; Maskininlärning;

    Abstract : Machine learning models are typically configured by minimizing the training error over a given training dataset. On the other hand, the main objective is to obtain models that can generalize, i.e., perform well on data unseen during training. READ MORE