Haku

This study explores the application of machine learning to forecast sovereign debt default likelihood. Challenges include a limited sample size of 8175 country-year observations across 180 countries from 1970 to 2019, high ...

This thesis investigates the use of machine learning models to accurately identify mispriced residential real estate properties by analyzing listing data. Unlike prior studies that incorporate various data types, this ...

In the fields of sports science, biomechanics, osteopathic medicine, medical diagnostics, etc are being used in gait analysis. Traditional systems like VICON, which use passive markers and advanced video cameras, require ...

Natural Language Processing (NLP) is crucial for enhancing machine learning-powered tools in business intelligence. NLP empowers these tools to grasp user queries phrased in natural language, streamlining data analysis and ...

The welfare state in Finland is weakening as a result of an ageing population and labour shortages in both the public and private sectors. Demographic projections suggest that our country will need up to 200 000 people of ...

Studien berör högre YH-socionomens kompetens inom småbarnspedagogiken och hur den kunde utnyttjas. Ett större behov av socionomens specialkompetens för att möta småbarnspedagogikens krav har påvisats. Även ett behov av att ...

This study examines several models for predicting deforestation trends in a specific region of Sequoia National Park using the Normalized Difference Vegetation Index (NDVI) and the Leaf Area Index (LAI). For the study, a ...

Tämän työn tarkoituksena oli Porvoon Kaupungin teettämän kyselyn avoimia kysymyksiä analysoimalla selvittää, miten Itä-Uudenmaan hyvinvointialueen ja alueella toimivien omaishoitajien yhteistyötä voisi parantaa. Kysely ...

The widespread adoption of social media platforms has revolutionized connectivity and information sharing, but it has also contributed to a significant environmental concern: digital carbon footprint. This thesis investigates ...

This thesis explores and simulates federated learning, specifically focusing on applying adversarial attacks against input data to assess their impact on training performance. In the context of the rising importance of ...