1种抑制巷道信号NLOS的矿井RSSI高精度定位算法*

在RSSI（Received Signal Strength Indication）测距定位技术中,为抑制巷道信号NLOS（Non Line of Sight）传输对定位结果的影响,提出信号指纹定位和几何优化算法。在离线阶段利用高斯滤波最大值加权法和最小二乘法建立符合矿井巷道环境的无线信号测距模型,设计改进卡尔曼滤波器平滑处理离线信号值,抑制巷道信号NLOS传输带来的影响,建立离线信号指纹库;在线定位阶段,利用加权K最近邻法（WKNN）将定位目标接收到的信号值与指纹库中的信号值进行匹配,将匹配到的最优信号值参与测距定位计算,最后通过几何优化算法将定位结果归一化处理,使其符合一维定位分布。结果表明:所提算法的平均定位误差为0.9 m,相比于高斯滤波最大值加权法、经典卡尔曼滤波指纹定位算法和改进卡尔曼滤波指纹定位方法,其平均误差分别减小2.36,1.17,0.35 m。所提算法能够有效抑制巷道信号NLOS传输对RSSI测距定位的影响,可实现RSSI方法在矿井NLOS环境中的有效应用。     

Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition

An important consideration in conservation and biodiversity planning is an appreciation of the condition or integrity of ecosystems. In this study, we have applied various machine learning methods to the problem of predicting the condition or quality of the remnant indigenous vegetation across an extensive area of south-eastern Australia—the state of Victoria. The field data were obtained using the ‘habitat hectares’ approach. This rapid assessment technique produces multiple scores that describe the condition of various attributes of the vegetation at a given site. Multiple sites were assessed and subsequently circumscribed with GIS and remote-sensed data.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

双极不对称预荷电静电增强过滤除尘技术的应用

双极不对称预荷电静电增强过滤除尘技术 ,是国家“九五”科技攻关课题所取得的成果之一 ,该技术采用双极不对称荷电增强方式 ,将普通静电增强效果与粉尘凝并机能有机地结合在一起 ,既提高了过滤除尘器的收尘效率 ,尤其是呼吸性粉尘的效率 ,同时又极大地改善了滤料粉尘层的结构 ,可显著地降低过滤阻力增值 ,节约运行能耗。笔者研究的该技术应用于焊接车间的焊接烟尘的治理上 ,取得了良好的效果。现场测试表明 ,该技术对焊接烟尘的滤除效率提高了 3% ,尤其对微细粉尘效果显著 ,2 μm粉尘穿透率相对下降了 4 7%。采用超细滑石粉高粉尘负荷测试结果表明 ,过滤阻力增值降低达 30 % ,清灰效果明显改善     

曝气生物滤池处理城市污水的试验研究

采用两级曝气生物滤池处理含工业废水的城市污水。结果表明:在水温26.7~29.5℃,气/水比6∶1,进水CODcr浓度为260~600mg/L,NH3 浓度为52~90mg/L、SS浓度为60~90mg/L、滤速为2.2m/h条件下,系统取得了良好的处理效果,其CODcr、NH3、SS的平均去除效率分别达到80.2%、97.8%、95.4%、出水CODcr、NH3、SS浓度满足污水综合排放要求。     

曝气生物滤池组合工艺处理肉类加工废水生产性试验研究

以实际工程调试为依据,阐述了曝气生物滤池组合工艺的原理和特点,通过运行结果分析及运行费用核算得出结论:该套组合工艺对地处北方的肉类加工企业,是一个技术可行、比较经济的废水处理方案     

曝气生物滤池处理啤酒废水的研究

曝气物滤池使用了新型的粒状填料,能同时发挥生物降解,过滤和吸附等多种功能。实验结果表明：曝气生物滤池处理啤酒废水效果较好,当ＣＯＤ容积负荷为１０ｋｇ／（ｍ＾３．ｄ）时,在０．８ｍ／ｈ、１．４ｍ／ｈ和２．５ｍ／ｈ３种不同水力负荷下ＣＯＤ的出水度分别在５９ｍｇ／Ｌ、８２ｍｇ／Ｌ和５１ｍｇ／Ｌ以下;     

山体对烟羽弥散影响的一种数值模拟方法

本文对山地和丘陵地区中烟羽浓度扩散分布的计算提出一种方法,该方法引用浓度方程的分析解,通过对山地绕流数值计算速度势和流函数,可较简易地求得烟羽浓度分布。作为算例,文中对中条山某工厂烟囟排放的SO2,预测了它在各种风速时被输运扩敢的浓度分布。      

城市污水处理厂中水回用初探

以沈阳市污水处理厂实际工程为例 ,提出了中水回用项目的可行性、项目方案及工程投资预测     

Optimized determination of airborne tetracycline resistance genes in laboratory atmosphere

• Sampling parameters with high efficiency was determined. • Operational process to detect airborne ARGs was optimized. • Providing research basis to control airborne ARGs of a laboratory atmosphere Antibiotic resistance genes (ARGs) have been detected in various atmospheric environments. Airborne ARGs transmission presents the public health threat. However, it is very difficult to quantify airborne ARGs because of the limited availability of collectable airborne particulate matter and the low biological content of samples. In this study, an optimized protocol for collecting and detecting airborne ARGs was presented. Experimental results showed that recovery efficiency tended to increase initially and then declined over time, and a range of 550–780 copies/mm² of capture loading was recommended to ensure that the recovery efficiency is greater than 75%. As the cell walls were mechanically disrupted and nucleic acids were released, the buffer wash protects ARGs dissolution. Three ratios of buffer volume to membrane area in buffer wash were compared. The highest concentrations of airborne ARGs were detected with 1.4 µL/mm² buffer wash. Furthermore, the majority of the cells were disrupted by an ultrasonication pretreatment (5 min), allowing the efficiency ARGs detection of airborne samples. While, extending the ultrasonication can disrupt cell structures and gene sequence was broken down into fragments. Therefore, this study could provide a theoretical basis for the efficient filter collection of airborne ARGs in different environments. An optimized sampling method was proposed that the buffer wash was 1.4 µL/mm² and the ultrasonication duration was 5 min. The indoor airborne ARGs were examined in accordance with the improved protocol in two laboratories. The result demonstrated that airborne ARGs in an indoor laboratory atmosphere could pose the considerable health risk to inhabitants and we should pay attention to some complicated indoor air environment.