Workplace-Initiated mHealth Intervention for Increased Physical Activity

In this research in progress paper, we discuss the acceptance and appropriation of workplace mobile health interventions aiming to increase physical activity and reduce sedentary behaviour, and how this is connected to social cohesion in the workplace. We utilised script theory to investigate what visions, assumptions and choice is made by developers in the design of the mobile health technology, and the consequences this hold in regards of user mobilisation and the effects of the intervention at the workplace. We report preliminary findings from four different workplaces, and with a total of 709 users. We contribute by discussing the importance of flexibility of the Avantas Aktiv script, how the script is accepted by some and rejected by others, and how social cohesion is both a result of and a premise for successful mobilisation of users. Finally, we point to future avenues for research

High-Performance Asynchronous Byzantine Fault Tolerance Consensus Protocol

In response to new and innovating blockchain-based systems with Internet of Things (IoT), there is a need for consensus mechanisms that can provide high transaction throughput and security, despite varying network quality. Honeybadger was the first practical, asynchronous Byzantine Fault Tolerance (BFT) consensus protocol, achieving high scalability and robustness without making any timing assumptions regarding the network. To improve the current asynchronous consensus protocols, we designed Asynchronous Byzantine Fault Tolerance (ABFT) consensus protocol through integrating threshold Elliptic Curve Digital Signature Algorithm (ECDSA) signatures and optimization of erasure coding parameters, as well as additional implementation-level optimizations. We implement a prototype of ABFT, and evaluate its performance at scale in a global WAN network and a network affected by asymmetric network degradation. Our results show that ABFT provides considerably higher performance, significantly lower computational overhead, and greater scalability than its predecessors. ABFT can reach up to 38.700 transactions per second in throughput. Furthermore, we empirically show that ABFT is unaffected by asymmetric network degradation within the fault threshold.acceptedVersio

Massey products and Linking

This master's thesis is focussed around investigating Massey products as tools for studying properties of links, in particular the Brunnian property. In the literature, there are only a few examples of the Massey product being used to study linking, none of which has any emphasis on links with the Brunnian property, except for computations for the Borromean rings. The result of the work is a number of thorough computations of Massey products in link complements, with the negative conclusion that the Massey product does not detect the Brunnian property

High-Performance Asynchronous Byzantine Fault Tolerance Consensus Protocol

In response to new and innovating blockchain-based systems with Internet of Things (IoT), there is a need for consensus mechanisms that can provide high transaction throughput and security, despite varying network quality. Honeybadger was the first practical, asynchronous Byzantine Fault Tolerance (BFT) consensus protocol, achieving high scalability and robustness without making any timing assumptions regarding the network. To improve the current asynchronous consensus protocols, we designed Asynchronous Byzantine Fault Tolerance (ABFT) consensus protocol through integrating threshold Elliptic Curve Digital Signature Algorithm (ECDSA) signatures and optimization of erasure coding parameters, as well as additional implementation-level optimizations. We implement a prototype of ABFT, and evaluate its performance at scale in a global WAN network and a network affected by asymmetric network degradation. Our results show that ABFT provides considerably higher performance, significantly lower computational overhead, and greater scalability than its predecessors. ABFT can reach up to 38.700 transactions per second in throughput. Furthermore, we empirically show that ABFT is unaffected by asymmetric network degradation within the fault threshold

Arbeidskraft i Nord

Source at https://www.sintef.no/projectweb/velferdsteknologi/publikasjoner/rapporter/Etterspurt kompetanse og rekrutteringsmønster i arbeidslivet endres i takt med den teknologiske og samfunnsmessige utviklingen. Rapporten tar for seg hvilke faktorer som påvirker hvordan bedrifter i sentrale nordnorske bransjer jobber med arbeidskraftbehov. Fire casebransjer og -bedrifter har deltatt i prosjektet. Gjennom en metodisk tilnærming, basert på databasert teoriutvikling, ble problemstillingen undersøkt ved hjelp av teoretiske og empiriske metoder. Funnene gjort gjennom kvalitative undersøkelser grupperer seg rundt kompetansebehov, rekrutteringsarbeid og endring i virksomheten som følge av digitalisering. Sted og attraktivitet er viktig i rekrutteringsarbeidet og flere benytter seg av sosiale medier som rekrutteringsplattform. Viktigheten av sosiale nettverk blir også trukket frem som en faktor i rekrutteringen for både norsk og utenlandsk arbeidskraft. Et gjennomgående behov som går på tvers av bransjer er digital kompetanse, og digitalisering vil påvirke bedriftenes fremtidige drift og omstillingsevne

High-Performance Asynchronous Byzantine Fault Tolerance Consensus Protocol

In response to new and innovating blockchain-based systems with Internet of Things (IoT), there is a need for consensus mechanisms that can provide high transaction throughput and security, despite varying network quality. Honeybadger was the first practical, asynchronous Byzantine Fault Tolerance (BFT) consensus protocol, achieving high scalability and robustness without making any timing assumptions regarding the network. To improve the current asynchronous consensus protocols, we designed Asynchronous Byzantine Fault Tolerance (ABFT) consensus protocol through integrating threshold Elliptic Curve Digital Signature Algorithm (ECDSA) signatures and optimization of erasure coding parameters, as well as additional implementation-level optimizations. We implement a prototype of ABFT, and evaluate its performance at scale in a global WAN network and a network affected by asymmetric network degradation. Our results show that ABFT provides considerably higher performance, significantly lower computational overhead, and greater scalability than its predecessors. ABFT can reach up to 38.700 transactions per second in throughput. Furthermore, we empirically show that ABFT is unaffected by asymmetric network degradation within the fault threshold

Arbeidskraft i Nord

Arbeidskraft i nord Etterspurt kompetanse og rekrutteringsmønster i arbeidslivet endres i takt med den teknologiske og samfunnsmessige utviklingen. Rapporten tar for seg hvilke faktorer som påvirker hvordan bedrifter i sentrale nordnorske bransjer jobber med arbeidskraftbehov. Fire casebransjer og -bedrifter har deltatt i prosjektet. Gjennom en metodisk tilnærming, basert på databasert teoriutvikling, ble problemstillingen undersøkt ved hjelp av teoretiske og empiriske metoder. Funnene gjort gjennom kvalitative undersøkelser grupperer seg rundt kompetansebehov, rekrutteringsarbeid og endring i virksomheten som følge av digitalisering. Sted og attraktivitet er viktig i rekrutteringsarbeidet og flere benytter seg av sosiale medier som rekrutteringsplattform. Viktigheten av sosiale nettverk blir også trukket frem som en faktor i rekrutteringen for både norsk og utenlandsk arbeidskraft. Et gjennomgående behov som går på tvers av bransjer er digital kompetanse, og digitalisering vil påvirke bedriftenes fremtidige drift og omstillingsevne. ISBN: 978-82-14-06451-3publishedVersio