• Mobile calibration for bus-based urban sensing

  Zarrar, Hassan; Limbu, Max; Haxha, Shyqyri; Dyo, Vladimir; ; University of Bedfordshire; Royal Holloway, University of London (IEEE, 2024-12-23)

  In bus-based sensing, public transport serves as a mobile urban sensing platform. While offering much higher geographical coverage, the low-cost sensors mounted on vehicles can be less accurate and demand more frequent calibration, which may be challenging for large vehicle fleets. As calibration is performed by relating mobile sensor readings to those of fixed reference stations, the placement of reference stations is very important. In this work, we propose an algorithm for computing the optimal locations for reference stations to maximize the sensing coverage. Contrary to prior work, coverage is defined in terms of geographical area, extending a certain distance away from the route trajectory, which represents the actual sensing capacity of the vehicles. The proposed algorithm computes it using geographical set operations, such as spatial join and subtraction to compute the unique contribution of each bus route. We evaluate the approach using real bus trajectories from Manhattan, USA, and compare it with a random baseline and prior work. The results indicate that given the bus routes, a complete sensing coverage can be achieved using a single reference station with a maximum 2-hop calibration path.
• Exploring the effects of compression ratio and initial flame kernel radius on 1 combustion characteristics and fuel economy of a dual-fuel spark ignition engine 2 under oxy-fuel combustion mode

  Li, Xiang; Zhang, Xuewen; Ni, Peiyong; Pei, Yiqiang; Li, Wanzhong; Peng, Zhijun; Li, Dayou; Weerasinghe, Rohitha; Mobasheri, Raouf; Nantong University; et al. (ELSEVIER, 2024-12-16)

  In order to mitigate greenhouse effect and promote carbon neutrality, Oxy-Fuel Combustion (OFC) technology implemented in the Internal Combustion Engine (ICE) has been an effective and promising approach to reduce or even eliminate CO2 emissions from the transportation sector. This research contributes novel insights into the effects of compression ratio (𝛿𝐶𝑅) and initial flame kernel radius (𝑅𝐹𝐾) on combustion characteristics and fuel economy of a Dual-Fuel Spark Ignition (DFSI) engine under OFC mode by a numerical method. The research results show that by increasing 𝛿𝐶𝑅 from 8.6 to 13.6, an apparent reduction can be seen in equivalent Brake Specific Fuel Consumption (BSFCE). The corresponding ignition delay (𝜃𝐹) has a reduction of 10 degrees, while combustion duration (𝜃𝐶) are relatively stable. Moreover, the maximum cylinder pressure (𝑃𝑚𝑎𝑥) has a rise of 8 bar and 20 bar at low load and mid-high load, respectively. By increasing 𝑅𝐹𝐾 from 0.2 mm to 1.2 mm, 𝑃𝑚𝑎𝑥 and 𝜑𝑃𝑚𝑎𝑥 each presents a monotonic trend of growth and advancement, respectively. The reduction of 𝜃𝐹 at low load and mid-high load is each 28.5 degrees and 34.9 degrees. In the meantime, both BSFCE and in-cylinder temperature show a low level of sensitivity. The research findings could provide valuable insights for enhancing the combustion performance and economy of DFSI engines under OFC mode to mitigate the greenhouse effect.
• Viewing mock crimes in virtual reality increases presence without impacting memory

  Green, Andrew D.; Clark, Andrew; Pitchford, Melanie; Guppy, Andrew; ; University of Bedfordshire; Arden University (Springer, 2025-02-03)

  Traditional methods of displaying stimuli in eyewitness memory research, such as mock crime videos, are often criticised for lacking ecological validity. To overcome this, researchers have suggested using virtual reality (VR) technology to display the stimuli as it can promote a sense of presence, leading to real-world responses. However, little research has compared VR with traditional methods to demonstrate this enhanced validity. In Study 1, 54 participants viewed a mock crime video on screen or in VR while their heart rate was recorded, then completed measures of presence and emotion, and had their recall tested after 10 min. In Study 2, 74 participants' recall was tested after a 7-day delay and included a more in-depth exploration of emotional experience. In both studies, participants in the VR group reported a statistically significant increase in their sense of general presence, spatial presence, and involvement in the scene; however, there was no statistically significant difference in recall between the groups. Participants in the VR group had a statistically significant increase in heart rate in Study 1 only, and emotional experience in Study 2 only. The findings of this research suggest that VR may provide a more ecologically valid eyewitness experience than videos, without impacting participant memory or wellbeing. The findings of the current research are discussed in relation to previous literature and implications for experimental eyewitness memory research.
• Implementing a study support service (Studiosity) software system to improve students' academic writing skills

  Pike, David; Aruna, Isabel; University of Bedfordshire (2022-12-31)

  In an effort to respond to the UK's OfS (Office for Students) Gravity Assist review the Digital Learning team at the University of Bedfordshire have been experimenting with ways to improve the experiences of students' academic writing skills as part of an effective digital induction, to support students' transitions into HE (Higher Education), and for our existing student body. A key part of our efforts has focussed upon using a study support service called Studiosity which provides students with feedback on their assessments and academic work. Rather than focusing upon a service which utilises AI for feedback, we opted to utilise a service which provides feedback from a writing assessor. In this way the service mirrors, supports and provides a route for us to better understand our students' writing skills and to determine how we can feed forward and back to students and a multitude of organisational layers within the University which stretch across staff and student groups. Using a DBR (Design Based Research) approach we explore our initial considerations before approaching staff and students with the service, the technical and pedagogical considerations we made before our first engagements, and detail some of our experiences of engaging staff and students in the process of improving their academic writing. We move from these initial considerations to explain how we are engaging with academic and support colleagues within the University, the insights the data provides us about our students writing skills. We conclude the paper by providing an initial version of a potential implementation framework which other colleagues implementing similar schemes can build upon our initial mode to critique and develop their own implementations from. We also examine the possibilities for demonstrating the ways in which we can evidence and explain the ways we and our students think the service is effective. As this is our first iteration of the implementation, this paper also serves the secondary purpose of bracketing and recording our assumptions about our implementation. Our intention is to use this paper to document our initial iteration and we will return to provide an updated version of this paper as a point of reference for our next iteration.
• Power line monitoring-based consensus algorithm for performance enhancement of energy blockchain applications in Smart Grid 2.0

  Yapa, Charithri; De Alwis, Chamitha; Wijewardhana, Uditha Lakmal; Liyanage, Madhusanka; Ekanayake, Janaka; University of Sri Jayewardenepura; University of Bedfordshire; University College Dublin; University of Peradeniya; Cardiff University (Institute of Electrical and Electronics Engineers Inc., 2024-08-21)

  Energy blockchain applications are becoming inevitable with the transformation of electricity distribution networks into the decentralized Smart Grid 2.0 architecture. The scalability of the blockchain platform plays a key role in catering to the increasing number of nodes connected due to consumer-turned-prosumers being integrated into the distribution grid in a distributed manner. Hence, this study aims to optimize blockchain utilization for Smart Grid 2.0 applications through a novel consensus mechanism, which eliminates the requirement for performing additional complex computations to mine a new block. The algorithm utilizes the grid monitoring process through the existing smart meters, and thus has been capable of reducing the energy footprint for block mining to a fraction of that of the legacy Proof-of-Work algorithm, and reducing the block creation time by ∼<60% . The proposed Power Line Monitoring-based Consensus Mechanism (PLMC) algorithm is validated using the Process Analysis Toolkit (PAT). In addition, data collected while monitoring the network for block mining is utilized for power quality measurement purposes.

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