《C语言程序设计》教学中问题和改进方法的探讨

《C语言程序设计》是计算机专业学习中的一门基础的课程．是培养学生对计算机学习兴趣的关键课程。提出C语言教学过程中存在的一些问题。对问题进行分析,提出解决问题的方法。根据笔者的多年的教学实践,阐述一些教学方法和教学经验,对教师在教学思路和方法上有一定的指导意义,能够更好地提高教学水平。     

基于地面先验的3D目标检测算法

为了提高自动驾驶汽车环境感知的性能,增强单目相机对障碍物三维和边界信息的感知能力,提出了一种基于地面先验的3D目标检测算法。基于优化的中心网络(CenterNet)模型,以DLA(deep layer aggregation)为主干网络,增加目标3D边沿框中心点冗余信息预测。根据自动驾驶场景的地面先验信息,结合针孔相机模型,获取目标3D中心深度信息,以优化深度网络学习效果。使用KITTI 3D数据集评测算法性能,结果表明:在保证2D目标检测准确性的基础上,该算法运行帧率约20 fps,满足自动驾驶感知实时性要求;同时相比于CenterNet模型,在平均方位角得分(average orientation score)和鸟视图平均准确率(bird eye view AP)上分别有4.4和4.4%的性能提升。因而,该算法可以提高自动驾驶汽车对障碍物三维和边界信息的感知能力。     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

Correction to: Parallel Single-Pixel Imaging: A General Method for Direct–Global Separation and 3D Shape Reconstruction Under Strong Global Illumination

International Journal of Computer Vision - In the original publication of the article, the name of the last author should be Yang Xu, instead of Xu Yang. “Xu” is the family name, and...     

Bibliometric analysis on tendency and topics of artificial intelligence over last decade

Microsystem Technologies - Artificial intelligence (AI), together with its applications, has received world-wide attentions and is expected to exert force on the development of global economy and...     

Texture compensation with multi-scale dilated residual blocks for image denoising

Neural Computing and Applications - Deep convolutional neural networks have achieved great success for image denoising recently. However, increasing the depth of the neural network cannot...     

井下人员定位系统读卡器存储算法分析与测试

从查找时间与存储容量2个方面分析了适用于井下人员定位系统读卡器的3种存储算法,即链式存储算法、哈希表存储算法和哈希二叉树存储算法,给出了该3种不同存储算法的使用效率与应用场合。测试结果表明,链式存储算法查找时间呈线性增长,哈希表存储算法明显优越于链式存储算法,如果测试数据增多,其优越性会更明显;当数据量较大时,哈希搜索二叉树存储算法又明显优于哈希表存储算法,当人数达到行业所要求的8 000人以上时,选择哈希搜索二叉树存储算法更为合理。     

AFDX网络协议研究

介绍了AFDX网络的产生背景及发展历程;解析了ARINC664规范各个部分的功能及与开放式系统参考模型的关系;总结了AFDX网络相对于商用以太网的特点和AFDX网络与机载系统的关系,通过对AFDX在A380等飞机上的应用研究,归纳了基于AFDX网络的航空电子系统的特点;AFDX网络已成功应用于工程实践,该网络具有完整的协议结构,具有高实时性、高确定性和高可靠性的特点,是一种新型的机载网络总线。     

基于LVDS技术的高速数据传输系统设计

串行传输技术具有更高的传输速率和更低的设计成本,被广泛应用于高速通信领域;研究了一种基于FPGA的LVDS高速数据传输系统方案,该方案以Altera FPGA芯片为核心,通过其LVDS I/O口稳定可靠地完成数据传输,系统采用Verilog语言完成8B/10B编解码、时钟数据恢复、CRC校验、字节边界调整、误码率测试模块等;通过实验表明,该方案既满足了长距离和高速数据传输的要求,又降低了系统成本。     

基于FPGA和ARM的弹上相位自动微调控制器设计与实现

为了提高相位自动微调控制器的控制性能,针对某型导弹,提出并实现了以ARM+ FPGA双微处理器为核心的硬件设计方案,采用了模糊PID控制算法,通过优化步进电机控制模式,提高了相位自动微调控制器的控制精度,将步进电机的调整时间由800 ms缩短到100 ms以内;该方案已成功应用于某型弹上系统,实践证明,该设计方案成本低、可扩展性强,能够满足系统控制需求,具有较高的实用性,大大提高了装备维护效率.