<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>BURA Collection:</title>
    <link>http://bura.brunel.ac.uk/handle/2438/8642</link>
    <description />
    <pubDate>Tue, 07 Apr 2026 07:01:37 GMT</pubDate>
    <dc:date>2026-04-07T07:01:37Z</dc:date>
    <item>
      <title>Enhancing Intelligence in Multi-Agent Systems with Edge-Assisted Causal Knowledge Aggregation</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32978</link>
      <description>Title: Enhancing Intelligence in Multi-Agent Systems with Edge-Assisted Causal Knowledge Aggregation
Authors: Nawaz, MW; Alam, MM; Swash, R; Abbasi, Q; Imran, MA; Popoola, O
Abstract: Dynamic and uncertain environments pose major challenges for multi-agent autonomous systems, particularly in achieving robust simultaneous localization and mapping (SLAM) and efficient knowledge sharing across robots. Conventional data-driven methods often overlook underlying causal structures, resulting in spurious correlations and limited generalization. To address this, we present CASK—an edge-assisted causal knowledge aggregation framework that fuses structured causal inference with data-driven learning to improve adaptive decision-making. A key feature is a time-based normalization mechanism that ensures mapping consistency across varying operational speeds, enabling speed-independent transfer of spatial knowledge between heterogeneous agents. We validate CASK through simulations and real-world experiments using autonomous ground vehicles, a class of mobile robots. Results show substantial gains over state-of-the-art methods: up to 20% higher success at low speeds, 40% at high speeds, 50% lower trajectory deviation, and 45% fewer re-planning steps. These findings demonstrate how causal inference combined with mobile edge computing enables scalable, reliable, and generalizable autonomy in multi-agent systems.
Description: Data availability: &#xD;
The datasets generated and analyzed during the current study, including occupancy grid maps, robot trajectories, and simulation results, are available from the corresponding author upon reasonable request. Due to hardware-specific constraints, real-world UGV and TurtleBot4 data can be shared in processed form to ensure reproducibility.</description>
      <pubDate>Wed, 07 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32978</guid>
      <dc:date>2026-01-07T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Evaluating Assistive Product With Designers: How To Understand And Address User Stigma Around Visible And Invisible Disability</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32976</link>
      <description>Title: Evaluating Assistive Product With Designers: How To Understand And Address User Stigma Around Visible And Invisible Disability
Authors: Niu, L; Manohar, A; Ning, W
Editors: Gray, C; Hekkert, P; Forlano, L; Ciuccarelli, P
Abstract: At the DRS conversation held on June 24, 2024, in Boston, researchers from&#xD;
Brunel University engaged in a discourse with ten audience members from diverse&#xD;
global backgrounds on the issue of user stigma in assistive product design. The purpose of this conversation was to delve into the potential challenges faced by disabled users when utilizing assistive products and to propose innovative design strategies aimed at eliminating stigma, fostering social inclusion, enhancing understanding of people with disabilities, and ultimately promoting the construction of a more barrier-free and equitable living environment. Through this discussion, participants gained a deeper understanding of the concept of disability and how design can effectively intervene to mitigate the associated stigma.</description>
      <pubDate>Sun, 23 Jun 2024 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32976</guid>
      <dc:date>2024-06-23T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Internet media and depression in older adults experiencing pain: Evidence from a five-year longitudinal study (2018–2023)</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32973</link>
      <description>Title: Internet media and depression in older adults experiencing pain: Evidence from a five-year longitudinal study (2018–2023)
Authors: Bai, F; Liao, Y; Tang, J; Du, S; Ning, W; Wang, C
Abstract: Background: &#xD;
Pain is a significant risk factor for depression among older adults. While prior studies suggest that internet media may improve mental well-being, it remains unclear whether such media can reduce pain-related depression. &#xD;
Objectives: &#xD;
This five-year longitudinal study explores the potential moderating effect of internet media on the relationship between pain and depression among older adults. &#xD;
Methods: &#xD;
Participants were sourced from 2018, 2020, and 2023 waves of the China Longitudinal Aging Social Survey, and this study utilized 3240 “person-year” observations from 1080 respondents. An individual fixed effects model was employed. The presence of pain, depression (measured by the CES-D scale), and media preference (measured by comparing internet and traditional media use frequency) were assessed. Subgroup heterogeneity was also explored. &#xD;
Results: &#xD;
The findings revealed that media preference significantly moderated the relationship between pain and depression among older adults (β = −0.725, p &lt; .01). Compared with traditional media, internet media was more effective in alleviating depression in individuals experiencing pain. The engagement breadth of internet media also exhibited a buffering effect. Heterogeneity analysis further illustrated that the beneficial effects of internet media were more pronounced among older adults who were less educated (β = −0.865, p &lt; .01) and retired (β = −0.887, p &lt; .01). &#xD;
Conclusion: &#xD;
This study enhances the understanding of the theoretical and practical aspects of internet media's moderating role in depression among older adults. It also highlights heterogeneous effects in vulnerable subpopulations. The findings offer insights for developing non-pharmacological interventions to address depression associated with pain, contributing to promoting mental health in the aging population.
Description: Data availability statement: &#xD;
The original data presented in the study are openly available in the China Longitudinal Aging Social Survey (CLASS) repository at http://class.ruc.edu.cn/English/Home.htm (accessed on 8 July 2025). Pre-registration is not mandatory. Formal permission to use the CLASS data and pre-registration were obtained on June 10, 2025.</description>
      <pubDate>Sun, 08 Mar 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32973</guid>
      <dc:date>2026-03-08T00:00:00Z</dc:date>
    </item>
    <item>
      <title>DRSelects: Hua Dong on the Proceedings of the First Conference on Doctoral Education in Design (1998)</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32830</link>
      <description>Title: DRSelects: Hua Dong on the Proceedings of the First Conference on Doctoral Education in Design (1998)
Authors: Dong, H
Abstract: My PhD research at the Engineering Design Centre (EDC), University of Cambridge and Postdoctoral job at Cambridge EDC and the Helen Hamlyn Research Centre at Royal College of Art laid the foundation of my research expertise in inclusive design. I share my passion and expertise through keynote speeches at international conferences, initiating new courses and research programmes, and academic and popular publications. I also have extensive experience in providing specialised research consultancy to industries in the UK …</description>
      <pubDate>Sun, 01 Oct 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32830</guid>
      <dc:date>2023-10-01T00:00:00Z</dc:date>
    </item>
  </channel>
</rss>

