Using Satellite Data to Analyze the Initiation and Evolution of Deep Convective Clouds

In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and propagated backward. Satellite data showed that prior to initiation of the deep convective clouds, thermodynamic and moist conditions were favorable for their formation. In the morning, a deep convective cloud at the rear of cold front cloud band propagated backward, the outflow boundary of which created favorable conditions for initiation. An additional deep convective cloud cluster moved in from the west and interacted with the outflow boundary to develop a mesoscale convective system(MCS) with large, ellipse-shaped deep convective clouds that brought strong rainfall. The initiation and evolution of these clouds are shown clearly in satellite data and provide significant information for nowcasting and short-term forecasting.

Cloud Data Center Selection Using a Modified Differential Evolution

The interest in selecting an appropriate cloud data center is exponentially increasing due to the popularity and continuous growth of the cloud computing sector.Cloud data center selection challenges are compounded by ever-increasing users’requests and the number of data centers required to execute these requests.Cloud service broker policy defines cloud data center’s selection,which is a case of an NP-hard problem that needs a precise solution for an efficient and superior solution.Differential evolution algorithm is a metaheuristic algorithm characterized by its speed and robustness,and it is well suited for selecting an appropriate cloud data center.This paper presents a modified differential evolution algorithm-based cloud service broker policy for the most appropriate data center selection in the cloud computing environment.The differential evolution algorithm is modified using the proposed new mutation technique ensuring enhanced performance and providing an appropriate selection of data centers.The proposed policy’s superiority in selecting the most suitable data center is evaluated using the CloudAnalyst simulator.The results are compared with the state-of-arts cloud service broker policies.

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin,China

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

Evolution of corporate environmental information disclosure framework of “knowledge and action”: Based on big data background

Cloud accounting is based on the traditional financial work process, the context of big data, and the necessary trend of future corporate accounting development. Its emergence and rapid development will have a fundamental impact on corporate environmental information disclosure. In the big data era of information sharing, companies will have a new understanding of the emergence, balance, and final consideration of social responsibility, and will have new changes in their overall decision-making and information disclosure methods. "Knowing" and "behavior" will be combined on the basis of rational judgment, so that corporate environmental information disclosure is more in line with the overall social development requirements. Based on the background of big data, this article starts with the disclosure of impact factors, footholds, and path choices. It describes the evolution of corporate environmental information disclosure and provides reference suggestions for enterprises to disclose environmental information truthfully and perform social responsibilities.

Resolving tumor evolution:a phylogenetic approach

The evolutionary dynamics of cancer,characterized by its profound heterogeneity,demand sophisticated tools for a holistic understanding.This review delves into tumor phylogenetics,an essential approach bridging evolu-tionary biology with oncology,offering unparalleled insights into cancer’s evolutionary trajectory.We provide an overview of the workflow,encompassing study design,data acquisition,and phylogeny reconstruction.No-tably,the integration of diverse data sets emerges as a transformative step,enhancing the depth and breadth of evolutionary insights.With this integrated perspective,tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.

Evolution algorithm for water storage forecasting response to climate change with little data sets:the Wolonghu Wetland,China

An attempt of applying a novel genetic programming(GP) technique,a new member of evolution algorithms,has been made to predict the water storage of Wolonghu wetland response to the climate change in northeastern part of China with little data set.Fourteen years(1993-2006) of annual water storage and climatic data set of the wetland were taken for model training and testing.The results of simulations and predictions illustrated a good fit between calculated water storage and observed values(MAPE=9.47,r=0.99).By comparison,a multilayer perceptron(MLP)(a popular artificial neural network model) method and a grey model(GM) with the same data set were applied for performances estimation.It was found that GP technique had better performances than the other two methods both in the simulation step and predicting phase and the results were analyzed and discussed.The case study confirmed that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under condition of little data set.

Tectonic evolution of structures in Southern Sindh Monocline,Indus Basin,Pakistan formed in multi-extensional tectonic episodes of Indian Plate

There are a number of structures and structural styles found in extensional tectonic settings of the world,and it is a big challenge to study the evolution of these structures. Evolution of structures formed in extensional tectonic settings have been studied by researchers on different extensional basins of the world. Southern Sindh Monocline lies on the western corner of Indian Plate and the tectonic history of Indian plate has also experienced different extensional episodes, and its journey rifted from Gondwanaland to its final welding to Asia. The aim of this study is to figure out the evolution of structures in the subsurface of Southern Sindh Monocline, Pakistan using the seismic data interpretation and flattening of horizons approach. Structures within the subsurface of Southern Sindh Monocline have been characterized by different tectonic episodes of Indian plate while rifting from Gondwanaland, rifting from other plates at different geological times and to its collision with the Asia. Basic structures within study area are classified into nine types while the structural styles have been classified into six types as horst and grabens, dominos, crotch, synthetic and antithetic, negative and flashlight structural style. The structures within the study area revealed evidence for three major structural episodes which can be characterized as Episode 1: Structures associated with rifting of Indian plate from Gondwanaland during Late Jurassic to Early Cretaceous, Episode 2: Modification and reactivation of previous structures while Madagascar rifted from Indian Plate during the Middle Cretaceous and during Episode 3: Inversion and reactivation of structures occurred when Indian Plate collided with Asia during Early Eocene.

Parameter inversion and location determination of evolutionary weak layer for open-pit mine slope

In light of the complex and dynamic mechanical properties of evolving weak strata in open-pit mines,and the consequent difficulty of determining their mechanical parameters,this study uses the ultimate balance theory,along with the back analysis method combined with monitoring data on field displacement,to carry out parameter inversion using the FLAC3D numerical simulation software.The edge slope of a working pit of the Weijiamao open-pit mine was used as research object to this end.As the results obtained by the constitutive model were consistent with the field monitoring data,the evolving weak strata in the slope and the position of the landslide in the mine could be obtained.The landslide was directed northeast.The mechanism of the edge slope of the working pit was identified as unloading shear failure,and the feasibility of the method of parameter inversion was verified.The internal friction angle φand cohesion C of evolving weak strata in the slope of the open-pit mine were also obtained,where this compensated for the deficiency of laboratory tests and enabled the transformation from qualitative to quantitative analysis.This can provide a reliable basis for the safe operation of open-pit mines.

User-Level Sentiment Evolution Analysis in Microblog

People's attitudes towards public events or products may change overtime,rather than staying on the same state.Understanding how sentiments change overtime is an interesting and important problem with many applications.Given a certain public event or product,a user's sentiments expressed in microblog stream can be regarded as a vector.In this paper,we define a novel problem of sentiment evolution analysis,and develop a simple yet effective method to detect sentiment evolution in user-level for public events.We firstly propose a multidimensional sentiment model with hierarchical structure to model user's complicate sentiments.Based on this model,we use FP-growth tree algorithm to mine frequent sentiment patterns and perform sentiment evolution analysis by Kullback-Leibler divergence.Moreover,we develop an improve Affinity Propagation algorithm to detect why people change their sentiments.Experimental evaluations on real data sets show that sentiment evolution could be implemented effectively using our method proposed in this article.

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.

Real traffic-data based evaluation of vehicular traffic environment and state- of-the-art with future issues in location-centric data dissemination for VANETs

Extensive investigation has been performed in location-centric or geocast routing protocols for reliable and efficient dissemination of information in Vehicular Adhoc Networks （VANETs）. Various location-centric routing protocols have been suggested in literature for road safety ITS applications considering urban and highway traffic environment. This paper characterizes vehicular environments based on real traffic data and investigates the evolution of location-centric data dissemination. The current study is carded out with three main objectives： （i） to analyze the impact of dynamic traffic environment on the design of data dissemination techniques, （ii） to characterize location-centric data dissemination in terms of functional and qualitative behavior of protocols, properties, and strengths and weaknesses, and （iii） to find some future research directions in information dissemination based on location. Vehicular traffic environments have been classified into three categories based on physical characteristics such as speed, inter-vehicular distance, neighborhood stability, traffic volume, etc. Real traffic data is considered to analyze on-road traffic environments based on the measurement of physical parameters and weather conditions. Design issues are identified in incorporating physical parameters and weather conditions into data dissemination. Functional and qualitative characteristics of location-centric techniques are explored considering urban and highway environments. Comparative analysis of location-centric techniques is carded out for both urban and highway environments individually based on some unique and common characteristics of the environments. Finally, some future research directions are identified in the area based on the detailed investigation of traffic environments and location-centric data dissemination techniques.

Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

In the IoT(Internet of Things)system,the introduction of UAV(Unmanned Aerial Vehicle)as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy.However,the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system.In this work,to deal with the problem,a deployment model of a mobile edge computing(MEC)system based on multi-UAV is proposed.The goal of the model is to minimize the energy consumption of the system in the process of data transmission by optimizing the deployment of UAVs.The DEVIPSK(differential evolution algorithm with variable population size based on a mutation strategy pool initialized by K-Means)is proposed to solve the model.In DEVIPSK,the population is initialized by K-Means to obtain better initial positions of UAVs.Besides,considering the limitation of the fixed mutation strategy in the traditional evolutionary algorithm,a mutation strategy pool is used to update the positions of UAVs.The experimental results show the superiority of the DEVIPSK and provide guidance for the deployment of UAVs in the field of edge data collection in the IoT system.

程序调试中的数据结构演变可视化方法

数据结构是程序执行时的重要信息载体,其演变过程往往较为复杂和抽象。针对程序设计初学者较难理解数据结构演变过程的问题,提出一种面向程序调试中的数据结构演变可视化方法。在调试开始时,首先使用组件表达式表示数据结构,然后通过配置表以及布局函数将组件表达式生成可视化视图。在进行单步调试后,通过对比单步调试前后的可视化数据方式生成组件演变行为,运用有限状态机理论构建数据结构演变模型,该模型的执行使得组件发生演变,同时生成可视化动作。使用动画单元执行可视化动作,实现数据结构演变的可视化呈现,帮助初学者理解数据结构相关程序的执行过程。实验结果表明,将该方法应用于1个数据结构演变可视化框架StructV,并应用于1个在线可视化编程实训云平台的研发,可有效降低初学者理解数据结构演变过程的难度,并提升编程实训时的程序调试效率。

数据要素价值演进路径研究

【目的】在数字经济时代,数据已经成为赋能经济发展的关键生产要素。研究表明数据要素质变升级的发展路径尚不明确,数据要素的价值释放面临诸多困难。【方法】本文系统研究了国内外相关文献及国家政策,总结分析了数据要素价值释放的研究现状,基于数据要素的价值提升,对我国数据要素发展路径展开相关研究。【结果】本文明确了从原始数据到数据资本的各类数据形态,提出了数据要素价值演进路径理论模型和数据要素发展路径。【结论】本研究厘清了数据要素“六状态”和价值演进“五阶段”,对于规范数据要素发展具有政策参考和实践意义,为促进数据要素价值的有效释放提供有力支持。

基于多源数据的长江流域1982—2022年骤旱事件时空演变

骤发性干旱(简称骤旱)是一种突发性高且强度大的极端干旱现象,会对农业生产和生态系统构成严重威胁。近年来,长江流域骤旱频发,然而其骤旱时空演变格局及规律尚不明晰。本研究基于GLEAM、GLDAS和ERA5-Land数据,以标准化蒸发胁迫比及其变化值作为识别指标,开展1982—2022年长江流域骤旱识别,全面分析长江流域骤旱空间分布和时间演变特征;并鉴于2022年旱情的严重性和特殊性,重点分析该年长江流域骤旱事件。研究结果表明:①在空间分布上,长江流域上游的金沙江水系和中下游的大型水库湖泊骤旱发生频率最高且强度最大;②在时间演变上,骤旱发生频率、平均持续时间和强度均在长江流域整体上呈现出非显著上升趋势,而有显著变化趋势的区域在2001年前后表现出明显的趋势反转现象;③2022年夏季受极端高温热浪影响,长江流域遭遇大规模骤旱事件,具有波及范围广、持续时间长的特点,且骤旱在空间上呈现出从上游向下游传递的态势。

我国数据安全政策文本主题挖掘及其演化分析

[目的/意义]揭示数据安全政策主题的演化规律,对完善数据安全政策体系具有重要意义。[方法/过程]本文选取我国547部数据安全政策文本,利用NMF主题模型进行主题挖掘并结合Word2Vec词向量模型,从主题内容演化和主题强度演化两个视角进行可视化处理与分析。[结果/结论]识别出网络安全、应急处置、安全保障、个人隐私等主题,而主题演化内容呈现聚集性,演化领域呈现扩散性;数据开放、公共数据等核心主题整体演化强度趋势不断提高,但个人隐私、安全可控、监测预警相关主题政策占比失衡。针对主题挖掘及演化分析结果,并结合我国数据安全治理现状提出4点建议:持续加强数据开放与安全的协同;加强全流程的数据安全治理;完善技术与政策融合的数据安全治理机制;平衡政策主题演化注意力分配。

基于专利异构数据融合的技术演化路径识别方法

[研究目的]针对目前技术演化分析中多关注专利文本,忽略专利引文信息的问题,提出一种基于专利异构数据融合的技术演化路径识别方法。[研究方法]首先,使用Sentence-BERT模型提取专利文本语义特征;其次,使用图卷积神经网络模型将文本语义特征与引文结构特征融合,实现异构数据融合构建专利向量;最后,划分时间窗,使用k-means算法对各时间窗进行技术主题聚类,基于相邻时间窗技术主题相似度构建技术演化路径。[研究结论]以人工智能领域为例进行实证研究,共发现4条技术演化路径。与相关权威报告进行比对,结果表明识别结果与人工智能技术领域的发展现状一致,验证了模型的有效性和科学性。

党“管”数据:基于政企数据权力演化的治理逻辑

数据是治国理政的重要资源,党“管”数据则是推动国家治理体系和治理能力现代化的关键路径。而在数据资源的流动下发生着数据权力的动态演化,存在政企主体数据发展优势表现不同,且需平衡少数大型企业依托政府数据资源优势异化形成数据权力的利弊影响,呈现出党“管”数据的需求。基于此,本文将从静态视角和动态视角分析政企主体间数据权力的形成和异化,从理论与实践的角度分别阐释党“管”数据的必要逻辑,进而探讨中国特色治理模式下党“管”数据的实现路径。研究认为,党“管”数据是制度优势、组织架构和安全发展的必然要求,是规制政企数据权力动态异化的必然选择,并凝练出“1+4”治理路径,推进实现善治目标与国家治理体系和治理能力现代化。

卫生健康标准中关系型数据共现矩阵计算及SAS程序实现

目的设计卫生健康标准中关系型数据共现矩阵的求解路径及其SAS实现方法。方法文章以计算一组标准的起草单位共现矩阵为例,将“标准-起草单位”二维表格导入SAS(版本号:9.4),按照“两两相乘”的计算思路自行设计宏程序计算起草单位之间的共现矩阵。结果以计算一组标准的起草单位共现矩阵为例,采用自行构建的模拟数据进行演示。首先,导入宏循环起始的数据集,并计算共现频次C_(j,k);然后,导出为out数据集,进一步合并数据集,形成最终的共现矩阵。结论SAS宏程序计算标准中关系型数据共现矩阵具有灵活高效的优势,可用于社会网络分析和互动演进规律总结。

站城一体化视角下高铁新城演变效应实证研究——以杭州东站城东新城为例

以高铁站点为核心,综合发展居住、商业、办公等功能的高铁新城建设模式逐渐被规划开发者所接受。高铁新城的发展是否达到规划预期,高铁站对城市的影响强度是研究的目标。文章以杭州东站所在的城东新城为对象,通过多年卫星地图、空间句法和大数据3种方法,揭示了城东新城12年的发展与站城融合发展预期目标的协同情况。从道路网络构成、房地产开发、商业建设情况、乘客微观感知4个考察维度建立高铁新城演变效应研究体系,证实了该体系对研究站与城关系的科学性和理论性。研究旨在通过综合多种数据采集方法,从城市设计和微观感知角度获得高铁站点对城市的具体发展效应,对我国高铁新城的城市规划评估体系和开发模式提供实证借鉴。