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In bepaalde single-core configuraties met één processor, b.v. embedded control systems zoals robotic applications die uit vele korte processen bestaan, kunnen de context switches van een proces een aanzienlijke hoeveelheid van de beschikbare processing power verbruiken. Het verminderen van het aantal context switches vermindert de executietijd en verhoogt daardoor de prestaties van de toepassing. Bovendien is de end-to-end executietijd van de processen langer dan strict noodzakelijk, b.v. omdat de processen moeten wachten op controllers die een taak uitvoeren. Door de regels voor synchrone communicatie via kanalen in de procesalgebraïsche specificatietaal Communicating Sequential Processes te versoepelen, kunnen we de end-to-end executietijd verkorten. In ons onderzoek definiëren we verschillende graafproducten, bewijzen we dat deze producten een prestatiewinst opleveren (onder bepaalde voorwaarden) en we werken de numerieke en combinatorische aspecten van deze graafproducten uit.
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Injuries and lack of motivation are common reasons for discontinuation of running. Real-time feedback from wearables can reduce discontinuation by reducing injury risk and improving performance and motivation. There are however several limitations and challenges with current real-time feedback approaches. We discuss these limitations and challenges and provide a framework to optimise real-time feedback for reducing injury risk and improving performance and motivation. We first discuss the reasons why individuals run and propose that feedback targeted to these reasons can improve motivation and compliance. Secondly, we review the association of running technique and running workload with injuries and performance and we elaborate how real-time feedback on running technique and workload can be applied to reduce injury risk and improve performance and motivation. We also review different feedback modalities and motor learning feedback strategies and their application to real-time feedback. Briefly, the most effective feedback modality and frequency differ between variables and individuals, but a combination of modalities and mixture of real-time and delayed feedback is most effective. Moreover, feedback promoting perceived competence, autonomy and an external focus can improve motivation, learning and performance. Although the focus is on wearables, the challenges and practical applications are also relevant for laboratory-based gait retraining.
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Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.
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Introduction: To determine if athletes with coordination impairment (CI) can continue playing wheelchair rugby (WR), while an evidence-based classification system, including impairment tests for CI is not yet available. This is a defensible practise if they show similar activity limitations as athletes with other eligible impairment types (OI) within the same sports class. Methods: Standardised activities were measured in 58 elite WR athletes; 14 with CI and 44 with OI. Wheelchair activities consisted of 20-meter sprint, 12-meter sprint with full stop, intermittent sprint (3-meter sprint, stop, 3-meter sprint, stop, 6-meter sprint with full stop), sprint-curve-slalom-curve, turn on the spot 180°, turn on the spot 90°, stop, turn 90°in the same direction, X-test (short circuit with sharp turns) without the ball. Ball activities consisted of maximal throwing distance, precision throwing short (25% of maximum throw) and long (75% of maximal throw) distance and X-test with the ball (pick-up the ball and dribble whilst pushing). Descriptive statistics were used and Spearman’s Rank correlation was assessed for athletes with CI and OI for each outcome measure. Differences between athletes with CI and OI were assessed using a Mann-Whitney U test. Results: Most activities showed a high correlation with the athlete class in both athletes with CI and athletes with OI. Furthermore, outcome measures of athletes with CI overlapped with athletes with OI in the same sports class for all activities. There was a trend for worse performance in athletes with CI in turn on the spot 90°, stop, turn 90°in the same direction, the short distance one handed precision throw (P 0.11)and in the X-test with the ball (P 0.10). Discussion: Despite the current lack of evidence based impairment tests for CI, it is a defensible practise to not exclude athletes with CI from WR with the current classification system. The trends for differences in performance that were found can support athletes and coaches in optimising performance of athletes with CI.
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Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.
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Pupils with problem behaviours are challenging teachers as well as they are a challenge to teachers to find a way to teach them what curricula prescribe. Especially middle school teachers and those working in schools for special education are con-fronted with pupils with behavioural problems. There, teachers experience hard classes and find it difficult to fit classroom management with the pupils needs. In this paper we focus on two questions: is pullout an effective treatment to handle problem behaviour? do special classes have advantages for pupils who were pulled out or not? First we present a theoretical framework about pullout and we explicit our expectations. Then we describe the methods of our research in schools for special educa-tion during two months for students (N=759) when pulled out. We examined the reason of pulling out and the interactions during the process outside the classroom and the return. Because teachers noticed date and time of the removal, it was possible to use survival analysis to show the effects of the treatment. We found that pullout occurs under quite different circumstances, so the treatment integrity is a problem because deficiency of the intervention leads to repeated pullout. The data also showed that special classes for pupils who are pulled out seem to trigger and/or in-tensify the process itself. So, we conclude that these classes have a contra-productive effect.
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Reading and writing is modelled in CSP using actions containing the symbols ? and !. These reading actions and writing actions are synchronous, and there is a one-to-one relationship between occurrences of pairs of these actions. In the CPA conference 2016, we introduced the half-synchronous alphabetised parallel operator X ⇓ Y , which disconnects the writing to and reading from a channel in time. We introduce in this paper an extension of X ⇓ Y , where the definition of X ⇓ Y is relaxed; the reading processes are divided into sets which are set-wise asynchronous, but intra-set-wise synchronous, giving full flexibility to the asynchronous writes and reads. Furthermore, we allow multiple writers to the same channel and we study the impact on a Vertex Removing Synchronised Product. The advantages we accomplish are that the extension of X ⇓ Y gives more flexibility by indexing the reading actions and allowing multiple write actions to the same channel. Furthermore, the extension of X ⇓Y reduces the end-to-end processing time of the processor or coprocessor in a distributed computing system. We show the effects of these advantages in a case study describing a Controlled Emergency Stop for a processor-coprocessor combination.
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The aim of this study was to assess the association between prescription changes frequency (PCF) and hospital admissions and to compare the PCF to the Chronic Disease Score (CDS). The CDS measures comorbidity on the basis of the 1-year pharmacy dispensing data. In contrast, the PCF is based on prescriptionchanges over a 3-month period. A retrospective matched case–control design was conducted. 10.000 patients were selected randomly from the Dutch PHARMO database, who had been hospitalized (index date) between July 1, 1998 and June 30, 2000. The primary study outcome was the number of prescription changes during several three-month time periods starting 18, 12, 9, 6, and 3 months before the index date. For each hospitalized patient, one nonhospitalized patient was matched for age, sex, and geographic area, and was assigned the same index date as the corresponding hospitalized patient.We classified four mutually exclusive types of prescription changes: change in dosage, switch, stop and start.
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