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Computer Modeling in Engineering & Sciences 2022年第3期130卷 1853-1882页

作者： Zhen Xu Shuai Guo Tao Song Yuwen Li Lingdong Zeng Shanghai Key Laboratory of IntelligentManufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444China

The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability.localization of mobile robot is increasingly important for the printing of buildings in the construction scene.Although many available studies on the localization have been conducted,only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes.To realize the accurate localization of mobile robot in designated stations,we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map.Then,the performances of localization for mobile robot based on the original and optimized map are compared and evaluated.Finally,experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21%compared to that of the original map.

关键词： Large-scale construction artificial landmark map localization mobile robot non-linear optimization

人机交互量子系统非平衡稳态中的自发对称破缺和局域化

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科学通报:英文版 2023年第18期68卷 2010-2016,M0003页

作者：吴烁杭蔡子 Wilczek Quantum Center and Key Laboratory of Artificial Structures and Quantum Control School of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China Shanghai Research Center for Quantum Sciences Shanghai 201315China

物理系统的时间演化一般用微分方程来描述,而数值求解微分方程往往需要将时空分立化,将微分方程变换成为差分方程,在这一分立化的过程往往伴随着累积误差的产生,进而降低模拟精度,但是,在量子电路计算系统中,“演化时间”表示量子线路... 详细信息

物理系统的时间演化一般用微分方程来描述,而数值求解微分方程往往需要将时空分立化,将微分方程变换成为差分方程,在这一分立化的过程往往伴随着累积误差的产生,进而降低模拟精度,但是,在量子电路计算系统中,“演化时间”表示量子线路的层数,只能取分立的数值。因此,在这类系统中,由时间分立化带来的累积误差不再是数值误差,而会带来物理上可观测的效果。本文提出了一种由反馈和时间分立化导致的新的量子动力学:人机交互量子动力学,这一动力学的特点是在保持了演化的么正性的前提下,系统能量不断耗散,最终达到一种非平衡稳态,这一非平衡稳态中可能涌现出超越平衡态框架的新的物理现象和物理机制,例如发生在零维系统的自发对称破缺,以及一种不同与安德森局域化的新的量子局域化机制。

关键词： Interactive quantum dynamics Quantum feedback Dissipation localization

Interplay between topology and localization on superconducting circuits

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Chinese Physics B 2024年第6期33卷 240-246页

作者：关欣霍炳燕陈刚 Department of Materials and Chemical Engineering Taiyuan UniversityTaiyuan 030032China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Laser SpectroscopyShanxi UniversityTaiyuan 030006China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China School of Physics Zhengzhou UniversityZhengzhou 450001China

Topological insulators occupy a prominent position in the realm of condensed matter physics. Nevertheless, the presence of strong disorder has the potential to disrupt the integrity of topological states, leading to the localization of all states.This study delves into the intricate interplay between topology and localization within the one-dimensional Su–Schrieffer–Heeger(SSH) model, which incorporates controllable off-diagonal quasi-periodic modulations on superconducting circuits.Through the application of external alternating current(ac) magnetic fluxes, each transmon undergoes controlled driving,enabling independent tuning of all coupling strengths. Within a framework of this model, we construct comprehensive phase diagrams delineating regions characterized by extended topologically nontrivial states, critical localization, and coexisting topological and critical localization phases. The paper also addresses the dynamics of qubit excitations, elucidating distinct quantum state transfers resulting from the intricate interplay between topology and localization. Additionally, we propose a method for detecting diverse quantum phases utilizing existing experimental setups.

关键词： topology localization superconducting circuits

Acquiring Weak Annotations for Tumor localization in Temporal and Volumetric Data

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Machine Intelligence Research 2024年第2期21卷 318-330页

作者： Yu-Cheng Chou Bowen Li Deng-Ping Fan Alan Yuille Zongwei Zhou Department of Computer Science Johns Hopkins UniversityBaltimore 21218USA Computer Vision Lab ETH ZurichZurich 8001Switzerland

Creating large-scale and well-annotated datasets to train AI algorithms is crucial for automated tumor detection and localization.However,with limited resources,it is challenging to determine the best type of annotations when annotating massive amounts of unlabeled data.To address this issue,we focus on polyps in colonoscopy videos and pancreatic tumors in abdominal CT scans;Both applications require significant effort and time for pixel-wise annotation due to the high dimensional nature of the data,involving either temporary or spatial dimensions.In this paper,we develop a new annotation strategy,termed Drag&Drop,which simplifies the annotation process to drag and drop.This annotation strategy is more efficient,particularly for temporal and volumetric imaging,than other types of weak annotations,such as per-pixel,bounding boxes,scribbles,ellipses and points.Furthermore,to exploit our Drag&Drop annotations,we develop a novel weakly supervised learning method based on the watershed algorithm.Experimental results show that our method achieves better detection and localization performance than alternative weak annotations and,more importantly,achieves similar performance to that trained on detailed per-pixel annotations.Interestingly,we find that,with limited resources,allocating weak annotations from a diverse patient population can foster models more robust to unseen images than allocating per-pixel annotations for a small set of images.In summary,this research proposes an efficient annotation strategy for tumor detection and localization that is less accurate than per-pixel annotations but useful for creating large-scale datasets for screening tumors in various medical modalities.

关键词： Weak annotation detection localization segmentation colonoscopy abdomen

localization optoacoustic tomography

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Light(Science & Applications) 2018年第1期7卷 1058-1062页

作者： X Luís Dean-Ben Daniel Razansky Institute for Biological and Medical Imaging Helmholtz Center MunichNeuherberg 85764Germany School of Medicine and School of Bioengineering Technical University of MunichMunich 81675Germany

localization-based imaging has revolutionized fluorescence optical microscopy and has also enabled unprecedented ultrasound images of microvascular structures in deep tissues.Herein,we introduce a new concept of localization optoacoustic tomography(LOT)that employs rapid sequential acquisition of three-dimensional optoacoustic images from flowing absorbing particles.We show that the new method enables breaking through the spatial resolution barrier of acoustic diffraction while further enhancing the visibility of structures under limited-view tomographic conditions.Given the intrinsic sensitivity of optoacoustics to multiple hemodynamic and oxygenation parameters,LOT may enable a new level of performance in studying functional and anatomical alterations of microcirculation.

关键词： acoustic diffraction limited-view effects localization optoacoustic imaging photoacoustic imaging super-resolution

Regulating the localization of Intumescent Flame Retardant for Improving the Flame Retardancy of Ethylene-vinyl Acetate Copolymer Using Polyamide 6 as a Charring Agent

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Journal of Wuhan University of Technology(Materials Science) 2023年第3期38卷 701-711页

作者：高喜平 ZHAO Pan YAO Dahu 陆昶 YUE Ruiheng SHENG Qi School of Chemical Engineering&Pharmaceutics Henan University of Science and TechnologyLuoyang 471023China

Polyamide 6 (PA6) was employed as a charring agent of intumescent flame retardant (IFR) to improve the flame retardancy of ethylene-vinyl acetate copolymer (EVA). Different processing procedures were used to regulate the localization of IFR in the EVA matrix. localizations in which IFR was dispersed in the PA6phase or in the EVA phase were prepared. The effect of the localization of IFR on the flame retardancy of EVA was investigated. The limited oxygen index (LOI), vertical burning (UL 94) and cone calorimeter test (CCT)showed that the localization of IFR in the EVA matrix exhibited a remarkable influence on the flame retardancy.Compared with EVA/IFR, a weak improvement in the flame retardancy was observed in the EVA/PA6/IFR blend withthe localization of IFR in the PA6 phase. When IFR was regulated from the PA6 phase to the EVA matrix,a remarkable increase in the flame retardancy was exhibited. The LOI was increased from 27.8%to 32.7%, and the UL 94 vertical rating was increased from V-2 to V-0. Moreover, an approximately 41.36%decrease in the peak heat release rate was exhibited. A continuous and compact intumescent charring layer that formed in the blends with the localization of IFR in the EVA matrix should be responsible for its excellent flame retardancy.

关键词： intumescent flame retardant charring agent localization polyamide 6 ethylene vinyl acetate

Visual-feature-assisted mobile robot localization in a long corridor environment

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Frontiers of Information Technology & Electronic Engineering 2023年第6期24卷 876-889页

作者： Gengyu GE Yi ZHANG Wei WANG Lihe HU Yang WANG Qin JIANG School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China School of Advanced Manufacturing Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China School of Information Engineering Zunyi Normal UniversityZunyi 563006China

localization plays a vital role in the mobile robot navigation system and is a fundamental capability for autonomous movement.In an indoor environment,the current mainstream localization scheme uses two-dimensional(2D)laser light detection and ranging(LiDAR)to build an occupancy grid map with simultaneous localization and mapping(SLAM)technology;it then locates the robot based on the known grid map.However,such solutions work effectively only in those areas with salient geometrical features.For areas with repeated,symmetrical,or similar structures,such as a long corridor,the conventional particle filtering method will fail.To solve this crucial problem,this paper presents a novel coarse-to-fine paradigm that uses visual features to assist mobile robot localization in a long corridor.First,the mobile robot is remote-controlled to move from the starting position to the end along a middle line.In the moving process,a grid map is built using the laser-based SLAM method.At the same time,a visual map consisting of special images which are keyframes is created according to a keyframe selection strategy.The keyframes are associated with the robot’s poses through timestamps.Second,a moving strategy is proposed,based on the extracted range features of the laser scans,to decide on an initial rough position.This is vital for the mobile robot because it gives instructions on where the robot needs to move to adjust its pose.Third,the mobile robot captures images in a proper perspective according to the moving strategy and matches them with the image map to achieve a coarse localization.Finally,an improved particle filtering method is presented to achieve fine localization.Experimental results show that our method is effective and robust for global localization.The localization success rate reaches 98.8%while the average moving distance is only 0.31 m.In addition,the method works well when the mobile robot is kidnapped to another position in the corridor.

关键词： Mobile robot localization Simultaneous localization and mapping(SLAM) Corridor environment Particle filter Visual features

Jointly beam stealing attackers detection and localization without training:an image processing viewpoint

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Frontiers of Computer Science 2023年第3期17卷 145-160页

作者： Yaoqi YANG Xianglin WEI Renhui XU Weizheng WANG Laixian PENG Yangang WANG College of Communication Engineer Army Engineering University of PLANanjing 210000China The 63rd Research Institute National University of Defense TechnologyNanjing 210007China Department of Computer Science City University of Hong KongHong Kong 999077China

Recently revealed beam stealing attacks could greatly threaten the security and privacy of IEEE 802.11ad communications.The premise to restore normal network service is detecting and locating beam stealing attackers without their cooperation.Current consistency-based methods are only valid for one single attacker and are parametersensitive.From the viewpoint of image processing,this paper proposes an algorithm to jointly detect and locate multiple beam stealing attackers based on RSSI(Received Signal Strength Indicator)map without the training process involved in deep learning-based solutions.Firstly,an RSSI map is constructed based on interpolating the raw RSSI data for enabling high-resolution localization while reducing monitoring cost.Secondly,three image processing steps,including edge detection and segmentation,are conducted on the constructed RSSI map to detect and locate multiple attackers without any prior knowledge about the attackers.To evaluate our proposal’s performance,a series of experiments are conducted based on the collected data.Experimental results have shown that in typical parameter settings,our algorithm’s positioning error does not exceed 0.41 m with a detection rate no less than 91%.

关键词： beam-stealing attacks detection localization image processing

Three-dimensional localization of near-field and strictly noncircular sources using steering vector decomposition

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Frontiers of Information Technology & Electronic Engineering 2022年第4期23卷 644-652页

作者： Zheng LI Jinqing SHEN Xiaofei ZHANG College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing211106China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing211106China

The three-dimensional localization problem for noncircular sources in near-field with a centro-symmetric cross array is rarely studied.In this paper,we propose an algorithm with improved estimation performance.We decompose the multiple parameters of the steering vector in a specific order so that it can be converted into the products of several matrices,and each of the matrices includes only one parameter.On this basis,each parameter to be resolved can be estimated by performing a one-dimensional spatial spectral search.Although the computational complexity of the proposed algorithm is several times that of our previous algorithm,the estimation performance,including its error and resolution,with respect to the direction of arrival,is improved,and the range estimation performance can be maintained.The superiority of the proposed algorithm is verified by simulation results.

关键词： localization Centro-symmetric cross array Noncircular sources Near-field Steering vector decomposition

Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention localization

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Machine Intelligence Research 2022年第2期19卷 153-168页

作者： Wei-Chen Chen Xin-Yi Yu Lin-Lin Ou College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

Pedestrian attribute recognition in surveillance scenarios is still a challenging task due to the inaccurate localization of specific attributes. In this paper, we propose a novel view-attribute localization method based on attention(VALA), which utilizes view information to guide the recognition process to focus on specific attributes and attention mechanism to localize specific attribute-corresponding areas. Concretely, view information is leveraged by the view prediction branch to generate four view weights that represent the confidences for attributes from different views. View weights are then delivered back to compose specific view-attributes, which will participate and supervise deep feature extraction. In order to explore the spatial location of a view-attribute, regional attention is introduced to aggregate spatial information and encode inter-channel dependencies of the view feature. Subsequently, a fine attentive attribute-specific region is localized, and regional weights for the view-attribute from different spatial locations are gained by the regional attention. The final view-attribute recognition outcome is obtained by combining the view weights with the regional weights. Experiments on three wide datasets(richly annotated pedestrian(RAP), annotated pedestrian v2(RAPv2), and PA-100 K) demonstrate the effectiveness of our approach compared with state-of-the-art methods.

关键词： Pedestrian attribute recognition surveillance scenarios view-attribute attention mechanism localization