Performance Histogram Curve: Abstractive Visualization and Analysis of NBA Games

NBA game is one of the world’s most exciting sports. Multiple datasets for a NBA game are available, e.g., play-by-play data, shot-position data, twitter and videos. Existing methods for visualizing game data commonly focus on the composition of multi-variate information of a game process. In this paper, we introduce a new parametric modeling approach, Performance Histogram Curve (PHC), that locally and adaptively encodes the game progression with game-related features derived from the play-by-play data. By transforming a PHC into the two-dimensional space with a two-phase projection technique, we create a unique 2D line representation. The 2D representation and auxiliary views abstracts the progress of a game and the performance of each team along the timeline. Our integrated system favor browsing a single play, analyzing game performance, and comparing multiple games. We conducted two case studies to demonstrate the effectiveness of our approach.     

A spatio‐temporal water quality assessment of the Beas and Sutlej Rivers at the Harike Wetland: A Ramsar site in Punjab,India

Lakes play a vital role in regulating water storage, flow of river water, and ultimately maintaining a balanced ecosystem. Spatial and temporal variations in physicochemical parameters of water in Harike Wetland, a Ramsar site in the northwestern state of Punjab, India, were studied. This study was conducted on a monthly basis from January to December 2015. The water quality was studied at ten locations from sites 1 to 10 upstream, central and downstream from Harike Lake for ten physicochemical parameters, including temperature, pH, electrical conductivity, turbidity, dissolved oxygen concentration biological oxygen demand, nitrate and phosphate concentrations and salinity. The findings of this study revealed that, except for temperature and pH, all parameters exhibited relatively higher values for the Sutlej River, compared with the Beas River, with sampling sites 5 to site 7 exhibiting intermediate results. The mean seasonal temperature variations ranged from 16.9 to 26.6 °C, the pH from 7.7 to 8.2, electrical conductivity from 223 to 303 μS cm^?1 and TDS concentration from 148.7 to 180.4 ppm. Correlation analysis was conducted to assess the relations between the variables. The electrical conductivity exhibited a high positive correlation with salinity and biological oxygen demand, whereas it correlated negatively with the dissolved oxygen concentration. Box and whisker plots were also plotted for the study results to better examine the data distribution.     

The annual cycle of Flehmen in black-tailed deer (Odocoileus hemionus columbianus)

Flehmen is a stereotyped response of ungulates and other mammals to urine. In black-tailed deer, Flehmen occurs typically in males (rarely in females), and its frequency shows an annual cycle. Flehmen in response to female urine was most frequent in November, and to male urine in January. The response minimum to both types of urine occurred in May. Fifty-five to 100% of initial responses to female urine resulted in Flehmen. The deer responded more often to female urine, and the difference between the responses to female and male urine increased from May to November. A male's own urine released Flehmen more often than did urine of other males. The response intensity varied with the spatial orientation of the male to the urinating female, and responses were usually limited to distances of 15 m or less.     

基于时间冗余的显著测量误差处理方法

提出基于时间冗余的不可删显著误差处理方法。对于该类特殊变量，采用线性回归的方法，根据历史数据进行预测，进而代替实际到量值进行协调运算。大大降低显著误差对协调数据的污染，确保协调物度。通过实例数据仿真计算证实该方法的有效性。     

一类考虑病毒发生变异的SIS疾病传播模型

为了研究变异行为对病毒传播的影响,提出了一个病毒发生变异的疾病传播模型,在模型中考虑了两种病毒相互转换的过程,计算机模拟结果表明,两种病毒的稳态感染比例与它们之间的相互转换概率γ1和γ2有关,当γ1＞0且γ2=0时,I1型感染者将消失,当γ1与γ2都大于0时,I1/I2与γ1/γ2成反比,且与α1/β1和α2/β2的取值无关.研究还发现病毒变异时由于缺乏对应的治疗药物和措施而出现一段真空期,这导致变异病毒的感染比例快速增加,但真空期的出现只能增加感染者的瞬时感染比例,而对稳态感染比例没有影响.该研究对人们深入理解病毒传播机理具有启发作用.     

LDE融合光谱回归分类的光照变化人脸识别

针对光照变化人脸识别问题中传统的光谱回归算法不能很好地进行特征提取而严重影响识别性能的问题,提出了局部判别嵌入优化光谱回归分类的人脸识别算法。计算出训练样本的特征向量;借助于数据的近邻和分类关系,利用局部判别嵌入算法构建分类问题所需的嵌入,同时学习每种分类的子流形所需的嵌入;利用光谱回归分类算法计算投影矩阵,并利用最近邻分类器完成人脸的识别。在两大人脸数据库扩展YaleB及CMU PIE上的实验验证了该算法的有效性,实验结果表明,相比其他光谱回归算法,该算法取得了更高的识别率、更好的工作特性,并且降低了计算复杂度。     

基于FBG传感器网络的煤矿巷道在线监测系统设计

在掘进和采煤的过程中,巷道围岩的受力情况复杂多变,因此,巷道离层位移和围岩压力的实时监测是保证巷道正常工作的一个重要因素。设计了一种基于FBG传感器网络的煤矿巷道在线监测系统。该系统实现井下700 m数据采集,井上分析处理,可提供时序趋势变化、结构分布变化和阈值报警等功能。根据朱仙庄煤矿巷道的特点,系统安装4只FBG位移传感器、4只FBG土压力传感器和4只FBG温度传感器,对巷道掘进区域的离层位移、围岩压力和温度变化进行在线监测。监测结果表明:系统对离层位移、围岩压力和巷道温度变化反映灵敏,能够有效保证巷道掘进的正常进行,且为后续巷道施工提供数据支持和理论依据。     

Spatial and temporal variability in lake trout diets in Lake Ontario as revealed by stomach contents and stable isotopes

Lake trout (Salvelinus namaycush) are an ecologically and economically important piscivore with reported differences in diet and feeding behaviour throughout its range. Eleven stomach content and stable isotope-based metrics were used to describe diets of 349 lake trout between two years (2013 and 2018) and among geographic zones (west, central, east, Kingston basin) in Lake Ontario. Using individual (e.g., volumetric, %V) and aggregate (e.g., index of relative importance, %IRI) diet metrics, we found an overwhelming dominance of alewife (Alosa pseudoharengus) in lake trout diets among some zones in 2013 (%V = 23.3 – 92.7; %IRI = 12.2 – 99.5) and all zones in 2018 (%V = 83.9 – 96.7; %IRI = 96.5 – 100). Round goby (Neogobius melanostomus) and rainbow smelt (Osmerus mordax) were secondary lake trout prey items with relative diet percentages only marginally reflected by spatial and temporal variation in prey abundance (round goby: %V = 1.0 – 33.3, %IRI = 0.1 – 13.2; rainbow smelt: %V = 2.5 – 54.0, %IRI = 0.1 – 54.0). Carbon (δ¹³C) and nitrogen (δ¹⁵N) isotopic niche areas and orientations were similar across all year-zone combinations reinforcing temporal and spatial consistency in lake trout diet. The findings of this study advance the time series in describing Lake Ontario lake trout diets and can be used to complement stock assessments and management decisions associated with carrying capacity for the diverse salmonid community.     

基于引力搜索算法的分数阶变异时序回归GSA-TSGM(1,1)模型

为了利用分数阶累加算子在灰色短期预测中的高效性能,首次将分数阶累加算子引入变异时序回归模型以期取得更高的预测精度。主要方法如下：首先取湖北省链子崖某监测点1978—1987年的十年数据作为训练集并使用引力搜索算法确定最佳分数阶累加阶数,而1988—1993年的六年数据作为验证集验证提出的模型;其次对比了经典灰色模型GM(1,1)、分数阶累加灰色模型、变异时序回归模型TSGM(1,1)三种灰色模型。结果如下：首先修正了陈西江等人变异时序回归模型仿真时出现的错误,其次表明了相比于其他的模型,基于引力搜索算法的分数阶累加时序回归模型在进行灰色长期预测中具有较高的预测精度。因此,通过分数阶累加算子提高了灰色理论中长期预测模型的精度,为灰色长期预测提供了指导。