18624 research outputs found
Sort by
My personal, professional, and academic journey and lived experience with domestic violence
No full textRegardless of its definition or perception, intimate partner, domestic, or family violence is a crime and remains a societal scourge around the world. Some people grow up in loving, stable homes while others are raised in an environment filled with violence, rage, fear, dysfunction, and toxicity. In the household I was raised in, discipline always came in the form of verbal and physical violence which was considered “the norm.” My personal development from infancy and into early adulthood was chaotic and destructive and I had no positive male role model in my life. I became needy, insecure, nihilistic, and angry with everyone and everything around me; I constantly failed in my own intimate and personal relationships. Academically, I was a below average student; professionally, I was undereducated with no advancement potential and I faced a life of perpetual failure. Now, upon reflection, I am convinced that my lived experience with domestic violence very nearly doomed me a cycle of failure. When I became a police officer, I used my personal experience with domestic violence to empathize with the victim; to be her champion. My goal was to become that officer who understood domestic violence, to bring her abuser to justice, and free her from being constantly abused. Later in my policing career, I wanted to transfer that personal and professional knowledge into a doctoral study and become a respected scholar/practitioner. © 2024 by Springer Nature Singapore
Wheeled mobility device stability on public buses using semi-active containment systems
No full textPeople who rely on wheeled mobility devices (WhMDs) often face challenges securing their WhMD on public transportation. Inadequate securement can cause a WhMD to slide or tip during transit, posing significant safety risks to both WhMD users and their fellow passengers. This thesis investigates the ability of two semi-active containment systems, the Mobility Device—Containment On Bus Options (MD–COBO) and Mobility Device—Mini Containment On Bus Options (MD–Mini-COBO), to enhance the safety of WhMDs on public buses. Both the MD–COBO and MD–Mini-COBO include a lateral excursion barrier (LEB), a forward excursion barrier (FEB) and two mobility device tethers. The MD–Mini-COBO features a smaller LEB design. Study 1 presents a methodology for validating the accuracy and reliability of a simulation model for the movement of WhMDs on buses using MSC Adams software. This was assessed by comparing displacement and acceleration data from simulated and real- world scenarios, demonstrating the validity of the simulation models. In Study 2, the MSC Adams simulation environment was used to analyse the efficacy of the extendable trombone-style LEB used in the MD–COBO, the extendable D-shape LEB used in the MD–Mini-COBO and the mobility device tethers. The aim of the analysis was to determine the acceleration point at which lateral sliding and tipping would occur and the forces exerted on the LEB by a sliding or tipping WhMD. Six commercially available WhMDs were simulated to highlight the effect of WhMD characteristics on sliding and tipping thresholds. The study confirms the effectiveness of mobility device tethers in reducing lateral sliding and tipping. The forces generated during sliding and tipping events depend on occupant weight, WhMD design and WhMD distance from the LEB.Masters of Engineering Scienc
Academic-industry divide: Australian video games sector
Get PDFEfforts in communication, collaboration and knowledge transference between industry and academia in the video game development sector have been limited, which has led to what is commonly termed the “academic–industry divide.” This thesis contends that this divide encompasses multifaceted issues beyond mere collaboration or knowledge transfer interactions, which is a perspective that has not been fully explored by previous studies. Identifying and understanding the factors that have perpetuated this divide, especially within the video gaming field in Australia, has been insufficiently addressed. The aim of this research study was to fill this gap by investigating the question: “How can the Academic–Industry divide within the Australian video game sector be characterised?” Employing mixed-method research using the concurrent triangulation strategy, the study included a quantitative survey of 103 participants and qualitative interviews with 16 individuals, who represented academia and industry as well as individuals who worked in a dual role bridging the sectors. Utilizing Kelly’s personal construct theory and Homans’ social exchange theory, this research study provided original insights that explained concepts within the facets of the framework that will be introduced in this thesis. The framework delineates the divide’s multifaceted nature across three key areas: communication, collaboration, and knowledge transference, which also inform the analysis of the divide’s impact on the Australian video-gaming industry. Key findings highlighted that time constraints were the primary barrier, followed by perceptions of value, limited awareness between communities, and systemic issues involving government bodies, university management, and funding agencies. This thesis concludes with actionable recommendations for all stakeholders that have the intention of facilitating collaboration and effectively bridging the divide.Doctor of Philosoph
Understanding mud rush hazards in sublevel caving mines : a geotechnical review
No full textSublevel caving (SLC) mining operations are inherently susceptible to the sudden onset of mud rushes, posing significant safety and operational challenges. Understanding the complex dynamics governing mud rush events is vital for effective risk management and the safe operation of mining activities. This study presents a comprehensive review of the geomechanics associated with mud rushes in SLC mines, aiming to strengthen understanding, enhance mitigation strategies, and outline future research directions. The review explores critical aspects including hydrogeological influences, rock mass behaviour, caving dynamics, mud characteristics, monitoring methodologies, physical and numerical modelling approaches, and effective mitigation measures. Each approach offers distinctive advantages and challenges, contributing to a thorough understanding of the complex processes involved in caving activities. Drawing upon industry experience and learned research, the review integrates key findings, identifies knowledge gaps, and proposes opportunities for further investigation. By interpreting the sophisticated relationship of geomechanical factors contributing to mud rush occurrences, this review seeks to provide vital understandings for mining engineers, geoscientists, and safety professionals involved in SLC operations. The review also highlights the importance of ongoing research and monitoring to enhance predictive capabilities and develop effective mitigation strategies adapted to specific geological and operational conditions. Ultimately, the review highlights the importance of interdisciplinary collaboration and ongoing research efforts to mitigate mud rush risks and ensure the safe, sustainable, and efficient operation of underground mining projects
Leveraging meteorological data and machine learning for improved rainfall forecasting in Australia
No full textThis study explores the application of machine learning techniques to predict rainfall in Australia, addressing the challenges posed by the country’s highly variable climate. Utilizing a comprehensive dataset spanning approximately 10 years of daily weather observations from multiple Australian locations, we implemented and compared six machine learning models: Random Forest, XGBoost, Logistic Regression, K-Nearest Neighbors (KNN), Artificial Neural Network (ANN) Classifier, and Naive Bayes. The models were evaluated on their ability to predict the binary outcome of rainfall occurrence for the following day. Our results demonstrate that ensemble methods, specifically Random Forest and XGBoost, achieved the highest accuracy at 86%, closely followed by Logistic Regression at 85%. All models showed stronger performance in predicting non-rainy days compared to rainy days, reflecting the dataset’s inherent class imbalance. The ANN Classifier exhibited the highest recall for rain prediction, suggesting its potential utility in identifying possible rainfall events. ©2024 IEEE
Limitations of sewer network modelling software and the use of artificial neural networks models to overcome these limitations
No full textExcessive flows due to inflow and infiltration (I&I) in sewer networks contribute to hydraulically overloaded nnetworks. Precise prediction of sewer flows is important for water utilities to effectively manage and maintain their hydraulically overloaded sanitary sewer networks. Water utilities widely use physics based software packages to predict sewer network flows under various rainfall conditions. A widely used software package was utilised to build and calibrate a sewer network model using best practise Australian guidelines for the case study catchment within the Ballarat sewer network, Victoria, Australia. The findings from this study indicated that software can predict total sewer flows with reasonable accuracy using the Wallingford or triangular hydrograph (RTK) hydrological methods. However, the software cannot replicate the dynamic nature of the complex hydrological process of sewer network flow generation over an extended time nor reliably separate the sewer network flow components. Due to the limitations of the commercially available software, an Artificial Neural Network (ANN) model was developed to predict the sewer flows accurately. Several parameters known to influence sewer flow generation were incrementally introduced to an ANN model to understand their relative importance towards the total sewer flow. Results indicated that the ANN model predicted sewer flows with very high accuracy. They identified that sewer network hydrology is dependent on soil moisture, which is the crucial parameter related to the sewer network hydrology. The ANN model can also provide insights into the sewer network catchment hydrology's dynamic and complex nature. This study has shown that ANN models can be very complementary to commercially available software in helping to understand the design and operational challenges of sewer networks. © 2024 National Committee on Water Engineering, Engineers Australia
Consistency checking for refactoring from coarse-grained locks to fine-grained locks
No full textRefactoring for locks is widely used to improve the scalability and performance of concurrent programs. However, when refactoring from coarse-grained locks to ¯ne-grained locks, the behavior of concurrent programs may be changed. To this end, we present LockCheck, a consistency-checking approach based on the parallel extended ¯nite automaton for ¯ne-grained locks. First, we model the critical sections of concurrent programs through control °ow analysis and dependency analysis. Second, we sequentialize the concurrent programs to get all the possible transition paths. Furthermore, it reduces the exploration of the redundant paths using partial order theory to obtain the compared transition paths. Finally, we combine consistency rules to check the consistency of the program before and after refactoring. We evaluated LockCheck in ¯ve open-source projects. A total of 1528 refactoring operations have been evaluated and 93 inconsistent refactoring operations have been detected. The results show that LockCheck can e®ectively detect inconsistent behavior when coarse-grained locks are refactored into ¯ne-grained locks. #c World Scienti¯c Publishing Company
Advancing young students’ computational thinking : an investigation of structured curriculum in early years primary schooling
Get PDFIn recent years, the development of computational thinking (CT) has become integral to many school curricula worldwide. This has been associated with calls for computational thinking to be considered a ‘21St Century’ competency, valuable to all students as a transferable process for solving problems and building understanding of human behaviour and systems. However, while computational thinking is a focus of most secondary school computer science curricula, proponents such as Jeanette Wing argue its relevance for younger students, indicating more work must be done investigating its development in early years' education. This study used a structured, problem-based curriculum supported by guided inquiry pedagogy, to explore 6 year old students' learning of basic computational thinking concepts and practices while coding programmable floor robots (Blue-bots and an iPad app). Results indicated improvement across the seven lessons in students' sequencing/algorithm authoring, error correction, and pattern recognition. Furthermore, they revealed evidence of higher order thinking such as identifying patterns in code, and how these can be transferred to help solve problems of different designs. While currently play-based approaches are used to introduce computational thinking concepts and practices in early years' education, results from this study suggest that more structured, problem-based methods should be seriously considered. Results challenge commonly understood developmental theories about what young children can and can't do, contextualised within the field of computer science, and hold implications for early years' teachers' professional knowledge and pedagogy if they are to promote their students' learning in this increasingly important area. Given rapid technological advancements such as artificial intelligence (AI) and increasingly earlier exposure of young children to digitally-mediated information, this study provides support for the earlier and more systematic introduction of basic digital literacy knowledge and skills in early years' education. © 2024 The Autho
Merging weather radar and rain gauges for dryland agriculture
Get PDFThe areal extent of rainfall remains one of the most challenging meteorological variables to model accurately due to its high spatial and temporal variability. Weather radar is a remote sensing instrument that is increasingly used to estimate rainfall by providing unique observations of precipitation events at fine spatial and temporal resolutions, which are difficult to obtain using conventional rain gauge networks. Dense rain gauge networks combined with operational weather radars are widely considered as the most reliable source of rainfall depth estimates. This paper compares the various sources of rainfall data available and explores the benefits of merging radar data with rain gauge data by reviewing the outcomes of a case study of a major agricultural cropping and pasture region. Comparison is made of rainfall measurements obtained from a dense rain gauge network covered by the output from a weather radar installation. We conclude that merging radar data with rain gauge data provides improved resolution of the spatial variability of rainfall, resulting in a significantly improved data source for agricultural water management and hydrological modelling. However, the use of weather radar merged with rain gauge data is generally underrated as a management tool. © 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the Bureau of Meteorology
Development and field testing of biodegradable seedling plug-tray cutting mechanism for automated vegetable transplanter
Get PDFTransplanting seedlings from plug trays into the field can cause transplant shock and lower the seedling survival rate. In order to avoid the need for a complicated clamping mechanism, this study developed a biodegradable seedling plug-tray cutting mechanism (SPCM) that separates seedlings with plug cells from plug trays. In order to cut and separate the plug cell from the plug tray and enable the seedling to fall into the transplanting hopper, the three sub-mechanisms that make up the SPCM align the plug cell at the point of seedling discharge. Approximately 82% of the plug cell was separated by the SPCM before being delivered to the planting unit. Additionally, using pepper and cabbage seedlings, the SPCM-equipped transplanter achieved a 74% transplanting performance, with an average field efficiency of 68%, a field capacity of 0.032-0.035 ha h-1, and a labor requirement that was 73% lower than that of manual seedling transplanting. The majority of pepper seedlings (85%) were transplanted with a planting angle of less than 10°, and 7% of cabbage seedlings were inclined with a planting depth of 48 mm for pepper and 53 mm for cabbage. These transplanting results were considered satisfactory. In conclusion, the SPCM represents a step toward effective and sustainable vegetable seedling transplanting. Enhancing productivity, precision in planting, and sustainability offer stimulating prospects for additional study and advancement in the area. ercial use only. © the Author(s), 2024