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At present, the limited existence of fossil fuels and the environmental issues over greenhouse gas emissions have been directly affected to the transition from conventional vehicles to electric vehicles (EVs). In fact, the electrification of transportation system and the growing demand of EVs have prompted recent researchers to investigate the optimal location of electric vehicle charging stations (EVCSs). However, there are numerous challenges would face when implementing EVs at large scale. For instance, underdeveloped EVCSs infrastructure, optimal EVCS locations, and charge scheduling in EVCSs. In addition, the most fundamental EV questions, such as EV cost and range, could be partly answered only by a well-developed EVCS infrastructure. According to the literature, the researchers have been followed different types of approaches, objective functions, constraints for problem formulation. Moreover, according to the approaches, objective functions, constraints, EV load modeling, uncertainty, vehicle to grid strategy, integration of distributed generation, charging types, optimization techniques, and sensitivity analysis are reviewed for the recent research articles. Furthermore, optimization techniques for optimal solution are also reviewed in this article. In addition, the EV load impact on the distribution network, environmental impacts and economic impact are discussed.

In this paper, we investigate a reconfigurable intelligent surface (RIS)-assisted wireless communication system with energy harvesting. In the single information user (IU) scenario, we consider the power control of base station (BS) and the random deployment of energy users (EUs). To this end, we first characterize the statistical features of the channel gains over BS-RIS-IU and BS-RIS-EU cascaded links. Then, we derive a closed-form expression of the information outage probability (IOP) of the IU and show an upper bound of the energy outage probability (EOP) of EUs by invoking the Jensen's inequality. Furthermore, we consider two more general extensions, namely, the existence of imperfect phase alignment and multiple IUs. Finally, the correctness of the analysis results is verified by Monte-Carlo simulation.

Apnoea, a major sleep disorder, affects many adults and causes several issues, such as fatigue, high blood pressure, liver conditions, increased risk of type II diabetes, and heart problems. Therefore, advanced monitoring and diagnosing tools of apnoea disorders are needed to facilitate better treatment, with advantages such as accuracy, comfort of use, cost effectiveness, and embedded computation capabilities to recognise, store, process, and transmit time series data. In this work we present an adaptation of our apnoea-Pi open-source surface acoustic wave (SAW) platform (Apnoea-Pi) to monitor and recognise apnoea in patients. The platform is based on a thin-film SAW device using bimorph ZnO and Al structures, including those fabricated as Al foils or plates, to achieve breath tracking based on humidity and temperature changes. We applied open-source electronics and provided embedded computing characteristics for signal processing, data recognition, storage, and transmission of breath signals. We show that the thin-film SAW device out-performed standard and off-the-shelf capacitive electronic sensors in terms of their response and accuracy for human breath-tracking purposes. This in combination with embedded electronics makes a suitable platform for human breath monitoring and sleep disorder recognition.

Mechanical and Electrical (M&E) services account for 10-70 of the total cost of projects, depending on the project type. Sadly, the complex nature of the design of M&E services among other peculiar attributes has led to an enormous challenge in the cost management of M&E services in the construction industry. This study examined the knowledge areas required to effectively cost-manage M&E services in construction projects. Data for the study were collected by administering copies of a carefully designed questionnaire among experts in M&E services after a pilot study with a team of experts. The variables outlined in the questionnaire were extracted from relevant literature. In selecting the M&E services experts that participated in the survey, purposive and snowballing sampling techniques were used. The professionals involved include Electrical, Mechanical engineers, and Quantity Surveyors. Data analysis was done using Mean Item Score, Gap analysis, Spearman rank correlation, and Kendall coefficient of concordance. Findings revealed that knowledge in Bill of Quantities (BOQ) preparation, valuation, measurement of M&E works, estimating, and quality management were ranked as the most important knowledge areas and a statistically significant agreement among the experts was recorded. Gap analysis revealed that the ability of cost managers/QSs on the knowledge areas is currently below expectation while a moderate relationship was observed between the importance and performance of QSs/cost managers in the knowledge areas. The study concludes that there is a need for cost managers/Quantity Surveyors to enhance their knowledge in the identified knowledge areas and strive hard to close the gap between importance and their performance on the knowledge areas.

In this paper, a dual hollow-core negative curvature fiber is proposed for the polarization beam splitter. The effects of the structure parameters of the dual hollow-core negative curvature fiber on the coupling length and coupling length ratio of the x -polarized and y -polarized core modes and the higher-order mode extinction ratio are analyzed by the finite element method. Moreover, the normalized output powers of the x -polarized and y -polarized modes in the cores A and B and the corresponding extinction ratio are also investigated by the mode coupling theory. The simulation results show that a dual hollow-core negative curvature fiber polarization beam splitter with the length of 6.45 cm can achieve a broad bandwidth of 400 nm (1.23–1.63 µm), covering the O + E + S + C + L communication band. In addition, the higher-order mode extinction ratio is greater than 100 in the considered wavelength range, which means that it has good single-mode characteristics. It is believed that the proposed dual hollow-core negative curvature fiber polarization beam splitter will have significant applications in the optical communication system.

In this study, polyacrylic acid (PAA) films were deposited onto a quartz surface acoustic wave (SAW) resonator using a spin-coating technique for ammonia sensing operated at room temperature, and the sensing mechanisms and performance were systematically studied. The oxygen-containing functional groups on the surfaces of the PAA film make it sensitive and selective to ammonia molecules, even when tested at room temperature. The ammonia molecules adsorbed by the oxygen-containing functional groups of PAA (e.g., hydroxyl and epoxy groups) increase the membrane’s stiffness, which was identified as the primary mechanism leading to the positive frequency shifts. However, mass loading due to adsorption of ammonia molecules is not a major reason as it will result in a negative frequency shifts. When the PAA coated SAW sensor was exposed to ammonia with a low concentration of 500 ppb, it showed a positive frequency shift of 225 Hz, with both good repeatability and stability, as well as a good selectivity to ammonia compared with those to C2H5OH, H2, HCl, H2S, CO, NO2, NO, and CH3COCH3.

Due to the widespread deployment of distributed energy resources, renewable energies and battery energy storage, the peer to peer (P2P) energy trading schematic has gained the staple attention for improving the energy efficiency and energy flexibility of power grids. This is while, smart demand response programming (DRP) is considered as the bridge between these two indicators of smart grid. Moreover, the subtle point of proliferating P2P schematics is the regulation towards the maximization of social welfare leading to economic profitability of customers and owner's of microgrid and, eventually, reduction of pollutant emission of fossil fuels. Also, uncertainty, aroused by electrical consumption and renewable energy resources, is the core of every considerations, which has to be dealt with intelligent algorithms for strengthening the stability of transactions. On the other hand, compatibility with upper grid's regulations, i.e. power loss and voltage deviation, along with determining fair price of energy trading are the subjects of P2P-based tactics. Therefore, this paper proposes a P2P-based transactive energy sharing architecture, as two stage mixed integer non-linear programming, using smart DRP integrated with machine learning approach, i.e. radial basis neural network.Firstly, the uncertainty of electrical demand and renewable energies are relaxed through short term forecasting. Doing so, the day-ahead transactions of peers are obtained based on their energy management objective, targeting the energy reliability of customers, which energy not supplied criterion has to be equal to zero. Then, participation of customers in DRP, cost of customers, revenue of microgrid's owner and transactions of real time programming are optimally acquired based on Pareto front technique. Also, the simulations are conducted on IEEE 85 bus test system to realize the considerations. The results convey that the profitability of customers and owners is tied with the implementation of smart DRP and accurate forecasting of uncertain variables. In addition, the maximum improvements towards maximizing the revenue of owners and minimizing the cost of customers take place at hours which the electrical consumption is shifted from peaks to off-peaks and mid-peaks, certifying the performance of proposed methodology.

Both MXene and conducting polymers are hot research topics on electrode materials for supercapacitors (SCs). The combination of these two different types of materials can solve the defects that exist when they are used as electrode materials alone. Based on theoretical capacity, specific surface area, mass load, flexibility and excellent mechanical properties, MXene/conducting polymers composites demonstrate their potential to become advanced electrode materials. In order to further illustrate the changes brought about by these composites, a large number of examples of MXene/conducting polymers as electrodes are described in details. In general, this review covers the latest developments in the study of SCs based on MXene/conducting polymers composites, including materials preparation, electrode materials, symmetrical supercapacitors (SSCs) and asymmetrical supercapacitors (ASCs). This article aims to understand the application of MXene/conducting polymers composites in the research of SCs, and provides a guideline for further research of these promising materials.

In this letter, we analyze the secrecy performance of a reconfigurable intelligent surface (RIS)-aided communication system with spatially random unmanned aerial vehicles (UAVs) acting as eavesdroppers. We consider the scenarios where the base station (BS) is equipped with single and multiple antennas.The signal-to-noise ratios (SNRs) of the legitimate user and the eavesdroppers are derived analytically and approximated through a computationally effective method. The ergodic secrecy capacity is approximated and derived in closed-form expressions.Simulation results validate the accuracy of the analytical and approximate expressions and show the security-enhanced effect of the deployment of the RIS., Comment: Accepted by IEEE Wireless Communications Letters (WCL)

There are significant challenges in controlling uniformity of crystal inclination angles, growth orientations and film thicknesses to generate dual-mode surface acoustic waves (e.g., Rayleigh ones and shear-horizontal ones) for lab-on-a-chip applications. In this study, we demonstrate large area (up to three inches) and uniformly inclined piezoelectric ZnO films, sputtering-deposited on silicon using a glancing angle deposition method. Characterization using X-ray diffraction showed that the inclined ZnO films have an average crystal inclination angle of 29.0°, apart from the vertical (0002) orientation, at a substrate tilting angle of 30 o. Reflection signals of ZnO/Si surface acoustic wave devices clearly show the generations of both shear horizontal surface acoustic waves and Rayleigh waves. The Rayleigh waves enable efficient acoustofluidic functions including streaming and transportation of sessile droplets. Excitation direction of Rayleigh waves on the acoustofluidics versus the inclined angle direction has apparent influences on the acoustofluidic performance due to the anisotropic microstructures of the inclined films. The same device has been used to demonstrate biosensing of biotin/streptavidin interactions in a liquid environment using the shear-horizontal surface acoustic waves, to demonstrate its potential for integration into a complete lab-on-a-chip device.

It is a great challenge to achieve both high specific capacity and high energy density of supercapacitors by designing and constructing hybrid electrode materials through a simple but effective process. In this paper, we proposed a hierarchically nanostructured hybrid material combining Zn0.76Co0.24S (ZCS) nanoparticles and Co(OH)2 (CH) nanosheets using a two-step hydrothermal synthesis strategy. Synergistic effects between ZCS nanoparticles and CH nanosheets result in efficient ion transports during the charge-discharge process, thus achieving a good electrochemical performance of the supercapacitor. The synthesized ZCS@CH hybrid exhibits a high specific capacity of 1152.0 C g-1 at a current density of 0.5 A g-1 in 2 M KOH electrolyte. Its capacity retention rate is maintained at ∼ 70.0% when the current density is changed from 1 A g-1 to 10 A g-1. A hybrid supercapacitor (HSC) assembled from ZCS@CH as the cathode and active carbon (AC) as the anode displays a capacitance of 155.7 F g-1 at 0.5 A g-1, with a remarkable cycling stability of 91.3% after 12,000cycles. Meanwhile, this HSC shows a high energy density of 62.5 Wh kg-1 at a power density of 425.0 W kg-1, proving that the developed ZCS@CH is a promising electrode material for energy storage applications.

Privacy protection as a major concern of the industrial Big Data enabling entities, makes the massive safety-critical operation data of wind turbine, unable to exert its great value because of the threat of privacy leakage. How to improve the diagnostic accuracy of decentralized machines without data transfer remains an open issue, especially these machines are almost accompanied by skewed class distribution in the real industries. In this study, a class-imbalance privacy-preserving federated learning framework for fault diagnosis of decentralized wind turbine is proposed. Specifically, a biometric authentication technique is first employed to ensure that only legitimate entities can access private data and defend against malicious attacks. Then, the federated learning with two privacy-enhancing techniques enables high potential privacy and security in low-trust systems. After that, a solely gradient based self-monitor scheme is integrated to acknowledge the global imbalance information for class-imbalanced fault diagnosis. We leverage a real-world industrial wind turbine dataset to verify the effectiveness of the proposed framework. By comparison with five state-of-the-art approaches and two non-parametric tests, the superiority of the proposed framework in imbalanced classification is ascertained. An ablation study indicates the proposed framework can maintain high diagnostic performance while enhancing privacy protection.

A dual-channel single-mode-multi-mode-single-mode (SMS) fiber optic sensor encapsulated by polydimethylsiloxane (PDMS) was proposed for the first time, for the simultaneous monitoring of the brachial and radial arteries for accurate blood pressure prediction. With the help of the machine learning algorithm Support Vector Regression (SVR), the SMS fiber sensor can continuously and accurately monitor the systolic and diastolic blood pressure. Commercial sphygmomanometers are used to calibrate the accuracy of blood pressure measurement. Compared with the single-channel system, this system can extract more pulse wave features for blood pressure prediction, such as radial artery transit time (RPTT), brachial artery transit time (BPTT), and the transit time difference between the radial artery and the brachial artery (DBRPTT). The results show that the performance of dual-channel blood pressure monitoring is more accurate than that of single-channel blood pressure monitoring in terms of the absolute value of the correlation coefficient (R) and the average value of the difference between SBP and DBP. In addition, both the single-channel and dual-channel blood pressure monitoring are in line with the Association for the Advancement of Medical Devices (AAMI), but the average deviation (DM, 0.06 mmHg) and standard deviation (SD, 1.54 mmHg) of dual-channel blood pressure monitoring are more accurate. The blood pressure monitoring system has the characteristics of low cost, high sensitivity, non-invasive and capability for remote real time monitoring, which can provide effective solution for intelligent health monitoring in the era of artificial intelligence in the future.

In this paper, we discuss the security and reliability performance of a communication system, where the base station (BS) transmits signals to multiple users and an unmanned aerial vehicle (UAV) jammer sends friendly jamming signals to protect against a full-duplex active eavesdropper with the aid of caching. We derive the closed-form expressions of outage probability (OP) and intercept probability (IP) for the legitimate users and active eavesdropper, respectively. Aimed at minimizing the sum of the IP and the maximum OP among all users, we jointly optimize the BS transmit power, UAV jammer location and jamming power. An efficient algorithm based on alternating optimization (AO) and successive convex approximation (SCA) methods is designed to solve the optimization problem. Numerical results show that compared to other benchmark strategies, the proposed solution improves the reliability and security performance with the aid of caching and UAV friendly jamming.

One of the key challenges in developing gel-based electronics is to achieve robust sensing performance, by overcoming the intrinsic weaknesses such as unwanted swelling induced deformation, signal distortion caused by dehydration, large hysteresis in sensing signal, etc. In this work, we proposed a structural gel composite (SGC) approach by encapsulating the conductive hydrogel/MXene with a lipid gel (Lipogel) layer through an in situ polymerization. The hydrophobic Lipogel coating fulfils the SGC with unique anti-swelling property at an aqueous environment and excellent dehydration feature at an open-air, thus leading to long-term ultra-stability (over 90 days) and durability (over 2000 testing cycles) for underwater mechanosensing applications. As a result, the SGC based mechanoreceptor demonstrates a high and stable sensitivity (GF of 14.5). Moreover, several SGC based conceptual sensors with high sensitivity are developed to unveil their profound potentials in underwater monitoring of human motions, waterproof anti-counterfeiting application, and tactile trajectory tracking.

A polymer-based micro-bottle resonator coated with graphene oxide (GO) film is presented to improve the relative humidity (RH) sensing performance. Polymeric material Loctite 3525 was coated onto a quartz fiber and cured by using UV light irradiation and thermal reflow technology. A layer of GO film was prepared on the micro-bottle resonator by the dip impregnation method, which realized a high Q-factor (>104) transmission of energy by appropriately designing a wave-guide resonator coupling. By optimizing the concentration of GO dip impregnation solution, high sensitivity and figure of merit (FoM) of 0.161 nm/%RH and 2.01/%RH were achieved in the RH range of 22–81%. In addition, after high-temperature annealing at 300 °C, the temperature sensitivity decreased by an order of magnitude from 0.793 nm/°C to 0.068 nm/°C, which significantly reduces the cross-sensitivity between humidity and temperature. The proposed resonator has the advantages of being compact in size, low in cost, high sensitivity, and low in temperature crosstalk.

Owing to its unique, concealment and easy customisation by combining different wrist and hand gestures, High-Density surface electromyogram (HD-sEMG) is recognised as a potential solution to the next generation biometric authentication, which usually adopts a wireless Body Sensor Network (BSN) to acquire the multi-channel HD-sEMG biosignals from distributed electrode arrays. For more accurate and reliable classification, biometric authentication requires the distributed biosignals to be sampled simultaneously and be well-aligned, which means that the sampling jitters among the arrays need to be tiny. To synchronise data sampling clocks of a cluster of BSN nodes for biometric authentication, this paper modifies the Packet-Coupled Oscillators protocol by using a Dynamic controller (D-PkCOs). This protocol only involves one-way single packet exchange, which reduces the communication overhead significantly. For the purpose of maintaining precise sampling of these BSN nodes subject to drifting clock frequency and varying delays, the dynamic controller is designed via the H∞ robust method, and it is proved that all the BSN nodes’ sampling jitters are bounded. The experimental results demonstrate that the D-PkCOs protocol can keep the sampling jitters less than a microsecond in a 10-node IEEE 802.15.4 network. The application of D-PkCOs to the BSN shows that the HD-sEMG signal with a high signal-to-noise ratio is obtained, which leads to better gesture classification performance.

A low-cost and environment-friendly surface acoustic wave (SAW) humidity sensor was fabricated on a quartz substrate using sol-gel/spin-coated sodium alginate (SA) sensing layer. The sensing mechanism is based on the frequency shift of the SAW sensor caused by both mass loading and electrical loading, with the former being the dominant factor. The SA film prepared in this study is an environment-friendly material with a large number of hydroxyl and carboxylate groups, which easily adsorb and react with H2O molecules to form hydrogen bonds. These adsorbed H2O molecules lead to significantly enhanced mass loading and signal responses of the SAW sensor. Electrical loading effect is also generated due to the transfer of hydrogen ions in the H2O molecules, which alters the electrical resistance and results in changes of resonant frequencies of the SAW device. When the relative humidity (RH) is increased from 35% to 85%, the responses of the SAW sensor with 1 wt% SA are significantly decreased. Whereas in a low humidity environment (e.g., RH

The inappropriate mechanism designs for demand response (DR) in the community of microgirds (CoMGs) may cause massive problems, such as increase of consumers’ costs, rebound peaks, and thereby lack of optimality in the network. In this article, a bilevel energy management system (EMS) is proposed to tackle the challenges associated with DR programs for CoMGs. The current structure successfully models users’ behavior and dissatisfaction in the first level of optimization to develop best DR program for each of them. Moreover, in the second level, power system constraints are taken into account to prevent voltage and current deviation from their statutory limits. Each user is assumed to be part of a microgrid (MG) whose operation is controlled and optimized through its local EMS in the first level. On the other hand, the overall operation of all MGs is delegated to the whole system operator, which acts as the central EMS (CEMS) in the second level. An iterative transactive energy management method is proposed by CEMS to fairly limit the excess power of the MGs one day ahead for voltage and current regulation. The obtained results indicate the effectiveness of the proposed structure in preventing discomfort issues, voltage deviation and creation of the rebound peaks in the system.

The sharply growing demand for increased transmission capacity and bandwidth in last meter and last mile access networks together with the commercialization of fifth generation (5G) wireless systems has been opening up new opportunities for non-radio frequency (RF)-based wireless technologies. Visible light communications (VLC) technology is a potential candidate for access networking in 5G, which offers a higher spectral efficiency than RF-based Femtocell networks by three orders of magnitude. This paper proposes an all wireless optical bidirectional VLC multiple access scheme for pure VLC network access points in terminals. Centralized coordination is adopted to reduce the system complexity. And reservation of resource is introduced to guarantee collision avoidance during data frame transmission. The proposed multiple access scheme introduces special system parameters to achieve the balance of system throughput and access latency. The feasibility of the proposed scheme is verified by both theoretical analysis and experimental investigation. We show that the proposed scheme is suitable for a bidirectional pure VLC access network and can be used as a supplement in the IEEE 802.11 bb for 5G+bidirectional VLC application scenarios.

The indoor connected environment has witnessed significant research and development attention from industries and academia due to the growing number of smaller smart indoor devices around us. Developing an effective and efficient wireless access standard is one of the challenging tasks to enable the next generation indoor connected environment. The technical characteristics of existing wireless access standards, including IEEE 802.11a, 802.11n, and 802.11ac, are considerably limited for realizing indoor connected environments, particularly with a growing number of smaller intelligent devices. Moreover, their backward compatibility and migration strategies are significant for developing the next-generation wireless access standard for the indoor Internet of Things environment. In this context, this paper presents an indoor environmental experimental study focusing on the backward compatibility and migration-centric performance analysis of existing wireless access standards. Three wireless access standards that operate in the 5 GHz frequency spectrum are evaluated considering the metrics, including throughput, range, efficiency, and backward compatibility in an indoor environment. The experimental results are also compared with the analytical path loss model to observe the attributes for next-generation wireless access between the observed and analytical models. The evaluation can attest to the suitable migration strategy for stable next-generation wireless access development and deployment for an indoor smart Internet of Things environment.

Using intelligent reflecting surfaces (IRSs) is a promising approach to enhance the performance of wireless communication systems. In this paper, the placement optimization of multi-IRSs is investigated in multi-IRS-aided wireless communication systems, with the aim of minimizing the number of IRSs subject to the average achievable data rate. Then, an adaptive differential evolution algorithm is developed to jointly optimize the number, locations, and phase shift coefficients of IRSs, in which a novel strategy is devised to adaptively select the mutation operator for each individual. Compared with other algorithms, the proposed algorithm performs well in reducing the number of IRSs while satisfying the average achievable data rate.

A high sensitivity human chorionic gonadotropin (hCG) detection was conducted by a tapered side-polished (TSP) optical fiber sensor. Experimentally, the TSP fiber sensor was made by side polishing a short section of single mode fiber to a D shape structure and tapering the D shape section to a small diameter (

During the material removal stage in stone rough processing, milling type has been widely explored, which, however, may cause time and material consumption, as well as substantial stress for the environment. To improve the material removal rate and waste reuse rate in the rough processing stage for three-dimensional stone products with a special shape, in this paper, circular saw disc cutting is explored to cut a convex polyhedron out of a blank box, which approaches a target product. Unlike milling optimization, this problem cannot be well solved by mathematical methods, which have to be solved by geometrical methods instead. An automatic block cutting strategy is proposed intuitively by considering a series of geometrical optimization approaches for the first time. To obtain a big removal block, constructing cutting planes based on convex vertices is uniquely proposed. Specifically, the removal vertices (the maximum thickness of material removal) are searched based on the octree algorithm, and the cutting plane is constructed based on this thickness to guarantee a relatively big removal block. Moreover, to minimize the cutting time, the geometrical characteristics of the intersecting convex polygon of the cutting plane with the convex polyhedron are analyzed, accompanied by the constraints of the guillotine cutting mode. The optimization algorithm determining the cutting path is presented with a feed direction accompanied by the shortest cutting stroke, which confirms the shortest cutting time. From the big removal block and shortest cutting time, the suboptimal solution of the average material removal rate (the ratio of material removal volume to cutting time) is generated. Finally, the simulation is carried out on a blank box to approach a bounding sphere both on MATLAB and the Vericut platform. In this case study, for the removal of 85% of material with 19 cuts, the proposed cutting strategy achieves five times higher the average material removal rate than that of one higher milling capacity case.

The key challenge in free space optical (FSO) communications is combating the turbulence induced fading. As the channel fading in FSO is quasi-static, the transmission parameters such as the code rates, transmit power and modulation schemes can be modified with respect to the channel state information transmitted via the feedback path. As a result, adaptive channel coding is considered as one of the practical approaches to improve the FSO link performance. In this paper we investigate the FSO system with polar codes and analyse its performance by determining the optimum code-rate required to achieve a bit error rate of 10-9 under weak turbulence. We show that, using Monte-Carlo simulations for the scintillation indices of 0.12 and 0.2, the successive cancellation list (SCL) decoder offers coding gains of 2.5 and 0.3 dB, respectively as compared with SC decoder, and for scintillation index of 0.31, the SC decoder offers a coding gain of 2.5 dB compared to SCL decoder for the code rate.

The control of the current injected into the grid with lower harmonics is considered as one of the most important issues for the grid integration of distributed energy resources (DERs). The unbalances and harmonics in the grid voltage usually pollute the current injected into the grid due to the power electronic interfaces, for example, inverters. To address such problems, the present paper proposes a nonlinear higher order sliding mode controller (HOSMC) for grid-connected three-phase inverters with LCL filters in order to control the current injected into grid and improve the power quality. The proposed current controller injects the desired current into the grid with lower values of total harmonic distortions (THDs) under any grid voltage condition as well as it reduces the harmonics in the grid voltage. Apart from these, the proposed scheme is developed to provide robustness against parametric uncertainties where these uncertainties are modeled using the Taylor series expansion method. Finally, the performance of the system is evaluated using processor-in-loop (PIL) simulations via MATLAB/Simulink platform through the implementation on a system considering the capacity of the DER as 2 kVA per phase and compared with other existing control strategies.

This work presents a nonlinear backstepping control scheme for rapid earth fault current limiters (REFCLs) in resonant grounded power distribution systems to mitigate the severity of powerline bushfires. The main feature of the proposed control scheme is that it quickly eliminates both active and reactive components of the fault current to make it zero for reducing the chance of igniting bushfires. The nonlinear backstepping control scheme is employed on the dynamical model of a REFCL equipped with a T-type inverter. The desired tracking of the fault current is ensured with the proposed scheme by appropriately injecting the current to the neutral point. The performance of the controller is evaluated in terms of the fault current and faulty phase-to-ground voltage under different fault conditions while following the standard criteria for the practical operation. The fault current compensation capability of the proposed scheme is evaluated for both low and high impedance faults. Simulation results in software and processor-in-loop platforms clearly demonstrate the fault current is limited to a value much lower than its desired value of 0.5~A in less than 1~s which means that the chance of igniting bushfires will be reduced with the proposed controller.

In this study, micro-size copper particles (less than 25 μm) were incorporated into polyurethane (PU) using a solution mixing method and spin-coating technique to fabricate composite films in concentrations from 0.5 to 20 vol.%. The conductivity behaviour of these composites under pressure was studied experimentally and numerically. The conductivity measurements were performed in-plane and through-thickness under pressure. It was found that changes in conductivity only occurred in the z-direction under an applied pressure from 1 to 20 kPa. The results showed that pressure could induce conductivity up to about 7.2 × 10−1 S∙m−1 for composites with a Cu concentration higher than 2.6 vol.%. It seems that applied pressure reduced the thickness of the polymer film, decreasing the distance between copper particles and promoting the formation of a conductive network, thus making the material conductive. A semi-analytical model that can accurately provide the percolation threshold (PT) concentration was used to fit the experimental conductivity. The PT concentrations for PU-Cu composite ranged from 7.1 vol.% to 1.4 vol.% and decreased with the rise in pressure. This is known as a pressure-induced percolation transition phenomenon (PIPT). Finally, the finite element method based on the representative volume element model (FE-RVE) simulation technique was used to predict the conductivity behaviour. This numerical simulation provided a good description of the experimental conductivity after the PT and correctly predicted the PT concentration. This study shows that FE-RVE could be used to effectively simulate the influence of pressure on the electrical properties of a polymer–metal composite, reducing the need for costly and time-consuming experiments.

To alleviate the negative impact of noise on wireless federated learning (FL), we propose a channel-weighted aggregation scheme of FL (CWA-FL), in which the parameter server (PS) makes aggregation of the gradients according to the channel conditions of devices.} \textcolor{blue}{In the proposed scheme}, the gradients are transmitted to the PS in an uncoded way through an orthogonal multiple access (OMA) channel\textcolor{blue}{, which can avoid the synchronization issue among devices faced by over-the-air FL.} The convergence analysis of CWA-FL is conducted and the theoretical results show that the scheme can converge with the rate of O(1/T). Simulation results show that the proposed scheme performs better than the equal-weighted aggregation scheme of FL (EWA-FL) and is more robust to noise.

Surface acoustic wave (SAW) devices are generally fabricated on rigid substrates that support the propagation of waves efficiently. Although very challenging, the realisation of SAW devices on bendable and flexible substrates can lead to new generation SAW devices for wearable technologies. In this paper, we report flexible acoustic wave devices based on ZnO thin films coated on various substrates consisting of thin layers of metal (e.g., Ni/Cu/Ni) and/or polymer (e.g., polyethylene terephthalate, PET). We comparatively characterise the fabricated SAW devices and demonstrate their sensing applications for temperature and ultraviolet (UV) light. We also investigate their acoustofluidic capabilities on different substrates. Our results show that the SAW devices fabricated on a polymer layer (e.g. ZnO/PET, ZnO/Ni/Cu/Ni/PET) show enhanced temperature responsivity, and the devices with larger wavelengths are more sensitive to UV exposure. For actuation purposes, the devices fabricated on ZnO/Ni/Cu/Ni layer have the best performance for acoustofluidics, whereas insignificant acoustofluidic effects are observed with the devices fabricated on ZnO/PET layers. We propose that the addition of a metallic layer of Ni/Cu/Ni between ZnO and polymer layers facilitates the actuation capability for the acoustofluidic applications while keeping temperature and UV sensing capabilities, thus enhancing the integration of sensing and acoustofluidic functions.

The lattice vibrations (phonon modes) of crystals underpin a large number of material properties. The harmonic phonon spectrum of a solid is the simplest description of its structural dynamics and can be straightforwardly derived from the Hellman–Feynman forces obtained in a ground-state electronic structure calculation. The presence of imaginary harmonic modes in the spectrum indicates that a structure is not a local minimum on the structural potential-energy surface and is instead a saddle point or a hilltop, for example. This can in turn yield important insight into the fundamental nature and physical properties of a material. In this review article, we discuss the physical significance of imaginary harmonic modes and distinguish between cases where imaginary modes are indicative of such phenomena, and those where they reflect technical problems in the calculations. We outline basic approaches for exploring and renormalising imaginary modes, and demonstrate their utility through a set of three case studies in the materials sciences.

A key challenge in developing lab-on-a-chip devices is integrating various functionalities such as liquid manipulation and sensing on a single platform, which conventionally requires different technologies to be separately optimized.A key challenge in developing lab-on-a-chip devices is integrating various functionalities such as liquid manipulation and sensing on a single platform, which conventionally requires different technologies to be separately optimized. In this paper, we design circular or ring-shape interdigitated structures on a piezoelectric substrate that can be used for both sensing and liquid manipulation for point-of-care applications. We present acoustofluidic functionalities including streaming, jetting and nebulisation using the circular surface acoustic wave device to demonstrate the acoustofluidic manipulation capabilities of the actuator. We then optimise the design inspired by the double split-ring resonator geometry so that the device geometry can be used as a high performance wireless and electromagnetic sensor. We present the wireless-sensing capabilities of the device with case studies in monitoring glucose concentration and the fermentation process of yeast cells.

With the advancement in understanding of the physics inside chaotic systems, chaos has been harnessed from a nuisance to a beneficial factor in optical devices. Light–matter interaction in chaotic systems has been utilised for improving broadband energy harvesting and momentum transformations, achieving light localization beyond diffraction limit and even stabilizing the dynamics of high power laser. While extensive study about wave chaos has been made in deformed microcavities, investigation of how chaos dynamics evolves in curved space manifold remains elusive. Here, we study the non-Euclidean billiard of a torus-like manifold, which is a closed 2D cavity system with effective periodic boundaries. The ray chaotic behaviours on the deformed toroidal surface are explored using the geodesic equation. By tuning the deformation parameter of the torus, we observe the transition of the billiard from the ordered phase state to mixed phase states and then complete ray chaos. The photon sphere of the torus is identified as the transition position from ordered states to chaotic states. Compared with other chaotic behaviours resulted from the random scattering inside deformed cavities, we demonstrate chaotic dynamics purely on a curved surface, which may shed light on the better understanding of chaos in optics.

With the emergence of the fifth generation and beyond mobile networks, both visible light communications (VLC) and radio frequency (RF) or millimetre wave (mmW) systems are expected to maintain the connectivity in various environments. In outdoor environments the link (VLC or RF) availability is paramount, which is affected by channel conditions. In particular, in vehicular communications other vehicles, harsh environment, and road geometry and structure will have the impact on the link connectivity and availability. In such cases, a front-end antenna solution, which benefits both optical and RF communication links, can be seen as an attractive option that can be fitted in future vehicles. In this paper, we present the design and practical implementation of a planar hybrid VLC/mmW antenna operating at 20.8 GHz and show measured results for characterization of RF and VLC links as well as communications performance. We have used the widely adopted on-off keying and quadrature amplitude modulation schemes with different orders to demonstrate data rates of 5 Mb/s and up to 100 Mb/s for the VLC and mmW links, respectively. By measuring the bit error rate and the error vector magnitude for VLC and Rf links, respectively for each modulation we have shown that the proposed hybrid planar antenna is suitable for example in a typical vehicle -to-vehicle communications.

This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in real-time. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost.

The wireless information carrier shift from the radio frequencies to optical frequencies has been studied in increasing detail since the invention of the laser in the 1960s. With the advent of optical fiber communications and their global use, we have seen a growing interest in the field of optical wireless communications (OWC) for front- and back-haul access networks and beyond as part of fifth-generation (5G) wireless networks. OWC has found niche applications in a wide range of systems, from short-range indoor to long-range outdoor and very long deep space and inter-satellite links. New components, such as visible light-emitting sources, image sensors, advanced signal processing techniques, multi-input multi-output, and machine learning are pushing the OWC technology into new application areas such as vehicular communications, smart environments, medical, manufacturing, etc., as part of 5G wireless networks and the emerging 6G networks and beyond.This Special Issue was put together with the goal of bringing together the latest research and development in wireless light communications. A total of 53 submissions were received, and 24 were selected for publication in this Special Issue. The published works present novel results mainly on outdoor and indoor applications of light communications, while a few papers also address broader areas. We briefly present these works in the following sections.

Networked complex systems in a wide range of physics, biology and social sciences involve synergy among multiple agents beyond pairwise interactions. Higher-order mathematical structures such as hypergraphs have been increasingly popular in modelling and analysis of complex dynamical behaviours. Here, we study a simple three-body consensus model, which favourably incorporates higher-order network interactions, higher-order dimensional states, the group reinforcement effect and the social homophily principle. The model features asymmetric roles of acting agents using modulating functions. We analytically establish sufficient conditions for nonlinear consensus and conservation of states for agents with both discrete-time and continuous-time dynamics. We show that higher-order interactions encoded in three-body edges give rise to consensus and conservation for systems with gravity-like and Heaviside-like modulating functions. Furthermore, we illustrate our theoretical results with numerical simulations and examine the system convergence time through a network depreciation process.

The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charging costs. Besides, the random nature of EV users restricts them from following fixed charging times. Consequently, the real-time pricing scenarios are natural and can support optimizing the charging load and cost for EV users. This paper aims to develop charging cost optimization algorithm (CCOA) for residential charging of EVs. The proposed CCOA coordinates the charging of EVs by heuristically learning the real-time price pattern and the EV’s information, such as the battery size, current state-of-charge, and arrival & departure times. In contrast to the holistic price, the CCOA determines a threshold price value for each arrival and departure sequence of EVs and accordingly coordinates the charging process with optimizing the cost at each scheduling period. The charging cost is captured at the end of each charging activity and the cumulative cost is calculated until the battery’s desired capacity. Various charging scenarios for individual and aggregated EVs with random arrival sequences of EVs against the real-time price pattern are simulated through MATLAB. The simulation results show that the proposed algorithm outperforms with a low charging cost while avoiding the overloading of the grid compared to the conventional uncoordinated, flat-rate, and time-of-use systems.

Constructing plasmonic-semiconductor nanoarchitecture provides a photocatalytic platform for enhancing solar energy conversion. The excitation and extraction of energetic carriers are critical for improving energy efficiency, which can be affected by the geometric features of plasmonic structures. An extensive study on morphology dependent hot electron utilization is desirable but challenging. In this paper, we applied photocurrent response from the microscale reaction region on Au-TiO2 photoanode to evaluate the influence of plasmonic morphology in water splitting. We compared the photocurrent of two structures, gold nanospheres and nanorods, under visible illumination. We experimentally proved that the nanorods demonstrate better energy performance. The possible origins of this enhancement are ascribed to the sharp curvature at tips, where strong hot spots boost the generation and injection efficiency of hot electrons. These results may pave a way for a rational geometry design for plasmonic enhanced photocatalysis.

To date, the production and development of portable analytical devices for environmental and healthcare applications are rapidly growing. Herein, a portable electrochemical sensor for monitoring of noradrenaline (NA) secreted from living cells using mesoporous carbon-based materials was fabricated. The modification of the interdigitated electrode array (IDA) by nitrogen-doped mesoporous carbon spheres (N-doped MCS) and nitrogen-doped carbon hollow trunk-like structure (N-doped CHT) was used to fabricate the NA sensor. The N-doped CHT surface shows multiple holes distributed with micrometer-sized open holes (1–2 μm) and nanometer-sized thin walls (∼98 nm). The N-doped CHT surface heterogeneity of wrinkled and twisted hollow trunk structures improve the diffusion pathway and the NA molecules loading. The N-doped CHT/IDA showed a highly selective assay for monitoring of NA with high sensitivity (1770 μA/μM × cm2), a low detection limit (0.005 μM), and a wide linear range (0.01–0.3 μM). The N-doped CHT/IDA monitored the NA secreted from PC12 cells under various concentrations of simulation agents (KCl). The designed N-doped CHT/IDA provides a portable NA-sensor assay with facile signaling, good stability, high biocompatibility, in-vitro assay compatibility, and good reproducibility. Therefore, the designed sensor can be used as a portable sensor for NA detection in live cells and can be matched with portable smartphones after further developments.

In this letter, we analyse and optimize an intelligent reflecting surface (IRS)-assisted ultra-reliable and low-latency communications (uRLLC) system supported by wireless energy transfer (WET) technology, in which short packets are used in both the WET and wireless information transfer (WIT) phases. We first present the statistical features of the signal-to-noise ratio (SNR) of the system. Then, we derive an approximate closed-form expression of the average packet error probability (APEP). Additionally, we optimize the channel uses in the WET and WIT phases to maximize the effective throughput (ET) of the system. Finally, the effectiveness of the proposed solution is verified by Monte-Carlo simulation.

Offshore wind energy is drawing increased attention for the decarbonization of electricity generation. Due to the unpredictable and complex nature of offshore aero-hydro dynamics, the Wind Turbine Power Curve (WTPC) model is an important tool for power forecasting and, hence, providing a reliable, predictable, and stable power supply. With the development of data-driven approaches, the Artificial Neural Network (ANN) has become a popular method for estimating WTPCs. This paper integrates the Isolation Forest (iForest), Nonsymmetric Fuzzy Means (NSFM) Radial Basis Neural Network (RBFNN), and metaheuristic algorithm to form a novel WTPC model. iForest performed anomaly detection and removal, NSFM RBFNN approximated the WTPC, and the metaheuristic solved NSFM optimization without training RBFNN. Four real-world datasets were used to assess the performance of NSFM RBFNN. According to multiple evaluation metrics and the Diebold-Mariano test, the accuracy of NSFM RBFNN was significantly better than the other competitive neural network-based methods. Additionally, NSFM RBFNN was shown to be more robust to anomalies than competitors, which is highly beneficial for practical applications.

Efficient on-chip manipulation of photon spin is of crucial importance in developing future integrated nanophotonics as is electron spin in spintronics. The unidirectionality induced by the interaction between spin and orbital angular momenta suffers low efficiency in classical macroscopic optics, while it can be highly enhanced on subwavelength scales with suitable architectures. Here we propose and demonstrate a spin-sorting achiral split-ring coupler to unidirectionally excite dielectric-loaded plasmonic modes in two independent waveguides. We found experimentally that the impinging light with different spin can be selectively directed into one of two branching plasmonic waveguides with a directionality contrast up to 15.1 dB. A circular-helicity-independent compact beam splitter is also realized demonstrating great potential in designing complex interconnect nanocircuits. The illustrated approach is believed to open new avenues for developing advanced optical functionalities with a flexible degree of freedom in manipulation of on-chip chirality within chiral optics.

Surface acoustic wave (SAW) devices are increasingly applied in life sciences, biology, and point-of-care applications due to their combined acoustofluidic sensing and actuating properties. Despite the advances in this field, there remain significant gaps in interfacing hardware and control strategies to facilitate system integration with high performance and low cost. In this work, we present a versatile and digitally controlled acoustofluidic platform by demonstrating key functions for biological assays such as droplet transportation and mixing using a closed-loop feedback control with image recognition. Moreover, we integrate optical detection by demonstrating in situ fluorescence sensing capabilities with a standard camera and digital filters, bypassing the need for expensive and complex optical setups. The Acousto-Pi setup is based on open-source Raspberry Pi hardware and 3-D printed housing, and the SAW devices are fabricated with piezoelectric thin films on a metallic substrate. The platform enables the control of droplet position and speed for sample processing (mixing and dilution of samples), as well as the control of temperature based on acousto-heating, offering embedded processing capability. It can be operated remotely while recording the measurements in cloud databases toward integrated in-field diagnostic applications such as disease outbreak control, mass healthcare screening, and food safety.

The fabrication and application for twist sensing of an eccentric three-core fiber were demonstrated. The fiber was made by stack-and-draw technique, in which silica rods and core canes were put in a tube and drawn on a fiber drawing tower. Three cores formed a Mach-Zehnder interferometer, where the lights transmitted in the three cores interfered with each other, resulted in the formation of envelopes on spectrum. Because two of the cores were off axis, phase differences among the cores varied with twist due to different stretches on each core, which caused shift of the spectral envelopes of the interference signal. Wide range twist measurement can be realized with relatively high sensitivity by tracking lower dips of the envelopes. Experimental results revealed that the dips shift quadratically with twist angle, which means that the sensitivity increases with twist. The compensation of temperature influence was also implemented by inscribing a Bragg grating on one of the cores with femtosecond laser. Because the fiber can be mass-produced, it is suitable for twist sensing in practical application for its low cost.

This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an image with certain neighboring pixels providing discrete image information. The descriptor proposed in this work utilizes the local intensity of pixels in all eight directions of its neighborhood. The local octa-directional pattern results in two patterns, i.e., magnitude and directional, and each is quantized into a 40-bin histogram. A joint histogram is created by concatenating directional and magnitude histograms. To measure similarities between images, the Manhattan distance is used. Moreover, to maintain the computational cost, PCA is applied, which reduces the dimensionality. The proposed methodology is tested on a subset of a Multi-PIE face dataset. The dataset contains almost 800,000 images of over 300 people. These images carries different poses and have a wide range of facial expressions. Results were compared with state-of-the-art local patterns, namely, the local tri-directional pattern (LTriDP), local tetra directional pattern (LTetDP), and local ternary pattern (LTP). The results of the proposed model supersede the work of previously defined work in terms of precision, accuracy, and recall.

By constructing digital twins (DT) of an integrated energy system (IES), one can benefit from DT's predictive capabilities to improve coordinations among various energy converters, hence enhancing energy efficiency, cost savings and carbon emission reduction. This paper is motivated by the fact that practical IESs suffer from multiple uncertainty sources, and complicated surrounding environment. To address this problem, a novel DT-based day-ahead scheduling method is proposed. The physical IES is modelled as a multi-vector energy system in its virtual space that interacts with the physical IES to manipulate its operations. A deep neural network is trained to make statistical cost-saving scheduling by learning from both historical forecasting errors and day-ahead forecasts. Case studies of IESs show that the proposed DT-based method is able to reduce the operating cost of IES by 63.5%, comparing to the existing forecast-based scheduling methods. It is also found that both electric vehicles and thermal energy storages play proactive roles in the proposed method, highlighting their importance in future energy system integration and decarbonisation., 28 pages, 8 figures, journal paper accepted by Applied Energy

Press-pack Insulated Gate Bipolar Transistors (PP IGBT) are becoming increasingly used in HVDC and FACT applications. Due to its unique packaging, its reliability issues have also attracted increasing attention in the engineering field. More comprehensive investigation into the thermal, electrical and mechanical factors should be conducted to reveal the operation condition and status of the devices. The objective of this work is to study the relationship among the deformation of the collector groove and the thermal stress of the chip as well as the contact pressure by simulating the PP IGBT under normal and abnormal conditions. A sophisticated 3D finite element (FE) model of a PP IGBT has been developed which includes the coupling with thermal–mechanical effect. Also, the influence of different pressure and thermal stress on deformation is discussed thoroughly that can provide insight of how to monitor the status of a PP IGBT from the perspective of deformation.