海洋天然气水合物储层拉削开采新方法及可行性分析

针对深水浅层非成岩天然气水合物借鉴刨煤机刨削采煤过程提出一种新的拉削开采方法，参照拉刀结构特点设计了一种集开采、收集和输送为一体的拉削管。建立了拉削开采三维模型，对其工作原理和工作步骤进行了说明。用有限元仿真对采空区和拉削管受力进行了分析。结果表明，岩土力学仿真下采空区开采半径和开采角度的增大都会引起剪切应力的增加，最大剪切应力发生在采空区上部的起始位置和终止位置；在不发生剪切破坏的采空区中选择体积较大者作为理想采空区，估算出拉削开采方法的日产气量为142000 m3，具有应用潜力；开采工况下，拉削管的最大等效应力小于管材的屈服极限，表明开采过程中拉削管处于弹性形变，满足方法需求。     

电子装备测试性融合评估方法

测试性是装备通用质量特性之一，其设计水平直接影响了装备保障效能的发挥，如何更加真实的评估装备的测试性水平是当前研究的热点。在研制阶段装备实物测试性试验数据数量少、获取难、费用高，可认为是“小子样”数据，为了更加全面客观地评价装备的测试性水平，需要充分利用测试性仿真试验获取仿真数据进行融合评估。进行测试性仿真试验时，研究电子装备的仿真模型、故障模型、仿真故障注入方法，获取测试性仿真数据；在此基础上，将仿真试验数据作为验前信息并进行的处理，结合“小子样”装备实物试验数据，采用贝叶斯方法进行测试性试验数据的融合来评估装备的测试性水平，提高评估结果的客观性和可信度。通过案例分析，验证了测试性融合评估方法的有效性。     

“半翻转”教学模式下评价指标体系研究与实践

研究基于“半翻转”教学模式的线上教学评价指标体系,包括课前活动开展、课中教学活动设计、课后任务以及基于此过程中的评价指标体系设计。最后通过层次分析法设计评价指标权重,设计评价算法得到动态评价结果。该评价指标体系应用在本专业“数据结构与算法”课程中,并得到良好的应用效果。     

Sustainability accounting for the construction and operation of a plant‐scale solar‐biogas heating system based on emergy analysis

Domestic heating systems have long been playing a significant role in China's energy structure. The sustainability of a hybrid solar‐biogas heating system (SBHS) under various feedstock fermentation scenarios was evaluated using emergy analysis. Representative emergy indices such as transformities, emergy yield ratio (EYR), environmental loading ratio (ELR), emergy sustainability index (ESI), ratio of waste treatment (%W), feedback yield ratio (FYR), and emission mitigation intensity (EMI; g/10¹⁰ sej) were selected to evaluate the sustainability performance of different feedstock scenarios including cow dung (CD), swine manure (SM), and poultry manure (PM). The results showed that PM fermentation scenario had greater market competitiveness, lower environmental pressure, better sustainability, and self‐organizing ability than the other two options. However, both the emergy efficiency and the CO₂ emissions mitigation intensity of PM scenario were worse than that of the SM and CD. Moreover, compared with other biogas systems and traditional agricultural systems, the hybrid SBHS was proved to be a promising mode for the treatment of rural manure waste with favorable economic benefits and environmental sustainability.     

基于遗传算法-BP神经网络法的深埋地下水水质评价

为探究开封市地下水水质特征及成因,依据开封市31眼深度600～1 600m地下水开采井的水质检测资料,系统研究了各亚含水层的水化学特征,利用遗传算法-BP神经网络法进行了水质评价,并从埋深、富水性两个方面分析了水质特征的分布规律。结果表明,开封市600～800m亚含水层地下水水质最好,800～1 400m次之,1 400～1 600m亚含水层水质最差,随着埋深的增加,水质变差,富水性越强、水质越好。可见遗传算法-BP神经网络法能够客观地描述地下水水质综合情况,避免了人为主观影响,使评价结果更为合理。     

A comprehensive appraisal of perceptual visual complexity analysis methods in GUI design

Graphical or Visual User Interface (GUI) is recognized as one of the most important application components for safety critical and business oriented software systems. It is highly advantageous for GUI designers and application developers to analyze the visual complexity of a GUI and predict users’ perception and judgment during the design phase. Although in recent years, various methods have been developed for visual complexity analysis, these have not been widely used due to applicability, practicality and validity issues. In this respect, we have conducted a comprehensive review of studies and methods in visual complexity analysis. After identifying and analyzing 85 research studies, we grouped the visual complexity analysis methods and accordingly a taxonomy is presented. Furthermore, conceptual comparison of the methods is given and gap analysis as well as possible future directions are provided. According to the our findings, major gaps for each visual complexity analysis method may be stated as follows: 1) In metric-model based methods, there is a lack of information about the suitability of the metric-model created for analysis, since the extent to which each metric contributes to visual complexity analysis is still not known exactly. 2) In heuristic- based methods, the extracted rule set is not yet extendable enough beyond the use for specific GUIs. 3) While the visual complexity analysis could be considered as a kind of computer vision task, there exist limited studies that does so. Therefore, generalizable solutions based on machine learning techniques seem to be a promising research direction to develop efficient approaches.     

Assessing Industrial Robot agility through international competitions

Manufacturing and Industrial Robotics have reached a point where to be more useful to small and medium sized manufacturers, the systems must become more agile and must be able to adapt to changes in the environment. This paper describes the process for creating and the lessons learned over multiple years of the Agile Robotics for Industrial Automation Competition (ARIAC) being run by the National Institute of Standards and Technology.     

基于VSE的大南湖一矿通风系统现状仿真与评估

为了掌握大南湖一矿通风系统现状,科学评估其安全性、稳定可靠性及合理性,对全矿进行了通风参数精准普查,基于VSE软件对通风系统运行状况进行了仿真与评估。结果表明大南湖一矿通风系统存在部分巷道微风、回风大巷风速偏高、井下通风设施较多、部分角联分支易发生风流转向、矿井通风阻力分布不合理等问题,为系统的优化改造指明了方向。     

Technical note: Genetic groups in single-step single nucleotide polymorphism best linear unbiased predictor

Genetic groups, also called unknown or phantom parents groups, are often used in dairy cattle genetic evaluations to account for selection that cannot be accounted for by known genetic relationships. With the advent of genomic evaluations, the theory of genetic groups was extended to the so-called single-step genomic BLUP (ssGBLUP). In short, genetic groups can be fitted in ssGBLUP through regression effects, or by including them in the pedigree and computing the adequate combined pedigree and genomic relationship matrix. In this study, we applied the so-called Quaas and Pollak transformation to a system of equations for single-step SNP BLUP (ssSNPBLUP), such that genetic groups can thereafter be included in the pedigree. The example in this study showed that including the genetic groups in the pedigree for ssSNPBLUP allowed reduced memory burden and computational costs in comparison to genetic groups fitted as covariates.