Optimization of CNC lathe turning parameters for super duplex 2507 stainless steel using taguchi method under dry and wet cutting conditions

This study examines the effects of various lathe turning parameters and cutting conditions on the average surface roughness of super duplex 2507 stainless steel which is predominantly used in oil, gas and petrochemical sectors due to its high strength and corrosion resistance. The machining experiments were conducted on a CNC lathe using Taguchi L9 orthogonal array. The control factors included cutting velocity, feed rate, and depth of cut under dry and flood cooling conditions. Analysis of variance (ANOVA) was used to identify the influence of these lathe turning parameters on average surface roughness. Based on Taguchi design principle, signal-to-noise ratios were calculated. Results from empirical models and Taguchi analysis indicated that feed rate had the most significant effect on average surface roughness (Ra). The optimum values of CNC lathe turning parameters with dry cooling are found to be 47 m/min cutting velocity, 0.05 mm/rev feed rate and 0.15 mm depth of cut. Similarly for wet cutting, these parameters are found to be 94 m/min cutting velocity, 0.05 mm/rev feed rate and 0.05 mm depth of cut. The predicted optimum surface roughness was found to be 0.716 μm and 0.386 μm for dry and wet cutting respectively. The experimental verification showed that the predicted surface roughness has less than 10% differences with actual (experimental) surface roughness values

Who knew that i, of all people, could be an academic, and even do well at it?

Alex Russell never thought he'd be an academic. He failed a few subjects at uni until he found a topic that interested him: wine. That led to an opportunity for a PhD with a fantastic supervisor in Prof Bob Boakes, and the opportunity to teach statistics under another fantastic mentor, Dr Margaret Charles. While wine was an interesting and fun research topic, an opportunity in gambling came up, working with Prof Nerilee Hing, and gambling became the focus of his work. He's won a bunch of awards along the way and has been involved in a lot of great projects and papers, but he's never really shaken that "imposter syndrome" that so many of us feel, especially due to some harsh comments along the way. His favourite goal is to help others be the best they can be, through supervision and mentorship, and through his approach to teaching a topic that many people dread: statistics. He's also conducted research on a bunch of interesting topics, like how video games are becoming more like gambling, how people describe the way that wine smells, synaesthesia and who is most at risk of harm from gambling. What he hopes that you'll take away from his story is that even if you fail a few times along the way, sometimes it's just a matter of finding what you're passionate about. And while there will always be detractors out there, it's so much more fun and rewarding lifting people up

Integrating generative artificial intelligence across the curriculum in higher education: Multi-disciplinary case studies

The advent of generative Artificial Intelligence (Gen-AI) has transformed the way higher education is delivered. Gen-AI is rapidly changing how students engage with learning resources, with academics adopting these tools in the classroom to provide insightful lessons and scalable solutions that enhance educational outcomes across disciplines. We use the Technological Pedagogical Content Knowledge (TPACK) framework to discuss the types of knowledge teachers require to effectively use GenAI tools in their teaching. This paper reports on five case studies from an Australian higher education institution examining the integration of Gen-AI across various academic disciplines in higher education, demonstrating its impact on teaching methodologies and creating innovative educational experiences. Throughout these diverse case studies, we show how Gen-AI tools can be used to enhance academic skills, foster creativity, and address pedagogical challenges. Each case study reveals the complexities and potentials of Gen-AI in educational settings, including the development of critical thinking skills and understanding Gen-AI’s limitations. We describe how Technological Knowledge, Pedagogical Knowledge and Content Knowledge of teachers has impacted the use of Gen-AI in the classrooms

Developments and trends in water level forecasting using machine learning models—A review

Water level forecasting in rivers, lakes, and reservoirs is crucial for effective water resource management, flood control, and environmental planning. This review examines the latest developments and trends in water level forecasting research from 2011-2024. A wide range of methods are explored, including traditional statistical models (ARIMA, regression) and advanced techniques like artificial neural networks (ANN), fuzzy logic, support vector machines (SVM), and deep learning models (LSTM). The study assesses the performance and accuracy of these applied models, analyzing their strengths and limitations in capturing water system dynamics and uncertainties. It investigates how data sources (hydrological, meteorological, historical) and variables (rainfall, evaporation, inflow) impact forecast accuracy. The significance of different variables for improving model predictive capabilities is determined. Spatiotemporal aspects are explored, examining model applicability across local, regional, and global scales. Approaches to quantifying and communicating uncertainties associated with probabilistic forecasting for decision-making are evaluated. Detailed analysis identifies proven model efficiencies, potential challenges, and suggests future research directions. By comprehensively reviewing recent water level forecasting literature, this study provides state-of-the-art knowledge on applying machine learning models for reservoir water level prediction. It guides water resource strategies, flood mitigation measures, and decision-making for sustainable water systems management. This review is a valuable resource for researchers and practitioners in hydrology and related fields.</p

Selling your old laptop or phone? You might be handing over your data too

You’re about to recycle your laptop or your phone, so you delete all your photos and personal files. Maybe you even reset the device to factory settings. You probably think your sensitive data is now safe. But there is more to be done: hackers may still be able to retrieve passwords, documents or bank details, even after a reset

Modelling and simulation of performance, combustion and emission of a diesel engine fueled with renewable dimethyl ether-ethanol blend

Due to price hikes, stringent emission regulations (Net Zero emissions by 2050), and global climate change issues, researchers are driven to explore sustainable fuels. This study reports on 1-dimensional (1D) modelling and simulation of performance, combustion and emission of a direct injection diesel engine using dimethyl ether (DME)-ethanol blend as one of the carbon-footprint compliance fuels. DME can be sourced from sustainable feedstocks, which are considered one of the cleanest fuels due to their inherent oxygen content in the molecular structure. Like DME, bioethanol can also be sourced from renewable feedstocks and is considered an oxygenated fuel. For the 1D modelling and simulation, GT-Suite Software was used. Using DME 50%+Ethanol 50% (henceforth termed DME50), the modelling and simulation were performed for performance, combustion and emission characteristics. The investigation aims to establish the reasons for higher power, higher efficiency, lower nitrogen oxides (NO), and lower carbon dioxide (CO2) emissions, with DME50. The simulation results were validated with those of experimental results. The results showed that DME50 increased efficiency and power and reduced harmful $\text{CO}_{2}$ and NO emissions. The simulation results were within the acceptable ranges with experimental results

The impact of action plans on habit and intention strength for physical activity in a web-based intervention: Is it the thought that counts?

Objective: Action planning is a common approach used in physical activity interventions. The aim of this study was to assess the association of frequency, consistency and content of action planning with physical activity behaviour, intention strength and habit strength. Methods and Measures: Within a 3-month web-based, computer-tailored physical activity intervention, participants (N = 115; 68.7% female, M age =43.9; range = 22–73 years) could create 6 rounds of action plans for 4 activities each (24 total). Results: Consistency of action planning during the intervention was associated with change in physical activity at 9-months, and intention and habit strength at 3-months and 9-months. Frequency of action planning was negatively associated with intention at 3-months and 9-months. The effect of action planning consistency on physical activity behaviour was no longer significant when accounting for change in intention and habit strength. Conclusion: Consistency of how, where, when and with whom people plan their physical activity may translate into stronger physical activity habits. Interventions should avoid encouraging making many distinct action plans, but rather encourage stable contexts through consistent action planning.</p

Self-Reports for Factors Impacting on the Ability of People with Acquired Disabilities to Obtain and/or Sustain Employment: An Australian Study

The purpose of this research is to study the factors impacting on the ability of people with acquired disabilities to gain and sustain employment, as well as finding a possible solutions to employment participation problems that would guide policy developers, employers and people with acquired disabilities. Several research have shown that people with a disability that can categorized as 'acquired' struggle to sustain employment and often suffer more discrimination than the other cohorts. Yet, not much research have sought to understand acquired disability in relation to employment outcomes. The study will follow an Active Case Study research design comprising of a casy study and intervention on 50 participants. The process will follow the following stages. Participants will be asked to complete a self report questionnaire to gain an insight of their experiences as jobseekers and perceptions of their own disabilities. This will be followed by unstructured observation to learn how participants go about their job search activities. The results from this self reporting process will enable the researcher to work on a schedule for the indepth interviews to further understand these experiences and perceptions. The interviews will beaudio recorded with the participant's full consent. The results from the indepth qualitative interviews will be used to craft questions for the pre- and post-measure questionnaires to be completed by participant before and after the intervention stage. The 50 participants will be divided into a control and an experimental group of 25 participants each. The control group will receive normal services. The experimental group will receive a structured program to assist in obtaining employment. Structured observation will be conducted on both groups during the process of the intervention to gage the impact of intervention. The process will go for six months. Both groups will be interviewed during the intervention for their views on observed points. At the end of the intervention, both groups will do the quantitative post-test measure to gage an change in perceptions. The qualitative and quantitative data from all components of the study will be analysed independently. The qualitative data will be analysed using Discourse Analysis, the quantitative data will be analysed using descriptive statistics. The data will then be triangulated.</p

Exploring the prevalence of renewable energy practices and awareness levels in Palestine

The growing demand for energy in developing societies, coupled with dwindling conventional resources, necessitates the adoption of renewable energy (RE) sources. A comprehensive understanding of these sources and their optimal utilization is crucial. The awareness of the users plays a very important role in the effective utilization of different energy sources. Hence, this study examines the level of RE awareness in Palestine, identifying factors influencing public perception and exploring potential strategies for promoting RE adoption. This awareness depends on different factors related to the users' education level, community type, and type of building. Different factors that affect the willingness and attitude to gain knowledge about RE are presented. In addition, various practices highlighting the increasing level of awareness regarding the adoption of RE sources are investigated. In addition, the status of RE education and its potential impact on engineers have also been discussed. Various individual and institutional efforts are highlighted in the study as strategies to bridge the gap and overcome obstacles to adopting RE sources. Suggestions for better use of these resources have been highlighted. Thereafter, recommendations for effective RE implementation in Palestine are analyzed and conclusions are drawn. The main challenges in integrating RE into Palestine's existing energy grid and system include infrastructure limitations, resources and financial constraints, and political issues. Still, there are possibilities in the form of international collaboration and investment. A flexible and modular RE grid could also address some of these challenges by integrating small-scale systems that can be scaled up as needed.</p

Obstetric ultrasound and women with obesity: Do we need industry guidance?

Australia, like many developed countries is experiencing an obesity crisis, with maternal obesity associated with increased risks of fetal and maternal complications. For obstetric sonographers, there are technical challenges to exclude a fetal anomaly or pregnancy complication in a woman with obesity. Furthermore, scan times are often longer, greater probe pressure is needed and follow up scans are often undertaken to complete examinations. There are numerous studies reporting high rates of work-related musculoskeletal disorders (WRMSDs) amongst sonographers and papers that provide tips and tricks to improve imaging and ergonomics. However, there is no specific industry guidance by way of a guideline, consensus statement or position paper from our leading professional associations, on how we can address this complex issue obstetric sonographers encounter when scanning women with obesity, or our communication with women about the difficulties faced. Given the high and increasing rates of obesity, the high risk of pain and WRMSDs for sonographers and limitations associated with these examinations, this raises the question—is it time for our industry to discuss guidance and communication in obstetric ultrasound for women with obesity to mitigate sonographer risk of WRMSDs, while ensuring safe, high quality care for these women?.</p