Holmesglen Institutional Repository (Holmesglen Inst. of TAFE)
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Blurring the lines: the vague boundary between mainstream and deviant internet pornography tags for at-risk viewers
No full textThis is an open-access article distributed under the terms of the Creative Commons Attribution License.Illegal material is increasingly appearing on popular mainstream websites.Many commentators worry about the impact of such material on adolescents’ psycho-sexual development and the potential for some legal pornography to act as a gateway to child sexual exploitation material (CSEM) for users of any age. In this study, we collected publicly available data from a popular legal pornography website to assess the risk of adolescent exposure to content that may hinder healthy psycho-sexual development. We analysed over 27 million customer searches involving 149 video tags from this site. Five international experts on the effects of pornography rated the tags, categorising them into five overlapping genres: mainstream, incestuous, underage, aggressive and non-consensual. They also assessed the potential risk each genre posed. Our analysis found a significant positive correlation between the harm ratings and the frequency of tags used as search terms. Additionally, eleven of the twelve tags with the highest mean risk scores involved potential underage and/or incestuous content. This study highlights a concerning relationship between the harm ratings of various pornographic genres and their popularity as search terms. While exploratory, these results emphasise the need for regulatory measures to address the presence of harmful material on mainstream websites.Computing and Information TechnologyDepartment of Psychology, Utrecht University, Utrecht, NetherlandsCyberstronomy Inc., Melbourne, AustraliaHolmesglen InstituteJill Dando Institute of Security & Crime Science, University College London, London, UKNew Zealand Institute ofSecurity & Crime Science, University of Waikato, Hamilton, New ZealandLaw School, University of Tasmania,Hobart, Australi
Navigating fandom: how user generated content reflected the conflicting emotions of sport’s importance during COVID-19
No full textAttached is the Final draft (i.e. the pre-published version of the paper)Despite the global cancellations of sport due to COVID-19, the Australian Football League commenced the 2020 season in empty stadiums. It was one of the few sports still being played globally before the league postponed the season days later. This handful of games helped fans to maintain connection with their sport and teams, albeit only on media platforms. This paper analyses user-generated content from Twitter (n = 2,484) to explore how fans engaged with, integrated, and responded to sport in a global crisis, as well as how they navigated and rationalised their fan experience during this unprecedented time. It focuses particularly on understanding evolving perceptions of sport’s role and importance in society amid evolving uncertainty, due to macro influences that cause conflict and tension within figuration. It also explores the temporal nature of fandom in uncertain and fluctuating sporting environments.Sports Media and Sport Business DegreesHolmesglen InstituteSwinburne University of TechnologyGriffith Universit
Emerging advances of blockchain technology in finance: a content analysis
No full textBlockchain has become a widely used information system technology recently because of its effectiveness as an intermediary-free platform. While the use of blockchain in various fields, such as finance, supply chains, healthcare, education, and energy consumption, is increasingly enabling the development of Internet-enabled “distributed databases,” there are not many exploratory studies available to provide an understanding of how the field is progressing. Therefore, it is imperative to explore the status quo of blockchain technology in the finance sector, particularly highlighting how blockchain architectures can aid the finance sector to gain competitive advantage. This systematic literature review analyzes the content of the 50 most relevant articles and professional industry reports through peer-reviewed relevant academic literature in the finance sector from 2008 to 2022 to identify several possible features of blockchain research in the financial sector. This study highlighted the dimensions of blockchain technology, blockchain in finance, its competitive advantages, the current status of finance, and various challenges that keep the implementation of blockchain-based financial information systems at the initial stage. We identified three main areas that require research attention in order for blockchain technology to become the “next-generation networks” that will revolutionize the financial sector.Computing and Information TechnologyHolmesglen Institut
Predicting stock price movement using sentiment analysis and CandleStick chart representation
No full textAbstract: Predicting stock price movement is an important topic of academic interest. Due to challenges of
traditional methods in predicting stock price movement perdition we address this challenge by using machine
learning which can use valuable near real-time information from social media platforms. We investigate
whether models using machine learning algorithms can predict stock price movement with accuracy. We
developed a comprehensive machine learning model and validated with real-world application using data
collected from Yahoo Finance on five high-demand stocks from the United States: Apple, Tesla, IBM, Amazon,
and Google. An experiment of deep neural network implementation in the stock investment comprises
technical indicators, sentiment, and candlestick to predict the stock price. Using Twitter data, we offer a
sentiment analysis and time series data transformed into the candlestick chart so that patterns can be
elucidated. The step is followed in the candlestick chart for the prediction of stock price for a period of 10-
days. We achieve the most favourable performance on AAPL stock with 75.38% accuracy over 10-day period
and less favourable performance for the IBM stock with 51.26% accuracy over a period of 4 days. Also, our
model was able to achieve the most balanced results for TSLA stock with 79.59% recall, 71.86% accuracy,
73.58% F-score and 68.42% precision over a period of 10-days. We demonstrate operational value of deep
learning approach by showing that stock price movement can be predicted over a short period by using Twitter
data, considering multichannel collaborative network, candlestick chart as well as sentiment analysis.
Keywords: stock price prediction; machine learning, deep learning neural network; sentiment analysis;
candlestick chart; TwitterComputing and Information TechnologyHolmesgle
Mission Possible: The Rise of Institutional Repository in TAFE
Full text linkBefore launching the Institutional Repository in Holmesglen, almost no one believed that an Institutional Repository was possible for TAFE, or/and there was any need for TAFE to have one.
Holmesglen has defeated the odds and launched the first Institutional Repository in Victorian TAFE sector in 2016. 7 years later, Holmesglen Institutional Repository (HIR) is still up and running, and with the new partnership with the Centre of Applied Research and Innovation, HIR has a steady growth of deposited items and researcher profiles.
Launching the first Institutional Repository in Victorian TAFE sector is the first step to break the barriers. TAFE also engages in applied research internally and in partnership with industry, so research and research outputs are not just university's privileges. TAFE section as well as it is libraries can contribute as well.LibraryHolmesglenALIA VET Libraries Australia Conference 2023Onlin
Impact of the COVID-19 pandemic on emergency department team dynamics and workforce sustainability in Australia: a qualitative study
No full textOnline journal article. Open access.The COVID-19 pandemic has challenged health care professionals and changed our approach to care delivery. The aim in this study was to explore nurses’ experiences providing care in the ED during the COVID-19 pandemic in Australia and the impact of this on ED team functioning.NursingHolmesglen InstituteDeakin University Centre for Quality and Patient Safety Research in the Institute for Health TransformationDeakin University Centre for Quality and Patient Safety Research Epworth Healthcare PartnershipDeakin University Centre for Innovation in Infectious Disease and Immunology Research (CIIDIR
Machine learning in pattern recognition
No full textOpen AccessSupervised or unsupervised classification is the main objective of pattern recognition. The statistical approach is the most popular approach that is practised among the several frameworks where pattern recognition is initially formulated. In the recent past, the neural network technique and the methodology scheme from the statistical learning theory have garnered the attention of people. It requires proper attention to deal with the design of the recognition system. There are several issues associated with the design of the recognition system. They are the pattern class definition, sensing environment and representation extraction and selection of features, cluster analysis, classifier design, learning, and choosing the training and test samples. There is no solution to the general issue of recognizing complex patterns associated with arbitrary patterns. Data mining, web searching, and retrieval of multimedia are the various emerging applications that require proper and effective regulation techniques. The main purpose of this paper is to give a detailed overview of the various methods that can be used in the different stages of the pattern recognition system. The paper also aims to figure out the research topics in the application that can be highlighted in this challenging field.Computing and Information TechnologyHolmesglen Teache
The recycling, reusing, and repurposing of nursing and medical equipment in nursing education
No full textOpen access.In a conscious attempt to manage the ever-growing waste problem, Holmesglen, led by the Laboratory Manager, have developed and implemented a recycling programme that incorporates all elements of its practical education. The aim is to prevent nursing supplies adding to landfill.NursingHolmesglen Institut
Handbook of big data and analyitcs in accounting and auditing
No full textAbstract: The chapter aims to discuss impact of data visualization on auditors’ analytical procedures and propose practical approaches to address audit efficiency through data visualization techniques. To ensure that efficient presentation of data improves audit efficiency and effectiveness, it is essential that auditors are aware of and effectively apply data visualization techniques in auditing. This chapter presents more profound data visualizations applications in audit procedures that can assist auditors in finding data discrepancies for improving audit risk management through insight development capacity. Further, this chapter considers numerous data visualization analysis tools that audit professionals can use in their specific audit procedures. Finally, this chapter provides avenues for future research in audit data analytics and recommends future research that will allow auditors to realize how technology-driven data visualization tools interact with the audit's standard features.Computing and Information TechnologyChetanpal Sing
Diabetes care pathways.
No full textThis is a series of documents about Diabetes Care Pathways show the milestones on a person’s journey from first diagnosis to successfully managing their condition through self-management education and support from their Credentialled Diabetes Educator (CDE). There are eight different pathways depending on the type of diabetes a person has and their health status. It’s important that you understand the key points on your pathway. It will help you plan for the future and keep you on the right track as your needs change and your knowledge grow.HSCSS Degree ProgramsHolmesglen Institut