基于分形插值的城市降雨时间序列精细化估算

基于分形原理对济宁市降雨时间序列进行精细化插值,对降雨数据的分形特征进行分析,通过MATLAB软件计算降雨分形插值,最终将分形插值与传统插值进行对比;所得结果可满足当前中小型城市的城市雨洪建模的降雨数据需求。     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

反转构造的反转程度及其与油气聚集的关系

结合典型反转构造地震剖面，分析了断层型和褶皱型两类反转构造的反转程度，上下皆正断层型和向形褶皱型反转构造的反转程度轻微；上逆下正断层型和透镜形褶皱型反转构造的反转程度中等；上下皆逆断层型和背形褶皱型反转构造的反转程度强烈。分析了反转构造的反转程度与油气聚集的关系，处于轻微反转程度的上下皆正断层型反转和向形褶皱型反转，以及处于强烈反转程度的上下皆逆断层型反转和背形褶皱型反转不利于油气聚集；处于中等反转程度的上逆下正断层型反转和透镜形褶皱型反转类型有利于油气聚集成藏。     

Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson’s disease

Neural Computing and Applications - Speech diagnosis of Parkinson’s disease (PD) as a non-invasive and simple diagnosis method is particularly worth exploring. However, the number of samples...     

A Dual Physical Cross-Linking Strategy to Construct Tough Hydrogels with High Strength,Excellent Fatigue Resistance,and Stretching-Induced Strengthening Effect

Hydrogels with excellent stiffness, toughness, anti-fatigue, and self-recovery properties are regarded as promising water-containing materials. In this work, a dual physically cross-linked (DPC) sodium alginate (SA)/poly[acrylamide (AAm)-acrylic acid (AAc)-octadecyl methacrylate (OMA)]-Fe³⁺ hydrogel is reported, which is constructed by hydrophobic association (HA) and ionic coordination (IC). The optimal DPC hydrogel demonstrates excellent mechanical performance: tensile modulus of 0.65 MPa, tensile strength of 3.31 MPa, elongation at break of 1547%, and toughness of 27.8 MJ m^–3. SA/P(AAm-AAc-OMA)-Fe³⁺ DPC hydrogels also exhibit prominent anti-fatigue and self-recovery performance (99.1–109.7% modulus recovery and 90.4–108.9% dissipated energy recovery after resting for 5 min without additional stimuli at ambient temperature) through the reconstruction of reversible physical cross-linking. Some of the SA/P(AAm-AAc-OMA)-Fe³⁺ DPC hydrogels even exhibit a stretching-induced strengthening effect, which is similar to the performance of muscle—“the more training, the more strength.” Hence, the combination of HA and IC will provide an effective approach to design DPC hydrogels with desirable mechanical performances and a longer service life for wider applications of soft materials.     

近40年来中国西北内陆5个典型湖泊面积变化遥感分析

在全球气候变暖的背景下,研究中国西北内陆地区湖泊的面积变化不仅对水资源管理和可持续发展战略有着重要意义,也为评价气候变化与人类活动对湖泊的影响提供参考。以中国西北内陆区5个典型湖泊为研究对象,利用1970-2015年的Landsat MSS/TM/ETM+/OLI影像数据,利用归一化差异水体指数(Normalized Difference Water Index,NDWI)和改进型归一化差异水体指数(Modified Normalized Difference Water Index,MNDWI)分别提取5个典型湖泊边界并获取湖泊面积,同时利用5个典型湖泊周边的气象站降雨量、蒸发量等气象数据,尝试分析湖泊面积发生变化的原因。结果表明:红碱淖近30年来面积呈减小趋势,入湖河流拦蓄和煤炭地下开采等是导致面积减少的原因;博斯腾湖近40年来的面积呈先增加后减少的趋势,其面积变化主要受地表径流和积雪融水的影响;呼伦湖近40年来面积呈减少的趋势,其面积变化主要受入湖径流量的影响;贝尔湖近30年来呈相对稳定的趋势,其面积变化主要入湖径流量的影响;青海湖近40年来面积呈现先减小后增大的趋势,其面积变化主要受区域降水和入湖径流量的影响。     

Explaining similarity for SPARQL queries

World Wide Web - Knowledge graph has gained significant popularity in recent years. As one of the W3C standards, SPARQL has become the de facto standard query language to retrieve the desired data...     

受天气与交通事故影响的安全路线选择模型

为完善安全为第一因素的路线规划导航系统,突出“以人为本”的理念,基于OD（Origin-Destination）的路段选择,综合考虑贵阳市交通事故数据和天气数据两大影响线路风险系数的因素。建立泊松分布模型和马尔可夫模型,分析区域内交通事故易发点在晴天、阴天、雨天发生交通事故点概率和路线概率,构建风险系数指标。针对模型求得的路线安全系数采用最大决策法选出最优安全路线。结果表明,贵阳市不同天气下发生的交通事故频率有差异,检验每个地点发生交通事故数服从泊松分布;现有导航软件推荐的第一路线并不是最优路线,第二条路线才是安全系数最大的路线。基于泊松分布模型和马尔可夫模型计算交通事故发生概率,为现有导航软件中增添了安全系数为第一参考值的人性化设置,有较好的社会价值和推广性。     

基于粗糙集的光电装备延伸保修策略评估研究

光电装备延伸保修策略选择中最重要工作就是评估待选择的策略;为选出最合适策略,提高决策的科学性和合理性,克服不同指标之间的属性不一致性和以往指标确定主观性过大的问题,提出基于粗糙集和模糊集理论的综合评估模型;根据粗糙集理论和经验,采用属性指标重要度计算属性评估指标权重;与专家模糊指标评估矩阵相结合,得到最终综合评估值,选定最优策略;通过具体实例应用分析,验证方法的合理性和可行性。     

A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

Visual tracking, as a popular computer vision technique, has a wide range of applications, such as camera pose estimation. Conventional methods for it are mostly based on vision only, which are complex for image processing due to the use of only one sensor. This paper proposes a novel sensor fusion algorithm fusing the data from the camera and the fiber-optic gyroscope. In this system, the camera acquires images and detects the object directly at the beginning of each tracking stage; while the relative motion between the camera and the object measured by the fiber-optic gyroscope can track the object coordinate so that it can improve the effectiveness of visual tracking. Therefore, the sensor fusion algorithm presented based on the tracking system can overcome the drawbacks of the two sensors and take advantage of the sensor fusion to track the object accurately. In addition, the computational complexity of our proposed algorithm is obviously lower compared with the existing approaches(86% reducing for a 0.5 min visual tracking). Experiment results show that this visual tracking system reduces the tracking error by 6.15% comparing with the conventional vision-only tracking scheme(edge detection), and our proposed sensor fusion algorithm can achieve a long-term tracking with the help of bias drift suppression calibration.