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    21438 research outputs found

    Potential Pollution Loads of the Cikembar Sub-Watershed to the Cicatih River, West Java, Indonesia

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    The Cicatih River in the Cikembar sub-watershed, located in Sukabumi Regency, flows along the upstream of the Cikembar sub-watershed and Palabuhan Ratu Bay. For decades, the river has served as a vital water resource, catering to various needs such as domestic use, agriculture, livestock, fisheries, industry, mining, tourism, and hydroelectric power. Recently, the Sukabumi Regency Government made the pollution of coastal and river areas one of the priority issues on sustainable development initiatives for the Sukabumi Regency. This highlights the importance of managing the Cicatih River, one of the main rivers in the regency. This research aims to analyze the potential pollution loads in the Cikembar sub-watershed to the Cicatih River by assessing its water quality status and potential pollution loads from four main sectors: domestic, agricultural, livestock, and industrial. The water quality was calculated based on the Pollution Index method. The potential pollution load from different sources was analyzed using various emission factor calculations. For each pollutant source, the following parameters were analyzed: total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), Total-N (nitrogen), and Total-P (phosphorus). Results showed that the condition of the Cicatih River is slightly polluted. The parameter exceeding its maximum threshold is BOD. The largest contributor to the potential pollution load of BOD is the domestic sector (53%), while the agricultural sector is the least (2%). In the domestic sector, Bojongkembar Village is the largest contributor to the potential pollution load. The results of this analysis can be used to develop strategies for managing the overall Cikembar sub-watershed

    Belonging in remote higher education classrooms: The dynamic interaction of intensive modes of learning and arts-based pedagogies

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    In this paper, the authors explore the conditions that support belonging in remote VU Block Model® teaching. They examine the role of arts-based, embodied pedagogy in promoting engagement in learning, connection between students, and between students and teachers, and in an environment in which vulnerability and risk-taking in learning is valued. A discussion of belonging in higher education and the practice of embodied learning is followed by the reflections of seven participants. These participants were students in a remotely taught, arts-based higher education block unit, which had been mindfully adapted to retain the embodied nature of delivery during the COVID-19 pandemic. After students’ participation in focus group interviews, the lead author constructed found poetry from their comments and reflections. This found poetry forms the dataset through which the questions of belonging are explored. The researchers found that when explored through the lens of the Community of Inquiry Framework, embodied and arts-based practices provided opportunities for students to develop a sense of belonging, deepen understanding of lived experiences, and realise higher education and career goals. This study elevates the voices of students, providing opportunities for higher education teachers to consider the importance of belonging for student success in remote, intensive, and on-campus modes of delivery

    Raced and risky subjects: the interplay of racial and managerial ideologies as an expression of “colorblind” racism

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    Contemporary manifestations of race are dynamic and elusive in the forms and shapes they take. “Colourblind” racism is effective at drawing on seemingly objective and race-neutral discourses to obfuscate racialized forms of structural exclusion. Framed by Critical Race Theory and Critical Narrative Analysis this paper presents an example from the Australian context that examines the relationships between a grassroots initiative developed by creatives from the African diaspora and two not-for-profit human services organizations, to illustrate how ideologies of race are enacted and obscured by managerialist ideologies and discourses of risk. Specifically, it shows how harmful dominant cultural narratives of deficit and danger transforms racialized Africans in Australia into “risky subjects.” In a managerialist organization, risk must be controlled, and thus risk becomes the rationality for the control of racialized and risky subjects. Resistance to control by those subjects produces forms of organizational defensiveness that are mobilized through managerialist discourses and practices that work to structurally exclude. These findings illustrate the ways ideologies of race work alongside and through other ideological discourses and practices which render racialized dynamics of oppression race-neutral

    Physics-based modelling of wind-driven junction fires

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    Numerical simulations of laboratory-scale junction fires were performed for a shrub fuel bed, using the fully-physical model FIRESTAR3D under various unidirectional wind conditions on different terrain slopes and junction angles. Simulations were carried out for a junction angle ranging from 15° to 90°, for a slope angle varying between 0 and 40°, and for low to intermediate driving wind speed, ranging from 0 to 4 m/s. Simulations show surge-and-stall-like behaviour of fire spread that is irregularly enhanced by the action of wind. Results of fire spread show that the effect of the junction angle on fire behaviour is non-linear, becoming stronger as the angle decreases. Both wind and slope effects are concealed by the junction effect for small angles, while wind has a significant impact at intermediate values of the junction angle. The driving heat transfer mode in junction fires varies based on the slope condition: on sloping terrain, convection is dominant for any wind speed, while on non-sloping terrain, radiation is the driving mode in no-wind condition but convection plays the greater role as the wind speed increases

    Fractal feature selection model for enhancing high-dimensional biological problems

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    The integration of biology, computer science, and statistics has given rise to the interdisciplinary field of bioinformatics, which aims to decode biological intricacies. It produces extensive and diverse features, presenting an enormous challenge in classifying bioinformatic problems. Therefore, an intelligent bioinformatics classification system must select the most relevant features to enhance machine learning performance. This paper proposes a feature selection model based on the fractal concept to improve the performance of intelligent systems in classifying high-dimensional biological problems. The proposed fractal feature selection (FFS) model divides features into blocks, measures the similarity between blocks using root mean square error (RMSE), and determines the importance of features based on low RMSE. The proposed FFS is tested and evaluated over ten high-dimensional bioinformatics datasets. The experiment results showed that the model significantly improved machine learning accuracy. The average accuracy rate was 79% with full features in machine learning algorithms, while FFS delivered promising results with an accuracy rate of 94%

    Single-session measures of quadriceps neuromuscular function are reliable in healthy females and unaffected by age

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    This study aimed to determine the inter-session reliability of quadriceps neuromuscular function measurements in healthy young and older females

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