Sökning: "Human Machine Interaction"

Visar resultat 1 - 5 av 122 avhandlingar innehållade orden Human Machine Interaction.

1. 1. Representing human-automation challenges

   Författare :Jonas Andersson; Chalmers tekniska högskola; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; human-machine systems; control rooms; cognitive systems engineering; automation;

   Sammanfattning : Automation technology is widely implemented in process control domains due to its benefits of improving efficiency and enhancing control. However, use of automation also introduces an often complex intermediary between the human and the controlled domain, which can obscure from the operator how system functioning is achieved. LÄS MER

3. 2. Human In Command Machine Learning

   Författare :Lars Holmberg; Paul Davidsson; Per Linde; Malmö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Human-centered AI ML; Explainable AI; Machine Learning; Human In the Loop ML; Interaktionsdesign; Interaktionsdesign;

   Sammanfattning : Machine Learning (ML) and Artificial Intelligence (AI) impact many aspects of human life, from recommending a significant other to assist the search for extraterrestrial life. The area develops rapidly and exiting unexplored design spaces are constantly laid bare. LÄS MER

4. 3. Spaces within Spaces : The Construction of a Collaborative Reality

   Författare :Hillevi Sundholm; Carl Gustaf Jansson; Yvonne Rogers; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Co-located collaboration; Distributed collaboration; Teamwork; Interactive spaces; Space; Computer and systems science; Data- och systemvetenskap; Man-Machine-Interaction MMI ; människa-maskin-interaktion MMI ;

   Sammanfattning : This thesis is about collaborative activities in interactive spaces. These spaces are characterized by having shared, large displays in combination with private displays and software tools that facilitate a fluent sharing of information between people and their resources. LÄS MER

5. 4. Exploring Road Traffic Interactions Between Highly Automated Vehicles and Vulnerable Road Users

   Författare :Victor Fabricius; Pontus Wärnestål; Jonas Andersson; Barry Brown; Högskolan i Halmstad; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Automated driving system; Vulnerable road user; Traffic interaction; User Experience;

   Sammanfattning : Understandings of road traffic interactions are largely based on human-human interactions. However, the development of vehicles controlled by highly auto- mated driving systems (ADS) would introduce a radically novel type of road user. LÄS MER

7. 5. Visual Analytics for Explainable and Trustworthy Machine Learning

   Författare :Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

   Sammanfattning : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. LÄS MER