Essays about: "Alexander technique"
Showing result 1 - 5 of 48 essays containing the words Alexander technique.
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1. Beyond Profits: Exploring the Investment Styles and Risk-Adjusted Returns of ESG-Driven Portfolios
University essay fromAbstract : This study uses daily data to examine how different ESG implementations affect performance and portfolio characteristics. With a non-homogenous view of how ESG investing is defined, ten different value-weighted portfolios are constructed. The geographical focus is the US market, with the S&P 500 total return index (SPXTR) as the screening universe. READ MORE
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2. Transformer Offline Reinforcement Learning for Downlink Link Adaptation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent advancements in Transformers have unlocked a new relational analysis technique for Reinforcement Learning (RL). This thesis researches the models for DownLink Link Adaptation (DLLA). READ MORE
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3. Flash Pulse Thermography Measurements of Coat Thickness
University essay from Umeå universitet/Institutionen för fysikAbstract : The application of varnish, metal coats, and paint is a common practice for modifying or enhancing material properties. Metal coats are frequently used as protective layers against corrosion, heat, and wear, while also influencing characteristics like conductivity, weight, and production costs. READ MORE
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4. Differentially Private Random Forests for Network Intrusion Detection in a Federated Learning Setting
University essay from Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)Abstract : För varje dag som går möter stora industrier en ökad mängd intrång i sina IT-system. De flesta befintliga verktyg som använder sig utav maskininlärning är starkt beroende av stora mängder data, vilket innebär risker under dataöverföringen. READ MORE
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5. Through the Blur with Deep Learning : A Comparative Study Assessing Robustness in Visual Odometry Techniques
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : In this thesis, the robustness of deep learning techniques in the field of visual odometry is investigated, with a specific focus on the impact of motion blur. A comparative study is conducted, evaluating the performance of state-of-the-art deep convolutional neural network methods, namely DF-VO and DytanVO, against ORB-SLAM3, a well-established non-deep-learning technique for visual simultaneous localization and mapping. READ MORE