Multiplane displays based on liquid crystals for AR applications

Multiplane displays are capable of displaying 3D scenes with correct focus cues by creating multilayer 2D images in the display volume. Hence, such a 3D display technique could effectively address the accommodation‐vergence conflict (AVC) problem, which is prevalent in augmented reality (AR) displays. In this paper, we review the recent progress on multiplane AR displays based on liquid crystals (LCs) for AR applications. The working principle of multiplane AR displays is illustrated, the electro‐optical properties of the tunable LC devices are investigated and display prototypes are demonstrated. Finally, we discuss the prospects and challenges of multiplane AR displays based on LCs.     

Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

Agent-based management of support systems for distributed brainstorming

In this paper, we describe the design and the management of an agent-based system that supports distributed brainstorming activities. The support system is a highly coordinated IoT application composed of many locally installed interface devices, multimedia communication functions, and cloud functions that process application logic and store meeting data. The system is designed to support a variety of brainstorming sessions, so its functionalities must be modifiable and enable the system to be adapted to different environments and user requirements without any loss of performance. System accessibility should be also ensured from any location for any user. These constraints require a flexible and usable support system.We further discuss the aspects of flexibility and usability that are important in a support system for distributed brainstorming, from which we propose a conceptual schema for flexible and usable support systems. To realize this schema, we present a resource-oriented architecture that can modify the brainstorming support system’s structure and functions. Flexibility is achieved thanks to an agent-based system that manages resources and operates on them according to users’ requests.We also describe the system architecture, which is organized around a set of channels dedicated to different services proposed to the users. We present in detail a video channel that ensures user awareness during synchronized activities. We then conduct several experiments verifying the usability of important channels in the architecture and present the results of these experiments.Finally, we discuss experimental scenarios that show how the system owes its adaptability to management based on an agent organization that supports distributed brainstorming and other activities.     

Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture

Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring a substantial labeling effort, both of which are scarce in precision agriculture. Additional design efforts are required to achieve commercially viable performance levels under varying environmental conditions and crop growth stages. In this paper, we explore the role of knowledge transfer between deep‐learning‐based classifiers for different crop types, with the goal of reducing the retraining time and labeling efforts required for a new crop. We examine the classification performance on three datasets with different crop types and containing a variety of weeds and compare the performance and retraining efforts required when using data labeled at pixel level with partially labeled data obtained through a less time‐consuming procedure of annotating the segmentation output. We show that transfer learning between different crop types is possible and reduces training times for up to 80%. Furthermore, we show that even when the data used for retraining are imperfectly annotated, the classification performance is within 2% of that of networks trained with laboriously annotated pixel‐precision data.     

空冷器用高压水清洗与雾化降温系统集成设计与开发

高压水清洗系统和喷淋降温系统分别是春季保持空冷器翅片表面清洁和夏季保证空冷器在高温下正常运行的2个重要辅助系统。针对喷淋系统的缺点研究了高压射流雾化技术,通过试验论证了高压水清洗与雾化降温系统集成的可行性和合理性。根据设计思路开发的集成系统已在山西某项目获得应用并取得了良好的使用效果,此高压水清洗与雾化降温集成系统中高压水发生装置及介质输送管路共用,产生的高压水射流雾化颗粒可达到60μm,夏季降温效果较传统喷淋降温效果大幅提升,水资源的利用率得到极大提高,系统性价比更高。     

视频侦查中人像智能分析应用及算法优化

人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。     

精细注水配套工艺技术优化研究

本文通过对注水配套工艺的优化研究,有效提高奈曼油田分注率和配注合格率,提高精细注水开发效果。     

浅析火力发电厂汽水系统中内径管与外径管的设计选择

按照管道加工工艺的不同,管道可分为内径控制管和外径控制管。通过热轧工艺生产的外径控制无缝钢管,可满足火力发电厂汽水系统中绝大部分管道的使用要求。对于超(超)临界机组的主蒸汽和高温再热蒸汽管道采用的P91/P92材质的大口径厚壁无缝钢管,由于对材料性能和加工工艺有特殊要求,因此宜采用内径控制管。     

水电站大型竖井施工安全风险控制措施研究

竖井是大型水电工程中广泛采用的重要建筑物,但竖井的传统施工方法存在施工程序复杂、人工劳动强度大、施工效率不高等特点,同时还存在较大的安全风险。通过对杨房沟水电站大型竖井施工过程的研究,总结出精细化控制爆破、小溜渣井施工方式,同时也设计了一套用于运输的综合提升系统。采用上述创新方法不仅减少了繁琐的施工程序,降低了安全施工风险,而且大量采用机械化手段进一步提高了施工效率,确保了该工程竖井施工的安全风险可控。相关措施可为类似工程的竖井施工提供较好的借鉴作用。