Subjects: Geosciences >> Geography submitted time 2019-11-15 Cooperative journals: 《干旱区地理》
Abstract：利用常规气象观测资料、NCEP/NCAR 1°×1°（美国气象环境预报中心—NCEP和美国国家大气研究中心—NCAR）再分析资料、全球同化系统(GDAS)数据、引入基于拉格朗日方法的气流轨迹模式（HYSPLIT_v4.9）、FY-2E卫星资料、多普勒雷达产品，对2014年2月和2016年3月天山北麓的两次暴雪天气过程进行了诊断分析。结果表明：两次暴雪过程的降雪落区均是出现在500 hPa槽前、低层切变或辐合区、高层辐散区、温度平流梯度在垂直方向大值区、相当黑体亮度温度(TBB)中心边缘的梯度较大处重叠区域。通过诊断发现，2016年暴雪天气的暴雪区上空有类似于暴雨过程的湿对称不稳定存在，使得大气潜在不稳定能量较大，为暴雪提供了不稳定机制。而在2014年暴雪天气中没有发现湿对称不稳定，说明条件对称不稳定并不是造成暴雪的唯一原因，还可能受别的不稳定机制或动力因子、热力因子影响，但其对单位时间内降雪强度有明显的增幅作用。分析雷达回波特征的演变发现，雷达回波中心的强度、持续时间、范围与强降雪中心的变化一致。
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-05-10 Cooperative journals: 《计算机应用研究》
Abstract： In order to avoid local-trap and premature convergence of robot motion planning in 2D complex environments, this paper proposes an improved metaheuristics-adaptive genetic algorithm (GA) . Firstly, it adoptes the random Dijkstra algorithm to create initial population; secondly, in each generation of the GA, improves the created paths, and replaces the conventional selection operator in GA with an adaptive one; finally, by using feedback information of the search process, the adaptive selection operator can control the selective pressure appropriately throughout the algorithm. To validate the effectiveness of the proposed method, compares the algorithm with two other methods in MATLAB. The results show that the proposed method can avoid the local convergence problem in motion planning, and can generate feasible path in complex environments.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem that the existing attitude estimation method can not accurately extract the feature parameters, this paper proposed a hierarchical model based on structured support vector machine (SSVM) and convolutional neural network (CNN) . First, it showed how a SSVM based on the PS component model could be implemented as a two-layer neural network, where the first layer was the convolutional layer and the other layer was the loss-enhanced inference layer. Then, by transforming the structured form of the model into a neural network in the model, the proposed method could simultaneously learn the structural model and the appearance model, and then backpropagated the error to learn the underlying learnable parameters. These parameters could be derived from the appearance model features. Extracted out. Finally, the SSVM model was transformed into a neural network model, the error was propagated back to the lower layer, and the exact SSVM loss was calculated, while the original SSVM was learned by the sub-gradient-based method. Comparing the model with the current advanced recognition model, the results show that the proposed success rate of the hierarchical model is 6% higher than the comparison method and has stronger recognition performance.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the drawbacks of the classical WSN coverage model, especially if a sensor dies, K-coverage model requires at least k sensor nodes to monitor whether there is a target within its coverage area. This paper proposed a mobile WSN coverage method based on improved adaptive genetic algorithm, which provided continuous monitoring of specified targets for longest possible time with limited energy resources. The algorithm took into account that the motion sensor could move at variable speeds continuously to ensure that all targets were within their coverage. Simulation results show that in the case of mobile nodes, the life span and the number of data packets of the improved method are obviously improved compared with other commonly models.
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2017-12-07 Cooperative journals: 《南方医科大学学报》
Abstract： Objective To explore the clinical value of screening the serum markers during the second trimester of pregnancy in preventing congenital birth defect and predicting the pregnancy outcome. Methods Between November, 2011 and October, 2013, a total of 25 520 pregnant women (15-20 + 6 gestational weeks) underwent a screening test of triple serum markers including free beta-human chorionic gonadotrophin (free β-hCG), alpha-fetoprotein (AFP), and unconjugated estriol (µE3) during the second semester of pregnancy. The women identified by the screening test to have high risks were referred to invasive prenatal diagnosis by amniocentesis, or to color Doppler ultrasound examination for suspected patent neural tube defect (NTD), and their pregnancy outcomes were followed up. Results High-risk pregnancies were identified by the screening test in 4.91% (1254/25520) of the total cohort. Of the 818 patients receiving invasive prenatal diagnosis, the abnormal rate was 5.75% (47/818). The high-risk pregnancies identified by the screening test was associated with a significantly higher rate of abnormal outcomes compared with the low-risk pregnancies (1.91% vs 0.1%, P<0.01). Of the 210 high-risk cases of NTD, a definite diagnosis was established in 34 cases. We also found that pregnancies at an advanced age (>35 years) was associated with increased risks for trisomy 21 compared with those at younger ages (15% vs 1.65% , P<0.01). The detection rate of abnormal karyotypes in pregnancies with an abnormal MoM value of a single marker was 3.17% (6/189). Conclusion Screening tests of serum markers during the second trimester of pregnancy can be helpful in identifying fetal chromosomal and anatomical anomalies, predicting unfavorable pregnancy outcomes, and preventing birth defects in pregnancies at an advanced age. The MoM value of a single marker in the second trimester can be indicative of potential chromosomal abnormalities.
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