The Mode of Data Exchange between PHRDC and HIS

参照国家有关个人健康档案的标准。分析HIS与PHRDC之间门诊、住院等不同医疗信息的数据交换时机及不同类型医院HIS与PHRDC的数据交换方式。以研究医疗机构与个人健康档案数据中心之间接口。并设计不同的交换方式和数据交换时机。针对不同医疗信息、医疗机构规模，提出不同的数据交换时机和交换方式，实现个人健康档案数据中心与HIS数据交换根据固化医疗信息的特点择时上传。并能挑选符合自身实际的数据交换方式。

High-speed broadband data acquisition system based on FPGA

A field-programmable gate array(FPGA)based high-speed broadband data acquisition system is designed.The system has a dual channel simultaneous acquisition function.The maximum sampling rate is 500 MSa/s and bandwidth is200 MHz,which solves the large bandwidth,high-speed signal acquisition and processing problems.At present,the data acquisition system is successfully used in broadband receiver test systems.

Implementing Marine XML for Observed CTD Data in a Marine Data Exchange Platform

In order to archive,quality control and disseminate a large variety of marine data in a marine data exchange platform,a marine XML has been developed to encapsulate marine data,which provides an efficient means to store,transfer and display marine data. This paper first presents the details of the main marine XML elements and then gives an example showing how to transform CTD-observed data into Marine XML format,which illustrates the XML encapsulation process of marine observed data.

Data Exchange in Grid Workflow

In existing web services-based workflow, data exchanging across the web services is centralized, the workflow engine intermediates at each step of the application sequence. However, many grid applications, especially data intensive scientific applications, require exchanging large amount of data across the grid services. Having a central workflow engine relay the data between the services would resu＇lts in a bottleneck in these cases. This paper proposes a data exchange model for individual grid workflow and multiworkflows composition respectively. The model enables direct communication for large amounts of data between two grid services. To enable data to exchange among multiple workflows, the bridge data service is used.

If real-time route and high-speed data is important,GoTa is vital.

GoTaTM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

If real-time route and high-speed data is important, GoTa is vital.

GoTa TM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring

If real-time route and high-speed data is important, GoTa is vital.

Go Tafrom ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration

In recent years,with the rapid development of high-speed railways(HSRs),power interruptions or disturbances in traction power supply systems have become increasingly dangerous.However,it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents.To coordinate the power quality data of both traction power supply systems(TPSSs)and high-speed trains(HSTs),a monitoring and assessing system is proposed to access the power quality issues on HSRs.By integrating train monitoring,traction substation monitoring and data center,this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs,but also conducts a comprehensive assessment of operational quality for train-network systems.Based on a large number of monitoring data,the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

Designing and Implementing an Advanced Big Data Governance Platform

Contemporary mainstream big data governance platforms are built atop the big data ecosystem components,offering a one-stop development and analysis governance platform for the collection,transmission,storage,cleansing,transformation,querying and analysis,data development,publishing,and subscription,sharing and exchange,management,and services of massive data.These platforms serve various role members who have internal and external data needs.However,in the era of big data,the rapid update and iteration of big data technologies,the diversification of data businesses,and the exponential growth of data present more challenges and uncertainties to the construction of big data governance platforms.This paper discusses how to effectively build a data governance platform under the big data system from the perspectives of functional architecture,logical architecture,data architecture,and functional design.

JSON-ASR:A lightweight data storage and exchange format for automatic systematic reviews of TCM

Objectives:The aim of this study was to investigate and develop a data storage and exchange format for the process of automatic systematic reviews(ASR)of traditional Chinese medicine(TCM).Methods:A lightweight and commonly used data format,namely,JavaScript Object Notation(JSON),was introduced in this study.We designed a fully described data structure to collect TCM clinical trial information based on the JSON syntax.Results:A smart and powerful data format,JSON-ASR,was developed.JSON-ASR uses a plain-text data format in the form of key/value pairs and consists of six sections and more than 80 preset pairs.JSON-ASR adopts extensible structured arrays to support the situations of multi-groups and multi-outcomes.Conclusion:JSON-ASR has the characteristics of light weight,flexibility,and good scalability,which is suitable for the complex data of clinical evidence.

To Overcome the Obstacle of Data Exchange to Increase the Utilization Efficiency of Accounting Data

On Nov.4th, AQSIQ (General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China), SAC (Standardization Administration of China), National Audit Office of China (CNAO), and National Ministry of Finance of China jointly held the conference press on the national standard of Information Technology-Data Interface of Accounting Software (GB/T 19581-2004) in Beijing. The standard was approved and issued on Sept. 20, 2004 by AQSIQ and SAC, and it would come into effect all over the whole nation from January 1st, 2005.

A Modified Generative Adversarial Network for Fault Diagnosis in High-Speed Train Components with Imbalanced and Heterogeneous Monitoring Data

Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To address this issue,synthetic minority methods for enhancing data have been proved to be effective in many applications.Generative adversarial networks(GANs),capable of automatic features extraction,can also be adopted for augmenting the faulty samples.However,the monitoring data of a complex system may include not only continuous signals but also discrete/categorical signals.Since the current GAN methods still have some challenges in handling such heterogeneous monitoring data,a Mixed Dual Discriminator GAN(noted as M-D2GAN)is proposed in this work.In order to render the expanded fault samples more aligned with the real situation and improve the accuracy and robustness of the fault diagnosis model,different types of variables are generated in different ways,including floating-point,integer,categorical,and hierarchical.For effectively considering the class imbalance problem,proper modifications are made to the GAN model,where a normal class discriminator is added.A practical case study concerning the braking system of a high-speed train is carried out to verify the effectiveness of the proposed framework.Compared to the classic GAN,the proposed framework achieves better results with respect to F-measure and G-mean metrics.

Application of Big Data Technology in Evaluation of Operating Status of High-pressure Hydrogenation Heat Exchanger

The high-pressure hydrogenation heat exchanger is an important equipment of the refinery, but it is exposed to the problem of leakage caused by ammonium salt corrosion. Therefore, it is very important to evaluate the operating status of the hydrogenation heat exchanger. To improve the method for evaluating the operating status of hydrogenation heat exchangers by using the traditional method, this paper proposes a new method for evaluating the operation of hydrogenation heat exchangers based on big data. To address the noisy data common in the industry, this paper proposes an automated noisy interval detection algorithm. To deal with the problem that the sensor parameters have voluminous and unrelated dimensions, this paper proposes a key parameter detection algorithm based on the Pearson correlation coefficient. Finally, this paper presents a system-based health scoring algorithm based on PCA(Principal Component Analysis) to assist site operators in assessing the health of hydrogenation heat exchangers. The evaluation of the operating status of the hydrorefining heat exchange device based on big data technology will help the operators to more accurately grasp the status of the industrial system and have positive guiding significance for the early warning of the failure.

Key technology of ship product data exchange based on STEP

In this paper, in order to implement the share and exchange of the ship product data, a new kind of global function model is established. By researching on the development and trend of the application of ship STEP (standard for the exchange of product model data) standards, the AIM (application interpreted model) of AP216 is developed and improved as an example, aiming at the characteristics and practical engineering of ship industry in our country. The data exchange interfaces are formed based on STEP in the CAD/CAM for the ship by all function modules and shared databases under the global function model. The share and exchange of all information and data are solved in the design, manufacture and all life-cycle of ship products among different computer application systems. The research work makes foundation for the ship industry informatization.

An Optimal Feed Interpolator Based on G^2 Continuous Bézier Curves for High-Speed Machining of Linear Tool Path

A numerical control (NC) tool path of digital CAD model is widely generated as a set of short line segments in machining. However, there are three shortcomings in the linear tool path, such as discontinuities of tangency and curvature, huge number of line segments, and short lengths of line segments. These disadvantages hinder the development of high speed machining. To smooth the linear tool path and improve machining efficiency of short line segments, this paper presents an optimal feed interpolator based on G^2 continuous Bézier curves for the linear tool path. First, the areas suitable for fitting are screened out based on the geometric characteristics of continuous short segments (CSSs). CSSs in every area are compressed and fitted into a G^2 Continuous Bézier curve by using the least square method. Then a series of cubic Bézier curves are generated. However, the junction between adjacent Bézier curves is only G^0 continuous. By adjusting the control points and inserting Bézier transition curves between adjacent Bézier curves, the G^2 continuous tool path is constructed. The fitting error is estimated by the second-order Taylor formula. Without iteration, the fitting algorithm can be implemented in real-time environment. Second, the optimal feed interpolator considering the comprehensive constraints (such as the chord error constraint, the maximum normal acceleration, servo capacity of each axis, etc.) is proposed. Simulation and experiment are conducted. The results shows that the proposed method can generate smooth path, decrease the amount of segments and reduce machining time for machining of linear tool path. The proposed research provides an effective method for high-speed machining of complex 2-D/3-D profiles described by short line segments.

HOTCAP:a new software package for high-speed oscilloscopebased three-dimensional bunch charge and position measurement

A software package to be used in high-speed oscilloscope-basedthree-dimensionalbunch-by-bunch charge and position measurement is presented.The software package takes the pick-up electrode signal waveform recorded by the high-speed oscilloscope as input,and it calculates and outputs the bunch-by-bunch charge and position.In addition to enabling a three-dimensional observation of the motion of each passing bunch on all beam position monitor pick-up electrodes,it offers many additional features such as injection analysis,bunch response function reconstruction,and turn-by-turn beam analysis.The software package has an easy-to-understand graphical user interface and convenient interactive operation,which has been verified on the Windows 10 system.

Multi-Factor Password-Authenticated Key Exchange via Pythia PRF Service

Multi-factor authentication(MFA)was proposed by Pointcheval et al.[Pointcheval and Zimmer(2008)]to improve the security of single-factor(and two-factor)authentication.As the backbone of multi-factor authentication,biometric data are widely observed.Especially,how to keep the privacy of biometric at the password database without impairing efficiency is still an open question.Using the vulnerability of encryption(or hash)algorithms,the attacker can still launch offline brute-force attacks on encrypted(or hashed)biometric data.To address the potential risk of biometric disclosure at the password database,in this paper,we propose a novel efficient and secure MFA key exchange(later denoted as MFAKE)protocol leveraging the Pythia PRF service and password-to-random(or PTR)protocol.Armed with the PTR protocol,a master password pwd can be translated by the user into independent pseudorandom passwords(or rwd)for each user account with the help of device(e.g.,smart phone).Meanwhile,using the Pythia PRF service,the password database can avoid leakage of the local user’s password and biometric data.This is the first paper to achieve the password and biometric harden service simultaneously using the PTR protocol and Pythia PRF.

Blockchain-Based Secure and Fair IoT Data Trading System with Bilateral Authorization

These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling data.However,online data trading poses challenges in terms of security and fairness because the seller and the buyer may not fully trust each other.Therefore,in this paper,a blockchain-based secure and fair data trading system is proposed by taking advantage of the smart contract and matchmaking encryption.The proposed system enables bilateral authorization,where data trading between a seller and a buyer is accomplished only if their policies,required by each other,are satisfied simultaneously.This can be achieved by exploiting the security features of the matchmaking encryption.To guarantee non-repudiation and fairness between trading parties,the proposed system leverages a smart contract to ensure that the parties honestly carry out the data trading protocol.However,the smart contract in the proposed system does not include complex cryptographic operations for the efficiency of onchain processes.Instead,these operations are carried out by off-chain parties and their results are used as input for the on-chain procedure.The system also uses an arbitration protocol to resolve disputes based on the trading proof recorded on the blockchain.The performance of the protocol is evaluated in terms of off-chain computation overhead and on-chain gas consumption.The results of the experiments demonstrate that the proposed protocols can enable the implementation of a cost-effective data trading system.

Statistical delay distribution analysis on high-speed railway trains

The focus of this study is to explore the statis-tical distribution models of high-speed railway (HSR) train delays. Based on actual HSR operational data, the delay causes and their classification, delay frequency, number of affected trains, and space–time delay distributions are discussed. Eleven types of delay events are classified, and a detailed analysis of delay distribution for each classifica-tion is presented. Models of delay probability delay prob-ability distribution for each cause are proposed. Different distribution functions, including the lognormal, exponen-tial, gamma, uniform, logistic, and normal distribution, were selected to estimate and model delay patterns. The most appropriate distribution, which can approximate the delay duration corresponding to each cause, is derived. Subsequently, the Kolmogorov–Smirnov (K–S) test was used to test the goodness of fit of different train delay distribution models and the associated parameter values. The test results show that the distribution of the test data is consistent with that of the selected models. The fitting distribution models show the execution effect of the timetable and help in finding out the potential conflicts in real-time train operations.