Upravljački algoritam za podupravljane mehaničke sustave s uključenom dinamikom pogona

U ovom radu izvodi se opći upravljački algoritam za istodobno stabiliziranje i praćenje trajektorija podupravljanih nelinearnih mehaničkih sustava (UNMS) s električnim, pneumatskim i hidrauličkim pogonima (aktuatorima). Istodobna stabilizacija i praćenje trajektorija odnosi se na stupnjeve slobode gibanja sustava, a obuhvaćaju se neholonomni sustavi drugog reda i sustavi sa spregom ulaznih veličina. Algoritam rješava probleme koji nastaju zbog podupravljanosti, zanemarivanja dinamike pogona i zanemarivanja statičkog trenja. S njim su poboljšane značajke zatvorenog upravljačkog kruga u odnosu na sustave sa zanemarenom dinamikom pogona i/ili zanemarenim statičkim trenjem kakvi se često koriste. Rješavanje ovakvih problema zahtijeva upravljačke algoritme temeljene na regulatorima s promjenjivom strukturom. Matematička jednostavnost novo uvedenog algoritma omogućuje laku ugradnju u računalne programe, pa je algoritam pogodan za realizaciju u praksi. Značaj ovog istraživanja leži u upravljačkom zakonu koji svojom uporabom omogućuje upravljanje proizvoljno odabranim stupnjevima slobode gibanja sustava s ciljem zadovoljenja kvalitativnih značajki regulacije. To rezultira stabilnim i robusnim ponašanjem podupravljanih sustava

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Bowdoin Orient v.98, no.1-26 (1968-1969)

https://digitalcommons.bowdoin.edu/bowdoinorient-1960s/1009/thumbnail.jp

Epidemiology of Injury in English Women's Super league Football: A Cohort Study

INTRODUCTION: The epidemiology of injury in male professional football has been well documented (Ekstrand, Hägglund, & Waldén, 2011) and used as a basis to understand injury trends for a number of years. The prevalence and incidence of injuries occurring in womens super league football is unknown. The aim of this study is to estimate the prevalence and incidence of injury in an English Super League Women’s Football squad. METHODS: Following ethical approval from Leeds Beckett University, players (n = 25) signed to a Women’s Super League Football club provided written informed consent to complete a self-administered injury survey. Measures of exposure, injury and performance over a 12-month period was gathered. Participants were classified as injured if they reported a football injury that required medical attention or withdrawal from participation for one day or more. Injuries were categorised as either traumatic or overuse and whether the injury was a new injury and/or re-injury of the same anatomical site RESULTS: 43 injuries, including re-injury were reported by the 25 participants providing a clinical incidence of 1.72 injuries per player. Total incidence of injury was 10.8/1000 h (95% CI: 7.5 to 14.03). Participants were at higher risk of injury during a match compared with training (32.4 (95% CI: 15.6 to 48.4) vs 8.0 (95% CI: 5.0 to 10.85)/1000 hours, p 28 days) of which there were three non-contact anterior cruciate ligament (ACL) injuries. The epidemiological incidence proportion was 0.80 (95% CI: 0.64 to 0.95) and the average probability that any player on this team will sustain at least one injury was 80.0% (95% CI: 64.3% to 95.6%) CONCLUSION: This is the first report capturing exposure and injury incidence by anatomical site from a cohort of English players and is comparable to that found in Europe (6.3/1000 h (95% CI 5.4 to 7.36) Larruskain et al 2017). The number of ACL injuries highlights a potential injury burden for a squad of this size. Multi-site prospective investigations into the incidence and prevalence of injury in women’s football are require