${session.getAttribute("locale")} 5 Visual tools for analysing evolution, emergence, and error in data streams Wed 31 Jul 2019 15:28:38 AEST ]]> A 3D object encryption scheme which maintains dimensional and spatial stability Wed 27 Mar 2019 14:06:10 AEDT ]]> On the security of permutation-only image encryption schemes Wed 27 Mar 2019 14:05:36 AEDT ]]> Collecting health and exposure data in Australian olympic combat sports : Feasibility study utilizing an electronic system 160 contacts, athlete engagement with online tools was poor, with only 13% compliance across the 12-week period. No taekwondo or wrestling athletes were compliant. Despite low overall engagement, a large number of injuries or illness were recorded across 11 athletes who entered data—22 unique injuries, 8 unique illnesses, 30 recurrent injuries, and 2 recurrent illnesses. The most frequent injuries were to the knee in boxing (n=41) and thigh in judo (n=9). In this cohort, judo players experienced more severe, but less frequent, injuries than boxers, yet judo players sustained more illnesses than boxers. In 97.0% (126/130) of cases, athletes in this cohort continued to train irrespective of their health problems. Conclusions: Among athletes who reported injuries, many reported multiple conditions, indicating a need for health monitoring in Australian combat sports. A number of factors May have influenced engagement with the AMS, including access to the internet, the design of the system, coach views on the system, previous experiences with the system, and the existing culture within Australian combat sports. To increase engagement, there May be a requirement for sports staff to provide relevant feedback on data entered into the system. Until the Barriers are addressed, it is not feasible to implement the system in its current form across a larger cohort of combat athletes.]]> Wed 27 Mar 2019 14:04:58 AEDT ]]> The role of interoperable data standards in precision livestock farming in extensive livestock systems : A review Wed 27 Mar 2019 14:04:19 AEDT ]]> K-complex detection using a hybrid-synergic machine learning method Wed 24 Jul 2019 15:10:10 AEST ]]> A model of the circadian clock in the cyanobacterium Cyanothece sp. ATCC 51142 Wed 20 Mar 2019 12:10:03 AEDT ]]> Multiple comorbidities of 21 psychological disorders and relationships with psychosocial variables: A study of the online assessment and diagnostic system within a web-based population Wed 17 Jul 2019 14:33:32 AEST ]]> Hybrid metaheuristic approaches to the expectation maximization for estimation of the hidden markov model for signal modeling Wed 17 Jul 2019 14:15:35 AEST ]]> A novel motion classification based intermode selection strategy for HEVC performance improvement Wed 13 Mar 2019 09:32:12 AEDT ]]> Adaptive weighted non-parametric background model for efficient video coding Wed 12 Dec 2018 12:18:35 AEDT ]]> Knowledge based regulation of statistical databases Wed 11 Jul 2018 16:07:04 AEST ]]> Online alcohol interventions: A systematic review Wed 10 Oct 2018 04:06:50 AEDT ]]> Posttreatment attrition and its predictors, attrition bias, and treatment efficacy of the anxiety online programs Wed 10 Jul 2019 15:16:26 AEST ]]> iPod therefore 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problem Thu 21 Mar 2019 11:42:07 AEDT ]]> An adaptive borrow-and-return model for broadcasting videos Thu 21 Mar 2019 11:19:09 AEDT ]]> Virtual machine consolidation in cloud data centers using ACO metaheuristic C3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Thu 21 Mar 2019 11:09:27 AEDT ]]> A new scoring system in Cystic Fibrosis : Statistical tools for database analysis - A preliminary report Thu 20 Dec 2018 10:19:09 AEDT ]]> Diagnosing transformer winding deformation faults based on the analysis of binary image obtained from FRA signature Thu 18 Jul 2019 14:03:01 AEST ]]> Improved method to obtain the online impulse frequency response signature of a power transformer by multi scale complex CWT Thu 18 Apr 2019 14:49:52 AEST ]]> Detection of power transformer winding deformation using improved FRA based on binary morphology and extreme point variation Thu 18 Apr 2019 14:38:39 AEST ]]> Time-delay 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