11,011 research outputs found
Towards Long-endurance Flight: Design and Implementation of a Variable-pitch Gasoline-engine Quadrotor
Majority of today's fixed-pitch, electric-power quadrotors have short flight
endurance ( 1 hour) which greatly limits their applications. This paper
presents a design methodology for the construction of a long-endurance
quadrotor using variable-pitch rotors and a gasoline-engine. The methodology
consists of three aspects. Firstly, the rotor blades and gasoline engine are
selected as a pair, so that sufficient lift can be comfortably provided by the
engine. Secondly, drivetrain and airframe are designed. Major challenges
include airframe vibration minimization and power transmission from one engine
to four rotors while keeping alternate rotors contra-rotating. Lastly, a PD
controller is tuned to facilitate preliminary flight tests. The methodology has
been verified by the construction and successful flight of our gasoline
quadrotor prototype, which is designed to have a flight time of 2 to 3 hours
and a maximum take-off weight of 10 kg.Comment: 6 page
A Hybrid Quantum Encoding Algorithm of Vector Quantization for Image Compression
Many classical encoding algorithms of Vector Quantization (VQ) of image
compression that can obtain global optimal solution have computational
complexity O(N). A pure quantum VQ encoding algorithm with probability of
success near 100% has been proposed, that performs operations 45sqrt(N) times
approximately. In this paper, a hybrid quantum VQ encoding algorithm between
classical method and quantum algorithm is presented. The number of its
operations is less than sqrt(N) for most images, and it is more efficient than
the pure quantum algorithm.
Key Words: Vector Quantization, Grover's Algorithm, Image Compression,
Quantum AlgorithmComment: Modify on June 21. 10pages, 3 figure
Are spectroscopic factors from transfer reactions consistent with asymptotic normalisation coefficients?
It is extremely important to devise a reliable method to extract
spectroscopic factors from transfer cross sections. We analyse the standard
DWBA procedure and combine it with the asymptotic normalisation coefficient,
extracted from an independent data set. We find that the single particle
parameters used in the past generate inconsistent asymptotic normalization
coefficients. In order to obtain a consistent spectroscopic factor,
non-standard parameters for the single particle overlap functions can be used
but, as a consequence, often reduced spectroscopic strengths emerge. Different
choices of optical potentials and higher order effects in the reaction model
are also studied. Our test cases consist of: C(d,p)C(g.s.) at
MeV, O(d,p)O(g.s.) at MeV and
Ca(d,p)Ca(g.s.) at MeV. We underline the
importance of performing experiments specifically designed to extract ANCs for
these systems.Comment: 15 pages, 12 figures, Phys. Rev. C (in press
Inferring Unusual Crowd Events From Mobile Phone Call Detail Records
The pervasiveness and availability of mobile phone data offer the opportunity
of discovering usable knowledge about crowd behaviors in urban environments.
Cities can leverage such knowledge in order to provide better services (e.g.,
public transport planning, optimized resource allocation) and safer cities.
Call Detail Record (CDR) data represents a practical data source to detect and
monitor unusual events considering the high level of mobile phone penetration,
compared with GPS equipped and open devices. In this paper, we provide a
methodology that is able to detect unusual events from CDR data that typically
has low accuracy in terms of space and time resolution. Moreover, we introduce
a concept of unusual event that involves a large amount of people who expose an
unusual mobility behavior. Our careful consideration of the issues that come
from coarse-grained CDR data ultimately leads to a completely general framework
that can detect unusual crowd events from CDR data effectively and efficiently.
Through extensive experiments on real-world CDR data for a large city in
Africa, we demonstrate that our method can detect unusual events with 16%
higher recall and over 10 times higher precision, compared to state-of-the-art
methods. We implement a visual analytics prototype system to help end users
analyze detected unusual crowd events to best suit different application
scenarios. To the best of our knowledge, this is the first work on the
detection of unusual events from CDR data with considerations of its temporal
and spatial sparseness and distinction between user unusual activities and
daily routines.Comment: 18 pages, 6 figure
Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints
This work presents a model for the Tramp Ship Scheduling problem including
berth allocation considerations, motivated by a real case of a shipping
company. The aim is to determine the travel schedule for each vessel
considering multiple docking and multiple time windows at the berths. This work
is innovative due to the consideration of both spatial and temporal attributes
during the scheduling process. The resulting model is formulated as a
mixed-integer linear programming problem, and a heuristic method to deal with
multiple vessel schedules is also presented. Numerical experimentation is
performed to highlight the benefits of the proposed approach and the
applicability of the heuristic. Conclusions and recommendations for further
research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican
International Conference on Artificial Intelligence (MICAI) 201
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