Now showing items 21-40 of 5696

    • Blockchain application in supply chain chemical substance reporting - a Delphi study

      Takhar, Sukhraj Singh; Liyanage, Kapila; University of Derby (Inderscience, 2021-02-08)
      Blockchains utilise digital ledger technology to enable data to be traced in a more efficient manner than traditional paper-based systems. Smart contracts extend the capabilities of a blockchain by defining specific obligations. Chemical regulations impose the need on industry to record and report the use of hazardous chemicals within products. The process of collating supply chain chemical substance reporting information is a manually intensive and lengthy process in order to identify potential business risks and reporting of information to employees, consumers and chemical regulators. The research question answered in this paper relates to use of a blockchain with a smart contract to enable the automated collation of supply chain chemical substance information. This paper presents the findings from a Delphi study and a proposed 'supply chain chemical substance reporting' (SCCSR) blockchain. The SCCSR blockchain enables industry to implement greater efficiencies in collecting the required chemical substance information.
    • Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs)

      Zada, Muhammad Sadiq Hassan; Yuan, Bo; Anjum, Ashiq; Azad, Muhammad Ajmal; Khan, Wajahat Ali; Reiff-Marganiec, Stephan; University of Derby; University of Leicester (IEEE, 2020-12-28)
      The diversity and proliferation of Knowledge bases have made data integration one of the key challenges in the data science domain. The imperfect representations of entities, particularly in graphs, add additional challenges in data integration. Graph dependencies (GDs) were investigated in existing studies for the integration and maintenance of data quality on graphs. However, the majority of graphs contain plenty of duplicates with high diversity. Consequently, the existence of dependencies over these graphs becomes highly uncertain. In this paper, we proposed graph probabilistic dependencies (GPDs) to address the issue of uncertainty over these large-scale graphs with a novel class of dependencies for graphs. GPDs can provide a probabilistic explanation for dealing with uncertainty while discovering dependencies over graphs. Furthermore, a case study is provided to verify the correctness of the data integration process based on GPDs. Preliminary results demonstrated the effectiveness of GPDs in terms of reducing redundancies and inconsistencies over the benchmark datasets.
    • Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks

      Saleem, Rabia; Yuan, Bo; Kurugollu, Fatih; Anjum, Ashiq; University of Derby; University of Leicester (IEEE, 2020-12-30)
      Artificial Intelligence (AI) models can learn from data and make decisions without any human intervention. However, the deployment of such models is challenging and risky because we do not know how the internal decisionmaking is happening in these models. Especially, the high-risk decisions such as medical diagnosis or automated navigation demand explainability and verification of the decision making process in AI algorithms. This research paper aims to explain Artificial Intelligence (AI) models by discretizing the black-box process model of deep neural networks using partial differential equations. The PDEs based deterministic models would minimize the time and computational cost of the decision-making process and reduce the chances of uncertainty that make the prediction more trustworthy.
    • A systematic review of evidence about the role of alexithymia in chronic back pain

      Elander, James; Kapadi, Romaana; Bateman, Antony H.; University of Derby; Royal Derby Spinal Centre, University Hospitals of Derby and Burton NHS Foundation Trust (British Psychological Society, 2021-02-01)
      Individuals with alexithymia struggle to make sense of their emotions. Alexithymia has been associated with a range of physical illnesses, but may influence different illnesses differently, so to understand the role of alexithymia in illness it is important to focus on specific conditions. This article reviews evidence from ten reports published between 2000 and 2018 of studies with samples of adults with chronic back pain that used the Toronto Alexithymia Scale (TAS). The studies were conducted in Germany, Israel, Italy, Russia, Turkey and the USA. Eight studies involved clinical samples and two involved public transit workers. Studies that compared participants with high and low alexithymia consistently found associations with measures of pain. The findings show that more severe alexithymia plays a role in the experience of chronic back pain, and support the incorporation of alexithymia-related elements in interventions to help people with chronic back pain improve their emotional regulation and reduce their pain-related distress.
    • A survey of interpretability of machine learning in accelerator-based high energy physics

      Turvill, Danielle; Barnby, Lee; Yuan, Bo; Zahir, Ali; University of Derby (IEEE, 2020-12-28)
      Data intensive studies in the domain of accelerator-based High Energy Physics, HEP, have become increasingly more achievable due to the emergence of machine learning with high-performance computing and big data technologies. In recent years, the intricate nature of physics tasks and data has prompted the use of more complex learning methods. To accurately identify physics of interest, and draw conclusions against proposed theories, it is crucial that these machine learning predictions are explainable. For it is not enough to accept an answer based on accuracy alone, but it is important in the process of physics discovery to understand exactly why an output was generated. That is, completeness of a solution is required. In this paper, we survey the application of machine learning methods to a variety of accelerator-based tasks in a bid to understand what role interpretability plays within this area. The main contribution of this paper is to promote the need for explainable artificial intelligence, XAI, for the future of machine learning in HEP.
    • Development of a novel 5kW/42V intelligent converter for automotive applications

      Amar, Bousbaine; Eljarh, M; University of Derby (IET, 2012-07-19)
      Growing pressure on the automotive industry to produce cars with less exhaust emission, better fuel economy, and to save energy necessitated the introduction of higher voltage electrical power system to meet these requirements in short to mid-term. Already, various electric systems architectures have been proposed and investigated over the past ten years. To meet such growing demands, the automotive industry has to move to higher voltage and the 42V power-net system is the preferred option [1]. The 42V is further processed by the interleaved six-phase dc-to- dc buck converter system to supply power to the conventional automotive loads that are expected to remain at 14V level as well as to absorb the peak transients on the 42V bus voltage. A special DC/DC converter is therefore needed to interconnect the 14V and the 42V DC buses in the car of the future. Automotive electronics place severe demands on the performance and price of power electronic components and making the development of a suitable converter a challenging task. This paper will present the initial development of the 5kW/42V intelligent converter for automotive applications using Matlab/Simulink.
    • A practical project approach for teaching experimental power electronics

      Amar, Bousbaine; Eljarh, Mohamed; University of Derby (VDE, 2011-09-05)
      This paper presents a design project, dc to dc converter, for a solar model car to provide hands-on engineering experience and real life educational design project. This paper focuses on the design, modelling, analysis and simulation of a dc/dc converter for a solar model car. A buck converter is designed and built to convert the output from a solar panel to a voltage level suitable for the electric motors that drive the model car. The effectiveness of the developed model is verified through simulation and corroborated using experimental results.
    • Simulation and experimental investigation into a photovoltaic and fuel cell hybrid integration power system for a typical small house application

      Djoudi, H; Benyahia, N; Badji, A; Bousbaine, Amar; Moualek, R; Aissou, S; Benamrouche, N; University of Tizi-Ouzou, Tizi-Ouzou, Algeria; French Naval Academy, Brest, France; Haute Alsace University, Mulhouse, France; et al. (Taylor & Francis, 2021-01-08)
      The paper addresses the simulation of a novel real-time implementation of a photovoltaic (PV) and fuel cell (FC) hybrid integration power system. The hybrid system has the potential of reducing the dependency on batteries, leading to reduced cost and increased life span of the whole system using the Proton Exchange Membrane (PEM) fuel cell. The interface structure of the hybrid system has been explored incorporating the Maximum Power Point Technique (MPPT) for maximum power extraction. The simulation of the hybrid system including fuel cell, PhotoVoltaic panels (PVs) and battery has been carried out using SimPowerSystems. An innovative Real Time Interface (RTI) approach using the concept of the Hardware-In-the-Loop (HIL) has been presented for a fast dynamic response of a closed loop control of the hybrid system. The corroboration of the hybrid system is validated experimentally, using a real photovoltaic panel connected to a PEM fuel cell emulator and battery. The PVs are controlled by the perturbation and observation Maximum Power point (MPP) technique and the PEM fuel cell is controlled through a boost DC-DC converter using current mode control. The whole system is implemented on the dSPACE 1103 platform for real-time interface and control strategies. The overall behavior of the hybrid system has been critically analyzed and corroboration of the simulated and experimental results have been presented.
    • ANTONYM: Life With and Without Animals: an online exhibition

      Bartram, Angela; Baker, Steve; University of Derby (2020-11)
      The online exhibition ANTONYM: Life With and Without Animals presents the work of eight artists from the UK, USA and Iceland at Artcore, Derby. Each makes artwork that engages with the more-than-human world, reflecting on contemporary threats to nonhuman life as well as on the pleasures of our relationships with other species. The exhibition coincides with the online conference Life With and Without Animals at the University of Derby, and is its companion exhibition. Like its companion, this exhibition was scheduled for physical delivery at Artcore, but due to the Covid-19 pandemic a decision was made to make this online. Both events were organised and curated by Steve Baker and Angela Bartram. The exhibition includes work by the following international artists: Andrea Roe and Cath Keay; Angela Bartram; Paula McCloskey and Sam Vardy; Johanna Hällsten; Julia Schlosser; Lee Deigaard; Bryndís Snæbjörnsdóttir and Mark Wilson; and Steve Baker.
    • Experimental characterisation of quad rotor controller based on Kalman Filter

      Fareha, Abdelkader; Bousbaine, Dr. Amar; Josaph, Ajay K; Amar, Bousbaine; University of Derby (IEEE, 2018-12-13)
      This paper presents experimental techniques to extract the calibration parameters needed for the control algorithm (electrical and aerodynamic constants) and Kalman filter (R and Q covariance matrices for noise measurement and process). The validation of the extracted parameters on the developed Matlab/Simulink models for the quadrotor are investigated before the final implementation of the real navigation algorithm system on quadcopter.
    • A Wireless communication system for a quadrotor helicopter

      Joseph, Ajay K; Bousbaine, Amar; Fareha, Abdelkader; Amar, Bousbaine; University of Derby (IEEE, 2018-12-13)
      The aim of this paper is to present real-time wireless communication between an AVR microcontroller and a quadcopter model built in Simulink representing a ground station. The wireless communication is achieved by using a pair of HC-05 Bluetooth modules. The wireless communication is performed on various controllers designed on Matlab/Simulink.
    • A More Refined Thermal Model for a Totally Enclosed Fan-cooled Induction Motor

      Amar, Bousbaine; University of Derby (Taylor and Francis Ltd, 2011-12-11)
      The aim of this article is to present a more refined thermal model based on a lumped parameter thermal network in which losses are determined more accurately from a 2D coupled electromagnetic complex finite-element method. In addition, saturation and end winding effects are taken into account. To check the validity of the theoretical results, an experimental investigation has been performed on a 2.2-kW totally enclosed fan-cooled induction motor. The calculated temperatures and those obtained from measurements are compared and showed good agreements. However, these results are comparable to those obtained previously (Benamrouche, N., Bouheraoua, M., and Haddad, S., “A thermal model for a TEFC induction motor—development and sensitivity analysis,” Elect. Power Compon. Syst., Vol. 34, No. 3, pp. 259–269, 2006), despite all the efforts and complexities involved.
    • Can compassion-focused imagery be used as an attention bias modification treatment?

      Leboeuf, Isabelle; McEwan, Kirsten; Rusinek, Stéphane; Andreotti, Eva; Antoine, Pascal; Université Lille Nord de France; University of Derby (Springer, 2021-01-06)
      Compassion focused-imagery (CFI), one of the psychological interventions of compassion-focused therapy, is receiving increasing attention. It is a therapeutic tool that targets the process of self-criticism by prompting individuals to imagine themselves as compassionate or to imagine receiving compassion from an ideal compassionate other. This research examines the role of self-criticism in the attentional processing of emotional stimuli, namely, critical and compassionate facial expressions. It is hypothesized that the activation of positive social emotions through CFI plays a role in broadening attention in the processing of emotional stimuli. The McEwan Faces stimulus set, which includes critical, neutral and compassionate faces, was used to create an attentional bias task called the dot probe task. The processing of emotional faces was assessed before and after exposure to either CFI or neutral imagery, controlling for the process of sensory integration (n = 80). A between-subject analysis was used to test the hypothesis. Before the imagery task, participants tended to look away from critical faces, and their level of self-criticism played a role. Both types of imagery significantly reduced the bias away from critical faces when the stimuli were presented for 1200 ms. This effect was reversed in the neutral condition for participants with high levels of self-criticism but not in the CFI condition. Interestingly, self-criticism impacts the attentional treatment of critical faces and the effect of imagery entailing sensory integration on this treatment. CFI seems to preserve this effect for participants with high levels of self-criticism, possibly due to the activation of positive social emotions.
    • The need for exercise sciences and an integrated response to COVID-19: A position statement from the international HL-PIVOT network

      Arena, Ross; Stoner, Lee; Haraf, Rebecca H.; Josephson, Richard; Hills, Andrew P.; Dixit, Snehil; Popovic, Dejana; Smith, Andy; Myers, Jonathan; Bacon, Simon L.; et al. (Elsevier, 2021-02-04)
      COVID-19 is one of the biggest health crises that the world has seen. Whilst measures to abate transmission and infection are ongoing, there continues to be growing numbers of patients requiring chronic support, which is already putting a strain on health care systems around the world and which may do so for years to come. A legacy of COVID-19 will be a long-term requirement to support patients with dedicated rehabilitation and support services. With many clinical settings characterized by a lack of funding and resources, the need to provide these additional services could overwhelm clinical capacity. This position statement from the Healthy Living for Pandemic Event Protection (HL-PIVOT) Network provides a collaborative blueprint focused on leading research and developing clinical guidelines, bringing together professionals with expertise in clinical services and the exercise sciences to develop the evidence base needed to improve outcomes for patients infected by COVID-19.
    • Life with and without animals: the second (Un)common worlds conference

      Bartram, Angela; Baker, Steve; University of Derby (University of Derby, 2020-11)
      Keynote speakers: Dr. Susan McHugh, Professor of English, University of New England and Snæbjörnsdóttir/Wilson - Dr Bryndís Snæbjörnsdóttir, Professor of Fine Art, Iceland University of the Arts, Reykjavík, and, Dr Mark Wilson, Professor of Fine Art, Institute of the the Arts, University of Cumbria, UK. Following the first (Un)common Worlds conference in Turku, Finland in 2018, called Contesting the Limits of Human – Animal Communities, the animal research group within the Digital and Material Artistic Research Centre at the University of Derby presented the second, Life With and Without Animals, a one-day online animal studies conference in November 2020. When the term ‘animal studies’ was coined in the early 1990s it was initially envisaged rather narrowly as a subfield of the social sciences, but by the time of two large and ground-breaking international conferences in 2000 – Representing Animals in Milwaukee and Millennial Animals in Sheffield – it was clear that the arts and humanities were at least as important to this nascent field as the social sciences. Some of the concerns of those early conferences remain as important as ever: the avoidance of anthropocentrism, an attention to the lives and experience of nonhuman animals that does not reduce them to symbolic representations of human values, and a recognition of the contested but necessary role of animal advocacy within the field of animal studies. Other priorities have shifted, perhaps most importantly in recognition of the impact of climate change, environmental degradation and species extinctions, and the changes these have brought about to our understanding of, and engagement with the more-than-human world. This conference conveyed a sense of what the interdisciplinary field of animal studies looked like in 2020, and included contributions in support of this proposal. Originally planned as a three-day physical conference for July 2020, this was rescheduled and re-orientated for online delivery over a day in November 2020 due to the Covid-19 pandemic. A recording of the day is attached to this record. Conference leads: Professor Steve Baker and Professor Angela Bartram.
    • A case study on the impact list event sound level regulations have on sound engineering practice

      Hill, Adam J.; Burton, Jon; University of Derby (Institute of Acoustics, 2020-11)
      Sound level management at live events in becoming increasingly common at live events in the UK, Europe and beyond. An inspection of regulations across the globe reveals a lack of standardization for sound level limits and averaging times. This case study is formed around a dataset generated on a recent tour by a well-known British musical act. The same sound engineer mixed the band throughout the tour using sound level monitoring software throughout. As the show’s configuration, engineer, musicians and running order were generally consistent day-to-day, the direct inspection of the influence of sound level limit and averaging time, as well as venue capacity and type (indoors or outdoors), is possible. The results from this study highlight both good and bad sound management practice, with key stakeholders’ experience and hearing safety in mind.
    • Delineating non-consensual sexual image offending: Towards an empirical approach

      Harper, Craig, A; Fido, Dean; Petronzi, Dominic; Nottingham Trent University; University of Derby (Elsevier, 2021-01-07)
      The topic of non-consensual sexual images has become an increasingly important issue within the social policy landscape. Social and legal scholars have advocated for these behaviours to be designated sexual offences due to the mode of perpetration of these behaviours, but are explicit in their rejection of a sexual element being important in the motivations underpinning such behaviours. However, this rejection is inconsistent with the core theoretical models related to sexual offending. In this article, we outline some of the potential psychological concepts that may help us to understand how and why people engage in a range of non-consensual sexual image offences, such as revenge pornography, upskirting, deepfake media production, and cyber-flashing. In doing so, we aim to begin to bridge the gap between legal scholars and psychological scientists, and develop a more comprehensive and theoretically coherent approach to studying this important social topic.
    • Tweets classification and sentiment analysis for personalized tweets recommendation

      Batool, Rabia; Satti, Fahad Ahmed; Hussain, Jamil; Khan, Wajahat Ali; Khan, Adil Mehmood; Hayat, Bashir; University of Derby (Hindawi, 2020-12-17)
      Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately.
    • A multilevel multidimensional finite mixture item response model to cluster respondents and countries: the forms of self-criticising/attacking and self-reassuring scale

      Kanovský, Martin; Halamová, Júlia; Zuroff, David C.; Troop, Nicholas A.; Gilbert, Paul; Shahar, Ben; Petrocchi, Nicola; Hermanto, Nicola; Krieger, Tobias; Kirby, James N.; et al. (Hogrefe Publishing Group, 2020-12-30)
      The aim of this study was to test the multilevel multidimensional finite mixture item response model of the Forms of Self-Criticising/Attacking and Self-Reassuring Scale (FSCRS) to cluster respondents and countries from 13 samples (N = 7,714) and from 12 countries. The practical goal was to learn how many discrete classes there are on the level of individuals (i.e., how many cut-offs are to be used) and countries (i.e., the magnitude of similarities and dissimilarities among them). We employed the multilevel multidimensional finite mixture approach which is based on an extended class of multidimensional latent class Item Response Theory (IRT) models. Individuals and countries are partitioned into discrete latent classes with different levels of self-criticism and self-reassurance, taking into account at the same time the multidimensional structure of the construct. This approach was applied to the analysis of the relationships between observed characteristics and latent trait at different levels (individuals and countries), and across different dimensions using the three-dimensional measure of the FSCRS. Results showed that respondents’ scores were dependent on unobserved (latent class) individual and country membership, the multidimensional structure of the instrument, and justified the use of a multilevel multidimensional finite mixture item response model in the comparative psychological assessment of individuals and countries. Latent class analysis of the FSCRS showed that individual participants and countries could be divided into discrete classes. Along with the previous findings that the FSCRS is psychometrically robust we can recommend using the FSCRS for measuring self-criticism.
    • NGO accountability on environmentalism: a literature review of relevant issues and themes

      Yekini, Liafisu Sina; Yekini, Kemi, C; University of Derby (Emerald Publishing, 2021-01-04)
      This chapter, which is in themes, starts with a survey of the rise of environmentalism for the purpose of sustainability. It then evaluates the roles of nongovernmental organisations' (NGOs') self-regulation and government regulation on the need for accountability that ensures sustainability. NGOs' accountability is a way of making sure that stakeholders' social, environmental and economic sustainability are protected and rigorously evaluated. This chapter further examines what the enduring mechanisms should be if true accountability, which leads to sustainability, will be achieved to suggest a holistic accountability that involves downward and upward accountability. In doing so, this chapter utilised the identified five mechanisms that ensure the continuity of world sustainability, which is prima-facie, the objective of funders/donors, beneficiaries/stakeholders and the NGO's loop.