[dipl] Perustieteiden korkeakoulu / SCI

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Browsing [dipl] Perustieteiden korkeakoulu / SCI by Degree programme/Major subject "Acoustics and Audio Technology"

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  • Applying Machine Learning to Root Cause Analysis in Agile CI/CD Software Testing Environments
    (2019-01-28) Kahles Bastida, Julen
     Perustieteiden korkeakoulu | Master's thesis
    This thesis evaluates machine learning classification and clustering algorithms with the aim of automating the root cause analysis of failed tests in agile software testing environments. The inefficiency of manually categorizing the root causes in terms of time and human resources motivates this work. The development and testing environments of an agile team at Ericsson Finland are used as this work's framework. The author of the thesis extracts relevant features from the raw log data after interviewing the team's testing engineers (human experts). The author puts his initial efforts into clustering the unlabeled data, and despite obtaining qualitative correlations between several clusters and failure root causes, the vagueness in the rest of the clusters leads to the consideration of labeling. The author then carries out a new round of interviews with the testing engineers, which leads to the conceptualization of ground-truth categories for the test failures. With these, the human experts label the dataset accordingly. A collection of artificial neural networks that either classify the data or pre-process it for clustering is then optimized by the author. The best solution comes in the form of a classification multilayer perceptron that correctly assigns the failure category to new examples, on average, 88.9\% of the time. The primary outcome of this thesis comes in the form of a methodology for the extraction of expert knowledge and its adaptation to machine learning techniques for test failure root cause analysis using test log data. The proposed methodology constitutes a prototype or baseline approach towards achieving this objective in a corporate environment.
  • A Biologically-Inspired Neural Network for Sound Lateralization
    (2023-10-09) Louise, Bryn
     Perustieteiden korkeakoulu | Master's thesis
    Models of the auditory periphery have been used to study human perception of sound. These models contribute to the improvement of listening devices such as hearing aids, cochlear implants, headphones, and loudspeakers. Physical models that explain the mechanics of the auditory periphery have proven to be accurate and slow. Due to the computational complexity of physical models, the use of deep learning to create biologically-inspired and easily parallelizable models has gained traction. In this thesis, we build on the recent advances in biologically-inspired neural networks and previous work in auditory modeling to model sound source localization in the frontal horizontal plane. This thesis presents CoCoNetti, a biologically inspired neural network that leverages the strengths of both CoNNear and Count-Comparison models for azimuth prediction in the frontal horizontal plane. CoCoNetti achieves accurate azimuth prediction while following trends in human perception.
  • Investigation of potential benefits of vibration and turbulence on the capacity and availability of an electrocoagulation process with paperboard coating wastewater
    (2021-01-25) Rönkä, Sami
     Perustieteiden korkeakoulu | Master's thesis
    Electrocoagulation is a wastewater treatment method that utilizes the ionic properties of dissolved substances to separate contaminants from water through electrolysis. Typical challenges in an electrocoagulation process include optimizing the reaction conditions within the reactor and preventing the passivation of the electrodes. This thesis evaluates the effect of various modifications involving vibration and turbulence with the goal to improve the capacity and availability of an electrocoagulation process. The examined modifications include ultrasonic vibration, mechanical vibration, and O-rings to alter the surface geometry of the electrodes. These modifications were tested against a reference reactor with no modifications. At first, laboratory scale testing was done with the ultrasonic transducer to ensure appropriate coupling between the transducer and the reactor, and to evaluate the cavitation potential of the transducer. Some cavitation was observed using clean water, but the effect was significantly reduced using the processed wastewater. Full scale process tests were performed with a test setup of 4 parallel reactors with the different modifications attached to each of them. The O-ring modification resulted in the worst purification result and fastest fouling of the reactor. The ultrasonic- and mechanical vibration did not have conclusive differences in results with the control reactor, although the ultrasonic reactor remained cleaner one of the trials. It is possible that a higher-powered ultrasonic transducer would have had a more significant effect in the full scale process. There were a number of unexpected setbacks and uncontrollable variables during the testing period, so further testing in a more controlled environment would be needed for more conclusive results.
  • Kannettavan Bluetooth-kaiuttimen suunnittelu ja toteutus
    (2019-06-17) Rautakoski, Johannes
     Perustieteiden korkeakoulu | Master's thesis