Consistency check of degradation mechanism between natural storage and enhancement test for missile servo system

Reliability enhancement testing(RET) is an accelerated testing which hastens the performance degradation process to surface its inherent defects of design and manufacture. It is an important hypothesis that the degradation mechanism of the RET is the same as the one of the normal stress condition. In order to check the consistency of two mechanisms, we conduct two enhancement tests with a missile servo system as an object of the study, and preprocess two sets of test data to establish the accelerated degradation models regarding the temperature change rate that is assumed to be the main applied stress of the servo system during the natural storage. Based on the accelerated degradation models and natural storage profile of the servo system, we provide and demonstrate a procedure to check the consistency of two mechanisms by checking the correlation and difference of two sets of degradation data. The results indicate that the two degradation mechanisms are significantly consistent with each other.

Blockchain Consistency Check Protocol for Improved Reliability

Blockchain is a technology that provides security features that can be used for more than just cryptocurrencies.Blockchain achieves security by saving the information of one block in the next block.Changing the information of one block will require changes to all the next block in order for that change to take effect.Which makes it unfeasible for such an attack to happen.However,the structure of how blockchain works makes the last block always vulnerable for attacks,given that its information is not saved yet in any block.This allows malicious node to change the information of the last block and generate a new block and broadcast it to the network.Given that the nodes always follow the longer chain wins rule,the malicious node will win given that it has the longest chain in the network.This paper suggests a solution to this issue by making the nodes send consistency check messages before broadcasting a block.If the nodes manage to successfully verify that the node that generated a new block hasn’t tampered with the blockchain than that block will be broadcasted.The results of the simulation show suggested protocol provided better security compared to the regular blockchain.

Model Checking-Based Testing of Web Applications

A formal model representing the navigation behavior of a Web application as the Kripke structure is proposed and an approach that applies model checking to test case generation is presented. The Object Relation Diagram as the object model is employed to describe the object structure of a Web application design and can be translated into the behavior model. A key problem of model checking-based test generation for a Web application is how to construct a set of trap properties that intend to cause the violations of model checking against the behavior model and output of counterexamples used to construct the test sequences. We give an algorithm that derives trap properties from the object model with respect to node and edge coverage criteria.

基于深度学习的函数名一致性检查及推荐方法

函数是大多数传统编程语言中聚合行为的最小命名单元,函数名的可读性对于程序员理解程序功能及不同模块之间的交互有着至关重要的作用,低质量的函数名会使开发人员感到困惑,增加代码中的坏味道,进而引发由API误用而导致的软件缺陷.为此,提出一种基于深度学习的函数名一致性检查及推荐方法,该方法被命名为DMName.首先,对于给定的目标函数源码,分别构建其内部上下文、交互上下文、兄弟上下文和封闭上下文,合并后得到上下文信息标记序列,然后利用FastText词嵌入技术将标记序列转换为上下文表示向量序列,输入到seq2seq模型编码器中,引入Copy机制和Coverage机制分别解决OOV问题和重复解码问题,输出目标函数名预测结果的向量序列,借助双通道CNN分类器进行函数名的一致性判断,若不一致则根据向量空间相似度匹配直接映射获得推荐的函数名.实验结果表明,DMName方法在函数名一致性检查任务和函数名推荐任务中的F1值分别达到82.65%和73.31%,比目前最优的DeepName方法分别提高2.01%和2.96%.最后,在GitHub大规模开源项目lancia中对DMName方法进行验证,挖掘得到16个函数名不一致问题并进行合理的名称推荐,进一步证实DMName方法的有效性.

随机误差传递的高空气象秒级数据快速校验方法

【目的】为保证气象预报结果的准确性。【方法】提出了考虑随机误差传递的高空气象秒级数据快速校验方法。对高空气象秒级数据进行预处理,包括数据中心化处理、特征点提取。数据中心化的处理方式为实施各组数据的加权平均处理,获得新的数据组作为基准数据;特征点提取使用的处理方法为遍历法,需要遍历全部数据点。考虑数据获取过程中的随机误差传递情况,对预处理后的高空气象秒级数据实施空间一致性检查、内部一致性检查。应用集合经验模态分解EEMD(Ensemble Empirical Mode Decomposition)算法与对比源反演CSI(Contrast Source Inversion)算法构建基于CSI-EEMD的高空气象秒级数据快速校验模型,实施数据得到快速校验。【结果】测试结果表明,该方法能够实现4个气象站数据的快速校验,校验结果的均方根误差与平均绝对误差均低于0.1,实现了数据的质量控制。【结论】将该方法应用于气象站数据校验中,可以实现精准度的数据校验,具有一定的实用价值。

EOS^(TM)3D影像系统诊断复发性髌骨脱位的可靠性和稳定性

目的 探讨EOS^(TM)3D影像系统诊断复发性髌骨脱位的可靠性和稳定性。方法 回顾性分析2022年3月至2023年3月西安交通大学附属红会医院运动医学中心收治的22例(26膝)复发性髌骨脱位病人的影像学资料,两位影像学医生同时使用EOS^(TM)系统测量病人下肢力线,使用sterEOS软件对影像图片进行3D模型重建,并在三维模型中测量胫骨结节-股骨滑车沟(tibial tubercle-trochlear groove,TTTG)间距,记录每次测量所需的时间和相关参数。所有病人同期进行常规膝关节CT扫描及三维重建。将EOS^(TM)3D影像和CT扫描测量的TT-TG数值进行比较,采用一致性检验研究和Bland-Altman分析图评价测量结果数据的可靠性和稳定性。结果 进行EOSTM下肢力线测量时,不同测量者间测量的股骨和胫骨长度、膝关节内外翻角度及股骨胫骨旋转角度之间差异无统计学意义(P>0.05)。病人常规下肢CT扫描及三维重建测量时间为(21.8±3.2)min(13~29 min),EOSTM3D测量时间为(6.3±1.8)min(4~11 min),差异有统计学意义(t=12.693,P<0.001)。两位医生使用EOS^(TM)3D测量TT-TG值的组内相关系数为0.791,使用常规CT测量的组内相关系数为0.843,两种测量方法组内一致性均较好。Bland-Altman分析结果显示两位测量者分别有96.2%(25/26)、92.3%(24/26)的点位于±1.96标准差范围内,显示使用常规CT三维重建和EOS^(TM)3D测量TT-TG值具备较好的一致性和稳定性。结论 使用EOS^(TM)3D影像系统测量复发性髌骨脱位病人的TT-TG值,具有良好的可靠性及可重复性,具有检查时间短、辐射低等优势,是评估此类病人下肢力线数据的一种快捷、可靠及稳定的方法。

Global consistency check of AIRS and IASI total CO2 column concentrations using WDCGG ground-based measurements

This article describes a global consistency check of CO2 satellite retrieval products from the Atmospheric Infrared Sounder （AIRS） and Infrared Atmospheric Sounding Interferometer （IASI） using statistical analysis and data from the World Data Centre for Greenhouse Gases （WDCGG）. We use the correlation coefficient （r）, relative difference （RD）, root mean square errors （RMSE）, and mean bias error （MBE） as evaluation indicators for this study. Statistical results show that a linear positive correlation between AIRS/IASI and WDCGG data occurs for most regions around the world. Temporal and spatial variations of these statistical quantities reflect obvious differences between satellite-derived and ground-based data based on geographic position, especially for stations near areas of intense human activities in the Northern Hemisphere. It is noteworthy that there appears to be a very weak correlation between AIRS/IASI data and ten ground- based observation stations in Europe, Asia, and North America. These results indicate that retrieval products from the two satellite-based instruments studied should be used with great caution.

The Complexity of Checking Consistency of Pedigree Information and Related Problems

Consistency checking is a fundamental computational problem in genetics.Given a pedigree and information on the genotypes (of some) of the individuals in it, the aim ofconsistency checking is to determine whether these data are consistent with the classic Mendelianlaws of inheritance. This problem arose originally from the geneticists'' need to filter their inputdata from erroneous information, and is well motivated from both a biological and a sociologicalviewpoint. This paper shows that consistency checking is NP-complete, even with focus on a singlegene and in the presence of three alleles. Several other results on the computational complexity ofproblems from genetics that are related to consistency checking are also offered. In particular, itis shown that checking the consistency of pedigrees over two alleles, and of pedigrees withoutloops, can be done in polynomial time.

导弹运动仿真模型验证方法

基于飞行试验数据开展导弹运动仿真模型验证是仿真模型定型的可行途径,本文系统介绍了基于动态性能一致性检验定性和基于静态性能一致性检验定量相结合的验证方法,确定了导弹运动模型验证指标和可信度计算方法,结果表明,尽管飞行试验样本有限,只要方法恰当,可以得到较好的验证结果。

一种纠删码条带化数据的一致性检查方法

纠删码冗余策略常用于分布式存储系统.在纠删码数据中,条带是一致性检查的基本单元,每个条带包含多份原始数据单元和校验数据单元.为了减少纠删码条带化数据一致性检查的读取开销,提高纠删码数据一致性检查和读后写的效率,在执行纠删码条带化数据写入时,为每个条带单元加入自修正数据标签(SCDT),后续对每个条带的一致性检查基于SCDT完成.该方法不需要读取每个条带中所有数据单元即可完成该条带的一致性检查,将一致性检查效率提升了1.7~2.6倍,并且当写入数据更新的条带单元数小于临界值时,可以有效减少写入的输入输出(IO)交互次数.本文方法可以更好地应对条带化数据组的部分更新,同时提高一致性检查效率.

一种多用户协同的BOM数据一致性校核与检测算法设计

针对航空航天制造领域中多用户协同工作场景下,由人为错误操作或数据库共享异常导致的数据一致性较差问题,文中基于改进函数依赖和着色PETRI网构建了BOM数据一致性校核与检验模型。该模型根据多用户BOM数据的结构特点,界定了零部件的层次结构与关系定义。同时对传统函数依赖算法加以改进,并控制数据迁移规模及并行度以改善函数依赖发现效率,从而进行数据信息的不一致校核。通过解构HDFS系统数据写入流程,利用着色PETRI网进行数据共享流程建模,进而实现数据共享一致性校核算法的构建。经仿真验证,所述方案的两种耗时指标与对照组算法相比分别降低了26.61%和38.23%,且状态空间及强连通构建图中状态节点和变迁的数量一致,不存在回路,由此证明了该方案的可行性。

医疗保障任务风险评估:一项结合判断矩阵与群智能优化算法的研究

目的提出一种快速智能优化算法,使在通过层次分析法(AHP)对医疗保障分队任务进行风险评估时存在的判断矩阵不满足一致性的问题得到解决,同时最大程度保留专家原始信息。方法在原判断矩阵的基础上,充分结合各指标间两两重要性程度,通过特征向量法构造一个各指标之间重要性程度完全合理的矩阵作为过渡矩阵。进而以一定比例系数将两个矩阵结合,使结合成的新矩阵既满足指标间重要程度比较的合理性,又能最大程度保留原矩阵的信息。为了找到最优的比例系数,结合群智能优化算法,设置优化目标为新矩阵与原始矩阵的相似度,约束条件为矩阵满足一致性检验。最终找到最优的比例系数,并将在此系数下形成的新矩阵作为优化后的矩阵。结果该算法可以优化AHP在医疗保障任务风险评估应用中判断矩阵的一致性,有效解决原始矩阵不满足一致性检验的问题,并最大程度保留专家的原始意图。结论本算法实现了智能优化判断矩阵的一致性,使AHP在医疗保障任务风险评估、医疗安全风险评估等复杂系统的应用中更具科学性与合理性。

Checking Content Consistency of Integrated Web Documents

A conceptual framework for the specification and verification of constraints on the content and narrative structure of documents is proposed. As a specification formalism, CTLDL is defined, which is an extension of the temporal logic CTL by description logic concepts. In contrast to existing solutions this approach allows for the integration of ontologies to achieve interoperability and abstraction from implementation aspects of documents. This makes CTLDL specifically suitable for the integration of heterogeneous and distributed information resources in the semantic web.

智能穿戴设备在心房颤动检测中的应用价值

目的评估智能穿戴设备识别心房颤动(简称房颤)的敏感性、特异性和准确性。方法选取行24 h动态心电图监测的患者410例,同期佩戴智能穿戴设备。比较两种检查方法下房颤检出率的一致性,并评估智能穿戴设备识别房颤的敏感性、特异性及准确性。结果智能穿戴设备检测房颤的敏感性为99.31%、特异性为81.48%,准确性为95.41%,K值为0.83,与动态心电图在房颤检出率方面具有较强的一致性。结论智能穿戴设备使用方便,患者依从性高,对房颤的自动识别准确性较高,更利于推动房颤筛查的家庭化、日常化。

一种基于模糊层次分析法的接地网状态评估方法

综合变电站接地网的实际情况,构建了变电站接地网状态评估体系,建立层次结构模型和优先判断矩阵,应用模糊层次分析法,优先关系矩阵被转化为满足一致性收敛条件的模糊一致判断矩阵。利用关系排序法,可以确定各因素的权重,从而确定所选指标在评估体系中的相对重要程度,接着对各指标进行加权平均求和得到变电站接地网的当前状态从而判断腐蚀级别,最后与三指标法得到的评估结果比较,证明评估方法的正确有效性。

Checking Causal Consistency of MongoDB

MongoDB is one of the first commercial distributed databases that support causal consistency.Its implementation of causal consistency combines several research ideas for achieving scalability,fault tolerance,and security.Given its inherent complexity,a natural question arises:"Has MongoDB correctly implemented causal consistency as it claimed?"To address this concern,the Jepsen team has conducted black-box testing of MongoDB.However,this Jepsen testing has several drawbacks in terms of specification,test case generation,implementation of causal consistency checking algorithms,and testing scenarios,which undermine the credibility of its reports.In this work,we propose a more thorough design of Jepsen testing of causal consistency of MongoDB.Specifically,we fully implement the causal consistency checking algorithms proposed by Bouajjani et al.and test MongoDB against three well-known variants of causal consistency,namely CC,CCv,and CM,under various scenarios including node failures,data movement,and network partitions.In addition,we develop formal specifications of causal consistency and their checking algorithms in TLA^(+),and verify them using the TLC model checker.We also explain how TLA^(+) specification can be related to Jepsen testing.

A Stronger Uniform Consistency Check and Adjustment Method

When vectors of a judgement matrix is arranged according to their weight in AHP, uniform consistency is always required and the check criterion is uniform check. In this paper, a stronger uniform consistency check is introduced which can obtain a exact and practical effect by making an adjust to any non-satisfying uniforming matrix.

基于模糊层次分析法的水系治理工程效果评价研究

以英德市石灰铺镇农村水系治理工程为研究对象,分析了当地河道、池塘和灌区3个方面存在的问题及相关整治工程。从生态、经济和社会效益3个方面考虑,构建了包含二十项子指标的评价指标体系,并采用模糊数学和层次分析方法建立了适用于评价水系治理工程的模糊层次分析模型。实际应用表明,提出的模糊层次分析方法可以较好地对治理工程进行综合评价,所建立的指标体系具有良好的适用性,指标获取方式简单,评价结果具有良好的参考价值。该工程的综合评价指标为0.70,证明治理工程达到了预期效果。因此,提出的评价方法可以为农村水系治理工程提供技术指导。

基于层次分析法的石材生产线布局优化

采用层次分析法对石材生产线的3种布局方案进行了评估。建立石材生产线布局方案的评价结构模型,计算不同层次评价指标的权重,对石材生产线布局方案进行评估,为实际生产线的建设提供依据。结果表明,基于层次分析法确定各评价指标权重的方法具有一定的实用价值,且能够为类似生产线优化布局的研究提供借鉴。

改进的模糊层次分析法

目的 改进传统的层次分析法。方法 将互反型判断矩阵改为模糊一致性判断矩阵,并把和行归一法或方根法与特征向量法结合使用,提出了改进的模糊层次分析法。结果 指出传统的层次分析法往往会导致判断矩阵不满足一致性条件,需要检验和修正,而且计算精度不高。改进后的模糊层次分析法既解决了判断矩阵的一致性问题,又解决了解的收敛速度及精度问题,以此求得与实际相符的排序向量。结论 改进传统的层次分析法较传统的层次分析法更加完善和行之有效,并符合人们的思维逻辑,形式简单,准确,且易建立。另外,由优先判断矩阵改造而成的模糊一致性矩阵满足一致性条件,无需再进行一致性检验,同时也可大大减少叠代次数,提高收敛速度,满足计算精度的要求,从而为多目标决策提供了较为可靠的决策方法。