Enhanced Hybrid Equilibrium Strategy in Fog-Cloud Computing Networks with Optimal Task Scheduling

More devices in the Intelligent Internet of Things(AIoT)result in an increased number of tasks that require low latency and real-time responsiveness,leading to an increased demand for computational resources.Cloud computing’s low-latency performance issues in AIoT scenarios have led researchers to explore fog computing as a complementary extension.However,the effective allocation of resources for task execution within fog environments,characterized by limitations and heterogeneity in computational resources,remains a formidable challenge.To tackle this challenge,in this study,we integrate fog computing and cloud computing.We begin by establishing a fog-cloud environment framework,followed by the formulation of a mathematical model for task scheduling.Lastly,we introduce an enhanced hybrid Equilibrium Optimizer(EHEO)tailored for AIoT task scheduling.The overarching objective is to decrease both the makespan and energy consumption of the fog-cloud system while accounting for task deadlines.The proposed EHEO method undergoes a thorough evaluation against multiple benchmark algorithms,encompassing metrics likemakespan,total energy consumption,success rate,and average waiting time.Comprehensive experimental results unequivocally demonstrate the superior performance of EHEO across all assessed metrics.Notably,in the most favorable conditions,EHEO significantly diminishes both the makespan and energy consumption by approximately 50%and 35.5%,respectively,compared to the secondbest performing approach,which affirms its efficacy in advancing the efficiency of AIoT task scheduling within fog-cloud networks.

The relationship between differentiation of self and satisfaction with life amongst Israeli women: A cross cultural perspective

The current study examined the relationships between satisfaction with life and differentiation of self among Jewish and Arab women living inIsrael. The sample included 268 participants: 114 Jewish women and 154 Arab women. For both ethnic groups, satisfaction with life was negatively correlated with emotional cutoff. Among Arab women, satisfaction with life was found positively associated with I-position, marriage duration and education. The examination of cross-cultural differences yielded several findings: Arab women reported higher levels of emotional reactivity and I-position than Jewish women. No cultural differences were found in the levels of fusion with others, emotional cutoff and satisfaction with life. The current findings show that working women, who are highly differentiated, are satisfied with life to a greater extent than non-working women who are poorly differentiated. In general, the research findings provide support to the universality of the Family Systems Theory, and to the argument that differentiation of self is an important factor which may influence emotional wellbeing in all cultures.

An Examination of the Validity of the Differentiation-of-Self Hypothesis and Its Mechanism Related to Negative Life Event Aversion among Japanese University Students

This study examined the validity of the differentiation-of-self hypothesis for Japanese university students, and its mechanism in relation to negative life event aversion. Although the differentiation-of-self hypothesis is accepted as one of the basic hypotheses in the clinical field of family therapy in Japan, empirical studies on the subject are scarce. Further, there are few studies, internationally, on its mechanism. A questionnaire survey was conducted with university students (n = 250) to measure their differentiation of self, maladaptive states, and negative life event aversion. Compared to the better-differentiated group, the less-differentiated group had higher scores both for maladaptive states—somatic symptoms (t(223) = -2.70, p = 0.008), social dysfunction (t(211.00) = -3.30, p = 0.001), and severe depression (t(208.78) = -4.08, p < 0.001)—and negative life event aversion—interpersonal domain (t(223) = -3.96, p < 0.001) and achievement domain (t(223) = -3.83, p < 0.001). The results supported the validity of the differentiation-of-self hypothesis for Japanese university students, and that cognitive tendencies toward negative life events may be part of the mechanism for less-differentiated individuals’ subsequent vulnerability. This suggests the effectiveness of cognitive interventions.

Self-adapting control parameters modifieddifferential evolution for trajectoryplanning of manipulators

Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.

A hybrid differential evolution algorithm for meta-task scheduling in grids

Task scheduling is one of the core steps to effectively exploit the capabilities of heterogeneous re-sources in the grid.This paper presents a new hybrid differential evolution(HDE)algorithm for findingan optimal or near-optimal schedule within reasonable time.The encoding scheme and the adaptation ofclassical differential evolution algorithm for dealing with discrete variables are discussed.A simple but ef-fective local search is incorporated into differential evolution to stress exploitation.The performance of theproposed HDE algorithm is showed by being compared with a genetic algorithm(GA)on a known staticbenchmark for the problem.Experimental results indicate that the proposed algorithm has better perfor-mance than GA in terms of both solution quality and computational time,and thus it can be used to de-sign efficient dynamic schedulers in batch mode for real grid systems.

A New Self-Adapting Admission Control Algorithm for Differential Service in Web Clusters

A new admission control algorithm considering the network self-similar access characteristics is proposed. Taking advantage of the mathematical model of the network traffic admission control which can effectively overcome the self-similar characteristics of the network requests, through the scheduling of the differential service qucue based on priority while at the same time taking into account various factors including access characteristics of requests, load information, etc, smoothness of the admission control is ensured by the algorithm proposed in this paper. We design a non-linear self-adapting control algorithm by introducing an exponential admission function, thus overcomes the negative aspects introduced by static threshold parameters. Simulation results show that the scheme proposed in this paper can effectively improve the resource utilization of the clusters, while at the same time protecting the service with high priority. Our simulation results also show that this algorithm can improve system stability and reliability too. Key words Web cluster - admission control - differential service - self-similar - self-adapting CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (10375024) and the Hunan Natural Science Foundation of China(03JJY4054)Biography: LIU An-feng(1971-), male, Ph. D candidate, majoring in network computing, Web QoS.

旅游自动问答系统中多任务问句分类研究

目前旅游产业信息化建设需要构建旅游自动问答系统,其中问句分类是问答系统的重要组成部分,传统问句类别体系角度单一,且传统分类模型对不平衡的问句数据集表现欠佳。针对这一问题,该文从问题主题和问句答案类型两个角度构建了旅游领域的问句类别体系架构,并提出多任务问句分类模型MT-Bert,在BERT上进行多任务训练,并加入自注意力机制,使用Softmax分类器,并设计了多任务融合损失函数。在山西旅游数据集的结果表明,MT-Bert在两种类别体系的微平均F1值分别为97.6%、91.7%,且避免了非平衡数据的预测失败问题,可以有效处理非平衡数据。

对数字平台自我优待行为批判的批判性分析

近年来,数字平台自我优待现象受到广泛关注。人们担心平台企业利用它传导市场势力,破坏平台内部竞争、垄断周边市场,因此对它作出概括性否定评价,主张对平台企业强化规制,设置平等对待义务。然而,自我优待行为具有广泛的促进竞争效果,不但是纵向一体化的必然内含之义,而且是某些有益商业模式的必要成分,以及约束甚至颠覆在位企业的重要机制。相反,以平等对待义务之名概括禁止自我优待,不但与反垄断法的立法目的相悖,还会损害动态竞争,过度夸大平台内竞争的重要性而无视平台间竞争的约束力量。自我优待行为种类繁多,竞争效果差异巨大,不应该概括规制,而应该回归反垄断法的基本范式,对具体自我优待行为作理性的个案分析。

虚拟化身性别对数学任务表现的影响:一个有中介的调节模型

本研究探讨了虚拟化身性别对数学任务表现的影响及其影响机制。实验采用2(化身性别:男/女)×2(自我肯定:高/低)的两因素组间设计,因变量为数学工作自我概念和数学任务表现。结果表明:虚拟化身性别和自我肯定均对数学工作自我概念和数学任务表现有显著主效应,且两者交互影响两个因变量。同时,研究还发现了有中介的调节作用模型,自我肯定显著地调节了虚拟化身性别与数学任务表现的关系,且该调节关系通过数学工作自我概念的中介作用来进一步影响数学任务表现。

基于Self-Attention的方面级情感分析方法研究

针对传统模型在细粒度的方面级情感分析上的不足,如RNN会遇到长距离依赖的问题,且模型不能并行计算;CNN的输出通常包含池化层,特征向量经过池化层的运算后会丢失相对位置信息和一些重要特征,且CNN没有考虑到文本的上下文信息。本文提出了一种Light-Transformer-ALSC模型,基于Self-Attention机制,且运用了交互注意力的思想,对方面词和上下文使用不同的注意力模块提取特征,细粒度地对文本进行情感分析,在SemEval2014 Task 4数据集上的实验结果表明本文模型的效果优于大部分仅基于LSTM的模型。除基于BERT的模型外,在Laptop数据集上准确率提高了1.3%~5.3%、在Restaurant数据集上准确率提高了2.5%~5.5%;对比基于BERT的模型,在准确率接近的情况下模型参数量大大减少。

电化学原理及应用课程教学创新与实践

电化学原理及应用作为一门新能源材料与器件专业应用型人才培养的专业主干课程,必须以新工科建设思维去培养适应于行业需求的人才。该文从如何使学生面向行业发展、如何缩小学业水平差距、如何发挥评学的激励作用等问题出发,提出相应的应对策略,实现“有效内容、有效学习、有效评学”的目标,为培养适应社会需求的应用型人才的教学目标提供支撑。

改进粒子群算法的紫外光协作多无人机任务分配方法

为了解决无人机协同作战问题,需要将多任务分配给多个无人机。利用无线紫外光实现强电磁干扰环境下无人机机间隐秘信息传输,提出一种改进粒子群算法的多无人机任务分配方法,综合考虑无人机执行任务所付出的威胁代价、航程代价以及完成任务的时间差,结合压缩因子和差分进化思想解决粒子群优化算法容易陷入局部最优的问题。仿真结果表明,改进粒子群算法相较于传统粒子群算法在不同无人机和任务数量比下的任务分配平均成功率提高了约16%,算法在收敛时的迭代次数平均减少了约4.5倍,最优适应度值平均减小了近一倍,在多无人机任务分配的实际应用中有一定的意义。

结合时间注意力机制和单模态标签自动生成策略的自监督多模态情感识别

大多数多模态情感识别方法旨在寻求一种有效的融合机制,构建异构模态的特征,从而学习到具有语义一致性的特征表示。然而,这些方法通常忽略了模态间情感语义的差异性信息。为解决这一问题,提出了一种多任务学习框架,联合训练1个多模态任务和3个单模态任务,分别学习多模态特征间的情感语义一致性信息和各个模态所含情感语义的差异性信息。首先,为了学习情感语义一致性信息,提出了一种基于多层循环神经网络的时间注意力机制(TAM),通过赋予时间序列特征向量不同的权重来描述情感特征的贡献度。然后,针对多模态融合,在语义空间进行了逐语义维度的细粒度特征融合。其次,为了有效学习各个模态所含情感语义的差异性信息,提出了一种基于模态间特征向量相似度的自监督单模态标签自动生成策略(ULAG)。通过在CMU-MOSI,CMU-MOSEI, CH-SIMS 3个数据集上的大量实验结果证实,提出的TAM-ULAG模型具有很强的竞争力:在分类指标(Acc_(2),F_(1))和回归指标(MAE, Corr)上与基准模型的指标相比均有所提升;对于二分类识别准确率,在CMUMOSI和CMU-MOSEI数据集上分别为87.2%和85.8%,而在CH-SIMS数据集上达到81.47%。这些研究结果表明,同时学习多模态间的情感语义一致性信息和各模态情感语义的差异性信息,有助于提高自监督多模态情感识别方法的性能。

领导差异化授权如何促进员工创新绩效:成就目标导向和工作重塑的作用

文章基于自我调节理论,运用跨层次分析方法探究领导差异化授权对员工创新绩效的影响。通过对66个团队331名员工的数据进行分析,得出如下结论:领导差异化授权正向影响员工创新绩效;领导差异化授权正向影响员工工作重塑,员工工作重塑在领导差异化授权与员工创新绩效之间起中介作用;成就目标导向显著正向调节领导差异化授权与员工工作重塑的关系,并且正向调节员工工作重塑在领导差异化授权与员工创新绩效之间的中介作用。

在线平台算法控制如何影响零工任务绩效

本文基于工作要求-资源理论,构建了在线平台算法控制影响零工工作者任务绩效的双链式中介模型,并对两家头部外卖平台的286名全职零工工作者的多时点数据进行分析。研究结果表明:信息质量感知、自我效能感、时间压力和情绪耗竭这四个影响因素在算法控制与任务绩效间的独立中介效应显著。具体而言,算法控制通过信息质量感知与自我效能感这一链式中介对任务绩效产生促进效应,并通过时间压力与情绪耗竭另一链式中介对任务绩效产生抑制作用。本研究不仅丰富了算法控制影响效应的理论研究成果,也为平台优化算法控制和零工工作者管理提供了实践启示。

一种基于Agent的任务自生成方法

任务自生成是基于预先设定的业务工作流完成任务执行流程制定的一个过程,任务执行流程制定主要包括任务执行步骤选取与任务执行步骤相应的解决方案选取。提出一种基于Agent的任务自生成方法来解决基于传统的业务工作流的流程制定机制,在面对有差异性需求的不同任务时,因其不能做出任务执行流程制定的自适应性改变而在处理任务时出现处理速度慢、结果不准确等问题。利用Agent的环境感知能力实现对任务需求信息和任务自生成系统环境的感知,利用Agent的自主行为决策能力结合感知的信息实现对任务执行流程制定工作的自主管理,在真实应用场景测试中,通过一系列比较实验验证了这种方法在处理速度和准确度方面具有明显优势。

中医辨证施护在糖尿病高危足病人中的干预效果

目的:观察中医辨证施护应用于糖尿病高危足的效果。方法:选取2021年10月—2022年12月医院收治的100例糖尿病高危足病人作为研究对象,按随机数字表法将其分为对照组、观察组,每组50例,对照组实施常规护理干预,观察组在常规护理的基础上给予中医辨证施护干预,比较两组病人中医证候积分、糖尿病足发生率、心理状态[心理弹性量表(CD-RISC)评分]、自我效能[自我效能量表(CDSES)评分]。结果:干预后观察组病人肢体麻木、蚁行感、肢末刺痛、失眠心烦中医证候积分均低于对照组(P<0.05);观察组病人糖尿病足发生率为6.00%,低于对照组的20.00%(P<0.05);干预后观察组病人CD-RISC量表各维度评分、总分及CDSES量表各维度评分均高于对照组(P<0.05)。结论:中医辨证施护可有效改善糖尿病高危足病人的中医证候积分,调节病人情绪状态,提高病人的自我效能,从而减少糖尿病足发生的风险。

候床管理系统在提高分化型甲状腺癌患者住院收治率中的作用

目的探讨核医学科分化型甲状腺癌患者候床管理系统构建方法及在提高住院收治率中的作用。方法选择2021年3月—2023年1月广西医科大学第一附属医院核医学科收治的960例分化型甲状腺癌患者为对象,随机数字表法分为2组,各480例。对照组采用常规方法管理,观察组构建候床管理系统。2组均完成3个月干预,比较2组自我管理水平、住院时间、不良反应发生率、住院收治率及满意度。结果观察组干预3个月后自我概念、自护技能、自护意识及健康知识评分高于对照组(P<0.05);观察组干预3个月后住院时间≥7 d病例数和治疗过程中乏力、辐射损伤、放射性炎症、消瘦及恶心呕吐总发生率低于对照组(P<0.05);观察组干预3个月期间住院收治率为64.58%,高于对照组的43.75%;干预方法、服务态度、干预效果及干预形式方面满意度高于对照组(P<0.05)。结论构建核医学科分化型甲状腺癌患者候床管理系统,有助于提高患者自我管理水平,缩短住院时间,降低不良反应发生率,提高住院收治率及满意度。

压差式流量计误差自动化修正算法研究

针对在多干扰源扰动下压差式流量计测量结果面临输出不稳、误差较大的问题,提出多源扰动下的压差式流量计误差自动化修正算法。考虑全补偿气体可膨胀性系数、压缩系数、密度系数和流出系数等因素,研究压差式流量计误差自动化修正算法。利用均值滤波滤除信号中的高斯噪声,结合一阶滞后滤波优化卡尔曼滤波算法,修正多源扰动误差。引入自组织算法和Volterra神经网络进一步改进卡尔曼滤波算法,并优化卡尔曼滤波算法的先验模型参数,以实现多源扰动误差的自动化修正。试验结果表明,经该算法控制后:当参考流量为900 m^(3)/h时,示值误差绝对值为0.203%;当参考流量为700 m^(3)/h时,流量计重复性为0.06%。该研究可以有效识别并修正由于多源扰动造成的流量异常值,且流量测量精度较高。

面向重访周期需求的敏捷成像卫星任务规划方法

为满足敏捷成像星座观测目标的重访周期需求,提出一种混合编码差分进化算法.分析敏捷成像卫星的工作特点,构造评价重访周期需求满足情况的目标函数,建立成像任务约束满足模型.针对观测任务选择与否、执行顺序和成像时间的优化需求,提出一种二进制-实数混合编码差分进化算法,实现了成像任务在时间轴上的分布优化.通过工程实例进行仿真校验,仿真结果表明相比于基于二进制编码的遗传算法,本文算法在优化时间和优化效果方面都有较大优势.