Essays about: "IMPORTANCE OF PROJECT WORK IN THE LEARNING PROCESS"
Showing result 1 - 5 of 24 essays containing the words IMPORTANCE OF PROJECT WORK IN THE LEARNING PROCESS.
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1. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. READ MORE
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2. Unsupervised Anomaly Detection and Explainability for Ladok Logs
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Anomaly detection is the process of finding outliers in data. This report will explore the use of unsupervised machine learning for anomaly detection as well as the importance of explaining the decision making of the model. READ MORE
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3. LAMP on disk
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Projektet har startat med ett samarbete med SciLifeLab forskning center vid Karolinska institutet där den Nano- biologiavdelningen har tagit fram en kemisk reaktion som kunde detektera Covid-19 metoden heter LAMP som står för Loop- mediated isothermal amplification. Den befintliga enheten som labbet har utvecklat används med hjälp av en mobiltelefon som tar bilder på proverna inför analys. READ MORE
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4. Många goda viljor : en fallstudie i Sege park om lärande kring delningsekonomi i en samarbetskontext
University essay from SLU/Dept. of Landscape Architecture, Planning and Management (from 130101)Abstract : Städer kan vara en del i omställningen till ett hållbart samhälle genom att skapa förutsättningar för de som bor och verkar i dessa att göra hållbara val. Samtidigt krävs nya lösningar i arbetet, till exempel hur vi organiserar oss för att hantera de utmaningar som finns i arbetet för hållbarhet. READ MORE
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5. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : This thesis presents the first attempt to estimate Dissolved Organic Carbon (DOC) in inland waters over a large-scale area using satellite data and machine learning (ML) methods. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were tested to retrieve DOC using a filtered version of the recently published open source AquaSat dataset with more than 16 thousand samples across the continental US matched with satellite data from Landsat 5, 7 and 8 missions. READ MORE
