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Showing result 1 - 5 of 28 essays matching the above criteria.
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1. Finding Anomalous Energy ConsumersUsing Time Series Clustering in the Swedish Energy Market
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Improving the energy efficiency of buildings is important for many reasons. There is a large body of data detailing the hourly energy consumption of buildings. This work studies a large data set from the Swedish energy market. READ MORE
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2. Classification of Radar Emitters using Semi-Supervised Contrastive Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Radar is a commonly used radio equipment in military and civilian settings for discovering and locating foreign objects. In a military context, pilots being discovered by radar could have fatal consequences. READ MORE
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3. An Intersectional Feminist WAP Pt. 2 : A Unique Case Study of the WAP Music Video by Cardi B and Meg Thee Stallion
University essay from Linköpings universitet/Tema GenusAbstract : Cardi B and Meg Thee Stallion have no problem destroying the male gaze to empower women through the female gaze within the WAP music video. They both empower women by creating a whorehouse for women by women as Cardi B and Meg Thee Stallion both play the role as the entertainer and the entertained therefore forcing the viewer into a trance. READ MORE
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4. Segmenting cruise passengers based on their spatio-temporal similarity : an approach utilising dynamic time warping
University essay from Uppsala universitet/Kulturgeografiska institutionenAbstract : The present thesis utilises dynamic time warping and cluster analysis with the aim of discovering different touristic profiles. GPS data of cruise passengers intra-destination movement at the destination of Visby, Gotland, was used in the analysis. READ MORE
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5. Improving Change Point Detection Using Self-Supervised VAEs : A Study on Distance Metrics and Hyperparameters in Time Series Analysis
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis addresses the optimization of the Variational Autoencoder-based Change Point Detection (VAE-CP) approach in time series analysis, a vital component in data-driven decision making. We evaluate the impact of various distance metrics and hyperparameters on the model’s performance using a systematic exploration and robustness testing on diverse real-world datasets. READ MORE