RETRACTED ARTICLE: Design of traffic object recognition system based on machine learning

Neural Computing and Applications - In recent years, researchers have proposed many methods to solve the problem of obstacle detection. However, computer vision-based vehicle detection and...     

RETRACTED ARTICLE: Research on image classification method based on convolutional neural network

Neural Computing and Applications - Image classification method is currently the more popular image technology, but it still has certain problems in practice. In order to improve the image...     

EEG extended source imaging with structured sparsity and $$L_1$$ -norm residual

Neural Computing and Applications - It is a long-standing challenge to reconstruct the locations and extents of cortical neural activities from electroencephalogram (EEG) recordings, especially...     

一种提升泵车臂架位置检测精度的工程应用解决方案

针对在利用倾角传感器实现混凝土泵车之类的大型操作机的臂架姿态的间接测量方案中存在的因为臂架的柔性和操作机在不同姿态下自身水平状态的不同可能导致的臂架末端的理论计算值存在较大测量误差的问题,采用了一种在臂架的不同位置增加传感器来实现对臂架柔性变形大小和自身水平状态的实时检测的方法,并着重研究了针对具体的柔性变形及水平状态变化所导致的理论偏差进行实时补偿的切实可行的方法,实验检测的数据证明,相对补偿前臂架的定位精度提升了75％以上.     

石英晶体振荡器的微处理器温度补偿技术研究

为改善石英晶体振荡器的频率特性,减小温度影响,通过对石英晶体振荡器的频率-温度特性的研究,提出了以微处理器（STC89C52RC）为核心的基于AT切晶体谐振器的温度补偿技术,并介绍了系统结构、补偿原理及硬件电路,给出了补偿结果。本设计具有结构简单、功耗低等优点。     

Morse set classification and hierarchical refinement using Conley index

Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion. Our framework allows a Morse set to be refined through a local update of the flow combinatorialization graph, as well as the connection regions between Morse sets. The computation is fast because the most expensive computation is concentrated on a small portion of the domain. Furthermore, the present work allows the generation of a topologically consistent hierarchy of MCGs, which cannot be obtained using a global method. The classification of the extracted Morse sets is a crucial step for the construction of the MCG, for which the Poincare′ index is inadequate. We make use of an upper bound for the Conley index, provided by the Betti numbers of an index pair for a translation along the flow, to classify the Morse sets. This upper bound is sufficiently accurate for Morse set classification and provides supportive information for the automatic refinement process. An improved visualization technique for MCG is developed to incorporate the Conley indices. Finally, we apply the proposed techniques to a number of synthetic and realworld simulation data to demonstrate their utility.     

On delay adjustment for dynamic load balancing in distributed virtual environments

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.     

结晶性高聚物作为相变材料的应用

本文研究了结晶性高聚物聚乙烯及其共混物作为相变材料对模拟发热体铜片热量的吸收作用，由于相变的吸热，铜片的温度在一定时间范围内保持在一个定值。选择不同的相变材料，可使这种温度平台出现在不同的温度范围，不共晶的共混物可有两个以上的温度平台，提高了降温效果。     

Comprehensive Benefit Evaluation System for Low-Impact Development of Urban Stormwater Management Measures

In recent years, plenty of simulation research about the low impact development(LID) control effect has emerged, but studies on scheme comparison and evaluation are lacking. In this study, a comprehensive benefit evaluation system for LID, including environmental, economic, and social benefits, was established on the basis of Analytic Hierarchy Process(AHP) and urban storm water model. Above all, benefit identification, quantitative evaluation and scheme comparison of single LID measures were obtained according to site investigation, simulated calculation and theoretical analysis. Whereafter, LID combination plans were designed based on single LID measures with high comprehensive benefit values, and their comprehensive benefits were evaluated to obtain the optimal plan. Then, based on well-founded system combined with Storm Water Management Model (SWMM), the design and optimization of LID were conducted, with a case in Xi’an, China. It turned out that the preferential order of the LID single measures according to the comprehensive benefit was: bio-retention > rain barrels > low-elevation greenbelt > green roofs > permeable pavement. Five LID combination plans were designed based on bio-retention, rain barrels, low-elevation greenbelt, and green roofs. Evaluation results showed that plan I (bio-retention and green roofs) was the optimal LID combination plan.     

Video background modeling: recent approaches,issues and our proposed techniques

Effective and efficient background subtraction is important to a number of computer vision tasks. We introduce several new techniques to address key challenges for background modeling using a Gaussian mixture model (GMM) for moving objects detection in a video acquired by a static camera. The novel features of our proposed model are that it automatically learns dynamics of a scene and adapts its parameters accordingly, suppresses ghosts in the foreground mask using a SURF features matching algorithm, and introduces a new spatio-temporal filter to further refine the foreground detection results. Detection of abrupt illumination changes in the scene is dealt with by a model shifting-based scheme to reuse already learned models and spatio-temporal history of foreground blobs is used to detect and handle paused objects. The proposed model is rigorously tested and compared with several previous models and has shown significant performance improvements.