2003—2020年新疆北部积雪因子时空变化分析

积雪作为冰冻圈的活跃因子之一,对气候环境的敏感性使其能够快速反映出与气温、降水等气候因素的关系变化,并影响着全球水文变化。对新疆北部地区2003年6月—2021年6月的中分辨率成像光谱仪(moderate resolution imaging spectrometer, MODIS)逐日积雪数据进行去云处理,并基于像元计算了积雪覆盖比例(snow cover percentage, SCP)、积雪覆盖日数(snow cover days, SCD)、积雪开始时间(snow onset day, SOD)和积雪结束时间(snow end day, SED)。实验结果表明：积雪产品相对于气象站点数据的总精度达到91.47%,有利于提高对积雪因子的时空变化分析。新疆北部地区SCD空间分布差异较大,SCD随海拔的升高而增加,SOD随海拔升高而提前,主要在11月和12月出现;SED随海拔升高而推迟,主要在2月和3月出现;夏季平均SCD最少,主要分布于天山中部以及阿尔泰山北部区域,约占3.35%,冬季平均SCD最为明显,大于60 d的区域占46.3%;而SCP在1月达到最大,7月和8月最小。趋势变...     

基于遗传算法-深度神经网络的分布式光纤监测工作面矿压预测

煤层开采过程中的工作面矿压分析与预测,对煤矿顶板管理与安全生产具有重要意义。然而,工作面开采引起的围岩移动和变形影响着矿压预测的准确度。为了提高工作面来压位置预测的精度,以分布式光纤监测采动覆岩变形的频移数据为基础,引入门控循环神经网络(gated recurrent neural networks, GRU),建立了遗传算法(genetic algorithm, GA)-GRU-反向传播(back propagation, BP)的工作面来压位置预测模型。将光纤频移值的统计特征融合工作面推进距离等因素作为特征向量,并采用GA对GRU及BP网络的超参数寻优。实验结果表明：预测模型的决定系数为98.7%,平均绝对误差为1.224 cm,均方根误差为1.769 cm,预测的准确性高,为工作面矿压预测提供了新的方法。     

Analytical determination of flow resistance characteristic for combination channel inside hydraulic manifold block

Computational fluid dynamics （CFD） was used in conjunction with BP neural network to study the flow resistance characteristic of the combination-channel inside hydraulic manifold block （HMB）. The input parameters of the combination-channel model were confirmed to have effect on the pressure-drop by the numerical method, and a BP neural network model was accordingly constructed to predict the channel pressure-drops. The flow resistance characteristic curves of various channels were achieved, and a performance parameter was given to evaluate the through-flow characteristic of the channel according to the curves. The predictions are in agreement with the numerical computation, indicating that the method can be utilized to accurately determine the flow characteristic of the combination channel with high efficiency.     

选用阀门时应考虑的技术问题

针对阀门产品的不断创新及个性化,从阀门连接方式、一般要求、阀门材料、阀门的操作机构、阀门的性能检测、阀门的内外防腐、阀门的出厂说明等方面论述选用阀门时应提出较详尽技术要求的必要性。     

优化快速流程模式对直肠癌患者手术效果的影响

目的分析快速流程模式(FT)对直肠癌手术效果的影响.方法选择100例符合条件的患者,随机分成两组,观察组进行FT,对照组应用传统模式(TC),对比研究两组患者的康复效果并统计两组出现并发症的例数.结果观察组患者的术后住院天数、首次排气时间、首次下床活动时间、首次经口进食时间、首次拔除胃管以及尿管时间均短于TC组,其差异具有统计学意义(P0.05);两组之间首次拔除引流管的时间差异无统计学意义(P0.05);两组患者在吻合口瘘、肠梗阻、切口感染的发生率及总发生率的差异均无统计学意义(P0.05).结论对直肠癌患者围手术期实施快速流程模式,手术效果显著,且并不增加术后并发症,是一种安全有效的方法.     

基于PHP的科研管理系统设计与实现

文中分析并设计出了高校科研管理系统,并使用PHP编程语言进行了系统的实现.     

对传媒类艺术学生开展挫折教育的思考

传媒类艺术生由于成长环境相对良好,成长道路较为顺利,具有纪律意识较差、文化基础不牢、自我认知缺乏、容易冲动、过于自信等自身显著的个性特征。日益激烈的竞争对传媒类艺术生的心理素质提出了更高的要求,因此,应通过开展挫折教育,提高他们的受挫能力,促进他们健康成长成才。     

Privacy Quantification Model Based on the Bayes Conditional Risk in Location-Based Services

The widespread use of Location-Based Services(LBSs),which allows untrusted service providers to collect large quantities of information regarding users’locations,has raised serious privacy concerns.In response to these issues,a variety of LBS Privacy Protection Mechanisms(LPPMs)have been recently proposed.However,evaluating these LPPMs remains problematic because of the absence of a generic adversarial model for most existing privacy metrics.In particular,the relationships between these metrics have not been examined in depth under a common adversarial model,leading to a possible selection of the inappropriate metric,which runs the risk of wrongly evaluating LPPMs.In this paper,we address these issues by proposing a privacy quantification model,which is based on Bayes conditional privacy,to specify a general adversarial model.This model employs a general definition of conditional privacy regarding the adversary’s estimation error to compare the different LBS privacy metrics.Moreover,we present a theoretical analysis for specifying how to connect our metric with other popular LBS privacy metrics.We show that our privacy quantification model permits interpretation and comparison of various popular LBS privacy metrics under a common perspective.Our results contribute to a better understanding of how privacy properties can be measured,as well as to the better selection of the most appropriate metric for any given LBS application.     

省级公共医疗卫生供给绩效评估实证研究——基于全面绩效管理的视角

为了研究安徽省公共医疗卫生供给绩效及其影响因素,从公共服务供给压力、状态和响应3个维度筛选了15个相关指标,构建了评估指标体系,利用最新数据和熵值-Tobit模型对安徽省公共医疗卫生供给绩效及其影响因素进行综合评估,认为样本考察期内安徽省公共医疗卫生供给绩效呈现"快速-平稳-快速-平稳"的动态波动趋势,且供给压力依然较大,供给状态不容乐观,但供给响应指数提升明显; Tobit回归显示,安徽省财政医疗支出占比呈现规模报酬递减效应,人口密度与公共医疗卫生供给绩效呈现负相关关系,而人均地区生产总值、城镇化水平和财政自给率与公共医疗卫生供给绩效呈现正相关关系,但财政自给率的影响不显著,据此,提出了促进省级公共医疗卫生供给绩效提升的相关对策建议。     

Secure pairing with wearable devices by using ambient sound and light

Wearable devices usually work together with smart phones. To ensure only legitimate smart phones can read the data, they must conduct pairing to establish a shared key. Traditional pairing methods require that the pairing devices have a keyboard or screen for user interaction. However, due to the size limitation, keyboards or screens are hard to be installed in the wearable devices. To solve this problem, we propose a novel pairing method by using ambient sound and light. In this new scheme, any pairing request from smart phone will trigger wearable device vibration. Only after users press the confirm key on the device can the pairing process continues. Then pairing devices collect ambient sound and light at the predetermined time and establish a shared key by using the Diffie-Hellman protocol. To protect against potential man-in-the-middle attacks in the key establishment process, an improved interlock protocol with sound and light comparison is conducted to authenticate the key. If both the sound and light collected by the pairing devices are similar enough, the key is accepted. Otherwise, it is rejected. Compared with current context based pairing methods, our scheme does not impose strict synchronization on devices to collect ambient context data. Moreover, our scheme need not collect and exchange contextual information for multiple times to resist offline brute force attacks. The experimental results and security analysis prove the effectiveness of our scheme.