基于XC2287M的工程机械ECU设计

ECU是工程机械电控系统的核心部件,目前国内中高端ECU市场基本被国外厂商所垄断。设计了一款基于XC2287M微控制器的工程机械智能ECU,采用CODESYS软PLC作为编程平台,支持IEC 61131-3定义的5种标准PLC语言进行编程。所设计的ECU拥有丰富的I/O资源和完善的安全保护机制,能够广泛应用于各种工程机械控制系统,打破国外厂商对ECU市场的垄断。     

高斯类小波变换的开关电流频域法实现

提出了一种基于频域共享结构的高斯类小波变换的开关电流电路。通过分析在频域具有相似表达的Morlet、Marr和DOG小波函数,基于频域共享单元实现高斯类小波变换频域共享系统。频域共享高斯类小波变换采用开关电流技术实现,不同尺度上的高斯类小波变换可通过调节开关电流电路的时钟频率获得。仿真结果证实了提出方法的有效性。     

Android平台i-Jetty服务器在智能家居中的应用研究

针对智能家居系统架构复杂、开发难度较大等问题,提出了一种基于Android平台嵌入式Web服务器i-Jetty的智能家居系统方案。在ARM硬件平台及Android软件平台上,采用i-Jetty服务器实现了家居环境信息网络远程监控功能。系统以Mini6410开发板为中央控制器、服务器和室内监控平台,采用蓝牙与被控设备进行通信,通过Linux层驱动加载、Android本地服务和Web服务的联合编程,实现对传感器数据的获取、家电控制和信息发布。实验结果证明了方案的可行性和实用性。     

Accelerating 2D orthogonal matching pursuit algorithm on GPU

Two-dimensional orthogonal matching pursuit (2D-OMP) algorithm is an extension of the one-dimensional OMP (1D-OMP), whose complexity and memory usage are lower than the 1D-OMP when they are applied to 2D sparse signal recovery. However, the major shortcoming of the 2D-OMP still resides in long computing time. To overcome this disadvantage, we develop a novel parallel design strategy of the 2D-OMP algorithm on a graphics processing unit (GPU) in this paper. We first analyze the complexity of the 2D-OMP and point out that the bottlenecks lie in matrix inverse and projection. After adopting the strategy of matrix inverse update whose performance is superior to traditional methods to reduce the complexity of original matrix inverse, projection becomes the most time-consuming module. Hence, a parallel matrix–matrix multiplication leveraging tiling algorithm strategy is launched to accelerate projection computation on GPU. Moreover, a fast matrix–vector multiplication, a parallel reduction algorithm, and some other parallel skills are also exploited to boost the performance of the 2D-OMP further on GPU. In the case of the sensing matrix of size 128 \(\times \) 256 (176 \(\times \) 256, resp.) for a 256 \(\times \) 256 scale image, experimental results show that the parallel 2D-OMP achieves 17 \(\times \) to 41 \(\times \) (24 \(\times \) to 62 \(\times \) , resp.) speedup over the original C code compiled with the O \(_2\) optimization option. Higher speedup would be further obtained with larger-size image recovery.     

An energy conservation replica placement strategy for Dynamo

With the fast development of cloud computing and wide application of cloud storage, the energy efficiency of cloud storage system is drawing significant attention from researchers or specialists. For the typical Dynamo cloud storage system, we design a new policy instead of the consistent hashing policy which is a combination of consistent hashing and sequential policy. The basic idea of this policy is that it divides the nodes into groups and allows each other to be mirror modes so it can find the full coverage subset of data items easily. Also we use autoregressive-moving-average model to estimate the task numbers of servers so that when under low utilization period, certain numbers of servers can be turned off to save energy. Based on the model, we demonstrate that it can save up to 23.7 % energy and maintain load balancing of servers. Furthermore, we compare our policy with Heuristic which is a classical energy conservation policy for cloud storage system that is based on consistent hash table. And we find several advantages of our policy which include finding the minimum subset of full coverage as well as other aspects.     

Reconstructing the World’s Museums

Virtual exploration tools for large indoor environments (e.g. museums) have so far been limited to either blueprint-style 2D maps that lack photo-realistic views of scenes, or ground-level image-to-image transitions, which are immersive but ill-suited for navigation. On the other hand, photorealistic aerial maps would be a useful navigational guide for large indoor environments, but it is impossible to directly acquire photographs covering a large indoor environment from aerial viewpoints. This paper presents a 3D reconstruction and visualization system for automatically producing clean and well-regularized texture-mapped 3D models for large indoor scenes, from ground-level photographs and 3D laser points. The key component is a new algorithm called “inverse constructive solid geometry (CSG)” for reconstructing a scene with a CSG representation consisting of volumetric primitives, which imposes powerful regularization constraints. We also propose several novel techniques to adjust the 3D model to make it suitable for rendering the 3D maps from aerial viewpoints. The visualization system enables users to easily browse a large-scale indoor environment from a bird’s-eye view, locate specific room interiors, fly into a place of interest, view immersive ground-level panorama views, and zoom out again, all with seamless 3D transitions. We demonstrate our system on various museums, including the Metropolitan Museum of Art in New York City—one of the largest art galleries in the world.     

A saliency-driven robotic head with bio-inspired saccadic behaviors for social robotics

This paper presents a robotic head for social robots to attend to scene saliency with bio-inspired saccadic behaviors. Scene saliency is determined by measuring low-level static scene information, motion, and object prior knowledge. Towards the extracted saliency spots, the designed robotic head is able to turn gazes in a saccadic manner while obeying eye–head coordination laws with the proposed control scheme. The results of the simulation study and actual applications show the effectiveness of the proposed method in discovering of scene saliency and human-like head motion. The proposed techniques could possibly be applied to social robots to improve social sense and user experience in human–robot interaction.     

Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

纳米微胶囊技术与纳米化妆品研究进展

本文着重阐述了有关纳米胶囊的制备方法及最新研究进展,并展望了纳米技术及纳米微胶囊在化妆品领域的应用前景.     

Multi-scale patch-based sparse appearance model for robust object tracking

When objects undergo large pose change, illumination variation or partial occlusion, most existing visual tracking algorithms tend to drift away from targets and even fail to track them. To address the issue, in this paper we propose a multi-scale patch-based appearance model with sparse representation and provide an efficient scheme involving the collaboration between multi-scale patches encoded by sparse coefficients. The key idea of our method is to model the appearance of an object by different scale patches, which are represented by sparse coefficients with different scale dictionaries. The model exploits both partial and spatial information of targets based on multi-scale patches. Afterwards, a similarity score of one candidate target is input into a particle filter framework to estimate the target state sequentially over time in visual tracking. Additionally, to decrease the visual drift caused by frequently updating model, we present a novel two-step object tracking method which exploits both the ground truth information of the target labeled in the first frame and the target obtained online with the multi-scale patch information. Experiments on some publicly available benchmarks of video sequences showed that the similarity involving complementary information can locate targets more accurately and the proposed tracker is more robust and effective than others.