Nettsider med emneord «DigiTech»

DigiTech explores the technological foundation for a digital society with emphasis on research on machine learning, artificial intelligence, industrial information technology and development and design of large and interactive information systems. 

ACDICOM’s main objective is to provide common protocols and standards for the improved exchange of cyber threat information between individuals and organisations experiencing a cyber incident. This primary aim will lead to easier and more efficient communication between individuals and organisations, across societal sectors, hierarchical layers and professional backgrounds.

The project objective is to advance the performance of the cybersecurity (CS) specialist by identifying possible improvements from three different perspectives: 1) considering the human as a biological entity, 2) analyzing behaviour patterns of the person; and 3) addressing the necessary knowledge and skills of the cybersecurity specialist.

Cybersikkerhet er gjenstand for rask teknologisk fremgang. Det medfører et økende behov for en vitenskapelig forståelse av det enkelte menneskes begrensninger og ytelse i interaksjon med cybertrusler. ACDICOM skal bidra til å øke denne forståelsen og dermed gi grunnlag for bedre beslutningsresultater.

The research group focuses on developing methods, tools, and techniques to increase participation in both professional and end-user design practices in the digital society. We aim to further the agenda of making design accessible to everyone, by empowering people with tools to actively engage in and contribute to co-creative practices in the digital society. Currently, the group is involved in projects in several domains, health, education, engineering, and media, providing a diverse research environment for the group members.

Forskergruppa CPSForsk vant Høyskolens Forskningsprisen 2020. Det er vi stolte av og tar med oss som en viktig inspirasjon videre!

Forskergruppa Cyber-fysiske systemer (CPSForsk) konsentrerer seg om systemer der det er essentielt å observerer og styre fysiske ting. Derfor undersøker vi digitalisering: roboter, smarte hjem, energieffektivisering og moderne produksjonsteknologi. I forskningen vår finner vi fag som modellering, sanntidssystemer, nettverk, skytjenester og tingenes internett.

The Research Group for Cyber-physical systems (CPSForsk) looks at systems where it is essential to observe and manage physical things. Therefore, we investigate digitalization: robots, smart houses, energy efficiency, and modern production technology. In our research we include modeling, real time systems, networks, cloud services and Internet-of-Things.

The research group focuses on developing methods, tools, and techniques to increase participation in both professional and end-user design practices in the digital society. We aim to further the agenda of making design accessible to everyone, by empowering people with tools to actively engage in and contribute to co-creative practices in the digital society. Currently, the group is involved in projects in several domains, health, education, engineering, and media, providing a diverse research environment for the group members.

In this project, we are looking at the possibility of developing decision support systems based on machine learning for several parts of the health care system.  The AI tool created would put the patient’s needs first, thus allowing the caregiver the opportunity to design the care and treatment for the patient in such a way that it would minimise treatment variations offered by different healthcare providers. The incorporation of AI in decision support would promote the utilisation of the most effective treatment program for each patient and would provide the means to compare the different treatment options provided to patients in terms of outcomes, costs and patient satisfaction.   The project is a collaborative project between the Østfold University College (HiØ), Østfold Hospital Trust, University of Borås and a number of partners within the health care system and on both sides of the Norway-Sweden border.

The Information Systems and Software Engineering (ISSE) research group conducts research and teaching in the broad field of information systems and software engineering disciplines.

Maskinlæring (ML) og Kunstig Intelligens (AI) er muliggjørende teknologier for det digitale samfunn. Vår gruppe gjennomfører grunnforskning til å utvikle nye metoder innen AL og ML, og anvender banebrytende metoder i ulike applikasjonsdomener.

I dette forskningsprosjektet ser vi på muligheten for å utvikle systemer for beslutningsstøtte basert på maskinlæring for flere deler av helsevesenet. Prosjektet er et samarbeidsprosjekt mellom Høgskolen i Østfold, Høgskolan i Borås og en rekke partnere innen helsevesenet på begge sider av grensen. 

DigiTech focuses on the technological foundation of a digital society. DigiTech's IT researchers concentrate their research efforts on machine learning, artificial intelligence, industrial IT, and the development and design of large and interactive information systems.

Machine Learning (ML) and Artificial Intelligence (AI) are enabling technologies for the digital society. Our group conducts both basic research to develop new methods in AI and ML, as well as apply cutting-edge methods in diverse application domains.

The project's main goal is the creation of a system based on Artificial Intelligence that can automatically transcribe any historical handwriting from Norwegian writers even if they have not been seen before, during the training phase of the system.

DigiTech utforsker det teknologiske fundamentet for et digitalt samfunn med vektlegging av forskning på maskinlæring, kunstig intelligens, industriell informasjonsteknologi og utvikling og design av store og interaktive informasjonssystemer. 

Prosjektets hovedmål er å lage et system basert på kunstig intelligens, som kan gjenkjenne historisk norsk håndskrift som systemet ikke har sett før og ikke er inkludert i treningen.

Prosjektets mål er å utvikle prestasjonene til cybersikkerhetsspesialister ved å indentifisere ulike perspektiver som biologiske forutsetninger, atferdsmønstere og nødvendig kunnskap og kompetanse. Les mer på prosjektets hjemmeside.