Design of a multiple bloom filter for distributed navigation routing

Unmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless sensors are often resource scarce and require a resource-saving design. In this paper, a multiple Bloom-filter scheme is proposed to compress a global routing table for a wireless sensor. It is used as a lookup table for routing a vehicle to any destination but requires significantly less memory space and search effort. An error-expectation-based design for a multiple Bloom filter is proposed as an improvement to the conventional false-positive-rate-based design. The new design is shown to provide an equal relative error expectation for all branched paths, which ensures a better network load balance and uses less memory space. The scheme is implemented in a project for wheelchair navigation using wireless camera motes. © 2013 IEEE

Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation

The study of universal approximation properties (UAP) for neural networks (NN) has a long history. When the network width is unlimited, only a single hidden layer is sufficient for UAP. In contrast, when the depth is unlimited, the width for UAP needs to be not less than the critical width $w^*_{\min}=\max(d_x,d_y)$, where $d_x$ and $d_y$ are the dimensions of the input and output, respectively. Recently, \cite{cai2022achieve} shows that a leaky-ReLU NN with this critical width can achieve UAP for $L^p$ functions on a compact domain $K$, \emph{i.e.,} the UAP for $L^p(K,\mathbb{R}^{d_y})$. This paper examines a uniform UAP for the function class $C(K,\mathbb{R}^{d_y})$ and gives the exact minimum width of the leaky-ReLU NN as $w_{\min}=\max(d_x+1,d_y)+1_{d_y=d_x+1}$, which involves the effects of the output dimensions. To obtain this result, we propose a novel lift-flow-discretization approach that shows that the uniform UAP has a deep connection with topological theory.Comment: ICML2023 camera read

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

Disks around massive young stellar objects: are they common?

We present K-band polarimetric images of several massive young stellar objects at resolutions $\sim$ 0.1-0.5 arcsec. The polarization vectors around these sources are nearly centro-symmetric, indicating they are dominating the illumination of each field. Three out of the four sources show elongated low-polarization structures passing through the centers, suggesting the presence of polarization disks. These structures and their surrounding reflection nebulae make up bipolar outflow/disk systems, supporting the collapse/accretion scenario as their low-mass siblings. In particular, S140 IRS1 show well defined outflow cavity walls and a polarization disk which matches the direction of previously observed equatorial disk wind, thus confirming the polarization disk is actually the circumstellar disk. To date, a dozen massive protostellar objects show evidence for the existence of disks; our work add additional samples around MYSOs equivalent to early B-type stars.Comment: 9 pages, including 2 figures, 1 table, to appear on ApJ

A multi-directional motion interacting fusion model for diver tracking

According to the diver motion characteristics, which are low speed and rapid change of direction, a multi-directional motion model is presented. Then the motion model is introduced into an interacting multiple model method, while the timevarying motion model transition probability was corrected according to current measurements. Firstly, the predictive state was obtained by a multi-directional motion model. Secondly, the parallel Kalman filters were applied to estimate multi-directional state. Finally, the interactive fusion processing for estimations from multidirectional motion model was conducted to implement diver state estimation. The method was verified by both simulation and experiment. The results show that the proposed method has higher tracking accuracy and superior adaptability than conventional interactive multiple model algorithm based on single direction motion model. The proposed method is effective for diver tracking

Doping the Buckminsterfullerene by Substitution: Density Functional Theory Studies of C 59

The heterofullerenes C59X (X = B, N, Al, Si, P, Ga, Ge, and As) were investigated by quantum chemistry calculations based on density functional theory. These hybrid cages can be seen as doping the buckminsterfullerene by heteroatom substitution. The geometrical structures, relative stabilities, electronic properties, vibrational frequencies, dielectric constants, and aromaticities of the doped cages were studied systemically and compared with those of the pristine C60 cage. It is found that the doped cages with different heteroatoms exhibit various electronic, vibrational, and aromatic properties. These results imply the possibility to modulate the physical properties of these fullerene-based materials by tuning substitution elements

Reversible transformation between CsPbBr3 nanowires and nanoparticles

We show that CsPbBr3 nanowires (NWs) are formed by the hierarchical arrangement of individual nanoparticles (NPs), and reversible transformation from NWs to NPs is also achieved by anion exchange

A new data-enabled intelligence framework for evaluating urban space perception

The urban environment has a great impact on the wellbeing of citizens and it is of great significance to understand how citizens perceive and evaluate places in a large scale urban region and to provide scientific evidence to support human-centered urban planning with a better urban environment. Existing studies for assessing urban perception have primarily relied on low efficiency methods, which also result in low evaluation accuracy. Furthermore, there lacks a sophisticated understanding on how to correlate the urban perception with the built environment and other socio-economic data, which limits their applications in supporting urban planning. In this study, a new data-enabled intelligence framework for evaluating human perceptions of urban space is proposed. Specifically, a novel classification-then-regression strategy based on a deep convolutional neural network and a random-forest algorithm is proposed. The proposed approach has been applied to evaluate the perceptions of Beijing and Chengdu against six perceptual criteria. Meanwhile, multi-source data were employed to investigate the associations between human perceptions and the indicators for the built environment and socio-economic data including visual elements, facility attributes and socio-economic indicators. Experimental results show that the proposed framework can effectively evaluate urban perceptions. The associations between urban perceptions and the visual elements, facility attributes and a socio-economic dimension have also been identified, which can provide substantial inputs to guide the urban planning for a better urban space