Application of GA-SVM in classification of surrounding rock based on model reliability examination

In order to improve the discrimination precision of support vector machine(SVM) in classification of surrounding rock, a Genetic Algorithm(GA) was used to optimize SVM parameters in the solution space.The idea of examination of model reliability was introduced to check the reliability of the SVM parameters,obtained by genetic algorithms.In the process of model reliability,a trend examination method is presented,which checks the reliability of the model via the influence trend of impact factors on the object of evaluation and their evaluation level.Trend examination methods are universal,showing new ideas in model reliability examination and can be used in any problems of examination of reliability of models,based on previous experience.We established a GA-SVM based reliability model of a classification the surrounding rock and applied it to a practical engineering situation.The result shows that the improved SVM has a high capability for generalization and prediction accuracy in classification of surrounding rock.

Classification using least squares support vector machine for reliability analysis

In order to improve the efficiency of the support vector machine （SVM） for classification to deal with a large amount of samples, the least squares support vector machine （LSSVM） for classification methods is introduced into the reliability analysis. To reduce the coraputational cost, the solution of the SVM is transformed from a quadratic programming to a group of linear equations. The numerical results indicate that the reliability method based on the LSSVM for classification has higher accuracy and requires less computational cost than the SVM method.

Inter-and intra-rater reliability of vertebral fracture classifications in the Swedish fracture register

AIM To investigate the inter-and intra-rater reliability of the vertebral fracture classifications used in the Swedish fracture register.METHODS Radiological images of consecutive patients with cervical spine fractures(n = 50)were classified by 5 raters with different experience levels at two occasions. An identical process was performed with thoracolumbar fractures(n = 50). Cohen's kappa was used to calculate the inter-and intra-rater reliability.RESULTS The mean kappa coefficient for inter-rater reliability ranged between 0.54 and0.79 for the cervical fracture classifications, between 0.51 and 0.72 for the thoracolumbar classifications(overall and for different sub classifications), and between 0.65 and 0.77 for the presence or absence of signs of ankylosing disorder in the fracture area. The mean kappa coefficient for intra-rater reliability ranged between 0.58 and 0.80 for the cervical fracture classifications, between 0.46 and0.68 for the thoracolumbar fracture classifications(overall and for different sub classifications) and between 0.79 and 0.81 for the presence or absence of signs of ankylosing disorder in the fracture area.CONCLUSION The classifications used in the Swedish fracture register for vertebral fractures have an acceptable inter-and intra-rater reliability with a moderate strength of agreement.

Testing Reliability and Validity of the Oulu Patient Classification Instrument—The First Step in Evaluating the RAFAELA System in Norway

Objective: To study reliability and validity of the Finnish Oulu Patient Classification instrument in Norway. Background: The Finnish patient classification system RAFAELA consists of three parts: 1) daily patient classification of nursing intensity using the Oulu Patient Classification instrument, 2) calculation of nursing resources providing bed side care per 24 hours, and 3) Professional Assessment of Optimal Nursing Care Intensity Level. The RAFAELA system has not been tested outside of Finland. Methods: A prospective, descriptive study was performed at 5 clinical units at Oslo University Hospital during 2011-2012. The interrater reliability of the Oulu Patient Classification instrument was tested by parallel classification including 100-167 patient classifications pr. unit, and analyzed by consensus in % and using Cohen’s Kappa. Convergent validity was tested by using the average Oulu Patient Classification instrument value to predict the average Professional Assessment of Optimal Nursing Care Intensity Level for the same calendar day by linear regression analysis. Results: The Oulu Patient Classification instrument consensus of parallel classifications varied between 70.1%-89%. Cohen’s Kappa within patient classes varied between 0.57 and 0.81, representing substantial interrater reliability. The Oulu Patient Classification instrument was valid as the instrument in average explained about 38% of the variation of the Professional Assessment of Optimal Nursing Care Intensity Level. Conclusions: Patient classification systems tested for psychometric properties are needed and this study provides evidence of satisfactory reliability and validity of the Oulu Patient Classification instrument as tested outside Finland, demonstrating that this instrument has international relevance within nursing.

Improving the Interpretability and Reliability of Regional Land Cover Classification by U-Net Using Remote Sensing Data

The accurate and reliable interpretation of regional land cover data is very important for natural resource monitoring and environmental assessment.At present,refined land cover data are mainly obtained by manual visual interpretation,which has the problems of heavy workload and inconsistent interpretation scales.Deep learning has greatly improved the automatic processing and analysis of remote sensing data.However,the accurate interpretation of feature information from massive datasets remains a difficult problem in wide regional land cover classification.To improve the efficiency of deep learning-based remote sensing image interpretation,we selected multisource remote sensing data,assessed the interpretability of the U-Net model based on surface spatial scenes with different levels of complexity,and proposed a new method of stereoscopic accuracy verification(SAV)to evaluate the reliability of the classification result.The results show that classification accuracy is more highly correlated with terrain and landscape than with other factors related to image data,such as platform and spatial resolution.As the complexity of surface spatial scenes increases,the accuracy of the classification results mainly shows a fluctuating declining trend.We also find the distribution characteristics from the SAV evaluation results of different land cover types in each surface spatial scene.Based on the results observed in this study,we consider the distinction of interpretability and reliability in diverse ground object types and design targeted classification strategies for different surface scenes,which can greatly improve the classification efficiency.The key achievement of this study is to provide the theoretical basis for remote sensing information analysis and an accuracy evaluation method for regional land cover classification,and the proposed method can help improve the likelihood that intelligent interpretation can replace manual acquisition.

Reliability and validity of sub-axial injury classification in clinical application

Objective To evaluate the clinical reliability and validity of the sub-axial injury classification (SLIC) system proposed by the Spine Trauma Study Group (STSG) in 2007. Methods Thirty cases of cervical injury were randomly chosen

Active learning accelerated Monte-Carlo simulation based on the modified K-nearest neighbors algorithm and its application to reliability estimations

This paper proposes an active learning accelerated Monte-Carlo simulation method based on the modified K-nearest neighbors algorithm.The core idea of the proposed method is to judge whether or not the output of a random input point can be postulated through a classifier implemented through the modified K-nearest neighbors algorithm.Compared to other active learning methods resorting to experimental designs,the proposed method is characterized by employing Monte-Carlo simulation for sampling inputs and saving a large portion of the actual evaluations of outputs through an accurate classification,which is applicable for most structural reliability estimation problems.Moreover,the validity,efficiency,and accuracy of the proposed method are demonstrated numerically.In addition,the optimal value of K that maximizes the computational efficiency is studied.Finally,the proposed method is applied to the reliability estimation of the carbon fiber reinforced silicon carbide composite specimens subjected to random displacements,which further validates its practicability.

适用于规划-运行两阶段的配电网可靠性等级划分及评估方法

新型电力系统的快速建设与发展对配电网的可靠性评估提出了更高的要求。综合考虑配电网中终端用户差异化的可靠性需求和电网规划、运行两阶段的不同特点,提出了配电网可靠性等级划分方法和适用于规划-运行两阶段的配电网可靠性评估方法。首先,考虑用电性质、用户侧负荷特性等多方面因素,计及可靠性电价的影响,从系统侧、用户侧和供用电交互侧出发,建立了配电网供电可靠性评估指标体系;然后考虑终端用户用电需求的差异性,进行了配电网可靠性等级的划分;在此基础上,基于终端用户的差异化可靠性需求,提出了适用于规划-运行两阶段的配电网可靠性评估方法。最后进行算例分析,验证了所提划分方法的合理性和评估方法的有效性。

Ⅰ型神经纤维瘤病伴萎缩性上胸段脊柱侧凸的冠状面影像学分型

目的:对Ⅰ型神经纤维瘤病伴萎缩性上胸段脊柱侧凸(dystrophic upper thoracic scoliosis with neurofibromatosis type 1,DUTS-NF1)进行冠状面影像学分型,验证其可信度与可重复性,探讨其临床意义。方法:回顾性分析2009年6月~2023年12月期间我院数据库中诊断为Ⅰ型神经纤维瘤病伴萎缩性脊柱侧凸患者的资料,从中筛选出主弯顶椎位于上胸椎(T1~T5)的患者,根据站立位全脊柱正位X线片上脊柱侧凸的冠状面形态分为:A型,肩颈型;B型,远端弯代偿型;C型,躯干倾斜型;测量各型患者的侧凸Cobb角、上胸段后凸角、锁骨角(clavicle angle,CA)、T1倾斜角(T1 tilt)、颈部倾斜角(neck tilt,NT)、头部偏移距离(head shift,HS)、冠状面平衡距离(coronal balanced distance,CBD),计算畸形角率(deformity angular ratio,DAR)。3位脊柱外科医师经过分型设计者专门培训后根据该冠状面分型方法独立进行两次分型,应用Kappa值对同一观察者两次分型结果进行可重复性分析,对不同观察者间分型结果进行可信度分析。结果:从367例Ⅰ型神经纤维瘤病伴萎缩性脊柱侧凸患者中共筛选出29例DUTS-NF1患者(7.9%),其萎缩性主弯Cobb角为78.7°±12.9°。分型设计者的分型结果A型16例,B型8例,C型5例。B型和C型的DAR显著性高于A型(20.6±2.2和20.0±3.0 vs 13.2±1.8,P<0.001);C型相对于A型存在更为显著的头部及冠状面偏移距离(HS:27.6±11.7mm vs 13.5±6.7mm,P<0.001;CBD:34.8±20.5mm vs 13.9±10.9mm,P<0.001);C型T1 tilt显著性大于A型(P<0.05);其余影像学指标三型间无统计学差异(P>0.05)。3位观察者使用DUTS-NF1冠状位影像学分型方法共进行174次(29例×3×2次)分型,包括A型96次,B型45次,C型33次,观察者内分型一致率为(82.57±8.44)%,Kappa值为0.771~0.81,属于“基本可信”;观察者间分型一致率为(84.19±8.65)%,Kappa值为0.884~0.886,属于“完全可信”。结论:根据冠状面影像学特征可将DUTS-NF1患者分为肩颈型、远端弯代偿型、躯干倾斜型三型,该分型方法具有较高的可重复性与可信度,可为临床提供诊疗决策依据。

适用于膝骨关节炎膝关节置换术围手术期ICF核心分类组合简明版临床评定工具的信度与效度

目的 验证适用于膝骨关节炎膝关节置换术围手术期ICF核心分类组合(ICSAKOPP)简明版临床评定工具的信度与效度。方法 2022年5月至2023年4月,选择北京大学第三医院、中日友好医院、北京大学第一医院、中国人民解放军总医院拟进行膝关节置换的膝骨关节炎患者320例。经过培训的评定者应用ICSAKOPP简明版对所有入组患者在术前、术后3 d (±1 d)、术后3周(±1周)、术后3个月(±1个月)时分别进行ICF评定,记录同期西安大略和麦克马斯特大学骨关节炎指数(WOMAC)得分。邀请5名康复专业人员对ICSAKOPP简明版所有类目进行评分,计算内容效度指数(CVI)。结果64例被剔除。ICSAKOPP简明版各类目CVI均≥0.8,量表平均CVI为0.938。ICSAKOPP简明版Cronbach α系数为0.813。ICSAKOPP简明版整体与WOMAC评分中等相关(r=0.681,P <0.001),身体功能维度(r=0.668,P <0.001)、活动和参与维度(r=0.657,P <0.001)与WOMAC评分中等相关。结论 ICSAKOPP简明版的内容效度良好,内部一致性信度和效标效度良好。

关节镜日间手术患者延续护理需求问卷的编制及信度、效度检验

目的 编制关节镜日间手术患者延续护理需求问卷,并检验其信度、效度,为临床提供评估工具。方法 2022年8月—12月以奥马哈问题分类系统为指导框架,通过文献回顾、质性访谈建立问卷条目池,选择全国6个省市临床护理、护理管理、临床医学、康复医学等6个领域的15名专家,采用德尔菲法对该问卷进行两轮专家函询构建问卷初稿;2023年3月—8月采用便利抽样法,选取山东省济南市4所三级甲等综合医院的280例关节镜日间手术患者进行问卷调查,并检验其信度与效度。结果 两轮专家函询的积极系数分别为83.33%和100.00%,权威程度系数均为0.82,该指标Kendall协调系数W分别为0.169和0.218,第一轮函询二级指标各条目的重要性均数为4.13~4.80分,该指标变异系数为0.086~0.208,满分率为33.33%~80.00%;第二轮函询二级指标各条目的重要性均数为4.20~5.00分,该指标变异系数为0.00~0.18,满分率为40%~100.00。共调查280例患者,问卷总的Cronbach α系数为0.922,折半信度为0.79;问卷总体水平的内容效度指数(scale-level content validity index,S-CVI)以及问卷条目水平的内容效度指数(item-level content validity index,I-CVI)均为1;探索性因子分析KMO值为0.925,Bartlett’s球形检验值为5456.320(P<0.001),累计方差贡献率为63.319%。经信度、效度检验后形成包含环境领域2个条目、心理社会领域5个条目、生理领域15个条目、健康相关行为领域8个条目共30个条目的正式版问卷。结论 关节镜日间手术患者延续护理需求问卷具有良好的信度、效度,适用于评估我国关节镜日间手术患者延续护理的相关需求。

一种层次化的人为差错分类方法

针对人为差错在差错描述的全面性、一致性以及方法本身的有效性等方面的不足,提出一种层次化的人为差错分类新方法。将当前的各种人为差错分类方法分为3类,分析各种方法的特点和缺陷。提出从宏观到微观分层次的分类思想,将人为差错分为4个层次,针对每个层次构建详细的分类框架;运用该方法对航空维修中的人为差错进行示例分析,演示方法的使用流程。分析结果表明:该方法是一种有效的人为差错分类方法,可用于指导各种任务场景的人为差错辨识。

ICF功能障碍组合在康复住院患者功能评估中的信度研究

目的探讨国际功能、残疾和健康分类(International Classification of Functioning,Disability,and Health,ICF)功能障碍组合(ICF generic-30 set)30个类目在康复科住院患者功能评估中的评估者间和评估者内信度,为其临床应用提供依据。方法选取宿迁市第一人民医院神经康复科的90例患者纳入本研究。所有患者在入院及出院2个时间点接受同一功能评估者的ICF功能障碍组合的评估,以进行评估者内信度分析。随机抽取30例患者同时接受2名ICF功能评估者的评估,以进行评估者间重测信度分析。以Cronbach’sα系数检验量表的内部一致性,以组内相关系数(intra-group correlation coefficient,ICC)检验评估者间信度和评估者内信度。结果ICF功能障碍组合及身体功能和活动与参与两个分量表的Cronbach’sα系数分别为0.941、0.717、0.942。评估者间信度分析显示量表总分及身体功能和活动与参与两个分量表总分的ICC分别为0.998、0.971、0.999(P<0.01),评估者间信度佳;评估者内信度分析显示量表总分及身体功能和活动与参与两个分量表总分的ICC分别为0.988、0.917、0.991(P<0.01),除b640性功能不适用,b130精力和驱力功能ICC为0.558、b280痛觉ICC为0.409,其他组合条目的ICC在0.838~0.986(P<0.01),评估者内信度佳;90例患者的ICF功能障碍组合量表30个类目入、出院比较除b640性功能不适用,其余差异均有统计学意义(P<0.05)。结论ICF功能障碍组合在神经康复科患者功能评估应用中具有良好的内部一致性及评估者间和评估者内信度。

沿海强风区500 kV架空输电线路防风加强设计

[目的]随着我国沿海地区极端天气的日趋频繁,台风灾害给沿海电网造成了极大威胁,为提升架空输电线路抗风能力,目前针对沿海强风区线路通常采取提高设计气象重现期的方法进行设计,《架空输电线路荷载规范》(DL/T 5551—2018)颁布后,由于新、旧规范间风荷载计算方法的差异,此前的抗风加强措施是否与现行规范相适应,成为亟待研究的问题。[方法]以南方电网沿海强风区500 kV重要线路为例,基于输电线路防风可靠度分级体系,通过制定不同的防风设计方案,进而对不同方案下输电线路的抗风能力水平及可靠度进行评估,并对不同设防方案下的技术经济性进行比较,最后结合工程实例,推荐了沿海强风区500 kV重要输电线路的防风设计方案。[结果]在执行荷载规范前提下,按50年重现期基准风速并考虑1.1倍重要性系数(方案三)方案可与此前基于GB50545-2010按100年重现期进行防风设计的抗风举措,无论是在抗风能力以及工程投资上均可良好适配。[结论]对于沿海强风区500 kV重要输电线路,方案三为各设防方案中技术经济指标综合最优的选择,输电线路抗风能力可达16级台风中限,研究对于节约资源、降低碳排放具有重要意义。

基于改进合成少数类过采样技术的非概率可靠性指标解

当结构的功能函数呈现高度非线性、极限状态曲面为多区域的情形时,现有算法无法有效求解非概率可靠性指标,为解决此类问题,将合成少数类过采样技术(SMOTE)进行改进,提出了基于改进SMOTE算法的非概率可靠性指标解法。首先基于非概率可靠性指标的几何意义,将样本分类策略、超球限制策略与标准SMOTE算法相结合,提出了改进SMOTE算法来进一步提升算法在极限状态曲面附近的采样效率;然后结合改进SMOTE算法在标准化空间中高精度的拟合局部极限状态曲面,进而搜索得到非概率可靠性指标;最后给出了基于改进SMOTE算法的非概率可靠性指标解的主要流程。数值算例表明,当极限状态曲面呈现局部闭合、多区域的特点时,改进后的SMOTE算法可以高效地获取位于极限状态曲面附近的样本点,进而高精度地拟合极限状态曲面。将本文方法的计算结果与解析解对比,相对误差远远小于工程中的最大误差限值5%,说明改进SMOTE算法能够较好地处理高度非线性功能函数,验证了所提算法的有效性和实用性。

基于ETAP的甲级大型体育馆体育照明供电可靠性分析

体育照明是体育场馆内电气设计最重要的一部分,其照明效果与供电方式会直接影响整场比赛的观感。在体育照明设计中,供电方式、供电可靠性与控制方式是此类设计的核心要素,它们直接关系体育照明系统能否稳定可靠运行。以济南大型甲级体育馆为例,采用ETAP软件进行综合体育照明供电系统的供电可靠性分析,通过计算数据,为体育照明设计提供指导与参考。

基于区域失效的数据中心和5G基站冷却设备可靠性预测方法研究

对数据中心和5G基站用冷却设备在不同安装区域的现场失效大数据进行分析,通过极大似然法建立寿命分布模型,其寿命分布最优拟合符合威布尔三参数分布规律,故障复发符合非齐次泊松过程,按区域聚类可靠性呈现显著性差异。对典型区域失效数据按可修复系统和不可修复系统分别进行可靠性预测,按可修复系统的预测结果与实际维修数据相关性良好。建立的基于区域失效的寿命分布、故障复发及可靠性预测方法适用于数据中心和5G基站用冷却设备的使用现场失效大数据分析,故障预测及维修备件、包修策略制定。

民用建筑砌体结构构件承载力鉴定评级的分析与建议

现行国家标准《民用建筑可靠性鉴定标准》(GB 50292—2015)中,各类构件的安全性鉴定评级均按照相同的分级原则确定。在各安全性等级下,不同结构构件通过抗力与效应比表达的验算表征基本参照《民用建筑可靠性鉴定标准》(GB 50292—1999)的规定。为改进各类砌体结构可靠性鉴定与分级标准,结合我国相关设计规范,以砌体结构为研究对象,通过当量正态化和验算点法计算砌体结构构件在不同安全性等级下的可靠指标,综合考虑荷载分项系数调整前后砌体结构构件可靠指标的变化,提出相应的分级标准。分析结果表明,《民用建筑可靠性鉴定标准》(GB 50292—2015)对于各个安全等级下的砌体结构构件的安全性分级偏于保守,在荷载分项系数调整后更为突出,而改进的分级标准能更准确地将可靠指标和抗力与效应比相对应。

基于多评价指标的输电铁塔构件重要性分类方法

铁塔构件重要性的合理分类是保证输电铁塔力学性能监测方案经济合理的前提。目前的分类方法存在分类依据考虑不全面,难以适用输电铁塔结构高冗余度特征的问题。本文基于改变路径法拆除铁塔构件,综合考虑剩余结构的最大应力均值变化率和可靠度两个评价指标,采用熵权—优劣解距离决策法构造综合评价模型,提出一种针对高压输电铁塔的构件重要性分类方法,并进行了算例分析。分析结果表明,铁塔构件重要性分布呈现非线性特征,不同工况下构件重要性表现出一定的差异性。根据本文的构件重要性分类方法计算所得结果与实际工程经验结果基本一致,能够定量判定输电铁塔结构中的关键构件,研究成果可为输电铁塔智能监测领域的传感器布置问题提供理论基础。

简要版COPD-ICF在慢性阻塞性肺疾病病人中的信效度检验

目的:探讨简要版慢性阻塞性肺疾病功能、残疾和健康分类核心组合(COPD-ICF)在慢性阻塞性肺疾病病人中的信效度。方法:采用一般资料问卷、简要版COPD-ICF、改良英国医学研究学会呼吸困难指数问卷(mMRC)、慢性阻塞性肺疾病呼吸测试问卷(CAT)对150例慢性阻塞性肺疾病病人进行调查。结果:简要版COPD-ICF量表的Cronbach’s α系数为0.873,3个分量表的Cronbach’s α系数为0.586~0.836。量表条目水平的内容效度(I-CVI)为0.80~1.00,全体一致量表水平的内容效度(S-CVI/UA)为0.986,平均量表水平的内容效度(S-CVI/Ave)为0.986。身心功能、身体结构、活动和参与3个分量表以及量表总分与mMRC、CAT得分均呈正相关。验证性因子分析结果显示,修正后模型拟合度良好,具有较好的结构效度。结论:简要版COPD-ICF可以作为评估慢性阻塞性肺疾病病人综合功能问题可靠、有效的工具。