Sökning: "Log classes"
Visar resultat 1 - 5 av 34 uppsatser innehållade orden Log classes.
1. Audio Anomaly Detection in Cars
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : Audio anomaly detection in the context of car driving is a crucial task for ensuring vehicle safety and identifying potential faults. This paper aims to investigate and compare different methods for unsupervised audio anomaly detection using a data set consisting of recorded audio data from fault injections and normal "no fault" driving. LÄS MER
2. The effect of covid-19 announcement on sustainable investment portfolios : Observation of the flight-to-quality phenomenon
Magister-uppsats, Jönköping University/Internationella HandelshögskolanSammanfattning : The economic impact of the COVID-19 pandemic is still an ongoing topic, broadly analysed and discussed in many studies. Recent articles state that sustainable assets can offer return volatility resilience during demand shock events and, in some cases, provide higher returns than their unsustainable counterparts. LÄS MER
3. Detection of software incidents from large log material with the use of unsupervised machine learning
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Computer systems generate log files, which contain information on the various operations performed by these systems. This information can support the process of error/failure detection and debugging. Therefore, anomalies can be spotted in the system through its produced log material. LÄS MER
4. Optimering av timmerplanslogistik : Minimering av transportavstånd för den nya timmerplanen på Sävar såg
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : An increase in demand for sawed wood products is the reason why Norra Timber has to expand their facility at Sävar Sawmill. During the expansion, a new log sorting will be implemented which can sort timber with different characteristics and qualities compared to the current log sorting. LÄS MER
5. Classification of Error Messages in Semi-Structured Log Files Using Machine Learning Algorithms
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : In Ericsson, newly developed applications are tested in an in-house testing framework. When an error occurs in the testing phase, manual inspection of errors in the log files and manual classification of these errors into production (PROD) or environment (ENV) classes cost a lot of time. LÄS MER