18,644 research outputs found
Rescaled range and transition matrix analysis of DNA sequences
In this paper we treat some fractal and statistical features of the DNA
sequences. First, a fractal record model of DNA sequence is proposed by mapping
DNA sequences to integer sequences, followed by R/S analysis of the model and
computation of the Hurst exponents. Second, we consider transition between the
four kinds of bases within DNA. The transition matrix analysis of DNA sequences
shows that some measures of complexity based on transition proportion matrix
are of interest. We use some measures of complexity to distinguish exon and
intron. Regarding the evolution, we find that for species of higher grade, the
transition rate among the four kinds of bases goes further from the
equilibrium.Comment: 8 pages with one figure. Communication in Theoretical Physics (2000)
(to appear
Capacity of Gaussian Many-Access Channels
Classical multiuser information theory studies the fundamental limits of
models with a fixed (often small) number of users as the coding blocklength
goes to infinity. This work proposes a new paradigm, referred to as {\em
many-user information theory}, where the number of users is allowed to grow
with the blocklength. This paradigm is motivated by emerging systems with a
massive number of users in an area, such as machine-to-machine communication
systems and sensor networks. The focus of the current paper is the {\em
many-access} channel model, which consists of a single receiver and many
transmitters, whose number increases unboundedly with the blocklength.
Moreover, an unknown subset of transmitters may transmit in a given block and
need to be identified. A new notion of capacity is introduced and characterized
for the Gaussian many-access channel with random user activities. The capacity
can be achieved by first detecting the set of active users and then decoding
their messages.Comment: To appear in the IEEE Transactions on Information Theor
A hybrid generalized extremal optimization algorithm for the quay crane scheduling problem with interference constraints
The quay crane scheduling problem (QCSP) determines the handling sequence of
tasks at ship bays by a set of cranes assigned to a container vessel such that
the vessel's service time is minimized. A number of heuristics or
meta-heuristics have been proposed to obtain the near-optimal solutions to
overcome the NP-hardness of the problem. In this article, the idea of
generalized extremal optimization (GEO) is adapted to solve the QCSP with
respect to various interference constraints. The resulted GEO is termed as the
modified GEO. A randomized searching method for neighboring task-to-QC
assignments to an incumbent task-to-QC assignment is developed in executing the
modified GEO. In addition, a unidirectional search decoding scheme is employed
to transform a task-to-QC assignment to an active quay crane schedule. The
effectiveness of the developed GEO is tested on a suite of benchmark problems
introduced by \citet{KimPark2004}. Compared with other well known existing
approaches, the experiment results show that the proposed modified GEO is
capable of obtaining the optimal or near-optimal solution in reasonable time,
especially for large-sized problems
A general variable neighborhood search for single-machine total tardiness scheduling problem with step-deteriorating jobs
In this article, we study a single-machine scheduling problem of minimizing
the total tardiness for a set of independent jobs. The processing time of a job
is modeled as a step function of its starting time and a specific deteriorating
date. A mixed integer programming model was applied to the problem and
validated. Since the problem is known to be NP-hard, we proposed a heuristic
named simple weighted search procedure (SWSP) and a general variable
neighborhood search algorithm (GVNS).
A perturbation procedure with 3-opt is embedded within the GVNS process in
order to explore broader spaces. Extensive numerical experiments are carried
out on some randomly generated test instances so as to investigate the
performance of the proposed algorithms. By comparing to the results of the
CPLEX optimization solver, the heuristic SWSP and the standard variable
neighborhood search, it is shown that the proposed GVNS algorithm can provide
better solutions within a reasonable running time
Pedestrian-Robot Interaction Experiments in an Exit Corridor
The study of human-robot interaction (HRI) has received increasing research
attention for robot navigation in pedestrian crowds. In this paper, we present
empirical study of pedestrian-robot interaction in an uni-directional exit
corridor. We deploy a mobile robot moving in a direction perpendicular to that
of the pedestrian flow, and install a pedestrian motion tracking system to
record the collective motion. We analyze both individual and collective motion
of pedestrians, and measure the effect of the robot motion on the overall
pedestrian flow. The experimental results show the effect of passive HRI, where
the pedestrians' overall speed is slowed down in the presence of the robot, and
the faster the robot moves, the lower the average pedestrian velocity becomes.
Experiment results show qualitative consistency of the collective HRI effect
with simulation results that was previously reported. The study can be used to
guide future design of robot-assisted pedestrian evacuation algorithms.Comment: Submitted to the 15th International Conference on Ubiquitous Robots,
Honolulu, 201
l1-norm Penalized Orthogonal Forward Regression
A l1-norm penalized orthogonal forward regression (l1-POFR) algorithm is
proposed based on the concept of leaveone- out mean square error (LOOMSE).
Firstly, a new l1-norm penalized cost function is defined in the constructed
orthogonal space, and each orthogonal basis is associated with an individually
tunable regularization parameter. Secondly, due to orthogonal computation, the
LOOMSE can be analytically computed without actually splitting the data set,
and moreover a closed form of the optimal regularization parameter in terms of
minimal LOOMSE is derived. Thirdly, a lower bound for regularization parameters
is proposed, which can be used for robust LOOMSE estimation by adaptively
detecting and removing regressors to an inactive set so that the computational
cost of the algorithm is significantly reduced. Illustrative examples are
included to demonstrate the effectiveness of this new l1-POFR approach
The m-least significant bits operation for quantum random number generation
Quantum random number generators (QRNGs) can provide genuine randomness based
on the inherent unpredictable nature of quantum physics. The extracted
randomness relies not only on the physical parts of the QRNG, such as the
entropy source and the measurement device, but also on appropriate
postprocessing method. The m-least significant bits (m-LSBs) operation is one
of the simplest randomness extraction method, which has the advantage of easy
implementations. Nonetheless, a detailed analysis of the m-LSBs operation in
QRNGs is still missing. In this work we give a physical explanation of the
m-LSBs operation by introducing a new positive operator-valued measurement
operator, which is obtained by regrouping the results of coarse-grained
measurements. Both trusted and untrusted source scenarios are discussed. The
results show that the m-LSBs operation can extract randomness effectively under
the condition of the trusted source, while it is not effective under the
untrusted source scenario.Comment: 19 pages, 5 figure
High speed error correction for continuous-variable quantum key distribution with multi-edge type LDPC code
Error correction is a significant step in postprocessing of
continuous-variable quantum key distribution system, which is used to make two
distant legitimate parties share identical corrected keys. We propose an
experiment demonstration of high speed error correction with multi-edge type
low-density parity check (MET-LDPC) codes based on graphic processing unit
(GPU). GPU supports to calculate the messages of MET-LDPC codes simultaneously
and decode multiple codewords in parallel. We optimize the memory structure of
parity check matrix and the belief propagation decoding algorithm to reduce
computational complexity. Our results show that GPU-based decoding algorithm
greatly improves the error correction speed. For the three typical code rate,
i.e., 0.1, 0.05 and 0.02, when the block length is and the iteration
number are 100, 150 and 200, the average error correction speed can be
respectively achieved to 30.39Mbits/s (over three times faster than previous
demonstrations), 21.23Mbits/s and 16.41Mbits/s with 64 codewords decoding in
parallel, which supports high-speed real-time continuous-variable quantum key
distribution system.Comment: 8 pages, 2 figure
Experimental implementation of bias-free quantum random number generator based on vacuum fluctuation
We experimentally demonstrate a bias-free optical quantum random number
generator with real-time randomness extraction to directly output uniform
distributed random numbers by measuring the vacuum fluctuation of quantum
state. A phase modulator is utilized in the scheme to effectively reduce the
influence of deviations between two arms of the generator caused by the
imperfect practical devices, which is an innovative solution in the field of
quantum random number generator. In the case where the feedback modulation
frequency is much faster than the phase jitter, an unbiased result can be
obtained by an additional subtraction between the compensation signal and its
average value to eliminate residual deviation. A following randomness extractor
is applied to eliminate the influence of residual side information introduced
by the imperfect devices in practical system.Comment: 7 pages, 3 figure
Shock-induced plasticity of semi-coherent 111 Cu-Ni multilayers
Using atomistic simulations, dislocation dynamics modeling, and continuum
elastic-plastic stress-wave theory, we present a systematic investigation on
shock-induced plasticity in semi-coherent CuNi multilayers. The features of
stress wave evolutions in the multilayers, including wave-front stress
attenuation and strong interfacial discontinuities, are revealed by atomistic
simulations. Continuum models are proposed to explain the shockwave propagation
features. The simulations provide insight into microplasticity behaviors
including interactions between lattice and misfit dislocations. The formation
of hybrid Lomer-Cottrell locks through the attraction and combination of
lattice and misfit dislocations is a major mechanism for trapping gliding
lattice dislocations at interfaces. The relationship between dislocation
activity and dynamic stress wave evolution history is explored. The hybrid
Lomer-Cottrell locks can dissociate under shock compression or reverse
yielding. This dissociation facilitates slip transmission. The influence of
coherent stress causes direction dependency in the slip transmission: a lattice
dislocation is transmitted more smoothly across an interface from Ni to Cu than
from Cu to Ni. The interaction forces between lattice and misfit dislocations
are calculated using dislocation dynamics code. Lattice dislocation nucleation
from semi-coherent interfaces under shock compression is also reported
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