基于双层修正无迹卡尔曼的水下节点定位算法* .txt

摘要：针对水下无线传感网络中运动节点定位精度低的问题，提出了一种新的基于双层修正无迹卡尔曼的水下节点定位算法(DLMUKF)。该算法利用下层无迹卡尔曼滤波算法对节点状态进行预测，根据各信标节点的测距传播时延对预测的节点状态进行修正。运用上层无迹卡尔曼滤波算法对修正后的状态进行新的预测与修正。仿真实验中，DLMUKF算法的平均定位误差约为传统多边定位算法的15%，约为基于无迹卡尔曼滤波（UKF）定位算法的16%，受节点运动时间与速度的影响最小。通过实验证明DLMUKF算法能更充分利用实际距离值，可以有效减小运动节点的定位误差。 .txt     

Efficient atom localization via probe absorption in an inverted-Y atomic system

The behaviour of atom localization in an inverted-Y atomic system is theoretically investigated. For the atoms interacting with a weak probe field and several orthogonal standing-wave fields, their position information can be obtained by measuring the probe absorption. Compared with the traditional scheme, we couple the probe field to the transition between the middle and top levels. It is found that the probe absorption sensitively depends on the detuning and strength of the relevant light fields. Remarkably, the atom can be localized at a particular position in the standing-wave fields by coupling a microwave field to the transition between the two ground levels.     

Window Detection in Facades Using Heatmap Fusion

Journal of Computer Science and Technology - Window detection is a key component in many graphics and vision applications related to 3D city modeling and scene visualization. We present a novel...     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

Prelabeling Expansion Single-Molecule Localization Microscopy with Minimal Linkage Error

Expansion microscopy combined with single-molecule localization microscopy (ExSMLM) has a potential for approaching molecular resolution. However, ExSMLM faces multiple challenges such as loss of fluorophores and proteins during polymerization, digestion or denaturation, and an increase in linkage error arising from the distance between the fluorophore and the target molecule. Here, we introduce a trifunctional streptavidin to link the target, fluorophore and gel matrix via a biotinylizable peptide tag. The resultant ExSMLM images of vimentin filaments demonstrated high labeling efficiency and a minimal linkage error of ∼5 nm. Our ExSMLM provides a simple and practical means for fluorescence imaging with molecular resolution.     

Image-Based Lifelogging: User Emotion Perspective

Lifelog is a digital record of an individual’s daily life. It collects, records, and archives a large amount of unstructured data; therefore, techniques are required to organize and summarize those data for easy retrieval. Lifelogging has been utilized for diverse applications including healthcare, self-tracking, and entertainment, among others. With regard to the image-based lifelogging, even though most users prefer to present photos with facial expressions that allow us to infer their emotions, there have been few studies on lifelogging techniques that focus upon users’ emotions. In this paper, we develop a system that extracts users’ own photos from their smartphones and configures their lifelogs with a focus on their emotions. We design an emotion classifier based on convolutional neural networks (CNN) to predict the users’ emotions. To train the model, we create a new dataset by collecting facial images from the CelebFaces Attributes (CelebA) dataset and labeling their facial emotion expressions, and by integrating parts of the Radboud Faces Database (RaFD). Our dataset consists of 4,715 high-resolution images. We propose Representative Emotional Data Extraction Scheme (REDES) to select representative photos based on inferring users’ emotions from their facial expressions. In addition, we develop a system that allows users to easily configure diaries for a special day and summaize their lifelogs. Our experimental results show that our method is able to effectively incorporate emotions into lifelog, allowing an enriched experience.     

Radar‐based structural health monitoring of wind turbine blades: The case of damage localization

This short communication reports on a radar approach for structural health monitoring of wind turbine blades. Therefore, a bistatic frequency‐modulated continuous wave (FMCW) radar in the frequency range from 33.4 to 36.0 GHz has been developed and tested experimentally using a laboratory wind turbine demonstrator. A differential damage localization framework is presented here that exploits signal differences between measurements from the intact and the damaged structure for 3D imaging of the defect. We have achieved the localization of a 30‐mm cut in a glass fiber composite structure as well as the localization of a water pack at the backside of the specimen with a localization error of several centimeters.     

纸浆漂白用二氧化氯制备方法及国产化

纸浆漂白采用二氧化氯为漂剂具有得率高、白度高、漂白废水色度和毒性低的特点,是化学纸浆无元素氯(ECF)漂白技术的主流漂白剂。本文主要阐述了二氧化氯发展历程和制备方法,比较了甲醇法和综合法的二氧化氯生产工艺与成本,介绍了国内目前制浆漂白用二氧化氯制备工艺及应用情况。     

Damage detection in beams from modal and wavelet analysis using a stationary roving mass and noise estimation

This paper uses the Continuous Wavelet Transform Analysis on mode shapes for damage identification. The wavelet analysis is applied to the difference in the mode shapes between a healthy and a damaged state. The paper also includes a novel methodology for estimating the level of noise of the experimental mode shapes based on a standard Signal to Noise Ratio (SNR). The estimated SNRs are used for identifying and making emphasis on the less noisy data. Moreover, a mass attached to the structure is considered to enhance the sensitivity of the structure to damage. Modal analysis is performed for different positions of the mass along the beam. The results obtained for all the positions of the mass are combined so an averaging process is implicitly applied. The paper presents the results from an experimental test of a cantilever steel beam with different severity levels of damage at the same location. The results show that the use of the attached mass reduces the effect of noise and increases the sensitivity to damage. Little damage can be identified with the proposed methodology even using a small number of sensors and only the first five bending modes.     

准周期量子动力系统的数值求解

本文提出了研究准周期量子动力系统的计算方法.传统计算方法通常使用大的周期系统来近似计算准周期系统,这会产生丢番图逼近误差.我们的方法将准周期系统在高维周期结构中表示和计算,这样不仅可以避免丢番图逼近误差,而且可以将周期系统的高效算法,比如快速Fourier变换直接运用到新的算法中.我们将算法用于计算具有准周期势的线性薛定谔方程和准周期初值的非线性薛定谔方程.数值结果表明了算法的可靠性和高效性,并可以用于研究包含Anderson局域化、非线性光子准晶在内的准周期量子行为.