Keil uVision3与Proteus的联合仿真在单片机教学中的应用

针对传统单片机教学的弊端,提出了使用Keil uVision3软件与proteus软件建立联合仿真解决降低硬件成本和减少调制周期的方法,描述了Keil uVision3软件与proteus软件,通过Proteus软件的ISIS模块画出原理图,在Keil uVision3编写C语言程序,进行联合仿真调试。再在ARES模块画出PCB图,使用ARES模块的3D Visualization功能提前预览成品。

Proteus和KeiluVision3联合应用实例

提出采用Proteus和KeiluVision3联合应用构建单片机虚拟实验室的方法来解决单片机实验和教学中遇到的实验手段落后、成本高等诸多问题,以实现基于AT89C52的数码时钟为例来论述这一方法的实现过程,并给出了数码时钟的电路原理图和全部的程序流程图。

浅谈Proteus与Keil uVision3的联机调试

本文简单介绍基于EDA技术的Proteus软件,用实例介绍Proteus与Keil uVision3的联机调试方法。

Multi-Branch High-Dimensional Guided Transformer-Based 3D Human Posture Estimation

The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.

Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+Deep Learning Model

The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage,impacting the aero-dynamic performance of the blades.To address the challenge of detecting and quantifying surface defects on wind turbine blades,a blade surface defect detection and quantification method based on an improved Deeplabv3+deep learning model is proposed.Firstly,an improved method for wind turbine blade surface defect detection,utilizing Mobilenetv2 as the backbone feature extraction network,is proposed based on an original Deeplabv3+deep learning model to address the issue of limited robustness.Secondly,through integrating the concept of pre-trained weights from transfer learning and implementing a freeze training strategy,significant improvements have been made to enhance both the training speed and model training accuracy of this deep learning model.Finally,based on segmented blade surface defect images,a method for quantifying blade defects is proposed.This method combines image stitching algorithms to achieve overall quantification and risk assessment of the entire blade.Test results show that the improved Deeplabv3+deep learning model reduces training time by approximately 43.03%compared to the original model,while achieving mAP and MIoU values of 96.87%and 96.93%,respectively.Moreover,it demonstrates robustness in detecting different surface defects on blades across different back-grounds.The application of a blade surface defect quantification method enables the precise quantification of dif-ferent defects and facilitates the assessment of risk levels associated with defect measurements across the entire blade.This method enables non-contact,long-distance,high-precision detection and quantification of surface defects on the blades,providing a reference for assessing surface defects on wind turbine blades.

Keil公司发布新的8051开发工具C51 μVision 3

2005年11月16日，Keil公司发布新的μVision 3 开发环境工具和C51第8版优化编译器，它们将用于典型及扩展的8051微处理器的开发。这两款产品将共同带给开发者丰富的功能特点，并提供一个为广泛的8051微处理器类型而优化的综合开发环境。

基于Keil μVision模拟器构建软件调试测试环境

详细描述了Keil μVision模拟器扩展接口的使用方式,以及进行调试测试环境构建的特定步骤.使用这种方式构建调试测试环境无需硬件设备,研制周期短、成本低,使单片机软件研制和测试人员能够快速构建软件运行环境,及时对软件进行调试和测试.

新型宽带近红外BaSnO_(3):Fe^(3+)荧光粉的特性研究

宽带近红外荧光粉转换的近红外LED光源广泛应用于生物医学、物性分析及夜视等领域中,而Fe^(3+)由于具有生物环境友好型特点,被视为一种有巨大潜力用于开发新型宽带近红外荧光粉的激活离子。采用高温固相法合成了一款Fe^(3+)掺杂的新型近红外荧光粉BaSnO_(3):Fe^(3+),并对Fe^(3+)宽带近红外发光机理进行了研究。结果表明:荧光粉BaSnO_(3):Fe^(3+)在波长380 nm的近紫外光激发下,发射出750—1 150 nm的宽带近红外光,其峰值位于896 nm处、半高宽为105 nm;BaSnO_(3):Fe^(3+)在380 nm处的电子跃迁对应于^(6)A_(1)(6S)→4E(4D)的跃迁,而在896 nm处的电子跃迁对应于^(4)T_(1)(4G)→^(6)A_(1)(6S)的跃迁;当Fe^(3+)掺杂浓度(摩尔分数)达到0.03%时,其发射强度达到最大、激活能约为0.657 eV。说明,将所合成的材料封装成宽带近红外LED器件,可实现夜视照明。

RANGE ACQUISITION IN BINOCULAR 3-D COMPUTER VISION USING EDGE-BASED HIERARCHICAL MATCHING

This paper deals with a binocular 3-D computer vision system based on the hierarchicalmatching of edge features, Frei and Chen operator is used to extract the edge. The averagegradients of an image obtained by two isotropic operators are non-equal quantized andthresholded in an angle, Edge features are extracted after passing a preemphasis transferfunction which can equalize, the noise affection. Binary edge images are decomposed into apyramid structure which is stored and searched using llliffe’s location method. Corre-sponding points are used to determine the range data using triangulation based on an improvedTrivedi’s formula. In calibration the authors set the optical axes of the two cameras parallelto simplify the calculation, A 3 rd order Householder transform is used to solve the compati-ble coupled equations.

3D电影的发展以及NVIDIA 3D VISION平台的搭建

本文简要回顾了3D电影的发展史,并讨论了如何搭建NVIDIA 3D Vision平台,以便在家中欣赏3D大片和玩3D游戏。

Modeling of a Linear Scanning 3D Vision Coordinate Measurement System

This paper theoretically analyzes and researches the coordinate frames of a 3D vision scanning system, establishes the mathematic model of a system scanning process, derives the relationship between the general non-orthonormal sensor coordinate system and the machine coordinate system and the coordinate transformation matrix of the extrinsic calibration for the system.

Recognition of Multifunctional Coded Target in Single-camera Mobile 3D-vision Coordination Measurement

Single-camera mobile-vision coordinate measurement is one of the primary methods of 3D-coordinate vision measurement, and coded target plays an important role in this system. A multifunctional coded target and its recognition algorithm is developed, which can realize automatic match of feature points, calculation of camera initial exterior orientation and space scale factor constraint in measurement system. The uniqueness and scalability of coding are guaranteed by the rational arrangement of code bits. The recognition of coded targets is realized by cross-ratio invariance restriction, space coordinates transform of feature points based on spacial pose estimation algorithm, recognition of code bits and computation of coding values. The experiment results demonstrate the uniqueness of the coding form and the reliability of recognition.

3D Reconstruction of Fruit Shape based on Vision and Edge Sections

The fruit industry has been known as one of the largest businesses in Malaysia,where most of the fruits pass through the peeling process well in advance before the final product as juice in a bottle or slices in a can.The current industrial fruit peeling techniques are passive and inefficient by cutting parts of the pulp of the fruit with peels leading to losses.To avoid this issue,a multi-axis CNC fruit peeler can be used to precisely peel the outer layer with the guidance of a 3D virtual model of fruit.In this work,a new cost-effective method of 3D image reconstruction was developed to convert 36 fruit images captured by a normal RGB camera to a 3D model by capturing a single image every 10 degrees of fruit rotation along a fixed axis.The point cloud data extracted with edge detection were passed to Blender 3D software for meshing in different approaches.The vertical link frame meshing method developed in this research proved a qualitative similarity between the output result and the scanned fruit in a processing time of less than 50 seconds.

Real Objects Understanding Using 3D Haptic Virtual Reality for E-Learning Education

In the past two decades,there has been a lot of work on computer vision technology that incorporates many tasks which implement basic filtering to image classification.Themajor research areas of this field include object detection and object recognition.Moreover,wireless communication technologies are presently adopted and they have impacted the way of education that has been changed.There are different phases of changes in the traditional system.Perception of three-dimensional(3D)from two-dimensional(2D)image is one of the demanding tasks.Because human can easily perceive but making 3D using software will take time manually.Firstly,the blackboard has been replaced by projectors and other digital screens so such that people can understand the concept better through visualization.Secondly,the computer labs in schools are now more common than ever.Thirdly,online classes have become a reality.However,transferring to online education or e-learning is not without challenges.Therefore,we propose a method for improving the efficiency of e-learning.Our proposed system consists of twoand-a-half dimensional(2.5D)features extraction using machine learning and image processing.Then,these features are utilized to generate 3D mesh using ellipsoidal deformation method.After that,3D bounding box estimation is applied.Our results show that there is a need to move to 3D virtual reality(VR)with haptic sensors in the field of e-learning for a better understanding of real-world objects.Thus,people will have more information as compared to the traditional or simple online education tools.We compare our result with the ShapeNet dataset to check the accuracy of our proposed method.Our proposed system achieved an accuracy of 90.77%on plane class,85.72%on chair class,and car class have 72.14%.Mean accuracy of our method is 70.89%.

Fast Estimation of Loader’s Shovel Load Volume by 3D Reconstruction of Material Piles

Fast and accurate measurement of the volume of earthmoving materials is of great signifcance for the real-time evaluation of loader operation efciency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fll factor estimation, and it has signifcant theoretical research and engineering application value.

Recognition of mortar pumpability via computer vision and deep learning

The mortar pumpability is essential in the construction industry,which requires much labor to estimate manually and always causes material waste.This paper proposes an effective method by combining a 3-dimensional convolutional neural network(3D CNN)with a 2-dimensional convolutional long short-term memory network(ConvLSTM2D)to automatically classify the mortar pumpability.Experiment results show that the proposed model has an accuracy rate of 100%with a fast convergence speed,based on the dataset organized by collecting the corresponding mortar image sequences.This work demonstrates the feasibility of using computer vision and deep learning for mortar pumpability classification.

An Efficient Method for Underwater Video Summarization and Object Detection Using YoLoV3

Currently,worldwide industries and communities are concerned with building,expanding,and exploring the assets and resources found in the oceans and seas.More precisely,to analyze a stock,archaeology,and surveillance,sev-eral cameras are installed underseas to collect videos.However,on the other hand,these large size videos require a lot of time and memory for their processing to extract relevant information.Hence,to automate this manual procedure of video assessment,an accurate and efficient automated system is a greater necessity.From this perspective,we intend to present a complete framework solution for the task of video summarization and object detection in underwater videos.We employed a perceived motion energy(PME)method tofirst extract the keyframes followed by an object detection model approach namely YoloV3 to perform object detection in underwater videos.The issues of blurriness and low contrast in underwater images are also taken into account in the presented approach by applying the image enhancement method.Furthermore,the suggested framework of underwater video summarization and object detection has been evaluated on a publicly available brackish dataset.It is observed that the proposed framework shows good performance and hence ultimately assists several marine researchers or scientists related to thefield of underwater archaeology,stock assessment,and surveillance.

只有EDGE大行其道,3G才能更好地推广——杰尔发布VisionX115解决方案

EDGE是一种基于G S M/G P R S网络的数据增强型移动通信技术,通常又被人们称为2.75G技术。2005年曾一度遭遇冷落的EDGE先后取得了TelefonicaMovistar、Orange、BrasilTelecomGSM等24家运营商的青睐。截至7月份,EDGE在全球已经拥有170个运营商追随。然而,中国市场3G的呼声日渐高涨,从标准到产品再到牌照,业界已经把3G研究了个彻头彻尾。因此,中国的移动市场对于EDGE来说又是不同于其他国家。作为全球著名移动通信整体解决方案供应商的杰尔系统本次推出了他们基于Vision架构的X115解决方案表达了来自杰尔系统对于移动市场的声音。

基于Proteus和Keil接口的单片机外围硬件电路仿真

单片机的开发需要良好的软件环境的支持,现在国内外已经有若干软件仿真支持51系列单片机,但外围设备的仿真仍然是仿真软件的一个薄弱环节。针对目前流行的Keil公司的仿真器,结合Proteus仿真软件,介绍了对单片机外围设备的仿真实现。为单片机的软硬件结合虚拟仿真提出了一个新的思路。

城市3～6岁儿童视力和立体视力发育状况及相关因素研究

目的 :探讨城市 3～ 6岁儿童视力和立体视力的现状及发育过程中的影响因素。方法 :选取城市 3～ 6岁儿童 15 5 6名进行视力和立体视力检查 ,通过调查表咨询及实验室测定等方法进行影响因素的调查分析。结果 :目前城市 3～ 6岁儿童视力低下率为 2 9.0 5 % ,以远视为多 ,约占视力低下人群的 4 8.2 3% ,近视约占视力低下的 36 .6 2 %。同时检测结果还表明 :3～ 6岁儿童立体视力低下的发病率较高。结论 :在调查的 4 9项因素中 ,儿童视力与看电视的时间与距离、遗传因素、出生时窒息或缺氧状态、是否饮用牛乳及年龄等有关。视力发育不好 。