张庄铁矿高阶段矿房切割天井施工工艺试验

张庄铁矿设计采矿方法为大直径深孔阶段空场嗣后充填法。为了最大化发挥采矿设备性能，降低采切工程量，提高回采效率，通过实施一系列技术攻关，实现了将采矿阶段高度由原来的60 m提高到90 m。而作为最初爆破回采的自由面及爆破补偿空间，切割天井施工工艺为影响高阶段矿房爆破回采效果的关键因素，施工质量的优劣，直接影响矿房爆破回采生产作业能否顺利进行，而二次处理在增加施工成本的同时将带来安全隐患。张庄铁矿在面临可参考的成熟经验较少的情况下，结合现场可用的作业条件采取了对比试验的方法，在安全、技术及经济多方面综合分析比较下，确定了最终方案，为张庄铁矿安全稳定生产奠定了基础，同时研究成果可为大型地下矿山生产实践提供一定的参考。     

基于竹筋-钢筋骨架的人工假顶首层充填厚度研究及现场应用

采用简支梁理论、ANSYS软件数值模拟与现场试验相结合的方法,对竹筋-钢筋骨架人工假顶进行了可行性、受力行为、破坏方式与合理设计参数研究。结果表明,竹筋-钢筋骨架人工假顶结构可有效保护上部充填体,最优充填厚度为4.75 m; 采用竹筋-钢筋配筋方式可兼顾采场稳定性与经济效益,减少支护成本约15%。     

Parametric study of aluminium alloy fouling in marine environment using RSM technique

ABSTRACT

Fouling is known to be a prominent industrial problem which is greatly affected by parameters like temperature, time and flowrate. The aim of this work was to simulate the fouling process in AA 6061 by developing a model through Minitab 16 and evaluate the models. Box Behnken design of Response surface methodology was applied for modelling and optimization of fouling propensity in artificial sea water. A response surface model was obtained and Analysis of Variance was performed to test the significance of the model. Fouling propensity was found in terms of weight gain. An experimental rig consisting of a recirculating loop mimicking the industrial conditions of fouling was used in the study. SEM analysis shows uneven deposits on the metal surface. Sharp, irregular deposits pressed deep into the metal was observed. The finding of this work would enable us to evaluate the individual and interactive effects of the parameters.     

基于改进人工蜂群算法的冗余机器臂逆解研究

针对具有移动关节的7自由度机械臂逆运动学求解困难的问题,提出了一种基于改进人工蜂群算法的逆运动学求解方法。首先根据冗余机械臂的物理结构简化出几何模型,利用D-H法建立运动学模型,由坐标系变换得到正运动学的解。由于该冗余机械臂不满足Pieper准则,难以用传统方法求得封闭解;因此采用改进人工蜂群智能算法,利用位置误差与姿态误差的标准差作为目标函数,求取逆运动学的最优解,并利用Matlab编程进行仿真验证,仿真结果表明该方法准确有效,为具有移动关节的冗余机械臂逆运动学的求解提供了一种新的途径。     

Investigation of flow parameters of Reiner–Philippoff nanofluid flow with higher-order slip properties,activation energy,and bioconvection by artificial neural networks

In this study, the flow parameters of Reiner–Philippoff nanofluid flow with high-order slip properties, activation energy, and bioconvection have been analyzed using artificial neural networks (ANNs). Local Nusselt number (LNN), local Sherwood number (LSN), and motile density number (MDN) are considered as flow parameters. Numerical values have been obtained by numerical methods using flow equations. To estimate the flow parameters, three different ANN models have been designed. The Levenberg–Marquardt training algorithm is used in multilayer perceptron network models with 10 neurons in the hidden layers. In all, 70% of the data set has been used for training the models, 15% for validation, and 15% for testing. The performance analysis of the network models has been made by calculating the determined performance parameters. The R values for the LNN, LSN, and MDN parameters have been calculated as 0.99261, 0.98769, and 0.99102, respectively, and the average deviation values are −0.65%, 0.06%, and −0.11%, respectively. The attained outcomes showed that the ANNs can predict the LNN, LSN, and MDN, which are the flow parameters of the Reiner–Philippoff nanofluid flow, with high accuracy.     

Factors influencing the use of artificial intelligence in government: Evidence from China

Some studies have discussed the potential and challenges related to the use of artificial intelligence (AI) in government. However, there are few empirical studies that have examined factors that influence the use of AI in government. By collecting policy documents and empirical data from the government, IT enterprises, and the public in China, we identified the influencing factors in the three stages of government adoption, implementation, and decision-making. The research results show that the influencing factors of government application of AI are different at different stages and with different stakeholders’ backgrounds.     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.     

Use of a sanitary sheath at artificial insemination by nonprofessional technicians does not markedly improve pregnancy rates to artificial insemination in pasture-based dairy cows

Plastic sanitary sheaths over artificial insemination (AI) guns have been used at the time of AI to improve hygiene at AI and fertility in cattle, but fertility responses have been variable in studies when AI was performed by professional inseminators. The aims of this study were to investigate whether the use of a sanitary sheath at the time of AI carried out by nonprofessional (do-it-yourself, or DIY) inseminators improves pregnancy rates to AI in pasture-based dairy cows and whether effects of sheaths are greater in cows with contaminated vulvas and in cows at increased risk of extended calving to conception intervals. Lactating dairy cows located in 10 pasture-based herds in a subtropical region of northern Australia were inseminated by herd-based DIY inseminators and assigned to be inseminated with (n = 3,655) or without (n = 3,969) a sanitary sheath, with potential effects assessed using multivariable logistic regression. Overall, use of a sheath at the time of AI did not significantly affect pregnancy rates to AI (36.3% for those inseminated without a sheath vs. 36.8% for those inseminated with a sheath; odds ratio: 1.02; 95% confidence interval: 0.92–1.11). Effects of using a sheath on pregnancy rates to AI varied by herd, with lower pregnancy rates with the use of sheaths in 1 herd and some evidence of increases in 3 herds. Unexpectedly, there was evidence that the effect of sheath on pregnancy rates was less positive (or more negative) when the vulva was classified as dirty before any cleaning of the vulva before insemination compared with when the vulva was classified as clean (interaction odds ratio: 0.75; 95% CI: 0.56–1.00). Interactions between sheath and other explanatory variables that could affect fertility were not significant; thus, there was no compelling evidence that the effect of using a sheath was modified by any of these variables. We conclude that the use of sheaths during AI of pasture-based dairy cows by DIY inseminators does not, on average, markedly improve pregnancy rates to AI. However, responses may vary between herds, and the response to sheaths may be inferior (i.e., less positive or more negative) when a cow's vulva is contaminated with feces or discharge at the time of AI compared with when the vulva is clean.     

个性化学习路径推荐综述

近年来，伴随着现代信息技术的迅猛发展，以人工智能为代表的新兴技术在教育领域得到了广泛应用，引发了学习理念和方式的深刻变革.在这种大背景下，在线学习超越了时空的限制，为学习者“随时随地”学习提供了更多的可能性，从而得到了蓬勃发展.然而，在线学习中师生时间、空间分离的特征，导致教师无法及时掌握学生的学习状态，一定程度上制约了在线学习中教学质量的提升.面对多元化的学习需求及海量学习资源，如何迅速完成学习目标、降低学习成本、合理分配学习资源等问题成为限制个人和时代发展的重大问题.然而，传统的“一刀切”的教育模式已经不能满足人们获取知识的需求了，需要一个更高效、更科学的个性化教育模式，以帮助学习者以最小的学习成本最大限度地完成学习目标.基于以上背景，如何自动高效识别学习者特征，高效地组织和分配学习资源，为每一位学习者规划个性化路径，成为面向个体的精准化教育资源匹配机制研究中亟待解决的问题.系统地综述并分析了当前个性化学习路径推荐的研究现状，并从多学科领域的角度分析了对于同一问题的不同研究思路，同时也归纳总结了当前研究中最为主流的核心推荐算法.最后，强调当前研究存在的主要不足之处.     

竞技二打一游戏中同等牌力的研究

全国竞技二打一扑克锦标赛是国家体育总局棋牌运动管理中心推出的新兴项目，比赛采用复式赛赛制，然而这种赛制存在无法杜绝线上比赛作弊的问题，为此提出用同等牌力赛制来代替复式赛制进行比赛的设想。本文主要针对如何判定和选取具有同等牌力的初始手牌进行研究，提出用等级难度评估指标来计算初始手牌的难度，初始手牌难度相近的牌认定为同等牌力，并给出了同等牌力的选取方法；为保证一副牌所得等级难度评估指标的可靠性，提出用多个不同水平的“二打一AI程序”来代替真人打牌产生牌谱的方法。实验证明了同等牌力生成方法的有效性，本文提出的同等牌力方法应用于比赛是可行的。