Now showing items 21-40 of 5628

    • A GRU-based prediction framework for intelligent resource management at cloud data centres in the age of 5G

      Lu, Yao; Liu, Lu; Panneerselvam, John; Yuan, Bo; Gu, Jiayan; Antonopoulos, Nick; University of Leicester; University of Derby; Edinburgh Napier University (IEEE, 2019-11-19)
      The increasing deployments of 5G mobile communication system is expected to bring more processing power and storage supplements to Internet of Things (IoT) and mobile devices. It is foreseeable the billions of devices will be connected and it is extremely likely that these devices receive compute supplements from Clouds and upload data to the back-end datacentres for execution. Increasing number of workloads at the Cloud datacentres demand better and efficient strategies of resource management in such a way to boost the socio-economic benefits of the service providers. To this end, this paper proposes an intelligent prediction framework named IGRU-SD (Improved Gated Recurrent Unit with Stragglers Detection) based on state-of-art data analytics and Artificial Intelligence (AI) techniques, aimed at predicting the anticipated level of resource requests over a period of time into the future. Our proposed prediction framework exploits an improved GRU neural network integrated with a resource straggler detection module to classify tasks based on their resource intensity, and further predicts the expected level of resource requests. Performance evaluations conducted on real-world Cloud trace logs demonstrate that the proposed IGRU-SD prediction framework outperforms the existing predicting models based on ARIMA, RNN and LSTM in terms of the achieved prediction accuracy.
    • A privacy-preserved probabilistic routing index model for decentralised online social networks

      Yuan, Bo; Gu, Jiayan; Liu, Lu; University of Derby; University of Leicester (IEEE, 2020-04-09)
      Despite the tremendous success of online social networks (OSNs), centrally controlled OSNs have inherent issues related to lack of user privacy and single point of failure. These limitations have motivated the research community to shift the computing paradigm from a centralised architecture to decentralised alternatives. Existing research works mainly focused on the routing mechanisms using social information in decentralised OSNs, without considering the user's privacy. This paper proposes a self-organised decentralised architecture (SDA) that leverages privacy-preserved routing methods to facilitate query routing in decentralised social networks. This architecture encompasses a hash-based profiling model to characterise semantic features of the user's content with low dimensionality and privacy-aware mechanisms to organise similarity users into semantic communities. Furthermore, a probabilistic routing method is proposed to support efficient information dissemination and service discovery. The correctness and efficiency of our proposed approach are evaluated through simulations on real-world datasets. The experimental results demonstrated that our approach achieved a better topological structure with high routing efficiency.
    • Artificial neural networks training acceleration through network science strategies

      Cavallaro, Lucia; Bagdasar, Ovidiu; De Meo, Pasquale; Fiumara, Giacomo; Liotta, Antonio; University of Derby; University of Messina, Polo Universitario Annunziata, 98122, Messina, Italy; Free University of Bozen-Bolzano, Bolzano, Italy (Springer Science and Business Media LLC, 2020-09-09)
      The development of deep learning has led to a dramatic increase in the number of applications of artificial intelligence. However, the training of deeper neural networks for stable and accurate models translates into artificial neural networks (ANNs) that become unmanageable as the number of features increases. This work extends our earlier study where we explored the acceleration effects obtained by enforcing, in turn, scale freeness, small worldness, and sparsity during the ANN training process. The efficiency of that approach was confirmed by recent studies (conducted independently) where a million-node ANN was trained on non-specialized laptops. Encouraged by those results, our study is now focused on some tunable parameters, to pursue a further acceleration effect. We show that, although optimal parameter tuning is unfeasible, due to the high non-linearity of ANN problems, we can actually come up with a set of useful guidelines that lead to speed-ups in practical cases. We find that significant reductions in execution time can generally be achieved by setting the revised fraction parameter (ζ) to relatively low values.
    • An application of judgment analysis to examination marking in psychology

      Elander, James; Hardman, David; University of Derby; London Guildhall University (Wiley, 2002)
      Statistical combinations of specific measures have been shown to be superior to expert judgement in several fields. In this study judgement analysis was applied to examination marking to investigate factors that influenced marks awarded and contributed to differences between first and second markers. Seven markers in psychology rated 551 examination answers on seven 'aspects' for which specific assessment criteria had been developed to support good practice in assessment. The aspects were addressing the question, covering the area, understanding, evaluation, development of argument, structure and organisation, and clarity. Principal components analysis indicated one major factor and no more than two minor factors underlying the seven aspects. Aspect ratings were used to predict overall marks, using multiple regression regression to ‘capture’ the marking policies of individual markers. These varied from marker to marker in terms of the numbers of aspect ratings that made independent contributions to the prediction of overall marks and the extent to which aspect ratings explained the variance in overall marks. The number of independently predictive aspect ratings, and the amount of variance in overall marks explained by aspect ratings, were consistently higher for first markers (question setters) than for second markers. Co-markers’ overall marks were then used as an external criterion to test the extent to which a simple model consisting of the sum of the aspect ratings improved on overall marks in the prediction of co-markers marks. The model significantly increased the variance in co-markers’ marks accounted for, but only for second markers, who had not taught the material and not set the question. Further research is needed to develop the criteria and especially to establish the reliability and validity of specific aspects of assessment. The present results support the view that, for second markers at least, combined measures of specific aspects of examination answers may help to improve the reliability of marking.
    • Comprehensive review of the recent advances in PV/T system with loop-pipe configuration and nanofluid

      Cui, Yuanlong; Zhu, Jie; Zoras, Stamatis; Zhang, Jizhe; University of Derby; University of Nottingham; Shandong University (Elsevier, 2020-08-24)
      Solar photovoltaic/thermal technology has been widely utilized in building service area as it generates thermal and electrical energy simultaneously. In order to improve the photovoltaic/thermal system performance, nanofluids are employed as the thermal fluid owing to its high thermal conductivity. This paper summarizes the state-of-the-art of the photovoltaic/thermal systems with different loop-pipe configurations (including heat pipe, vacuum tube, roll-bond, heat exchanger, micro-channel, U-tube, triangular tube and heat mat) and nanoparticles (including Copper-oxide, Aluminium-oxide, Silicon carbide, Tribute, Magnesium-oxide, Cerium-oxide, Tungsten-oxide, Titanium-oxide, Zirconia-oxide, Graphene and Carbon). The influences of the critical parameters like nanoparticle optical and thermal properties, volume fraction, mass flux and mass flow rates, on the photovoltaic/thermal system performance are for the optimum energy efficiency. Furthermore, the structure and manufacturing of solar cells, micro-thermometry analysis of solar cells and recycling process of photovoltaic panels are explored. At the end, the standpoints, recommendations and potential future development on the solar photovoltaic/thermal system with various configurations and nanofluids are deliberated to overcome the barriers and challenges for the practical application. This study demonstrates that the advanced photovoltaic/thermal configuration could improve the system energy efficiency approximately 15%–30% in comparison with the conventional type whereas the nanofluid is able to boost the efficiency around 10%–20% compared to that with traditional working fluid.
    • The recognition and management of sepsis in urgent care out of hours setting

      Mortimore, Gerri; University of Derby (MAG, 2020-07-11)
      As the majority of sepsis cases occur in the community, Justine Dexter and Gerri Mortimore provide an overview of the assessment, diagnosis and management of the condition for those working in out of hours settings. Sepsis is a life-threatening and common condition prompted by a microbial infection. Sepsis is responsible for the death of more people than prostate, bowel or breast cancer collectively, and it causes the second highest mortality rates after cardiovascular disease. The majority of sepsis cases occur in the community, with 30% developing while the patient is in hospital. In many instances, sepsis is avoidable and treatable. The aetiology of sepsis is not always known, making diagnosis difficult, with only 50% of cases having a confirmed pathogenic organism. The signs and symptoms most obviously connected with sepsis are confusion or unusual behaviour, hypotension and increased respiratory rate. However, some patients have non-specific symptoms, and just complain of feeling extremely unwell. Any patients who have these signs or symptoms should be assessed for the possibility of sepsis, regardless of whether pyrexia is present. To aid in detection and decision making about sepsis, the use of screening tools have been advocated to shorten the period prior to the administration of antibiotics. Children characteristically compensate physiologically for a considerable time and then deteriorate quickly; therefore, a crucial focus is to spot a sick child rapidly. Many urgent care out of hours (UCOOH) services are nurse-led. Therefore, it often falls on advanced nurse practitioners (ANPs) to educate healthcare assistants to spot the sick person, especially as they are usually the first person the patient sees. Leadership plays a key role for ANPs in UCOOH by helping to progress the pathway for patients to ensure the sickest are prioritised.
    • The impacts of R&D investment and stock markets on clean energy uses and CO2 emissions in a panel of OECD economies

      Apergis, Nicholas; Alam, Md. Samsul; Paramati, Sudharshan Reddy; Fang, Jianchun; University of Derby; De Montfort University; University of Dundee; Zhejiang University of Technology (Wiley, 2020-09-14)
      The goal of this paper is to examine to what extent R&D investment and stock market development promote clean energy consumption and environmental protection across a panel of 30 OECD economies. Based on the IPAT theoretical approach, study employs robust panel econometric models which account for cross-sectional dependence in the analysis and uses annual data, spanning the period 1996 to 2013. The empirical results illustrate that R&D and stock market have a significant long-run equilibrium relationship with clean energy and CO2 emissions. The long-run elasticities display that R&D and stock market growth have a significant positive impact on clean energy consumption, while they have a negative effect on the growth of CO2 emissions. Given these findings, the paper suggests that the policy makers in the OECD economies should realize that it is worth investing in R&D activities as it is promoting the use of clean energy and ensuring low carbon economies. Therefore, the policymakers have to initiate effective policies to promote R&D activities and also encourage the firms that are listed in the stock market to adopt environmental friendly policies.
    • Natural disasters and housing prices: Fresh evidence from a global country sample

      Apergis, Nicholas; University of Derby (Asian Real Estate Society, 2020)
      Given that the literature on the impact of natural disasters on house prices is highly limited, this paper combines data on natural disasters and house prices from 117 countries, spanning the period 2000-2018 and a panel regression method to estimate the effects of natural disasters on house prices. The findings document that natural disasters lead to lower house prices, with the results surviving a number of robustness tests. When examining the impacts of natural disasters by type, the findings highlight that geological disasters exert the strongest (negative) impact on house prices. The results also illustrate the negative impact of those disasters on house prices when the distinction between small and large disasters is also accounted. The findings provide important implications for policymakers and property investors. Lower house prices in countries experience natural disasters events could significantly signify lower consumption and investment (the wealth effect), with further negative spillovers to the real economy. Economic policymakers could implement low-tax policies or quantitative easing schemes to support these areas/countries. The findings exemplify the need of governments and policymakers to mitigate climate change effects on housing by adopting new, more environmentally friendly technologies and energy sources.
    • Institutional development and the Astana international financial center in Kazakhstan

      Huang, Flora; Yeung, Horace; Bekmurzayeva, Zhanyl; Janaidar, Dina; University of Essex (Washington University, 2020)
      This article investigates the most recent instance of the transplantation of English corporate and financial law into a different legal environment. The Astana International Financial Center (AIFC) in Kazakhstan was launched in 2018. The AIFC has largely built on the institutional model pioneered by the Dubai International Financial Center. This key institutional innovation is the transplanting and operation of laws based on the English common law, independent of their national legal systems (civil law systems, heavily influenced by Islamic tradition, and, in the case of Kazakhstan, also Soviet socialist principles). This article seeks to contribute to the understanding of the system of Kazakhstan, a strategically located but well under-investigated country, and a potentially viable institutional model for other aspiring financial centers. To the best knowledge of the authors, this work is the first ever English academic literature on the development of the AIFC.
    • Energy consumption, carbon dioxide emissions and economic growth: Fresh evidence from 57 countries and panel quantile regressions

      Apergis, Nicholas; Altinoz, Buket; Aslan, Alper; University of Derby; Nisantasi University; Erciyes University (Asian Pacific Economic Association, 2020-09-11)
      This paper analyzes the association across energy consumption, carbon dioxide emissions and economic growth. According to the results of panel quantile regression model for 57 countries from three different regions, deviations from sustainable growth after the middle growth level in the full sample and the European and Asian countries sample are prominent. Similar results are obtained from Middle East and African countries, but the deviations begin earlier. In the case of the Latin American findings, the estimates clearly document that carbon emissions (at all levels) and energy consumption (at the medium and high levels) exert a negative impact on economic growth, indicating the inability of Latin American countries to achieve sustainable economic growth targets.
    • The role of Covid-19 for Chinese stock returns: evidence from a GARCHX model

      Apergis, Nicholas; Apergis, Emmanuel; University of Derby; University of Huddersfield (Taylor & Francis, 2020-09-03)
      This paper examines the effect of Covid-19 pandemic on the Chinese stock market returns and their volatility using the generalized autoregressive conditionally heteroskedastic GARCHX model. The GARCHX model allows us to include Covid-19 information within the GARCH framework. The findings document that daily increases in total confirmed Covid-19 cases in China, measured as total daily deaths and cases, have a significant negative impact on stock returns, with the negative impact of the Covid-19 on stock returns being more pronounced when total deaths proxy the effect of this infectious disease. The results also document that Covid-19 has a positive and statistically significant effect on the volatility of these market returns. Overall, new evidence is offered that infectious diseases, such as Covid-19, can seriously impact market returns, as well as their volatility. The findings could be essential in understanding the implications of Covid-19 for the stock market in China.
    • U.S. monetary policy and herding: Evidence from commodity markets

      Apergis, Nicholas; Christou, Christina; Hayat, Tasawar; Saeed, Tareq; University of Derby; Open University of Cyprus; King Abdulaziz University (Springer, 2020-08-28)
      This paper investigates the presence of herding behavior across a spectrum of commodities (i.e., agricultural, energy, precious metals, and metals) futures prices obtained from Datastream. The main novelty of this study is, for the first time in the literature, the explicit investigation of the role of deviations of U.S. monetary policy decisions from a standard Taylor-type monetary rule, in driving herding behavior with respect to commodity futures prices, spanning the period 1990-2017. The results document that the commodity markets are characterized by herding, while such herding behavior is not only driven by U.S. monetary policy decisions, but also such decisions exert asymmetric effects this behavior. An additional novelty of the results is that they document that herding is stronger in discretionary monetary policy regimes.
    • Stability of discrete-time fractional-order time-delayed neural networks in complex field

      Pratap, Anbalagan; Raja, Ramachandran; Cao, Jinde; Huang, Chuangxia; Niezabitowski, Michal; Bagdasar, Ovidiu; Alagappa University, Karaikudi, India; Southeast University, Nanjing, China; Changsha University of Science and Technology, Changsha 410114, China; University of Technology, Gliwice, Poland; et al. (Wiley, 2020-07-30)
      Dynamics of discrete‐time neural networks have not been well documented yet in fractional‐order cases, which is the first time documented in this manuscript. This manuscript is mainly considered on the stability criterion of discrete‐time fractional‐order complex‐valued neural networks with time delays. When the fractional‐order β holds 1 < β < 2, sufficient criteria based on a discrete version of generalized Gronwall inequality and rising function property are established for ensuring the finite stability of addressing fractional‐order discrete‐time‐delayed complex‐valued neural networks (FODCVNNs). In the meanwhile, when the fractional‐order β holds 0 < β < 1, a global Mittag–Leffler stability criterion of a class of FODCVNNs is demonstrated with two classes of neuron activation function by means of two different new inequalities, fractional‐order discrete‐time Lyapunov method, discrete version Laplace transforms as well as a discrete version of Mittag–Leffler function. Finally, computer simulations of two numerical examples are illustrated to the correctness and effectiveness of the presented stability results.
    • Persation: an IoT based personal safety prediction model aided solution

      Alofe, Olasunkanmi Matthew; Fatema, Kaniz; Azad, Muhammad Ajmal; Kurugollu, Fatih; University of Derby; Aston University, Birmingham (University of Bahrain, 2020)
      The number of attacks on innocent victims in moving vehicles, and abduction of individuals in their vehicles has risen alarmingly in the past few years. One common scenario evident from the modus operandi of this kind of attack is the random motion of these vehicles, due to the driver’s unpredictable behaviours. To save the victims in such kinds of assault, it is essential to offer help promptly. An effective strategy to save victims is to predict the future location of the vehicles so that the rescue mission can be actioned at the earliest possibility. We have done a comprehensive survey of the state-of-the-art personal safety solutions and location prediction technologies and proposes an Internet of Things (IoT) based personal safety model, encompassing a prediction framework to anticipate the future vehicle locations by exploiting complex analytics of current and past data variables including the speed, direction and geolocation of the vehicles. Experiments conducted based on real-world datasets demonstrate the feasibility of our proposed framework in accurately predicting future vehicle locations. In this paper, we have a risk assessment of our safety solution model based on OCTAVE ALLEGRO model and the implementation of our prediction model.
    • Here’s looking at youse: Understanding the place of yous(e) in Australian English

      Mulder, Jean; Penry Williams, Cara; University of Melbourne, Australia; University of Derby (Springer, 2020-08-31)
      This chapter further documents the place of yous(e) in Australian English (AuE) by analyzing occurrences in Australian literature taken from the Macquarie Dictionary’s OzCorp. Firstly, we substantiate that in AuE yous(e) has developed a singular usage alongside the plural. Analysis of the reference in 308 tokens within our subcorpus of literature finds 40% clearly have a singular referent and that such forms occur in just over half of the texts. Secondly, we provide an analysis of its social evaluation as a stigmatized form by examining its utilization in the voices authors give to their characters. Focussing on texts with high use, we uncover yous(e) is linked both to particular ‘types’ and to certain fictional worlds/milieus. In both cases, the authors draw on understandings of it as Australian and working class, with recognition of its claimed Irish origins only (potentially) indirectly indexed.
    • Endings are not always completed with a full stop

      Jones, Rhiannon; University of Derby (Intellect Books, 2020-11-06)
      This chapter provides a critical discourse between Jones and Pinchbeck about the making of The Trilogy, offering a unique framework for a dialogue on dramaturgy. The conversation metaphorically occupies the corner points marked out on a stage, balanced on the edges of white masking tape, the threshold of dramaturgy. The chapter explores the dramaturgical twists and turns in the making of The Trilogy. Divided into three parts, The Preview, The Interview The Review and it is presented as a release statement from a contract in a final act of ‘signing off’ The Trilogy. A final act marked in permanent ink honouring that promise Pinchbeck once made never to perform again. The dialogue questions the undulations of dramaturgy and, like the work, the discourse between Jones and Pinchbeck consciously touches at the edges, it is sticky and non-linear. It weaves together fragments of other contributors’ voices in order to float a range of ideas. Of falling in and out of love with the theatre. And a conversation takes place.
    • RE: AB (termination of pregnancy)[2019] EWA CIV 1215: ‘wishes and feelings’ under the mental capacity act 2005

      Cherkassky, Lisa; University of Derby (Oxford University Press (OUP), 2020-06-15)
      In Re: AB (Termination of Pregnancy), the Court of Appeal was asked to consider an assumption made about the future living arrangements of a pregnant patient, and the weight to be ascribed to her wishes and feelings when she had no real understanding of her predicament. This commentary explores the importance of taking into account the perspective of the patient, even if suffering from a mental disorder, and it will analyse the existing common law to show that the weaker the ability of the patient to form her own wishes and feelings, the more appropriate it would be to rely on the remaining evidence.
    • An inductive content-augmented network embedding model for edge artificial intelligence

      Yuan, Bo; Panneerselvam, John; Liu, Lu; Antonopoulos, Nick; Lu, Yao; University of Derby; Tongji University, Shanghai, China; University of Leicester; Edinburgh Napier University (IEEE, 2019-03-04)
      Real-time data processing applications demand dynamic resource provisioning and efficient service discovery, which is particularly challenging in resource-constraint edge computing environments. Network embedding techniques can potentially aid effective resource discovery services in edge environments, by achieving a proximity-preserving representation of the network resources. Most of the existing techniques of network embedding fail to capture accurate proximity information among the network nodes and further lack exploiting information beyond the second-order neighbourhood. This paper leverages artificial intelligence for network representation and proposes a deep learning model, named inductive content augmented network embedding (ICANE), which integrates the network structure and resource content attributes into a feature vector. Secondly, a hierarchical aggregation approach is introduced to explicitly learn the network representation through sampling the nodes and aggregating features from the higher-order neighbourhood. A semantic proximity search model is then designed to generate the top-k ranking of relevant nodes using the learned network representation. Experiments conducted on real-world datasets demonstrate the superiority of the proposed model over the existing popular methods in terms of resource discovery and the query resolving performance.
    • Psychometric properties of the German version of the fears of compassion scales

      Biermann, Miriam; Bohus, Martin; Gilbert, Paul; Vonderlin, Ruben; Cornelisse, Sven; Osen, Bernhard; Graser, Johannes; Brüne, Martin; Ebert, Andreas; Lyssenko, Lisa; et al. (Wiley, 2020-08-18)
      The cultivation of compassion is associated with beneficial effects on physical and psychological health, satisfaction with life and social relationships. However, some individuals, especially those high in psychopathological symptoms or those with particular disorders such as borderline personality disorder (BPD) may demonstrate pronounced fears of engagement in compassionate experiences or behaviours. Furthermore, fears of compassion have been found to impede progress in psychotherapy. The 38‐item fears of compassion scales (FCS) is a self‐report questionnaire for measuring trait levels of fears of compassion (a) one receives from others (FCFO), (b) one feels towards others (FCTO) and (c) one feels for oneself (self‐compassion; FSC). The FCS is an internationally used instrument of proven validity and reliability in both clinical and nonclinical samples. In the present study, a German translation of the FCS including its three subscales was provided, and the psychometric properties were examined in 430 participants from four different samples: (a) a sample from the general population; (b) a mixed sample of psychiatric residential and outpatients; (c) a clinical sample of residential and outpatients with a primary diagnosis of BPD and (d) a sample of healthy control participants. Internal consistencies were excellent for the German version of the FSC and acceptable to excellent for its subscales. Correlations with established measures of mental health demonstrate its validity. Additionally, the German FCS discriminates significantly between individuals from the general population and patients, thus supporting its specificity. The German FCS is suitable to detect potential obstacles in cultivating compassion in psychotherapeutic treatments and beyond.