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Use of biochar and coal ash as passive sorbent barriers for long-term mitigation of chlorinated solvent vapours
Get PDFThis study explores the potential of biochar and coal ashes as novel passive sorbent barriers to mitigate chlorinated solvent vapours at contaminated sites, addressing the need for sustainable risk mitigation alternatives to traditional remediation. Trichloroethylene (TCE) was used as a model compound in adsorption batch tests under varying temperatures (5–35 °C) and humidity levels (0–50 %) to evaluate the adsorption capacity of biochar derived from pyrolysed biomass and coal ash from wood pellets gasification. All materials exhibited good adsorption capacities (75–170 mg g^−1), with biochar outperforming coal ashes due to higher carbon content. Adsorption capacity showed a decline with increasing temperature and humidity of maximum 30 %, consistent with exothermic physical adsorption. Freundlich isotherms best described the adsorption behaviour, suggesting a non-linear, reversible, and multilayer process. Column adsorption tests of TCE vapours were then carried out with biochar to assess the adsorption behaviour under dynamic conditions showing good performance. Modelling revealed that a 50 cm thick barrier of biochar could effectively mitigate chlorinated vapours for over 15 years for entering concentrations up to 1 g m^−3, proving the suitability of the tested materials as long-term risk management solutions in the subsurface. The overall results challenge the prevailing reliance on traditional remediation systems, highlighting the potential of a passive risk mitigation approach aligned with sustainability objectives and advancing knowledge in this field.The authors would like to acknowledge the financial support of the Biotechnology and Biological Sciences Research Council (BBSRC) NIBB's Environmental Biotechnology Network (EBNET, grant reference BB/S009795/1)Journal of Environmental Managemen
Understanding the relevance of parallelising machine learning algorithms using CUDA for sentiment analysis
Get PDFSentiment classification is essential in natural language processing, leveraging machine learning algorithms to understand the sentiment expressed in textual data. Over the years, advancements in machine learning, particularly with Naive Bayes (NB) and Support Vector Machines (SVM), have tremendously improved sentiment classification. These models benefit from word embedding techniques such as Word2Vec and GloVe, which provide dense vector representations of words, capturing their semantic and syntactic relationships. This paper explores the parallelisation of NB and SVM models using CUDA on GPUs to enhance computational efficiency and performance. Despite the computational power offered by GPUs, the literature on parallelising machine learning methods, especially for sentiment classification, remains limited. Our work aims to fill this gap by comparing the performance of NB and SVM on CPU and GPU platforms, focusing on execution time and model accuracy. Our experiments demonstrate that NB outperforms SVM in execution time and overall efficiency, mainly when using GPU acceleration. The NB model consistently achieves higher accuracy, precision, and F1 scores with Word2Vec and GloVe embeddings. The results show the importance of leveraging GPU acceleration using varying numbers of threads per block for large-scale sentiment analysis and laying the foundation for parallelising sentiment classification tasks.We acknowledge the Petroleum Technology Development Fund (PTDF) Nigeria funding, which sponsors the first author's PhD research, with ID PTDF/ED/OSS/PHD/DMC/1972/22.ICAAI 2024: 2024 The 8th International Conference on Advances in Artificial Intelligenc
Blockchain and distributed digital watermarking effort on federated learning: innovating intellectual property protection
Get PDFFederated Learning with Digital Watermarks (FLDW) have been recognized as a promising solution for property protection. However, the existing FLDW-related technologies neglect the requirements of decentralized settings, leading to recurrent issues such as discrepancies in distributed client data. This paper introduces a Blockchain Federated Learning Intellectual Property Protection Framework (BFLIPR), to address the data security and model validation challenges in decentralized federated learning environments. BFLIPR merges blockchain, digital watermarking, and federated learning technologies. By harnessing the blockchain’s tamper-proof properties, digital watermarking’s concealment capabilities, and federated learning’s distributed feature, the framework offers a solution that aligns with intellectual property protection mechanism, to bolster data security and property safeguarding. Experimental findings demonstrate its high feasibility and robust for data privacy and model security in the federated learning.This work was supported by the National Natural Science Foundation of China under Grant No. 61962026, the Natural Science Foundation of Jiangxi Province under Grant No. 20224ACB202007, Jiangxi Provincial Natural Science Foundation under Grant No. 20224BAB212015, Jiangxi Provincial 03 Special Project, and 5G Project (20224ABC03A13, 20232ABC03A26).2024 IEEE Smart World Congress (SWC
Mitigating no fault found phenomena through ensemble learning: a mixture of experts approach
Get PDFIn the aviation industry, the reliance on precise fault diagnostic decision-making is critical for equipment maintenance. A significant challenge encountered is the erroneous categorization of components under 'No Fault Found' (NFF), which subjects these components to unwarranted repairs or further testing. Such misclassifications not only trap on airlines through costly cycles of unnecessary maintenance but also exacerbate degeneration and potential safety hazards. Consequently, there is a heightened demand for the development of effective fault diagnosis models that are adapting to the aircraft complex systems and adeptly addressing issues related to the NFF phenomenon. In this study, we draw inspiration from ensemble learning and propose a multiple Naive Bayes experts (MNBMoEs) approach based on a mixture of experts (MoEs) model. This method leverages the predictive advantages of each sub-model on specific features, allowing the hybrid expert decision to outperform any single expert. It also includes a quantitative analysis method for the NFF issue, derived from the confusion matrix according to the industrial definition of NFF. Experiments evaluated on public datasets results show that the ensemble learning approach, based on Mixture of Multiple Naive-Bayes expert models, can effectively utilize the strengths of different models, improving fault diagnosis accuracy to 96.96%, with a maximum reduction in NFF occurrence rates of up to 94.17% and 84.2% model performance improvement.2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC
Geometric optimisation of volumetric solar receivers: a study of polygonal cavity configurations
No full textVolumetric solar receivers integrated with reticulated porous ceramics (RPCs) are a key component in high-temperature concentrated solar power (CSP) systems, enabling efficient radiative absorption and convective heat transfer. While prior studies have largely focused on material properties and operating conditions, the influence of cavity geometry on thermal performance remains underexplored. This study presents a systematic computational investigation of four polygonal cavity configurations: hexagonal, heptagonal, octagonal, and nonagonal, using high-fidelity CFD simulations in ANSYS Fluent coupled with the Monte Carlo radiation model. All designs were evaluated under consistent geometric constraints and two solar heat flux inputs (4.1 kW and 4.9 kW), with varying air mass flow rates. The nonagonal receiver achieved the highest thermal efficiencies of 75 % and 73 % at the respective flux levels, outperforming conventional designs. This improvement is attributed to its compact internal structure and increased edge count, which enhance surface energy density and fluid–wall interaction. The findings demonstrate that geometric optimisation, particularly through polygonal cavity design, offers a viable pathway to enhance the thermal performance of volumetric receivers. This work provides new design insights for next-generation CSP applications requiring compact, high-efficiency thermal energy conversion.The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number “NBU-SAFIR-2024”.Results in Engineerin
Soybean supply chains, markets, and global trade
No full textSoybean is one of the most important commodities worldwide. It is an essential source of vegetal protein, and it has been used for human nutrition, animal feeding, and biofuel production. The main growers and exporters are Brazil, the United States, and Argentina accounting for almost 82% of total soybean exports by quantity in any form in 2021. On the other hand, this is a highly concentrated supply chain, where China received more than 56% of imports by quantity in 2021. On-shore logistics is a bottleneck for many countries, but the off-shore logistics is efficient and produces a great quantity of movement between a few producers and the market in a low-cost transportation process. Finally, environmental concerns over the impact of soybean overproduction motivate environmental protection legislation. In this chapter, we investigate the evolution of this global supply chain over the years and present an outlook of the market considering uses, world trade, logistics, and environmental impacts. To do so, we conducted a literature review on the topic, collected statistical data from international organizations, and illustrated the current state of soybean supply chain using descriptive statistics and social network analysis. Our results will inform policymakers in regulating the soybean market.Soybean Production Technolog
Mind the gap: Towards performance measurement beyond a plan-execute logic
Get PDFProject performance measurement aims to identify deviations from intended goals and reduce ‘the gap’ between actual and expected performance. However, despite extensive measurement and control efforts, the gap is hard to close and, intriguingly, not necessarily related to the project's perceived performance, which is what will ultimately influence a stakeholder's satisfaction. Based on service quality research, this study explores the differences between perception and expectations of performance. Our mixed method study involving eighteen interviews and 85 survey responses in an IT-enabled change context shows that expectations and perceptions are fundamentally different concepts. As they are different, managing the gap between expectations and perceptions may be a nugatory task. The paper expands the literature on project performance measurement by questioning its foundations and offering a first step towards developing a more dynamic and subjective understanding of project performance that is consistent with a project's evolving nature
High glass transition catalyst-free polybenzoxazine vitrimer through one-pot solventless method
Get PDFA high glass transition polybenzoxazine has been synthesised by a one-pot solventless method via the Mannich condensation of a phenolic disulphide, paraformaldehyde and aniline. The solventless process reduces synthesis time, material costs, and the need for post-synthesis purification. The polybenzoxazine exhibits a glass transition temperature (Tg) of 155 °C and thermosetting behaviour below this temperature. Dynamic disulphide bond metathesis associated with a topological freezing temperature of 78 °C and an activation energy of 127 kJ/mol delivers vitrimeric functionality with fast, catalyst-free stress relaxation above Tg. This material fully relaxes stress within 5 s at 190 °C, with thermal degradation beginning above 250 °C. It exhibits a glassy modulus of 3.6 GPa, high char yield (57.4 %) translating to a high limiting oxygen index (LOI) of 40.5 % and excellent environmental resistance, as evidenced by low water uptake (1.4 %) after immersion at 75 °C for 31 days. The combination of environmental resistance, due to thermosetting character, high glass transition, facile synthesis, high char yield, good processability, and fast stress relaxation position this polybenzoxazine as a promising candidate matrix system for repairable aerospace thermosetting continuous fibre composites.Tertiary Education Trust FundThis research was supported by the Tertiary Education Trust Fund, Nigeria, through the overseas scholarship award grant reference TETF/ES/POLY/IMO STATE/TSAS/2019/VOL.I.Reactive and Functional Polymer
Developing reliable floating solar systems on seas: a review
Get PDFSolar PhotoVoltaic (PV), as a clean and affordable energy solution, has become ubiquitous around the world. In order to install enough PV coverage to meet the demand of global climate action, there has been a growing research interest in deploying solar panels on abundant sea space. However, the harsh marine environment is holding stakeholders back with safety concerns. There is a necessity to ensure the reliability of FPV on seas. To facilitate research in this area, the present review scans all Floating PV (FPV) literature related to the ocean, with a focus on reliability and risk mitigation. It starts by presenting contemporary and potentially future FPV designs for seas, inventorying both mechanical and electrical components. Accordingly, possible risks in the system are discussed with the associate mitigations suggested. Subsequently, a series of protective approaches to assess offshore wind and wave loads on FPV are introduced. This is followed by a structural integrity review for the system’s fatigue and ultimate strength, accompanied by anti-corrosion, anti-biofouling, and robust mooring concerns. Finally, essential research gaps are identified, including the modelling of numerous floating bodies on seas, mooring methodology for enormous FPV coverage, the interactions between FPV and the surrounding sea environments, and remote sensing and digital twins of the system for optimal energy efficiency and structural health. Overall, this work provides comprehensive insights into essential considerations of FPV on seas, supporting sustainable developments and long-term cost reductions in this sector.L.H. acknowledges grants received from Innovate UK, United Kingdom (No. 10048187, 10079774, 10081314), the Royal Society, United Kingdom (IEC NSFC 223253, RG R2 232462) and UK Department for Transport (TRIG2023 - No. 30066).Ocean Engineerin
An integrated battery unit regulation strategy
Get PDFFotouhi, Abbas - Associate SupervisorIn the research community, hybrid battery systems (HBSs) employing dual battery chemistries
have been proposed as a solution to address the suboptimal overall performance exhibited
by most state-of-the-art single-chemistry battery systems used in electric vehicle (EV) ap-
plications. Currently, the predominant approach for regulating power distribution among
different battery chemistries in HBSs is to configure DC/DC converters. However, the
cost and weight associated with this configuration pose a significant barrier to its practical
application. To overcome these limitations, this project presents a novel HBS design that
utilizes a discrete-switched structure combined with intelligent low-frequency switching
algorithms to replace DC/DC converters. The discrete-switched structure offers a simpler
system architecture and lower power electronics costs while still maintaining the power
allocation functionality of DC/DC converters. The switching algorithms developed, en-
compassing heuristic and model-predictive control algorithms, enable the switching of
cells within battery strings based on battery status and power demands, facilitating effec-
tive power management. Through simulations and experiments, the HBS equipped with
intelligent algorithms effectively regulates power distribution among different batteries
and ensures a broadly balanced state of charge. Moreover, the novel HBS configura-
tion employing nickel cobalt manganese oxide (NCM) and lithium-sulfur (Li-S) batteries
has been thoroughly investigated, encompassing the hardware structure and control algo-
rithms. This design enables both a long-range capability and high-power performance in
EV applications. It should be noted that this work assumed the usage of homogeneous cells
and effective cell cooling. Future research endeavors will focus on exploring cell-to-cell
variations and the development of corresponding thermal management systems.PhD in Transport System