Rags to Riches:Positive Psychological Attributes and Spiritual Factors Creating Meaning

In mainstream media,the common perception is that“rags to riches”stories only consist of becoming“rich and famous”.This paper aims to reflect on the phenomenological experiences of 19 South Africans who significantly were able to move beyond their own significant low point experiences(imaginary:“rags”)into high point experiences(imaginary:“riches”).The presence of a meaningful experience indicates a turning point divide between low and high.Having the right positive psychological attributes supports the change required to move beyond your circumstances.The study explored the deeper internal psychological attributes within a person along with spiritual factors that could affect change in a person’s life to have an improved and fulfilling life.An existential-phenomenological-humanistic approach,from a positive psychological theoretical viewpoint,was used.The attributes were identified as themes through thematic analysis.The study found that meaning was the most prevalent feature in all respondents’lives to indicate a turn away from,sometimes intense,negative experiences.The presence of a positive mind-set(including positive attitude,self-thought,and self-talk)played a dominant role in affecting change,while the presence of faith and religious belief indicated the spiritual factors associated with change.

Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making

Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.

Maclaurin Symmetric Mean Aggregation Operators and Their Application to Hesitant Q-Rung Orthopair Fuzzy Multiple Attribute Decision Making

The Maclaurin symmetric mean(MSM)operator exhibits a desirable characteristic by effectively capturing the correlations among multiple input parameters,and it serves as an extension of certain existing aggregation operators through adjustments to the parameter k.The hesitant q-rung orthopair set(Hq-ROFSs)can serve as an extension of the existing orthopair fuzzy sets,which provides decision makers more freedom in describing their true opinions.The objective of this paper is to present an MSM operator to aggregate hesitant q-rung orthopair numbers and solve the multiple attribute decision making(MADM)problems in which the attribute values take the form of hesitant q-rung orthopair fuzzy sets(H-qROFSs).Firstly,the definition of H-qROFSs and some operational laws of H-qROFSs are proposed.Then we develop a family of hesitant q-rung orthopair fuzzy maclaurin symmetric mean aggregation operators,such as the hesitant q-rung orthopair fuzzy maclaurin symmetric mean(Hq-ROFMSM)operator,the hesitant q-rung orthopair fuzzy weighted maclaurin symmetric mean(Hq-ROFWMSM)operator,the hesitant q-rung orthopair fuzzy dual maclaurin symmetric mean(Hq-ROFDMSM)operator,the hesitant q-rung orthopair fuzzy weighted dual maclaurin symmetric mean(Hq-ROFWDMSM)operator.And the properties and special cases of these proposed operators are studied.Furthermore,an approach based on the Hq-ROFWMSM operator is proposed for multiple attribute decision making problems under hesitant q-rung orthopair fuzzy environment.Finally,a numerical example and comparative analysis is given to illustrate the application of the proposed approach.

Between-Class Ability Grouping, Cram Schooling, and Student Academic Achievement in Taiwan

Taiwan government has been executing the educational reform programs for more than two decades. However, the so-called between-class ability grouping which is prohibited by Taiwan government is still found in many places; and Taiwan＇s cram schools are even more popular and diversified than before. The authors argue that, in addition to individual＇s socio-economic background, regional characteristics and school attributes also play important roles. Bringing these two factors back in, the causal relationships among ability grouping, cram schooling, and student academic achievement can be analyzed more accurately. Using data from Taiwan Education Panel Survey, the authors＇ empirical results show that, first of all, in more urbanized area, between-class ability grouping is less popular but cram school participation is wider spread these years. Secondly, the effects of family backgrounds on students＇ cram school participation are not as critical as they were before. Thirdly, between-class ability grouping and students＇ performance are positively associated but the internal mechanism still needs further investigation.

An Analysis of Cultivation of College Students'Interpersonal Ability

In modern society,good communicative ability is very important;it plays an important part in communication.But as college students,who enter into the society newly,their interpersonal range is expanded constantly;to a certain extent,there are some communication disorders which many students'worries in life and study are relevant to.So this text will analyze the poor communicative ability from internal and external factors.And then give several suggestions about how to cultivate the college students'communicative ability.

Different Feature Selection of Soil Attributes Influenced Clustering Performance on Soil Datasets

Feature selection is very important to obtain meaningful and interpretive clustering results from a clustering analysis. In the application of soil data clustering, there is a lack of good understanding of the response of clustering performance to different features subsets. In the present paper, we analyzed the performance differences between k-means, fuzzy c-means, and spectral clustering algorithms in the conditions of different feature subsets of soil data sets. The experimental results demonstrated that the performances of spectral clustering algorithm were generally better than those of k-means and fuzzy c-means with different features subsets. The feature subsets containing environmental attributes helped to improve clustering performances better than those having spatial attributes and produced more accurate and meaningful clustering results. Our results demonstrated that combination of spectral clustering algorithm with the feature subsets containing environmental attributes rather than spatial attributes may be a better choice in applications of soil data clustering.

Research on the role of attribution in reading comprehension among Chinese EFL learners

This empirical study investigates Chinese EFL students＇ attributions in reading. The purposes ot this study are to investigate the development of Chinese EFL learners＇ attributions for their perceived success and failure in second language reading and to clarify the relationship between learners＇ reading proficiency levels and their attributions. The results show that （1） Nearly half of the university students feel ＂Just so so＂ in English reading; （2） Environmental variables such as teacher feedback, peers or classroom play an influential role in the learners＇ attribution. This paper concludes with a number of pedagogical suggestions for the teaching and learning of English reading.

基于COMET职业评价模型的工学结合课程职业能力内涵及评价探索

为实现“培养什么人,怎样培养人,为谁培养人”的教育价值回归,积极推进职业教育的“提质培优”建设,分析培养对象作为“学习者、社会人、职业人、岗位者、筑梦人”五类属性的职业能力要求。基于COMET职业评价模型建立基于职业能力发展逻辑顺序的工学结合学习领域课程体系,以及专业能力加关键能力的项目任务型课程与课程职业能力评价规范性操作文件并例证。构建工学结合课程职业能力培养与评价体系,为高职课程教学质量提升提供了新参考。

舰船编队电子干扰决策研究

舰船编队的电子干扰资源分配问题在现代海战中占有非常重要的地位,针对舰船编队自卫反导作战干扰资源分配问题,通过联合概率关联算法和优劣解距离法完成对目标的数据融合和威胁度排序,提出干扰资源分配指标,结合模糊理论构建了干扰资源分配模型。针对大规模目标干扰资源优化分配问题求解速度慢、难以收敛的问题,引入聚类思想来提高问题的求解速度和求解稳定性。通过改进K-means聚类方法,保证不能将一艘舰船的干扰资源耗尽这一干扰资源分配原则。最终,使用遗传算法求解所建的干扰资源分配模型,对比引入聚类和不使用聚类方法证明了引入聚类对大规模优化分配问题的意义,仿真验证了引入聚类后优化分配方法求解的实时性和稳定性。

急诊科护理实习生死亡应对能力现状及影响因素研究

目的 调查急诊科护理实习生的死亡应对能力现状并分析其影响因素。方法 采用便利抽样法,选取2022年8月-2023年4月在河南省、陕西省、甘肃省各1所三级甲等医院急诊科的217名护理实习生为研究对象,采用生命意义感量表、简化版死亡应对能力量表、中文版死亡态度描绘量表对其进行调查。结果 回收有效问卷93.5%。急诊科护理实习生的死亡应对能力得分为(37.99±8.50)分,处于中等偏下水平。多元线性回归分析结果显示,学校是否设置死亡教育或安宁疗护课程、是否支持生前预嘱、生命意义感、趋近接受是急诊科护理实习生死亡应对能力水平的影响因素(P<0.05),可解释29.8%的总变异。结论 急诊科护理实习生死亡应对能力有待提升。临床教学应弥补学校死亡教育的相对不足,引导其深层次思考死亡事件并培养正向死亡态度,立足中国传统文化探寻生命意义感,从而提升护理实习生的死亡应对能力。

基于压力与适应理论的护理干预在恶性肿瘤化疗患者中的应用

目的探讨基于压力与适应理论的护理干预在恶性肿瘤化疗患者中的应用效果。方法选取医院2022年7月—2023年6月收治的92例恶性肿瘤化疗患者为研究对象,按照组间基本特征具有可比性的原则分为对照组和观察组,每组46例。对照组接受常规护理干预,观察组在对照组基础上接受基于压力与适应理论的护理干预。比较两组患者压力应对能力量表(MSI)、心境状态量表(POMS)、癌症患者生命意义量表(MiLS)评分。结果干预前,两组患者变化、成熟、肯定、接受评分及压力应对能力量表总分比较差异无统计学意义(P>0.05);干预后,观察组变化、成熟、肯定、接受评分及压力应对能力量表总分高于对照组,差异有统计学意义(P<0.05)。干预前,两组患者愤怒-敌意、疲乏-迟钝、抑郁-沮丧、迷惑-混乱、紧张-焦虑及精力-活力评分比较差异无统计学意义(P>0.05);干预后,观察组患者愤怒-敌意、疲乏-迟钝、抑郁-沮丧、迷惑-混乱、紧张-焦虑评分均低于对照组,精力-活力评分高于对照组,差异有统计学意义(P<0.05)。干预前,两组患者癌症患者生命意义量表各维度评分及总分比较差异无统计学意义(P>0.05);干预后,观察组患者癌症患者生命意义量表各维度评分及总分高于对照组,差异有统计学意义(P<0.05)。结论基于压力与适应理论的护理干预能够提高恶性肿瘤化疗患者的压力应对能力,改善心境状态,提升生命意义水平。

基于异形同义现象的机器空间语义理解能力评测研究

不同的方位义词语可以用于表达相同的空间场景。文章考察了汉语空间表达“异形同义”现象的不同类型,并据此制作测试题,作为“异形同义判别”子任务,成为中文空间语义理解能力SpaCE评测基准的一个组成部分。针对大语言模型的评测结果显示,大语言模型在“异形同义判别”任务上与人类水平尚有较大差距,且机器在不同试题上的表现特点也与人类表现有所不同。从空间认知图式的角度讲,大语言模型基于语符分布学习到的人类语言知识,还没有转化为类人的空间认知图式理解能力。

师范生手机依赖对学业挫折感的影响:一个有调节的中介模型

为探寻师范生手机依赖与学业挫折感的关系,考察人生意义的中介作用和自我管理能力的调节作用,采用手机依赖性量表、自我管理能力量表、青年学生学业挫折感问卷和人生意义量表对广东省普通高等院校628名师范生进行调查.结果表明:(1)师范生手机依赖可显著正向预测学业挫折感,人生意义与自我管理能力可显著负向预测学业挫折感;(2)师范生人生意义在手机依赖和学业挫折感之间起部分中介作用;(3)师范生自我管理能力在人生意义与学业挫折感之间、手机依赖与学业挫折感之间起调节作用.

语言界面理论视角下词义知识的深度更新——《词义球结构的理论与实践》评介

《词义球结构的理论与实践》一书阐释了词义的基础性核心地位及其蕴涵的句法特征,完善了认知组合性词义观以及词义球结构理论及模型建构,并且进行了词义球结构理论的实践探索。作者基于语言界面理论,通过词义影响句法来研究词义,认为词义、句法、认知和信息具有内在的结构一致性,说明了四者之间全新的界面关系。这部著作体现了语言界面理论视角下词义知识的深度更新,不仅提出了一套全新的理论体系和思路方法,还从实践和应用价值上进一步深化了该理论,具有较高的学术价值和应用价值。

引导模糊C均值聚类算法在联合反演综合解释中的应用

不同地球物理方法的反演结果常常存在差异,根据不同方法的联合反演结果得到最终合理解释是了解地下结构的关键。为此,提出了一种引导式模糊C均值(FCM)聚类算法,即在FCM聚类算法的基础上,结合现有地质认识,引入先验约束信息指导聚类中心的确定,对地球物理联合反演结果进行综合定量解释,旨在降低传统人工解释的主观性和局限性。模型测试表明,与传统FCM聚类技术相比,引导FCM聚类技术效果更好,特别是处理复杂地质结构的反演数据时,能够有效地区分不同地质体。实际数据的应用结果证明了引导FCM聚类技术在多属性地球物理联合反演结果综合解释中的应用潜力较大。该技术不仅提升了地球物理数据解释的科学性,而且为地下资源勘探提供了一个更可靠和精确的工具。

K-means算法在学生能力评估中的应用

针对教育领域中学生能力评估的难题,即传统方法难以全面、客观地反映学生综合能力的现状,引入K-means算法作为核心方法,通过数据挖掘手段实现了对学生能力进行多维度、精细化的分类评估.首先,详细探讨了K-means算法在学生能力评估中的具体应用;然后,通过科学的数据处理流程,揭示了学生能力的内在结构和特点.本文方法不仅有助于识别学生的优势与短板,还为教育政策的制定及教学策略的调整提供了有力支持,促进了教育教学的个性化和精准化.

一种基于rough集的属性约简的改进算法

目前粗糙集属性约简基本上是通过差别矩阵先求出属性核,然后在属性核的基础上再求出属性约简。这种计算方法具有较高的复杂度。因此提出并分析了属性的加权平均重要性的属性约简算法,该算法可以确保得到决策表的一个约简,且不需要计算核,减少计算量,提高计算速度。以实例验证了算法的正确性。

模糊C均值地震属性聚类分析

地震多属性聚类分析是进行储层预测的有效工具。本文提出了基于模糊C均值的地震属性聚类方法,该方法可以将多种地震属性进行分析从而生成有效的特征图,它可以寻找各个类的最优聚类中心,并给出样本点属于每一类的隶属度。此算法是一个简单迭代过程,且算法的关键取决于两个参数:其一是聚类数要远小于聚类样本的总个数;其二是加权参数要适中,过大或过小均不利于聚类效果的改善。模型试验和实际资料的应用表明了该方法原理简单且算法鲁棒性好,具有很好的实际应用价值。

基于FCM算法的粗糙集理论在边坡稳定性影响因素敏感性分析中的应用

结合粗糙集理论与模糊C-均值(FCM)算法,提出一种边坡稳定性影响因素敏感性分析新方法。将边坡稳定性影响因素敏感性分析问题转化为粗糙集理论中的属性重要性评价问题,采用FCM算法离散连续属性数据,给出敏感性分析的具体算法。以圆弧型破坏边坡为例,对影响边坡稳定性的单因素与多因素敏感性进行分析,证明了该方法的可行性和有效性。

辱虐管理对下属反馈规避行为的影响:积极归因与工作意义的作用

反馈规避行为是学术界新近提出的一种反馈管理行为,具体指员工工作表现较差时,采用一系列策略避免与领导进行反馈交换的行为。本研究以219名销售人员为被试,基于内部动机理论,探讨了辱虐管理对下属反馈规避行为的作用效果和作用机制。结果表明:(1)辱虐管理对反馈规避行为有正向影响;(2)工作意义在辱虐管理与反馈规避行为之间起到部分中介作用;(3)个体对辱虐管理的积极归因对辱虐管理与工作意义之间的关系有负向调节作用;(4)研究进一步验证了有中介的调节效应,即上述调节效应是通过工作意义的中介作用实现的。研究首次从内部动机视角探索了反馈规避行为的诱发机制,丰富了已有相关研究,为组织实践进行干预管理提供了理论参考。