飞腾平台中硬件数据压缩的驱动设计与实现

数据压缩是有效处理大数据的关键技术,在飞腾处理器平台上基于zlib库的数据压缩通常采用软件的方式实现,在数据处理量大而且实时性要求较高的情况下,已经难以满足需求。针对这个问题,通过研究zlib编程函数库,结合飞腾处理器的特性,完成了飞腾平台中硬件数据压缩的驱动设计与实现,其中提出了双向DMA传输技术和基于一致性内存的命令环机制,从而进一步提高了基于硬件的数据压缩的效率。通过实验证实了飞腾平台中采用硬件数据压缩改进的有效性。     

分布式网络测量中测量节点的智能选择算法

大规模网络结构复杂,需要有针对性的网络监测方法。测量节点的自动选择必须在测量代价和覆盖范围之间进行权衡。合理地测量节点选择,能在获取全网性能状况的同时,有效减少测量给待测网络带来的带宽占用和软硬件资源消耗的影响。以最小化测量节点数量为目标,选择蚁群算法作为测量节点自动选择的基本算法,并通过对基本算法进行改进和创新,可形成一种针对分布式网络测量的测量节点智能选择算法。     

Band selection for hyperspectral images using probabilistic memetic algorithm

Band selection plays an important role in identifying the most useful and valuable information contained in the hyperspectral images for further data analysis such as classification, clustering, etc. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving the NP-hard band selection problem. In this paper, we propose a formal probabilistic memetic algorithm for band selection, which is able to adaptively control the degree of global exploration against local exploitation as the search progresses. To verify the effectiveness of the proposed probabilistic mechanism, empirical studies conducted on five well-known hyperspectral images against two recently proposed state-of-the-art MAs for band selection are presented.     

A low-complexity sensor fusion algorithm based on a fiber-optic gyroscope aided camera pose estimation system

Visual tracking, as a popular computer vision technique, has a wide range of applications, such as camera pose estimation. Conventional methods for it are mostly based on vision only, which are complex for image processing due to the use of only one sensor. This paper proposes a novel sensor fusion algorithm fusing the data from the camera and the fiber-optic gyroscope. In this system, the camera acquires images and detects the object directly at the beginning of each tracking stage; while the relative motion between the camera and the object measured by the fiber-optic gyroscope can track the object coordinate so that it can improve the effectiveness of visual tracking. Therefore, the sensor fusion algorithm presented based on the tracking system can overcome the drawbacks of the two sensors and take advantage of the sensor fusion to track the object accurately. In addition, the computational complexity of our proposed algorithm is obviously lower compared with the existing approaches(86% reducing for a 0.5 min visual tracking). Experiment results show that this visual tracking system reduces the tracking error by 6.15% comparing with the conventional vision-only tracking scheme(edge detection), and our proposed sensor fusion algorithm can achieve a long-term tracking with the help of bias drift suppression calibration.     

Proportional directional valve based automatic steering system for tractors

Most automatic steering systems for large tractors are designed with hydraulic systems that run on either constant flow or constant pressure. Such designs are limited in adaptability and applicability. Moreover, their control valves can unload in the neutral position and eventually lead to serious hydraulic leakage over long operation periods. In response to the problems noted above, a multifunctional automatic hydraulic steering circuit is presented. The system design is composed of a 5-way-3- position proportional directional valve, two pilot-controlled check valves, a pressure-compensated directional valve, a pressurecompensated flow regulator valve, a load shuttle valve, and a check valve, among other components. It is adaptable to most open-center systems with constant flow supply and closed-center systems with load feedback. The design maintains the lowest pressure under load feedback and stays at the neutral position during unloading, thus meeting the requirements for steering. The steering controller is based on proportional-integral-derivative (PID) running on a 51-microcontroller-unit master control chip. An experimental platform is developed to establish the basic characteristics of the system subject to stepwise inputs and sinusoidal tracking. Test results show that the system design demonstrates excellent control accuracy, fast response, and negligible leak during long operation periods.     

数字化医院信息安全因素的分析与研究

随着计算机的高速发展,各大医院都加快了信息数字化的建设。在数字化信息的建设过程中,医院网络系统大大的提高了医院的工作进展效率,使得信息得到了更好的管理,但是在建设过程中,系统的保密性和安全性是首要考虑的要素。为了确保数字化医院系统的安全稳定运行,减少安全隐患,需要考虑有关安全方面的各个因素。本文针对医院数字化网络系统,对影响其安全的各个主要因素进行分析与研究。     

A grid-based clustering algorithm for wild bird distribution

Advanced satellite tracking technologies provide biologists with long-term location sequence data to understand movement of wild birds then to find explicit correlation between dynamics of migratory birds and the spread of avian influenza. In this paper, we propose a hierarchical clustering algorithm based on a recursive grid partition and kernel density estimation (KDE) to hierarchically identify wild bird habitats with different densities. We hierarchically cluster the GPS data by taking into account the following observations: 1) the habitat variation on a variety of geospatial scales; 2) the spatial variation of the activity patterns of birds in different stages of the migration cycle. In addition, we measure the site fidelity of wild birds based on clustering. To assess effectiveness, we have evaluated our system using a large-scale GPS dataset collected from 59 birds over three years. As a result, our approach can identify the hierarchical habitats and distribution of wild birds more efficiently than several commonly used algorithms such as DBSCAN and DENCLUE.