The AME2012 atomic mass evaluation(Ⅰ).Evaluation of input data,adjustment procedures

This paper is the second part of the new evaluation of atomic masses, AME2012. From the results of a leastsquares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs to replace those of AME2003. The first table lists atomic masses. It is followed by a table of the influences of data on primary nuclides, a table of separation energies and reaction energies, and finally, a series of graphs of separation and decay energies. The last section in this paper lists all references to the input data used in Part I of this AME2012 and also to the data included in the NUBASE2012 evaluation （first paper in this issue）.

Input Data Dependency of a Genetic Algorithm to Solve the Set Covering Problem

A genetic algorithm to solve the set covering problem proposed in the literature had some improvements which gave better solutions, i.e., better chromosomes in the first starting population, taking full account of domain specific knowledge with sound programming skill. We have further investigated the input data dependency of their genetic algorithm, i.e., the dependency on costs and density. We have found that for input problem data sets with densities greater than or equal to 3%, our genetic algorithm is still practical both in computing time and approximation ratio.

Input database related uncertainty of Biome-BGCMuSo agroenvironmental model outputs

Gridded model assessments require at least one climatic and one soil database for carrying out the simulations.There are several parallel soil and climate database development projects that provide sufficient,albeit considerably different,observation based input data for crop model based impact studies.The input database related uncertainty of the Biome-BGCMuSo agro-environmental model outputs was investigated using three and four different gridded climatic and soil databases,respectively covering an area of nearly 100.000 km2 with 1104 grid cells.Spatial,temporal,climate and soil database selection related variances were calculated and compared for four model outputs obtained from 30-year-long simulations.The choice of the input database introduced model output variability that was comparable to the variability the year-to-year change of the weather or the spatial heterogeneity of the soil causes.Input database selection could be a decisive factor in carbon sequestration related studies as the soil carbon stock change estimates may either suggest that the simulated ecosystem is a carbon sink or to the contrary a carbon source on the long run.Careful evaluation of the input database quality seems to be an inevitable and highly relevant step towards more realistic plant production and carbon balance simulations.

Automation of input data to discrete event simulation for manufacturing: A review

Discrete event simulation(DES)is a well-established decision support tool in modeling work flows in manufacturing industry.But,there are an amount of practical and financial obstacles that deter the employment of this technology in industry.One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model.Another issue is the cost of integrating simulation applications with other manufacturing applications.These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing.This review presents the existing research studies in the literature that address the above issues,demonstrating in parallel the already implemented concepts.The scope of this review is to provide an overview of the input data phase,focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.

第五代PSU/NCAR中尺度模式(MM5)介绍Ⅱ:第一猜测场的形成(DATAGRID模块)

:通过对DATAGRID模块的主要功能、基本原理及其结构的介绍 ,同时对模块的操作使用方法给予了说明。并对模块的主要控制参数进行了较为详尽的讨论 ,最后 。

LSMW的Direct Input方法在SAP中的应用

LSMW为系统应用程序和产品的数据处理软件(SAP)提供批量数据导入平台,Direct Input方法是LSMW批量数据导入的方法之一。以上传采购订单为例,介绍了采用LSMW的Direct Input方法上传数据的步骤和方法。将LSMW的Direct Input方法应用于华能集团SAP中,显著提高了SAP启动时海量数据导入的速率,保证了SAP按时上线运行。

河南省大中型工业企业技术创新Panel Data模型分析

从投入-产出的角度对河南省各市地大中型工业企业技术创新的差异化进行研究.应用面板数据模型对18个市地大中型工业企业的技术创新投入对产出的结构影响进行深入分析,找出它们之间的结构差异并说明其存在的原因,为各市地提升大中型工业企业技术创新能力提供一些具有针对性的建议.

基于PANEL DATA模型的江苏医药产业研发投入效率实证研究

医药产业是我国重要的支柱产业之一,关系到国计民生和社会稳定,同时又具有高投入、高风险、高效益等特点,对经济增长的贡献不断提升。本文比较分析了江苏与山东等五省市医药制造业的科技创新总体情况,并在此基础上根据1997-2012年的面板数据对江苏等省市医药制造业研发经费的产出弹性进行测算,定量分析江苏医药产业研发经费投入的产出效率。

一个包含数据要素的经济增长模型:生产率效应与数据要素化

数字经济时代,数据成为独立生产要素,是科技创新的新引擎和经济高质量发展的新动能。从纯数字资产与数据匹配性投入共同组成数据要素化投入的角度理解数据生产要素化,使用数据匹配性投入综合得分对中国数据要素化投入进行时空分析和生产率效应分析。结果表明,中国数据要素化投入存在明显的区域差异,基于数据要素化投入对经济产出的积极作用,其对区域经济协调发展具有重要作用;数据匹配性投入价格持续下降会影响生产要素间的交互作用,数据生产要素的使用带来生产方式的根本变革;数据生产要素化基于数据间的互联互通和经济融合,能够加快数据确权,促进生产要素合理配置,从而推动产业创新和经济高质量发展。

DataGrid控件录入与编辑功能优化方法初探

首先介绍了DataGrid控件的不足,在此基础上探讨了如何对DataGrid控件的录入、编辑和显示等功能进行完善,阐述了DataGrid控件在地质信息三维可视化系统中的应用,从而较好地实现地质数据的录入、编辑和显示功能。

Impact of the arterial input function on microvascularization parameter measurements using dynamic contrast-enhanced ultrasonography

AIM: To evaluate the sources of variation influencing the microvascularization parameters measured by dynamic contrast-enhanced ultrasonography (DCE-US). METHODS: Firstly, we evaluated, in vitro , the impact of the manual repositioning of the ultrasound probe and the variations in flow rates. Experiments were conducted using a custom-made phantom setup simulating a tumor and its associated arterial input. Secondly, we evaluated, in vivo , the impact of multiple contrast agent injections and of examination day, as well as the influence of the size of region of interest (ROI) associated with the arterial input function (AIF). Experiments were conducted on xenografted B16F10 female nude mice. For all of the experiments, an ultrasound scanner along with a linear transducer was used to perform pulse inversion imaging based on linear raw data throughout the experiments. Semi-quantitative and quantitative analyses were performed using two signal-processing methods. RESULTS:In vitro , no microvascularization parameters, whether semi-quantitative or quantitative, were significantly correlated (P values from 0.059 to 0.860) with the repositioning of the probe. In addition, all semiquantitative microvascularization parameters were correlated with the flow variation while only one quantitative parameter, the tumor blood flow, exhibited P value lower than 0.05 (P = 0.004). In vivo , multiple contrast agent injections had no significant impact (P values from 0.060 to 0.885) on microvascularization parameters. In addition, it was demonstrated that semi-quantitative microvascularization parameters were correlated with the tumor growth while among the quantitative parameters, only the tissue blood flow exhibited P value lower than 0.05 (P = 0.015). Based on these results, it was demonstrated that the ROI size of the AIF had significant influence on microvascularization parameters: in the context of larger arterial ROI (from 1.17 ± 0.6 mm 3 to 3.65 ± 0.3 mm 3 ), tumor blood flow and tumor blood volume were correlated with the tumor growth, exhibiting P values lower than 0.001. CONCLUSION: AIF selection is an essential aspect of the deconvolution process to validate the quantitative DCE-US method.

Measuring Railway Efficiencies with Consideration of Input Congestion

Input congestion very likely existed in rail transport. However, early works measuring the rail transport efficiencies rarely took the input congestion into account;hence, the proposed strategies for enhancing efficiencies can be misleading. This study revisited the rail transport efficiencies with consideration of input congestion. We employed data envelopment analysis extension method to investigate the input congestion for some selected 24 European Union (EU) railways in 2006. The results indicated that there is no strong congestion in these 24 railways. However, 12 railways have been diagnosed with weak congestion in the available capacity of freight transport as well as the number of locomotives, 7 railways in the available capacity of passenger transport, and 4 railways in the number of employees. Based on our findings, the managerial implication is to contract the available capacity of freight transport (tonnages) as the most critical strategy, rather than laying-off the excess number of employees suggested by most previous studies, which did not consider the input congestion effects while measuring the rail transport efficiencies.

Augmented input estimation in multiple maneuvering target tracking

This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observations are assigned to the considered tracks.In real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done simply.In this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in computations.After DA,estimation and tracking should be done.Since in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is eliminated.This model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector.Some comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.

基于高通量监测数据的PMF源解析数据输入量研究

为探究数据输入量的变化对源解析结果的影响,以上海某工业区的大气重金属高通量监测数据为例,按不同数据量将监测数据分别输入至正定矩阵因子分解(Positive Matrix Factorization, PMF)模型中,通过考察模型中Q理论值(Qtheo)与Q计算值(Qtrue)的接近程度、源分类以及源贡献与研究区污染源分布特点的吻合情况,分析数据输入量对源解析结果的影响。结果显示:该区域大气重金属污染受工业生产主导(64.44%),其次是扬尘(19.60%)和交通运输(15.96%)。通过对数据量的考察,发现输入量为60~120时能够得出研究区域的污染源数量与贡献率,但考虑到测试成本、获取数据的时间,认为输入量为60~80时,也能得出合理的源解析结果。短期高通量的分钟级数据集,有益于PMF模型输出高精密度、高时效性的源解析结果,是解决应急污染监控的最佳手段。

生命体征智能采录系统在监护患者护理中的应用研究

目的探索生命体征智能采录系统在监护患者护理中的应用效果,用以解决原有手工抄录生命体征数据带来的效率低下、误差率高问题,推进全院一体化生命体征数据监测中心的建立。方法利用设备集成模块,将各类生命体征测量设备统一接入中心监护系统,中心监护系统将接收到的生命体征数据进行统一化、标准化和智能化处理,再通过数据网关转发数据至医院各业务系统,完成生命体征智能采录系统的设计,实现医疗设备应用过程中,采集数据的自动化传输、智能化存储和标准化应用。选取5个普通病房和5个重症监护室的生命体征数据采集时间及采录准确性、护理人员满意度作为评价指标对生命体征智能采录系统的效果进行分析。结果生命体征智能采录系统应用后,普通病房及重症病房各科室的生命体征数据采录时间均较系统应用前显著降低,每天平均节省时间分别为14.14~72.59 h、17.00~81.70 h;数据采录准确性和护理人员满意度均高于系统应用前,且差异均有统计学意义(P<0.05)。结论生命体征智能采录系统的应用,实现了生命体征测量设备互联、数据互通、生命体征数据采集流程的数字化,提升了护理安全和护理质量,可帮助医生动态监测患者病情变化并作出准确诊断。

Novel Grouped Probability Data Association Algorithm for MIMO Detection

To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.

SmartPlantReference Data Plus在SP3D复杂几何尺寸数据建立上的应用

为使设计人员更快更容易使用SPRD功能,Intergraph提供了一套基于Java技术开发SPRD(标准数据库)模块功能数据库SDB,用以建立材料编码、标准尺寸数据库、材料等级库。SDB平台数据需人工逐个逐行输入,在复杂几何尺寸数据的录入上费时费力,因此Intergraph又以.Net技术为基础开发的SPRD另一界面Smart Plant Reference Data Plus,与传统的Java技术开发的界面共同管理一个数据库,经过探索发现Smart Plant Reference Data Plus在数据量最大、耗时最长、最枯燥的外形尺寸的数据库录入中具备较大优势,尤其方便了复杂几何尺寸数据的建立。

基于时频域联合数据辅助MIMO均衡算法的多维度复用千公里级相干传输系统

基于少模光纤的模式复用系统利用单根纤芯中的正交模式实现各独立信道的并行传输,能够有效提升系统容量,解决单模光纤系统的容量危机.本文联合使用模式复用、波分复用与偏振复用技术,基于六模渐变型光纤实现了80个波长通道下32 Gbaud四模双偏振16阶正交振幅调制信号的1000 km相干传输,并在接收端使用时频域联合数据辅助8×8多输入多输出最小均方算法,以补偿由光纤传输导致的模式耦合及模间色散等线性损伤.与传统的纯时域或纯频域多输入输出最小均方均衡算法相比,该算法分别实现了57.1%的收敛速度提升与25.1%的收敛误差下降.经过1000 km少模光纤传输后,80通道每个模式及偏振态的误码率均低于开销为20%的软判决前向纠错编码阈值2.4×10^(-2),系统净速率达68.2 Tbit/s.

含有输入时滞的非线性系统的输出反馈采样控制

针对含有输入时滞和低阶非线性项的非线性系统,提出一种基于采样机制的无记忆输出反馈控制方法.该方法移除了传统预测控制方法预测映射难以确定的限制,同时避免了时滞依赖方法对过去时刻状态信息的依赖性,在实际中更易实现.首先,根据系统输出在采样时刻的信息,利用加幂积分技术和齐次占优思想设计了无记忆输出反馈采样控制器.然后,利用齐次系统理论提出了闭环系统的稳定性条件.最后,仿真结果验证了所提方法的有效性和优越性.