Østfold University College

About: Østfold University College is a education organization based out in Halden, Norway. It is known for research contribution in the topics: Context (language use) & Health care. The organization has 438 authors who have published 1213 publications receiving 12510 citations. The organization is also known as: HiØ.

The Role of Trunk Training for Physical Fitness and Sport-Specific Performance. Protocol for a Meta-Analysis

Abstract: The trunk (core) muscles are involved in daily functions (i. e., stabilizing the body in everyday tasks) and force generation of the limbs during athletic tasks such as kicking, throwing, or running. Even though trunk training is a popular means for improving physical fitness and athletic performance, the direct relationship of improved trunk function (i.e., stability, strength, or endurance), fitness and sport-specific performance is not conclusive. The aim of this proposed review is to evaluate the effects of trunk training on physical fitness and sport-specific performance, and to examine potential subject-related (e.g., age, sex) and trunk training-related moderator variables (e.g., training period, training frequency) for performance changes. We will conduct a systematic literature search in Web of Science, MEDLINE (via EBSCO) and SportDiscus. Relevant papers will be screened independently by two reviewers in two stages: (1) title and abstracts and (2) the full text of the remaining papers. A third reviewer will resolve possible disagreements. Data extraction and risk of bias of the included studies will be performed in addition to the PEDro scoring to judge the quality of the studies. A meta-analysis will be conducted to determine the efficacy of trunk training to increase physical fitness and sport-specific performance measures. In addition, subgroup univariate analyses were computed for subject-related (i.e., age, sex, performance level) and training-related moderator variables (i.e., training period, training frequency, training sessions, session duration). The results of this proposed systematic review and meta-analysis will assess the effects of trunk training on physical fitness and sport-specific and identify which subject-related and training-related moderate variables of trunk training modality might be beneficial for performance gains. This knowledge has potential importance for athletes and coaches in sports.

A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost

Abstract: The Internet of Things (IoT) will connect more than 50 billion heterogenous devices around the world by 2020. As an Ultra Dense Network (UDN), which needs high resources to be established, different technologies are emerging to improve the efficiency of IoT. Fog is a new phenomenon that uses close powerful nodes to help end users achieve reduced delays, optimize resource consumption, and improve the quality of service. In techniques such as routing, clustering, caching, etc., nodes need to select pairing nodes or the next hop nodes which are used to help nodes transfer or process data. In this paper, a new mathematical fuzzy-based method is proposed to evaluate the suitability of a node’s neighbors. Nodes broadcast their information to inform neighbors about their situations, and each node compares itself to its neighbors, broadcasting a score that shows its tendency to be a pairing node. The proposed method is application-agnostic and can be used in different techniques regarding parameters that are being evaluated. A fuzzy method is used to integrate the parameters and calculate the score. As a new attitude, we use the XGBoost algorithm to extract the fuzzy rules from examples. After receiving the score, another fuzzy method is used to give other eligible neighbors the chance to be the next hop due to support network load balancing. Riverbed Modeler, MATLAB and Python are used to evaluate the node assessment model.

Hva arbeider tidligere it-studenter ved høgskolen i østfold med, og hvor relevant har utdanningen deres vært for na?værende jobbsituasjon?

Abstract: rtikkelen beskriver resultatene fra en undersokelse som er gjort va?ren 2017 blant IT-studentene som avsluttet ved Hogskolen i Ostfold 2011-2016. Temaene som ble tatt opp omfattet • sokeprosessen/hvordan og hvor raskt studentene fikk jobb • jobbinnhold / hva arbeider de tidligere studentene med • sammenhengen mellom studier og jobbinnhold • for de studentene som ikke fullforte: hva var a?rsaken til at de ikke fullforte IT-studiet. Undersokelsen har ba?de en kvantitativ del og en kvalitativ del. Metodisk bygger den ba?de pa? kategoriseringer som er gjort fra en av bransjeforeningene (IKT-Norge) og pa? ulike studentundersokelser (NOKUT, NIFU), og det gjores en kort sammenligning med disse. Det er ogsa? gjort andre metodiske grep som beskrives. Undersokelsen viser at de aller fleste som svarte fikk jobb fort (0-3 ma?neder). Funnene indikerer dermed studiets relevans for senere jobbsituasjon. Svarene viser en sterk sammenheng mellom HiOs studier og de ulike fagomra?dene som respondentene jobber med. Ser vi pa? de ulike fagomra?dene innen IT, uavhengig av retning, scorer programmering, databaser og prosjektarbeide/ledelse hoyest, men ogsa? systemarkitektur, support og systemdrift. De 4 IT-Bachelor-studiene som studeres har en faglig bredde, fra vekt pa? IT-teknisk via programmering til IT-organisasjon og naeringsliv og medieproduksjon. Vi finner et klart samsvar mellom de ulike studiene og hvilke typer IT-jobber som studentene fa?r etterpa?. Generelt viser funnene ogsa? at studiene var «Litt relevant» eller «Svaert relevant» (de to hoyeste kategoriene, som til sammen hadde 78%, likt fordelt mellom disse to). Tilsvarende studeres relevans av enkeltfag, ba?de direkte nyttig og nyttig som bakgrunn. For de som ikke fullforte, ser vi at det for de fleste var personlige grunner som var den viktigste a?rsaken til at de avsluttet studiet underveis. Totalt sett gir resultatene ny innsikt i sammenhengen mellom IT-studier og jobbinnhold, noe som kan vaere nyttig ba?de for hogskoler/universiteter og for arbeidsliv.

Adapting a learning tool for specialized nursing

Abstract: Purpose – Nursing has for a long time used a variety of technological tools to improve and support patient care. Tool use changes knowledge processes, offering opportunities to explore processes of specialization in this field. The purpose of this paper is to report from a collaborative process to achieve shared meaning potential while adapting a generic learning tool to meet learning needs of specialized nursing. A complex chain of actions, interactions and negotiations during the adaptation process is disentangled. The paper draws from the theoretical construct known as trajectories of participation. Design/methodology/approach – The method employed in data analysis is interaction analysis, allowing detailed studies of the actions represented in the participants' intersecting trajectories. Findings – The analysis shows how project members seek to combine different modes of knowledge when they sort out and establish shared meaning potential. Typically the negotiations start with a concrete problem arisin...

Assessing Professional Skills in a Multi-scale Environment by Means of Graph-Based Algorithms

Abstract: The present paper introduces a study of different techniques to assess professional skills in social networks and to align those user skills with existing multi-scale knowledge classifications Currently both job seekers and talent hunters are looking for new and innovative techniques to filter jobs and candidates as well as candidates are also trying to improve and make more attractive their profiles In this environment it is necessary to provide new techniques to assess the quality of professional skills depending on user's activity and to compare with existing scales To do so some relevant graph-based techniques such as the HITS and the SPEAR algorithms have been used for calculating the confidence of a certain user in a particular skill Moreover a new re-interpretation of the SPEAR algorithm, called Skill rank, is introduced to take advantage of user's behavior and history A major outcome of this approach is that expertise and experts can be detected, verified and ranked using a suited trust metric The paper also presents a validation of the Skill rank accuracy by means of a sound qualitative and quantitative comparison with existing approaches based on the opinions of a panel of experts (3) on a real dataset (created using the Linked in API) and two different scales Although results show in general low values of accuracy (close to 50% of correct classified skills), the Skill rank technique is more accurate than other techniques to align a user skill in a certain scale of knowledge Finally some discussion, conclusions and future work are also outlined