A time-sharing multi-channel pulse amplitude analyzer

A conventional multi-channel pulse amplitude analyzer acquires single energy spectrum,but provides no information on its tendency with time.To address the limitation,we propose a scheme of time-sharing multichannel pulse amplitude analyzer(TSMCA).A dual-port random access memory is divided into two storage spaces,one for current energy spectrum data acquisition and another for previous energy spectrum data storage.The two tasks can be performed simultaneously,and the time-related variation tendency of energy spectrum can be obtained.A prototype system of TSMCA is designed.It performs nicely,with maximum channel number of 4096 in capacity of 2^(32)/Ch,minimal time-sharing slice of 25 ms,the differential nonlinearity of <1.5%,and the integral nonlinearity of <0.3%.

Driving Mechanism of Cotton Comber's Detaching Roller Based on Time-Sharing Unidirectional Drive

The high-speed reciprocating motion of a detaching roller limits the velocity of a cotton comber and affects the quality of comber slivers. The article has proposed a controllable time-sharing unidirectional hybrid drive mechanism after analyzing detaching roller's current numerical control drive method. The analysis focuses on the detaching roller motion required according to cotton comber's velocity and process. The double-servo motors of the mechanism consists of differential gear trains. The mechanism addresses the problem of increased servo motor power,and failure of promptly responded to the positive inversion process of mechanism driven by servo motors. A velocity calculation model of the detaching roller controllable drive mechanism will be generated by using superposition method and design of differential gear trains. The accuracy of the model will be verified using the test platform. This study has presented a reliable and practical high-speed drive mechanism and can be a reference to future studies on high-speed reciprocating motion drive.

Holistic care model of time-sharing management for severe and critical COVID-19 patients

The rapid global outbreak of coronavirus disease 2019(COVID-19)and the surge of infected patients have led to the verge of exhaustion of critical care medicine resources worldwide,especially with regard to critical care staff.A holistic care model on time-sharing management for severe and critical COVID-19 patients is proposed,which includes formulation of individualized care objectives and plans,identification of care tasks in each shift and making detailed checklist,and management of quality of care.This study was conducted in the COVID-19 treatment center of Harbin,Heilongjiang Province.The data collected from the treatment center were recorded and analyzed.From the results we can deduce that it is especially suitable for non-intensive care unit(non-ICU)nurses to adapt care management mode of ICU as soon as possible and ensure the quality and efficiency of care during the epidemic.The holistic care model on time-sharing management for severe and critical cases with COVID-19 proposed based on our daily work experiences can assist in improving the quality and efficiency of care,thus reducing the mortality rate of patients in ICU.

Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based onMulti-Scale and Multi Feature Convolution Neural Network

There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.

Jamming Assisted Covert Wireless Communication in Multi-Channel Systems

This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.

New Multi-Channel VSMFxLMS Algorithm for Vibration Reduction of Gear Systems

At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a multi-channel VSMFxLMS algorithm based on the FxLMS algorithm.This novel approach takes into account the time-varying nature of the vibration signal during gear vibration.Adaptive filter power coefficients are updated in a skip-tongue variable-step manner using momentum factors.Firstly,the paper establishes the dynamics model of the gear system and analyzes the nonlinear dynamic characteristics of the system.It then examines the vibration damping effect of the FxLMS algorithm and analyzes its performance under different gear system motion states,considering different step lengths and momentum factors.Lastly,the proposed VSMFxLMS algorithm is compared with the FxLMS algorithm,highlighting the superiority of the former.Overall,this research highlights the potential of a multi-channel VSMFxLMS algorithm in reducing vibrations in gear systems.The study optimizes the performance of gear systems while using advanced control strategies.

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis(AWE)efficiency by optimizing the mass transport mechanisms.This effect becomes even more pronounced when aiming to achieve elevated current densities.Herein,we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes.Particularly,the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec^(-1)(HER)and 49 mV dec^(-1)(OER).As anticipated,the alkaline electrolyzer(AEL)cell incorporating multi-channel porous electrodes(NP-LT30)exhibited a remarkable improvement in cell efficiency,with voltage drops(from 2.28 to 1.97 V)exceeding 300 mV under 1 A cm^(-1),compared to conventional perforated Ni plate electrodes.This enhancement mainly stemmed from the employed multi-channel porous structure,facilitating mass transport and bubble dynamics through an innovative convection mode,surpassing the traditional convection mode.Furthermore,the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm^(-2).This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

Design of Cold-Junction Compensation and Disconnection Detection Circuits of Various Thermocouples and Implementation of Multi-Channel Interfaces Using Them-A Secondary Publication

Cold-junction compensation(CJC)and disconnection detection circuit design of various thermocouples(TC)and multi-channel TC interface circuits were designed.The CJC and disconnection detection circuit consists of a CJC semiconductor device,an instrumentation amplifier(IA),two resistors,and a diode for disconnection detection.Based on the basic circuit,a multi-channel interface circuit was also implemented.The CJC was implemented using compensation semiconductor and IA,and disconnection detection was detected by using two resistors and a diode so that IA input voltage became-0.42 V.As a result of the experiment using R-type TC,the error of the designed circuit was reduced from 0.14 mV to 3μV after CJC in the temperature range of 0°C to 1400°C.In addition,it was confirmed that the output voltage of IA was saturated from 88 mV to-14.2 V when TC was disconnected from normal.The output voltage of the designed circuit was 0 V to 10 V in the temperature range of 0°C to 1400°C.The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel.The implemented multi-channel interface has a feature that can be applied equally to E,J,K,T,R,and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

Development of multi-channel observation and inversion for IP electrical sounding method

In order to improve the exploration effect of deep non-ferrous mineral resources, multi-channel observation methods for induced polarization （IP） electrical sounding data and their inversion imaging technology are studied. First of all, four multi-channel observation methods are developed based on conventional IP electrical method, namely three-electrode and four-electrode arrays of unilateral and bilateral current transmitting. Then the maximum smoothness constrained inversion method of the least squares sense for IP electrical sounding data is proposed, and the inversion software is programmed. Finally, the simulation and inversion results of geo-electrical model for the proposed observation methods are analyzed. And the comparison results show that three-electrode array of bilateral current transmitting gives the best result, but the intensity in field work is larger than others; unilateral three-electrode and four-electrode arrays give the better results. Taking detection results and convenience of field exploration work into consideration, these two methods are more suitable for practical application; bilateral observation method of four-electrode array is not suitable for the detection of the steep ore bodies.

Design of multi-channel data acquisition system based on LabVIEW and NI PXI-5105

A data acquisition system based on LabVIEW and NI PXI-5105 is presented for multi-channel data acquisition. It can realize the functions of parameter setting, data acquisition and storage, waveform display and data analysis using LabVIEW and NI-SCOPE device driver. The advantages of the system are that the setting is convenient, the operation is easy, the interface is friendly and the functions are practical. The experiment results show that the system has good stability and high reliability and is a powerful tool for multi-channel data acquisition.

A maximum-independent-set-based channel allocation algorithm for multi-channel wireless networks

A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.

基于Multi-Radio Multi-Channel传感器网络无冲突信道分配算法的研究

为降低通信冲突和信道干扰,对Mult-i Radio Mult-i Channel传感器网络无冲突信道进行研究,结果证实在网络通信半径大于3倍的网络最大功率通信半径的前提下,Sensor节点规模满足2倍网络功率级数加1的环境下,网络无冲突信道分配的信道数达到网络信道冲突图的最大值。文章通过对无冲突信道算法的运用,最终证实其可以有效地提高传感器网络的工作效率,大幅度提升网络的吞吐量。

A Novel Design of Efficient Multi-channel UART Controller Based on FPGA

In traditional universal asynchronous receiver transmitter （UART） controller, the data transmission is inefficient and the data bus utilization ratio is low. A novel design is provided to solve these problems. The architecture of the system is introduced, the flow charts of data processing as well as the implementation state machine are also presented in detail. This paper is concluded by comparing the performance of this design, which is realized on field programmable gate army （FPGA） using Verilog hardware description language （HDL）, with other traditional UART controllers.

Performance analysis of multi-channel order statistics detector for range-spread target

The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.

Receding Horizon Estimation for Linear Discrete-time Systems with Multi-channel Observation Delays

This paper investigates the receding horizon state estimation for the linear discrete-time system with multi-channel observation delays. The receding horizon estimation is designed by the reorganized observation technique and the linear unbiased estimation method. The estimation gains are developed by solving a set of Riccati equations, and a stability result about the state estimation is shown. Finally, an example is given to illustrate the efficiency of the receding horizon state estimation.

Multi-Channel Iterative FDE for Single Carrier Block Transmission over Underwater Acoustic Channels

Recently, single carrier block transmission(SCBT) has received much attention in high-rate phase-coherent underwater acoustic communication.However,minimum-mean-square-error(MMSE) linear FDE may suffer performance loss in the severely time dispersive underwater acoustic channel. To combat the channel distortion, a novel multi-channel receiver with maximum ratio combining and a low complex T/4 fractional iterative frequency domain equalization(FDE) is investigated to improve diversity gain and the bit error rate(BER) performance. The proposed method has been verified by the real data from a lake underwater acoustic communication test in November 2011. At 1.8 km, the useful data rates are around 1500 and 3000 bits/s for BPSK and QPSK respectively. The results show the improvements of system performance. Compared with MMSE FDE system, the output SNR improvement is 6.9 d B, and the BER is from 10-3 to no error bits for BPSK. The output SNR improvement is 5.3 d B, and the BER is from 1.91×10-2 to 2.2×10-4for QPSK.

A Hybrid Deep Learning Scheme for Multi-Channel Sleep Stage Classification

Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases.This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography(EEG),electrocardiogram(ECG),electromyogram(EMG),and electrooculogram(EOG).Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods.Traditional hand-crafted feature extraction methods choose features manually from raw data,which is tedious,and these features are limited in their ability to balance efficiency and accuracy.Moreover,most of the existing works on sleep staging are either single channel(a single-lead EEG may not contain enough information)or only EEG signal based which can not reveal more complicated physical features for reliable classification of various sleep stages.This study proposes an approach to combine Convolutional Neural Networks(CNNs)and Gated Recurrent Units(GRUs)that can discover hidden features from multi-biological signal data to recognize the different sleep stages efficiently.In the proposed scheme,the CNN is designed to extract concealed features from the multi-biological signals,and the GRU is employed to automatically learn the transition rules among different sleep stages.After that,the softmax layers are used to classify various sleep stages.The proposed method was tested on two publicly available databases:Sleep Heart Health Study(SHHS)and St.Vincent’s University Hospital/University College Dublin Sleep Apnoea(UCDDB).The experimental results reveal that the proposed model yields better performance compared to state-of-the-art works.Our proposed scheme will assist in building a new system to deal with multi-channel or multi-modal signal processing tasks in various applications.

A Multi-Gap Multi-Channel Gas Switch for the Linear Transformer Driver

A multi-gap and multi-channel gas switch with convexo-convex discal planet electrodes was designed and investigated. Eight gaps are formed in series by a trigger electrode, six intermediate electrodes and two high voltage electrodes with a uniform gap length of 5 ram. The self breakdown and triggered breakdown performance of the switch are reported. Both the delay time and jitter decrease with the increase in the trigger voltage, switching coefficient and the decrease in the trigger isolating resistor. The delay time of the switch is about 40 ns, and the jitter is less than 2 ns when charged with 4-85 kV and triggered by a voltage pule of -75 kV. The inductance of the switch is about 30 nH.

Automatic pickup of arrival time of channel wave based on multi-channel constraints

Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography （CT） result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multi- channel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.

Joint channel assignment and cross-layer routing protocol for multi-radio multi-channel Ad Hoc networks

To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.