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.

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.

电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响

背景:创伤性脑损伤是由头部受到撞击、打击而导致大脑正常功能被破坏的疾病,目前需要寻找有效治疗方式和客观指标,帮助医生判别损伤状况及恢复患者脑功能。目的:探究电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响。方法:将40只6周龄SPF级雄性SD大鼠随机分为假手术组、模型组、电针组、低频经颅超声刺激组和联合组(n=8),后4组采用Feeney自由落体法造模,假手术组只开骨窗而不打击。各干预组均于造模后1 d开始实施干预,电针组进行电针干预,低频经颅超声刺激组进行低频经颅超声刺激干预,联合组进行两者联合干预,共干预7 d。造模后8 h,用改良神经功能缺损评分评定大鼠神经功能缺损情况;干预7 d后观察大鼠Y迷宫自发轮流行为百分比,而后采集脑电信号,利用快速傅里叶变换分解出α、β、θ和δ波段,计算各频段振荡幅值、能量占比百分比以及Lempel-Ziv复杂度、样本熵。结果与结论:①造模后8 h,模型组、电针组、低频经颅超声刺激组和联合组的改良神经功能缺损评分显著高于假手术组(P<0.05);②造模后第7天,模型组的α波、δ波频带振荡幅值、δ波能量占比百分比显著高于假手术组(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Ziv复杂度、样本熵显著低于假手术组(P<0.05);③与模型组比较,联合组的α波、δ波频带振荡幅值显著下降(P<0.05),电针组、低频经颅超声刺激组、联合组的α波、β波频带能量占比百分比显著升高(P<0.05),δ波能量占比百分比显著下降(P<0.05);④与电针组和低频经颅超声刺激组相比,联合组的δ波能量占比百分比显著降低(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Zi复杂度、样本熵显著升高(P<0.05);⑤结果显示,创伤性脑损伤大鼠出现脑电信号异常,而电针联合低频经颅超声刺激干预后可以改善大鼠脑电信号的异常情况,提示脑电频域特征和非线性特征可用来评估创伤性脑损伤情况。

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。

The modulation of brain functional connectivity with manual acupuncture in healthy subjects:An electroencephalograph case study

Manual acupuncture is widely used for pain relief and stress control.Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions.To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level,we acupuncture at ST36 of a right leg to obtain electroencephalograph（EEG） signals.By coherence estimation,we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states.The resulting synchronization matrices are converted into functional networks by applying a threshold,and the clustering coefficients and path lengths are computed as a function of threshold.The results show that acupuncture can increase functional connections and synchronizations between different brain areas.For a wide range of thresholds,the clustering coefficient during acupuncture and postacupuncture period is higher than that during the pre-acupuncture control period,whereas the characteristic path length is shorter.We provide further support for the presence of ＂small-world＂ network characteristics in functional networks by using acupuncture.These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture,which could contribute to the understanding of the effects of acupuncture on the entire brain,as well as the neurophysiological mechanisms underlying acupuncture.Moreover,the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

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.

Modulation of electroencephalograph activity by manual acupuncture stimulation in healthy subjects:An autoregressive spectral analysis

To investigate whether and how manual acupuncture（MA） modulates brain activities,we design an experiment where acupuncture at acupoint ST36 of the right leg is used to obtain electroencephalograph（EEG） signals in healthy subjects.We adopt the autoregressive（AR） Burg method to estimate the power spectrum of EEG signals and analyze the relative powers in delta（0 Hz-4 Hz）,theta（4 Hz-8 Hz）,alpha（8 Hz-13 Hz）,and beta（13 Hz-30 Hz） bands.Our results show that MA at ST36 can significantly increase the EEG slow wave relative power（delta band） and reduce the fast wave relative powers（alpha and beta bands）,while there are no statistical differences in theta band relative power between different acupuncture states.In order to quantify the ratio of slow to fast wave EEG activity,we compute the power ratio index.It is found that the MA can significantly increase the power ratio index,especially in frontal and central lobes.All the results highlight the modulation of brain activities with MA and may provide potential help for the clinical use of acupuncture.The proposed quantitative method of acupuncture signals may be further used to make MA more standardized.

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.

Characteristics analysis of acupuncture electroencephalograph based on mutual information Lempel-Ziv complexity

As a convenient approach to the characterization of cerebral cortex electrical information, electroencephalograph （EEG） has potential clinical application in monitoring the acupuncture effects. In this paper, a method composed of the mutual information method and Lempel-Ziv complexity method （MILZC） is proposed to investigate the effects of acupuncture on the complexity of information exchanges between different brain regions based on EEGs. In the experiments, eight subjects are manually acupunctured at ＇Zusanli＇ acupuncture point （ST-36） with different frequencies （i.e., 50, 100, 150, and 200 times/min） and the EEGs are recorded simultaneously. First, MILZC values are compared in general. Then average brain connections are used to quantify the effectiveness of acupuncture under the above four frequencies. Finally, significance index P values are used to study the spatiality of the acupuncture effect on the brain. Three main findings are obtained： （i） MILZC values increase during the acupuncture; （ii） manual acupunctures （MAs） with 100 times/rain and 150 times/min are more effective than with 50 times/min and 200 times/rain; （iii） contralateral hemisphere activation is more prominent than ipsilateral hemisphere＇s. All these findings suggest that acupuncture contributes to the increase of brain information exchange complexity and the MILZC method can successfully describe these changes.

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%.

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.