The impact of spatial scale on local Moran's I clustering of annual fishing effort for Dosidicus gigas offshore Peru

The spatial scale(?shing grid) of ?sheries research af fects the observed spatial patterns of?sheries resources such as catch-per-unit-ef fort(CPUE) and ?shing ef fort. We examined the scale impact of high value(HH) clusters of the annual ?shing ef fort for Dosidicus gigas of fshore Peru from 2009 to 2012.For a multi-scale analysis, the original commercial ?shery data were tessellated to twelve spatial scales from 6′ to 72′ with an interval of 6′. Under these spatial scales, D. gigas clusters were identi?ed using the Anselin Local Moran's I. Statistics including the number of points, mean CPUE, standard deviation(SD),skewness, kurtosis, area and centroid were calculated for these HH clusters. We found that the z-score of global Moran's I and the number of points for HH clusters follow a power law scaling relationship from2009 to 2012. The mean ef fort and its SD also follow a power law scaling relationship from 2009 to 2012.The skewness follows a linear scaling relationship in 2010 and 2011 but ?uctuates with spatial scale in2009 and 2012; kurtosis follows a logarithmic scale relationship in 2009, 2011 and 2012 but a linear scale relationship in 2010. Cluster area follows a power law scaling relationship in 2010 and 2012, a linear scaling relationship in 2009, and a quadratic scaling relationship in 2011. Based on the peaks of Moran's I indices and the multi-scale analysis, we conclude that the optimum scales are 12′ in 2009 ? 2011 and 6′ in 2012, while the coarsest allowable scales are 48′ in 2009, 2010 and 2012, and 60′ in 2011. Our research provides the best spatial scales for conducting spatial analysis of this pelagic species, and provides a better understanding of scaling behavior for the ?shing ef fort of D. gigas in the of fshore Peruvian waters.

Local and global approaches of affinity propagation clustering for large scale data

Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a dense similarity matrix. The local approach is partition affinity propagation (PAP) and the global method is landmark affinity propagation (LAP). PAP passes messages in the subsets of data first and then merges them as the number of initial step of iterations; it can effectively reduce the number of iterations of clustering. LAP passes messages between the landmark data points first and then clusters non-landmark data points; it is a large global approximation method to speed up clustering. Experiments are conducted on many datasets, such as random data points, manifold subspaces, images of faces and Chinese calligraphy, and the results demonstrate that the two ap-proaches are feasible and practicable.

Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative accuracy.However,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering metric.This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering metric.Realistic traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time complexity.The Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the clustering.OMNET++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in Python.The Scott’s formula estimation of the K number only matched the baseline when the road layout was simple.Moreover,the clustering algorithm required one iteration on average to converge when used with LET.

A Hierarchical Clustering and Fixed-Layer Local Learning Based Support Vector Machine Algorithm for Large Scale Classification Problems

It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed- layer local learning （HCFLL） based support vector machine（SVM） algorithm is proposed to deal with this problem. Firstly, HCFLL hierarchically dusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering. Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree. The experimental results show that compared with the existing popular algorithms such as core vector machine and decision.tree support vector machine, HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.

PDBSCAN: Parallel DBSCAN for Large-Scale Clustering Applications

Density-based algorithm for discovering clusters in large spatial databases with noise(DBSCAN) is a classic kind of density-based spatial clustering algorithm and is widely applied in several aspects due to good performance in capturing arbitrary shapes and detecting outliers. However, in practice, datasets are always too massive to fit the serial DBSCAN. And a new parallel algorithm-Parallel DBSCAN(PDBSCAN) was proposed to solve the problem which DBSCAN faced. The proposed parallel algorithm bases on MapReduce mechanism. The usage of parallel mechanism in the algorithm focuses on region query and candidate queue processing which needed substantive computation resources. As a result, PDBSCAN is scalable for large-scale dataset clustering and is extremely suitable for applications in E-Commence, especially for recommendation.

The Scale Benefit Analysis of Sugar Clusters in Resource-rich Area of Southweatern Guangxi——A Case of Chongzuo City

Based on the scope economic theory of "resource curse" and industrial clusters,the scale of sugar cluster is calculated by the output of sugarcane and sugar while the scale benefit of sugar cluster is measured by the productivity(rate of sugar production),sales output ratio,industrial output value as well as profit margin.Positive analysis of the scale merit of sugar clusters in resource-rich area of southwestern Guangxi is conducted according to related statistics of Chongzuo City.And the primary problems of sugar clusters are pointed out.The profit created by sugar for the sugar industry in Chongzuo City has already been near capacity.The sugar industry is big but not strong.With much governmental interfernce,there is no effective connections and inadequte competitive forces among subjects of the clusters.The extention of industrial chain is limited.Therefore,measures for developing sugar clusters in resource-rich area of southwestern Guangxi are proposed.Industrial structure is to be adjusted to improve the sugarcane cultivation techniques.The industrial chain should be extended to increase the economic benefits of sugar industry.Industrial support is to be strengthened and capital output for sicence and technology increased.Price regualtion fund of grain sugar is to be established with coordination with the superior region.The transformation from savings to investment should be quickened to evade "resource curse".

FUZZY CLUSTER ANALYSIS OF TURBULENT SCALES

Turbulent motion could be regarded as the superposition of fluctuations with different scales. It's of great theoretical and practical importance to determine the classification of turbulent scales quantitatively to the better description of vortex motions with different scales, and to the research of the interaction among different sclaes of vortex and the construction of better turbulent models. The mathematical method, which carries out the classification on a certain requirement, is called cluster analysis. In this paper, fuzzy cluster analysis method is used to study the classification of turbulent scales quantitatively in smooth and rough wall boundary conditions. Furthermore, the properties and interactions among all kinds of flow structures are also studied. The results are helpful to gain some insight into the properties and interactions of all kinds of turbulent scales in wall turbulent shear flow.

基于空间投影和聚类划分的SVR加速算法

数据不仅能产生价值,还对统计学的科学发展提供了动力。随着科技的飞速发展,海量数据得以涌现,但大规模的数据会导致很多传统处理方法很难满足各领域对数据分析的需求。面对海量数据时代学习算法的低效性,分治法通常被认为是解决这一问题最直接、最广泛使用的策略。SVR是一种强大的回归算法,在模式识别和数据挖掘等领域有广泛应用。然而在处理大规模数据时,SVR训练效率低。为此,该文利用分治思想提出一种基于空间投影和聚类划分的SVR加速算法(PKM-SVR)。利用投影向量将数据投影到二维空间;利用聚类方法将数据空间划分为k个互不相交的区域;在每个区域上训练SVR模型;利用每个区域的SVR模型预测落入同一区域的待识别样本。在标准数据集上与传统的数据划分方法进行对比实验,实验结果表明该算法训练速度较快,并表现出更好的预测性能。

电液3-UPS/S并联稳定平台参数振动特性分析

针对电液3-UPS/S并联稳定平台驱动液压缸的压力脉动所产生的参数振动,建立了稳定平台的参数振动方程并利用多尺度法求解了主共振响应与组合共振响应的一次近似解;分析了主共振与组合共振响应特性以及振动幅值在初始工作空间内的变化规律,最后采用四阶龙格库塔法与模态试验对参数振动模型进行验证。结果表明:数值解与理论解之间的最大误差为4.20%,固有频率理论值与试验值之间的最大误差为4.66%,可验证参数振动模型的正确性。

基于改进Yolov5s的水稻叶病检测方法

水稻叶病防治在提高水稻产量中具有重要作用,针对水稻叶病人工检查速度慢、主观性高的问题,提出一种基于改进Yolov5s的水稻叶病目标检测方法。采用K-means聚类算法得到先验框尺寸,增强检测模型对水稻叶病的适应性;将轻量级空间注意力与通道注意力融合,对高层语义特征信息增强,增强模型对病害信息的感知度;并结合特征金字塔网络,融合多尺度感受野获取目标上下文信息,有效地增强模型对目标周围特征的提取,提高目标检测的准确度。试验结果表明:改进后的Yolov5s算法平均检测精度(IOU=0.5)提高4.3%,F1值提高5.3%,帧率FPS为58.7 f/s。有效提升Yolov5s算法对水稻叶病的检测精度,达到实时检测的需求。

Impacts of changing scale on Getis-Ord Gi* hotspots of CPUE:a case study of the neon flying squid (Ommastrephes bartramii)in the northwest Pacific Ocean

We examined the scale impacts on spatial hot and cold spots of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. The original fishery data were tessellated to 18 spatial scales from 5′×5′ to 90′×90′ with a scale interval of 5′ to identify the local clusters. The changes in location, boundaries, and statistics regarding the Getis-Ord Gi＊ hot and cold spots in response to the spatial scales were analyzed in detail. Several statistics including Min, mean, Max, SD, CV, skewness, kurtosis, first quartile（Q1）, median, third quartile（Q3）, area and centroid were calculated for spatial hot and cold spots. Scaling impacts were examined for the selected statistics using linear, logarithmic, exponential, power law and polynomial functions. Clear scaling relations were identified for Max, SD and kurtosis for both hot and cold spots. For the remaining statistics, either a difference of scale impacts was found between the two clusters, or no clear scaling relation was identified. Spatial scales coarser than 30′ are not recommended to identify the local spatial patterns of fisheries because the boundary and locations of hot and cold spots at a coarser scale are significantly different from those at the original scale.

径流预报误差的混合t Location-Scale分布模型及应用

基于混合t Location-Scale分布良好的自适应性,利用k均值聚类法挖掘数据隐含结构、良好的聚类效果特点,建立了不同预见期径流预报误差混合t Location-Scale分布模型。将模型应用于雅砻江流域官地水库,对预见期分别为6、12、18 h和24 h的区间径流预报误差进行了分析与建模,结果发现混合t Location-Scale分布模型弥补了单一分布难以描述径流预报误差特征多样性的局限,能更准确地描述不同预见期径流预报误差的统计特征,误差分布与实测径流预报误差的变化规律一致,可为水库水电站的径流预报和调度运行提供更加准确、可靠的来水数据。

Caries Patterns in the Primary Dentition: Cluster Analysis of a Sample of 5,169 Arizona Children 5-59 Months of Age

Aim Cluster analysis was conducted on data from 5,169 United States （U.S.） Arizona children, age＇s 5-59-months with the goal of delineating patterns of caries in the primary dentition of pre-school children without a priori pattern definitions. Methodology Cluster analyses were conducted using all data for children ages 0-4 years in aggregate： 1） for all subjects, and 2） for subjects without crowned restored teeth. Each of these two sets of analyses consisted of 8 differently specified cluster analyses as a validation procedure. Results The caries patterns identified from the clustering analysis are： 1） smooth surfaces （other than the maxillary incisor）, 2） maxillary incisor, 3） occlusal surfaces of first molars, and 4） pit and fissure surfaces of second molars. Conclusion The cluster analysis findings were consistent with results produced by multidimensional scaling. These cross-validated patterns may represent resulting disease conditions from different risks or the timing of various risk factor exposures. As such, the patterns may be useful case definitions for caries risk factor investigations in children under 60 months of age.

新型分散型抗垢剂在S Zorb装置的工业应用

中国石化广州分公司S Zorb装置为有效抑制原料侧换热器E-7101A-G因高温结垢而导致的换热器传热效率下降、换热器总压差上涨过快等影响装置长周期运行问题,决定使用浙江杭化科技股份有限公司生产的新型分散型抗垢剂HK-17DC。工业应用结果表明,HK-17DC在线除垢及阻垢作用良好,且使用HK-17DC对装置运行和产品质量无不良影响。

Mei’s symmetry theorem for time scales nonshifted mechanical systems

We focus on Mei symmetry for time scales nonshifted mechanical systems within Lagrangian framework and its resulting new conserved quantities.Firstly,the dynamic equations of time scales nonshifted holonomic systems and time scales nonshifted nonholonomic systems are derived from the generalized Hamilton’s principle.Secondly,the definitions of Mei symmetry on time scales are given and its criterions are deduced.Finally,Mei’s symmetry theorems for time scales nonshifted holonomic conservative systems,time scales nonshifted holonomic nonconservative systems and time scales nonshifted nonholonomic systems are established and proved,and new conserved quantities of above systems are obtained.Results are illustrated with two examples.

Identification and Comparison of Aircraft Industry Clusters in China and United States

Aircraft industry is very important to the economy and security of a country,and aircraft industry clusters have already existed in the world.Based on Input-Output data and Czamanski's method,the aircraft industry clusters in China and USA were identified quantitatively in this paper.Furthermore,this article carried out comparison analyses of the identification results.The research finds out:1) a mature aircraft industry cluster would be generally composed of 7 industrial subgroups,including aircraft industry,metal making and products manufacturing industry,machinery and equipment industry,electronics industry,automobile industry,material industry and others,and electronics industrial subgroup will play a more and more important role in the cluster;2) in the range of industry-covering,the level of industry-linkage,and the economic performance,there is a tremendously large gap between the aircraft industry cluster of China and that of USA;3) the spatial evolution of these clusters or centers is highly consistent with the diffusion of a country's industrialization.Finally,based on those findings,the paper gives some advice on how to improve Czamanski's method and what China should do to develop its own competitive aircraft industry:1) China should employ institutional innovation,and turn to be market-oriented;2) China should abandon the traditional pattern of closed-development,and strengthen the interaction and collaboration between aircraft industry and related industries,especially the electronics industry;3) China should rectify and perfect its spatial development planning of aircraft industry.

Experimental Study of the Interaction between Building Clusters and Flash Floods

In recent years, flash flood disasters have occurred frequently in southwest China due to the increased frequency of extreme climate events. To solve this problem, great efforts have been made in studying the process of flash flood. However, little attention was paid on bearing body of hazard, the clusters of buildings. Thus the real disaster mechanism of flash flood remains unclear.Accordingly, based on the experiments of artificial flash floods in a conceptual solid model, this paper focuses on the flood-impacted inundation characteristics of the building clusters at different locations of the gully model, in order to obtain a better understanding of the disaster process and the interaction between the flash floods and building clusters. The results showed that, in a typical smallscale flash flood gully with hot and dry climate, 1)clusters of buildings on an alluvial fan could reduce about 35% of the flooding area by blocking the diffusion of the flood to the depression areas, and could also promote the deposition in lower reaches of the river channel by blocking the overbank flow from going back into the channel, making the width-depth ratio of the channel larger. 2) The flash flood rates of disaster and hazard on the alluvial fan are generally higher than that of the inner gully. For the inner gully,buildings located on the beaches along the lower river and the transitional areas of the straight channel and channel bends can easily be affected because of their lower elevations. For the alluvial fan, buildings nearby the meanders suffer the greatest impacts because of bank collapsing and flooding. 3) The safe vertical distance from a building to the river channel is 13 m for the buildings in the inner gully under extreme floods. Below this threshold, the smaller the vertical distance is, the greater the risk exposure is. For the buildings on the alluvial fan, especially for the buildings near the concave bank of the top rush point,the horizontal distance is more important, and the safe value is 80 m under extreme floods.

Developing a Subjective Evaluation Scale for Assessing the Built Environments of China’s Hygienic City Initiative

Objective To develop a preliminary subjective evaluation scale for assessing the built environments of China’s Hygienic City Initiative and to evaluate its reliability and validity.Methods The initial items of the scale were determined based on a review of policy documents and consultations with experts. The final items of the scale were confirmed through individual interviews with residents combined with the discretetrend method, critical ratio method, correlation coefficient method, and factor analysis method. Then, the dimensions of the scale were determined using exploratory factor analysis(EFA). The Cronbach’s α coefficient, split-half reliability coefficient, and confirmatory factor analysis(CFA) were used to assess the reliability and validity of the scale.Results A scale containing five dimensions with 22 items was established, including urban lifestyle,governance, basic functions, environmental sanitation, and amenities. The Cronbach’s α coefficient of the scale was 0.876, and the split-half reliability coefficient was 0.796. The CFA results indicate that each inspection level was within the standard limit.Conclusion The preliminarily subjective evaluation scale for assessing the built environments of China’s Hygienic City Initiative demonstrates a high level of reliability and validity. Additional empirical studies should be carried out to further verify the value of the scale in terms of practical application.

A Content-Based Parallel Image Retrieval System on Cluster Architectures

We propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval. servers to supply the service of content-based image retrieval. It adopts the Browser/Server (B/S) mode. The users could visit our system though web pages. It uses the symmetrical color-spatial features (SCSF) to represent the content of an image. The SCSF is effective and efficient for image matching because it is independent of image distortion such as rotation and flip as well as it increases the matching accuracy. The SCSF was organized by M-tree, which could speedup the searching procedure. Our experiments show that the image matching is quickly and efficiently with the use of SCSF. And with the support of several retrieval servers, the system could respond to many users at mean time. Key words content-based image retrieval - cluster architecture - color-spatial feature - B/S mode - task parallel - WWW - Internet CLC number TP391 Foundation item: Supported by the National Natural Science Foundation of China (60173058)Biography: ZHOU Bing (1975-), male, Ph. D candidate, reseach direction: data mining, content-based image retrieval.

Fluid substitution in a shaley sandstone reservoir at seismic scale

Shaley sandstone is heterogeneous at a seismic scale. Gassmann＇s equation is suited for fluid substitution in a homogeneous medium. To study the difference between shaley sandstone effective elastic moduli calculated by mean porosity as a homogeneous medium, and those calculated directly from the sub-volumes of the volume as a heterogeneous medium, computational experiments are conducted on Han＇s shaley sand model, the soft-sand model, the stiff-sand model, and their combination under the assumption that the shaley sandstone volume is made up of separate homogenous sub-volumes with independent porosity and clay content. Fluid substitutions are conducted by Gassmann＇s equation on rock volume and sub-volumes respectively. The computational data show that at seismic scale, there are minor differences between fluid substitution on rock volume and that on sub-volumes using Gassmann＇s equation. But fluid substitution on sub-volumes can take consideration of the effects of low porosity and low permeability sub-volumes, which can get more reasonable data, especially for low porosity reservoirs.