Low-power SiPM readout BETA ASIC for space applications

The BETA application-specific integrated circuit(ASIC)is a fully programmable chip designed to amplify,shape and digitize the signal of up to 64 Silicon photomultiplier(SiPM)channels,with a power consumption of approximately~1 mW/channel.Owing to its dual-path gain,the BETA chip is capable of resolving single photoelectrons(phes)with a signal-to-noise ratio(SNR)>5 while simultaneously achieving a dynamic range of~4000 phes.Thus,BETA can provide a cost-effective solution for the readout of SiPMs in space missions and other applications with a maximum rate below 10 kHz.In this study,we describe the key characteristics of the BETA ASIC and present an evaluation of the performance of its 16-channel version,which is implemented using 130 nm technology.The ASIC also contains two discriminators that can provide trigger signals with a time jitter down to 400 ps FWHM for 10 phes.The linearity error of the charge gain measurement was less than 2%for a dynamic range as large as 15 bits.

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.

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.

Depolarization Degree to Determine Dihedral Attribute of Radar Target

This paper investigates the ability of the depolarization degree, derived from the characteristic polarization states at the resonant frequency set, to identify corner or swept, i.e. dihedral, changes in same-class targets by a metallic wire example. A well-estimated depolarization degree requires a robust extraction of the fundamental target resonance set in two orthogonal sets of fully co-polarized and cross-polarized polarization channels, then finding the null polarization states using the Lagrangian method. Such depolarization degree per resonance mode has the potential to form a robust feature set because it is relatively less sensitive to onset ambiguity, invariant to rotation, and could create a compact, recognizable, and separable distribution in the proposed feature space. The study was limited to two targets with two swept changes of fifteen degrees within normal incidence;under a supervised learning approach, the results showed that the identification rate converging to upper-bound (100%) for a signal-to-noise ratio above 20 dB and lower-bound around (50%) below −10 dB.

The Pairing Analysis Improvement of Magnetized Structure in Electromagnetic Bulging Process in Case of Tube with Field Shaper

In the current practical science, the accuracy in the formability of metal alloys being the goal when using electromagnetic forming (EMF) technology, which is a high-speed processing technology that uses Lorentz forces to achieve plastic deformation of sheet metal;according to the previous analysis, the results have shown that in most cases, the Lorentz force acting on the workpiece (metal) is not uniform, there are uneven axial deformations of the metal plates which prevent the rapid advancement of today’s technology. In this article, we presented some advanced analyzes which will lead us to improve the technical solution for the problems of non-uniform axial deformations of the metals in the traditional tube electromagnetic forming technology (EMF). A field shaper is used as a practical forming tool to influence the magnetic field and magnetic pressure distribution, thereby improving the forming ability and result during the electromagnetic forming (EMF) process and we see that induced eddy current control is realized by changing the structural parameters of the magnetic field shaper;which improves the strength and controllability of the magnetic force that acts on the workpiece;thereby a greater radial magnetic pressure can be achieved with field shaper than the case without it;the field shaper regulates the electromagnetic force, the distribution of the magnetic pressure decreases, and the uniform force area of the tube increases which effectively enhances the uniform range of the pipe electromagnetic bulging and the electromagnetic induction coupling between the coil and the metallic workpiece is generally required to produce the Lorentz forces. Using COMSOL Multiphysics® simulation software helped us to accurately represent the real world, simulating multiple physical effects that happened in this model during the process.

Development of VME system in RPC electronics for reactor neutrino experiment at Daya Bay Nuclear Power Plant

VME system of the Resistive Plate Chamber (RPC) electronics for the Daya Bay Reactor Neutrino Experiment is described in this paper. A 9U VME RPC trigger module (RTM) is designed to process coincidence signals coming from front end cards (FECs), to generate local triggers and send them to FECs to select the hit data from RPC detector, to report trigger information to a master trigger system and receive cross triggers from the master trigger system. Another 9U VME readout module is designed to collect data from all FECs, to send out configurations to FECs, and to transmit collected hit data to the data acquisition system via VME bus. Test results prove that the VME system is capable of treating a maximum data rate (2.2 MB·s-1 ), without data loss.

Pinning energies of organic semiconductors in high-efficiency organic solar cells

With the emergence of new materials for high-efficiency organic solar cells(OSCs),understanding and finetuning the interface energetics become increasingly important.Precise determination of the so-called pinning energies,one of the critical characteristics of the material to predict the energy level alignment(ELA)at either electrode/organic or organic/organic interfaces,are urgently needed for the new materials.Here,pinning energies of a wide variety of newly developed donors and nonfullerene acceptors(NFAs)are measured through ultraviolet photoelectron spectroscopy.The positive pinning energies of the studied donors and the negative pinning energies of NFAs are in the same energy range of 4.3−4.6 eV,which follows the design rules developed for fullerene-based OSCs.The ELA for metal/organic and inorganic/organic interfaces follows the predicted behavior for all of the materials studied.For organic-organic heterojunctions where both the donor and the NFA feature strong intramolecular charge transfer,the pinning energies often underestimate the experimentally obtained interface vacuum level shift,which has consequences for OSC device performance.

Comparison of pulse-modulated and continuous operation modes of a radio-frequency inductive ion source

The paper describes an experimental study of the characteristics of a pulse-modulated radiofrequency(RF)discharge sustained at low pressures,typical of the operating modes of RF gridded ion sources.The motivation for the study is the question of whether the RF pulsemodulated mode can increase the efficiency of the ion source.The ion current values extracted from an RF inductive ion source operating in continuous and pulse-modulated modes were compared.The experimental data were also compared with the parameter calculations based on a0D numerical model of the discharge.The measurements showed that the pulse-modulated operation mode of the RF ion source had a noticeable advantage when the power of the RF generator was 140 W or lower.However,as the generator power increased,the advantage was lost because the pulse-modulated operation mode,having a higher RF power instant value,entered the region of existence sooner than the continuous mode,where the ion production cost begins to grow with RF power.

Squeezed state generation using cryogenic InP HEMT nonlinearity

This study focuses on generating and manipulating squeezed states with two external oscillators coupled by an InP HEMT operating at cryogenic temperatures.First,the small-signal nonlinear model of the transistor at high frequency at 5 K is analyzed using quantum theory,and the related Lagrangian is theoretically derived.Subsequently,the total quantum Hamiltonian of the system is derived using Legendre transformation.The Hamiltonian of the system includes linear and nonlinear terms by which the effects on the time evolution of the states are studied.The main result shows that the squeezed state can be generated owing to the transistor’s nonlinearity;more importantly,it can be manipulated by some specific terms introduced in the nonlinear Hamiltonian.In fact,the nonlinearity of the transistors induces some effects,such as capacitance,inductance,and second-order transconductance,by which the properties of the external oscillators are changed.These changes may lead to squeezing or manipulating the parameters related to squeezing in the oscillators.In addition,it is theoretically derived that the circuit can generate two-mode squeezing.Finally,second-order correlation(photon counting statistics)is studied,and the results demonstrate that the designed circuit exhibits antibunching,where the quadrature operator shows squeezing behavior.

Online coal dust suppression system for opencast coal mines

Coal is the major source of power in India and world over.Coal mining is an essential industry which has a major role in the economic development of the country.Most major mining activities contribute directly or indirectly to air pollution.Coal dust is a major air pollutant which affects the personal working in the mines and also people residing in villages near the mines.Air pollution due to coal particulates can affect human health and cause damages to the environment.Hence effective pollution control mechanisms are needed to keep the pollution levels within permissible levels.The easiest and most common method employed for dust suppression worldwide is sprinkling of water.In majority of mines,water sprinklers are operated manually and can lead to wastage of water due to over sprinkling.It can also prove to be ineffective in dust suppression if sprinkling is not done properly.The paper proposes a system which can be deployed to automate the dust suppressions sprinklers.The system will monitor the concentration of PM_(10) and PM_(2.5) in the air and initiate sprinkling operation when the particulate matter content exceeds preconfigured limits.

Analysing Various Control Techniques for Manipulator Robotic System (Robogymnast)

The Robogymnast is a highly complex,three-link system based on the triple-inverted pendulum and is modelled on the human example of a gymnast suspended by their hands from the high bar and executing larger and larger upswings to eventually rotate fully.The links of the Robogymnast correspond respectively to the arms,trunk,and lower limbs of the gymnast,and from its three joints,one is under passive operation,while the remaining two are powered.The passive top joint poses severe challenges in attaining the smooth movement control needed to operate the Robogymnast effectively.This study assesses four types of controllers used for systems operation and identifies how far response stabilisation is achieved with each.The system is simulated using MATLAB Simulink,with findings generated regarding rising and settling time,as well as overshoot.The research primarily seeks to exam-ine the application of a linear quadratic regulator controller,proportional-integral-derivative controller,fuzzy linear quadratic regulator controller and linear quadratic regulator-proportional-integral-derivative controller for this type of system and comparisons between the different controllers to demon-strate successful performance,which highlights the claimed advantages of the proposed system.

Employing adaptive fuzzy computing for RCP intelligent control and fault diagnosis

Loss of coolant accident(LOCA),loss of fluid accident(LOFA),and loss of vacuum accident(LOVA)are the most severe accidents that can occur in nuclear power reactors(NPRs).These accidents occur when the reactor loses its cooling media,leading to uncontrolled chain reactions akin to a nuclear bomb.This article is focused on exploring methods to prevent such accidents and ensure that the reactor cooling system remains fully controlled.The reactor coolant pump(RCP)has a pivotal role in facilitating heat exchange between the primary cycle,which is connected to the reactor core,and the secondary cycle associated with the steam generator.Furthermore,the RCP is integral to preventing catastrophic events such as LOCA,LOFA,and LOVA accidents.In this study,we discuss the most critical aspects related to the RCP,specifically focusing on RCP control and RCP fault diagnosis.The AI-based adaptive fuzzy method is used to regulate the RCP’s speed and torque,whereas the neural fault diagnosis system(NFDS)is implemented for alarm signaling and fault diagnosis in nuclear reactors.To address the limitations of linguistic and statistical intelligence approaches,an integration of the statistical approach with fuzzy logic has been proposed.This integrated system leverages the strengths of both methods.Adaptive fuzzy control was applied to the VVER 1200 NPR-RCP induction motor,and the NFDS was implemented on the Kori-2 NPR-RCP.

Electroencephalography (EEG) Based Neonatal Sleep Staging and Detection Using Various Classification Algorithms

Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system.EEG based neonatal sleep staging provides valuable information about an infant’s growth and health,but is challenging due to the unique characteristics of EEG and lack of standardized protocols.This study aims to develop and compare 18 machine learning models using Automated Machine Learning(autoML)technique for accurate and reliable multi-channel EEG-based neonatal sleep-wake classification.The study investigates autoML feasibility without extensive manual selection of features or hyperparameter tuning.The data is obtained from neonates at post-menstrual age 37±05 weeks.352530-s EEG segments from 19 infants are used to train and test the proposed models.There are twelve time and frequency domain features extracted from each channel.Each model receives the common features of nine channels as an input vector of size 108.Each model’s performance was evaluated based on a variety of evaluation metrics.The maximum mean accuracy of 84.78%and kappa of 69.63%has been obtained by the AutoML-based Random Forest estimator.This is the highest accuracy for EEG-based sleep-wake classification,until now.While,for the AutoML-based Adaboost Random Forest model,accuracy and kappa were 84.59%and 69.24%,respectively.High performance achieved in the proposed autoML-based approach can facilitate early identification and treatment of sleep-related issues in neonates.

Advances in nuclear detection and readout techniques

“A Craftsman Must Sharpen His Tools to Do His Job,”said Confucius.Nuclear detection and readout techniques are the foundation of particle physics,nuclear physics,and particle astrophysics to reveal the nature of the universe.Also,they are being increasingly used in other disciplines like nuclear power generation,life sciences,environmental sciences,medical sciences,etc.The article reviews the short history,recent development,and trend of nuclear detection and readout techniques,covering Semiconductor Detector,Gaseous Detector,Scintillation Detector,Cherenkov Detector,Transition Radiation Detector,and Readout Techniques.By explaining the principle and using examples,we hope to help the interested reader underst and this research field and bring exciting information to the community.

A Fractional Order Fast Repetitive Control Paradigm of Vienna Rectifier for Power Quality Improvement

Due to attractive features,including high efficiency,low device stress,and ability to boost voltage,a Vienna rectifier is commonly employed as a battery charger in an electric vehicle(EV).However,the 6k±1 harmonics in the acside current of the Vienna rectifier deteriorate theTHDof the ac current,thus lowering the power factor.Therefore,the current closed-loop for suppressing 6k±1 harmonics is essential tomeet the desired total harmonic distortion(THD).Fast repetitive control(FRC)is generally adopted;however,the deviation of power grid frequency causes delay link in the six frequency fast repetitive control to become non-integer and the tracking performance to deteriorate.This paper presents the detailed parameter design and calculation of fractional order fast repetitive controller(FOFRC)for the non-integer delay link.The finite polynomial approximates the non-integer delay link through the Lagrange interpolation method.By comparing the frequency characteristics of traditional repetitive control,the effectiveness of the FOFRC strategy is verified.Finally,simulation and experiment validate the steadystate performance and harmonics suppression ability of FOFRC.

Design and Implementation of Smart Power Voltage and Frequency Synchroniser in Power Distribution System

Voltage and frequency are usually considered and assessed independently in the design and operation of electrical networks. However, these two are linked. Each and every malfunctioning electrical system has an impact on both voltage and frequency. This paper presents the opportunity for monitoring the distributed electrical energy by means of a system that monitors, controls, and provides a breakpoint based on high or low voltage and frequency tripping mechanism that avoids any damage to the load. The designed system comprised a switch mode power supply (SMPS), a direct digital synthesizer (DDS), and PIC16F876A microcontroller techniques for stable voltage and frequency outputs. Proteus design suite version 8.11 software and Benchcope SDS1102CN were used for modeling and simulation. The hardware prototype was implemented at a telecom cell site for data capturing and analysis. Test results showed that the implementation of the prototype provided stable and constant outputs of 222 V/50 Hz and 112 V/60 Hz which constituted 99% and 99.8% efficiency for voltage and frequency performance respectively. The paper also discusses different technologies that can be adopted by the system to mitigate voltage and frequency effects on customer appliances.

Controlled LED Lighting for Horticulture: A Review

As energy gradually becomes a more valuable commodity, the desire for reduced energy losses strengthens. Lighting is a critical field on this matter, as it accounts for a large percentage of the global electricity consumption and modern lighting systems are greatly more efficient than incandescent, discharge, and fluorescent lights. Previous research has proven that plants do not require the entire visible spectrum but react only to specific wavelengths, making it possible to control their growth and yield via artificial lighting. The flexibility of control of Light Emitting Diode (LED) lights allows for the combination of great energy losses reduction and controlled plant growth, achieving the improvement of two major parameters in a single action. This review paper summarizes the current research on the effect different light wavelengths have on specific plant species and discusses the applications of LED lighting for horticulture, yield storage, and disease protection.

Selection of Metaheuristic Algorithm to Design Wireless Sensor Network

The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance.The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’access network.The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness.Coverage and energy usage are mostly determined by successful sensor placement strategies.Nature-inspired algorithms are the most effective solution for short sensor lifetime.The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks(WSNs’)maximum network coverage.Moreover,it identifies quantity of installed sensor nodes for the given area.Superiority of algorithm has been identified based on value of optimized energy.The first half of the paper’s literature on nature-inspired algorithms is discussed.Later six metaheuristics algorithms(Grey wolf,Ant lion,Dragonfly,Whale,Moth flame,Sine cosine optimizer)are compared for optimal coverage of WSNs.The simulation outcomes confirm that whale opti-mization algorithm(WOA)gives optimized Energy with improved network coverage with the least number of nodes.This comparison will be helpful for researchers who will use WSNs in their applications.