E-Jurnal Universitas Tunas Husada Tasikmalaya
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22393 research outputs found
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Development and implementation of a sustainability assessment tool for wastewater asset decision-making
No full text"The UK wastewater sector is facing increasing challenges such as regulatory pressure, population growth and climate change when making investment decisions. This has resulted in a growing demand for assessment tools that informs the selection of suitable wastewater treatment processes and technologies from the sustainability perspective. The objective of this research was to develop a sustainability assessment tool for a water company in the UK to compare wastewater treatment processes and inform its investment decisions given its unique combination of challenges and needs.The development of the assessment tool encompassed several phases with an underlying pragmatic research paradigm. The first stage utilised an exploratory case study to understand the current decision drivers and the organisational context. The case study specifically involved a round of semi-structured interviews with stakeholders and thematic analyses. The findings then informed the methodological design of the assessment tool. A suite of assessment criteria and indicators were selected based on literature review and findings from the case study. Multi-Criteria Decision Analysis (MCDA) was selected as the assessment methodology as it was considered suitable and useful to incorporate the Three- Pillars model of sustainability. The assessment methodology was applied to two pilot studies to test its feasibility and robustness. Once the methodology had been confirmed, the assessment methodology was built into a ‘tool’ with a user interface, culminating in a round of usability testing with end-users in the organisation to examine its overall utility and ease of use. The results of testing suggest the assessment tool is easy to use and understand and offered useful insights into the sustainability credentials of wastewater treatment alternatives. This research also proposed a provisional framework for developing a multi- criteria sustainability tool in a corporate environment, which can be extrapolated for wider applications. The research also demonstrated the significance of pragmatic research in developing a practical solution for industrial-based research whilst highlighting the potential synergy between sustainability assessment, MCDA and decision support systems. The findings and insights of this research will accelerate the practical integration of MCDA into the corporate decision-making process for performing sustainability assessments.
ECMS: An Edge Intelligent Energy Efficient Model in Mobile Edge Computing
No full textWith the increasing popularity of mobile edge computing (MEC) for processing intensive and delay sensitive IoT applications, the problem of high energy consumption of MEC has become a significant concern. Energy consumption prediction and monitoring of edge servers are crucial for reducing MEC's carbon footprint in accordance with green computing and sustainable development. However, predicting energy consumption of edge servers is a nontrivial problem due to the fluctuation and variation of different loads. To address this problem, we propose ECMS, a new edge intelligent energy modeling approach that jointly adopts Elman Neural Network (ENN) and feature selection to optimize the consumption of energy on edge servers. ECMS considers 29 parameters relevant to edge server energy consumption and uses the ENN to develop an energy consumption model. Unlike other energy consumption models, ECMS can successfully deal with load fluctuation and various sorts of tasks, such as CPU-intensive, online transaction-intensive, and I/O-intensive. We have validated ECMS through extensive experiments and compared its performance in terms of accuracy and training time to several baseline approaches. The experimental results show the superiority of ECMS to the baseline models. We believe that the proposed model can be used by the MEC resource providers to forecast and optimize energy use
Life Cycle Assessment of the High Performance Discontinuous Fibre (HiPerDiF) Technology and Its Operation in Various Countries
No full textComposite waste is a growing issue due to the increased global demand for products manufactured from these advanced engineering materials. Current reclamation methods produce short length fibres that, if not realigned during remanufacture, result in low-value additives for non-structural applications. Consequently, to maximise the economic and functional potential, fibre realignment must occur. The High Performance Discontinuous Fibre (HiPerDiF) technology is a novel process that produces highly aligned discontinuous fibre-reinforced composites, which largely meet the structural performance of virgin fibres, but to date, the environmental performance of the machine is yet to be quantified. This study assessed the environmental impacts of the operation of the machine using life cycle assessment methodology. Electrical energy consumption accounts for the majority of the greenhouse gas emissions, with water consumption as the main contributor to ecosystem quality damage. Suggestions have been made to reduce energy demand and reuse the water in order to reduce the overall environmental impact. The hypothetical operation of the machine across different European countries was also examined to understand the impacts associated with bulk material transport and electricity from different energy sources. It was observed that the environmental impact showed an inverse correlation with the increased use of renewable sources for electricity generation due to a reduction in air pollutants from fossil fuel combustion. The analysis also revealed that significant reductions in environmental damage from material transport between the reclamation facility to the remanufacturing site should also be accounted for, and concluded that transportation routes predominantly via shipping have a lower environmental impact than road and rail haulage. This study is one of the first attempts to evaluate the environmental impact of this new technology at early conceptual development and to assess how it would operate in a European scenario
Enhancing the resistance to H2S toxicity during anaerobic digestion of low-strength wastewater through granular activated carbon (GAC) addition
No full textLow-strength wastewater was treated using two laboratory-scale up-flow anaerobic sludge blankets (UASB) for 130 days under sulfate-reducing conditions. Granular activated carbon (GAC) was added to one of the reactors. The GAC addition increased the total chemical oxygen demand removal by 21% - 28% and total methane production by 32% - 78%. The sludge from the GAC-amended UASB showed higher specific methanogenic activities (SMA) and higher activities in the presence of H2S, indicating that the GAC addition enhanced the resistance of methanogens to H2S toxicity. Further, the microbial communities showed that the GAC addition shifted microbial communities. A robust syntrophic partnership between bacteria (i.e., Bacteroidetes_vadinHA17 and Trichococcus) and methanogens was established in the GAC-amended UASB. Sulfate-reducing bacteria (SRB) were enriched in the GAC biofilm, indicating the coexistence of competition and cooperation between SRB and methanogens. These findings provide significant insights regarding microbial community dynamics, especially SRB and methanogens, in a GAC-amended anaerobic digestion process under sulfate-reducing conditions
Anaerobic digestion of untreated and treated process water from the hydrothermal carbonisation of spent coffee grounds
No full textThis study investigates the long-term performance of the mesophilic (35 °C) anaerobic mono-digestion of process waters (PW) from the hydrothermal carbonisation (HTC) of spent coffee grounds. At an organic loading rate (OLR) of 0.4 gCOD L−1 d−1, initial instability was seen, but after 40 days and supplementary alkalinity, the digestion stabilised with the chemical oxygen demand (COD) in the untreated PW degraded with 37.8–64.6% efficiency and the yield of methane at 0.16 L gCOD−1. An increase in OLR to 0.8 gCOD L−1 d−1 caused a collapse in biogas production, and resulted in severe instability in the reactor, characterised by falling pH and an increasing volatile fatty acid concentration. Comparatively, the digestion of a treated PW (concentrated in nanofiltration and reverse osmosis after removal of the fouling fraction), at OLR between 0.4 and 0.8 gCOD L−1 d−1, was stable over the entire 117 days of treated PW addition, yielded methane at 0.21 L gCOD−1 and the COD was degraded with an average efficiency of 93.5% - the highest efficiency the authors have seen for HTC PW. Further anaerobic digestion of untreated PW at an average OLR of 0.95 gCOD L−1 d−1 was stable for 38 days, with an average COD degradation of 69.6%, and methane production between 0.15 and 0.19 L gCOD−1. The digestion of treated PW produced significantly higher COD degradation and methane yield than untreated PW, which is likely to be related to the removal of refractory and inhibitory organic material in the post-HTC treatment by adsorption of hydrophobic material
An eIF3d-dependent switch regulates HCMV replication by remodeling the infected cell translation landscape to mimic chronic ER stress
No full textRegulated loading of eIF3-bound 40S ribosomes on capped mRNA is generally dependent upon the translation initiation factor eIF4E; however, mRNA translation often proceeds during physiological stress, such as virus infection, when eIF4E availability and activity are limiting. It remains poorly understood how translation of virus and host mRNAs are regulated during infection stress. While initially sensitive to mTOR inhibition, which limits eIF4E-dependent translation, we show that protein synthesis in human cytomegalovirus (HCMV)-infected cells unexpectedly becomes progressively reliant upon eIF3d. Targeting eIF3d selectively inhibits HCMV replication, reduces polyribosome abundance, and interferes with expression of essential virus genes and a host gene expression signature indicative of chronic ER stress that fosters HCMV reproduction. This reveals a strategy whereby cellular eIF3d-dependent protein production is hijacked to exploit virus-induced ER stress. Moreover, it establishes how switching between eIF4E and eIF3d-responsive cap-dependent translation can differentially tune virus and host gene expression in infected cells
Engineered Electromagnetic Metasurfaces in Wireless Communications: Applications, ResearchFrontiers and Future Directions
No full textSurface electromagnetics (SEM), as a sub-discipline of electromagnetic (EM) science, is strongly linked with the ability to manipulate an arbitrary EM wavefront. This exceptional capability of manipulating the surface-bound and free-space EM waves for the guidance and control of anomalous reflection, refraction and transmission has catapulted an abundance of new research frontiers. This has resulted in the realization of many novel applications for modern real-life platforms and the introduction of several new modelling techniques and engineering approaches to give rise to some unconventional devices. Consequently, EM engineered metasurfaces, due to numerous emerging applications, are beginning to revolutionize the EM industry. Recently, the practical usage of metasurfaces has gained a substantial amount of interest and traction for a wide range of applications in microwave, millimetre-wave (mmWave), Terahertz (THz) and even optical wavelengths. This tutorial is aimed at presenting a plethora of EM metasurface applications and research frontiers to illustrate a broader impact of SEM in real-world platforms, advanced communication systems and new devices
SIEMS: A Secure Intelligent Energy Management System for Industrial IoT applications
No full textIn this work, we deploy a one-day-ahead prediction algorithm using a deep neural network for a fast-response BESS in an intelligent energy management system (I-EMS) that is called SIEMS. The main role of the SIEMS is to maintain the state of charge at high rates based on the one-day-ahead information about solar power, which depends on meteorological conditions. The remaining power is supplied by the main grid for sustained power streaming between BESS and end-users. Considering the usage of information and communication technology components in the microgrids, the main objective of this paper is focused on the hybrid microgrid performance under cyber-physical security adversarial attacks. Fast gradient sign, basic iterative, and DeepFool methods, which are investigated for the first time in power systems e.g. smart grid and microgrids, in order to produce perturbation for training data
Medusa: Universal Feature Learning via Attentional Multitasking
No full textRecent approaches to multi-task learning (MTL) have fo-cused on modelling connections between tasks at the de-coder level. This leads to a tight coupling between tasks, which need retraining if a new task is inserted or removed. We argue that MTL is a stepping stone towards universal feature learning (UFL), which is the ability to learn generic features that can be applied to new tasks without retraining. We propose Medusa to realize this goal, designing task heads with dual attention mechanisms. The shared feature attention masks relevant backbone features for each task, allowing it to learn a generic representation. Meanwhile, a novel Multi-Scale Attention head allows the network to better combine per-task features from different scales when making the final prediction. We show the effectiveness of Medusa in UFL (+13.18% improvement), while maintaining MTL performance and being 25% more efficient than previous approaches
Iodine fortification of plant-based dairy and fish alternatives - the effect of substitution on iodine intake based on a market survey in the UK
No full textIodine deficiency has been demonstrated in UK women, which is of concern as iodine is required for fetal brain development during pregnancy. Plant-based diets are increasingly popular, especially with young females, which may affect iodine intake as the main dietary sources are dairy and fish; plant-based products are naturally low in iodine. We, therefore, aimed to (i) assess the iodine fortification of milk-, yoghurt-, cheese- and fish-alternative products available in UK supermarkets and (ii) model the impact that substitution with such products would have on iodine intake using portion-based scenarios. A cross-sectional survey of retail outlets was conducted in 2020 and nutritional data was extracted from food labels. We identified 300 products, including plant-based alternatives to: (i) milk (n=146), (ii) yoghurt (n=76), (iii) cheese (n=67), and (iv) fish (n=11). After excluding organic products (n=48), which cannot be fortified, only 28% (n=29) of milk alternatives and 6% (n=4) of yoghurt alternatives were fortified with iodine, compared to 88% (n=92) and 73% (n=51) respectively with calcium. No cheese alternative was fortified with iodine but 55% were fortified with calcium. None of the fish-alternatives were iodine-fortified. Substitution of three portions of dairy (milk/yoghurt/cheese) per day with unfortified alternatives would reduce iodine provision by 97.9% (124 vs. 2.6 µg) and substantially reduce the contribution to adult intake recommendations (83 vs. 1.8%). Our study highlights that the majority of plant-based alternatives are not iodine-fortified and that use of unfortified alternatives in place of dairy and fish may put consumers at risk of iodine deficiency