Newcastle University Singapore

Recently, multilevel inverters (MLIs) have gained lots of interest in industry and academia, as they are changing into a viable technology for numerous applications, such as renewable power conversion system and drives. For these high power and high/medium voltage applications, MLIs are widely used as one of the advanced power converter topologies. To produce high-quality output without the need for a large number of switches, development of reduced switch MLI (RS MLI) topologies has been a major focus of current research. Therefore, this review paper focuses on a number of recently developed MLIs used in various applications. To assist with advanced current research in this field and in the selection of suitable inverter for various applications, significant understanding on these topologies is clearly summarized based on the three categories, i.e., symmetrical, asymmetrical, and modified topologies. This review paper also includes a comparison based on important performance parameters, detailed technical challenges, current focus, and future development trends. By a suitable combination of switches, the MLI produces a staircase output with low harmonic distortion. For a better understanding of the working principle, a single-phase RS MLI topology is experimentally illustrated for different level generation using both fundamental and high switching frequency techniques which will help the readers to gain the utmost knowledge for advance research.

Multilevel inverters (MLIs) with switched-capacitor (SC) units have been a widely rehearsed research topic in power electronics since the last decade. Inductorless/transformerless operation with voltage-boosting feature and inherent capacitor self-voltage balancing performance with a reduced electromagnetic interference make the SC-MLI an attractive converter over the other available counterparts for various applications. There have been many developed SC-MLI structures recently put forward, where different basic switching techniques are used to generate multiple (discrete) output voltage levels. In general, the priority of the topological development is motivated by the number of output voltage levels, overall voltage gain, and full dc-link voltage utilization, while reducing the component counts and stress on devices for better efficiency and power density. To facilitate the direction of future research in SC-MLIs, this article presents a comprehensive review, critical analysis, and categorization of the existing topologies. Common fundamental units are generalized and summarized with their merits and demerits. Ultimately, major challenges and research directions are outlined leading to the future technology roadmap for more practical applications.

The great promise of photodynamic therapy (PDT) has thrusted the rapid progress of developing highly effective photosensitizers (PS) in killing cancerous cells and bacteria. To mitigate the intrinsic limitations of the classical molecular photosensitizers, researchers have been looking into designing new generation of nanomaterial-based photosensitizers (nano-photosensitizers) with better photostability and higher singlet oxygen generation (SOG) efficiency, and ways of enhancing the performance of existing photosensitizers. In this paper, we review the recent development of nano-photosensitizers and nanoplasmonic strategies to enhance the SOG efficiency for better PDT performance. Firstly, we explain the mechanism of reactive oxygen species generation by classical photosensitizers, followed by a brief discussion on the commercially available photosensitizers and their limitations in PDT. We then introduce three types of new generation nano-photosensitizers that can effectively produce singlet oxygen molecules under visible light illumination, i.e., aggregation-induced emission nanodots, metal nanoclusters (< 2 nm), and carbon dots. Different design approaches to synthesize these nano-photosensitizers were also discussed. To further enhance the SOG rate of nano-photosensitizers, plasmonic strategies on using different types of metal nanoparticles in both colloidal and planar metal-PS systems are reviewed. The key parameters that determine the metal-enhanced SOG (ME-SOG) efficiency and their underlined enhancement mechanism are discussed. Lastly, we highlight the future prospects of these nanoengineering strategies, and discuss how the future development in nanobiotechnology and theoretical simulation could accelerate the design of new photosensitizers and ME-SOG systems for highly effective image-guided photodynamic therapy.

In the modern smart home, smart meters, and Internet of Things (IoT) have been massively deployed to replace traditional analogue meters. It digitalises the data collection and the meter readings. The data can be wirelessly transmitted that significantly reduces manual works. However, the community of smart home network is vulnerable to energy theft. Such attacks cannot be effectively detected since the existing techniques require certain devices to be installed to work. This imposes a challenge for energy theft detection systems to be implemented despite the lack of energy monitoring devices. This paper develops an energy detection system called smart energy theft system (SETS) based on machine learning and statistical models. There are three stages of decision-making modules, the first stage is the prediction model which uses multimodel forecasting system. This system integrates various machine learning models into a single forecast system for predicting the power consumption. The second stage is the primary decision making model that uses simple moving average (SMA) for filtering abnormally. The third stage is the secondary decision making model that makes the final stage of the decision on energy theft. The simulation results demonstrate that the proposed system can successfully detect 99.96% accuracy that enhances the security of the IoT-based smart home.

Electric vehicles (EVs) are universally recognized as an incredibly effective method of lowering gas emissions and dependence on oil for transportation. Electricity, rather than more traditional fuels like gasoline or diesel, is used as the main source of energy to recharge the batteries in EVs. Future oil demand should decline as a result of the predicted rise in the number of EVs on the road. The charging infrastructure is considered as a key element of EV technology where the recent research is mostly focused. A strong charging infrastructure that serves both urban and rural areas, especially those with an unstable or nonexistent electrical supply, is essential in promoting the global adoption of EVs. Followed by different EV structures such as fuel-cell- and battery-integrated EVs, the charging infrastructures are thoroughly reviewed in three modes, specifically—off-grid (standalone), grid-connected, and hybrid modes (capable of both standalone and grid-connected operations). It will be interesting for the readers to understand in detail several energy-source-based charging systems and the usage of charging stations for different power levels. Towards the improvement of the lifetime and efficiency of EVs, charging methods and charging stations in integration with microgrid architectures are thoroughly investigated. EVs are a multi-energy system, which requires effective power management and control to optimize energy utilization. This review article also includes an evaluation of several power management and control strategies followed by the impact assessment of EVs on the utility grid. The findings and the future research directions provided in this review article will be extremely beneficial for EV operators and research engineers.

Water is a precious resource that should be managed carefully. However, due to leakages in water distributed networks (WDNs), a large amount of water is lost each year that suggests the need for reliable and robust leak detection and localization system. This paper attempts to review the current technologies for leakage detection in WDN as well as several proposed intelligent methodologies (such as support vector machine, neural network, and convolution neural network) over the past few years. The current methodologies and their limitations are discussed. Uncertainties involved in the implementation of WDN leakage detection are also discussed, and several suggestions to overcome such uncertainties are provided for future implementations.

Recent research on common-ground switched-capacitor transformerless (CGSC-TL) inverters shows some intriguing features, such as integrated voltage boosting ability, possible multilevel output voltage generation, and nullification of the leakage current issue. However, the number of output voltage levels and also the overall voltage boosting ratio of most of the existing CGSC-TL inverters are limited to five and two, respectively. This article presents a generalized circuit configuration of such converters capable of higher voltage gain and output voltage levels generation. A basic five-level (5L) CGSC-TL inverter is first proposed using eight power switches and two self-balanced dc-link capacitors. A generalized extension of the circuit for any output voltage levels and voltage gain is then presented while keeping all the traits of the proposed basic 5L-CGSC-TL inverter. The circuit descriptions, control strategy, design guidelines, comparative study, and the relevant simulation and experimental results for the proposed 5L-CGSC-TL inverters and its seven-level derived topology are presented to validate the effectiveness and feasibility of this proposal.

Conventional active-neutral-point-clamped (ANPC) inverters exhibit low voltage gain that inherently leads to a high dc-link voltage requirement. An improved ANPC inverter that is capable of generating five voltage levels has recently reduced the dc-link voltage twofold to achieve unity gain. This led to the development of a single-stage dc-ac power converter with no frontend boost dc-dc converter. This article proposes novel ANPC inverters capable of unity or boosted voltage gain while generating higher voltage levels. The first topology can provide a voltage gain of 1.5 and extends the number of levels to seven by incorporating only one additional switch. The topology can also be extended by adding three switches and one floating capacitor to generate nine levels with unity voltage gain, or 11 levels with a voltage gain of 2.5. The proposed ANPC inverters and their operations are comprehensively discussed. Experimental results are provided to validate the feasibility of the proposed ANPC inverters.

BACKGROUND: To overcome the flaws of high energy consumption of freeze drying (FD) and the non-uniform drying of microwave freeze drying (MFD), pulse-spouted microwave vacuum drying (PSMVD) was developed. RESULTS: The results showed that the drying time can be dramatically shortened if microwave was used as the heating source. In this experiment, both MFD and PSMVD could shorten drying time by 50% as compared to the FD process. Depending on the heating method, MFD and PSMVD dried banana cubes showed trends of expansion while FD dried samples demonstrated trends of shrinkage. Shrinkage also brought intensive structure and highest fracturability of all three samples dried by different methods. The residual ascorbic acid content of PSMVD dried samples can be as high as in FD dried samples, which were superior to MFD dried samples. CONCLUSION: The tests confirmed that PSMVD could bring about better drying uniformity than MFD. Besides, compared with traditional MFD, PSMVD can provide better extrinsic feature, and can bring about improved nutritional features because of the higher residual ascorbic acid content.

Environmental pollution, such as air, water, and soil pollution, has become the most serious issue. Soil pollution is a major concern as it generally affects the lands and makes them non-fertile. The main cause of soil pollution is agro-waste. It may be possible to mitigate the agro-waste pollution by re-utilizing this agro-waste, namely natural fibres (NFs), by blending into polymer-based material to reinforce the polymer composite. However, there are pros and cons to this approach. Consequently, the polymer composite materials fabricated using NFs are inferior to those polymer composites that are reinforced by, e.g., carbon or glass fibres from the mechanical properties’ perspectives. The limitations of utilizing natural fibres in polymer matrix are their high moisture absorption, resulting in high swelling rate and degradation, inferior resistance to fire and chemical, and inferior mechanical properties. In particular, the NF polymer composites exhibit inferior interfacial adhesion between the fibre and the matrix, which, if improved, ultimately overcome all the listed limitations and improve the mechanical properties of the developed composites. To improve the interfacial adhesion leading to the enhancement of the mechanical properties, optimum chemical treatment such as Alkalization/Mercerization of the fibres have been explored. This article discusses the Mercerization/Alkali surface treatment method for NFs and its effects on the fibres regarding the Mercerization/Alkali surface treatment method for NFs and its effect on the fibres regarding their utilization in the polymer composites, the morphological features, and mechanical properties of composites.

Internet of Things makes deployment of smart home concept easy and real. Smart home concept ensures residents to control, monitor, and manage their energy consumption without any wastage. This paper presents a self-learning home management system. In the proposed system, a home energy management system, demand side management system, and supply side management system were developed and integrated for real time operation of a smart home. This integrated system has some capabilities such as price forecasting, price clustering, and power alert system to enhance its functions. These enhancing capabilities were developed and implemented using computational and machine learning technologies. In order to validate the proposed system, real-time power consumption data was collected from a Singapore smart home and a realistic experimental case study was carried out. The case study has shown that the developed system has performed well and created energy awareness to the residents. This proposed system also displays its ability to customize the model for different types of environments compared to traditional smart home models.

The reduction of noises, achieved through absorption, is of paramount importance to the well-being of both humans and machines. Lattice structures, defined as architectured porous solids arranged in repeating patterns, are emerging as advanced sound-absorbing materials. Their immense design freedom allows for customizable pore morphology and interconnectivity, enabling the design of specific absorption properties. Thus far, the sound absorption performance of various types of lattice structures are studied and they demonstrated favorable properties compared to conventional materials. Herein, this review gives a thorough overview on the current research status, and characterizations for lattice structures in terms of acoustics is proposed. Till date, there are four main sound absorption mechanisms associated with lattice structures. Despite their complexity, lattice structures can be accurately modelled using acoustical impedance models that focus on critical acoustical geometries. Four defining features: morphology, relative density, cell size, and number of cells, have significant influences on the acoustical geometries and hence sound wave dissipation within the lattice. Drawing upon their structural-property relationships, a classification of lattice structures into three distinct types in terms of acoustics is proposed. It is proposed that future attentions can be placed on new design concepts, advanced materials selections, and multifunctionalities.

For a hybrid ac/dc microgrid (MG), bidirectional interlinking converters (BICs) enable flexible power interactions between ac and dc subgrids. In each subgrid, power sharing among diversified sources has been effectively realized by droop controllers. These power sharing concepts can also be extended to BIC applications. This paper proposes a distributed power management strategy (DPMS) for multi-paralleled BICs in the hybrid MG to avoid the overstress of a single BIC. In this strategy, each BIC is assigned with a well-devised localized distributed controller (LDC) which generates the respective power reference for the BIC. By using the LDC, BICs are allowed to exchange information with one another in the distributed communication graph. The power interactions between ac and dc subgrids can be proportionally allocated to BICs based on their different power ratings in a full distributed manner. Then the system reliability and scalability are significantly improved. Meanwhile, accurate global power sharing among all ac and dc sources in the MG would be accordingly attained. Considering the communication time delay involved in BICs, a small signal model is derived to predict the maximum tolerable delay of the studied system. The validities of the proposed DPMS and delay stability analyses are verified by a controller hardware-in-loop experimental platform.

This article proposes a fuzzy logic-based energy-management system (FEMS) for a grid-connected microgrid with renewable energy sources (RESs) and energy storage system (ESS). The objectives of the FEMS are reducing the average peak load (APL) and operating cost through arbitrage operation of the ESS. These objectives are achieved by controlling the charge and discharge rate of the ESS based on the state of charge of ESS, the power difference between load and RES, and electricity market price. The effectiveness of the fuzzy logic greatly depends on the membership functions (MFs). The fuzzy MFs of the FEMS are optimized offline using a Pareto-based multiobjective evolutionary algorithm, nondominated sorting genetic algorithm (NSGA-II). The best compromise solution is selected as the final solution and implemented in the fuzzy-logic controller. A comparison with other control strategies with similar objectives is carried out at a simulation level. The proposed FEMS is experimentally validated on a real microgrid in the energy storage test bed at Newcastle University, U.K.

Purpose – This study aims to build on previous research into lean practices and the associated barriers reported in various contexts to empirically address the question of what possible barriers exist to hinder the implementation of lean practices in the construction industry in China. Despite the potential that lean practices have to improve quality and productivity while reducing costs, successful stories of lean deployment are not frequently heard of. Design/methodology/approach – A large-scale survey of Chinese building professionals is used to identify these barriers. Findings – The results suggest that the most crucial barriers to implementation of lean practices, as perceived by Chinese building professionals, include “their lack of a long-term philosophy”, “the absence of a lean culture in their organizations”, “the use of multi-layer subcontracting” and others. This study also reports the findings using a factor analysis that shows the six underlying factors hindering the implementation of lean practices in the Chinese construction industry, namely, people and partner issues, managerial and organizational issues, lack of support issues, culture and philosophy issues, government issues and procurement issues. Originality/value – This study offers a thorough overview of the barriers to implementing lean practices in various contexts, with a focus on construction. This study also contributes to the knowledge by recommending the measures that can be taken to appropriately overcome the barriers identified.

Human factors are the primary catalyst for traffic accidents. Among different factors, fatigue, distraction, drunkenness, and/or recklessness are the most common types of abnormal driving behavior that leads to an accident. With technological advances, modern smartphones have the capabilities for driving behavior analysis. There has not yet been a comprehensive review on methodologies utilizing only a smartphone for drowsiness detection and abnormal driver behavior detection. In this paper, different methodologies proposed by different authors are discussed. It includes the sensing schemes, detection algorithms, and their corresponding accuracy and limitations. Challenges and possible solutions such as integration of the smartphone behavior classification system with the concept of context-aware, mobile crowdsensing, and active steering control are analyzed. The issue of model training and updating on the smartphone and cloud environment is also included.

Purpose This study aims to investigate the intention of using mobile payment (m-payment) services in Sarawak, Malaysia. Design/methodology/approach A total of 194 online payment users were selected to respond to the structured questionnaire. The partial least squares-structural equation modelling (PLS-SEM) was used to analyse the data by assessing the measurement and model. Findings Perceived usefulness (PU) and perceived ease of use mediated the relationship between perceived compatibility (PC) and the intention to use the mobile payment for mobile network operators’ services. Research limitations/implications The analysis provides insights that PC is considered as a significant determinant for mobile payment of mobile network operators’ services. Practical implications The operators can consider factors such as PC in the design of their mobile applications and the potential to expand the m-payment services to others e-wallet such as Sarawak e-wallet. The model possesses medium prediction power, which suggests that other variables such as perceived security and personal innovativeness also can be used to predict the usage behaviour of mobile payment for the mobile network services. Originality/value The present study contributes to the m-payment users’ behaviour intention literature by investigating the mobile-based predictors of using m-payment technology in an emerging digital economy state in Sarawak, Malaysia. This study also extends the knowledge of technology acceptance model by introducing the mediation effect of PU and ease of use between the mobile-based predictors and m-payment intention.

In traditional steam reforming of CH4, the CH4 conversion and its selectivity to CO and H2 are thermodynamically limited. In this work, we designed a series of Ni–Fe redox catalysts with varying Ni/Fe ratios. The Ni–Fe redox catalysts could function as oxygen carriers to selectively convert CH4 to syngas via chemical looping. The selectivity to CO was dramatically enhanced via a selective conversion route of CH4 to C and H2 in the reduction, followed by C gasification to syngas with hot steam. Taking the advantages of the highly reactive Ni species for CH4 activation and Fe species for water splitting, together with the resulting NiFe alloy in the reduced catalyst for catalytic CH4 decomposition, high CH4 conversion up to 97.5% and CO selectivity up to 92.9% were achieved at 900 °C with productivity of CO and H2 of 9.6 and 29.0 mol kgcatalyst–1, respectively, on equimolar Ni–Fe catalyst.

In practical microgrids, the inhomogeneous initial values are widely appeared due to soft-starting operation. If traditional model order reduction approaches are applied, the input-output maps error between the original system and reduced-order system is large. To address this problem, this paper proposes a reduced-order aggregate model based on balanced truncation approach to provide the preprocessing approach for the real-time simulation of large-scale converters with inhomogeneous initial conditions in DC microgrid. Firstly, the standard linear time-invariant model with inhomogeneous initial conditions is established through non-leader multiagents concept. To end this, it is convenient for scholars to build complex system modeling with switched topology. Furthermore, the full system is divided into two components, i.e., the unforced component with nontrivial initial conditions and forced component with null initial conditions. Moreover, this paper presents an aggregated approach that involves independent reducing component responses and combining reducing component responses. Based on this, the input-output maps error is reduced. Then, the approximated error estimate of the reduced-order aggregate model regarding large-scale converters in DC microgrid is first provided, which provides prior knowledge and theoretical basis for DC microgrid designers. Finally, the simulation results illustrate the accuracy of the proposed approach.

Purpose – This paper aims to determine the nutritional profile of popular takeaway meals in the UK. Fast food has a poor nutritional profile; research has focused on the major catering chains, with limited data on takeaway food from independent establishments. Design/methodology/approach – Random samples of takeaway meals were purchased from small, independent takeaway establishments. Multiple samples of 27 different takeaway meals, from Indian, Chinese, kebab, pizza and English-style establishments ( n = 489), were analysed for portion size, energy, protein, carbohydrate, total fat, salt and total sugars. Findings – Takeaway meals were inconsistent with UK dietary recommendations; pizzas revealed the highest energy content, and Chinese meals were lowest in total fat. However, there was a high degree of variability between and within categories, but the majority of meals were excessive for portion size, energy, macronutrients and salt. Research limitations/implications – The present study focused on energy, macronutrients, salt and total sugars. Future research should analyse the quality of fat and carbohydrates and micronutrients to provide a more detailed nutritional profile of takeaway food. Practical implications – The nutritional variability between establishments suggests that recipe reformulation should be explored in an attempt to improve the nutritional quality of takeaway foods. In addition, portion size reduction could favour both the consumer and the industry. Social implications – Takeaway outlets do not provide nutritional information; due to the excessive nutritional profiles, regular intake may increase the risk of non-communicable disease. Therefore, there is a pressing need for this provision to help consumers make conscious food choices. Originality/value – This is the first study to analyse energy and macronutrient content of independent takeaway meals in the UK.