What causes positive customer satisfaction in an ineffectual software development project? A mechanism from a process tracing case study

The customer role is crucial in agile information systems development (ISD). There is, however, a scarceness in research on how this role is enacted, and how its practice influences project outcome. In this longitudinal case study, an agile ISD project is followed with a particular focus on the customer organization’s participation, aiming to contribute to the understanding of how customers influence agile ISD projects. The data analysis follows a process tracing approach, a case study method where one aims to identify the causes and outcomes of any kind of process through the rigorous analysis of qualitative data. The analysis of the case shows that the low completion of the initial project requirements was caused by over-scoping and by an immature customer. Further, the customer’s acceptance of the outcome was caused by the agile practices introduced in the project. These helped to create a high customer’s sense of responsibility for the outcome, which worked as a mediator towards a positive acceptance of the delivery. The study contributes a mechanism for why agile projects may still be successful in light of low delivery. It is also a first case study in the information systems field explicitly using a process tracing approach

Interval probability propagation

AbstractBelief networks are tried as a method for propagation of singleton interval probabilities. A convex polytope representation of the interval probabilities is shown to make the problem intractable even for small parameters. A solution to this is to use the interval bounds directly in computations of the propagation algorithm. The algorithm presented leads to approximative results but has the advantage of being polynomial in time. It is shown that the method gives fairly good results

Gangfunksjon etter hjerneslag - er hastighet og symmetri relevante mål for opptreningen?

Innledning: De fleste personer som rammes av hjerneslag får problemer med gangfunksjonen i større eller mindre grad. Selvstendig gangfunksjon er nært knyttet til aktivitet og deltakelse på de fleste samfunnsområder, og er en viktig målsetning for personer som er rammet av slag. n Hoveddel: Artikkelen presenterer kunnskap fra vitenskapelige studier, og spørsmålet som stilles er hvorvidt økt symmetri og økt hastighet under gange er relevante mål for fysioterapi. Personer med slag i kronisk stadium (minimum 6 måneder etter slaget), går saktere enn friske og bruker opp til 1.5-2 ganger så mye energi ved samme ganghastighet. En langsom gange, i betydningen mindre automatisert, kan medvirke til at energikravet øker. Økt hastighet kan gi en mer energieffektiv gange gjennom en bedre motorisk koordinering av underekstremitene. Det er påvist positive effekter på økning av ganghastighet gjennom gangrelatert utholdenhetstrening og høyintensiv funksjonell styrketrening. Derimot er det mangelfull dokumentasjon på at styrke- og gangrelatert trening fører til varig økt symmetri mellom affisert og ikke affisert underekstremitet. n Avslutning: Økt ganghastighet alene er ikke tilstrekkelig for å oppnå større samfunnsmessig deltakelse. Det viktigste er ikke nødvendigvis å kunne forflytte seg raskere, men å kunne opprettholde en komfortabel ganghastighet med mindre muskulær anstrengelse. Sterkere muskler og større utholdenhet kan gi grunnlag for en mer energisparende gange. Dette kan i neste omgang gi større fleksibilitet med mulighet for tempoendringer ved beho

Acculturation experience of first generation Muslim immigrant women in a Canadian prairie city

This thesis explores first generation Muslim immigrant women’s acculturation experiences and strategies from a religious, cultural and gender perspective. It aims to increase our understanding of the diverse and confounding roles and expectations of their heritage culture and host Canadian culture. Qualitative interviews with eight married with children, English-speaking Muslim immigrant women who have lived in Canada for at least three years explored: (a) their overall experiences living in a Canadian Prairie city; (b) their experience transitioning from their role in the family in a traditional non-Western culture to their role in the family in an egalitarian Canadian culture; and (c) factors that hinder and facilitate their adaptation in Canada. Findings demonstrated that although women’s acculturation experiences and strategies are unique and dynamic, all women expressed the interconnectivity and significance of God, community and family in their lives. Women’s personal experiences and goals related to work, family, and community influence how and to what degree they negotiate and reconcile the diverse and confounding roles and expectations of their heritage and Canadian cultures. Their acculturation experiences are constantly evolving, and their adaptation in Canada is largely influenced by their daily experiences, including the supports they have and do not have both at home and in their local heritage and host communities. Women also face the central challenge of raising their children in a culture that promotes a set of values that compromises the transmission of their own core religious/cultural values. Thus, they employ strategies such as conscientiously modeling devotion to Islam through practice and teaching, restricting their children’s personal freedom and independence, and monitoring and limiting their children’s Canadian friendships, while increasing contact with their local heritage community. This research contributes to cross-cultural inquiry via a cultural comparison that established cultural aspects of women’s traditional heritage cultures, which was subsequently compared to Canadian culture as a tool for gauging cultural discrepancies. Future research may explore the whole family unit through a longitudinal lens to facilitate both the adaptation and integration of immigrants from collectivistic cultures into Canadian culture, and improved policies and programs that mark Canada as a pluralistic and egalitarian culture

Towards Ontological Support for Journalistic Angles

Journalism relies more and more on information and communication technology (ICT). New journalistic ICT platforms continuously harvest potentially news-related information from the internet and try to make it useful for journalists. Because the information sources and formats vary widely, knowledge graphs are emerging as a preferred technology for integrating, enriching, and preparing journalistic information. The paper explores how journalistic knowledge graphs can be augmented with support for news angles, in order to help journalists detect news-worthy events and present them in ways that will interest the intended audience. We argue that finding newsworthy angles on news-related information is important as an example of a more general problem in information science: that of finding the most interesting events and situations in big data sets and presenting those events and situations in the most interesting ways.acceptedVersio

Construction of a relevance knowledge graph with application to the LOCAL news angle

News angles are approaches to journalism content often used to provide a way to present a new report from an event. One particular type of news angle is the LOCAL news angle where a local news outlet focuses on an event by emphasising a local connection. Knowledge graphs are most often used to represent knowledge about a particular entity in the form of relationships to other entities. In this paper we see how we can extract a knowledge sub graph containing entities and relevant relationships that are connected to the locality of a news outlet. The purpose of this graph is to use it for automated journalism or as an aid for the journalist to find local connections to an event, as well as how the local connection relate to the event. We call such a graph a relevance knowledge graph. An algorithm for extracting such a graph from a linked data source like DBpedia is presented and examples of the use of a relevance graph in a LOCAL news angle context are provided.publishedVersio

Towards an automated journalism framework for social data monitoring

Presented at: Nordic AI young researcher symposium, Oslo, 14.11. - 15.11.22News and information dissemination have long been a vital human practice. Concurrent with the traditional media channels such as radio and television, online social networks (OSNs), are regarded as the new generation of media that seem to have the ability to compete with traditional media. Millions of individuals around the world can communicate breaking news on social media platforms during the hours after midnight. The spread of misinformation and disinformation aside, the process of publishing news on OSNs, to a very good extent, happens more openly and unbiasedly. Automated journalism or according to [1] “the auto generation of journalistic stories through software and algorithms, without any human input”, can be used in newsrooms to supplement or replace traditional journalism in a variety of ways, such as providing real-time reporting of events or generating stories from data that would be otherwise difficult to mine. Due to their real-time and open nature, OSNs, particularly Twitter, are among the greatest candidate data sources to be explored in this context. MediaFutures, Centre for Research-Based Innovation (SFI), is a research centre in Bergen, Norway, which is a consortium of the most important media players in Norway and beyond. The centre is hosted and lead by the University of Bergen’s Department of Information Science and Media Studies. In this research, in collaboration with MediaFuture SFI, we are developing a platform that can assist journalists in newsrooms in real time and enables them to easily obtain and monitor their desired newsworthy content from the mass volume of unverified content from Twitter platform. AI techniques have been applied for analysing social media data but many of them do not function in real time. In MediaFuture SFI we are involved in developing innovative tools which could be used by the journalists in the newsroom daily, secondly, most of prior works, either focus on collecting, filtering, and analysing tweets using predefined metrics [2] (such as number of replies, likes, etc.) or are only focused on analysing tweets’ content [3][4]. Considering the lack of a comprehensive framework suited to the needs of journalists, we present our own visual analytical framework that is not only based on information retrieval from Twitter but also enriched by machine learning and network science. In this work, we intend to use state of the art techniques such as community detection, influential node identification and monitoring, fake news, deepfake and cheapfake detection, etc