Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.     

Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.     

Thiamine concentrations in lake whitefish eggs from the upper Great Lakes are related to maternal diet

Thiamine deficiency is responsible for reproductive impairment in several species of salmonines in the Great lakes, and is thought to be caused by the consumption of prey containing thiaminase, a thiamine-degrading enzyme. Because thiaminase levels are extremely high in dreissenid mussels, fish that prey on them may be susceptible to thiamine deficiency. We determined thiamine concentrations in lake whitefish Coregonus clupeaformis eggs from the upper Laurentian Great Lakes to assess the potential for thiamine deficiency and to determine if thiamine concentrations in lake whitefish eggs were related to maternal diet. Mean thiamine concentrations in lake whitefish eggs were highest in Lake Huron, intermediate in Lake Superior, and lowest in Lake Michigan. Some fish had thiamine concentrations below putative thresholds for lethal and sublethal effects in salmonines, suggesting that some larval lake whitefish may currently be at risk of at least sublethal effects of low thiamine concentrations, although thiamine thresholds are unknown for lake whitefish. Egg thiamine concentrations in lake whitefish eggs were statistically significantly related to isotopic carbon signatures, suggesting that egg thiamine levels were related to maternal diet, but low egg thiamine concentrations did not appear to be associated with a diet of dreissenids. Egg thiamine concentrations were not statistically significantly related to multifunction oxidase induction, suggesting that lower egg thiamine concentrations in lake whitefish were not related to contaminant exposure.     

Experimental study of a novel hybrid constructed wetland for water reuse and its application in Southern China

A new type of hybrid constructed wetland (CW), consisting of both vertical-baffled flow wetland (VBFW) and horizontal subsurface flow wetland (HSFW), has been deployed in Southern China to naturally accelerate the removal of organic matter and nitrogen. The hybrid CW system is characterised by a combination of continuous baffled flow vertical wetland and 'S' pattern horizontal subsurface flow wetland with natural aeration ditches to increase the concentration of dissolved oxygen in the HSFW bed. An internal circulatory system from the HSFW effluent back to the VBFW may optionally be operated to enhance the biological denitrification effect. Cyperus alternifolius is the main macrophyte in the wetland bed. The performance of the hybrid CW was studied with a pilot-scale system and three full-scale systems for municipal sewage treatment in Southern China. The results suggest that this new hybrid CW can achieve removal efficiencies of chemical oxygen demand, suspended solids, ammonia nitrogen, total nitrogen, and total phosphorus of better than 83.6, 95.0, 71.7, 64.5 and 68.1% respectively, with a specific wetland bed area of 0.70-0.93 m(2) PE(-1). The mean effluent concentrations of these parameters would meet the regulatory discharge limits for wastewater treatment systems (GB18918, 2002) and reuse in the context of agricultural irrigation solutions in China.     

Determination of reaction rate constants for phenol oxidation using SnO2/Ti anodes coupled with activated carbon adsorption in the presence of TiO2 as catalyst

Series of experiments for phenol degradation with assistance of TiO2 catalyst at pH of 6.5 and temperature of 25 degrees C were conducted using a lab-scale electrochemical reactor constructed in our laboratory. According to the results, at the presence of the TiO2 catalyst the removal of phenol was increased and first-order kinetics could describe the evolution of phenol concentration. For inspecting the relationship between rate constants and dosage of TiO2, two possible kinetics were proposed in this study. Contrasted to the abundant experimental data, a reasonable kinetics was obtained for the estimation of phenol concentration effluent during continuous flow of raw wastewater, especially when the TiO2 dosage was less than 0.5g L(-1). The model obtained from these experiments could employed for the calculation of rate constants at different TiO2 dosage and the necessary dosage of catalyst when a discharge standard was designed.     

小型湖泊应用于地表水源热泵时的热承载能力分析

分析了小型湖泊应用于地表水源热泵时的两种热承载能力计算方法——水面温度法和均匀混合法,并采用其计算了杭州小型湖泊应用于地表水源热泵时的热承载能力。计算结果表明：水面温度法较客观地反映了实际的排水混合及水温恢复过程,可信度更高。用水面温度法对7个代表性城市小型湖泊热承载能力进行分析的结果表明：夏季热承载能力在23-4—29．5W／m2之间,冬季热承载能力在31．6～45．7W／m2之间;设计这类系统的关键在于满足夏季热承载能力的约束。     

自动化技术在青山湖泵站工程中的应用

通过介绍青山湖电排站综合自动化系统,阐述了泵站采用监控自动化技术后,提高了泵站运行的安全性和可靠性,以及运行管理水平.     

国产200MW机组给水温度低的原因分析及处理

给水温度是火力发电厂中一项重要的经济指标,它的高低直接影响煤耗率,并最终表现在火电厂的供电成本上。通过对高压加热器、低压加热器及管道、阀门结构、运行特性和保温情况的分析,找出了影响给水温度的因素,确定了提高给水温度的措施,通过不断完善相关措施可进一步提高机组运行的经济效益。     

Path planning in complex 3D environments using a probabilistic roadmap method

This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method （PRM） is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A＊ algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.     

Planar Segment Based Three‐dimensional Point Cloud Registration in Outdoor Environments

We present an odometry‐free three‐dimensional (3D) point cloud registration strategy for outdoor environments based on area attributed planar patches. The approach is split into three steps. The first step is to segment each point cloud into planar segments, utilizing a cached‐octree region growing algorithm, which does not require the 2.5D image‐like structure of organized point clouds. The second step is to calculate the area of each segment based on small local faces inspired by the idea of surface integrals. The third step is to find segment correspondences between overlapping point clouds using a search algorithm, and compute the transformation from determined correspondences. The transformation is searched globally so as to maximize a spherical correlation‐like metric by enumerating solutions derived from potential segment correspondences. The novelty of this step is that only the area and plane parameters of each segment are employed, and no prior pose estimation from other sensors is required. Four datasets have been used to evaluate the proposed approach, three of which are publicly available and one that stems from our custom‐built platform. Based on these datasets, the following evaluations have been done: segmentation speed benchmarking, segment area calculation accuracy and speed benchmarking, processing data acquired by scanners with different fields of view, comparison with the iterative closest point algorithm, robustness with respect to occlusions and partial observations, and registration accuracy compared to ground truth. Experimental results confirm that the approach offers an alternative to state‐of‐the‐art algorithms in plane‐rich environments.