Deakin University

About: Deakin University is a education organization based out in Burwood, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 12118 authors who have published 46470 publications receiving 1188841 citations. The organization is also known as: Deakin.

Management of Tendinopathy

Abstract: Overuse disorders of tendons, or tendinopathies, present a challenge to sports physicians, surgeons, and other health care professionals dealing with athletes. The Achilles, patellar, and supraspinatus tendons are particularly vulnerable to injury and often difficult to manage successfully. Inflammation was believed central to the pathologic process, but histopathologic evidence has confirmed the failed healing response nature of these conditions. Excessive or inappropriate loading of the musculotendinous unit is believed to be central to the disease process, although the exact mechanism by which this occurs remains uncertain. Additionally, the location of the lesion (for example, the midtendon or osteotendinous junction) has become increasingly recognized as influencing both the pathologic process and subsequent management. The mechanical, vascular, neural, and other theories that seek to explain the pathologic process are explored in this article. Recent developments in the nonoperative management of chronic tendon disorders are reviewed, as is the rationale for surgical intervention. Recent surgical advances, including minimally invasive tendon surgery, are reviewed. Potential future management strategies, such as stem cell therapy, growth factor treatment, and gene transfer, are also discussed.

Federated Learning for Internet of Things: A Comprehensive Survey

Abstract: The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may not be feasible in realistic application scenarios due to the high scalability of modern IoT networks and growing data privacy concerns. Federated Learning (FL) has emerged as a distributed collaborative AI approach that can enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices without the need for data sharing. In this article, we provide a comprehensive survey of the emerging applications of FL in IoT networks, beginning from an introduction to the recent advances in FL and IoT to a discussion of their integration. Particularly, we explore and analyze the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing, and IoT privacy and security. We then provide an extensive survey of the use of FL in various key IoT applications such as smart healthcare, smart transportation, Unmanned Aerial Vehicles (UAVs), smart cities, and smart industry. The important lessons learned from this review of the FL-IoT services and applications are also highlighted. We complete this survey by highlighting the current challenges and possible directions for future research in this booming area.

Network Traffic Classification Using Correlation Information

Abstract: Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine learning techniques to flow statistical feature based classification methods. The nearest neighbor (NN)-based method has exhibited superior classification performance. It also has several important advantages, such as no requirements of training procedure, no risk of overfitting of parameters, and naturally being able to handle a huge number of classes. However, the performance of NN classifier can be severely affected if the size of training data is small. In this paper, we propose a novel nonparametric approach for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approach and its performance benefit from both theoretical and empirical perspectives. A large number of experiments are carried out on two real-world traffic data sets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples.

Moving from task‐oriented to learning‐oriented strategies on school excursions to museums

Abstract: Museums are best considered as venues for informal learning and yet the authors' observations were that most school classes that visit museums are restricted and structured, the students not being provided with optimal opportunities to learn in an informal manner. Although research has addressed some features of successful school group visits to museums, such as preparation and orientation, emphasis on first-hand experience, and use of worksheets, there has been little research on the role of the class teacher in facilitating learning during excursions. This study investigated strategies used by class teachers before, during, and following excursions to two venues in Sydney, Australia, offering opportunities for learning science in an informal setting. The sample chosen for the study comprised 12 school groups involving 29 teachers and 735 students in 30 classes ranging from grade 5 to grade 10. Data were collected through observation and interviews before, during, and 2–3 weeks after the visit. The results indicate that class teachers used mainly task-oriented teaching practices and made little effort to link topics being studied at school and the museum. Little congruence was apparent between the practices observed and what the literature suggested for effective planning and management of school excursions. The authors propose a framework to guide teachers in planning learning-oriented excursions based on a synthesis of knowledge of natural learning behaviors exhibited by family groups in museums and lessons from constructivist theories of learning, together with strategies reported in the literature and confirmed by this study as contributing to learning on school excursions to museums. © 1997 John Wiley & Sons, Inc. Sci Ed81:763–779, 1997.