23,742 research outputs found
PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation
Recently most popular tracking frameworks focus on 2D image sequences. They
seldom track the 3D object in point clouds. In this paper, we propose PointIT,
a fast, simple tracking method based on 3D on-road instance segmentation.
Firstly, we transform 3D LiDAR data into the spherical image with the size of
64 x 512 x 4 and feed it into instance segment model to get the predicted
instance mask for each class. Then we use MobileNet as our primary encoder
instead of the original ResNet to reduce the computational complexity. Finally,
we extend the Sort algorithm with this instance framework to realize tracking
in the 3D LiDAR point cloud data. The model is trained on the spherical images
dataset with the corresponding instance label masks which are provided by KITTI
3D Object Track dataset. According to the experiment results, our network can
achieve on Average Precision (AP) of 0.617 and the performance of
multi-tracking task has also been improved
Joint Transportation and Charging Scheduling in Public Vehicle Systems - A Game Theoretic Approach
Public vehicle (PV) systems are promising transportation systems for future
smart cities which provide dynamic ride-sharing services according to
passengers' requests. PVs are driverless/self-driving electric vehicles which
require frequent recharging from smart grids. For such systems, the challenge
lies in both the efficient scheduling scheme to satisfy transportation demands
with service guarantee and the cost-effective charging strategy under the
real-time electricity pricing. In this paper, we study the joint transportation
and charging scheduling for PV systems to balance the transportation and
charging demands, ensuring the long-term operation. We adopt a cake cutting
game model to capture the interactions among PV groups, the cloud and smart
grids. The cloud announces strategies to coordinate the allocation of
transportation and energy resources among PV groups. All the PV groups try to
maximize their joint transportation and charging utilities. We propose an
algorithm to obtain the unique normalized Nash equilibrium point for this
problem. Simulations are performed to confirm the effects of our scheme under
the real taxi and power grid data sets of New York City. Our results show that
our scheme achieves almost the same transportation performance compared with a
heuristic scheme, namely, transportation with greedy charging; however, the
average energy price of the proposed scheme is 10.86% lower than the latter
one.Comment: 13 page
Suppressing epidemic spreading by risk-averse migration in dynamical networks
In this paper, we study the interplay between individual behaviors and
epidemic spreading in a dynamical network. We distribute agents on a
square-shaped region with periodic boundary conditions. Every agent is regarded
as a node of the network and a wireless link is established between two agents
if their geographical distance is less than a certain radius. At each time,
every agent assesses the epidemic situation and make decisions on whether it
should stay in or leave its current place. An agent will leave its current
place with a speed if the number of infected neighbors reaches or exceeds a
critical value . Owing to the movement of agents, the network's structure is
dynamical. Interestingly, we find that there exists an optimal value of
leading to the maximum epidemic threshold. This means that epidemic spreading
can be effectively controlled by risk-averse migration. Besides, we find that
the epidemic threshold increases as the recovering rate increases, decreases as
the contact radius increases, and is maximized by an optimal moving speed. Our
findings offer a deeper understanding of epidemic spreading in dynamical
networks.Comment: 7 pages, 6 figure
An Online Ride-Sharing Path Planning Strategy for Public Vehicle Systems
As efficient traffic-management platforms, public vehicle (PV) systems are
envisioned to be a promising approach to solving traffic congestions and
pollutions for future smart cities. PV systems provide online/dynamic
peer-to-peer ride-sharing services with the goal of serving sufficient number
of customers with minimum number of vehicles and lowest possible cost. A key
component of the PV system is the online ride-sharing scheduling strategy. In
this paper, we propose an efficient path planning strategy that focuses on a
limited potential search area for each vehicle by filtering out the requests
that violate passenger service quality level, so that the global search is
reduced to local search. We analyze the performance of the proposed solution
such as reduction ratio of computational complexity. Simulations based on the
Manhattan taxi data set show that, the computing time is reduced by 22%
compared with the exhaustive search method under the same service quality
performance.Comment: 12 page
Beam losses due to the foil scattering for CSNS/RCS
For the Rapid Cycling Synchrotron of China Spallation Neutron Source
(CSNS/RCS), the stripping foil scattering generates the beam halo and gives
rise to additional beam losses during the injection process. The interaction
between the proton beam and the stripping foil was discussed and the foil
scattering was studied. A simple model and the realistic situation of the foil
scattering were considered. By using the codes ORBIT and FLUKA, the multi-turn
phase space painting injection process with the stripping foil scattering for
CSNS/RCS was simulated and the beam losses due to the foil scattering were
obtained.Comment: Submitted to HB2012, IHEP, Beijing, Sep. 17-21, 201
Collaborative Similarity Embedding for Recommender Systems
We present collaborative similarity embedding (CSE), a unified framework that
exploits comprehensive collaborative relations available in a user-item
bipartite graph for representation learning and recommendation. In the proposed
framework, we differentiate two types of proximity relations: direct proximity
and k-th order neighborhood proximity. While learning from the former exploits
direct user-item associations observable from the graph, learning from the
latter makes use of implicit associations such as user-user similarities and
item-item similarities, which can provide valuable information especially when
the graph is sparse. Moreover, for improving scalability and flexibility, we
propose a sampling technique that is specifically designed to capture the two
types of proximity relations. Extensive experiments on eight benchmark datasets
show that CSE yields significantly better performance than state-of-the-art
recommendation methods.Comment: The shorten version is accepted by WWW'1
Joint Calibration of Panoramic Camera and Lidar Based on Supervised Learning
In view of contemporary panoramic camera-laser scanner system, the
traditional calibration method is not suitable for panoramic cameras whose
imaging model is extremely nonlinear. The method based on statistical
optimization has the disadvantage that the requirement of the number of laser
scanner's channels is relatively high. Calibration equipments with extreme
accuracy for panoramic camera-laser scanner system are costly. Facing all these
in the calibration of panoramic camera-laser scanner system, a method based on
supervised learning is proposed. Firstly, corresponding feature points of
panoramic images and point clouds are gained to generate the training dataset
by designing a round calibration object. Furthermore, the traditional
calibration problem is transformed into a multiple nonlinear regression
optimization problem by designing a supervised learning network with
preprocessing of the panoramic imaging model. Back propagation algorithm is
utilized to regress the rotation and translation matrix with high accuracy.
Experimental results show that this method can quickly regress the calibration
parameters and the accuracy is better than the traditional calibration method
and the method based on statistical optimization. The calibration accuracy of
this method is really high, and it is more highly-automated.Comment: in Chines
Delivery-Secrecy Tradeoff for Cache-Enabled Stochastic Networks: Content Placement Optimization
Wireless caching has been widely recognized as a promising technique for
efficient content delivery. In this paper, by taking different file secrecy
levels into consideration, physical-layer security oriented content placement
is optimized in a stochastic cache-enabled cellular network. We propose an
analytical framework to investigate the nontrivial file delivery-secrecy
tradeoff. Specifically, we first derive the closed-form expressions for the
file hit and secrecy probabilities. The global optimal probabilistic content
placement policy is then analytically derived in terms of hit probability
maximization under file secrecy constraints. Numerical results are demonstrated
to verify our analytical findings and show that the targeted file secrecy
levels are crucial in balancing the file delivery-secrecy tradeoff.Comment: 5 pages, 4 figures, accepted to be published in IEEE Transactions on
Vehicular Technolog
On the Cramer-Rao Lower Bound for Spatial Correlation Matrices of Doubly Selective Fading Channels for MIMO OFDM Systems
The analytic expression of CRLB and the maximum likelihood estimator for
spatial correlation matrices in time-varying multipath fading channels for MIMO
OFDM systems are reported in this paper. The analytical and numerical results
reveal that the amount of samples and the order of frequency selectivity have
dominant impact on the CRLB. Moreover, the number of pilot tones, SNR as well
as the normalized maximum Doppler spread together influence the effective order
of frequency selectivity.Comment: 6 pages, 8 figures, Submitted to IEEE WCNC'0
Fractional Non-Markovian effect and Newton's 2nd law of motion
We report in this paper a thorough study on the the dynamical mechanics of
the fractional Brownian motion systems. Where several non-trivial properties
are revealed such as the abundant non-Markovian effects resulted from the
fractional characters of the system. In general, the dynamics of the fBm system
is found to be of a purely Newton's type, despite of the anomalous fractional
properties of the system
- …