Dye and its removal from aqueous solution by adsorption: A review

In this review article the authors presented up to-date development on the application of adsorption in the removal of dyes from aqueous solution. This review article provides extensive literature information about dyes, its classification and toxicity, various treatment methods, and dye adsorption characteristics by various adsorbents. One of the objectives of this review article is to organise the scattered available information on various aspects on a wide range of potentially effective adsorbents in the removal of dyes. Therefore, an extensive list of various adsorbents such as natural materials, waste materials from industry, agricultural by-products, and biomass based activated carbon in the removal of various dyes has been compiled here. Dye bearing waste treatment by adsorption using low cost alternative adsorbent is a demanding area as it has double benefits i.e. water treatment and waste management. Further, activated carbon from biomass has the advantage of offering an effected low cost replacement for non-renewable coal based granular activated carbon provided that they have similar or better adsorption on efficiency. The effectiveness of various adsorbents under different physico-chemical process parameters and their comparative adsorption capacity towards dye adsorption has also been presented. This review paper also includes the affective adsorption factors of dye such as solution pH, initial dye concentration, adsorbent dosage, and temperature. The applicability of various adsorption kinetic models and isotherm models for dye removal by wide range of adsorbents is also reported here. Conclusions have been drawn from the literature reviewed and few suggestions for future research are proposed.     

基于卡尔曼滤波的压缩感知弱匹配去噪重构

现有的贪婪迭代类压缩感知重构算法均基于最小二乘对信号进行波形估计,未考虑到可能将量测噪声引入信号估计的情况.针对以上不足,提出了一种基于线性Kalman滤波的压缩感知弱匹配去噪重构算法.该算法不需已知稀疏度先验,通过引入Kalman滤波,在最小均方误差准则下,每次迭代都获得最佳信号估计;并以弱匹配的方式同时筛选出有效的原子,并剔除冗余原子进而重构原信号.新算法继承了现有贪婪迭代类算法的有效性,同时避免了因噪声干扰或稀疏度未知导致的重构失败.理论分析和实验表明,新算法在同等条件下,重构性能优于现有典型贪婪迭代类算法,且其运算时间低于BPDN算法和同类的KFCS算法.     

改进的Camshift与Kalman融合的目标跟踪算法

Camshift算法主要利用物体的颜色信息进行跟踪,在复杂背景条件下容易造成目标的跟丢,且在目标被遮挡时,也容易造成跟踪失效。本文提出了一种改进的Camshift目标跟踪算法。首先将目标图像的HSV模型的三个分量进行加权建立一种新的目标颜色模型,然后由对整帧图像计算反向投影改为比搜索窗口稍大的区域计算反向投影,减少了相似背景的干扰。同时为了解决遮挡问题,结合了Kalman滤波器,有效地预测了目标的位置。实验表明,本算法能够避免背景颜色干扰和解决遮挡问题,实现了对运动目标准确跟踪。     

自适应滤波技术在扩频通信系统抗窄带干扰中的应用

自适应滤波技术在扩频通信窄带干扰抑制的应用中,需要一种快速收敛的自适应算法以便能跟踪快速变化的干扰信号。文章提出将基于LSL自适应算法的格型滤波器应用于直接序列扩频通信系统中。仿真结果表明,LSL自适应算法在线性预测中具有快速收敛特性,并且在收敛过程中具有数值稳定性,从而显著改善了系统的抗窄带干扰能力。     

基于权重一致性优化的实时Marginalized粒子滤波算法

针对Marginalized粒子滤波中随机量测噪声对于非线性状态估计精度的不利影响以及线性状态估计中计算量较大问题,提出了一种基于权重一致性优化的实时Marginalized粒子滤波算法.首先,结合量测系统建模中先验信息的提取和利用,通过粒子权重间一致性距离和一致性矩阵的构建,提出了量测提升策略下权重的一致性优化方法,以改善粒子滤波在非线性状态估计中的滤波精度.其次,通过对Marginalized粒子滤波实现中时间更新和量测更新环节的结构优化,给出了实时Marginalized粒子滤波,以降低蒙特卡罗仿真实现下卡尔曼滤波在状态线性估计中的计算复杂度.最后,在两者的动态结合基础上给出了新算法具体实现步骤.利用基于单站雷达目标跟踪仿真场景,分析了算法性能.理论分析和仿真实验结果验证了算法的可行性和有效性.     

Adaptive depth truncation filter for MVC based compressed depth image

In multiview video plus depth (MVD) format, virtual views are generated from decoded texture videos with corresponding decoded depth images through depth image based rendering (DIBR). 3DV-ATM is a reference model for the H.264/AVC based multiview video coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding based nature of H.264/AVC in 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized virtual views. This paper presents a low complexity adaptive depth truncation filter to recover the sharp object boundaries of the depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results demonstrate that the sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25 dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views.     

穿戴式生理检测设备电源设计

介绍了三种典型的稳压电源,结合穿戴式生理检测设备电源管理的特点,分析了电路低功耗设计和电源保护的关键技术,提出了一种基于低压差线性稳压电源MAX8881、无线充电接收器BQ51013和自恢复保险丝的电源设计实例。     

反射式离轴数字全息再现像中的噪声抑制

为了抑制反射式离轴数字全息再现像中的零级像和散斑噪声对再现像的影响,利用高斯核函数在空域对数字全息图进行低通滤波,再用原数字全息图减去滤波后的低频信息来抑制零级像,采用非局部均值滤波来抑制散斑噪声。实验结果表明空域高斯核函数处理法能有效地抑制零级像,非局部均值滤波可以抑制散斑噪声但对部分细节的保持能力不强,改进后的非局部均值滤波在抑制散斑噪声的同时能很好地保护细节信息,提高了离轴数字全息再现像的质量。     

星敏感器高阶畸变的观星标定模型

由于恒星具有很高的姿态精度,使得观星标定成为星敏感器相机参数标定中不可缺少的一种方法.针对高阶非线性畸变情况下的星敏感器相机参数标定问题进行研究,基于星间距的不变性建立了一个两步标定模型.设计了一个紧致的递归均值滤波器来进行参数估计,该滤波器可以在不显著增加计算量的情况下提高参数估计的精度.实验结果表明,相比已有方法,所提出的方法能够实现更高精度的星敏感器相机标定.