基于混合蚁群算法的异质车队低碳VRP研究

针对货运车辆在配送调度过程中产生大量碳排放的问题，建立模型将多种影响碳排放量的因素协同优化。模型中考虑了不同载重量的异质车队，两个节点之间有多条道路的柔性路径，以及车辆重量随卸货而减少的动态负载等因素，以碳排放量、行驶时间和行驶路程为优化目标，并加入了节点需求时间窗、根据速度变化划分路段、交接和卸货时间的约束。提出了一种混合蚁群算法，利用蚁群算法信息素强度更新方式保持群体记忆性，利用粒子群算法的快速收敛特性增加计算效率。通过随机数值算例的仿真优化与对比分析，验证了算法和模型的有效性。     

沉浸式艺术审美体验的自我发现与再设计

探讨沉浸式艺术这一新概念，研究其审美体验是如何有助于自我发现并运用于艺术创作再设计中的。沉浸式艺术是一种能够启发感知联觉的审美体验方式，可使人们重新思考自己与“世界”(真实和虚拟)之间的关系。“感知”、“关系”和“转换”是三个相互交织并贯穿全文的主要问题，同时也是沉浸式艺术的研究基础。结合海德格尔“在世界上”(être-au-monde) 的观念来看，与其说“存在”，不如说人们沉浸并感知于这个世界中。然而，人们对周围环境的感知通常是无意识的，对于感知的认识也时常是冷漠和忽视的。沉浸式艺术使这些感觉得以被强调，它突出了个人的感知运动能力，同时也引起了人们对身体本身的重视。又如Bergson所提出的“投机性关注是建立在一种感知机制的基础上的，这种感知机制从根本上允许对世界进行一定行动而不是仅仅了解这个世界”。因此，对于一个完善的沉浸式审美体验过程来说，重要的是使观众自然地参与其中。当无意识的行为转换为肉眼可见的视觉效果时，审美体验将会更加深入人心。因此关于沉浸式艺术作品的创作，可以结合西方艺术家Marcel Duchamp的Ready-made的创作理念和中国道家的“无为”思想，研究怎样将被忽视的日常行为自然地转换为可见的，被重视的视觉效果，从而揭发主体与“世界”之间的多种潜在关系。     

How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research

Partial least squares path modeling (PLS-PM) is an estimator that has found widespread application for causal information systems (IS) research. Recently, the method has been subject to many improvements, such as consistent PLS (PLSc) for latent variable models, a bootstrap-based test for overall model fit, and the heterotrait-to-monotrait ratio of correlations for assessing discriminant validity. Scholars who would like to rigorously apply PLS-PM need updated guidelines for its use. This paper explains how to perform and report empirical analyses using PLS-PM including the latest enhancements, and illustrates its application with a fictive example on business value of social media.     

新一代信息基础设施推动能源发展的路径安排和绩效研究

随着信息技术的迅猛发展,其带来的变革浪潮涌动在各个角落。作为社会的运行动脉,能源的产生运转和利用体系享受新一代信息基础设施的优势,发生着巨大变化。文章研究了新一代信息基础设施对于能源革命的推动传导方式的影响,分析了在这一过程中新一代信息基础设施普及对能源行业及能源使用方式的影响。基于过往信息化数据、已有理论及当下流行的5G运用方式,做回溯性探究,前瞻未来能源革命的蓝图。     

钛合金铣削加工表面残余应力有限元仿真

为了分析铣削工艺参数对钛合金已加工表面残余应力的影响,根据金属切削有限元分析的相关理论,以钛合金Ti6Al4V为工件材料,建立了铣削加工的有限元模型。采用正交试验设计法对钛合金Ti6Al4V铣削仿真的工艺参数进行优化,并用极差法分析不同的铣削速度、铣削深度、铣削路径对钛合金Ti6Al4V工已加工表面残余应力的影响。研究表明:在钛合金Ti6Al4V铣削过程中,对工件已加工表面残余应力影响因素由小到大依次为:铣削深度<铣削路径<铣削速度,切削深度对已加工表面残余应力影响较小,铣削速度对已加工表面残余应力影响最大;在研究范围内,随着铣削速度的增大,已加工表面残余应力逐渐增加。     

Cooperative path planning with priority target assignment and collision avoidance guidance for rescue unmanned surface vehicles in a complex ocean environment

In this paper, a novel cooperative path planning scheme of unmanned surface vehicles (USVs) for rescuing targets in a complex ocean environment is proposed. The primary objective of the rescue USVs is to bring all targets back safely on the premise of first rescuing priority targets, while optimizing the path length, the navigation time and the angular energy. The main contributions of this paper are as follows: (1) The proposed K-means-division (KMD) algorithm is able to identify a complex ocean environment with collision-free zone and static-obstacles zone; (2) The proposed path planning method with fast-marching-method-based ellipse guidance range (E-FMM) is able to optimize the angular energy while ensuring safety; (3) The proposed cooperative management system (including priority-target-assignment (PTA) with reward-mechanism genetic-optimization (RM-GO) and collision-avoidance (CA) guidance law with Tangent-based surge-varying wave-disturbances-observer (Tangent-SV-WDO)) can accomplish the mission of the rescue USVs. Comparative studies with the state-of-the-art methods demonstrate that the proposed cooperative path planning scheme is superior in terms of priority-target-assignment (PTA) and collision-avoidance (CA) of the actual rescue work.     

个性化学习路径推荐综述

近年来，伴随着现代信息技术的迅猛发展，以人工智能为代表的新兴技术在教育领域得到了广泛应用，引发了学习理念和方式的深刻变革.在这种大背景下，在线学习超越了时空的限制，为学习者“随时随地”学习提供了更多的可能性，从而得到了蓬勃发展.然而，在线学习中师生时间、空间分离的特征，导致教师无法及时掌握学生的学习状态，一定程度上制约了在线学习中教学质量的提升.面对多元化的学习需求及海量学习资源，如何迅速完成学习目标、降低学习成本、合理分配学习资源等问题成为限制个人和时代发展的重大问题.然而，传统的“一刀切”的教育模式已经不能满足人们获取知识的需求了，需要一个更高效、更科学的个性化教育模式，以帮助学习者以最小的学习成本最大限度地完成学习目标.基于以上背景，如何自动高效识别学习者特征，高效地组织和分配学习资源，为每一位学习者规划个性化路径，成为面向个体的精准化教育资源匹配机制研究中亟待解决的问题.系统地综述并分析了当前个性化学习路径推荐的研究现状，并从多学科领域的角度分析了对于同一问题的不同研究思路，同时也归纳总结了当前研究中最为主流的核心推荐算法.最后，强调当前研究存在的主要不足之处.     

The impact of a 360° virtual tour on the reduction of psychological stress caused by COVID-19

The continuous spread of the COVID-19 pandemic is causing people to feel anxiety and stress. This study constructs a four-layer research model to examine how a 360° virtual tour can reduce people's psychological stress through two types of presence (the sense of presence and telepresence) and affective-motivational states (enjoyment and involvement) in this extraordinary period of the COVID-19 pandemic. In order to test the moderating effect of involvement, partial least squares (PLS) analysis is employed to analyse valid data collected from 235 individuals. The results of this study indicate that telepresence has a higher impact in generating affective-motivational states than the sense of presence. Among the factors, enjoyment shows the highest effect on satisfaction with the 360° virtual tour experience and stress reduction; involvement moderates the effect of telepresence on satisfaction with the 360° virtual tour experience. This study also contributes to virtual reality research by distinguishing the concepts of ‘sense of presence’ and ‘telepresence’ as well as demonstrating the mechanisms whereby virtual reality technology influences people's psychological well-being. Timely recommendations are provided for people in order to reduce psychological stress during and after COVID-19 pandemic.     

Frequency domain analysis of the mirror-modified filtered-x least mean squares algorithm with low ambient noise

The mirror-modified filtered-x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results.     

基于虚拟导航线的农业机器人精确视觉导航方法

针对农田、野外环境中无人工标记情况下的导航问题，提出了一种基于虚拟导航线的农业机器人精确视觉导航方法。该方法不需要铺设导航线或者路标即可引导机器人行走直线。首先，根据需求确定需要跟踪的目标区域，之后控制机器人调整方向直到目标移至视野中央；其次，根据机器人和目标的位置确定参照目标，并依据两个目标的位置确定虚拟导航线；然后，动态更新导航线，并结合虚拟定标线和虚拟导航线确定偏移角度和偏移距离；最后，利用偏移参数构建模糊控制表，并以此实现对机器人旋转角度和行走速度的调整。实验结果表明，该算法能较为精确地实现对导航路线的识别，进而利用模糊控制策略使机器人沿直线向目标行走，且导航精度在10 cm以内。