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Showing result 1 - 5 of 12 essays matching the above criteria.

1. 1. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Love Marcus; [2023]
   Keywords : User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Abstract : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. READ MORE

3. 2. Head impact detection with sensor fusion and machine learning

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Aron Strandberg; [2022]
   Keywords : head impact detection; sensor fusion; 3D; machine learning; support vector machine; random forests;

   Abstract : Head injury is common in many different sports and elsewhere, and is often associated with differentdifficulties. One major problem is to identify and value the injury or the severity. Sometimes there is no sign of head injury, but a serious neck distortion has occurred, causing similar symptoms as head injuries e.g. READ MORE

4. 3. Antenna as a sensor for sensing available LTE networks

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Barath Kumar Sathish Kumar; [2022]
   Keywords : Radio Frequency energy harvesting; Antenna as a sensor; Long-Term Evolution; Rectifier; Printed Circuit Board; Altium Designer; Matching network; Voltage multiplier; Schottky diodes; Multiband LTE antenna; Ambient energy harvesting; Low power Internet of Things; Wireless power transfer; Radiofrekvensenergiskörd; Antenn som sensor; LTE; Likriktare; Printed Circuit Board; Altium Designer; Matchande nätverk; Spänningsmultiplikator; Schottky-dioder; Multiband LTE-antenn; Omgivande energiskörd; Lågeffekt Internet of Things; Trådlös kraftöverföring;

   Abstract : This thesis primarily deals with the concept of designing an antenna based device to harvest energy from Radio Frequency (RF) and using the harvested energy to sense the available Long Term Evolution (LTE) network in order for the Internet of Things (IoT) devices to connect to the network for the purpose of transmitting and receiving data. Secondarily the importance of this project is targeting how to conserve battery power in an IoT device and extend it’s lifetime. READ MORE

5. 4. Utilizing Hybrid Ensemble Prediction Model In Order to Predict Energy Demand in Sweden : A Machine-Learning Approach

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Binxin Su; [2022]
   Keywords : Energy Demand Prediction; Machine Learning; Hybrid Model; Ensemble Model; Random Forest; XGBoost; CatBoost; Prognos av Energiefterfrågan; Maskininlärning; Hybridmodell; Ensemblemodell; Random Forest; XGBoost; CatBoost;

   Abstract : Conventional machine learning (ML) models and algorithms are constantly advancing at a fast pace. Most of this development are due to the implementation of hybrid- and ensemble techniques that are powerful tools to complement and empower the efficiency of the algorithms. READ MORE

6. 5. Cropland and tree cover mapping using Sentinel-2 data in an agroforestry landscape, Burkina Faso

   University essay from Göteborgs universitet/Institutionen för geovetenskaper

   Author : Ntandokazi Masimula; [2020-06-29]
   Keywords : Sentinel-2; Cropland mask; Tree cover estimation; Burkina Faso; Agroforestry; Random Forest;

   Abstract : Sentinel-2, with high spatial resolution bands and increased number of spectral channels, has provided increased capabilities for vegetation mapping. Cropland masks within heterogeneous areas such as the Sudano-Sahel zone have become useful for monitoring landscapes. READ MORE