一种区域卫星定位系统的星座方案

提出了一种用静止卫星和同步椭圆轨道卫星构造的区域卫星定位系统。并以GDOP最小化为目标,对该系统的星座参数进行了优化。利用仿真得到了该星座在我国的性能指标,并和GPS星座进行了比较。仿真结果表明,该方案能够满足我国及周边地区的卫星定位需要。     

分布式卫星INSAR中姿态变化对测高的影响

讨论了分布式卫星系统中卫星姿态变化、地球自转、卫星环绕等因素,及对小卫星间基线测量引起的误差。分析了卫星姿态变化带来的基线误差对干涉SAR测高的影响。理论分析和仿真结果表明,当姿态误差为0.1时,将导致0.1 m的基线误差和20.42 m的干涉SAR测高误差。     

21世纪精确农业的新内涵及我国的发展对策

介绍了精确农业的产生,拓宽了21世纪精确农业的内涵;阐述发展我国精确农业的必要性和紧迫性;简要总结目前国内外精确农业的发展应用状况;并提出21世纪发展我国精确农业的对策。     

新时代民族地区精准扶贫法治保障研究

民族地区精准扶贫既是“十三五”脱贫攻坚主战场,又是国家减贫治理方式的重要体现。当前我国民族地区扶贫工作已进入新时代,要使民族地区精准扶贫工作取得显著成效,确保如期实现脱贫攻坚目标,必须以强大法治保障为前提。纵观目前我国民族法治建设运行现状,仍存在精准化扶贫刚性立法供给不足、运行程序不规范、精准扶贫纠纷现代解决机制阙如等问题。因此,必须加快民族地区精准扶贫法律体系构建、健全相关精准扶贫法治化工作制度、构建民族地区精准扶贫多元化纠纷解决机制,确保相关扶贫工作在法治框架下规范实施。     

集中连片特困区旅游扶贫的产业融合发展模式研究——以山西兴县蔡家崖村为例

实施乡村振兴、精准扶贫是中国破解城乡二元结构、实现人民美好生活的战略选择。旅游产业以其强大的市场优势、新兴的产业活力、强劲的造血功能和巨大的带动作用,成为新时期乡村振兴战略和精准扶贫战略的重要抓手和主要动力之一。蔡家崖村地处吕梁山集中连片特困地区,脱贫攻坚任务艰巨。近年来,蔡家崖村依托其良好的生态环境资源和红色旅游资源,大力发展农业旅游和文化旅游产业,积极探索旅游富民之路,形成了现代农业与红色旅游互促共赢的发展局面,目前基本实现了全村脱贫,共同富裕,乡村振兴。山西省兴县蔡家崖村作为集中连片特困区旅游扶贫的代表地,通过分析其旅游扶贫的背景、模式与实施路径,深入研究蔡家崖村“红色旅游扶贫,农旅融合兴村,旅游电商富民”的转型发展之路,进一步总结蔡家崖村旅游扶贫的经验和启示,探讨其产业融合发展模式,以期为其他地区的旅游发展助推精准扶贫与乡村振兴提供参考借鉴。     

动态定量称重技术控制策略和算法

在物料包装的动态定量称重过程中的一个关键性问题是称重速度和称重精度不能有效的结合起来,而解决这个问题的基本途径是根据物料的不同特性选择不同的控制策略和算法。文中主要是回顾了传统的控制策略和算法,重点介绍了4种比较先进的控制策略和算法,分析了这4种控制策略和算法的优缺点,最后简单介绍了现代先进控制策略和算法的发展趋势。     

一次性卫生用品生产线调向装置圆柱凸轮机构CAD／CAM系统

结合摆动从动件圆柱凸轮机构在一次性卫生用品生产线上调向装置中的应用,针对圆柱凸轮设计和制造的技术 难题,根据摆动从动件圆柱凸轮轮廓曲面的方程,基于两重包络法,推导出非等径加工摆动从动件圆柱凸轮的刀具轨迹 方程。并根据布尔差运算原理和展成法加工原理,基于三维软件的二次开发接口,完成了圆柱凸轮的三维参数化精确建 模和CAD/CAM系统开发。应用结果表明该系统能准确加工出调向装置中的圆柱凸轮,且成本低。该系统的开发能有 效提高圆柱凸轮的设计和制造效率。     

A signature enrichment design with Bayesian adaptive randomization

Clinical trials in the era of precision cancer medicine aim to identify and validate biomarker signatures which can guide the assignment of individually optimal treatments to patients. In this article, we propose a group sequential randomized phase II design, which updates the biomarker signature as the trial goes on, utilizes enrichment strategies for patient selection, and uses Bayesian response-adaptive randomization for treatment assignment. To evaluate the performance of the new design, in addition to the commonly considered criteria of Type I error and power, we propose four new criteria measuring the benefits and losses for individuals both inside and outside of the clinical trial. Compared with designs with equal randomization, the proposed design gives trial participants a better chance to receive their personalized optimal treatments and thus results in a higher response rate on the trial. This design increases the chance to discover a successful new drug by an adaptive enrichment strategy, i.e. identification and selective enrollment of a subset of patients who are sensitive to the experimental therapies. Simulation studies demonstrate these advantages of the proposed design. It is illustrated by an example based on an actual clinical trial in non-small-cell lung cancer.     

Some unbiased estimators versus mean per unit and ratio estimators in finite population sample surveys

We present some unbiased estimators at the population mean in a finite population sample surveys with simple random sampling design where information on an auxiliary variance x positively correlated with the main variate y is available. Exact variance and unbiased estimate of the variance are computed for any sample size. These estimators are compared for their precision with the mean per unit and the ratio estimators. Modifications of the estimators are suggested to make them more precise than the mean per unit estimator or the ratio estimator regardless of the value of the population correlation coefficient between the variates x and y. Asymptotic distribution of our estimators and confidnece intervals for the population mean are also obtained.     

The two-period crossover design with baseline measurements

We consider a two-period crossover study in which each patients measured on the response variable at the start as well as at the end of both periods. We examine models in which the carryover effect at the start of the second period may be different from the carryover effect at the end, and in which the correlations between observations decrease as a function of the time between them.

In trials with a relatively short washout period, we recommend that the second baseline measurement not be incorporated into the analysis and that the data be evaluated by analysis of covariance, with the difference between the post-treatment values as the response variable and the first period's baseline value as the covariate. The absence of carryover effects must be assumed.

When the washout period is moderately long (comparable in length to either treatment period), the preferred analysis for a difference between direct treatment effects will again generally be based on the differences between post-treatment values. An analysis based on changes from baseline would, under certain assumptions about the form of the variance-covariance matrix, be preferred only for quite long washout periods and large correlations between observations. Even then, the efficiency of the test for equality of direct effects is improved if the difference between the baseline values is used as the covariate.