基于视觉颜色感知——光学相似的图像去雾方法

针对雾霾环境影响致使户外获取的图像质量严重下降问题，提出了一种基于视觉颜色感知—光学相似的图像去雾方法。充分利用人眼感知颜色的视觉机理，结合图像的相似性原理，构造了光学相似度函数，建立了新的基于视觉颜色感知—光学相似的图像去雾模型并设计相关算法，进而进行仿真验证。仿真实验结果表明，提出的方法在对有雾图像清晰化处理过程中效果明显，并与现有的图像去雾方法在主观视觉和客观量化方面进行图像去雾效果对比，进一步表明提出的方法在清晰化含雾图像处理中取得了较好的效果。     

塔里木盆地中秋1凝析气藏成藏条件及演化过程

2018年12月,塔里木盆地秋里塔格构造带天然气勘探取得重大突破,中秋1井在下白垩统巴什基奇克组测试获高产工业气流,发现了该构造带迄今为止最大的整装凝析气藏。为了给该构造带下一步油气勘探部署提供依据,在充分利用前人研究成果的基础上,基于岩心、薄片、测井及地球化学分析资料,明确了中秋1大型凝析气藏的油气藏特征和气藏类型,分析了该气藏天然气成藏条件并推演其演化过程。研究结果表明:①中秋1大型气藏属于低含凝析油凝析气藏,天然气为煤成气,主要来自区内侏罗系腐殖型煤系烃源岩;②该构造带能够形成大型油气藏的有利地质条件是三叠系和侏罗系发育的两套巨厚高演化烃源岩、白垩系发育的大型辫状河三角洲规模有效砂岩储层、喜马拉雅晚期以来的构造活动形成的大规模楔状叠瓦构造圈闭、古近系和新近系巨厚膏盐岩形成的优越保存条件,以及油气生成与圈闭形成的良好时空匹配;③该气藏具有先油后气、晚期快速气侵聚集成藏的成藏模式,总体上是一个"早期聚油、晚期气侵、改造调整、快速成藏"的成藏过程。结论认为,该构造带油气成藏条件优越,具有广阔的油气勘探前景。     

柴达木盆地三湖坳陷横波勘探中的低幅异常消除技术

近年来,在柴达木盆地三湖坳陷开展了横波地震勘探,但是由于该区低幅度构造发育,横波静校正引起的"低幅"异常与上述低幅度构造相互混杂,难以区分。为此,针对该区横波表层调查难以控制表层横波速度模型的变化、横波近偏移距初至污染严重、横波折射层发育导致高速界面难以确定等问题,首先采用曲线拟合技术预测污染区横波初至时间确保初至完整性,然后采用面波模型与多层折射分层联合约束反演横波表层速度,最后通过基于速度谱分析的层位匹配建模技术确定合理的横波速度界面,形成了横波表层"低幅"异常消除技术,并进行了现场应用及效果评价。研究结果表明:①曲线拟合技术可以弥补近道污染区横波初至空白,保证层析反演模型的完整性;②基于瑞雷波的频散特性反演建模可以为确定该区浅层横波速度提供可靠的资料,提高浅层模型精度;③面波模型与多层折射分层联合约束反演能够更准确的反演该区表层横波速度场,较好地建立横波速度模型,消除横波剖面上"低幅"异常现象。结论认为,所形成的横波地震勘探低幅异常消除技术消除了横波静校正引起的"低幅"异常现象,提高了横波地震资料的成像品质。     

废脱硫剂在铁矿烧结中的应用

钢厂煤气脱硫工序排放的废脱硫剂是一种难以利用的有害固体废弃物，含一定量的铁及较高的钙和硫等元素。对废脱硫剂配入铁矿粉中进行了烧结杯的试验研究，结果表明，当废脱硫剂配比超过01%后，随着废脱硫剂配比的升高，烧结矿转鼓强度下降，利用系数下降，烧结烟气中SO2与NOx浓度增加，烧结矿的还原度有所下降，但烧结矿的低温还原粉化性能有所改善。烧结矿的矿相研究发现，废脱硫剂配比偏大时，磁铁矿体积分数增大，铁酸钙体积分数减少，并由针状结构向柱状、板状演变，烧结矿的气孔率上升。主要原因在于其粒度偏粗，含硫高，不利于成矿。当废脱硫剂粒度为-63mm及其配比控制在01%时，烧结矿的产量和质量有所改善，烟气中SO2、NOx较基准试验变化不大。工业试验表明，在烧结混匀矿中配入废脱硫剂配比小于012%时，烧结矿产量和质量没有明显变化，烧结烟气脱硫脱硝效果也没有受到影响。废脱硫剂掺入铁矿中进行烧结是一种资源化利用的有效方法，不仅解决了有害固体废弃物对环境的影响，而且使二次资源得到综合利用。     

Robust orientation control of multi‐DOF cell based on uncertainty and disturbance estimation

Multiple degrees‐of‐freedom (multi‐DOF) cell orientation control is a vital important technique involved in single cell surgery applications. Currently, few studies have been performed toward automation of multi‐DOF cell orientation control using robotically controlled optical tweezers. In this paper, a robust control framework is developed to perform multi‐DOF cell rotational control with consideration of model uncertainties and external disturbances. Both simulation and experimental studies are presented to illustrate the performance of the proposed control strategy. The main contributions of this work lie in that this is the first time to develop a unified framework to achieve multi‐DOF cell orientation control without the need for accurate dynamic model parameters and/or any knowledge about uncertainty characteristic, which greatly enhances the robustness of the overall system.     

New version of continuous–discrete cubature Kalman filtering for nonlinear continuous–discrete systems

For nonlinear continuous–discrete systems, this paper elaborates a new accurate implementation of continuous–discrete cubature Kalman filter (CD-CKF). As the main contribution of this work, the new Kalman prediction stage begins by integrating the nonlinear continuous model for all the cubature sample vectors; the prior estimate state and covariance prediction are based on the weighted statistics of these integrated cubature sample vectors and the Gauss–Legendre approximation scheme. The new square root form CD-CKF is also derived and accurately implemented by combining with the modified variable stepsize NIRK. As the advantages of proposed approach, the complicated and error-prone processes of solving covariance differential equation or calculating derivatives are avoided, while the positive semi-definiteness of prior error covariance are numerically guaranteed. Simulations of traffic control scenarios further confirm the new approach’s superior filtering performance in both reliability and accuracy.     

基于变异算子和邻域值自适应的MOEA/D算法

基于分解的多目标进化算法（MOEA/D）在解决多目标问题时，具有简单有效的特点。但多数MOEA/D采用固定的控制参数，导致全局搜索能力差，难以平衡收敛性和多样性。针对以上问题提出一种基于变异算子和邻域值自适应的多目标优化算法。该算法根据种群中个体适应度值的分散或集中程度进行判断，并据此对变异算子进行自适应的调节，从而增强算法的全局搜索能力；根据进化所处的阶段以及个体适应度值的集中程度，自适应地调节邻域值大小，保证每个个体在不同的进化代数都有一个邻域值大小；在子问题邻域中，统计子问题对应个体的被支配数，通过判断被支配数是否超过设定的上限，来决定是否将Pareto支配关系也作为邻域内判断个体好坏的准则之一。将提出的算法与传统的MOEA/D在标准测试问题上进行对比。实验结果表明，提出的算法求得的解集具有更好的收敛性和多样性，在求解性能上具有一定的优势。     

采用信道估计法的基站VSWR实时检测

为解决无线基站宽带工作频带内电压驻波比(Voltage Standing Wave Ratio,VSWR)的实时测量，提出了一种采用信道估计法的测量方案。该方案实现简单，在基带处理单元高速率位置发送数据，依次抓取射频通道反馈和反射数据，分别求取信道响应序列，结合工厂装备测试数据，计算驻波反射系数和反射点位置。发送信号采用宽带正交频分复用信号，能检测到工作频段内任何频点处的驻波异常。有用信号前加循环前缀，并引入峰值抵消核，能正确检测到多个反射点驻波。仿真结果表明，该方案驻波测量精度和单回波点位置精度达到预期，多回波点测量能抓准外部主要故障点，在基站VSWR实时测量中具有良好的应用前景。     

Individual-based multi-objective optimal structured treatment interruption for HIV infection

In this paper, based on the measurable quantities from an individual patient that has infection to human immunodeficiency virus (HIV) and his/her condition is near to acquired immune deficiency syndrome (AIDS), individual-based multi-objective optimal treatments have been proposed. Firstly, the most effective parameters of the patient in computing Long-term non-progressor (LTNP) equilibrium are derived using global sensitivity analysis (GSA). To accomplish GSA effectively, Latin hypercube sampling (LHS) and partial rank correlation coefficients (PRCC) are utilized to rank each of the parameters based on each state of the 5-dimensional model. Then, these results are used by Dempster–Shafer (D–S) evidence theory (DSET) to rank the most effective parameters comprehensively. Now, these effective identified parameters are estimated using extended Kalman filter (EKF), which its covariance matrices are optimized based on particle swarm optimization (PSO) algorithm. Thus, the proposed methodology gives a calibrated model corresponding to the individual patient. Based on this calibrated model, the LTNP equilibrium related to the individual patient is derived. Using the derived individual-based LTNP equilibrium optimal structured treatment interruption (STI) strategies are extracted by defining suitable multi-objective optimization problem and solving it through using non-dominated sorting genetic algorithm-II (NSGA-II). The results demonstrate that the proposed optimal treatments are able to effectively reach LTNP equilibrium with using the minimum and maximum drug usage of 3.6% and 35.1% of full drug usage treatment. Meanwhile, the different optimal treatments give the decision-makers enough flexibility to choose the suitable treatment based on existing facilities and necessities.     

Field‐based robotic phenotyping of sorghum plant architecture using stereo vision

Sorghum (Sorghum bicolor) is known as a major feedstock for biofuel production. To improve its biomass yield through genetic research, manually measuring yield component traits (e.g. plant height, stem diameter, leaf angle, leaf area, leaf number, and panicle size) in the field is the current best practice. However, such laborious and time‐consuming tasks have become a bottleneck limiting experiment scale and data acquisition frequency. This paper presents a high‐throughput field‐based robotic phenotyping system which performed side‐view stereo imaging for dense sorghum plants with a wide range of plant heights throughout the growing season. Our study demonstrated the suitability of stereo vision for field‐based three‐dimensional plant phenotyping when recent advances in stereo matching algorithms were incorporated. A robust data processing pipeline was developed to quantify the variations or morphological traits in plant architecture, which included plot‐based plant height, plot‐based plant width, convex hull volume, plant surface area, and stem diameter (semiautomated). These image‐derived measurements were highly repeatable and showed high correlations with the in‐field manual measurements. Meanwhile, manually collecting the same traits required a large amount of manpower and time compared to the robotic system. The results demonstrated that the proposed system could be a promising tool for large‐scale field‐based high‐throughput plant phenotyping of bioenergy crops.