The significance of Traveler's Route Knowledge for Choice of commuting mode of transport

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Travelling in a city is an essential part of everyone’s life, whether it is the routine daily commute or navigating to a previously unknown place, and can be accomplished with a variety of means of transport. This thesis explores how personal, first-hand route knowledge influences choice of mode of transport. This is motivated by the premise that human-oriented approach for computer systems design can be of significant benefit to the user. Public (bus, train, tram, metro) and private (bicycle, car, on foot) means of transport are considered and compared. Collected survey data analysed with a logistic regression method does not show any relationship between route knowledge and choice of mode of transport

Earliest-deadline-first service in heavy-traffic acyclic networks

This paper presents a heavy traffic analysis of the behavior of multi-class acyclic queueing networks in which the customers have deadlines. We assume the queueing system consists of J stations, and there are K different customer classes. Customers from each class arrive to the network according to independent renewal processes. The customers from each class are assigned a random deadline drawn from a deadline distribution associated with that class and they move from station to station according to a fixed acyclic route. The customers at a given node are processed according to the earliest-deadline-first (EDF) queue discipline. At any time, the customers of each type at each node have a lead time, the time until their deadline lapses. We model these lead times as a random counting measure on the real line. Under heavy traffic conditions and suitable scaling, it is proved that the measure-valued lead-time process converges to a deterministic function of the workload process

The impact of reneging in processor sharing queues

We investigate an overloaded processor sharing queue with renewal arrivals and generally distributed service times. Impatient customers may abandon the queue, or renege, before completing service. The random time representing a customer’s patience has a general distribution and may be dependent on his initial service time requirement. We propose a scaling procedure that gives rise to a fluid model, with nontrivial yet tractable steady state behavior. This fluid model captures many essential features of the underlying stochastic model, and we use it to analyze the impact of impatience in processor sharing queues. We show that this impact can be substantial compared with FCFS, and we propose a simple admission control policy to overcome these negative impacts

Hvordan påvirker sosiale medier psykisk helse hos barn og ungdom?

Dette bachelorprosjekt undersøker problemstillingen: Hvordan påvirker sosiale medier psykisk helse hos barn og ungdom? Dette tema er relevant for sosialt arbeid fordi det gir innsikt i ungdommens forhold til sosiale medier og hvilke risikofaktorer de kan ha for utviklingen av psykiske plager. Dette tema er viktig forstå bedre, for å kunne identifisere disse, slik at jeg som sosialarbeider kan veilede dem i en bedre retning. Som metode bruker jeg litteraturstudie, og ser på både kvantitative og kvalitative studier. Her bruker jeg studier fra både Norge og andre vestlige, industrialiserte land. I teoridelen presenterer jeg hvilken relasjon sosiale medier har på psykisk helse, men også hvordan psykisk helse påvirker bruken av sosiale medier. I diskusjonsdelen undersøker jeg medierende faktorer for mediebruk og psykisk helse. Jeg identifiserer og legger vekt på følgende risikofaktorer: selvtillit, sosiale ferdigheter, søvn og fysisk aktivitet. I konklusjonen drøfter jeg forbedringsmuligheter til oppgaven min. Nøkkelord: Angst, Barn, Depresjon, Ungdom, Sosiale medier, Sosialt Arbei