Merkle Tree Digital Signature and Trusted Computing Platform

Lack of efficiency in the initial key generation process is a serious shortcoming of Merkle tree signature scheme with a large number of possible signatures. Based on two kinds of Merkle trees, a new tree type signature scheme is constructed, and it is provably existentially unforgeable under adaptive chosen message attack. By decentralizing the initial key generation process of the original scheme within the signature process, a large Merkle tree with 6.87×10^10 possible signatures can be initialized in 590 milliseconds. Storing some small Merkle trees in hard disk and memory can speed up Merkle tree signature scheme. Mekle tree signature schemes are fit for trusted computing platform in most scenarios.

Analysis on medication rule of traditional Chinese medicine treating chemotherapy-induced diarrhea based on traditional Chinese medicine(TCM) inheritance computing platform system

Objective:To dig deeper into the traditional Chinese medicine treatment rules of chemotherapy-induced diarrhea with traditional Chinese medicine(TCM)inheritance computing platform system.Methods:Taking“traditional Chinese medicine”,“chemotherapy”and“diarrhea”as the theme words,comprehensive search of the database of CNKI,Wanfang and VIP from its inception to November 2020 was conduct-ed.The formulas of external treatment of traditional Chinese medicine for chemotherapy-induced diarrhea were included and the association rule,clustering and factor analysis were carried out.Results:A total of 145 papers,57 prescriptions meeting the inclusion criteria were collected,among which high-frequency drugs including Baizhu(Atractylodis macrocephalae rhizoma),Fuling(Poria),Dangshen(Codonopsisradix),Huanglian(Coptidis rhizoma),Zhigancao(Glycyrrhizae radix et rhizoma praeparata cum melle)were the most commonly used.The confidence level was set as 0.7 and the support level was set as 10,12 core compatibility groups were obtained,and 6 categories were cluster analyzed.Conclusion:The principle of external treatment of chemotherapy-induced diarrhea is mainly“restore deficiency and benefiting qi”,“benefiting water infiltration and dampness”,“clearing heat”and“inducing astringency”.Prescription combination and new prescription combination based on traditional Chinese medicine(TCM)inheritance computing platform system can be used as reference for clinicians and applied in primary hospitals.

Research and Application of Multi-level Diverse Intelligent Algorithm Library Based on Artificial Intelligence Computing Platform

At present,artificial intelligence computing platforms are usually based on cloud hosts for services,which have the characteristics of fast training speed and a wide variety of model types.However,the online models of such platforms mostly adopt the form of downloading model files,which is difficult to integrate into traditional software system systems.In response to existing problems,this paper takes the relevant theoretical technologies of next-generation intelligent computing platforms as the development framework,and conducts research on the diversity of multi-level intelligent computing requirements,by implementing a universal algorithm model construction and automatic integration mechanism;Build a multi domain and multi-level application algorithm library for different application scenarios;Design a personalized algorithm recommendation based on knowledge reasoning and object-oriented approach,and build an emerging intelligent computing platform for analyzing and understanding real-world data,meeting the needs of complex engineering application software such as heavy backend,light frontend,loose coupling,microservices,etc.,providing theoretical and technical support for innovative big data services and applications with diverse computing requirements.

Research on multi-terminal traveling wave fault location method in complicated networks based on cloud computing platform

Cloud computing technology is used in traveling wave fault location,which establishes a new technology platform for multi-terminal traveling wave fault location in complicated power systems.In this paper,multi-terminal traveling wave fault location network is developed,and massive data storage,management,and algorithm realization are implemented in the cloud computing platform.Based on network topology structure,the section connecting points for any lines and corresponding detection placement in the loop are determined first.The loop is divided into different sections,in which the shortest transmission path for any of the fault points is directly and uniquely obtained.In order to minimize the number of traveling wave acquisition unit(TWU),multi-objective optimal configuration model for TWU is then set up based on network full observability.Finally,according to the TWU distribution,fault section can be located by using temporal correlation,and the final fault location point can be precisely calculated by fusing all the times recorded in TWU.PSCAD/EMTDC simulation results show that the proposed method can quickly,accurately,and reliably locate the fault point under limited TWU with optimal placement.

Real-time hybrid simulation of structures equipped with viscoelastic-plastic dampers using a user-programmable computational platform

A user-programmable computational/control platform was developed at the University of Toronto that offers real-time hybrid simulation （RTHS） capabilities. The platform was verified previously using several linear physical substructures. The study presented in this paper is focused on further validating the RTHS platform using a nonlinear viscoelastic-plastic damper that has displacement, frequency and temperature-dependent properties. The validation study includes damper component characterization tests, as well as RTHS of a series of single-degree-of-freedom （SDOF） systems equipped with viscoelastic-plastic dampers that represent different structural designs. From the component characterization tests, it was found that for a wide range of excitation frequencies and friction slip loads, the tracking errors are comparable to the errors in RTHS of linear spring systems. The hybrid SDOF results are compared to an independently validated thermal- mechanical viscoelastic model to further validate the ability for the platform to test nonlinear systems. After the validation, as an application study, nonlinear SDOF hybrid tests were used to develop performance spectra to predict the response of structures equipped with damping systems that are more challenging to model analytically. The use of the experimental performance spectra is illustrated by comparing the predicted response to the hybrid test response of 2DOF systems equipped with viscoelastic-plastic dampers.

Design and Implementation of Cloud Platform for Intelligent Logistics in the Trend of Intellectualization

Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.

Cloud Computing Technology and Its Applications

Virtualization and distributed parallel architecture are typical cloud computing technologies. In the area of virtuatization technology, this article discusses physical resource pooling, resource pool management and use, cluster fault location and maintenance, resource pool grouping, and construction and application of heterogeneous virtualization platforms. In the area of distributed technology, distributed file system and KeyNalue storage engine are discussed. A solution is proposed for the host bottleneck problem, and a standard storage interface is proposed for the distributed file system. A directory-based storage scheme for Key/Value storage engine is also proposed.

Analysis of CLARANS Algorithm for Weather Data Based on Spark

With the rapid development of technology,processing the explosive growth of meteorological data on traditional standalone computing has become increasingly time-consuming,which cannot meet the demands of scientific research and business.Therefore,this paper proposes the implementation of the parallel Clustering Large Application based upon RANdomized Search(CLARANS)clustering algorithm on the Spark cloud computing platformto cluster China’s climate regions usingmeteorological data from1988 to 2018.The aim is to address the challenge of applying clustering algorithms to large datasets.In this paper,the morphological similarity distance is adopted as the similarity measurement standard instead of Euclidean distance,which improves clustering accuracy.Furthermore,the issue of local optima caused by an improper selection of initial clustering centers is addressed by utilizing the max-distance criterion.Compared to the k-means clustering algorithm already implemented in the Spark platform,the proposed algorithm has strong robustness,can reduce the interference of outliers in the dataset on clustering results,and has higher parallel performance than the frequently used serial algorithms,thus improving the efficiency of big data analysis.This experiment compares the clustered centroid data with the annual average meteorological data of representative cities in the five typical meteorological regions that exist in China,and the results show that the clustering results are in good agreement with the meteorological data obtained from the National Meteorological Science Data Center.This algorithm has a positive effect on the clustering analysis of massive meteorological data and deserves attention in scientific research activities.

A Cloud Framework for High Spatial Resolution Soil Moisture Mapping from Radar and Optical Satellite Imageries

Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.

LuoJiaAI:A cloud-based artificial intelligence platform for remote sensing image interpretation

The rapid processing,analysis,and mining of remote-sensing big data based on intelligent interpretation technology using remote-sensing cloud computing platforms(RS-CCPs)have recently become a new trend.The existing RS-CCPs mainly focus on developing and optimizing high-performance data storage and intelligent computing for common visual representation,which ignores remote sensing data characteristics such as large image size,large-scale change,multiple data channels,and geographic knowledge embedding,thus impairing computational efficiency and accuracy.We construct a LuoJiaAI platform composed of a standard large-scale sample database(LuoJiaSET)and a dedicated deep learning framework(LuoJiaNET)to achieve state-of-the-art performance on five typical remote sensing interpretation tasks,including scene classification,object detection,land-use classification,change detection,and multi-view 3D reconstruction.The details of the LuoJiaAI application experiment can be found at the white paper for LuoJiaAI industrial application.In addition,LuoJiaAI is an open-source RS-CCP that supports the latest Open Geospatial Consortium(OGC)standards for better developing and sharing Earth Artificial Intelligence(AI)algorithms and products on benchmark datasets.LuoJiaAI narrows the gap between the sample database and deep learning frameworks through a user-friendly data-framework collaboration mechanism,showing great potential in high-precision remote sensing mapping applications.

China’s EarthLab-Forefront of Earth System Simulation Research

This article introduces“EarthLab”,a major new Earth system numerical simulation facility developed in China.EarthLab is a numerical simulation system for a physical climate system,an environmental system,an ecological system,a solid earth system,and a space weather system as a whole with a high-performance scientific computing platform.EarthLab consists of five key elements-namely:a global earth numerical simulation system,a regional high-precision simulation system,a supercomputing support and management system,a database,data assimilation and visualization system,and a high-performance computing system for earth sciences.EarthLab helps to study the atmosphere,hydrosphere,cryosphere,lithosphere,and biosphere,as well as their interactions,to improve the accuracy of predictions by integrating simulations and observations,and to provide a scientific foundation for major issues such as national disaster prevention and mitigation.The construction and operation of EarthLab will involve close cooperation with joint contributions and shared benefits.

Rule of prescribing traditional Chinese medicine in the treatment of pneumoconiosis basedon association rules and k-means clustering algorithm

Objective:To analyze the rule of prescribing traditional Chinese medicine for treating pneumoconiosis,so as to provide reference for differential diagnosis and treatment of pneumoconiosis as well as for the development of new drugs for treatingthe disease.Methods:We searched China National Knowledge Infrastructure,Wanfang Database and VIP Chinese PublicationDatabase to retrieve relevant literatures which were then screened according to the enrollment criteria to establish a prescriptiondatabase of traditional Chinese medicine for the treatment of pneumoconiosis.The inheritance calculation platform of traditionalChinese medicine was used to analyze the prescribing rule of traditional Chinese medicine in the treatment of pneumoconiosisbased on association rules,k-means clustering algorithm and regression model analysis.Results:A total of 131 related literature were preliminarily selected,from which 97 prescriptions of traditional Chinese medicine with a total of 195 herbs were included.The most frequently prescribed herbs included Radix astragali,Platycodon grandiflorum,Pinellia ternata,licorice,Codonopsispilosula,Salvia miltiorrhiza,bitter almond etc.A total of 14 association rules,13 high-frequency herb pairs were found and 5groups of formulas were revealed by cluster analysis.Conclusion:The prescriptions for the treatment of pneumoconiosis are mainly composed of herbs for tonifying deficiency,resolving phlegm,relieving cough and asthma,activating blood circulation and removingblood stasis,which are supplemented with herbs for clearing heat,relieving appearance,regulating qi,promoting waterand permeating dampness,etc.,The prescribing rules reflect the basic pathological characteristics of lung deficiency and collateral arthralgia in pneumoconiosis,which provides some ideas for the clinical differentiation and treatment of pneumoconiosis in traditionalChinese medicine.It also provides reference for the research and development of new treatment methods.

Three Dimension Finite Element Analysis of the Influence Factors of Stress Responses in the Roadbed and Ground under a Moving Load

Focusing on the vibration of the roadbed and ground induced by high-speed train load, a three dimensional finite element model which includes the roadbed and horizontal layered site is established to study how the site conditions, the load moving speed and the depth of the soil element influence the soil element stress response. Based on a track-subsoil analytical model in which the rail is simulated as an Euler-Bernoulli beam resting on Winkler foundation in the vertical plane, the reaction force between the sleeper and roadbed excited by a single axle is presented, and then that is exerted on relevant elements to simulate the moving load. The dynamic response in the roadbed and subsoil excited by a single axle moving load is computed based on the parallel computing platform of the ABAQUS finite element software, and the stress time-history, stress path and curves of the principal stress axes rotation of the soil element under the track are presented. The results show that： the soil element stress path is an apple-shaped curve in the horizontal shear stress τd versus the stress difference （σsh - σch ）/2 coordinate system; the principal stress axes rotate 180° for the soil element under the load moving line during the load running, and the stress state changes from the pure shear to triaxial shear and then back to the pure shear again. The element dynamic stress increases as the moving load speed increases, which increases sharply when the load speed approaches the Rayleigh wave velocity of soil layer; the site conditions and the soil element depth affect the soil element stress path significantly.

Nonlinear finite-element-based structural system failure probability analysis methodology for gravity dams considering correlated failure modes

The structural system failure probability(SFP) is a valuable tool for evaluating the global safety level of concrete gravity dams.Traditional methods for estimating the failure probabilities are based on defined mathematical descriptions,namely,limit state functions of failure modes.Several problems are to be solved in the use of traditional methods for gravity dams.One is how to define the limit state function really reflecting the mechanical mechanism of the failure mode;another is how to understand the relationship among failure modes and enable the probability of the whole structure to be determined.Performing SFP analysis for a gravity dam system is a challenging task.This work proposes a novel nonlinear finite-element-based SFP analysis method for gravity dams.Firstly,reasonable nonlinear constitutive modes for dam concrete,concrete/rock interface and rock foundation are respectively introduced according to corresponding mechanical mechanisms.Meanwhile the response surface(RS) method is used to model limit state functions of main failure modes through the Monte Carlo(MC) simulation results of the dam-interface-foundation interaction finite element(FE) analysis.Secondly,a numerical SFP method is studied to compute the probabilities of several failure modes efficiently by simple matrix integration operations.Then,the nonlinear FE-based SFP analysis methodology for gravity dams considering correlated failure modes with the additional sensitivity analysis is proposed.Finally,a comprehensive computational platform for interfacing the proposed method with the open source FE code Code Aster is developed via a freely available MATLAB software tool(FERUM).This methodology is demonstrated by a case study of an existing gravity dam analysis,in which the dominant failure modes are identified,and the corresponding performance functions are established.Then,the dam failure probability of the structural system is obtained by the proposed method considering the correlation relationship of main failure modes on the basis of the mechanical mechanism analysis with the MC-FE simulations.

An Early Evaluation and Comparison of Three Private Cloud Computing Software Platforms

Cloud computing, after its success as a commercial infrastructure, is now emerging as a private infrastructure. The software platforms available to build private cloud computing infrastructure vary in their performance for management of cloud resources as well as in utilization of local physical resources. Organizations and individuals looking forward to reaping the benefits of private cloud computing need to understand which software platform would provide the efficient services and optimum utilization of cloud resources for their target applications. In this paper, we present our initial study on performance evaluation and comparison of three cloud computing software platforms from the perspective of common cloud users who intend to build their private clouds. We compare the performance of the selected software platforms from several respects describing their suitability for applications from different domains. Our results highlight the critical parameters for performance evaluation of a software platform and the best software platform for different application domains.

A Solution of Grid Computing Flow Using MDA Methodology

This paper presents an approach to build a flow of grid services named GFlow. This approach converts all of the services＇ interfaces in globus toolkit 3 into platform independent model format. The conversion uses eclipse modeling framework plug-ins and graphical editing framework plug-ins to parse the models into platform specific models, which are responsible for implementation of grid services＇ clients and servers and their automatic deployment. This paper emphasizes on design method, which uses model drive architecture, and design process, which uses model-view-control.

MobSafe:Cloud Computing Based Forensic Analysis for Massive Mobile Applications Using Data Mining

With the explosive increase in mobile apps, more and more threats migrate from traditional PC client to mobile device. Compared with traditional Win＋Intel alliance in PC, Android＋ARM alliance dominates in Mobile Internet, the apps replace the PC client software as the major target of malicious usage. In this paper, to improve the security status of current mobile apps, we propose a methodology to evaluate mobile apps based on cloud computing platform and data mining. We also present a prototype system named MobSafe to identify the mobile app＇s virulence or benignancy. Compared with traditional method, such as permission pattern based method, MobSafe combines the dynamic and static analysis methods to comprehensively evaluate an Android app. In the implementation, we adopt Android Security Evaluation Framework （ASEF） and Static Android Analysis Framework （SAAF）, the two representative dynamic and static analysis methods, to evaluate the Android apps and estimate the total time needed to evaluate all the apps stored in one mobile app market. Based on the real trace from a commercial mobile app market called AppChina, we can collect the statistics of the number of active Android apps, the average number apps installed in one Android device, and the expanding ratio of mobile apps. As mobile app market serves as the main line of defence against mobile malwares, our evaluation results show that it is practical to use cloud computing platform and data mining to verify all stored apps routinely to filter out malware apps from mobile app markets. As the future work, MobSafe can extensively use machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.

A New Process and Framework for Direct Anonymous Attestation Based on Symmetric Bilinear Maps

For the problem of the original direct anonymous attestation （DAA） scheme＇s complexity and great time consumption, a new DAA scheme based on symmetric bilinear pairings is presented, which gives a practical solution to ECC-based TPM in protecting the privacy of the TPM. The scheme still includes five procedures or algorithms： Setup, Join, Sign, Verify and Rogue tagging, but gets rid of zero-knowledge proof and takes on a new process and framework, of which the main operations are addition, scalar multiplication and bilinear maps on supersingular elliptic curve systems. Moreover, the scheme adequately utilizes the properties of bilinear maps as well as the signature and verification of the ecliptic curve system itself. Compared with other schemes, the new DAA scheme not only satis- fies the same properties, and shows better simplicity and high effi- ciency. This paper gives not only a detailed security proof of the proposed scheme, but also a careful performance analysis by comparing with the existing DAA schemes.

Intelligent and connected vehicles： Current status and future perspectives

Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.