Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

Remote Steering of Self‐Propelling Microcircuits by Modulated Electric Field

The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics.     

An agile model for the eco-design of electric vehicle Li-ion batteries

Numerous design choices need to be made at several levels when designing high-tech products: technology, processes, architecture, components, materials… and these choices need to be made in relation to the product life cycle with the corresponding experts for each stage of the life cycle. At the same time, to ensure product sustainability, a specific focus on the future potential environmental impacts is highly recommended. In this research, an agile model is proposed to help designers make decisions while monitoring environmental performance indicators of high-tech solutions. The concept of Critical Product Life Cycle Parameters had to be introduced to facilitate the eco-design of the final product. The approach is illustrated by the Electric Vehicle Li-Ion Batteries case study.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

Animations showing Lego manipulative tasks: Three potential moderators of effectiveness

Evidence suggests that transient visual information, such as animations, may be more challenging to learn than static visualizations. However, when a procedural-manipulative task is involved, our evolved embodied cognition seems to reverse this transitory challenge. Hence, for object manipulative tasks, instructional animations may be more suitable than statics. We investigated this argument further by comparing animations with statics using a Lego task shown to university students, by examining three potential moderators of effectiveness: (a) the environment of manipulation (virtual or physical), (b) the quality of visual information (focused or unfocused), and (c) the presence of hands (no hands or with hands). In Experiment 1 we found an advantage of animation over statics, and no differences among the environments. In Experiment 2, we again observed an animation advantage, a small advantage of focused static information compared to unfocused static information, and a positive effect of not showing the hands.     

径向水平井弯曲转向机构影响因素仿真研究

针对径向水平井钻进中钻杆弯曲转向前进运动困难的问题,通过建立弯曲转向机构仿真有限元模型,对其主要影响因素:滑道轨迹曲率、间隙、工作压力、滚轮形状与位置和钻杆壁厚等用ANSYS软件进行仿真研究。研究表明:影响截面变形的主要因素是滑道曲率的改变和滑道摩擦因数,钻井失败时钻杆所受阻力的增大不是因为升高工作压力导致截面变形过大与滑道干涉所致,钻杆经校直段,钻头中轴线与校直中心线存在一定的角度,即钻杆的前进轨迹就会偏离理论值,或与地层干涉,或可能再次发生弯曲变形;另一主要原因是转向器滑道工作恶化。增加钻杆壁厚,降低工作压力和滑道摩擦因数,设计合理弯曲转向机构是解决问题的关键。     

Trace elements in particles of motor vehicle exhaust in Shanghai

A nuclear microprobe with high spatial resolution and high analytical sensitivity was applied to analyze trace elements,especially lead,in vehicle exhaust of Shanghai city.The result shows that the chemical composition and its corresponding x-ray relative intensity are different among different vehicle exhausts.There are many kinds of metal elements in particles of vehicle exhaust.most are harmful to people,such as Ti,Cr,Mn,Pb,etc.We found that the lead concentration was 6820μg/g and the bromine concentration was 5300μg/g in the exhaust from Santana using leaded gasoline(SULG).which is higher than any other kinds of vehicle exhausts.We have also detected the minimum lead in the particles of unleaded gasoline and its content varies from one to another.Its mean concentration was 450μg/g and the highest reached 6210μg/g.The unleaded gasoline‘s Pb existed in the whole particle while the leaded gasoline‘s enriched in the surface of the particle and was more harmful to the human beings.     

近期河北冶金工业结构调整形势与任务

分析了河北冶金近期行业发展特别关注的几个问题：钢铁生产发展过快；产业结构缺陷，资源供应和环境压力。同时，文章从分析国内外市场形势和国家宏观政策形势入手，提出了河北冶金工业对产品结构调整，工艺装备调整和组织结构调整的必要性，任务和需注意的问题。