一种林业手持式多功能测树仪设计

针对森林调查对便携式测量设备自动化和集成化的需求,设计了一种集测高器、角规和标准蓄积量计算功能于一体,具有测量、数据存储、计算等多种功能的手持式多功能电子测树仪GForest。该仪器通过采样控制算法实现对测高器防抖动设计,采用计数器存储并控制角规计数结果,提供USB接口同PC和移动智能终端设备进行数据共享,旨在解决目前森林地面调查数据采集硬件设备信息化与数据采集软件发展不同步的问题,大幅减少了外业调查中手工数据记录和录入的工作,提高了野外数据采集的效率。经实测验证:GForest测得的立木高度与实际值的平均误差为4%,与进口同类设备精度持平,同时还具有角规绕测计数与控制等实用功能,且具有明显的成本优势,适合在行业内推广应用。     

Preparation,characterization, and adsorption properties for metal ions of a novel chelating resin containing sulfoxide and diethylene glycol

A novel chelating resin containing sulfoxide and diethylene glycol, poly{4‐vinylbenzyl‐[2‐2‐(hydroxyethyl)ethoxyl]sulfoxide} (PVESO) was synthesized using chloromethylated polystyrene (PS‐Cl) as material. Its structure was characterized by elemental analysis, infrared spectra, and scanning electron microscopy (SEM). The adsorption capacities of the resin for Hg²⁺, Ag⁺, Cu²⁺, Zn²⁺, and Pb²⁺ at various pH values were determined. The maximum adsorption capacities for Hg²⁺ and Ag⁺ were 1.56 and 0.75 mmol g^?1 respectively. The resin had high selectivity for Hg²⁺ and Ag⁺ over the pH range 1.0–7.0. The adsorption capacities for Hg²⁺ and Ag⁺ under competitive condition were also determined by batch experiment method. In addition, the adsorption kinetics of the resin towards Hg²⁺ at different temperatures was also investigated. The results showed that the adsorption rate was governed by film diffusion at 20°C and 25°C, by particle diffusion at 30°C and 35°C. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 6054–6059, 2006     

基于信息流动分析的动态社区发现方法

随着社交网络和微博等互联网应用的逐渐流行,其用户规模在迅速膨胀.在这些大规模网络中,社区发现可以为个性化服务推荐和产品推广提供重要依据.不同于传统的网络,这些新型网络的节点之间除了拓扑结构外,还进行频繁的信息交互.信息流动使得这些网络具有方向性和动态性等特征.传统的社区发现方法由于没有考虑到这些新的特征,并不适用于这些新型网络.在传染病动力学理论的基础上,从节点间信息流动的角度,提出一种动态社区发现方法.该方法通过对信息流动的分析来发现联系紧密、兴趣相近的节点集合,以实现动态的社区发现.在真实数据集上的实验结果表明：相对于传统的社区发现方法,所提出的方法能够更准确地发现社区,并且更能体现网络中社区的动态变化.     

Communicating Is Crowdsourcing: Wi-Fi Indoor Localization with CSI-Based Speed Estimation

Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location-based service (LBS). Among them, the most popular solutions are the Wi-Fi fingerprint-based approaches. The core challenge is to lower the cost of fingerprint site-survey. One of the trends is to collect the piecewise data from clients and establish the radio map in crowdsourcing manner. However the low participation rate blocks the practical use. In this work, we propose a passive crowdsourcing channel state information (CSI) based indoor localization scheme, C²IL. Despite a crowdsourcing based approach, our scheme is totally transparent to the client and the only requirement is to connect to our 802.11n access points (APs). C²IL is built upon an innovative method to accurately estimate the moving speed solely based on 802.11n CSI. Knowing the walking speed of a client and its surrounding APs, a graph matching algorithm is employed to extract the received signal strength (RSS) fingerprints and establish the fingerprint map. For localization phase, we design a trajectory clustering based localization algorithm to provide precise real-time indoor localization and tracking. We develop and deploy a practical working system of C²IL in a large office environment. Extensive evaluations indicate that the error of speed estimation is within 3%, and the localization error is within 2 m at 80% time in a very complex indoor environment.     

计算思维导向的计算机程序设计课程教学改革研究

根据程序设计类课程与计算思维之间的内在联系,提出以“案例教学、趣味教学、微课堂”为根本的教学改革,阐述如何在新的人才培养模式下构建教学方法,即通过优化教学内容、创新实践方法等一系列举措,将程序设计的思想与方法转化为学生的创新精神和创新能力。     

国内BOPP膜生产现状

介绍了国内BOPP薄膜和专用料的生产情况，并提出了建议。     

玻璃钢筋混凝土的有限元计算与试验

钢筋混凝土广泛应用于土木工程领域，但其结构耐久性因钢筋本身的锈蚀成为现今急待解决的问题。人们一直在寻找对钢筋混凝土进行改良的途径，用玻璃钢筋代替普通钢筋是解决这一问题的一个有效的方法，为此进行了试验和ANSYS有限元分析，结果证明此法具有可行性。     

3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

Coupling-and-decoupling: A hierarchical model for occlusion-free object detection

Handling occlusion is a very challenging problem in object detection. This paper presents a method of learning a hierarchical model for X-to-X occlusion-free object detection (e.g., car-to-car and person-to-person occlusions in our experiments). The proposed method is motivated by an intuitive coupling-and-decoupling strategy. In the learning stage, the pair of occluding X?s (e.g., car pairs or person pairs) is represented directly and jointly by a hierarchical And–Or directed acyclic graph (AOG) which accounts for the statistically significant co-occurrence (i.e., coupling). The structure and the parameters of the AOG are learned using the latent structural SVM (LSSVM) framework. In detection, a dynamic programming (DP) algorithm is utilized to find the best parse trees for all sliding windows with detection scores being greater than the learned threshold. Then, the two single X?s are decoupled from the declared detections of X-to-X occluding pairs together with some non-maximum suppression (NMS) post-processing. In experiments, our method is tested on both a roadside-car dataset collected by ourselves (which will be released with this paper) and two public person datasets, the MPII-2Person dataset and the TUD-Crossing dataset. Our method is compared with state-of-the-art deformable part-based methods, and obtains comparable or better detection performance.     

Target detection based on a dynamic subspace

For hyperspectral target detection, it is usually the case that only part of the targets pixels can be used as target signatures, so can we use them to construct the most proper background subspace for detecting all the probable targets? In this paper, a dynamic subspace detection (DSD) method which establishes a multiple detection framework is proposed. In each detection procedure, blocks of pixels are calculated by the random selection and the succeeding detection performance distribution analysis. Manifold analysis is further used to eliminate the probable anomalous pixels and purify the subspace datasets, and the remaining pixels construct the subspace for each detection procedure. The final detection results are then enhanced by the fusion of target occurrence frequencies in all the detection procedures. Experiments with both synthetic and real hyperspectral images (HSI) evaluate the validation of our proposed DSD method by using several different state-of-the-art methods as the basic detectors. With several other single detectors and multiple detection methods as comparable methods, improved receiver operating characteristic curves and better separability between targets and backgrounds by the DSD methods are illustrated. The DSD methods also perform well with the covariance-based detectors, showing their efficiency in selecting covariance information for detection.