一个面向短波通信的LHOG话音检测方法

噪声环境下语音检测准确率偏低是短波通话面临的公开挑战。当前已有方法应用有限,其根源在于难以可靠地在噪音环境下提取准确且高效的语音特征。针对上述问题,提出了一个面向短波通信的低秩方向梯度直方图(Low-rank Histogram of Oriented Gradient,LHOG)话音检测方法。首先,对目标音频源数据进行预处理,实现噪声环境下语音信息的可视化表征;然后,在HOG特征提取器中嵌入低秩化结构,缓解特征中的冗余信息,并降低噪声干扰,从而获得准确且高效的特征;最后,通过常用的SVM分类模型便可在噪声环境中准确快速地区分话音和噪声。测试结果表明,该方法的准确率达到了95.12%,误报率仅为0.96%,漏报率为13.14%。与现有主流方法的对比实验证明,该方法话音检测准确率高,资源占用少,能够有效提高短波通信侦控效率。

提取多场景视频关键帧的复合HOG特征聚类方法

由于直接利用帧差数据提取动态多场景视频关键帧往往会产生过多冗余帧,方向梯度直方图(HOG)特征对图像亮度、场景变化具有较好的稳定性。为此,提出了用于提取多场景视频关键帧的复合HOG特征聚类方法来提升关键帧提取效率。首先,通过提取视频帧的HOG特征引入图像信息熵构成复合特征矢量,以保持数据特征相关性。其次,根据复合特征矢量统计视频帧间差异数据确定视频分割镜头、关键帧提取个数;再次,分别考虑镜头内帧集合和完整视频帧集合,无重复地将信息熵较大的视频帧选为初始聚类中心以引导聚类算法搜索方向,并通过K均值聚类抽取视频关键帧。与传统K均值聚类方法比较后发现,所提算法冗余度降低0.003~0.015,查准率提高了0.14~0.21,聚类时间得到下降,精度和效率较优。

基于HOG图像处理的滚动轴承故障诊断方法

对于滚动轴承的智能故障诊断问题,文章提出一种基于梯度直方图(histogram of oriented gradient,HOG)图像处理的轴承故障诊断方法。首先将传感器采集到的原始时域振动信号经变分模态分解(variational mode decomposition,VMD)后得到二维图像;再利用HOG数字图像处理算法对上述图像提取特征信息;使用多维尺度分析(multi-dimensional scaling,MDS)方法对特征数据进行降维处理,得到低维空间下的故障特征数据并对故障特征数据添加标签构建数据集,该数据集被划分为训练集和测试集;然后引入遗传算法(genetic algorithm,GA)优化支持向量机(support vector machine,SVM)中的惩罚因子和核函数关键参数,用训练集进行训练得到最优故障分类模型;最后对测试集的数据进行处理,得到分类结果。对比分析结果表明,该文方法能快速提取轴承故障有效特征,提高故障诊断准确率。

基于CNN和HOG的司机分心检测

针对现有CNN网络模型只关注网络最后一层的输出而未能充分利用中间层的输出特征,而事实上中间层特征包含很多有用信息,提出一种端到端的提取多阶段中间网络层输出特征,并与HOG(Histogram of Oriented Gradient)特征融合的司机分心检测模型。模型参数量仅为3.6 M,同时采用L2权重正则化、Dropout以及批量正则化对模型性能进行提升。在两个公开的数据集State Farm Distracted Driver Detection(SFD3)和AUC Distracted Driver(AUCD2)进行了实验验证,在SFD3准确度达到99.78%,比现有论文提高约3百分点,网络参数量分别减少约95%;在AUCD2上准确度达到95.15%,比现有论文提高约2百分点,网络参数量减少约60%。

基于HOG和TSO-SVM的水电机组轴心轨迹智能识别

水电机组的轴心轨迹能够反映机组不同的运行状态,为了提高轴心轨迹的识别率,准确判断机组运行状态,本文提出方向梯度直方图(Histogram of Oriented Gradient, HOG)结合由瞬态搜索优化(Transient Search Optimization, TSO)算法优化的支持向量机(Support Vector Machine, SVM)的方法。将轴心轨迹信号经改进小波阈值方法去噪后,生成轴心轨迹图像,之后提取图像HOG特征,经主成分分析(Principal Components Analysis, PCA)降维处理后,利用TSO-SVM对降维后的特征进行分类识别。结果表明所提方法能够很好地识别不同状态的轴心轨迹,具有识别准确率高和识别速度快的特点。

Gradient coil design with enhanced shielding constraint for a cryogen-free superconducting MRI system

The relatively fragile low-temperature stability of cryogen-free superconducting magnetic resonance imaging(MRI)magnets requires the careful management of exogenous heat sources.A strongly shielded gradient magnetic field is important for the optimal operation of cryogen-free MRI systems.In this study,we present an enhanced shielding method incorporating a regionalized stray field constraining strategy.By optimizing the constraint parameters,we could develop engineering-feasible gradient coil schemes without increasing system complexity but with the stray field intensity reduced by half.In real measurement in an integrated MRI system,the developed gradient assembly demonstrated good performance and supported to output images of excellent quality.Our findings suggested that the proposed method could potentially form a useful design paradigm for cryogen-free MRI magnets.

Climate-growth relationships of Pinus tabuliformis along an altitudinal gradient on Baiyunshan Mountain,Central China

A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central China to analyze the effect of varying temperature and precipitation on growth along the gradi-ent.Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had signifi-cant negative correlations with mean and maximum tem-peratures in the current April and May and with minimum temperatures in the prior July and August,but significant positive correlations with precipitation in the current May.Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August,indicating that the prior summer temperature had a strong lag effect on the growth of P.tabuliformis that increased with altitude.The correlation with the standard-ized precipitation evapotranspiration index(SPEI)confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes.Significant altitudinal differences were also found;at 1400 m,there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September,but these correlations were not significant at 1450 m.At 1350 m,there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August,but these cor-relations were not significant at 1400 m.Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July-August at 1400 m from 2002 to 2018.The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction.These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China.

Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

HOG1基因缺失对酵母细胞锌耐受的影响

以酿酒酵母(ΔHOG1突变株和野生株BY4741)为材料,检测了酵母细胞在硫酸锌胁迫下生长、凋亡、ROS水平和线粒体膜电位的变化.结果显示,高浓度硫酸锌可抑制酵母细胞生长,引起胞内ROS水平升高和线粒体膜电位下降,进而诱导细胞发生凋亡.在3 mmol/L的硫酸锌处理组中,ΔHOG1突变株的锌耐受性和线粒体膜电位显著低于野生株BY4741,而胞内ROS水平和细胞凋亡率显著高于野生株BY4741.结果表明,HOG1 MAPK可通过影响胞内ROS水平调控酵母细胞对硫酸锌的耐受性.

Distribution law and susceptibility of geohazards across a gradient belt of the Western Sichuan Plateau

Across a gradient belt of the Western Sichuan Plateau,geohazards have seriously limited economic and social development.According to incomplete statistics,15,673 geohazards have been recorded in the study area.In order to mitigate the threat of geohazards to human engineering activities in the region,an overall understanding of the distribution pattern of geohazards and susceptibility assessment are necessary.In this paper,a gradient belt of the Western Sichuan Plateau and its zoning criteria were defined.Subsequently,on the basis of relief amplitude,distance to faults,rainfall,and human activities,three indicators of endogenic process were introduced:Bouguer gravity anomaly gradient,vertical deformation gradient,and horizontal deformation gradient.Thereafter,the distribution patterns of geohazards were investigated through mathematical statistics and ArcGIS software.By randomly selecting 10,449 hazards,a geohazard susceptibility map was generated using the Information Value(IV)model.Finally,the IV model was validated against 5224 hazards using the Area Under Curve(AUC)method.The results show that 47.6%of the geohazards were distributed in the zone of steep slope.Geohazards showed strong responses to distance to faults,human activities,and annual rainfall.The distribution of geohazards in the gradient belt of the Western Sichuan Plateau is more sensitive to vertical internal dynamics factors(such as vertical deformation gradient and Bouguer gravity anomaly gradient)without any apparent sensitivity to horizontal internal dynamics factors.The areas of high and very-high risk account for up to 32.22%,mainly distributed in the Longmenshan and Anning River faults.According to the AUC plot,the success rate of the IV model for generating the susceptibility map is 76%.This susceptibility map and geohazard distribution pattern can provide a reference for geological disaster monitoring,preparation of post-disaster emergency measures,and town planning.

Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.

Stochastic Gradient Compression for Federated Learning over Wireless Network

As a mature distributed machine learning paradigm,federated learning enables wireless edge devices to collaboratively train a shared AI-model by stochastic gradient descent(SGD).However,devices need to upload high-dimensional stochastic gradients to edge server in training,which cause severe communication bottleneck.To address this problem,we compress the communication by sparsifying and quantizing the stochastic gradients of edge devices.We first derive a closed form of the communication compression in terms of sparsification and quantization factors.Then,the convergence rate of this communicationcompressed system is analyzed and several insights are obtained.Finally,we formulate and deal with the quantization resource allocation problem for the goal of minimizing the convergence upper bound,under the constraint of multiple-access channel capacity.Simulations show that the proposed scheme outperforms the benchmarks.

Wettability Gradient-Induced Diode:MXene-Engineered Membrane for Passive-Evaporative Cooling

Thermoregulatory textiles,leveraging high-emissivity structural materials,have arisen as a promising candidate for personal cooling management;however,their advancement has been hindered by the underperformed water moisture transportation capacity,which impacts on their thermophysiological comfort.Herein,we designed a wettability-gradient-induced-diode(WGID)membrane achieving by MXene-engineered electrospun technology,which could facilitate heat dissipation and moisture-wicking transportation.As a result,the obtained WGID membrane could obtain a cooling temperature of 1.5℃ in the“dry”state,and 7.1℃ in the“wet”state,which was ascribed to its high emissivity of 96.40%in the MIR range,superior thermal conductivity of 0.3349 W m^(-1) K^(-1)(based on radiation-and conduction-controlled mechanisms),and unidirectional moisture transportation property.The proposed design offers an approach for meticulously engineering electrospun membranes with enhanced heat dissipation and moisture transportation,thereby paving the way for developing more efficient and comfortable thermoregulatory textiles in a high-humidity microenvironment.

Bioinspired Multifunctional Self-Sensing Actuated Gradient Hydrogel for Soft-Hard Robot Remote Interaction

The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. Here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO_(2) nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation(21° s^(-1)) and enhanced photothermal efficiency(increase by 3.7 ℃ s^(-1) under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca^(2+) endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity(gauge factor 3.94 within a wide strain range of 600%), fast response times(140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the Internet of Things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human–machine interactions.

Local Adaptive Gradient Variance Attack for Deep Fake Fingerprint Detection

In recent years,deep learning has been the mainstream technology for fingerprint liveness detection(FLD)tasks because of its remarkable performance.However,recent studies have shown that these deep fake fingerprint detection(DFFD)models are not resistant to attacks by adversarial examples,which are generated by the introduction of subtle perturbations in the fingerprint image,allowing the model to make fake judgments.Most of the existing adversarial example generation methods are based on gradient optimization,which is easy to fall into local optimal,resulting in poor transferability of adversarial attacks.In addition,the perturbation added to the blank area of the fingerprint image is easily perceived by the human eye,leading to poor visual quality.In response to the above challenges,this paper proposes a novel adversarial attack method based on local adaptive gradient variance for DFFD.The ridge texture area within the fingerprint image has been identified and designated as the region for perturbation generation.Subsequently,the images are fed into the targeted white-box model,and the gradient direction is optimized to compute gradient variance.Additionally,an adaptive parameter search method is proposed using stochastic gradient ascent to explore the parameter values during adversarial example generation,aiming to maximize adversarial attack performance.Experimental results on two publicly available fingerprint datasets show that ourmethod achieves higher attack transferability and robustness than existing methods,and the perturbation is harder to perceive.

Strong evidence for latitudinal diversity gradient in mosses across the world

Species richness generally decreases with increasing latitude,a biodiversity gradient that has long been considered as one of the few laws in ecology.This latitudinal diversity gradient has been observed in many major groups of organisms.In plants,the latitudinal diversity gradient has been observed in vascular plants,angiosperms,ferns,and liverworts.However,a conspicuous latitudinal diversity gradient in mosses at a global or continental scale has not been observed until now.Here,we analyze a comprehensive data set including moss species in each band of 20° in latitude worldwide.Our results show that moss species richness decreases strongly with increasing latitude,regardless of whether the globe is considered as a whole or different longitudinal segments(e.g.,Old World versus New World) are considered separately.This result holds when variation in area size among latitudinal bands is taken into account.Pearson's correlation coefficient between latitude and species richness is-0.99 for both the Northern and Southern Hemispheres.Because bryophytes are an extant lineage of early land plants and because mosses not only include most of extant species of bryophytes but also are important constituents of most terrestrial ecosystems,understanding geographic patterns of mosses is particularly important The finding of our study fills a critical knowledge gap.

基于BP神经网络和HOG特征的茶小绿叶蝉识别

为解决茶小绿叶蝉在复杂环境中快速识别的问题,提出了一种基于BP神经网络和HOG特征提取算法的茶叶病虫害识别方法。首先对采集的茶叶病虫害图片进行数据增强,用来扩充样本数量,并将样本尺寸大小统一到256×256,以方便网络模型训练。然后使用HOG算法提取图片的局部边缘特征,以减少光照变化造成的影响和降低噪声。最后将提取的特征数据输入到BP神经网络进行训练,并使用随机梯度下降法(SGD)减少模型训练的时间。实验结果表明,基于BP和HOG的茶小绿叶蝉识别方法,准确率为0.94,所提出的模型具有较高的识别能力和鲁棒性,可以为茶叶病虫害智能诊断提供参考。

Changes of growth-climate relationships of Smith fir forests along an altitudinal gradient

Temporal changes in the relationship between tree growth and climate have been observed in numerous forests across the world.The patterns and the possible regu-lators(e.g.,forest community structure)of such changes are,however,not well understood.A vegetation survey and analyses of growth-climate relationships for Abies georgei var.Smithii(Smith fir)forests were carried along an altitudi-nal gradient from 3600 to 4200 m on Meili Snow Mountain,southeastern Tibetan Plateau.The results showed that the associations between growth and temperature have declined since the 1970s over the whole transect,while response to standardized precipitation-evapotranspiration indices(SPEI)strengthened in the mid-and lower-transect.Comparison between growth and vegetation data showed that tree growth was more sensitive to drought in stands with higher species richness and greater shrub cover.Drought stress on growth may be increased by heavy competition from shrub and herb layers.These results show the non-stationary nature of tree growth-climate associations and the linkage to for-est community structures.Vegetation components should be considered in future modeling and forecasting of forest dynamics in relation to climate changes.

Full waveform inversion based on hybrid gradient

The low-wavenumber components in the gradient of full waveform inversion(FWI)play a vital role in the stability of the inversion.However,when FWI is implemented in some high frequencies and current models are not far away from the real velocity model,an excessive number of low-wavenumber components in the gradient will also reduce the convergence rate and inversion accuracy.To solve this problem,this paper firstly derives a formula of scattering angle weighted gradient in FWI,then proposes a hybrid gradient.The hybrid gradient combines the conventional gradient of FWI with the scattering angle weighted gradient in each inversion frequency band based on an empirical formula derived herein.Using weighted hybrid mode,we can retain some low-wavenumber components in the initial lowfrequency inversion to ensure the stability of the inversion,and use more high-wavenumber components in the high-frequency inversion to improve the convergence rate.The results of synthetic data experiment demonstrate that compared to the conventional FWI,the FWI based on the proposed hybrid gradient can effectively reduce the low-wavenumber components in the gradient under the premise of ensuring inversion stability.It also greatly enhances the convergence rate and inversion accuracy,especially in the deep part of the model.And the field marine seismic data experiment also illustrates that the FWI based on hybrid gradient(HGFWI)has good stability and adaptability.

Simultaneous purification of minor components in natural products using twin-column recycling chromatography with a step solvent gradient

The isolation of minor components from complex natural product matrices presents a significant challenge in the field of purification science due to their low concentrations and the presence of structurally similar compounds.This study introduces an optimized twin-column recycling chromatography method for the efficient and simultaneous purification of these elusive constituents.By introducing water at a small flowing rate between the twin columns,a step solvent gradient is created,by which the leading edge of concentration band would migrate at a slower rate than the trailing edge as it flowing from the upstream to downstream column.Hence,the band broadening is counterbalanced,resulting in an enrichment effect for those minor components in separation process.Herein,two target substances,which showed similar peak position in high performance liquid chromatography(HPLC)and did not exceed 1.8%in crude paclitaxel were selected as target compounds for separation.By using the twin-column recycling chromatography with a step solvent gradient,a successful purification was achieved in getting the two with the purity almost 100%.We suggest this method is suitable for the separation of most components in natural produces,which shows higher precision and recovery rate compared with the common lab-operated separation ways for natural products(thin-layer chromatography and prep-HPLC).