Stroke Based Painterly Rendering with Mass Data through Auto Warping Generation

Painting is done according to the artist’s style.The most representative of the style is the texture and shape of the brush stroke.Computer simulations allow the artist’s painting to be produced by taking this stroke and pasting it onto the image.This is called stroke-based rendering.The quality of the result depends on the number or quality of this stroke,since the stroke is taken to create the image.It is not easy to render using a large amount of information,as there is a limit to having a stroke scanned.In this work,we intend to produce rendering results using mass data that produces large amounts of strokes by expanding existing strokes through warping.Through this,we have produced results that have higher quality than conventional studies.Finally,we also compare the correlation between the amount of data and the results.

A Distributed In-Memory Database Solution for Mass Data Applications

In this paper, a Distributed In-Memory Database （DIMDB） system is proposed to improve processing efficiency in mass data applications. The system uses an enhanced language similar to Structured Query Language （SQL） with a key-value storage schema. The design goals of the DIMDB system is described and its system architecture is discussed. Operation flow and the enhanced SOL-like language are also discussed, and experimental results are used to test the validity of the system.

Mass Data—A Gold Mine to be Explored

Click on a shopping website and looking for the products you are interested in,then you will place the order and wait for home delivery.Or you may talk with your families living far away on the video conference,or share your video on the website.It will be interesting to know how does this happen and what is its significance.

Database-oriented storage based on LMDB and linear octree for massive block model

Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.

Analysis and assessment of bridge health monitoring mass data——progress in research/development of “Structural Health Monitoring”

The "Structural Health Monitoring" is a project supported by National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.50725828).To meet the urgent requirements of analysis and assessment of mass monitoring data of bridge environmental actions and structural responses,the monitoring of environmental actions and action effect modeling methods,dynamic performance monitoring and early warning methods,condition assessment and operation maintenance methods of key members are systematically studied in close combination with structural characteristics of long-span cable-stayed bridges and suspension bridges.The paper reports the progress of the project as follows.(1) The environmental action modeling methods of long-span bridges are established based on monitoring data of temperature,sustained wind and typhoon.The action effect modeling methods are further developed in combination with the multi-scale baseline finite element modeling method for long-span bridges.(2) The identification methods of global dynamic characteristics and internal forces of cables and hangers for long-span cable-stayed bridges and suspension bridges are proposed using the vibration monitoring data,on the basis of which the condition monitoring and early warning methods of bridges are developed using the environmental-condition-normalization technique.(3) The analysis methods for fatigue loading effect of welded details of steel box girder,temperature and traffic loading effect of expansion joint are presented based on long-term monitoring data of strain and beam-end displacement,on the basis of which the service performance assessment and remaining life prediction methods are developed.

Design of new format for mass data compression

In the field of lossless compression, most kinds of traditional software have some shortages when they face the mass data. Their compressing abilities are limited by the data window size and the compressing format design. This paper presents a new design of compressing format named ＇CZ format＇ which supports the data window size up to 4 GB and has some advantages in the mass data compression. Using this format, a compressing shareware named ＇ComZip＇ is designed. The experiment results support that ComZip has better compression ratio than WinZip, Bzip2 and are compressed. And ComZip has the potential to beat 7-zip in WinRAR in most cases, especially when GBs or TBs of mass data future as the data window size exceeds 128 MB.

Substance Identification in Anti-Doping Control by Means of Mass Spectrometry. Data Reduction and Decision Criteria

A real doping case for which the national-level reviewing body deemed it probable that a misidentification of the national-level athlete’s sample occurred at the WADA accredited laboratory, thus making the athlete in this case strictly anonymous, is used to discuss criteria for data reduction and tolerance windows in GC-MS and LC-MS/MS. Stricter criteria for data reduction would remedy the present ambiguities.

不同观察者基于卵巢-附件影像报告和数据系统诊断卵巢附件肿块的一致性研究

目的 探讨不同年资超声医师使用卵巢-附件影像报告和数据系统(O-RADS)判读观察指标的一致性,以及对卵巢附件肿块的诊断效能评价。方法 选取经手术组织学病理确诊的244例(304个病灶)卵巢附件肿块患者的超声存储图像。2位不同年资超声医师按照O-RADS分类标准对每个肿块进行观察指标盲读,进行O-RADS分类。对照病理结果,采用Kappa检验评估一致性,构建ROC曲线,分析两者诊断卵巢肿块的诊断效能。结果 2位不同年资超声医师根据O-RADS分类标准对卵巢附件肿块外部轮廓、内部回声、血流信号、腹水以及腹膜增厚或腹膜结节5项观察指标判读的一致性检验Kappa值分别为0.748、0.835、0.652、0.973、0.979,差异有统计学意义(P<0.001);2位超声医师对同一肿块O-RADS分类一致性检验Kappa值为0.795,差异有统计学意义(P<0.001);2位医师O-RADS分类的ROC曲线面积为0.897、0.918,准确率为80.92%、80.92%,灵敏度为77.3%、76.7%,特异度为88.3%、91.5%,差异均无统计学意义(P>0.05)。结论 不同年资超声医师对O-RADS观察指标判读具有较高一致性;O-RADS分类标准对卵巢肿块的诊断也具有较高诊断效能。

Data Analysis for High Throughput Detection of 18 Phthalates in Textiles Based on High Resolution Mass Spectrometry

Liquid chromatography coupled to high resolution mass spectrometry(LC-HRMS)was used to establish a high throughput and sensitive method for 18 phthalic acid esters(PAEs)in textiles.The method was applied to screen PAEs in 413 textile samples and 7 434 pieces of test data were analyzed.Further discussion was conducted about specific compounds,textile materials,detected value distribution and positive rate of samples.Twenty-nine percent of samples were detected with PAEs,and no samples were detected beyond regulations.Diisobutyl phthalate(DiBP),Dibutyl phthalate(DBP)and Di-2-ethylhexyl phthalate(DEHP)were detected with high frequency,and most samples were fabrics with coating and printing.This study can be used to reflect distribution of phthalate residues in textiles on the market and provide data support for risk assessment of PAEs for textile producers and consumers.

A DATA ACQUISITION SYSTEM FOR ACCELERATOR MASS SPECTROMETRY

A single and dual parameter data acquisition, ion beam measurements and control system for accelerator mass spectrometry is described. The system hardware has been constructed with the advantage of the lower cost and higher reliability. It is provided with varieties of functions such as selecting acquisition mode carrying out the multiple display, analyzing data and especially viewing isometric spectrum at different directions. It can also be used for ordinary nuclear spectrum system.

戴维孙-革末电子衍射实验数据的一点启示

1927年戴维孙(C.Davisson)和革末(L.H.Germer)的电子衍射实验第一次可争辩地验证实物粒子的波动性。事实上,与德布罗意(de Broglie)假设的理论计算相比,戴维孙-革末的电子衍射实验数据存在着一种明显的系统性偏离。在近百年之后的今天,该偏离或许为当前电子的电磁质量的研究提供一个有价值的启示和实验依据。

基于数据挖掘探讨肿块期肉芽肿性小叶性乳腺炎的用药规律

目的:基于数据挖掘的方法探讨文献中中药治疗肿块期肉芽肿性小叶性乳腺炎(Granulomatous Lobular Mastitis,GLM)的用药规律和组方配伍特点。方法:利用计算机检索1980年(维普为收录起始年)至2022年中国知网、万方数据库、维普期刊资源整合服务平台、中国生物医学文献数据库中关于中药治疗肿块期GLM的文献,严格筛选符合纳入标准的文献,利用Excel建立肿块期GLM规范化方药数据库,采用数据挖掘的方法对中药的功效类别、性味归经等进行频数统计分析以及关联规则和系统聚类分析。结果:纳入中药复方47首,涉及中药111味,累计药物使用频次574次,用药频次较高的药物包括柴胡、皂角刺、白芥子、蒲公英、熟地黄等,常用的中药功效类别为理气药、化痰药,四气多为寒、温,五味多为苦、辛,归经前3位分别为肝经、脾经、胃经。经关联规则分析,得出潜在配伍组合共16组,为白芥子、麻黄、熟地黄、炮姜、肉桂、香附的加减组合。聚类分析挖掘出5个核心组方。结论:中药治疗肿块期GLM多采用温阳散结、理气化痰之法。

基于车联网大数据的重型货车载重估计方法

针对当前货车载重计算方法普遍存在的成本高昂及泛化性能不明确的问题,提出一种创新的重型货车载重估计方法,方法融合了车辆行驶动力学理论与机器学习算法,通过有监督学习,利用高速通行大数据对模型进行训练与验证.首先采用聚类分析,确定车辆空、半、满载判断阈值,为后续的计算提供了重要依据.随后,利用随机森林算法训练分类模型,用以判断车辆在一段行驶过程中的基本载重情况.在此基础上,进一步在车辆行驶数据中筛选出稳定行驶的小片段,根据车辆系统动力学理论,对这些小片段车重进行计算.最后,根据载重状态的判断结果,对小片段车重结果进行筛选与计算,得到最终车辆载重计算结果.研究表明,在高速通行大数据的验证下,该方法对于空载及满载状态下趟次车重计算结果的整体平均绝对百分比误差(mean absolute percent error,MAPE)均可控制在10%以内,展现了较高的准确性.相比于现有技术,由于该方法无需安装额外传感器,对数据采集、存储、运算设备的要求也相对较低,因此在成本方面具有显著优势.在交通监管、物流运输、基于大数据的产品开发方面具有快速广泛推广的潜力.

基于社交媒体数据的应急决策大群体群智知识挖掘及其价值测度方法研究

本文针对突发事件下的社交媒体数据体量庞大,但能够辅助应急决策的大群体群智知识分布无序且价值难以测度的问题,提出了一种应急决策大群体群智知识挖掘及其价值测度方法。首先,基于社交媒体博文数据,依据特定应急决策知识框架,采用TF-IDF(term frequency-inverse document trequency)法和改进后的词汇链算法构建了应急决策大群体群智知识挖掘方法;然后,提出了博文热度计算方法,在此基础上根据知识的语义重要性计算博文包含的群智知识总价值,并使用Shapley函数对群智知识价值进行分配;最后,以“新冠疫情”事件为案例对方法进行应用,并通过对比分析说明了方法的有效性和优越性。

基于《中华医典》文献挖掘中医治疗积聚的用药规律研究

目的:探讨《中华医典》中治疗积聚方剂的用药特点及其规律。方法:检索《中华医典》治疗积聚的方剂,按照纳入和排除标准筛选治疗积聚的方剂,建立Excel数据库,进行用药频次、性味、归经分析。并使用R语言arules包及arulesViz包对筛选处方中的药物进行关联规则分析及可视化,使用IBM SPSS Modeler 18.0对药物进行复杂网络分析,采用SPSS Statistics 26.0对聚类方剂进行分析。结果:筛选后共纳入方剂426首,包含中药303种,总用药频次4075次;四气9种,总频次3214次;五味8种,总频次5490次;十二经总频次11936次。治疗积聚应用频次较高的药物前3位为木香、肉桂、当归;关联性药对以三棱、木香出现频次最高。复杂网络分析,木香-肉桂、木香-三棱之间的关联性较强。聚类图谱显示,皮尔逊相关性为20时,高频药物可聚为5类。结论:历代医家在积聚治疗时,所用药物药性以温性为主,药味以辛味和苦味为主,归经侧重于脾胃经,功效以理气药、温里药、补益药为主。通过对《中华医典》中治疗积聚的用药规律研究,为临床实践中药治疗积聚相关疾病提供参考。

卵巢-附件超声报告和数据系统分类联合超声图像特征对卵巢附件良恶性肿块的鉴别诊断价值

目的 探讨卵巢-附件超声报告和数据系统(O-RADS)分类联合超声图像特征对卵巢附件良恶性肿块的鉴别诊断价值。方法 选取O-RADS分类为3~5类的140例卵巢附件肿块患者,所有患者均接受彩色多普勒超声检查。以病理检查结果为金标准,绘制受试者工作特征曲线,计算曲线下面积(AUC),分析O-RADS分类、多项超声图像特征单独及联合检查对卵巢附件恶性肿块的诊断价值。结果 病理检查结果显示,140例患者中共147个卵巢附件肿块,恶性56个(包括交界性肿瘤),良性91个;O-RADS分类3类46个,4类61个,5类40个。O-RADS分类联合肿块实性部分最大径、血流评分、肿块形态诊断卵巢附件恶性肿块的AUC为0.959,高于各指标单独检查的0.738、0.882、0.913、0.894。结论 在O-RADS分类定性诊断卵巢附件肿块的基础上,结合肿块实性部分最大径线、血流评分、肿块形态等彩色多普勒超声图像特征可进一步提高卵巢附件良恶性肿块的鉴别诊断效能。

一种基于Mosaic Dataset的海量影像数据处理方法

高精度海量影像数据是天地图、数字城市等公共服务平台的基础数据源之一。巨大的数据量使得传统影像数据加工方法的效率大大降低,这也成为制约公共服务平台数据生产效率的瓶颈之一。本文基于ArcGIS10版本推出的Mosaic Dataset模型,实现了海量高精度影像数据的高效处理,从海量数据管理、数据预处理、投影变换、去黑边、填补空洞等方面,详细叙述了该模型在海量影像数据处理方面的应用。本研究期望为相关数据加工与生产提供借鉴。

多尺度人口空间大数据聚合模型在地图可视化中的研究与应用

为解决海量人口和建筑物数据导致的地图渲染时间长、页面卡顿无响应等技术问题,本文提出了一种多尺度人口空间大数据聚合模型,通过研究海量数据逐级嵌套的树型逻辑架构和可视域内的空间关系,实现了超大城市多尺度行政区域的人口空间数据统计分析与可视化,并在多源异构属性融合方面得到了较好的应用,更好地满足了超大城市精细化管理需求。

基于质谱熵的小分子化合物相似性计算方法研究

在二级质谱(MS2)数据检索中,通常利用质谱数据之间的相似性进行检索。针对质谱数据相似性计算中数据不整齐导致的检索效率和准确性不高以及商用软件相似性计算方法单一的问题,研究提出了“拼接填充”与“匹配填充”两种MS2数据对齐方法,并基于信息熵采用质谱熵相似性计算方法进行相似性检索。首先对归一化后的原始质谱数据进行特征提取,保留能突出质谱数据特征的数据,再分别采用两种数据对齐方法对质谱数据进行预处理;然后基于信息熵方法,分别计算未知质谱与已知质谱混合后的虚拟质谱与两者质谱的熵差,获得未知质谱与已知质谱的相关系数即相似性;最后选择小分子化合物的质谱数据集进行实例验证。结果表明:两种质谱数据预处理方法能够解决相似性计算中质谱长度不等的问题,基于质谱熵的相似性计算方法稳定且结果可靠,适用于小分子化合物的相似性检索,同时也为商用软件的谱图相似性计算提供了新的方案。

基于冷却水管的大体积混凝土基础有限元仿真分析

为研究大体积筏板基础混凝土水化热过程,避免因温差过大引起温度裂缝,以广州市锦佳华庭C2#超高层住宅楼筏板基础为依托,在ANSYS有限元软件中建立模型,对有无冷却水管情况下筏板基础的温度场和温度应力分布进行分析。研究结果表明:筏板基础出现裂缝的风险相对较高,需要实施适当的保护措施;冷却水管的降温效果明显,相比无冷却水管作用,温度峰值下降11.69℃,提前出现26小时,降温效率达到26.08%,且混凝土的温度应力均低于允许应力,不易产生裂缝;在现场实际测量中,基础里表温差最大值为16.1℃,单日最大降温速率1.7℃/d,实测数据均满足规范标准;基础在养护完成后,其外部未出现明显裂痕,证实以设置冷却水管为主的温控措施可以显著减少水化热的影响,减小内外温差以避免温度裂缝的产生;实测结果与有限元结果基本吻合,可为类似的超高层住宅建筑基础温控措施提供参考。