Low profile cavity-embedded ultra-wideband UHF array antenna with end-fire beams

A low-profile,vertically polarized,ultra-wideband array antenna with end-fire beams operating in an ultra-high frequency(UHF)band is developed in this paper.The array antenna consists of 1×16 log-periodic top-hat loaded monopole antenna arrays and is feasible to embed into a shallow cavity to further reduce the array height.Capacitance is introduced in the proposed antenna element to reduce profile height and the rectangular top hats are carefully designed to minimize the transverse dimension.Simulated results show that when the antenna array operates in a frequency range of 300 MHz-900 MHz,the end-fire radiation pattern achieves±45°scanning range in the horizontal plane.Then prototypes of the proposed end-fire antenna element and a uniformly spaced linear array(1×2)are fabricated and validated.The end-fire antenna array should be suitable for airborne applications where low-profile and conformal scanning phased antenna arrays with end-fire radiations are required.This design is attractive for airborne platform applications that are used to search,discover,identify,and scout the aerial target with vertically polarized beams.

Propagation Modeling and Characteristic Analysis of Terahertz Waves via High Altitude Platforms

Satellite-to-ground terahertz communication is limited by the power of signal source and antenna gain level,and has large path loss,which is difficult to implement.In this paper,a feasible scheme of satellite-to-ground terahertz communication using High Altitude Platforms(HAPs)as relay is presented,and the path loss on terahertz communication links is modeled and analyzed.Combined with the path loss model,the transmission loss along HAP-to-ground paths under different seasons and complex weather environment in Ali,Xizang,China is calculated.The results show that the transmission characteristics of terahertz waves in winter and summer are significantly different,mainly reflected in the number and bandwidth of usable atmospheric windows.Furthermore,the additional attenuation caused by the typical sand dust and ice cloud environment on terahertz band can reach 6.1 dB and 1.9 dB at the maximum respectively.With the aid of high gain antenna,the usable communication frequencies of the HAP-to-ground links in winter are significantly more than those in summer.When the transmitting and receiving antenna gain is 40 dBi respectively,the usable communication frequency can reach 1.35 THz in winter,while it is limited to less than 1 THz in summer,up to 0.493 THz.

Improved organs at risk segmentation based on modified U‐Net with self‐attention and consistency regularisation

Cancer is one of the leading causes of death in the world,with radiotherapy as one of the treatment options.Radiotherapy planning starts with delineating the affected area from healthy organs,called organs at risk(OAR).A new approach to automatic OAR seg-mentation in the chest cavity in Computed Tomography(CT)images is presented.The proposed approach is based on the modified U‐Net architecture with the ResNet‐34 encoder,which is the baseline adopted in this work.The new two‐branch CS‐SA U‐Net architecture is proposed,which consists of two parallel U‐Net models in which self‐attention blocks with cosine similarity as query‐key similarity function(CS‐SA)blocks are inserted between the encoder and decoder,which enabled the use of con-sistency regularisation.The proposed solution demonstrates state‐of‐the‐art performance for the problem of OAR segmentation in CT images on the publicly available SegTHOR benchmark dataset in terms of a Dice coefficient(oesophagus-0.8714,heart-0.9516,trachea-0.9286,aorta-0.9510)and Hausdorff distance(oesophagus-0.2541,heart-0.1514,trachea-0.1722,aorta-0.1114)and significantly outperforms the baseline.The current approach is demonstrated to be viable for improving the quality of OAR segmentation for radiotherapy planning.

Guest Editorial:Special issue on advances in representation learning for computer vision

Deep learning has been a catalyst for a transformative revo-lution in machine learning and computer vision in the past decade.Within these research domains,methods grounded in deep learning have exhibited exceptional performance across a spectrum of tasks.The success of deep learning methods can be attributed to their capability to derive potent representations from data,integral for a myriad of downstream applications.These representations encapsulate the intrinsic structure,fea-tures,or latent variables characterising the underlying statistics of visual data.Despite these achievements,the challenge per-sists in effectively conducting representation learning of visual data with deep models,particularly when confronted with vast and noisy datasets.This special issue is a dedicated platform for researchers worldwide to disseminate their latest,high-quality articles,aiming to enhance readers'comprehension of the principles,limitations,and diverse applications of repre-sentation learning in computer vision.

SmartMicro Grid Energy System Management Based on Optimum Running Cost for Rural Communities in Rwanda

The governmental electric utility and the private sector are joining hands to meet the target of electrifying all households by 2024.However,the aforementioned goal is challenged by households that are scattered in remote areas.So far,Solar Home Systems(SHS)have mostly been applied to increase electricity access in rural areas.SHSs have continuous constraints to meet electricity demands and cannot run income-generating activities.The current research presents the feasibility study of electrifying Remera village with the smart microgrid as a case study.The renewable energy resources available in Remera are the key sources of electricity in that village.The generation capacity is estimated based on the load profile.The microgrid configurations are simulated with HOMER,and the genetic algorithm is used to analyze the optimum cost.By analyzing the impact of operation and maintenance costs,the results show that the absence of subsidies increases the levelized cost of electricity(COE)five times greater than the electricity price from the public utility.The microgrid made up of PV,diesel generator,and batteries proved to be the most viable solution and ensured continuous power supply to customers.By considering the subsidies,COE reaches 0.186$/kWh,a competitive price with electricity from public utilities in Rwanda.

Impact of welding equipment on power quality

In an industrial facility,many electrical consumers can affect the quality of electricity.Therefore,the freedom from interference sources of these devices and equipment can be crucial for quality and uninterrupted electricity supply.Electric welding equipment is also a possible source of interference.The electrical harmonic injections created by welding equipment into the electrical network can affect the operation of other consumers connected to the given distribution points and cause unjustified overheating and shutdowns of some network components.The aim of the research is to analyse the current harmonic injection of welding equipment of different types and modes of operation connected to the internal distribution network of the industrial facility.The effectiveness of the active harmonic filter built into the welding equipment was also examined in the paper.The results showed that the built-in active harmonic filter of the DC045 laser welding equipment was ineffective because the total harmonic distortion(THD)was about three times the 8%allowed by IEEE 519−2022 standard.The current harmonic injection of MIG 320 and MM403 type welding equipment was more than five times the permissible value of 5%.The current harmonic distortion of the PLAS140 type plasma-jet cutter equipment was below the 5% value allowed in the standard,thus it complied with it.Based on the measurement results,it can be concluded that the use of protection against harmonics is also necessary for welding equipment.Finally,proposals were made in the paper to reduce the effect of harmonics.

Polariton lasing in Mie-resonant perovskite nanocavity

Deeply subwavelength lasers(or nanolasers)are highly demanded for compact on-chip bioimaging and sensing at the nanoscale.One of the main obstacles for the development of single-particle nanolasers with all three dimensions shorter than the emitting wavelength in the visible range is the high lasing thresholds and the resulting overheating.Here we ex-ploit exciton-polariton condensation and mirror-image Mie modes in a cuboid CsPbBr3 nanoparticle to achieve coherent emission at the visible wavelength of around 0.53μm from its ultra-small(≈0.007μm3 or≈λ3/20)semiconductor nanocav-ity.The polaritonic nature of the emission from the nanocavity localized in all three dimensions is proven by direct com-parison with corresponding one-dimensional and two-dimensional waveguiding systems with similar material parameters.Such a deeply subwavelength nanolaser is enabled not only by the high values for exciton binding energy(≈35 meV),re-fractive index(>2.5 at low temperature),and luminescence quantum yield of CsPbBr3,but also by the optimization of po-laritons condensation on the Mie resonances with quality factors improved by the metallic substrate.Moreover,the key parameters for optimal lasing conditions are intermode free spectral range and phonons spectrum in CsPbBr3,which govern polaritons condensation path.Such chemically synthesized colloidal CsPbBr3 nanolasers can be potentially de-posited on arbitrary surfaces,which makes them a versatile tool for integration with various on-chip systems.

利用近似解加速求解SAT问题的启发式完全算法

结合DPLL完全算法能够证明可满足性(SAT)问题的不可满足性和局部搜索算法快速的优点,提出利用近似解加速求解SAT问题的启发式完全算法.首先利用局部搜索算法快速地得到一个近似解,并将该近似解作为完全算法的初始输入,用于其中分支变量的相位决策.该算法引导完全算法优先搜索近似解所在的子空间,加速解决器找到可满足解的过程,为SAT问题的求解提供了一种新的有效途径.实验结果表明,该算法有效地提高了决策的精度和SAT解决器的效率,对很多实例非常有效.

干涉型光纤传感器阵列消PIF技术的研究

针对低双折射光纤双光束干涉型传感器两臂偏振态随机变化引起的信号衰落 ,提出了一种新型消偏振方式 ,它可以在可见度略有下降的情况下 ,较好地消除偏振态变化引起的干涉信号可见度的随机变化。该方案是通过相互正交的两个偏振态来补偿由于其中一个偏振态变化导致的干涉信号衰落。通过自动增益控制电路可以使传感信号稳定 ,能够在信噪比有所下降的情况下消除偏振衰落的影响 。

Angle estimation in bistatic MIMO radar using improved reduced dimension Capon algorithm

This paper discusses the problem of direction of departure （DOD） and direction of arrival （DOA） estimation for a bistatic multiple input multiple output （MIMO） radar, and proposes an improved reduced-dimension Capon algorithm therein. Compared with the reduced-dimension Capon algorithm which requires pair matching between the two-dimensional angle estimation, the pro- posed algorithm can obtain automatically paired DOD and DOA estimation without debasing the performance of angle estimation in bistatic MIMO radar. Furthermore, the proposed algorithm has a lower complexity than the reduced-dimension Capon algorithm, and it is suitable for non-uniform linear arrays. The complexity of the proposed algorithm is analyzed and the Cramer-Rao bound （CRB） is also derived. Simulation results verify the usefulness of the proposed algorithm.

External Characteristics and Internal Flow Features of a Centrifugal Pump during Rapid Startup

Centrifugal pumps always work under steady conditions,and many researches focus on the steady operation.But transient conditions,such as sudden startup and shutdown,are inevitable.The researches on the inner flow of centrifugal pumps under transient conditions have been done,and they show that the transient operation is different from the steady operation.In order to research the evolution of unsteady flow in a centrifugal pump under transient conditions,and to investigate the mechanism of transient effects by analyzing the unsteady flow in a centrifugal pump,the external characteristic experiment and the internal flow numerical calculation of the centrifugal pump with an open impeller during startup is presented.The relationships of the rotation speed,capacity and head between start-time are obtained by the external characteristics experiment.The numerical calculations under startup process are carried out by using the k-e model and N-S equation.The distribution of velocity and pressure in the inner channel of the tested pump was obtained by choosing fourteen start-time points and twelve geometrical points in the impeller channel during startup.The calculation results show that the velocity and the pressure increase linearly with the start-time before rotation＇s speed gets steady,then changes almost horizontally after rotation speed becomes steady,then fluctuates until being steady.The internal flow characteristics are in good agreement with the external characteristic experimental results and numerical calculation.The simulation methods and results make the basis for the diagnosis and optimization of under flow in the centrifugal pump during transient operation.

A distributed VSG control method for a battery energy storage system with a cascaded H-bridge in a grid-connected mode

With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role in renewable energy integration.In this paper,a distributed virtual synchronous generator(VSG)control method for a battery energy storage system(BESS)with a cascaded H-bridge converter in a grid-connected mode is proposed.The VSG is developed without communication dependence,and state-of-charge(SOC)balancing control is achieved using the distributed average algorithm.Owing to the low varying speed of SOC,the bandwidth of the distributed communication networks is extremely slow,which decreases the cost.Therefore,the proposed method can simultaneously provide inertial support and accurate SOC balancing.The stability is also proved using root locus analysis.Finally,simulations under different conditions are carried out to verify the effectiveness of the proposed method.

A realizable quantum encryption algorithm for qubits

A realizable quantum encryption algorithm for qubits is presented by employing bit-wise quantum computation. System extension and bit-swapping are introduced into the encryption process, which makes the ciphertext space expanded greatly. The security of the proposed algorithm is analysed in detail and the schematic physical implementation is also provided. It is shown that the algorithm, which can prevent quantum attack strategy as well as classical attack strategy, is effective to protect qubits. Finally, we extend our algorithm to encrypt classical binary bits and quantum entanglements.

Sliding Mode Control in Power Converters and Drives: A Review

Sliding mode control(SMC)has been studied since the 1950s and widely used in practical applications due to its insensitivity to matched disturbances.The aim of this paper is to present a review of SMC describing the key developments and examining the new trends and challenges for its application to power electronic systems.The fundamental theory of SMC is briefly reviewed and the key technical problems associated with the implementation of SMC to power converters and drives,such chattering phenomenon and variable switching frequency,are discussed and analyzed.The recent developments in SMC systems,future challenges and perspectives of SMC for power converters are discussed.

Fault Diagnosis for Aero-engine Applying a New Multi-class Support Vector Algorithm

Hierarchical Support Vector Machine （H-SVM） is faster in training and classification than other usual multi-class SVMs such as ＂1-V-R＂and ＂1-V-1＂. In this paper, a new multi-class fault diagnosis algorithm based on H-SVM is proposed and applied to aero-engine. Before SVM training, the training data are first clustered according to their class-center Euclid distances in some feature spaces. The samples which have close distances are divided into the same sub-classes for training, and this makes the H-SVM have reasonable hierarchical construction and good generalization performance. Instead of the common C-SVM, the v-SVM is selected as the binary classifier, in which the parameter v varies only from 0 to 1 and can be determined more easily. The simulation results show that the designed H-SVMs can fast diagnose the multi-class single faults and combination faults for the gas path components of an aero-engine. The fault classifiers have good diagnosis accuracy and can keep robust even when the measurement inputs are disturbed by noises.

A secure identification system using coherent states

A quantum identification system based on the transformation of polarization of a mesoscopic coherent state is proposed. Physically, an initial polarization state which carries the identity information is transformed into an arbitrary elliptical polarization state, To verify the identity of a communicator, a reverse procedure is performed by the receiver, For simply describing the transformation procedure, the analytical methods of Poincaré sphere and quaternion are adopted. Since quantum noise provides such a measurement uncertainty for the eavesdropping that the identity information cannot be retrieved from the elliptical polarization state, the proposed scheme is secure.

Event-triggered leader-following formation control for multi-agent systems under communication faults: application to a fleet of unmanned aerial vehicles

The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems(MASs)under communication faults.All the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the agents.Linear matrix inequalities(LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization error.Based on the closed-loop system,an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy consumption.The proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles(UAVs)under communication faults.A comparison between a state-of-the-art technique and the proposed technique has been provided,demonstrating the performance improvement brought by the proposed approach.

Performance Analysis of Modulation Techniques in 5G Communication System

In the 5^(th) generation mobile communication(5G)system,better bitrate,better power consumption,and better Bit Error Rate are needed.To meet all these requirements in 5G,the waveform is important.Although the Orthogonal Frequency Division Multiplexing(OFDM)modulation scheme has been commonly used in 4G,it is difficult to meet the requirements of 5G.A lot of candidate waveforms are discussed in the 5G system included Filter Bank Multicarrier(FBMC),Universal Filtered Multicarrier(UFMC),Filtered OFDM(F-OFDM),and Generalized Frequency Division Multiplexing(GFDM),etc.However,since GFDM is no longer widely used,in this paper,FBMC,UFMC,and F-OFDM modulation schemes are discussed and compared with OFDM.Power Spectral Density(PSD),Bit Error Rate(BER),Transmitted Signal Power,Peak Average Power Ratio(PAPR)and Bit Rate parameters of the modulation schemes are studied and compared with OFDM.FBMC demonstrates to be the most promising modulation scheme for 5G systems.

A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

Anti-slip control systems are essential for railway vehicle systems with traction.In order to propose an effective anti-slip control system,adhesion information between wheel and rail can be useful.However,direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding.Therefore,a proportional–integral controller,which operates simultaneously with a recently proposed swarm intelligencebased adhesion estimation algorithm,is proposed in this study.This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail.To validate the methodology,a tram wheel test stand with an independently rotating wheel,which is a model of some low floor trams produced in Czechia,is considered.Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

High Performance Viterbi Decoder on Cell/B.E.

Viterbi decoding is widely used in many radio systems. Because of the large computation complexity, it is usually implemented with ASIC chips, FPGA chips, or optimized hardware accelerators. With the rapid development of the multicore technology, multicore platforms become a reasonable choice for software radio (SR) systems. The Cell Broadband Engine processor is a state-of-art multi-core processor designed by Sony, Toshiba, and IBM. In this paper, we present a 64-state soft input Viterbi decoder for WiMAX SR Baseband system based on the Cell processor. With one Synergistic Processor Element (SPE) of a Cell Processor running at 3.2GHz, our Viterbi decoder can achieve the throughput up to 30Mb/s to decode the tail-biting convolutional code. The performance demonstrates that the proposed Viterbi decoding implementation is very efficient. Moreover, the Viterbi decoder can be easily integrated to the SR system and can provide a highly integrated SR solution. The optimization methodology in this module design can be extended to other modules on Cell platform.