A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

In a cloud environment,consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost.On the other hand,Cloud Service Providers(CSPs)seek to maximize their profits by attracting and serving more consumers based on their resource capabilities.The literature has discussed the problem by considering either consumers’needs or CSPs’capabilities.A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task scheduling in a more efficient way.The paper proposes a model that adopts a Multi-Criteria Decision Making(MCDM)method,called Analytic Hierarchy Process(AHP),to acquire the information of consumers’preferences and service providers’capabilities to prioritize both tasks and resources.The model also provides a matching technique to assign each task to the best resource of a CSP while preserves the fairness of scheduling more tasks for resources with higher capabilities.Our experimental results prove the feasibility of the proposed model for prioritizing hundreds of tasks/services and CSPs based on a defined set of criteria,and matching each set of tasks/services to the best CSPS.

Analysis of Two Bradyrhizobium japonicum Strains with Different Symbiotic Matching for Nodulation by Primary Proteomic

The symbiotic matching for nodulation of Bradyrhizobium japonicum strains is a synergy of multi-proteins and plays a key role in symbiotic nitrogen fixation in nature. Studies on mechanism of symbiotic matching are significant in both theory and practice. In this paper, B. japonicum USDA110-A with high symbiotic matching with high-oil content soybean cultivar Suinong 20 and B. japonicum 2178 with low symbiotic matching were selected for proteomic to reveal mechanism of different symbiotic nodulation. The results showed that the amount and categories of proteins identified in this test were different when the two strains were treated by symbiotic nodulation. There were 10 up-regulated proteins and 5 down-regulated proteins with significant difference for B. japonicum USDA110-A. Proteins associated with nodulation and metabolism of energy and material, which were propitious to symbiotic nodulation, were all up-regulated, such as PHDPS synthase, metal-dependent phosphohydrolase, glycosyl transferase family. In contrast, only 5 up-regulated and 7 down-regulated differential proteins were detected in B. japonicum 2178. Molecular chaperones and defensive proteins, which influence the folding of nascent polypeptide chains and the active of azotase were down-regulated. To a certain extent, the different responses of B. japonicum to daidzein were one of the most important reasons that cause varieties in symbiotic matching ability.

Wavelet estimation by matching well-log,VSP,and surfaceseismic data

In this paper,we present a method of wavelet estimation by matching well-log, VSP,and surface-seismic data.It＇s based on a statistical model in which both input and output are contaminated with additive random noise.A coherency matching technique is used to estimate the wavelet.Measurements of goodness-of-fit and accuracy provide tools for quality control.A practical example suggests that our method is robust and stable.The matching and estimation of the wavelet is reliable within the seismic bandwidth.This method needs no assumption on the wavelet amplitude and phase and the main advantage of the method is its ability to determine phase.

An effective method for laboratory acoustic emission detection and location using template matching

In this paper, a template matching and location method, which has been rapidly adopted in microseismic research in recent years, is applied to laboratory acoustic emission(AE) monitoring. First, we used traditional methods to detect P-wave first motions and locate AE hypocenters in three dimensions. In addition, we selected events located with sufficient accuracy(normally corresponding AE events of relatively larger energy, showing clear P-wave first motion and a higher signal-to-noise ratio in most channels) as template events. Then, the template events were used to scan and match other poorly located events in triggered event records or weak events in continuous records. Through crosscorrelation of the multi-channel waveforms between the template and the event to be detected, the weak signal was detected and located using a grid-searching algorithm(with the grid centered at the template hypocenter). In order to examine the performance of the approach, we calibrated the proposed method using experimental data of different rocks and different types of experiments. The results show that the proposed method can significantly improve the detection capability and location accuracy, and can be applied to various laboratory and in situ experiments, which use multi-channel AE monitoring with waveforms recorded in either triggering or continuous mode.

Dual Image Reversible Data Hiding by Modifying Least Significant-Bit Matching Revisited Rules

The concept of dual image reversible data hiding（DIRDH） is the technique that can produce two camouflage images after embedding secret data into one original image.Moreover,not only can the secret data be extracted from two camouflage images but also the original image can be recovered.To achieve high image quality,Lu et al.＇s method applied least-significant-bit（LSB） matching revisited to DIRDH.In order to further improve the image quality,the proposed method modifies LSB matching revisited rules and applies them to DIRDH.According to the experimental results,the image quality of the proposed method is better than that of Lu et al.＇s method.

Up-Sampled Cross-Correlation Based Object Tracking & Vibration Measurement in Agriculture Tractor System

This research introduces a challenge in integrating and cleaning the data,which is a crucial task in object matching.While the object is detected and then measured,the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage,abnormal stopping,and disaster.Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement.To solve all these problems,this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to a predetermined portion of the image.A novel white color sticker of the known dimensions marked with a color dot is pasted on the surface of an object for the best result in the template matching using the Improved Up-Sampled Cross-Correlation(UCC)algorithm.The vibration measurement is calculated using the Finite-Difference Algorithm(FDA),a machine vision systemfitted with a macro lens sensor that is capable of capturing the image at a closer range,which does not affect the quality of displacement measurement from the video frames.Thefield test was conducted on the TAFE(Tractors and Farm Equipment Limited)tractor parts,and the percentage of error was recorded between 30%and 50%at very low vibration values close to zero,whereas it was recorded between 5%and 10%error in most high-accelerations,the essential range for vibration analysis.Finally,the suggested system is more suitable for measuring the vibration of stationary machinery having low frequency ranges.The use of a macro lens enables to capture of image frames at very close-ups.A 30%to 50%error percentage has been reported when the vibration amplitude is very small.Therefore,this study is not suitable for Nano vibration analysis.

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

利用匹配滤波的调频连续波激光测距技术研究

基于差频解算的调频连续波激光测距技术存在测量距离短、易受噪声干扰、受非线性调频影响大的问题。为了在相同机制条件下解决此问题,提出了基于匹配滤波的调频连续波激光测距方法,改进相干探测光路,加入信号反转单元和信号共轭单元,将混频器换成卷积器,同时满足系统响应与发射波形匹配,并进行了相关仿真实验。结果表明,相比差频解算方法,匹配滤波方法可实现两倍于差频解算方法的测距范围,信噪比提高了9.5 dB,在非线性调频误差为19.8 MHz、198 MHz和396 MHz条件下均能得到较高分辨率的距离谱,表现出较好的抵抗非线性调频的能力。此研究可为该领域的科研工作者提供技术指导和新的思路。

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

Mapping croplands,including fallow areas,are an important measure to determine the quantity of food that is produced,where they are produced,and when they are produced(e.g.seasonality).Furthermore,croplands are known as water guzzlers by consuming anywhere between 70%and 90%of all human water use globally.Given these facts and the increase in global population to nearly 10 billion by the year 2050,the need for routine,rapid,and automated cropland mapping year-after-year and/or season-after-season is of great importance.The overarching goal of this study was to generate standard and routine cropland products,year-after-year,over very large areas through the use of two novel methods:(a)quantitative spectral matching techniques(QSMTs)applied at continental level and(b)rule-based Automated Cropland Classification Algorithm(ACCA)with the ability to hind-cast,now-cast,and future-cast.Australia was chosen for the study given its extensive croplands,rich history of agriculture,and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing.This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer(MODIS)250-m normalized difference vegetation index 16-day composite time-series data for 16 years:2000 through 2015.The products consisted of:(1)cropland extent/areas versus cropland fallow areas,(2)irrigated versus rainfed croplands,and(3)cropping intensities:single,double,and continuous cropping.An accurate reference cropland product(RCP)for the year 2014(RCP2014)produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015.A comparison between the ACCA-derived cropland products(ACPs)for the year 2014(ACP2014)versus RCP2014 provided an overall agreement of 89.4%(kappa=0.814)with six classes:(a)producer’s accuracies varying between 72%and 90%and(b)user’s accuracies varying between 79%and 90%.ACPs for the individual years 2000–2013 and 2015(ACP2000–ACP2013,ACP2015)showed very strong similarities with several other studies.The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015,thus highlighting the value of the study in food security analysis.

A Configurable Circuit for Cross-Correlation in Real-Time Image Matching

Cross-correlation （CC） is the most time-consuming in the implementation of image matching algorithms based on the correlation method. Therefore, how to calculate CC fast is crucial to real-time image matching. This work reveals that the single cascading multiply-accumulate （CAMAC） and concurrent multiply-accumulate （COMAC） architectures which have been widely used in the past, actually, do not necessarily bring about a satisfactory time performance for CC. To obtain better time performance and higher resource efficiency, this paper proposes a configurable circuit involving the advantages of CAMAC and COMAC for a large amount of multiply-accumulate （MAC） operations of CC in exhaustive search. The proposed circuit works in an array manner and can better adapt to changing size image matching in real-time processing. Experimental results demonstrate that this novel circuit which involves the two structures can complete vast MAC calculations at a very high speed. Compared with existing related work, it improves the computation density further and is more flexible to use.

利用自我重复取样匹配技术组建生命表:以梨小食心虫为例

【目的】针对一些昆虫在进行生命表研究时由于个体从出生到死亡的发育、存活和繁殖数据无法连续记录或难以记录的问题,本研究旨在引入一种适宜该类昆虫的生命表组建技术,并证明该技术的可靠性。【方法】将24个以传统方式组建的昆虫连续记录生命表拆分为未成熟期与成虫期生命表,再利用自我重复取样匹配技术重新组建新的完整生命表,与原始生命表的主要种群参数进行比较与验证。利用该技术重新组建包含滞育期的梨小食心虫Grapholita molesta生命表,并借助模拟软件预测越冬种群增长趋势,将预测的种群数据与田间取样数据进行对比。【结果】24个种群基于0.5百分位净增殖率(R_(0))和周限增长率(λ)采用自我重复取样匹配构建的生命表的种群参数与原始生命表一致。梨小食心虫自我重复取样匹配生命表无滞育期与含180 d滞育期的生命表周限增长率(λ)、内禀增长率(r)与平均世代周期(T)有显著差异,但净增殖率(R_(0))与平均繁殖率(F)无显著差异。进行种群增长预测时,忽略滞育期会高估田间种群的增长潜力,呈现不现实的快速增长,而包含180 d滞育期的同时降低繁殖率并增加越冬期幼虫的死亡率的生命表,可得到更接近田间观察的实际种群结构。【结论】本研究展示了分别独立收集未成熟期和成虫期数据,利用两性生命表软件经100000次自我重复取样和匹配,进而组建完整生命表的技术。借助年龄-龄期两性生命表理论的计算机模拟可以预测害虫种群增长,有助于确定防治的最佳时期和制定有效的害虫管理方案,以促进农业可持续发展。

武汉青山长江公路大桥宽幅钢箱梁悬臂拼装横向线形匹配技术

武汉青山长江公路大桥主桥为主跨938 m的双塔双索面全飘浮体系斜拉桥,主跨整体式钢箱梁高4.5 m、全宽48 m,采用500 t架梁吊机分节段悬臂拼装架设。钢箱梁悬臂拼装时,架梁吊机站位节段、待架节段由于荷载及约束不同,横截面变形呈现出不同的趋势,线形匹配难度大。为解决该问题,主跨钢箱梁悬臂拼装时选择上、下游分体式架梁吊机,减少架梁吊机自重;经比选选择横桥向27.7 m间距的架梁吊机站位,减小了架梁吊机荷载对横向线形匹配的影响;通过设置顶压装置(由顶压牛腿、支承底座组成),在架梁吊机站位节段、待架节段钢箱梁边腹板处施加1500 kN顶压力,配合少量马板,一次加载完成对接口竖向变形匹配调整。施工后,钢箱梁横向线形匹配精度均满足要求。

60例不典型肝血管瘤患者声速匹配技术及剪切波弹性成像表现及其与肝细胞癌的鉴别

目的分析肝血管瘤患者声速匹配技术及剪切波弹性成像表现及其与肝细胞癌的鉴别。方法2019年7月—2020年7月唐山市第三医院收治的经CT确诊的60例肝血管瘤患者,另外选择经病理穿刺确诊的肝细胞癌患者40例,将其作为肝血管瘤组(n=60)和肝癌组(n=40)。比较两组声速匹配技术及剪切波弹性成像表现,采用受试者工作特征曲线(ROC)分析声速匹配技术及剪切波弹性成像鉴别肝血管瘤与肝细胞癌的价值。结果肝血管瘤组声速匹配值、弹性模量值、剪切波速度最大值、剪切波速度平均值分别为(22.4±3.5)m/s、(16.1±2.5)kPa、(2.7±0.3)m/s、(2.3±0.2)m/s,均低于肝癌组[(40.6±4.5)m/s、(33.5±2.5)kPa、(3.8±0.6)m/s、(3.4±0.4)m/s,P<0.05];ROC曲线分析结果显示,声速匹配值、弹性模量值、剪切波速度最大值、剪切波速度平均值在鉴别肝血管瘤与肝细胞癌中具有极高的价值。结论声速匹配值、弹性模量值、剪切波速度最大值、剪切波速度平均值在鉴别肝血管瘤与肝细胞癌中具有极高的价值,声速匹配技术及剪切波弹性成像可用于鉴别肝血管瘤与肝细胞癌。

2008年M_(W)7.9汶川地震早期余震频度衰减速率空间分布特征分析

深入认识余震频度衰减及其影响因素对理解余震触发机理和震后应急救援具有重要意义.然而,由于强震后余震数量庞大,波形相互叠加导致了目录中余震缺失,进而影响了余震频度衰减速率的估计.本研究采用模板匹配技术对2008年M_(W)7.9汶川地震后约50天内连续数据进行扫描,检测余震数量约为模板地震数量的5倍,完备震级由M3.0降低到M2.3.根据余震沿映秀—北川断裂走向优势深度分布的变化,以映秀、汶川、茂县、北川、南坝为界,余震活动大致可分为6个区域.本研究利用最大似然法分别计算了各个区域的余震频度衰减速率,结果显示:以茂县、青川为界,余震频度衰减速率表现出映秀—北川断裂西南段较快、中间段居中、东北段较慢的特征.将余震频度衰减速率和余震空间分布、断裂类型、震后形变、同震形变等进行对比分析,本研究得到以下结论:1、余震频度衰减速率分区与断裂类型分区吻合.其中,映秀—北川断裂西南段余震频度较快衰减速率区域断裂以逆冲为主,中间段为经过各种震源机制类型交替出现的过渡带,映秀—北川断裂东北段余震频度较慢衰减速率区域断裂以右旋走滑为主;2、余震频度衰减速率西南段较快、东北段较慢的空间分布特征与震后形变特征相一致;3、余震频度衰减速率与同震形变相关性不强.结合本研究观测到的同震滑移量较大区域余震分布较少、部分区域余震数目和震后形变空间分布一致性等特征,我们推测汶川地震早期余震可能主要与震后余滑相关,余震频度衰减速率的空间分布差异主要与不同类型断裂震间滑移速率不同相关,震间滑移速率较快的区域余震频度衰减速率较快及震后形变较大.

基于光学影像的滑坡形变监测研究——以2018年Palu地震触发滑坡为例

以2018年印度尼西亚Palu地震触发的低坡度滑坡为例,利用Planet、Landsat-8和Sentinel-2等3种光学影像对Gumbasa水渠沿线高含水量区域的地表形变进行监测和精度评估。结果表明:1)3种独立的光学卫星获得的形变场结果具有较好一致性,且Planet获得的形变场结果精度最高;2)沿Gumbasa水渠分布有4个主要形变区,最大形变超过20 m;3)光学影像地表形变监测精度与影像空间分辨率之间并非呈现简单的线性关系。最后,通过滑坡位置、地物属性和水渠的空间位置分析地震触发滑坡的机理。

深中通道中山大桥主桥超宽大节段钢箱梁吊装匹配技术

深中通道中山大桥主桥为主跨580 m的双塔双索面钢箱梁斜拉桥,主梁采用流线型扁平钢箱梁,梁宽46 m(含风嘴),主梁共划分69个节段,标准段长18 m、最大吊重约429 t,采用桥面吊机双悬臂吊装。由于钢箱梁节段自重大、宽度较大、横桥向竖向刚度较小等,在桥面吊机悬臂吊装过程中,会出现钢箱梁匹配面高差过大(最大约63 mm)的问题。为解决该问题,实现梁段精确匹配安装,提出3种钢箱梁吊装匹配方案:“门架+拉索”方案、“牛腿反力架”方案、“一字梁锁定+C形焊缝+部分张拉斜拉索”方案。经有限元仿真分析综合比选,最终选择“一字梁锁定+C形焊缝+部分张拉斜拉索”方案。该方案以箱梁竖腹板为定位点,提前焊接一字梁,采用法兰连接后锁定待拼梁段,部分焊接拼接面内箱梁形成C形焊缝;通过提前挂索并张拉部分斜拉索,减小匹配面已拼梁段横桥向竖向变形,达到箱梁匹配要求。施工中采取了匹配高差调节、局部应力控制、拼接缝宽控制等关键技术,最终将该桥钢箱梁匹配面高差减小至9.8 mm以内,钢箱梁局部应力可控,斜拉索初张过程中钢箱梁应力增量小于10 MPa,且各箱梁节段拼接缝宽可控制在1 cm以内。

Solumbra技术和SWIM技术治疗脑卒中的疗效对比

目的评估Solumbra技术和SWIM技术治疗急性缺血性脑卒中(acute ischemic stroke,AIS)的有效性与安全性。方法回顾性分析191例AIS病例资料,根据手术方式分为Solumbra组(n=97)和SWIM组(n=94)。应用倾向性评分匹配法(propensity score matching,PSM)将两组患者按1∶1配比。对比匹配后两组患者临床相关指标、术后不同时间点美国国立卫生院卒中量表(the National Institutes of Health Stroke Scale,NIHSS)评分、侧支循环改善情况及并发症发生率。结果经PSM匹配,有50对患者匹配成功。Solumbra组患者取栓>2次占比与住院时间均高于SWIM组,预后良好占比低于SWIM组(P<0.05)。Solumbra组患者术后7d及术后2周NIHSS评分均低于SWIM组(P<0.05)。并发症发生率Solumbra组为20.00%,SWIM组为38.00%,Solumbra组低于SWIM组(P<0.05)。结论Solumbra技术和SWIM技术取栓治疗各有优势,临床可充分结合患者实际病情,针对性选择取栓方式。

黄茅海跨海通道高栏港大桥钢箱梁施工关键技术

黄茅海跨海通道高栏港大桥为(110+248+700+248+110)m全飘浮体系双塔双索面斜拉桥,主梁为分体式钢箱梁,标准梁段重约370 t、最大悬臂拼装梁段重约468 t,采用桥面吊机进行悬臂拼装,施工阶段抗风问题突出。通过设置塔梁三向临时锚固抵抗施工过程中的不平衡力及力矩,有限元计算结果表明塔梁三向临时锚固均满足受力需求;在边跨侧设置抗风临时墩,并依据受力分析结果确定抗风临时墩的钢管桩选用∅1200 mm×12 mm,平联、斜撑选用∅426 mm×6 mm,施工阶段安全渡台;通过设置横断面预拱度保证了钢箱梁成桥横坡;采用反力牛腿法在被吊装梁段和已安装梁段匹配侧施加成对反力有效减小匹配高差,保证了钢箱梁的顺利匹配安装;边、辅墩墩顶前一梁段的斜拉索二次张拉后再进行合龙,避免了施工期间边、辅墩支座出现负反力;中跨采用单边起吊加配重和自然温差配切的合龙方式。

基于点云特征的城市道路标识线提取与分类

为了解决基于车载激光雷达(LiDAR)点云数据中的道路标识线提取完整度与提取精确度方面数值偏低等问题,提出了一种基于点云多元特征的道路标识线快速提取方法。在城市道路标识线的强度信息、几何信息和语义信息基础上,结合路面点云的强度特征、高程特征和点密度特征,生成多个地理参考图像,对多元特征图像进行特征提取与填充,再利用Ostu算法以及Alpha shapes算法实现道路标识线点云精提取,并根据标识线的几何、语义信息和模型匹配方案实现标识线的细分类,进行了理论分析和实验验证,取得了澳大利亚某城市道路的点云数据。结果表明,提取的短虚线、斑马线、单向转向箭头、长虚线的准确率均高于96%,召回率均达到91%及以上,综合评价指标均达到94%及以上。这些结果对无人驾驶领域研究起到了添砖加瓦的作用,也为城市数字化建设提供了一定的参考价值。

基于图像特征的模板匹配技术

模板匹配是图像识别和目标定位的基础方法之一,如何选取效率更高的模板匹配方式尤为重要。首先讨论了图像特征的提取方法,包括统计特征提取、Hu不变矩特征提取和纹理特征提取。然后详细介绍了模板匹配的实现过程,包括特征点提取和相似度计算。最后对基于不同图像特征提取方法的模板匹配结果进行了分析,通过仿真实验结果对比得出,基于纹理特征提取的模板匹配方式具有更高的效率,匹配准确率均在96%及以上。