Essays about: "sensitivity training"

Showing result 1 - 5 of 70 essays containing the words sensitivity training.

  1. 1. “We have to speak one language to stop FGM“ : Inside and outside perspectives on challenges and strategies related to the elimination of Female Genital Mutilation/Cutting within the Maasai in the Northern central part of in Tanzania

    University essay from

    Author : Anna Bergman; Stina Olausson; [2023]
    Keywords : ;

    Abstract : Female Genital Mutilation/Cutting (FGM/C) is a universal concern, with more than 200 million girls and women alive today who have undergone the practice primarily concentrated in Africa. The Maasai, a semi-nomadic ethnic group inhabiting the Northern Central part of Tanzania, have the highest rate of FGM/C in the whole country. READ MORE

  3. 2. Unsupervised Detection of Interictal Epileptiform Discharges in Routine Scalp EEG : Machine Learning Assisted Epilepsy Diagnosis

    University essay from Uppsala universitet/Avdelningen Vi3

    Author : Shuai Shao; [2023]
    Keywords : EEG; electroencephalography; IED; interictal epileptiform discharges; spike detection; epilepsy; unsupervised; Fourier transform; STFT; short-time Fourier transform; CWT; continuous wavelet transform; DWT; discrete wavelet transform; ML; machine learning; ANN; artificial neural network; CNN; convolutional neural network; autoencoder; HMM; hidden Markov model; ECS; Euclidean distance of cumulative spectrum;

    Abstract : Epilepsy affects more than 50 million people and is one of the most prevalent neurological disorders and has a high impact on the quality of life of those suffering from it. However, 70% of epilepsy patients can live seizure free with proper diagnosis and treatment. Patients are evaluated using scalp EEG recordings which is cheap and non-invasive. READ MORE

  4. 3. Wind Turbine Recovery Forecasting using Survival Analysis

    University essay from Lunds universitet/Matematisk statistik

    Author : Anton Palets; [2023]
    Keywords : Survival analysis; Recovery Forecast; Wind Turbine; Availability Forecast; AFT model; Aalen s model; Cox regression; Cox Proportional Hazards; Variation Processes; Mathematics and Statistics;

    Abstract : The goal of this thesis is to present a methodology for predicting time until recovery of failed wind turbines. The necessity is motivated by the potential for more accurate wind energy export forecasts. The current approach rests entirely on having an expert examine the turbine and produce a time estimate. READ MORE

  5. 4. Event categorisation and Machine-learning Techniques in Searches for Higgs Boson Pairs in the ATLAS Experiment at the LHC

    University essay from Uppsala universitet/Högenergifysik

    Author : Milads Emadi; [2023]
    Keywords : Particle Physics; ATLAS; BDT; Boosted Decision Tree; Decision Tree; Optimization; Machine Learning; Analysis;

    Abstract : This thesis investigates the pair production of Higgs bosons (di-Higgs events) at the ATLAS experiment in the Large Hadron Collider (LHC), focusing on the channel where one Higgs boson decays into two bottom quarks and the other decays into two tau leptons. The main objective was to determine whether introducing a split in the invariant mass of the decay products from the two Higgs bosons (the di-Higgs mass) and using this as an analysis variable improves the sensitivity of the Boosted Decision Tree (BDT) machine learning algorithm to the di-Higgs signal. READ MORE

  6. 5. Evaluation of Ferroelectric Tunnel Junction memristor for in-memory computation in real world use cases

    University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

    Author : Alec Guerin; Christos Papadopoulos; [2023]
    Keywords : FTJ; Ferroelectric Tunneling Junction; Analog in-memory computing; AIMC; Memristor; A.I.; AIHWKIT; Semantic segmentation; Natural Language Processing; NLP; Neuromorphic Computing; Matrix Vector Multiplication; Technology and Engineering;

    Abstract : Machine learning algorithms are experiencing unprecedented attention, but their inherent computational complexity leads to high energy consumption. However, a paradigm shift in computing methods has the potential to address the issue. READ MORE