Film and television industry cloud exhibition design based on 3D imaging and virtual reality

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the RANSAC algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.     

In-situ point cloud fusion for layer-wise monitoring of additive manufacturing

Additive manufacturing (AM) has received an increasing attention in the manufacturing sector, owing to its high-level design freedom and enhanced capability to produce parts with complex geometries. With advances in AM technologies, the role of AM has been shifting from rapid prototyping to viable production-worthy manufacturing of functional parts. However, AM processes are highly inconsistent, and the lack of quality assurance significantly hampers the broader adoption of AM. Most existing techniques for AM online monitoring focus on the detection of conspicuous defects, such as under-fills and cracks. They are limited in their ability to detect layer surface variations induced by miniature process shifts. The objective of this study is to develop a new layer-wise monitoring framework for AM quality assurance based on in-situ point cloud fusion. Specifically, online 3D structured-light scanning is used to capture the surface morphology from each printed layer. The collected point cloud is partitioned, and the morphological patterns in local regions are delineated with a new affinity measure to evaluate the conformity to the reference. A deep cascade model is further introduced to leverage the local affinities for the identification of abnormal patterns on the printed layers. Finally, a statistical control chart is constructed for process monitoring and the identification of miniature shifts. Simulation and real-world case studies using the fused filament fabrication (FFF) process are conducted, and experimental results have demonstrated the effectiveness of the developed framework. It has a great potential to be implemented in diverse AM processes with a wide variety of materials for mission-critical applications.     

A robot hand-eye calibration method of line laser sensor based on 3D reconstruction

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in robotic manufacturing systems, this paper proposes a 3D reconstruction-based robot line laser hand-eye calibration method. In this method, combined with the point cloud registration technique, the newly defined error-index more intuitively reflects the calibration result than traditional methods. To raise the performance of the calibration algorithm, a Particle Swarm Optimization - Gaussian Process (PSO-GP) method is adopted to improve the efficiency of the calibration. The experiments show that the Root Mean Square Error (RMSE) of the reconstructed point cloud can reach 0.1256 mm when using the proposed method, and the reprojection error is superior to those using traditional hand-eye calibration methods.     

网络安全管理

就网络安全管理的几个方面进行了简述,提出了按照不同维度对网络安全管理进行深入管理和保护的思路和方法。     

以ARM为核心的嵌入式体感遥控器设计

介绍一种以ARM为核心的嵌入式服务机器人体感遥控器的设计。硬件上,本遥控器采用具有ARM Cortex—M3内核的STM32F103C8T6作为核心处理器,选用ST公司的iNEMO惯性导航模块进行手部姿态的识别,同时还具有LCD显示模块、无线收发模块和电源模块;软件上,采用嵌入式操作系统μC／OS—Ⅱ实现多任务的调度和外围设备的管理。经实验验证,本遥控器具有高稳定性、高实时性、高可靠性、低误码率等优点。     

Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

检验标准管理系统的设计与实现

检验标准管理系统从工作实际出发,采用VisualBasic来制作交互介面,MicrosoftAccess作为后台支持的数据库来管理数据信息,从而实现产品质量检验机构的检验标准管理自动化。该系统是从服务客户和检验人员的角度出发,本着为客户提供准确、快捷、方便服务和更好管理本单位检验标准、方便检验人员使用的原则,可使检验机构大量的检验标准信息得以快捷管理,缩短了客户办理检验业务的时间,以及检验人员检验过程中快速查询使用检验标准的相关信息。本管理系统主要完成:对检验标准中数据的增加、数据的删除、数据的查询和数据的浏览。     

高空作业平台臂架伸缩运动的横向振动特性

为了探究高空作业平台做伸缩运动时变幅平面内的横向振动动力学特性,针对臂架的实际搭接和支承情况,将臂架等效为根部铰接、中间弹性支承且带有集中参数的变截面变长度梁. 基于牛顿第二定律建立各臂段的运动微分方程,采用模态叠加法、结合边界条件求解臂架一系列时刻的瞬态振型函数,曲线拟合时变参数以近似表示梁的振型,并依据伽辽金截断方法,得到广义坐标下的状态空间方程. 在Matlab/Simulink环境下进行动态仿真,得到伸缩过程中臂架头部的变幅平面横向振动动态响应. 结果表明,就横向振动振幅而言,搭接简化会带来15.63%计算结果误差;支承简化会加大臂架整体刚度、减小臂架振动响应,不可取。     

Factors Influencing Movements of Two Migratory Fishes within the Tailrace of a Large Neotropical Dam and their Implications for Hydropower Impacts

Fish attempting to move upstream through hydroelectric dams can be trapped and killed in turbines. Understanding fish movement patterns can provide useful insights for how to manage dam operations to minimize fish kill in turbines. We evaluated the movements of two migratory fish (Curimba—Prochilodus argenteus and Mandi—Pimelodus maculatus ) using acoustic telemetry in the tailrace of Três Marias Dam (São Francisco River, Brazil) from 31 October 2011 to 16 February 2012. The majority of tagged fish left the tailrace in less than one week; however, some individuals returned, performing several visits to the tailrace. Mandi remained longer in the tailrace than Curimba. The number of visits was influenced by diel period, turbine and spillway discharge. Although the diel period was the only important contributor to the visits performed by Curimba, the movements of Mandi were significantly influenced by three factors. We found that whereas Curimba was predominantly diurnal, Mandi showed nocturnal habits. Additionally, visits of Mandi were significantly greater during higher turbine and spillway discharge. We discuss the implications of these results for understanding fish movements in the Três Marias Dam tailrace and their potential implications for adapting hydroelectric operations to minimize fish kills. Copyright © 2016 John Wiley & Sons, Ltd.     

Host odor and visual stimulus interaction during intratree host finding behavior ofRhagoletis pomonella flies

Responses ofRhagoletis pomonella (Walsh) (Diptera: Tephritidae) flies to host fruit visual stimuli (apples or models of apples) and chemical stimuli (synthetic apple volatile blend) were studied in semidwarf field-caged apple trees. Three different fruit or model densities (1, 4, or 16 fruit or models/ tree) and two odor release rates [ca. 0.7g/hr (close to the natural release rate of a ripe apple) and ca. 500g/hr (amount of odor released by commercially sold apple maggot traps)] were tested. Individually released flies were followed as they moved within a tree for a maximum of 20 min. We recorded three-dimensional search paths followed by foraging flies and computed such variables as total relative distance traveled before alighting on a fruit or model, track length between individual alightment sites, and directness of flight to fruits or models. Effect of odor on propensity to alight on fruit or models and host-searching behavior prior to alighting on fruit or on models varied according to fruit or model color and density. If the fruit visual stimulus was strong (e.g., red color), odor did not increase the probability of finding fruit or fruit models. As the visual stimulus became progressively weaker (red to green to clear), odor (irrespective of concentration) appeared to aid flies during the fruit-finding process. As density of fruit or models increased, the probability of flies finding a fruit or model also increased (e.g., 50% of flies found a red fruit model at 1 model/tree while 90% found a red model at 16 models/tree; 4% of flies found a clear model with odor at 1 model/tree while 35% found a clear model with odor at 16 models/tree). Findings reported elsewhere indicate thatR. pomonella flies are able to discover a point source of odor (an odor-bearing tree in a patch of trees) by flying upwind (in the tree patch) in response to intermittent exposure to odor. Findings here indicate that after arrival on a host tree (point source), flies discover individual apparent and abundant host fruit on the basis of vision. If fruit are less apparent or scarce, odor appears to interact with vision during the fruit-finding process.