A Cognitive Psychological Study on the Acquisition of Chinese Word’s Coloring Meaning--Chinese as a Second Language

Lexical meaning mainly includes rational meaning,grammatical meaning,and coloring meaning.Mastering the coloring meaning of vocabulary is of great significance for foreign students to use Chinese vocabulary correctly.This study mainly examines the psychological mechanism of Chinese second language learners mastering the coloring meaning of words,examines the psychological characteristics of students mastering the color meaning of words from the perspectives of second language learning theory and cognitive theory,establishes a cognitive schema for coloring meaning learning,and proposes corresponding learning models and teaching strategies.

The Claimed Revolution to Understand Consciousness:Information Plays the Driving/Essential Role for the Structuration and Behavior of the Living Organisms

A prestigious conference claimed recently a revolution in neuroscience to understand consciousness.In this paper it is shown that this revolution already came,revealing the determinant role of information for human and living structures,both for their structuration and behavior,explaining consciousness at human as the result of the activity of the Informational System of Human and Living Structures.For this,it is emphasized and discussed the informational structure of the eukaryotic cell,the basic/representative composing unit of the multicellular body of human,animals,and plants,showing that the composition and functions of the informational system are basically similar with that of human.To reveal the driving role of informational mechanisms in human and subhuman organisms,it is introduced the concept of matter-related information,showing that information can be hidden/“embodied”or released/“disembodied”in or from the elemental micro/macro components of the body,during the multiple chain/cascade interactions including transduction processes.It is shown that such interactions are initiated from two main categories of informational sources:implicit(genetic)and explicit(external/internal)sources,the first category leading to structuration of the body and the second the reactive behavior.Consciousness in human and subhuman organisms,expressed by two corresponding informational relations,is the result of the release of information by the mind,acting as an informational operator/device,the development degree of mind and consciousness depending on the complexity degree and adaptation.An analogy of this Informational Model of Human and Living Structures(IMHLS)with the ancient model of chakras is highlighted,showing that these models support each other,applied with beneficial effects in Reiki technique and music-based cognitive multi-task therapy for neuro-rehabilitation.

Exploring the meaning of care among lived experiences of patients with blindness:an interpretive phenomenological study

Objective:To explore the meaning of care experienced by people with blindness in hospitals.Methods:Interpretive phenomenology along with the 6-step method of van Manen was used to conduct the study.Using purposeful sampling,15 people with legal blindness were interviewed.Thematic analysis was used to isolate the meaning of care.Results:Five themes emerged:(a)nurses in the eyes of patients with blindness;(b)negligence in the caring moments;(c)being cared for in ambiguity;(d)Uncoordinated care;and(e)Psychological discomfor t.These sub-themes were condensed into an overarching theme titled as“marginalized patients inside the stereotypical healthcare system.”Conclusions:Lived experiences of patients with blindness revealed that hospitals provide stereotypic or inappropriate care for this minority group in society.Health professionals par ticularly nurses should be skilled to provide person-centered and coordinated care for patients with blindness.

The Axiology of Consciousness in Mocombeian Consciousness Field Theory

This work explores the axiology of consciousness in Mocombe’s consciousness field in the material world.The paper critically assesses Mocombe’s consciousness field theory(CFT)within the larger body of contemporary ontological debates regarding the nature,origin,and constitution of consciousness in the universe.The work goes on to highlight the manifestation of Mocombe’s consciousness field in the material resource framework that is the earth,and the nature and origins of ethics and values.

Analysis of Commuting Modal Shift in Consideration of Social Interaction of Consciousness for Environment

It is the matter for achievement of the low carbon transport system that the excessive use of private vehicles can be controlled appropriately.Not only improvement of service level of modes except private vehicle,but also consciousness for environmental problem of individual trip maker is important for eco-commuting promotion.On the other hand,consciousness for environment would be changed by influence of other person.Accordingly,it is aimed in the study that the structure of decision-making process for modal shift to the eco-commuting mode in the local city is described considering environmental consciousness and social interaction.For the purpose,the consciousness for the environment problem and the travel behavior of the commuter at the suburban area in the local city are investigated by the questionnaire survey.The covariance structure about the eco-consciousness is analyzed with the database of the questionnaire survey by structural equation modeling.As the result,it can be confirmed with the structural equation model that the individual environmental consciousness is strongly related with the intention of self-sacrifice and is influenced with the local interaction of the individual connections.On the other hand,the intention of modal shift for the commuting mode is analyzed with the database of the questionnaire survey.It can be found out that the environmental consciousness is not statistically significant for commuting mode choice with the present poor level of service of public transport.However,the intention of self-sacrifice for the prevention of the global warming is statistically confirmed as the factor of modal shift with the operation of eco-commuting bus service with the RP/SP integrated estimation method.As the result,the multi-agent simulation system with social interaction model for eco consciousness is developed to measure the effect of the eco-commuting promotion.For the purpose,the carbon dioxide emission is estimated based on traffic demand and road network condition in the traffic environment model.On the other hand,the relation between agents is defined based on the small world network.The proposed multi-agent simulation is applied to measure the effect of the eco-commuting promotion such as improvement of level of service on the public transport or education of eco-consciousness.The effect of the promotion plan can be observed with the proposed multi-agent system.Finally,it can be concluded that the proposed multi-agent simulation with social interaction for eco-consciousness is useful for planning of eco-commuting promotion.

The Guidance and Meaning directed by the Three Phases of Memory on the Reading of Literature Works Written by the Style of Stream of Consciousness ——taking the Work Hear the Wind Sing by Haruki Murakami as an Example

Recently, the researchers put their attention on the literature works on Virginia Woolf or James Joyce too heavily just because the skill of stream of consciousness is used through the novel completely. Choosing this novel by Japanese writer as an example is an experiment, because the stream of consciousness as a composing method has melted its impression into the modem novel. And in the researcher＇s opinion, regardless the traditional part, the researching focus should be shifted on the works written by nowadays writer. To begin this paper, there are four questions should be solved： First, the definition of stream of consciousness should be known clearly; another question is the structure analysis of structure of Hear the Wind Sing; secondly, compared with the mental space theory and blending theory by Fauconnier, how to judge the function of Three Phases of memory＇s direction on reading should be focused on; thirdly, the reason why readers meet the problem of barrier when they read the stream of consciousness novel, and how the memory helps to solve the problem should be study in this section. Fourth, the extra factors which support the function of memory will enhance the skill of reading the SOC novel and finally foreground the meaning.

Mean Shift跟踪算法创新实验项目设计

视频跟踪算法是计算机视觉实践课程中比较受关注的实验项目。针对突变情况下传统Mean Shift跟踪算法无法实时准确跟踪的问题,设计了基于模板更新和线性预估的Mean Shift跟踪算法创新实验项目。在模板更新策略下,引入背景模板,通过将原目标模板和背景模板与设定的阈值进行比较来对干扰因素进行判定,当干扰因素判定目标受到遮挡时,引入线性预估方程进行目标位置预测,有效解决目标在遮挡情况下跟踪丢失的问题。通过对测试视频的跟踪效果和性能进行对比分析,验证了算法在突变情况下相较于传统算法具有更好的抗干扰能力。以算法创新设计为核心,通过开放性创新实验项目的选题、设计、答辩、反馈的闭环实验过程,有效提高了学生算法创新设计能力。

加入跳跃连接的深度嵌入K-means聚类

现有的深度聚类算法大多采用对称的自编码器来提取高维数据的低维特征,但随着自编码器训练次数的不断增加,数据的低维特征空间在一定程度上发生了扭曲,这样得到的数据低维特征空间无法反映原始数据空间中潜在的聚类结构信息.为了解决上述问题,本文提出了一种新的深度嵌入K-means算法(SDEKC).首先,在低维特征提取阶段,在对称的卷积自编码器中相对应的编码器与解码器之间以一定的权重加入两个跳跃连接,以减弱解码器对编码器的编码要求同时突出卷积自编码器的编码能力,这样可以更好地保留原始数据空间中蕴含的聚类结构信息;其次,在聚类阶段,通过一个标准正交变换矩阵将低维数据空间转换为一个新的揭示聚类结构信息的空间;最后,本文以端到端的方式采用贪婪算法迭代优化数据的低维表示及其聚类,在6个真实数据集上验证了本文提出新算法的有效性.

基于蚁群算法的三支k-means聚类算法

在聚类分析中,三支k-means聚类算法较具有较强的处理边界不确定数据的能力,但仍然存在对初始聚类中心敏感的问题.通过将蚁群算法和三支k-means聚类算法相结合,给出了一种基于蚁群算法的三支k-means聚类算法来解决这一问题.利用蚁群算法中随机概率选择策略和信息素的正负反馈机制,动态调整权重的方法,对三支k-means聚类算法进行优化.在UCI数据集上实验证明,该方法对聚类结果的性能指标有所提高.

基于K-Means聚类与熵权TOPSIS法的岩石可爆性评价研究

露天矿山的爆破块度分布,直接影响到后续的采装、运输和破碎工作。为了控制石墨矿山不同区域爆破块度分布,基于K-means无监督聚类学习法与熵权TOPSIS评价法建立了一种新的岩石可爆性评价模型,选取岩石密度、动力能量耗散率、动态抗压强度、平均应变率、脆性指数作为评价指标,通过熵权计算,发现岩石破碎程度受脆性指数影响最大,受平均应变率影响最小。将此模型应用于实际石墨矿山,可爆性分为10个等级,统计不同分级下的岩石平均破碎粒径,发现可爆性分级等级越高平均粒径越大,有明显的分级特征,验证了模型的有效性。从爆破石墨矿石岩体类型看,岩石可爆性从易到难排序为:片岩、片麻岩、变粒岩、混合岩。结合石墨矿石微观观测结果分析可知:岩性从片岩向混合岩转变,岩石内部石墨晶质呈下降趋势,石墨矿石可爆性等级也随之越来越高。岩石密度、能量耗散率、动态抗压强度之间呈线性正相关,岩石可爆性与平均应变率、脆性指数存在负相关性。研究成果为矿山矿岩可爆性评价提供了一条新思路,对露天矿山爆破块度优化具有一定的理论和实践指导意义。

基于K-means算法的建筑群震害分析模型缩减方法

基于建筑群模型和弹塑性时程分析的精细化城市震害模拟技术能够为防震减灾及应急救援决策提供必要的依据和参考。为了减小城市建筑群震害模拟的计算量和计算时间,本文提出一种基于聚类算法的建筑群模型缩减方法。该方法采用K-means聚类算法,首先基于建筑结构属性向量对建筑群进行聚类,将相似的建筑结构聚为一组;然后从每组选取一个代表建筑组成建筑群缩减模型,通过减少需要分析的建筑结构数量来减少建筑群震害模拟的计算量。本文对传统的K-means算法进行改进,通过设定组内建筑结构的差异上限自动调整聚类分组数量;提出将具体地震动作用下结构地震损伤指数作为结构属性向量进行聚类,并通过算例对比分别采用两种缩减模型,即基于损伤指数聚类的缩减模型与基于结构力学模型参数聚类的缩减模型,计算结构损伤状态准确程度。对比结果表明:在聚类分组数量相同的情况下,基于损伤指数的分组明显优于基于模型参数的分组,采用模型缩减方法能够在保证足够计算精度前提下显著减少建筑群震害模拟计算量和计算时间。

光伏波动平抑下改进K-means的电池储能动态分组控制策略

针对电池储能系统(battery energy storage system,BESS)进行光伏波动平抑时寿命损耗高及荷电状态(state of charge,SOC)一致性差的问题,提出了光伏波动平抑下改进K-means的BESS动态分组控制策略。首先,采用最小最大调度方法获取光伏并网指令。其次,设计了改进侏儒猫鼬优化算法(improved dwarf mongoose optimizer,IDMO),并利用它对传统K-means聚类算法进行改进,加快了聚类速度。接着,制定了电池单元动态分组原则,并根据电池单元SOC利用改进K-means将其分为3个电池组。然后,设计了基于充放电函数的电池单元SOC一致性功率分配方法,并据此提出BESS双层功率分配策略,上层确定电池组充放电顺序及指令,下层计算电池单元充放电指令。对所提策略进行仿真验证,结果表明,所设计的IDMO具有更高的寻优精度及更快的寻优速度。所提BESS平抑光伏波动策略在有效平抑波动的同时,降低了BESS运行寿命损耗并提高了电池单元SOC的均衡性。

基于主题词向量中心点的K-means文本聚类算法

K-means由于其时间复杂度低运行速度快一直是最为流行的聚类算法之一,但是该算法在进行聚类时需要预先给出聚类个数和初始类中心点,其选取得合适与否会直接影响最终聚类效果。该文对初始类中心和迭代类中心的选取进行大量研究,根据决策图进行初始类中心的选择,利用每个类簇的主题词向量替代均值作为迭代类中心。实验表明,该文的初始点选取方法能够准确地选取初始点,且利用主题词向量作为迭代类中心能够很好地避免噪声点和噪声特征的影响,很大程度上地提高了K-means算法的性能。

基于特征分箱和K-Means算法的用户行为分析方法

针对网购用户所产生的购物行为进行分析,首先通过数据处理构建客户关系管理模型(RFM模型),在此模型的基础上采用特征分箱法和K-Means聚类两种方法对用户进行细分,并对2种模型结果进行比较分析,讨论二者的差异性和具体的应用范围和意义.其中,基于特征分箱法的RFM模型将变量转化到相似的尺度上并将变量离散化,使得用户分类标签更加清晰,也可依据各类标签分类出不同类型的用户.K-Means算法通过轮廓系数评估聚类算法质量以至于选取最优K值.本文实验分析结果可为运营商提供更加可靠直观的数据,使得运营商可以根据不同用户的不同行为进行市场细分,进而进行精准营销和服务设置.

基于k-means聚类算法的兴义维蚋幼虫龄数的估算

目的探讨基于k-means聚类算法估算兴义维蚋幼虫的龄数,以明确虫龄与日龄及鳃斑发育阶段的关系。方法采集贵州青岩河流中兴义维蚋虫卵,于实验室的蚋类饲养系统中培育至幼虫,每日收集幼虫至大量化蛹,持续20 d;收集到幼虫1112头,于体视显微镜下测量头壳长(HCW)、后颊长(PGL)、上颚基横骨长(MPL)及体长(BL),观察不同虫龄幼虫的破卵器、鳃斑及性腺的形态学特征,并判断其龄期、分析虫龄与日龄和鳃斑发育关系;选取具有明显腮斑发育的兴义维蚋幼虫10头、制作石蜡切片,采用HE染色鉴定精巢和卵巢、辅助确认性别鉴定结果;采用k-means聚类方法划分形态计量学数据、利用Brooks-Dyar定律检测k-means聚类结果,R语言下行聚类与Brooks-Dyar定律检验、t检验等,根据拟合度分析判断兴义维蚋幼虫龄数。结果1112头兴义维蚋幼虫中有破卵器89头,出现鳃斑发育334头,6~7龄幼虫320头,有预蛹特征34头;Brooks-Dyar定律与破卵器、鳃斑形态特征显示7龄幼虫假设符合昆虫幼虫生长规律;组织学观察见幼虫精巢为椭圆形、体积大、外有几丁质层包裹,卵巢为长条形、体积小、后端有色素细胞包裹;鉴定6、7龄幼虫性别结果,仅7龄幼虫雌雄性PGL有差异(P<0.05);幼虫虫龄与日龄、鳃斑发育关系结果显示,约2~3 d对应1个幼虫生长龄期,第17天首见幼虫蛹化,6龄幼虫出现明显的鳃斑。结论兴义维蚋幼虫具7龄,实验室下幼虫发育约需3周,最短17 d;腮斑发育起始于6龄,7龄出现明显形态学特征。

管制扇区运行稳度K-means聚类与分析

为更好地分析管制扇区运行存在的稳定亚安全状态和不稳定亚安全状态,使用K-means算法划分超容比(ECR)、滞留度和飞行姿态混合比3个管制扇区运行稳度评价指标聚类,确定管制扇区运行稳度最佳等级划分;聚类分析单一指标,获得各等级对应的指标阈值,结合熵权法计算的指标权重,遵循隶属度最大原则,获取各时间段的管制扇区运行稳度等级,构建管制扇区运行稳度综合评价模型;选取厦门01号扇区的实际飞行数据,从稳度和趋度2个角度更加全面地分析管制扇区运行态势。结果表明:管制扇区运行稳度等级划分为3类时效果最好;稳度受空中交通流和管制状况的影响会随时间而变化,尤其7:30—9:15和20:00—21:00这2个时间段管制扇区运行稳度的变化最为明显,需引起管制员高度重视,提高空域运行安全。

基于改进K-means与机器视觉的档案数据分析技术

为了提升医疗信息系统对健康档案数据的分析效率,文中采用图像采集、降噪、配准与差分等技术提取医疗图像信息,进而有效提升信息系统的数据采集效率。同时还对传统的K-means算法加以改进,并提出了一种基于类间、类内距离的聚类初始化评价指标体系(BWP),将其应用于采集到的档案数据中,以实现快速的聚类分析。将所提算法在CUDA计算平台上进行了实现,测试结果表明,该方法的聚类精度和运行效率较现有算法均有显著提升。此外,改进后K-means算法的正确聚类样本数量占比提升了4.88%,高于现有的主流指标体系,且当聚类数k的取值为16或32时,运行时间大幅降低。

基于改进K-means的局部离群点检测方法

离群点检测任务是指检测与正常数据在特征属性上存在显著差异的异常数据。大多数基于聚类的离群点检测方法主要从全局角度对数据集中的离群点进行检测,而对局部离群点的检测性能较弱。基于此,本文通过引入快速搜索和发现密度峰值方法改进K-means聚类算法,提出了一种名为KLOD(local outlier detection based on improved K-means and least-squares methods)的局部离群点检测方法,以实现对局部离群点的精确检测。首先,利用快速搜索和发现密度峰值方法计算数据点的局部密度和相对距离,并将二者相乘得到γ值。其次,将γ值降序排序,利用肘部法则选择γ值最大的k个数据点作为K-means聚类算法的初始聚类中心。然后,通过K-means聚类算法将数据集聚类成k个簇,计算数据点在每个维度上的目标函数值并进行升序排列。接着,确定数据点的每个维度的离散程度并选择适当的拟合函数和拟合点,通过最小二乘法对升序排列的每个簇的每1维目标函数值进行函数拟合并求导,以获取变化率。最后,结合信息熵,将每个数据点的每个维度目标函数值乘以相应的变化率进行加权,得到最终的异常得分,并将异常值得分较高的top-n个数据点视为离群点。通过人工数据集和UCI数据集,对KLOD、LOF和KNN方法在准确度上进行仿真实验对比。结果表明KLOD方法相较于KNN和LOF方法具有更高的准确度。本文提出的KLOD方法能够有效改善K-means聚类算法的聚类效果,并且在局部离群点检测方面具有较好的精度和性能。

基于K-means聚类和特征空间增强的噪声标签深度学习算法

深度学习中神经网络的性能依赖于高质量的样本,然而噪声标签会降低网络的分类准确率。为降低噪声标签对网络性能的影响,噪声标签学习算法被提出。该算法首先将训练样本集划分成干净样本集和噪声样本集,然后使用半监督学习算法对噪声样本集赋予伪标签。然而,错误的伪标签以及训练样本数量不足的问题仍然限制着噪声标签学习算法性能的提升。为解决上述问题,提出基于K-means聚类和特征空间增强的噪声标签深度学习算法。首先,该算法利用K-means聚类算法对干净样本集进行标签聚类,并根据噪声样本集与聚类中心的距离大小筛选出难以分类的噪声样本,以提高训练样本的质量;其次,使用mixup算法扩充干净样本集和噪声样本集,以增加训练样本的数量;最后,采用特征空间增强算法抑制mixup算法新生成的噪声样本,从而提高网络的分类准确率。并在CIFAR10、CIFAR100、MNIST和ANIMAL-10共4个数据集上试验验证了该算法的有效性。

基于改进K-means算法的物流配送中心选址研究

针对传统K-means算法需要主观设定K值及无法处理类别型数据问题,文章运用肘部法及轮廓系数法确定合理K值,对类别型数据采取独热编码(One-Hot Encoding)转换为可以处理的连续型数据,并将其运用到在物流配送中心选址中;并综合考虑多种类别的影响因素,构建了相应的影响因素指标体系,提出的模型能够识别输入数据的数值型及类别型数据,实现样本的有效聚类。相关的案例分析结果表明,相比传统K-means聚类,文章的改进K-means算法选址结果可使物流总成本降低8.76%,运营成本降低14.85%,固定成本降低8.09%,效果显著。