Indigenous Knowledge on Soil Classification of Ethnic Groups in Luang Prabang Province of the Lao PDR

The objectives of this study were to demonstrate ethno-scientific elicitation techniques in retrieving indigenous knowledge at village-level, and to document the indigenous soil classification systems of different ethnic groups in Luang Prabang province in the Lao PDR. The study area comprised three villages – Nambo, Huaymaha and Thapo, in the Phonxay district of Luang Prabang province. Three ethnic groups were covered by the study – Hmong, Khmu and Lao Loum. All three ethnic groups used soil color as main criteria for soil classification. However, even within the same ethnic group, sometimes different villages have differences in the way they classify soils; this was apparent for the Hmong ethnic group in the villages of Huaymaha and Nambo. A significant difference of the Lao Loum ethnic group from the other two, was the emphasis used in classifying soil types according to their water holding capabilities. In contrast, the Khmu and Hmong classified many soil types in relation to their rock content (‘with rock’ or ‘pure rock’ sometimesbeing used). The results of the study suggest that the ethnic groups classify the soils in relation to their potential for different types of agricultural production.

On the Construction and Classification of the Common Invariant Solutions for Some P(1,4) -Invariant Partial Differential Equations

We consider the following (1 + 3)-dimensional P(1,4)-invariant partial differential equations (PDEs): the Eikonal equation, the Euler-Lagrange-Born-Infeld equation, the homogeneous Monge-Ampère equation, the inhomogeneous Monge-Ampère equation. The purpose of this paper is to construct and classify the common invariant solutions for those equations. For this aim, we have used the results concerning construction and classification of invariant solutions for the (1 + 3)-dimensional P(1,4)-invariant Eikonal equation, since this equation is the simplest among the equations under investigation. The direct checked allowed us to conclude that the majority of invariant solutions of the (1 + 3)-dimensional Eikonal equation, obtained on the base of low-dimensional (dimL ≤ 3) nonconjugate subalgebras of the Lie algebra of the Poincaré group P(1,4), satisfy all the equations under investigation. In this paper, we present obtained common invariant solutions of the equations under study as well as the classification of those invariant solutions.

Preliminary Group Classification for One Class of Nonlinear Wave Equations

The group classification is carried out on the nonlinear wave equation u_(tt)=f(x,u,u_x)u_(xx)+g(x,u,u_x)by using the preliminary group classification approach.The generators of equivalence group are determined and thecorresponding reduced forms are obtained.The result of the work is shown in table form.

Group classification for path equation describing minimum drag work and symmetry reductions

The path equation describing the minimum drag work first proposed by Pakdemirli is reconsidered （Pakdemirli, M. The drag work minimization path for a fly- ing object with altitude-dependent drag parameters. Proceedings of the Institution of Mechanical Engineers, Part C, Journal of Mechanical Engineering Science 223（5）, 1113- 1116 （2009））. The Lie group theory is applied to the general equation. The group classi- fication with respect to an altitude-dependent arbitrary function is presented. Using the symmetries, the group-invariant solutions are determined, and the reduction of order is performed by the canonical coordinates.

Preliminary group classification of quasilinear third-order evolution equations

Group classification of quasilinear third-order evolution equations is given by using the classical infinitesimal Lie method, the technique of equivalence transformations, and the theory of classification of abstract low-dimensional Lie algebras. We show that there are three equations admitting simple Lie algebras of dimension three. All non-equivalent equations admitting simple Lie algebras are nothing but these three. Furthermore, we also show that there exist two, five, twenty-nine and twenty-six non- equivalent third-order nonlinear evolution equations admitting one-, two-, three-, and four-dimensional solvable Lie algebras, respectively.

The classification of travelling wave solutions and superposition of multi-solutions to Camassa-Holm equation with dispersion

Under the travelling wave transformation, the Camassa-Holm equation with dispersion is reduced to an integrable ordinary differential equation （ODE）, whose general solution can be obtained using the trick of one-parameter group. Furthermore, by using a complete discrimination system for polynomial, the classification of all single travelling wave solutions to the Camassa-Holm equation with dispersion is obtained. In particular, an affine subspace structure in the set of the solutions of the reduced ODE is obtained. More generally, an implicit linear structure in the Camassa-Holm equation with dispersion is found. According to the linear structure, we obtain the superposition of multi-solutions to Camassa-Holm equation with dispersion.

Site classification of the eastern forest region of Daxing'an Mountains

Based on the plot data from the investigation and the theory of forest ecology and ecological system,the site classification of the eastern forest region of Daxing’an Mountains was made by mean of mathematical method. The main factors were slope, thickness of soil layer, slope position and slope aspect. Grades of slope were used as the division standard for site type group. The slope aspect, slope position and thickness of soil layer were used as the division standards for site type. Altogether 7 site type groups and 15 main site types were determined the region. It provided reliable fundamental basis for the reasonable management and planting design in the area.

Solution of ODE u″+p(u)(u′)2+q(u)=0 and Applications to Classifications of All Single Travelling Wave Solutions to Some Nonlinear Mathematical Physics Equations

在旅行波浪转变下面，一些非线性的部分微分方程例如 Camassa 河边肥沃的低地方程，高顺序的 KdV 方程，等等，被归结为 u″ 表示的一首 integrable 颂诗+ p (u)(u')2+ q (u)= 0 答案能被给其将军。而且，为多项式联合完全的辨别系统，这些方程的所有单个旅行波浪答案的分类被获得。方程 u″0 包括的 + p (u)(u')2+ q (u)= 是的方程(u')2= f (u) 一种特殊情况，建议方法能也因此被用于很多非线性的方程。这些完全的结果不能被任何间接方法获得。

Two Important Classes of p-groups and the Orders of Their Automorphism Groups

在纸，我们获得 p 组的二个无限的班，计算他们的自守组的订单并且改正一个错误(也许印错) 在 1980 的 Rodney James'paper。

On-demand multicast routing protocol based on node classification in MANET

An improved on-demand multicast routing protocol(ODMRP), node classification on-demand multicast routing protocol(NC-ODMRP), which is based on node classification in mobile ad hoc networks was proposed. NC-ODMRP classifies nodes into such three categories as ordinary node, forwarding group(FG) node, neighbor node of FG node according to their history forwarding information. The categories are distinguished with different weights by a weight table in the nodes. NC-ODMRP chooses the node with the highest weight as an FG node during the setup of forwarding group, which reduces a lot of redundant FG nodes by sharing more FG nodes between different sender and receiver pairs. The simulation results show that NC-ODMRP can reduce more than 20% FG number of ODMRP, thus enhances nearly 14% data forwarding efficiency and 12% energy consumption efficiency when the number of multicast senders is more than 5.

High Performance Classification of Android Malware Using Ensemble Machine Learning

Although Android becomes a leading operating system in market,Android users suffer from security threats due to malwares.To protect users from the threats,the solutions to detect and identify the malware variant are essential.However,modern malware evades existing solutions by applying code obfuscation and native code.To resolve this problem,we introduce an ensemble-based malware classification algorithm using malware family grouping.The proposed family grouping algorithm finds the optimal combination of families belonging to the same group while the total number of families is fixed to the optimal total number.It also adopts unified feature extraction technique for handling seamless both bytecode and native code.We propose a unique feature selection algorithm that improves classification performance and time simultaneously.2-gram based features are generated from the instructions and segments,and then selected by using multiple filters to choose most effective features.Through extensive simulation with many obfuscated and native code malware applications,we confirm that it can classify malwares with high accuracy and short processing time.Most existing approaches failed to achieve classification speed and detection time simultaneously.Therefore,the approach can help Android users to keep themselves safe from various and evolving cyber-attacks very effectively.

Simple groups with orders 2~a3~b5~cp^d, 2~a3~b7~cp^d and 2~a3~b5~c7~d

This work deals with the power exponent 1rand 2r respectively of the maximal and second-maximal prime factors of the order of simple K4-group, and the classification for simple 4{5,7}K--group G (i.e. G can not be divided by 5 nor by 7 or ()Gp= 4 ), simple 5 -4K-group G (i.e. G can not divided by 5 and ()Gp=4) and simple 7-4K-group G (i.e. G can not divided by 7 and ()Gp= 4). It is derived that 1r =1, 2 and 4, and 2r is not greater than 4. All the simple 4K-groups with order 235,237abcdabcdpp and 2357abcd are obtained.

临床科室功能定位和病种结构分类的精细化管理

目的探索医院临床科室分类方法,为实现科室的精细化管理提供科学依据。方法利用2022年深圳市某三甲医院临床科室的实际占用总床日数、出院患者手术占比、出院患者四级手术比例、CMI值、DRG组数进行快速聚类分析,把临床科室分成三个类别,分析不同类别的特点和临床科室的分类结果。结果30个临床科室分类成一般手术科室、非手术科室和高难度治疗科室。分类结果与预期一致,但普外科分类于非手术科室,而新生儿科分类于一般手术科室。结论应用快速聚类法进行临床科室分类,能客观反映科室特点,达到医院精细化管理的目的。利用分组异常结果信息,有利于分析临床科室的功能定位和病种结构特点,进行调整优化。

基于CMCP-LMCL的多分类深度神经网络及其应用

多分类问题涉及信用风险管理、股票走势预测等多个领域。深度神经网络(DNN)是常用于多分类预测的机器学习模型,然而输入特征维度较高且存在冗余信号时,将加重其可解释性不强和结构冗余等缺陷;同时,常用的Softmax损失也可能面临分类边界模糊导致预测效果不佳等问题。为此,本文针对多分类问题,提出一个新的深度神经网络CMCP-LMCL,利用CMCP变量选择方法压缩输入特征到第1隐藏层的权重。该方法融合权重的组结构,能够剔除无关特征以及不重要的连接;同时,对特征层之外的权重施加权重衰减L;2;惩罚,有利于改进过拟合问题。新方法的增强边缘余弦损失(LMCL)在Softmax基础上引入扩大参数和距离参数,增大分类决策边界的间隔以期提高分类预测性能。模拟分析表明,对比已有DNN和传统分类方法,无论特征以简单线性形式还是复杂非线性形式映射到因变量,本文所提出的方法均具有良好的特征选择性能和预测表现。基于信用贷款数据的实证分析表明,该方法能够有效选择风险指标并进行违约风险预警。

基于兴趣小组的管理类人才分类培养实践——以河北农业大学文管学院为例

经济社会发展对管理类人才需求日益多元化,传统人才培养模式亟待变革。在分析人才分类培养的逻辑基础上,提出基于兴趣小组的人才分类培养实践活动。结合学生发展意愿,总结出“应用型小组”“研究型小组”的兴趣小组,详细分析了各个小组项目化训练的内容和培养效果,为高校人才分类培养的实施提供经验借鉴。

湖南省辰溪县古树群特征与分级研究

对辰溪县44个古树群调查研究,分析古树群群落特征,计算树种重要值和古树群生物多样性指数,对古树群评估分级,希望为辰溪县乃至更大区域的生物多样性研究与保护、古树群利用提供理论依据。本研究采用实地专业调查,测量古树胸径、树高等因子,访问居民了解村寨和古树群基本情况,从生态、人文、民居、交通、利用现状及潜能这五个方面对古树群评分。44个古树群共有2258株古树,隶属23科41属49种;植被类型以落叶阔叶林为主,树种以马尾松、枫香树、栓皮栎、麻栎和青冈为主;株数按科分以松科、壳斗科、金缕梅科、漆树科和榆科为主,按属分以松属、金缕梅属、栎属、青冈属、黄连木属为主。古树群综合评分后分3级,其中Ⅰ级3个、Ⅱ级34个、Ⅲ级7个。经计算,古树群物种丰富度指数49、Shannon-Wiener指数1.8345、Simpson指数0.6339、Pielou均匀度指数0.4714、种间相遇率指数0.6339。研究认为辰溪县古树群树种和株数资源丰富,生物多样性指数均不高,但群落生态和景观稳定性很好;分值较大的古树群生态和景观价值很高,可以结合县域森林生态旅游开发、乡村振兴建设合理利用。

基于轻量级SE-PPM的自然状态烟叶正副组分类算法

【目的】针对自然状态烟叶传统正副组分类速度慢、正副组易错分、特征提取困难的问题,提出了一种基于轻量级SE-PPM的自然状态烟叶正副组分类算法(SAPMDSNet)。【方法】基于轻量级ShuffleNetV2网络,先通过降低网络卷积深度和进化激活函数,加快网络模型的训练速度;再引入通道注意力机制SE模块,增强通道间的特征差异,提高网络模型的表征能力,避免正副组烟叶叶部区域化导致的组别错分;最后通过嵌入金字塔池化模块PPM充分融合烟叶显露特征与全局信息,增强对正副组烟叶上下文信息的聚合,并采用自行构建的烟叶数据集进行对比试验。【结果】SAPMDSNet网络模型的分类准确率为91.09%,计算量(FLOPs)为151.70 M,取得了相对较高的分类效果。与原网络ShuffleNetV2模型和轻量级GhostNet模型相比,SAPMDSNet网络模型的FLOPs分别升高2.65%和2.84%,而识别准确率则分别提高2.72和21.13个百分点;MobileNetV2、DenseNet和SqueezeNet模型的识别准确率分别为87.02%,89.53%和87.60%,虽均与SAPMDSNet模型的识别准确率接近,但其FLOPs明显较SAPMDSNet模型大。【结论】构建的SAPMDSNet模型能提高烟叶正副组分类精度且具有较好的整体性能,为烤烟烟叶品质初筛提供了新的思路和方法。