20505 research outputs found
Sort by
Promoting Sino-UK Collaboration on Developing Low Carbon and Sustainable Methodologies for Brownfields and Marginal Land Re-use in China
Get PDFThe authors are grateful to all partners of the SPF project which include a wide team of
collaborators and advisors across China and UK for their useful discussions and contribution during the project. Ming Liu and Chris He (Department of Science, Technology & Innovation, British Consulate-General Guangzhou), Rongxia Liu and Xia Yang (Administrative Centre for China’s Agenda21), Kate Canning (Arup) and David Middleton (Department for Environment and Rural Affairs, UK) helped discussion and revision of the report.
We acknowledge the financial support from the Foreign Common Office’s Prosperity Fund programme. We also are grateful to the contribution of the University of Brighton and the Land Trust who supported the PSRP case study development project and shared its findings with this project.
This report is one of the outputs of the China Prosperity Strategic Programme Fund (SPF) on “Promoting Sino-UK collaboration on developing low carbon and sustainable methodologies for Brownfields and marginal land re-use in China” (project 16AG15)Rapid urbanisation and changes in land use resulting from industrial change has left a legacy of vast polluted industrial and commercial areas (also called brownfields) and marginal land areas. Recent evidence from the UK, EU and USA indicate that these land areas may have considerable potential for renewables production, for example from solar, wind or biomass. In parallel there are opportunities for carbon storage in rehabilitated soil, as well as substitution by the production of renewables. The UK is also leading the understanding in the wider parallel benefits that can be achieved from ecosystem services and public health benefits from improved provision of green space. These multiple services can be provided together, in synergy, from soft re-uses of post-industrial sites, and in this way the post-industrial regeneration areas in China should be seen as a major opportunity for new enterprise, society and the wider environment. The improving bankability of renewable energy projects, and the possibility of creating a voluntary carbon offset business, means that revenue streams may be sufficient to pay for ongoing land management over time as a profit generating activity. In terms of fastest benefit to UK PLC and China, the likelihood is that combination of renewable energies with “dual use” for habitat will provide both more readily commercial brownfield re-use opportunities for cities in China in the short term, and also create better carbon management opportunities, as well as a variety of wider sustainability benefits. Thus this type of re-uses will create a platform for rapid commercial exchange and development between Chinese and UK companies. Considering that China is preparing an action plan for managing soil pollution and remediation across the country estimated to be RMB 7tn which is equivalent to one-third of the national exchange reserves, this report on developing low carbon and sustainable methodologies for brownfields and marginal land re-use in China provides timely information that will support the decision making for sustainable remediation opportunities in China.
The report is intended to serve as a tool and resource guide to stakeholders involved in land remediation willing to engage in sustainable remediation implementation for renewable energy and carbon management applications. It is intended to inform remediation stakeholders unfamiliar with sustainable remediation about the concept, practices, and available resources. The report capitalises on UK leadership positions on the sustainable rehabilitation of brownfields land (SURF-UK), the soft re-use of brownfields (e.g. for energy or amenity rather than buildings); effective end-use directed risk management for contaminated land, and
sustainable remediation.Foreign Common Office’s Prosperity Fund programme SPF project 16AG1
Land Contamination and Brownfield Management Policy Development in China: Learning from the UK Experience
Get PDFMing Liu (Department of Science, Technology & Innovation, British Consulate-General Guangzhou), Xia Yang (Administrative Centre for China’s Agenda21) and Paul Wills (UK Trade & Investment) helped discussion and revision of the report. Diogo Gomes (Cranfield University) also provided support for the graphical arts and assisted with the editing.
The authors are grateful to all partners of the SPF project which include a wide team of collaborators and advisors across China and UK for their useful discussions and contribution during the two workshops organised during the project. Government, Academia, Industry and Public bodies have been collaborating together to drive structural changes far beyond the scope of a single organisation.Over the last 30 years, China’s fast urbanisation along with huge expansion of its manufacturing industry has
led to the emergence of significant soil and water contamination problems across China. In the meantime, a number of policies and regulatory agencies for the protection of the environment have been implemented to stop deliberate pollution and more recently to address pollution prevention at source on a wider scale.
Soil protection and management have been featured in policy discussions since the late 1950s in China.
However, the topic has recently been of greatly expanded interest in the development of
emerging policies, particularly with regards to the role of soil as a resource, independent of the functions that it carries out. Soil provides multiple important functions such as provision of food and raw materials, a platform for urban development and human wellbeing and a filtering and transforming media for water, nutrients, and carbon.
However as pointed out by Yuan Si, Deputy Director of the Environmental Protection and
Resources Conservation Committee of the National People Congress (China Daily, 11 March 2016), the move toward integrated management that has been driving policies for air and water has proven to be a challenge for soil management, mainly due to the multiple functions that soils provide. This is also true internationally and explained by several drivers for soil protection including among others soil contamination, construction, agriculture and amenity value.Foreign and Commonwealth Office’s Prosperity Fund programme - China Prosperity Strategic Programme Fund (SPF) 15SU3
Subtractive clustering Takagi-Sugeno position tracking for humans by low-cost inertial sensors and velocity classification
Get PDFIn this work, open-loop position tracking using low-cost inertial measurement units is aided by Takagi-Sugeno velocity classification using the subtractive clustering algorithm to help generate the fuzzy rule base. Using the grid search approach, a suitable window of classified velocity vectors was obtained and then integrated to generate trajectory segments. Using publicly available experimental data, the reconstruction accuracy of the method is compared against four competitive pedestrian tracking algorithms. The comparison on selected test data, has demonstrated more competitive relative and absolute trajectory error metrics. The proposed method in this paper is also verified on an independent experimental data set. Unlike the methods which use deep learning, the proposed method has shown to be transparent (fuzzy rule base). Lastly, a sensitivity analysis of the velocity classification models to perturbations from the training orientation at test time is investigated, to guide developers of such data-driven algorithms on the granularity required in an ensemble modelling approach. The accuracy and transparency of the approach may positively influence applications requiring low-cost inertial position tracking such as augmented reality headsets for emergency responders.Engineering and Physical Sciences Research Council (EPSRC): EP/S513623/1
BAE SystemsMeasurement and Contro
Historical defence capability analysis: applying the defence lines of development retrospectively
Get PDFThe Defence Lines of Development (DLOD) used by the Ministry of Defence encompass all elements of military capability. Historical study of military capabilities does not use a similar or equivalent model. Richard Fisher describes how the current DLOD model can be used to analyse historical capabilities. He provides an objective approach to any comparison by capturing the training, equipment, personnel, information, doctrine and concepts, organisation, infrastructure and logistics requirements of machine gunnery in the British Army from the First World War to the 1960s, as a case study to demonstrate the method.RUSI Journa
Perceptions of farming stakeholders towards automating dairy cattle mobility and body condition scoring in farm assurance schemes
Get PDFAnimal welfare standards are used within the food industry to demonstrate efforts in reaching higher welfare on farms. To verify compliance with those standards, inspectors conduct regular on-farm animal welfare assessments. Conducting these welfare assessments can, however, be time-consuming and prone to human bias. The emergence of Digital Livestock Technologies (DLTs) offers new ways of monitoring farm animal welfare and can alleviate some of the challenges related to animal welfare assessments by collecting data automatically and more frequently. Whilst automating welfare assessments with DLTs may be promising, little attention has been paid to farmers’ perceptions of the challenges that could prevent successful implementation. This study aims to address this gap by focusing on the trial of a DLT (a 3D machine learning camera) to automate mobility and body condition scoring on 11 dairy cattle farms. Semi-structured, in-depth interviews were conducted with farmers, technology developers and a stakeholder involved in a farm assurance scheme (N=14). Findings suggest that stakeholders perceived important benefits to the use of the camera in this context, from building consumer trust by increasing transparency to improved management efficiency. There was also a potential for greater consistency in data collection and thus for enhanced fairness across the UK dairy sector, particularly on the issue of lameness prevalence. However, stakeholders also raised important concerns, such as a lack of clarity around data ownership, reliability, and use, and the possibility of some farmers being penalised (e.g., if the technology failed to work). Better clarity should thus be given to farmers in relation to data governance and evidence provided in terms of technical performance and accuracy. The findings of this study highlighted the need for more inclusive approaches to ensure farmers’ concerns are adequately identified and addressed. These approaches can help minimise negative consequences to farmers and animal welfare, whilst maximising the potential benefits of automating welfare-related data collection.anima
5G aviation networks using novel AI approach for DDoS detection
Get PDFThe advent of Fifth Generation (5G) technology has ushered in a new era of advancements in the aviation sector. However, the introduction of smart infrastructure has significantly altered the threat landscape at airports, leading to an increased vulnerability due to the proliferation of endpoints. Consequently, there is an urgent requirement for an automated detection system capable of promptly identifying and thwarting network intrusions. This research paper proposes a deep learning methodology that merges a Convolutional Neural Network (CNN) with a Gated Recurrent Unit (GRU) to effectively detect various types of cyber threats using tabular-based image data. To transform time series features into 2D texture images, Gramian Angular Fields (GAFs) are utilized. These images are then stacked to form an N-channel image, which is fed into the CNN-GRU architecture for sequence analysis and identification of potential threats. The provide solution GAF-CNN-GRU achieved an accuracy of 98.6% on the Cranfield Embedded Systems Attack Dataset. We further achieved Precision, Recall and F1-scores of 97.84%, 91% and 94.3%. To evaluate model robustness we further tested this approach, using a benchmark random selection of input features, on the Canadian Institute for Cyber-Security (CIC) 2019 Distributed Denial-of-service attack (DDoS) Dataset achieving an Accuracy of 89.08%. Following feature optimisation our approach was able to achieve an accuracy of 98.36% with Precision, Recall and F1 scores of 93.09%, 95.45% and 94.56% respectively.IEEE Acces
The strategic fit between strategic purchasing and purchasing involvement: the moderating role of leadership styles
Get PDFPurpose – The aim of this study is to investigate and examine the impact of strategic purchasing practices on strategic fit by analysing the influence of strategic purchasing practices on purchasing involvement in business strategy formulation with path-goal theory leadership styles as moderators.
Design/methodology/approach – Using survey data from 320 respondents representing 64 manufacturing firms in the Middle East, we measure strategic purchasing practices, purchasing involvement, leadership styles, and strategic fit of the purchasing function with business strategy.
Findings – Building on the path-goal approach to leadership, results suggest that participative, supportive, and achievement-oriented leadership styles are pure moderators, while directive leadership style is a quasi-moderator in boosting the relationship between strategic purchasing practices and strategic purchasing involvement.
Research limitations/implications – Limitations of the sampling methodology and sample size restricts the scope for generalising the hypotheses. Further, data were collected only from manufacturing companies. The paper provides managerial implications on purchasing involvement in business strategy formulation and the different roles of leadership styles.
Originality/value – This is the first scholarly work to examine the different leadership styles as a moderator that affects the strategic involvement and status of strategic purchasing
Automation of knowledge extraction for degradation analysis
Get PDFDegradation analysis relies heavily on capturing degradation data manually and its interpretation using knowledge to deduce an assessment of the health of a component. Health monitoring requires automation of knowledge extraction to improve the analysis, quality and effectiveness over manual degradation analysis. This paper proposes a novel approach to achieve automation by combining natural language processing methods, ontology and a knowledge graph to represent the extracted degradation causality and a rule based decision-making system to enable a continuous learning process. The effectiveness of this approach is demonstrated by using an aero-engine component as a use-case.CIRP Annals - Manufacturing Technolog
Unleashing the power of Internet of Things and blockchain: a comprehensive analysis and future directions
Get PDFAs the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field.Internet of Things and Cyber-Physical System
Street-scale dispersion modelling framework of road-traffic derived air pollution in Hanoi, Vietnam
Get PDFTraffic is an important source of air pollution in Vietnamese cities. The spatio-temporal variation of air pollution derived from traffic is poorly understood. Application of dispersion modelling can help but is hindered by the local scarcity of suitable input data. This study fills the data gap, by establishing a framework employing open-access global data to model emission from traffic activities in Hanoi. The outlined methodology explicitly defines road sources, calculates their emission, and employs background pollution profiles from Copernicus Atmospheric Monitoring Service (CAMS) to produce street-scale distribution maps for CO, PM10 and PM2.5. Pollution hotspots are found near major traffic flows with the highest hourly average CO, PM10 and PM2.5 concentrations at 1206, 87.5 and 61.5 μgm−3, respectively. The relationship between concentrations and properties of the road network is assessed. Motorcycles are the main emitters of the traffic sector. Emission from Heavy Good Vehicles dominate during the night, with contribution percentages increase as it gets further away from the city core. Modelled concentrations are underestimated mainly due to low vehicular emission factor. Adjusting emission factors according to vehicle quality in Vietnam greatly improves agreement. The presence of non-traffic emission sources contributes to the model underestimation. Results for comparisons of daily averaged PM values are broadly in agreement between models and observations; however, diurnal patters are skewed. This results partly from the uncertainties linked with background pollution levels from CAMS, and partly from non-traffic sources which are not accounted for here. Further work is needed to assess the use of CAMS's concentrations in Vietnam. Meteorological input contributes to the temporal disagreement between the model and observations. The impact is most noticeable with CO concentrations during morning traffic rush hours. This study recommends approaches to improve input for future model iterations and encourage applications of dispersion modelling studies in similar economic settings.Environmental Researc