R2D2: A scalable deep learning toolkit for medical imaging segmentation

Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures.     

神经网络全局势函数在多相催化中的应用

当今的多相催化研究需要新的技术和方法从原子尺度上表征活性中心结构和反应中间体。本文作者课题组近期开发了理论模拟新技术来探索催化剂活性位点结构，即基于神经网络势函数的大规模原子模拟（LASP）软件中实现的全局神经网络势函数计算方法。本文介绍了该方法可以显著降低催化体系的计算代价，而维持与密度泛函理论同一级别的计算精度，从而解决多相催化中的许多复杂问题。本文对神经网络势函数方法的实现细节和目前已实现的应用场景进行了详细介绍。神经网络势函数可以用来预测材料晶体结构，理解高压氢化条件下TiO₂表面的结构演化和确定三元氧化物ZnCrO晶相中合成气制甲醇活性位点。最后文章分析了神经网络势函数的局限性和今后可能的三个研究方向，即材料性质预测、多元素体系神经网络势函数构造和化学反应拟合。     

无人机控制站通用软件平台设计

针对无人机控制站难以与多型无人机互联互通的问题，从通用控制软件的角度开展研究，分析了设计需求，提出了一种采用平台+插件的软件架构，并分析了软件架构、基于XML技术的帧格式信号和参数信息描述、动态报文解析和组包、软件界面定制等关键技术。在车载控制站和便携控制站的工程验证表明，所提解决方案实现了对多型无人机的控制，具有良好的通用性、扩展性，并支持用户自定义对外通信协议和人机交互功能、界面。     

基于BOPPPS模型的数字电路实验教学设计

针对目前军队院校“数字电路”课程实验环节中存在的学员参与度不高、实验方式固化、灵活性不够等问题,提出将BOPPPS模型和Multisim软件引入到实验过程中。以“时序逻辑电路设计”一节内容为例,按照导入、目标、前测、参与式学习和后测、总结等六个环节进行“四人抢答器实验”的实验教学设计。实践结果表明,该方法能有效解决传统实验环节存在的问题,激发学员学习兴趣,取得了较好的教学效果。     

干湿联合冷却塔冷却节水分析软件开发及应用

为实现对干湿联合冷却塔冷却特性、节水特性的综合分析，编制干湿联合冷却塔校核计算流程，基于Visual Studio开发平台，本文开发了干湿联合冷却塔冷却节水特性分析优化软件。通过对某在运干湿联合冷却塔进行冷却节水特性计算，验证了所开发软件计算结果的准确性；在消雾节水计算结果基础上，对标干湿联合消雾冷却塔验收测试规程，生成其成雾频率曲线、耗水量曲线、塔雾指数、冷却特性曲线，综合分析其消雾特性、节水特性及冷却特性，从而确定了干湿联合冷却塔的最佳运行工况。同时运用所开发软件对比分析了某冷却塔设计干段散热面积对其消雾特性、节水特性及冷却特性的耦合影响，并分析了百叶窗开度对干湿联合冷却塔性能的影响，为干湿联合冷却塔的运行优化和设计优化提供了工具性软件支持。     

Integrated multi-factory production and distribution scheduling applying vehicle routing approach

This paper introduces a new integrated multi-factory production and distribution scheduling problem in supply chain management. This supply chain consists of a number of factories joined together in a network configuration. The factories produce intermediate or finished products and supply them to other factories or to end customers that are distributed in various geographical zones. The problem consists of finding a production schedule together with a vehicle routing solution simultaneously to minimise the sum of tardiness cost and transportation cost. A mixed-integer programming model is developed to tackle the small-sized problems using CPLEX, optimally. Due to the NP-hardness, to deal with medium- and large-sized instances, this paper develops a novel Improved Imperialist Competitive Algorithm (IICA) employing a local search based on simulated annealing algorithm. Performance of the proposed IICA is compared with the optimal solution and also with four variants of population-based metaheuristics: Imperialist Competitive Algorithm, Genetic Algorithm, Particle Swarm Optimisation (PSO), and Improved PSO. Based on the computational results, it is statistically shown that quality of the IICA’s solutions is the same as optimal ones solving small problems. It also outperforms other algorithms in finding near-optimal solutions dealing with medium and large instances in a reasonably short running time.     

Use of Modelica language to simulate electrified railway lines and trains

Simulation of multi-engineering systems typically requires many issues to be solved, which are to be addressed by developing appropriate modeling and simulation programming techniques. In the last years, the authors have participated in several studies in which they analyzed in detail electrified railway systems and simulated them using Modelica language. After a few years of study, despite the huge complexity of these systems, it has appeared evident that Modelica language is very well suited and able to effectively solve the typical issues they present. While specific railway system simulations have already been discussed in specific papers, whose focus was on application and actual results, in this paper, the authors show how to use Modelica language to solve specific modeling issues through suitable programming techniques. Moreover, the issues to be solved and the conceived techniques may be interpreted in a general way and to be applied also in different engineering domains. Finally, this paper briefly recalls the principal results obtained in previous specific papers, in which these techniques were fully implemented.     

Policy translation and configuration using dynamic template

To solve the problem of complex,cumbersome and error-prone configuration of security devices caused by the heterogeneous configuration modes in complex networks,a dynamic template-based scheme for translating and configuring policy was proposed.In detail,considering the code’s features,the code-based template for translating policies was constructed to configure the command line conversion,and the keyword comparison method was used to ensure the accuracy of policy configuration.Experiments show that the scalability and the accuracy of the proposed scheme.     

负径向电场对带电粒子俘获率影响的数值模拟

本文采用数值方法求解Grad-Shafranov方程反演EAST典型长脉冲放电实验(炮号33068)的平衡位形和磁场分布，进而结合粒子在托卡马克电磁场中的运动方程，模拟氘离子在负径向电场存在时的运动轨迹，并统计不同负径向电场下的氘离子俘获率。结果表明：随负径向电场的增大，氘离子轨迹由扩张通行轨迹向外翻香蕉轨迹再向内翻香蕉轨迹，最后向压缩通行轨迹演变；氘离子俘获率随负径向电场的增大而减小，氘离子初始速度越小，其变化越大。     

新型地锚张弦梁式泥石流格栅坝构件受力的简化计算方法

针对常见泥石流防治结构被冲击破坏的问题，基于“柔性消能”理念，结合张弦梁结构和竖向预应力锚杆技术，提出一种既能改善结构受力性能、增加结构整体抗冲击能力、保证结构安全可靠，又能减小结构构件截面尺寸、节约成本、便于现场施工组装和后期运营维护的新型地锚张弦梁式泥石流格栅坝，并阐述其技术原理。根据泥石流荷载分布和新型地锚张弦梁式泥石流格栅坝的受力特征，给出其简化的内力计算方法；并利用SAP2000建立新结构有限元模型，分析了结构的整体受力，验证了构件简化计算方法的合理性；结合Python语言和Qt De? signer软件开发了相应的设计计算软件，对新型地锚张弦梁式泥石流格栅坝的内力进行求解。结果表明：提出的新结构抗冲击性能好，构件受力均匀；以后设计中应关注竖杆的剪切脆性破坏和立柱偏心受力情况，保证结构安全；变形协调仅使底层张弦梁与竖杆内力偏大，实际工程应用时，应着重验算底层构件，防止其破坏；文中提出的简化计算方法能较准确的反映结构的受力特性，具有一定的合理性，研究可为新型地锚张弦梁式泥石流格栅坝的设计计算和推广应用提供理论依据和技术支持。