煤矿井下钻孔裂隙识别技术

为研究采区煤岩体中裂隙、断裂、破碎带等结构面的自动检测技术,解决现有人工智能技术中迭代次数大、检测框准确度低等问题,采用YOLOv5算法融合注意力机制、损失函数、多尺度检测的方法,对煤矿巷道上顶板5种不同地质钻孔进行裂隙检测试验。结果表明：将注意力机制SENet引入YOLOv5模型框架,避免了图像背景区域与裂隙区域相似度较高问题;采用有效交并比损失函数代替完全交并比损失函数,使得预测框能够更加有效拟合真实目标框;对YOLOv5模型增添3种不同尺寸的锚定框并添加160×160特征层,实现检测更小的目标。该方法与SSD、YOLOv5等检测算法在同样条件下相比,其检测精度分别提升了18.9%,2.1%,召回率提升了39.5%,1.6%,平均精度提升了28.1%,1.0%。改进后的模型将三尺度检测变为四尺度检测,提升了算法的多尺度目标检测性能,能够对钻孔裂隙进行高精度检测,满足钻孔裂隙实时检测需求。     

基于改进YOLOv5的拥挤行人检测算法

针对密集场景下行人检测的目标重叠和尺寸偏小等问题,提出了基于改进YOLOv5的拥挤行人检测算法。在主干网络中嵌入坐标注意力机制,提高模型对目标的精准定位能力;在原算法三尺度检测的基础上增加浅层检测尺度,增强小尺寸目标的检测效果;将部分普通卷积替换为深度可分离卷积,在不影响模型精度的前提下减少模型的计算量和参数量;优化边界框回归损失函数,提升模型精度和加快收敛速度。实验结果表明,与原始的YOLOv5算法相比,改进后YOLOv5算法的平均精度均值提升了7.4个百分点,检测速度达到了56.1帧/s,可以满足密集场景下拥挤行人的实时检测需求。     

基于YOLOv5的遥感图像目标检测

目标检测是遥感图像处理领域的一项重要技术,遥感图像目标种类繁多且存在目标物体难以被检测.提出把YOLOv5算法应用到遥感图像目标检测的方法,首先选择YOLOv5x来构建网络模型,再通过Mosaic数据增强对样本集进行预处理和自适应锚框筛选方法确定锚框大小,然后切片卷积操作得到原始特征图,将原始特征图送入主干网络进行特征融合得到最优权重,最后采用GIOU Loss做边界框的损失函数和非极大值抑制目标框的筛选,对遥感图像进行目标检测.在公开的10类地理空间物体(NWPU-VHR 10)数据集进行了检测实验,以评估所提出模型的目标检测性能.对比实验表明,本文的模型mAP达到了0.9239,与使用相同数据集的模型中的最佳结果进行比较,mAP提升了1.78％,该方法可以提高遥感图像目标检测精度.     

一种改进YOLOv3的手势识别算法

为了解决YOLOv3算法在手势识别中存在识别精度低及易受光照条件影响的问题,提出了一种改进的YOLOv3手势识别算法。首先,在原来3个检测尺度上新增加1个更小的检测尺度,提高对小目标的检测能力;其次,以DIoU代替原来的均方差损失函数作为坐标误差损失函数,用改进后的Focal损失函数作为边界框置信度损失函数,目标分类损失函数以交叉熵作为损失函数。结果表明,将改进的YOLOv3手势识别算法用于手势检测中,mAP指标达到90.38%,较改进前提升了6.62%,FPS也提升了近2倍。采用改进的YOLOv3方法训练得到的新模型,识别手势精度更高,检测速度更快,整体识别效率大幅提升,平衡了简单样本和困难样本的损失权重,有效提高了模型的训练质量和泛化能力。     

改进YOLOv5的光伏组件热斑及遮挡物检测

针对光伏组件热斑若未及时发现处理,会严重影响光伏组件及阵列正常运行的问题,为了有效检测光伏阵列热斑,提出一种基于YOLOv5框架的深度学习热斑检测方法.首先,采用像素加权平均法融合红外和可见光图像作为检测对象,实现同时对光伏组件热斑和遮挡物的检测,并初步分析热斑成因.其次,改进模型框架,在轻量级网络MobileNetV3-large的基础上,融合坐标注意力机制,设计更轻量、更高效的MobileNetCA作为特征提取网络.然后,针对训练中正负样本数量极不平衡的情况,更换损失函数为变焦距损失函数,达到训练中突出正例的效果.同时,改进模型anchor box目标框生成算法,使生成的目标框与实际标注框更一致.实验结果表明,改进后的模型mAP为88.9%,较原YOLOv5s模型提升了3.8%,且模型参数量仅为原模型的48.6%.     

改进后的YOLOv5用于跌倒行为检测

随着全球人口老龄化不断加剧，由于跌倒致死的比例也随之增加，及时发现跌倒行为对降低死亡风险至关重要。针对现有跌倒检测算法在实际应用场景中出现漏检、准确率低等问题，本文将改进后的YOLOv5目标检测方法用于跌倒行为检测。具体改进措施：将YOLOv5的边界框损失函数GIoU更换为α-IoU；引入卷积块注意力机制模块（CBAM），使网络可以更专注地学习跌倒特征；在特征融合层引入加权双向特征金字塔网络结构（BiFPN）以充分利用不同尺度的特征，从而提高检测精度。实验结果表明，改进的YOLOv5模型对跌倒行为的检测精度mAP达到了98.8%，比改进前提高了4%，满足对实际应用场景下跌倒检测的要求。     

基于改进YOLOv5的铝型材表面缺陷检测方法

针对铝型材表面缺陷不同类别尺寸差别较大,导致检测效果较差的情况,本文提出一种基于改进YOLOv5的铝型材表面缺陷检测算法。首先,在网络中嵌入CA(coordinate attention)注意力机制模块,使网络更好地抑制图像中无效样本的干扰,更多聚焦于有用信息;其次,在原有检测层上增加一个小目标检测层,获取和传递更为丰富且更具判别性的小目标特征,以解决对小目标缺陷检测精度低的问题,提高整体检测精度;最后,引入SIoU损失函数,用边界框回归之间的向量角度来重新定义损失函数,在有效减少总自由度损失的同时提高推理精度。将改进算法应用到天池铝型材数据集中进行验证,实验结果表明：该模型能有效识别铝型材表面不同种类的缺陷,较原YOLOv5算法mAP提高11.4个百分点,检测速度达到66.4 frame/s,能够满足目前铝型材工厂生产现场缺陷检测要求。     

基于改进YOLOv5的电动摩托车驾驶人头盔检测方法

随着经济的快速发展及低碳环保出行方式的普及,电动摩托车投入量逐年上升,但由此带来的安全隐患也随之上升.针对传统的人工检查骑手是否规范佩戴安全帽耗时、耗力且存在漏检等问题,提出一种基于改进YOLOv5的头盔检测算法.首先,针对摩托车头盔大小尺寸不一的问题,使用K-means++算法重新设计初始锚框,增加了网络收敛速度;其次引入坐标注意力机制(Coordinate Attention),增强网络学习特征的表达能力;最后,引入α-IoU损失函数提高目标检测精度.实验表明,改进的YOLOv5模型的mAP达到98.83%,比YOLOv5的平均精度提升了5.29%,符合在道路复杂环境下对电动摩托车驾驶人头盔检测的要求.     

采用卷积神经网络的烟火智能识别算法

相较于传统烟火、烟雾检测,基于卷积神经网络算法的烟火检测具有更高检测精度和效率,提出基于改进YOLOv3算法的烟火识别方法,应用高斯参数设计损失函数并建立YOLOv3边界框模型,实现边界框置信度计算以减少负样本.为充分利用图像局部特征信息,对网络结构进行改进,以实际烟火现场图片为待检对象,完成烟火识别过程计算.结果表明,与基础YOLOv3对比,本研究提出的改进YOLOv3算法平均精度提高5.5%,该方法有助于提升智能烟火预警、人员救助和险情跟踪作业水平,最终提升事故灾害应急和管理能力.     

基于轻量化卷积神经网络的毛巾织物瑕疵检测方法

针对毛巾织物瑕疵检测中存在的小目标瑕疵漏检率高、形变尺度大的瑕疵检测精度低以及模型检测效率不理想等问题,提出一种基于YOLOv4网络的轻量化毛巾织物瑕疵检测方法。采用轻量级网络Ghost Net重构主干特征提取网络,以降低模型运算量,提升检测速度;在深层特征提取网络中引入结合空洞卷积和SoftP ool的DS-CBAM模块,扩大感受野的同时保证特征图分辨率并提高模型对毛巾织物瑕疵特征的提取能力;根据各类毛巾织物瑕疵正负样本不平衡的数据特点,引入难易样本聚焦参数和正负样本平衡参数对损失函数进行优化,降低样本失衡对检测性能的影响;采用改进度量距离的K-means算法自适应生成适合毛巾织物瑕疵尺寸的先验框,提高先验框和毛巾织物瑕疵目标的匹配度。研究结果表明:改进后的模型在毛巾织物瑕疵数据集上的检测精度要优于原YOLOv4和其他主流检测算法,综合类别平均精度达到92.14%,检测速度达到49.98帧/s,分别比原模型提高了5.31%、22.83%,有效平衡了检测精度和检测速度之间的关系。     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Lower Paleozoic oil relationships within Williston Basin, Canada

The Williston Basin is a significant petroleum province, containing oil production zones that include the Middle Cambrian to Lower Ordovician, Upper Ordovician, Middle Devonian, Upper Devonian and Mississippian and within the Jurassic and Cretaceous. The oils of the Williston Basin exhibit a wide range of geochemical characteristics defined as "oil families", although the geochemical signature of the Cambrian Deadwood Formation and Lower Ordovician Winnipeg reservoired oils does not match any "oil family". Despite their close stratigraphic proximity, it is evident that the oils of the Lower Palaeozoic within the Williston Basin are distinct. This suggests the presence of a new "oil family" within the Williston Basin. Diagnostic geochemical signatures occur in the gasoline range chromatograms, within saturate fraction gas chromatograms and biomarker fingerprints. However, some of the established criteria and cross-plots that are currently used to segregate oils into distinct genetic families within the basin do not always meet with success, particularly when applied to the Lower Palaeozoic oils of the Deadwood and Winnipeg Formation.     

An Analysis of Catherine＇s Character——Wuthering Heights

Wuthering Heights, Emily Bronte＇s only novel, was published in December of 1847 under the pseudonym Ellis Bell. The book did not gain immediate success, but it is now thought one of the finest novels in the English language. Catherine is the key character of this masterpiece, because everybody and everything center on her though she had a short life. We can understand this masterpiece better if we know Catherine well.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

Design and analysis of generic LBS application developing platform

Location based services is promising due to its novel working style and contents.A software platform is proposed to provide application programs of typical location based services and support new applications developing efficiently. The analysis shows that this scheme is easy implemented, low cost and adapt to all kinds of mobile nework system.     

橡胶颗粒沥青混合料低温抗裂性试验研究

以AC-13级配为基础,将橡胶颗粒代替部分集料掺入混合料中,以低温弯曲试验为评价方法对不同橡胶颗粒掺量下沥青混合料的低温抗裂性进行研究,并引入应变能密度值对混合料的低温抗裂性进行综合评价.试验结果表明:橡胶颗粒沥青混合料试件的破坏微应变均超过2 300,满足冬寒区的技术指标;无论是否掺加橡胶颗粒,随着温度的下降,沥青混合料破坏时的最大弯拉强度增大,弯拉应变降低,劲度模量增大;弯曲应变能密度在胶粒掺量为1%左右时具有较大的弯曲应变能密度值,此时橡胶颗粒沥青混合料具有较好的低温抗裂性.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

Quantitative trait loci （QTLs） for quality traits related to protein and starch in wheat

Quality traits in wheat （Triticum aestirum L.） were studied by quantitative trait locus （QTL） analysis in a recombinant inbred line （RIL） population, a set of 131 lines derived from Chuan 35050 × Shannong 483 cross （ChSh）. Grains from RILs were assayed for 21 quality traits related to protein and starch. A total of 35 putative QTLs for 19 traits with a single QTL explaining 7.99-40.52% of phenotypic variations were detected on 10 chromosomes, 1D, 2A, 2D, 3B, 3D, 5A, 6A, 6B, 6D, and 7B. The additive effects of 30 QTLs were positive, contributed by Chuan 35050, the remaining 5 QTLs were negative with the additive effect contributed by Shannong 483. For protein traits, 15 QTLs were obtained and most of them were located on chromosomes 1 D, 3B and 6D, while 20 QTLs for starch traits were detected and most of them were located on chromosomes 3D, 6B and 7B. Only 7 QTLs for protein and starch traits were co-located in three regions on chromosomes 1D, 2A and 2D. These protein and starch trait QTLs showed a distinct distribution pattern in certain regions and chromosomes. Twenty-two QTLs were clustered in 6 regions of 5 chromosomes. Two QTL clusters for protein traits were located on chromosomes 1D and 3B, respectively, three clusters for starch traits on chromosomes 3D, 6B and 7B, and one cluster including protein and starch traits on chromosome 1D.     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.