Improved non-maximum suppression for object detection using harmony search algorithm

Non-maximum suppression (NMS) plays a key role in many modern object detectors. It is responsible to remove detection boxes that cover the same object. NMS greedily selects the detection box with maximum score; other detection boxes are suppressed when the degree of overlap between these detection boxes and the selected box exceeds a predefined threshold. Such a strategy easily retain some false positives, and it limits the ability of NMS to perceive nearby objects in cluttered scenes. This paper proposes an effective method combining harmony search algorithm and NMS to alleviate this problem. This method regards the task of NMS as a combination optimization problem. It seeks final detection boxes under the guidance of an objective function. NMS is applied to each harmony to remove imprecise detection boxes, and the remaining boxes are used to calculate the fitness value. The remaining detection boxes in a harmony with highest fitness value are chosen as the final detection results. The standard Pattern Analysis, Statistical Modeling and Computational Learning Visual Object Classes dataset and the Microsoft Common Objects in Context dataset are used in all of the experiments. The proposed method is applied to two popular detection networks, namely Faster Region-based Convolutional Neural Networks and Region-based Fully Convolutional Networks. The experimental results show that the proposed method improves the average precision of these two detection networks. Moreover, the location performance and average recall of these two detectors are also improved.     

Behavior of phase transformation of Baotou mixed rare earth concentrate during oxidation roasting

Based on the new process named “Combination Method” for metallurgy and separation of Baotou mixed rare earth concentrate (BMREC), the aim of this paper is to clearly elucidate the phase change behavior of BMREC without additives during oxidative roasting at 450–800 °C. The results indicate that the bastnaesite in BMREC is decomposed at 450–550 °C, the weight loss is about 10.3 wt%, and the activation energy (E) is 144 kJ/mol. The bastnaesite in BMREC is decomposed into rare earth fluoride, rare earth oxides (La₂O₃, Ce₇O₁₂, Pr₆O₁₁ and Nd₂O₃), and CO₂, particularly, with the increase of roasting temperature, bastnaesite in BMREC is more completely decomposed into LaF₃, which causes a decrease in leaching rate of La during the HCl leaching process. Additionally, the maximum cerium oxidation efficiency reaches about 60 wt% when the roasting temperature is equal to or above 500 °C, and the oxidation reaction rate of cerium increases with the increasing roasting temperature.     

特征组合、工艺排序决策法研究

提取零件的输入特征信息，通过特征组合成组合特征单元，对组合特征单元进行编号，并根据工艺规则，工艺数据库和资源库对组合特征单元进一步进行分解成可作为加工工序的特征组合元。根据工艺规则，资源库，工艺数据库，对组合特征单元进行排序，即进行工艺决策。     

平面运动链型综合组合法开链规划的一种改进方法

提出了平面闭式运动链型综合组合法中开链规划的改进方法。为获得给定自由度和构件数的全部独立的运动链结构类型,按照构件数递增的顺序,将开链与相应的闭链进行组合。在开链规划中,如果必要仅需对单杆开链增设铰链,然后依次选定二杆开链、三杆开链等,直到自由度加一的两副杆串联开链,开链规划即可停止。指出了上述方法在型综合应用中的正确性,并从理论上进行了探讨。     

An optimized combination prediction model for concrete dam deformation considering quantitative evaluation and hysteresis correction

Certain degree of deformation is natural while dam operates and evolves. Due to the impact of internal and external environment, dam deformation is highly nonlinear by nature. For dam safety, it is of great significance to analyze timely deformation monitoring data and be able to predict reliably deformation. A comprehensive review of existing deformation prediction models reveals two issues that deserves further attention: (1) each environmental influencing factor contributes differently to deformation, and (2) deformation lags behind environmental factors (e.g., water level and air temperature). In response, this study presents a combination deformation prediction model considering both quantitative evaluation of influencing factors and hysteresis correction in order to further improve estimation accuracy. In this study, the complex relationship in deformation prediction is effectively captured through support vector machine (SVM) modeling. Furthermore, a modified fruit fly optimization algorithm (MFOA) is presented for SVM hyper-parameter optimization. Also, a synthetic evaluation method and a hysteresis quantification algorithm are introduced to further enhance the MFOA-SVM-based model in regards to contribution quantification and phase correction respectively. The accuracy and validity of the proposed model is evaluated in a concrete dam case, where its performance is compared with other existing models. The simulated results indicated that the proposed nonlinear MFOA-SVM model considering both quantitative evaluation and hysteresis correction, abbreviated as SEV-MFOA-SVM, is more accurate and robust than conventional models. This novel model also provides an alternative method for predicting and analyzing dam deformation and evolution behavior of other similar hydraulic structures.     

基于Rényi散度最大化的多特征闭环检测

相比单特征,多图像特征的组合提供更多的场景判别信息,可以提高检测精度,但需要设计合适的组合准则.文中提出多特征组合的加权方法,把特征组合的闭环检测精度表示为正确匹配和错误匹配的图像对在特征空间中距离分布的Rényi散度,最优特征组合为最大化Rényi散度.分析验证Rényi散度的参数与对应最优特征组合的闭环检测性能之间的关系.实验表明,文中方法可以提高闭环检测精度.当Rényi散度的参数取0.75~1 时,最优特征组合性能最佳.     

压力管道组合管件模块化设计软件开发

阐述了以VB 6.0为开发环境、运用ActiveX Autom ation提供的接口进行AutoCAD的压力管道组合管件专用软件的二次开发过程,介绍了该专用软件的设计流程及关键步骤,并给出了部分程序代码和例证,应用效果良好。     

建设校内生产性实训基地的校企组合模式的比较研究

校内生产性实训基地是高职院校开展技能型、实用性人才培养的重要教学基础资源。建设校内生产性实训基地,必然要实施产学研合作的校企组合模式。校企组合的方式与程度不同,形成了“企业主导型”、“企业管理型”和“校企融合型”等模式。本文通过讨论三个典型案例,对三种主要的校企组合模式进行分类比较研究。     

旅游管理专业产学合作模式构建研究

近年来,旅游业发生了巨大的变化。一方面,为旅游专业人才提供了广阔的发展空间,另一方面也对旅游专业人才培养提出了更高的要求。本文从高等院校的基本职能和理论依据出发,论证了高等院校采用产学相结合发展的必然性,并提出相应的对策措施。     

RESEARCH ON COMBINATION AND PLANNING OF PROCESSING UNITS UNDER CIMS CONDITION

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