46870 research outputs found
Sort by
Collectively Committing to ‘What Is Interesting’ in Qualitative Research:A methodological application of interactional sociolinguistics
Get PDFSelecting which aspects of empirical phenomena to investigate is a fundamental yet underexplored challenge in qualitative research. This paper introduces an interactional sociolinguistic methodology to examine how a qualitative research team navigated this challenge during a three-year project. By analysing real-life team discussions, we identify four types of interactionally co-constructed commitments—straightforward, uncertain, repeated and withheld commitments—that enable teams to balance exploratory openness with the need to narrow their focus within the interplay between the observed empirical field and academic discourse. Building on these insights, we propose an interactional sociolinguistic model of collective commitments to ‘what is interesting’ in qualitative research. Our study contributes to methodological scholarship by revealing how linguistic interaction shapes shared direction and methodological decision-making in team-based qualitative inquiries
Application research and effectiveness analysis of phase change materials in building envelope:A review
No full textThe construction industry is responsible for a significant amount of global energy consumption and CO2 emissions. To address this issue, phase change material (PCM) is commonly used as an effective heat storage material in building construction. It improves the thermal comfort of building occupants and reduces energy consumption. This paper provides an in-depth review of recent research on integrating PCM with building envelopes. The research primarily focuses on integrating PCM into walls, ceilings, roofs, floors, and windows, categorized by envelope structure components such as plaster, cement mortar, concrete, and brick. The specific approaches for each category are summarized and analyzed. The modification and optimization of PCMs, along with the impact of applying composite building PCM solutions in buildings, are consistently identified as two key areas of investigation. The paper also delves into the influence of PCMs on building thermal performance, humid environments, energy saving, CO2 emissions, and cost. Additionally, it highlights key considerations for applying PCMs in architecture and suggests potential future research directions to guide subsequent work
A calculation model of the mean flow velocity of overland flow considering a variety of grass covers and raindrop’s characteristics
No full textThe effect of vegetation distribution patterns, coverage, and raindrop impact on the overland flow velocity is highly intricate. To quantify these effects, a rigorous experimental campaign was conducted involving five rainfall intensities (ranging between 60 and 120 mm h−1), six vegetation patterns (diamond pattern - DP, random pattern - RP, checkerboard pattern - CP, vertical strip pattern aligned with the slope direction - VP, step strip pattern - SP, banded pattern perpendicular to the slope direction - BP), five vegetation coverage (ranging between 30% and 70%) and three slope gradients (ranging between 8.72% and 25.88%). The results obtained show that the BP configuration has the best flow velocity reduction effect, which can lessen the flow velocity by 58.68% - 69.27% compared with the bare slope, while the change for VP is only 4.80% - 6.30%. This indicates that BP yields significant soil and water conservation benefits. Furthermore, when the vegetation coverage is 30%, a concentrated flow formed between the vegetation patches under the RP and CP configurations, resulting in a higher overland flow velocity greater than the one recorded for the bare slope, which is unfavorable for soil and water conservation and should be avoided. Finally, a model was established to predict flow velocity and it was built by combining the equations of momentum and mechanical balance. After having calibrated the model and assessed its performance against research data available in literature, it was possible to confirm its reliability and consistency. These findings provide scientific guidance for assessing the soil and water conservation effectiveness of different vegetation patterns
Applications of Artificial Intelligence in Coronary Computed Tomography Angiography:Progress and Challenges
No full textCCTA (coronary computed tomography angiography) is an important tool for evaluating patients with suspected stable coronary artery disease. Recently, the development of artificial intelligence (AI), including machine learning in data analytics and deep learning in image processing, is reshaping the landscape of CCTA in clinical practice. The noise, radiation dose, and motion artifacts have been largely reduced. More advanced algorithms have been proposed for geometric construction, including image segmentation and centerline extraction. Based on the improved image quality, the assessment of different components (calcification, plaque, stenosis, myocardium, and pericardial fat) has achieved higher accuracy. Computational simulation can estimate hemodynamic parameters like fractional flow reserve. These new applications enable clinicians to improve the accuracy of diagnosis and treatment of coronary artery disease. This chapter summarizes the state-of-the-art methods of AI in CCTA, providing an updated reference for biomedical engineers, health professionals, and policymakers
Federated Reinforcement Learning for Uplink Centric Broadband Communication Optimization over Unlicensed Spectrum
Get PDFTo provide Uplink Centric Broadband Communication (UCBC), New Radio Unlicensed (NR-U) network has been standardized to exploit the unlicensed spectrum using Listen Before Talk (LBT) scheme to fairly coexist with the incumbent Wireless Fidelity (WiFi) network. Existing access schemes over unlicensed spectrum are required to perform Clear Channel Assessment (CCA) before transmissions, where fixed Energy Detection (ED) thresholds are adopted to identify the channel as idle or busy. However, fixed ED thresholds setting prevents devices from accessing the channel effectively and efficiently, which leads to the hidden node (HN) and exposed node (EN) problems. In this paper, we first develop a centralized double Deep Q-Network (DDQN) algorithm to optimize the uplink system throughput, where the agent is deployed at the central server to dynamically adjust the ED thresholds for NR-U and WiFi networks. Considering that heterogeneous NR-U and WiFi networks, in practice, may not be able to share the raw data with the central server directly due to data privacy, we then develop a vertical federated DDQN algorithm, where two agents are deployed in the NR-U and WiFi networks, respectively. Our results have shown that the uplink system throughput increases by over 100%, where cell throughput of NR-U network rises by 150%, and cell throughput of WiFi network decreases by 30%. To guarantee the cell throughput of WiFi network, we redesign the reward function to punish the agent when the cell throughput of WiFi network is below the threshold, and our revised design can still provide 70% uplink system throughput gain, where cell throughput of NR-U network rises by 100%, and cell throughput of WiFi network rises by 35%
Does product market competition affect corporate waste management? International evidence
No full textWe investigate the impact of product market competition (PMC) on corporate waste generation and Recycling. Analysing a global sample of 42 countries from 2002-2020, we find a positive (negative) association between the PMC and corporate waste generation (Recycling). Our channel analysis reveals that PMC diminishes both a company's profitability and cash flow, leading to lower waste management (Recycling). In further analysis, we demonstrate that the positive effect of PMC on waste generation is more prominent in financially constrained firms. Our study provides novel evidence of the consequential impact of competition on sustainability initiatives and presents important policy implications for regulators
“What are we looking at?”: The development and implementation of a performance analysis framework for netball umpires
Get PDFTechnology is progressively being used in sports development, with video feedback playing a central role in performance analysis (PA). However, the impact of PA on learning remains unclear. This study aimed to create, validate, and implement a self-controlled PA framework, targeting sports officials who must balance high-performance demands with personal life. The framework was tested as an intervention with two umpires in the 2023 Netball Super League. Results showed improvements in performance scores, suggesting enhanced identification and understanding of umpiring-related factors. Interviews revealed that developmental processes, video feedback, and external life factors significantly influence PA effectiveness. This research highlights the potential of structured PA frameworks to optimise learning and performance in sports officiating
Two-Timescale Optimization Framework for IAB-Enabled Heterogeneous UAV Networks
Get PDFIn post-disaster scenarios, the rapid deployment of adequate communication infrastructure is essential to support disaster search, rescue, and recovery operations. To achieve this, uncrewed aerial vehicle (UAV) has emerged as a promising solution for emergency communication due to its low cost and deployment flexibility. However, conventional untethered UAV (U-UAV) is constrained by size, weight, and power (SWaP) limitations, making it incapable of maintaining the operation of a macro base station. To address this limitation, we propose a heterogeneous UAV-based framework that integrates tethered UAV (T-UAV) and U-UAVs, where U-UAVs are utilized to enhance the throughput of cell-edge ground user equipments (G-UEs) and guarantee seamless connectivity during G-UEs' mobility to safe zones. It is noted that the integrated access and backhaul (IAB) technique is adopted to support the wireless backhaul of U-UAVs. Accordingly, we formulate a two-timescale joint user scheduling and trajectory control optimization problem, aiming to maximize the downlink throughput under asymmetric traffic demands and G-UEs' mobility. To solve the formulated problem, we proposed a two-timescale multi-agent deep deterministic policy gradient (TTS-MADDPG) algorithm based on the centralized training and distributed execution paradigm. Numerical results show that the proposed algorithm outperforms other benchmarks, including the two-timescale multi-agent proximal policy optimization (TTS-MAPPO) algorithm and MADDPG scheduling method, with robust and higher throughput. Specifically, the proposed algorithm obtains up to 12.2% average throughput gain compared to the MADDPG scheduling method.</p
Challenging Women’s Entrepreneurship: A decolonizing and antiracist approach
No full textEntrepreneurship is increasingly held up as ‘a universal “solution”’ (Ojediran et al., 2020, p. 87) for numerous problems in the Global South and North alike. However, Calăs, Smircich, and Bourne (2009) caution that ‘the act of bringing more women to entrepreneurship is not necessarily a straightforward solution, and it may even be a distraction from real social change’ (p. 558). Race-conscious and intersectional approaches are crucial to understanding both women’s entrepreneurial activity and the conditions under which it might flourish. For example, Ferraro (2023) shows that key tensions must be accounted for between Black enterprise and capitalism as a racist institution (p. 48), as must the specificity of Indigenous women businessowners and entrepreneurial activities in other late-colonial contexts. This chapter builds upon a long-standing feminist strategy to constantly question the grounds upon which we stand, to interrogate the languages and frameworks being used outside and within feminist criticism, to check in with for whom and how common terms are working, and to create new terms when needed. A review of the critical entrepreneurship literature makes clear that there is no one size fits all model for entrepreneurship. This chapter synthesizes entrepreneurship literature that incorporates Critical Race Studies, Critical Whiteness Studies, Postcolonial Studies, and perspectives that are markedly anticolonial, antiracist, feminist, and Indigenizing. This chapter suggests an approach to entrepreneurship grounded in egalitarian principles that might subsequently contradict some of the conventional business and economic development terms upon which national agendas to expand entrepreneurship are most often founded. Innovating entrepreneurship means making room for the diverse perspectives needed to solve modern social, economic, and cultural problems while creating more prosperity for all.<br/