M型预制袋袋口折合机构运动精度可靠性优化

目的 为提高M型预制袋包装机袋口折合机构轨迹输出点的运动精度,对袋口折合机构进行运动精度可靠性优化。方法 在运动学分析的基础上,用环路增量法建立考虑杆长误差时袋口折合机构的位置误差模型,接着对轨迹输出点进行可靠性分析及蒙特卡洛法验证,通过灵敏度分析确定关键误差影响因素,最后进行运动精度可靠性优化。结果 建立的可靠性模型可以有效地反映杆长误差对机构运动精度的影响,x分量轨迹的可靠度由82.5%提高至92.91%,y分量轨迹可靠度由65.34%提高至89%。结论 经过可靠性优化能够使袋口折合机构运动精度满足设计要求。     

宽翼T形梁桥动力学理论与特性分析

考虑了剪滞翘曲应力自平衡条件、剪切变形和剪力滞后效应等因素的影响,本文提出了一种对宽翼薄壁T形梁动力学特性的分析方法.分析中为了准确反应T形梁翼板的动位移变化,三个广义动位移被引入,且以能量变分原理为基础建立了T形梁动力反应的控制微分方程和自然边界条件,据此对T形梁的动力反应特性进行了分析,揭示了T形梁桥动力反应的规律.算例中,对比了考虑和不考虑剪滞翘曲应力自平衡条件对T形梁动力反应的影响,结果显示考虑剪滞翘曲应力自平衡条件的计算方法与有限元数值解吻合更好.     

考虑消费者预期后悔的零售商策略选择

建立随机需求下的两阶段销售模型,研究消费者高价后悔和缺货后悔对零售商定价与库存决策的影响,分析两种运营策略：价格承诺和快速响应。结果表明,高价(缺货)后悔加重(减轻)消费者策略性等待行为,零售商应降低(提高)定价并减少(增加)库存;价格承诺和快速响应均能缓解消费者策略性等待行为,但两者的价值受消费者预期后悔的影响相反;价格承诺仅在补货成本高于某个阈值且消费者预期后悔敏感度低于某个阈值时优于快速响应。     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.     

Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning

With the growing discovery of exposed vulnerabilities in the Industrial Control Components (ICCs), identification of the exploitable ones is urgent for Industrial Control System (ICS) administrators to proactively forecast potential threats. However, it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods. To address these challenges, we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph (KG) in which relation paths contain abundant potential evidence to support the reasoning. The reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical paths. The proposed method consists of three primary building blocks: KG construction, relation path representation, and query relation reasoning. A security-oriented ontology combines exploit modeling, which provides a guideline for the integration of the scattered knowledge while constructing the KG. We emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate reasoning. In order to acquire a high-quality representation, the entity and relation embeddings take advantage of their local structure and related semantics. Some critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation validity. In particular, similarity calculation is introduced into a critical path selection algorithm, which improves search and reasoning performance. Meanwhile, the proposed algorithm avoids redundant paths between the given pairs of entities. Experimental results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy.     

Peptidyl Virus-Like Nanovesicles as Reconfigurable “Trojan Horse” for Targeted siRNA Delivery and Synergistic Inhibition of Cancer Cells

The self-assembly of peptidyl virus-like nanovesicles (pVLNs) composed of highly ordered peptide bilayer membranes that encapsulate the small interfering RNA (siRNA) is reported. The targeting and enzyme-responsive sequences on the bilayer's surface allow the pVLNs to enter cancer cells with high efficiency and control the release of genetic drugs in response to the subcellular environment. By transforming its structure in response to the highly expressed enzyme matrix metalloproteinase 7 (MMP-7) in cancer cells, it helps the siRNA escape from the lysosomes, resulting in a final silencing efficiency of 92%. Moreover, the pVLNs can serve as reconfigurable “Trojan horse” by transforming into membranes triggered by the MMP-7 and disrupting the cytoplasmic structure, thereby achieving synergistic anticancer effects and 96% cancer cell mortality with little damage to normal cells. The pVLNs benefit from their biocompatibility, targeting, and enzyme responsiveness, making them a promising platform for gene therapy and anticancer therapy.     

Transient response of Bouc–Wen hysteretic system under random excitation via RBFNN method

Hysteresis normally exhibited by mechanical systems and materials is so prevalent that its response prediction under random excitation has been extensively investigated for decades. Nevertheless, the transient solution of the response, which is crucial for assessing the system’s reliability, is still a challenging topic that requires additional development. To this regard, this work proposes a semi-analytical method using the radial basis function neural network (RBFNN) to attain the transient probability density distribution of the randomly excited Bouc–Wen system. Specifically, the trial solution of the corresponding FPK equation is configured as the RBFNN with undetermined time-varying weight coefficients. By discretizing the time derivative with the Euler difference method, a loss function with time recurrence is derived and minimized to yield the time-varying optimal weight coefficients through the optimization method. Additionally, an optimized sampling strategy is adopted to reduce the burden of calculation. Finally, the Bouc–Wen hysteretic systems with softening and hardening nonlinearity are considered to investigate the performance of the adopted technique. The numerical results have shown that the evaluation process of the probability density functions(PDFs) can be captured well with sufficient accuracy and efficiency. The proposed efficient sampling technique can provide considerable efficiency improvement for the medium dimension system. The work of the paper will contribute to the reliability design of hysteretic structures in engineering.     

25Cr_2Mo_1V钢螺栓在长期高温高压下脆化机理的研究

通过对已脆化的２５Ｃｒ２Ｍｏ１Ｖ钢螺栓及经恢复热处理后的螺栓的金相及电子显微分析,阐述了２５Ｃｒ２Ｍｏ１Ｖ钢在长期高温高压下工作发生脆化的原因,讨论了恢复热处理对脆化螺栓恢复性能的作用     

CAD/CAM 中 Undo/Redo 技术的研究

介绍了一种基于实体模型的ＣＡＤ／ＣＡＭ系统的Ｕｎｄｏ／Ｒｅｄｏ操作实现技术．它支持多层次嵌套的ＣＡＤ／ＣＡＭ建模环境．因而当用户在ＣＡＤ／ＣＡＭ系统环境中建模时,可以方便地对模型进行Ｕｎｄｏ／Ｒｅｄｏ编辑操作．     

一种新型加工中心加工球面的研究

介绍一种采用 STEWART机构的新型加工中心 .对这种加工中心加工球面时各“腿”长度变化的规律进行了分析 .结果表明 :各“腿”长度呈正 (余 )弦规律变化 ,且其变化周期与幅度均相同 ;它们的变化曲线依次相差 1 2 0°到达峰顶 ,其顺序与加工球面上截面圆各点的逆时针顺序相互对应 .导出的各“腿”长度变化的公式可用于指导数控编程