A Study of the Bullwhip Effect for Short Life Cycle Products in Supply Chain Management

Shorter product life cycles present new dressed in supply chain literature. This research challenges to managing production and logistics not adequately adaddresses issues pertaining to the management of supply chains in a short life cycle environment. In this paper, we study the short life cycle environment; then we develop the ventory policy of the indirect manufacturer by explicitly using his demand us an output of the retailer＇s optimal inoptimal ordering policy. Finally, we also provide causes of the bullwhip effect in the context of short life cycle products.

Effectiveness of Short Message Service Support on Adherence to Chemotherapy Treatment among Patients Attending Cancer Treatment Facilities in Kenya

Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ2dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ2dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ2dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ2dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .

Optimal ordering policy for short life-cycle products under credit financing with dynamic adoption in supply chain

Traditional inventory models are mostly ignorant of the life cycle dynamics of a technology product;hence,they often fail to identify different dimensions of inventory research.This paper attempts to investigate the relationship between adoption behavior of customers using life cycle dynamics and associated trade credit policies in order to optimize the total inventory cost.The demand model used in this paper treats sales as a function of awareness diffusion and adoption.Awareness is considered as a function of feedback effects from users/customers.Retailer’s optimal strategies for short life cycle product under credit financing were determined analytically.Finally,numerical examples have been used to support the theoretical results.Theoretical results have further been used to gain some managerial insights.

On Hemingway's Iceberg Theory——From The Short Happy Life of Francis Macomber

Ernest Hemingway's world-wide influence and distinctive writing style-the Iceberg Style-caused a stylistic revolution in the field of literature all over the world.Hemingway always tries his best to avoid depicting things by piling gorgeously big words;on the contrary,he adopts direct description and short sentences which are precise,laconic,bright and vivid.For instance,the novel titled The Short and Happy Life of Francis Macomber is universally acknowledged as his masterpiece,in which "Iceberg Theory"is skillfully presented.With a full analysis of the story,the uniqueness of "Iceberg Theory"will be emphasized in this paper.

On the Unequal Relationship in “The Short Happy Life of Francis Macomber” from the Perspective of Discourse Framework

"The Short Happy Life of Francis Macomber",is a representative short story of Hemingway since it clearly embodies hisprinciple of creation.To illustrate the unequal relationship between the hero Macomber and the heroine Margot,this paper employsBurton’s(1980)Discourse Framework theory to analyze the distribution,classification and pattern of these two characters’chal-lenging moves.On the basis of the dialogue analysis,the author attempts to analyze the patterns of their challenging moves,whichcan reflect Macomber is in a more inferior position in marriage than his wife.And the reasons for this are Margot not only holdsmany challenging moves but also seizes the speaking rights in communication.

Talking about Height and Quality of Life: A Content-Analysis of Focus Group Discussions with Short-Statured Children and Their Parents in the US

Background: To understand what life is like for US children with a diagnosis of Growth Hormone Deficiency or Idiopathic Short Stature, the impact of short stature on Health related Quality of Life (HrQoL) was qualitatively examined and needs for care from the young patients and their parents perspective were identified. Methods: Focus group discussions with 26 American-English speaking and nine American-Spanish speaking children and their parents were conducted, transcribed verbatim and subsequently qualitatively analyzed by two independent raters, using an existing coding guideline, based on the multidimensional HrQoL concept and a special software (VERBI-Software MAXQDA 10). Results: A total of 1313 statements for the English-speaking and 447 statements for the Spanish-speaking families were categorized. In the US, the strongest frequency of mention was found for the HrQoL dimension “Social” across respondents, followed by “Treatment” and “Emotion”. Conclusion: Conducting and analyzing data generated from focus groups ensure that young patients’ experiences of disease are represented in the measure of outcomes for use in clinical trials and patient care.

STUDY ON FATIGUE SHORT CRACK GROWTH LAW AND FATIGUE LIFE FOR MEDIUM CARBON STEELS

The fatigue crack initiation from notch root and the short-crack growth laws of two medium carbon alloying structural steels—35CrMo and 42CrMo are investigated under the different stress ratios R =0.1, 0.3) and three-point bending condition. The relationships between the maximum stress range at the notch root Δ σ max and the number of cycles before fatigue crack initiation N i are determined. The threshold stresses of fatigue crack initiation (Δ σ max ) th are got, and the smallcrack growth laws are obtained for these steels. An effective and convenient method is proposed for predicting the fatigue life of the notch specimens.

基于柔轮裂纹扩展的谐波减速器剩余寿命预测方法

针对单一时频域指标未能较好表征谐波减速器全寿命周期退化特性问题,并考虑柔轮裂纹在不同部位的扩展速率差异性对剩余寿命预测精度的影响,提出一种基于长短期记忆网络和几何平均优化的粒子滤波(LSTM-GMOPF)的谐波减速器剩余寿命预测方法。谐波减速器退化特性难以通过单一时频域指标表征,在基于局部均值分解的振动信号处理的基础上,利用LSTM获取多个时频域指标关系,实现信号特征与退化状态之间的映射;考虑裂纹扩展速率的差异性,基于Paris及Foreman模型构建了谐波减速器前中后3个退化模型状态方程;为缓解粒子权值退化问题,引入双适应度指标,提出了基于GMOPF的状态方程参数更新迭代方法。通过谐波减速器加速寿命试验验证了方法的有效性,对比目前流行方法预测准确性最大提高了16.2%,为谐波减速器可靠性设计提供依据。

短视频“泛娱乐化”现象对大学生精神生活的影响与重构

短视频“泛娱乐化”现象的产生具有信息技术、意识形态、哲学、社会心理等多重背景。调查显示,受短视频“泛娱乐化”现象的影响,大学生呈现出理想信念矮化、思想观念虚化、政治素养弱化、审美情趣庸俗化等现象。资本的逻辑本性、学生娱乐性需求扩大、课堂教学娱乐化倾向是该现象在大学生中盛行的生成机理。为重构大学生精神生活,政府、社会、高校应加强对大学生的引导,提升大学生精神生活质量。

基于WOA-LSTM的锂电池寿命预测研究

针对LSTM模型参数较难选取导致锂电池寿命预测效果较差,提出一种长短期记忆神经网络(LSTM)结合鲸鱼优化算法(WOA)的锂电池产品寿命预测方法,该方法通过WOA对参数进行优化以提高模型的准确性。在此基础上,采用NASA锂电池数据集进行对比实验分析,分别运用WOA-LSTM算法、CNN-LSTM算法和LSTM算法对锂电池的剩余使用寿命进行预测,实验结果证明,WOA-LSTM模型相较于CNN-LSTM模型和LSTM模型的精度分别提升了3.2%和4.5%,验证了WOA方法的有效性,为推动锂电池相关研究的进展提供思路和依据。

基于CNN-LSTM的机床滚动轴承性能退化趋势和寿命预测

滚动轴承作为机床主轴的关键部件,其剩余寿命预测直接决定着整机设备的剩余寿命。若不能及时地预知滚动轴承的健康状态或损伤情况,不仅会影响维修策略的制定,还会造成级联故障,易造成机床灾难性的事故。针对大数据下滚动轴承振动信号的自适应故障特征提取和智能诊断问题,构建卷积神经网络和长短期记忆网络(CNN-LSTM)相结合的寿命预测模型,它可以避免人工参与的影响,实现网络的互补优势。对滚动轴承的退化状态以及剩余寿命进行预测,并与卷积神经网络(CNN)、长短时记忆神经网络(LSTM)进行对比实验。结果表明:所提方法CNN-LSTM有着较高的预测准确度。

EEMD与LSTM在轴承剩余寿命预测中的应用

剩余使用寿命(RUL)预测是实现装备健康管理与预测性维护的最主要技术手段之一,为了准确预测轴承的剩余使用寿命,提出了一种基于集合经验模态分解(EEMD)和长短时记忆网络(LSTM)的轴承剩余寿命预测方法。首先,对采集到的振动信号做时域、频域及时频分析,同时记录相应特征;进而,筛选特征,通过EEMD对振动信号予以分解并重构;最后,通过LSTM结合经过处理的信号构建健康特征指标。通过实验证明了该方法能有效的预测出轴承的剩余寿命,且有较高的预测精度。

结合GCN与LSTM的滚动轴承剩余寿命预测方法

针对滚动轴承剩余寿命预测因振动信号的非线性和非平稳性而缺乏刻画健康状态可靠指标的问题,提出了将图卷积网络与长短期记忆网络结合的预测方法.首先,对轴承振动信号进行经验模态分解得到内涵模态分量,并且对内涵模态分量进行归一化处理后计算邻接矩阵和特征矩阵;其次,将邻接矩阵和特征矩阵作为图卷积网络的输入,捕获数据关系,挖掘深层特征;然后,将深层特征和内涵模态分量输入长短期记忆网络从而实现时序关系建模,构建健康指标;最后,使用移动平均滤波消除振荡,对健康指标进行多项式拟合,并且计算达到阈值时刻,确定轴承剩余寿命.同时,以IEEE PHM 2012数据挑战赛数据集和XJTU-SY滚动轴承加速实验数据集为对象,验证所提方法.结果表明,使用图卷积网络与长短期记忆网络结合的模型构建健康指标进行滚动轴承剩余寿命预测时,预测结果能够较好地接近真实值,在实际应用中具有一定优势.

融合兴趣主题矩阵和主题生命树的社交用户长短兴趣挖掘

[目的/意义]针对当前社交用户兴趣挖掘效果不理想,且缺乏对兴趣类型特征的深入研究,提出一种新的长短兴趣挖掘方法。[方法/过程]首先引入兴趣价值参数作为先验知识对Labeled LDA主题模型进行改进,依据改进的主题模型挖掘不同时间窗口的兴趣主题,构建兴趣主题矩阵。然后基于用户兴趣的变化规律构建主题生命树,挖掘用户兴趣的生命特征和潜在关联,将用户兴趣划分为长期兴趣、短期兴趣和过期兴趣。最后依据兴趣主题的强度和波动幅度量化用户不同类型兴趣的权重,实现对用户兴趣的准确表示。[结果/结论]实验采用从新浪微博爬取的真实数据作为训练集和测试集,与已有的兴趣挖掘方法进行比较,结果发现长短兴趣挖掘方法在F1值和MRR值上最高分别提升了7.68%和7.41%。[局限]仅利用微博文本信息对方法进行验证,缺乏对跨平台信息的深入探讨。

多传感器融合和MHA-LSTM的电机轴承剩余寿命预测

轴承作为电机的核心部件,主要起到支撑引导轴、减小设备摩擦、连接不同设备等作用,其剩余寿命预测对系统健康管理起着十分重要的作用。针对单一传感器信号通常难以全面描述系统的潜在退化机制,论文提出一种基于多头注意力机制和长短时记忆神经网络的电机轴承剩余寿命预测模型。首先,基于马氏距离确定轴承性能退化起始点,将滚动轴承全寿命周期分为正常阶段与退化阶段;其次,使用自编码器自动提取振动信号特征,并将其与电机电流、轴承温度融合,构成多源信息特征矩阵;然后基于多头注意力机制和长短时记忆网络模型动态选择相关度较高的特征,提高寿命预测的准确性。最后,采用实验数据进行验证,结果表明所提出的模型具有更高的准确性。

基于自适应噪声完全集合经验模态分解与BiLSTM-Transformer的锂离子电池剩余使用寿命预测

锂离子电池剩余使用寿命(remaining useful life,RUL)是使用者十分关心的问题,其涉及电池的更换时间和安全。针对锂离子电池的电容量非线性变化趋势,提出了一种基于自适应噪声完全集合经验模态分解与双向长短期记忆网络-Transformer的锂离子电池剩余使用寿命预测方法。首先,利用自适应噪声完全集合经验模态分解方法对锂离子电池电容量数据进行分解。其次,使用串联的双向长短期记忆神经网络和Transformer网络对分解后得到的残差序列和本征模态分量序列进行建模预测。最后,将预测的若干本征模态分量序列和残差序列进行求和,并对求和之后的最终预测数据与原始数据进行RUL预测。采用NASA公开的电池数据集对所提方法进行验证,结果表明,所提方法的平均绝对误差、均方根误差、平均绝对百分比误差和绝对误差控制分别控制在0.0173、0.0231、1.2084%和3个循环周期以内,能够有效地提高锂离子电池RUL的预测精度。

鲸鱼优化算法-双向长短期记忆神经网络用于断路器机械剩余寿命的预测研究

低压断路器的安全可靠是电力系统能否稳定运行的关键一环,因此对断路器进行退化趋势预测和剩余寿命评估具有重要意义。基于鲸鱼优化算法(whale optimization algorithm,WOA)和双向长短期记忆神经网络(bidirectional long short-term memory,BiLSTM)提出了一种断路器操动机构剩余寿命的预测方法,首先采用Pearson相关系数法对获得的原始监测数据进行筛选,选择与断路器开断次数相关度较高的数据作为关键退化特征量,基于主成分分析法进行数据融合获得能够综合表征断路器运行状态的健康指数;随后使用滑动时间窗的方法对健康指数时间序列进行重构,再通过WOA-Bi LSTM寻优获得的最佳模型对健康指数进行时间序列预测,从而获得断路器未来多步的退化趋势;最后再根据设定的失效阈值,确定断路器操动机构的剩余寿命。实例验证表明,该文提出的混合预测模型预测精度最高可达96.43%,相比于其他传统预测模型显著提高,对于断路器的实际运维工作具有一定的指导意义。

基于LSTM-UPF混合驱动方法的燃料电池寿命预测

燃料电池的寿命预测是燃料电池健康管理的重要组成部分,可为燃料电池的运行和维护提供指导性意见。为提高寿命预测的工况适应性并保证预测精度,本工作结合长短期记忆神经网络(long short-term memory neural network,LSTM)和无迹粒子滤波(unscented particle filter,UPF)两种算法的优势,提出了一种LSTMUPF混合驱动方法进行稳态和准动态工况下燃料电池的寿命预测。该方法首先优化训练预测模型的实验数据并采用离散小波变换(discrete wavelet transform,DWT)技术将其分解为高频部分和低频部分,使用LSTM算法对这两部分分别进行预测实现对燃料电池长期老化趋势的预测,并使用修正因子对趋势预测结果进行漂移修正,然后利用得到的燃料电池长期老化趋势,根据UPF算法对燃料电池的剩余使用寿命(remaining useful life,RUL)进行估计。采用预测寿命终点、预测寿命误差、置信区间宽度、RUL预测误差等评价指标对不同寿命预测方法进行对比分析,结果表明,LSTM-UPF混合预测方法对燃料电池稳态工况和准动态工况的RUL预测误差分别为4.1%和3.4%,比基于模型的PF和UPF方法具有更精确的RUL预测结果与高质量的预测置信区间,工况适应性良好。本研究有助于提高多工况下的燃料电池寿命预测精度和置信度。

基于S-MCLSTM和DANN的滚动轴承剩余寿命预测方法

针对在不同工作条件和不同故障形式下,滚动轴承剩余寿命预测泛化能力差和精确度不高的问题,提出一种基于孪生多卷积长短时记忆网络(S-MCLSTM)和域对抗网络(DANN)的剩余寿命预测方法。首先针对不同的工作条件对退化过程的影响,提出基于S-MCLSTM的差异化特征提取器以提取一定时间间隔的两个样本之间的差异化特征。同时,进一步使用工作条件判别器与差异化特征提取器进行对抗训练,减少由于工作条件的原因产生的冗余特征。之后针对故障形式对退化过程的影响,设计了故障诊断器用于和差异化特征提取器对抗训练。最后,考虑到滚动轴承一般退化过程中,不同阶段的退化过程与特征之间的映射关系可能存在的差异,提出了阶段判别器,并在不同阶段应用不同的剩余寿命预测器进行预测。最终在西安交通大学XJTU-SY轴承数据集上的实验表明,该方法在多种工作条件和故障形式下都能较准确地预测剩余寿命,有较为广泛的应用前景。