Ground data transfer research in AMS-02

To increase the performance of bulk data transfer mission with ultra-long TCP （ transmission control protocol） connection in high-energy physics experiments, a series of experiments were conducted to explore the way to enhance the transmission efficiency. This paper introduces the overall structure of RC@ SEU （ regional center @ Southeast University） in AMS （alpha magnetic spectrometer）-02 ground data transfer system as well as the experiments conducted in CERNET （China Education and Research Network）/CERNET2 and global academic Internet. The effects of the number of parallel streams and TCP buffer size are tested. The test confirms that in the current circumstance of CERNET, to find the fight number of parallel TCP connections is the main method to improve the throughput. TCP buffer size tuning has little effect now, but may have good effects when the available bandwidth becomes higher.

Data Transfer Over the Internet for Real Time Applications

Efficient real time data exchange over the Internet plays a crucial role in the successful application of web-based systems. In this paper, a data transfer mechanism over the Internet is proposed for real time web based applications. The mechanism incorporates the eXtensible Markup Language （XML） and Hierarchical Data Format （HDF） to provide a flexible and efficient data format. Heterogeneous transfer data is classified into light and heavy data, which are stored using XML and HDF respectively; the HDF data format is then mapped to Java Document Object Model （JDOM） objects in XML in the Java environment. These JDOM data objects are sent across computer networks with the support of the Java Remote Method Invocation （RMI） data transfer infrastructure. Client＇s defined data priority levels are implemented in RMI, which guides a server to transfer data objects at different priorities. A remote monitoring system for an industrial reactor process simulator is used as a case study to illustrate the proposed data transfer mechanism.

Design and FPGA verification of a novel reliable real-time data transfer system

Considering the increasing use of information technology with established standards, such as TCP/IP and XML in modem industrial automation, we present a high cost performance solution with FPGA （field programmable gate array） implementation of a novel reliable real-time data transfer system based on EPA （Ethemet for plant automation） protocol and IEEE 1588 standard. This combination can provide more predictable and real-time communication between automation equipments and precise synchronization between devices. The designed EPA system has been verified on Xilinx Spartan3 XC3S1500 and it consumed 75% of the total slices. The experimental results show that the novel industrial control system achieves high synchronization precision and provides a 1.59-ps standard deviation between the master device and the slave ones. Such a real-time data transfer system is an excellent candidate for automation equipments which require precise synchronization based on Ethemet at a comparatively low price.

Does Checklist Implementation Improve Quantity of Data Transfer: An Observation in Postanesthesia Care Unit (PACU)

Background: Omission of patient information in perioperative communication is closely linked to adverse events. Use of checklists to standardize the handoff in the post anesthesia care unit (PACU) has been shown to effectively reduce medical errors. Objective: Our study investigates the use of a checklist to improve quantity of data transfer during handoffs in the PACU. Design: A cross-sectional observational study. Setting: PACU at Memorial Sloan Kettering Cancer Center (MSKCC);June 13, 2016 through July 15, 2016. Patients, other participants: We observed the handoff reports between the nurses, PACU midlevel providers, anesthesia staff, and surgical staff. Intervention: A physical checklist was provided to all anesthesia staff and recommended to adhere to the list at all observed PACU handoffs. Main outcome measure: Quantity of reported handoff items during 60 pre- and 60 post-implementation of a checklist. Results: Composite value from both surgical and anesthesia reports showed an increase in the mean report of 8.7 items from pre-implementation period to 10.9 post-implementation. Given that surgical staff reported the mean of 5.9 items pre-implementation and 5.5 items post-implementation without intervention, improvements in anesthesia staff report with intervention improved the overall handoff data transfer. Conclusions: Using a physical 12-item checklist for PACU handoff increased overall data transfer.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Accelerating Data Transfer in Dataflow Architectures Through a Look-Ahead Acknowledgment Mechanism

The dataflow architecture,which is characterized by a lack of a redundant unified control logic,has been shown to have an advantage over the control-flow architecture as it improves the computational performance and power efficiency,especially of applications used in high-performance computing(HPC).Importantly,the high computational efficiency of systems using the dataflow architecture is achieved by allowing program kernels to be activated in a simultaneous manner.Therefore,a proper acknowledgment mechanism is required to distinguish the data that logically belongs to different contexts.Possible solutions include the tagged-token matching mechanism in which the data is sent before acknowledgments are received but retried after rejection,or a handshake mechanism in which the data is only sent after acknowledgments are received.However,these mechanisms are characterized by both inefficient data transfer and increased area cost.Good performance of the dataflow architecture depends on the efficiency of data transfer.In order to optimize the efficiency of data transfer in existing dataflow architectures with a minimal increase in area and power cost,we propose a Look-Ahead Acknowledgment(LAA)mechanism.LAA accelerates the execution flow by speculatively acknowledging ahead without penalties.Our simulation analysis based on a handshake mechanism shows that our LAA increases the average utilization of computational units by 23.9%,with a reduction in the average execution time by 17.4%and an increase in the average power efficiency of dataflow processors by 22.4%.Crucially,our novel approach results in a relatively small increase in the area and power consumption of the on-chip logic of less than 0.9%.In conclusion,the evaluation results suggest that Look-Ahead Acknowledgment is an effective improvement for data transfer in existing dataflow architectures.

The Way to Optimize the Right to Personal Data Portability in Chinese Practice——Based on Empirical Analysis of the Privacy Policies of 66 Mobile Apps

Although the existing legal norms and judicial practic-es can provide basic guidance for the right to personal data portabili-ty, it can be concluded that there are obstacles to the realization of this right through empirical research of the privacy policies of 66 mobile apps, such as whether they have stipulations on the right to personal data portability, whether they are able to derive copies of personal in-formation automatically, whether there are textual examples, whether ID verification is required, whether the copied documents are encrypt-ed, and whether the scope of personal information involved is consis-tent. This gap in practice, on the one hand, reflects the misunderstand-ing of the right to personal data portability, and on the other hand, is a result of the negative externalities, practical costs and technical lim-itations of the right to personal data portability. Based on rethinking the right to data portability, we can somehow solve practical problems concerning the right to personal data portability through multiple measures such as promoting the fulfillment of this right by legislation, optimizing technology-oriented operations, refining response process mechanisms, and enhancing system interoperability.

Decision Model of Knowledge Transfer in Big Data Environment

A decision model of knowledge transfer is presented on the basis of the characteristics of knowledge transfer in a big data environment.This model can determine the weight of knowledge transferred from another enterprise or from a big data provider.Numerous simulation experiments are implemented to test the efficiency of the optimization model.Simulation experiment results show that when increasing the weight of knowledge from big data knowledge provider,the total discount expectation of profits will increase,and the transfer cost will be reduced.The calculated results are in accordance with the actual economic situation.The optimization model can provide useful decision support for enterprises in a big data environment.

Multi-Sinusoidal Waveform Shaping for Integrated Data and Energy Transfer in Aging Channels

Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.

Pattern recognition and data mining software based on artificial neural networks applied to proton transfer in aqueous environments

In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories： transfer ＇occurred＇ and transfer ＇not occurred＇. The goal of this paper is to evaluate the use of artificial neural networks in the classification of proton transfer events, based on the feed-forward back propagation neural network, used as a classifier to distinguish between the two transfer cases. In this paper, we use a new developed data mining and pattern recognition tool for automating, controlling, and drawing charts of the output data of an Empirical Valence Bond existing code. The study analyzes the need for pattern recognition in aqueous proton transfer processes and how the learning approach in error back propagation （multilayer perceptron algorithms） could be satisfactorily employed in the present case. We present a tool for pattern recognition and validate the code including a real physical case study. The results of applying the artificial neural networks methodology to crowd patterns based upon selected physical properties （e.g., temperature, density） show the abilities of the network to learn proton transfer patterns corresponding to properties of the aqueous environments, which is in turn proved to be fully compatible with previous proton transfer studies.

跨城市人类移动行为预测研究综述

城市化进程积累了大量记录人类移动行为的时空数据,为研究人类移动行为建模及预测提供了良好的数据基础。在智慧城市建设背景下,跨城市人类移动预测是实现城市协同管理与治理的必然要求,时常面临数据匮乏以及数据分布不平衡等问题,传统机器学习方法难以取得理想的性能。因此,将人类移动相关知识从数据丰富的源城市迁移到数据稀疏乃至稀缺的目标城市至关重要。首先概述了现有跨城市人类移动行为预测研究所使用的数据集和评价指标,随后循序渐进地讨论人类个体和群体层面的跨城市移动预测问题并分类综述各自适用的研究方法。针对人类个体跨城市移动预测,主要分析协同过滤、矩阵分解、统计学习以及深度学习这4类模型方法的应用。针对人类群体跨城市移动预测,则聚焦知识迁移和元学习这两种面向少样本机器学习方法的应用。最后,展望了跨城市人类移动行为预测领域亟需解决的重要问题。

基于Panel-data的区际产业转移粘性分析

利用面板数据模型,以江苏省为例,对28个制造业的科技进步、产业集群、区域人力资本积累、沉没成本和资产专用性、劳动力跨区域流动、制度创新、政府阻力等因素对产业转移粘性的关系进行了实证研究,并依据各个因素的贡献率得出了跨区域产业转移的初步结论。

EpiData软件与SPSS软件数据文件的转接

EpiData软件是一款非常流行的数据输入与管理软件,但由于缺乏数据的统计分析功能,对于数据录入后的数据分析还需借助专业的统计分析软件进行,本文对如何应用EpiData软件与SPSS统计软件实现数据文件的转接作一简要介绍。

DataSocket技术与交互式网页

ＤａｔａＳｏｃｋｅｔ是一种新的实时数据传输技术，它本身又是一种ＡｃｔｉｖｅＸ控件，进一步开发后可以插入到 Ｗｅｂ页面中形成一个基于 Ｉｎｔｅｒｎｅｔ的虚拟仪器软面板。本文介绍了这一新技术并给出了一个应用实例。

Influence of Data Clouds Fusion From 3D RealTime Vision System on Robotic Group Dead Reckoning in Unknown Terrain

This paper proposes the solution of tasks set required for autonomous robotic group behavior optimization during the mission on a distributed area in a cluttered hazardous terrain.The navigation scheme uses the benefits of the original real-time technical vision system(TVS)based on a dynamic triangulation principle.The method uses TVS output data with fuzzy logic rules processing for resolution stabilization.Based on previous researches,the dynamic communication network model is modified to implement the propagation of information with a feedback method for more stable data exchange inside the robotic group.According to the comparative analysis of approximation methods,in this paper authors are proposing to use two-steps post-processing path planning aiming to get a smooth and energy-saving trajectory.The article provides a wide range of studies and computational experiment results for different scenarios for evaluation of common cloud point influence on robotic motion planning.

基于条件生成对抗网络与迁移学习的暂态电压稳定超前判别

为解决样本不平衡导致的暂态电压稳定判别准确性不足的问题以及实现暂态电压稳定超前判别,提出一种基于条件生成对抗网络(CGAN)与迁移学习的暂态电压稳定超前判别方法。考虑暂态电压稳定样本类型,利用CGAN定向扩增暂态电压样本集,解决样本不平衡问题,从而提升暂态电压稳定判别准确性;考虑到CGAN生成器与暂态电压时序预测模型具有相似的学习任务,将CGAN生成器模型迁移至暂态电压时序预测模型,结合工程判据实现暂态电压稳定超前判别,并进一步提升暂态电压稳定判别准确性。在CEPRI-VC暂态电压稳定分析系统中验证了所提方法的有效性。

使用WinSock控件和Internet Transfer控件的实例

通过笔者编制的上机考试系统程序的实例,给出了在VisualBasic语言编程中使用WinSock控件进行客户端与服务器的通信和使用InternetTransfer控件控制文件的网络传输的几种特殊方法,说明了如何使用AD和Data控件对考生数据库和试题数据库进行管理,并对考试系统中试题的选择提出了可行的办法.

阿尔茨海默病辅助诊断的多模态数据融合轻量级网络

单模态阿尔茨海默病辅助诊断方法缺少专业标注的影像数据,特征提取不稳定且要求高计算能力,为此融合核磁成像、正电子发射断层扫描影像数据和精神认知评分数据,提出多模态轻量级阿尔茨海默病辅助诊断网络(LightMoDAD).在影像特征提取模块中,去冗余卷积以提取局部特征,引入全局滤波用于提取全局特征,通过配准并相加实现多模态影像特征融合.在文本特征提取模块中,由可分离深度卷积提取精神认知评分数据特征与多模态影像特征融合,通过迁移学习增强特征判别性.采用多层感知器识别复杂的模式和特征,提高所提网络的分类准确率.在ADNI数据库中开展有效性验证实验,LightMoDAD的分类准确率、敏感性和特异性分别为0.980、0.985和0.975.实验结果表明,所提网络有助于提高医生诊断效率,具有移动端部署潜力.

Graphical-based data placement algorithm for cloud workflow

When workflow task needs several datasets from different locations m cloud, data transfer becomes a challenge. To avoid the unnecessary data transfer, a graphical-based data placement algo- rithm for cloud workflow is proposed. The algorithm uses affinity graph to group datasets while keeping a polynomial time complexity. By integrating the algorithm, the workflow engine can intelligently select locations in which the data will reside to avoid the unnecessary data transfer during the initial stage and runtime stage. Simulations show that the proposed algorithm can effectively reduce data transfer during the workflow＇ s execution.