Abstract: Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm.
Abstract: In this article, we consider the estimation of P[Y < X], when strength, X and stress, Y are two independent variables of Burr Type XII distribution. The MLE of the R based on one simple iterative procedure is obtained. Assuming that the common parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator and Bayes estimator of P[Y < X] are discussed. The exact confidence interval of the R is also obtained. Monte Carlo simulations are performed to compare the different proposed methods.
Abstract: In this paper we present a substantiation of a new
Laguerre-s type iterative method for solving of a nonlinear
polynomial equations systems with real coefficients. The problems of
its implementation, including relating to the structural choice of
initial approximations, were considered. Test examples demonstrate
the effectiveness of the method at the solving of many practical
problems solving.
Abstract: The Time-Domain Boundary Element Method (TDBEM)
is a well known numerical technique that handles quite
properly dynamic analyses considering infinite dimension media.
However, when these analyses are also related to nonlinear behavior,
very complex numerical procedures arise considering the TD-BEM,
which may turn its application prohibitive. In order to avoid this
drawback and model nonlinear infinite media, the present work
couples two BEM formulations, aiming to achieve the best of two
worlds. In this context, the regions expected to behave nonlinearly
are discretized by the Domain Boundary Element Method (D-BEM),
which has a simpler mathematical formulation but is unable to deal
with infinite domain analyses; the TD-BEM is employed as in the
sense of an effective non-reflexive boundary. An iterative procedure
is considered for the coupling of the TD-BEM and D-BEM, which is
based on a relaxed renew of the variables at the common interfaces.
Elastoplastic models are focused and different time-steps are allowed
to be considered by each BEM formulation in the coupled analysis.
Abstract: The image segmentation method described in this
paper has been developed as a pre-processing stage to be used in
methodologies and tools for video/image indexing and retrieval by
content. This method solves the problem of whole objects extraction
from background and it produces images of single complete objects
from videos or photos. The extracted images are used for calculating
the object visual features necessary for both indexing and retrieval
processes.
The segmentation algorithm is based on the cooperation among an
optical flow evaluation method, edge detection and region growing
procedures. The optical flow estimator belongs to the class of
differential methods. It permits to detect motions ranging from a
fraction of a pixel to a few pixels per frame, achieving good results in
presence of noise without the need of a filtering pre-processing stage
and includes a specialised model for moving object detection.
The first task of the presented method exploits the cues from
motion analysis for moving areas detection. Objects and background
are then refined using respectively edge detection and seeded region
growing procedures. All the tasks are iteratively performed until
objects and background are completely resolved.
The method has been applied to a variety of indoor and outdoor
scenes where objects of different type and shape are represented on
variously textured background.
Abstract: In today scenario, to meet enhanced demand imposed
by domestic, commercial and industrial consumers, various
operational & control activities of Radial Distribution Network
(RDN) requires a focused attention. Irrespective of sub-domains
research aspects of RDN like network reconfiguration, reactive
power compensation and economic load scheduling etc, network
performance parameters are usually estimated by an iterative process
and is commonly known as load (power) flow algorithm. In this
paper, a simple mechanism is presented to implement the load flow
analysis (LFA) algorithm. The reported algorithm utilizes graph
theory principles and is tested on a 69- bus RDN.
Abstract: In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.
Abstract: In this paper, a new learning algorithm based on a
hybrid metaheuristic integrating Differential Evolution (DE) and
Reduced Variable Neighborhood Search (RVNS) is introduced to train
the classification method PROAFTN. To apply PROAFTN, values of
several parameters need to be determined prior to classification. These
parameters include boundaries of intervals and relative weights for
each attribute. Based on these requirements, the hybrid approach,
named DEPRO-RVNS, is presented in this study. In some cases, the
major problem when applying DE to some classification problems
was the premature convergence of some individuals to local optima.
To eliminate this shortcoming and to improve the exploration and
exploitation capabilities of DE, such individuals were set to iteratively
re-explored using RVNS. Based on the generated results on
both training and testing data, it is shown that the performance of
PROAFTN is significantly improved. Furthermore, the experimental
study shows that DEPRO-RVNS outperforms well-known machine
learning classifiers in a variety of problems.
Abstract: This paper presents a new problem solving approach
that is able to generate optimal policy solution for finite-state
stochastic sequential decision-making problems with high data
efficiency. The proposed algorithm iteratively builds and improves
an approximate Markov Decision Process (MDP) model along with
cost-to-go value approximates by generating finite length trajectories
through the state-space. The approach creates a synergy between an
approximate evolving model and approximate cost-to-go values to
produce a sequence of improving policies finally converging to the
optimal policy through an intelligent and structured search of the
policy space. The approach modifies the policy update step of the
policy iteration so as to result in a speedy and stable convergence to
the optimal policy. We apply the algorithm to a non-holonomic
mobile robot control problem and compare its performance with
other Reinforcement Learning (RL) approaches, e.g., a) Q-learning,
b) Watkins Q(λ), c) SARSA(λ).
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: Overloading is a technique to accommodate more
number of users than the spreading factor N. This is a bandwidth
efficient scheme to increase the number users in a fixed bandwidth.
One of the efficient schemes to overload a CDMA system is to use
two sets of orthogonal signal waveforms (O/O). The first set is
assigned to the N users and the second set is assigned to the
additional M users. An iterative interference cancellation technique is
used to cancel interference between the two sets of users. In this
paper, the performance of an overloading scheme in which the first N
users are assigned Walsh-Hadamard orthogonal codes and extra users
are assigned the same WH codes but overlaid by a fixed (quasi) bent
sequence [11] is evaluated. This particular scheme is called Quasi-
Orthogonal Sequence (QOS) O/O scheme, which is a part of
cdma2000 standard [12] to provide overloading in the downlink
using single user detector. QOS scheme are balance O/O scheme,
where the correlation between any set-1 and set-2 users are
equalized. The allowable overload of this scheme is investigated in
the uplink on an AWGN and Rayleigh fading channels, so that the
uncoded performance with iterative multistage interference
cancellation detector remains close to the single user bound. It is
shown that this scheme provides 19% and 11% overloading with
SDIC technique for N= 16 and 64 respectively, with an SNR
degradation of less than 0.35 dB as compared to single user bound at
a BER of 0.00001. But on a Rayleigh fading channel, the channel
overloading is 45% (29 extra users) at a BER of 0.0005, with an SNR
degradation of about 1 dB as compared to single user performance
for N=64. This is a significant amount of channel overloading on a
Rayleigh fading channel.
Abstract: In this paper channel estimation techniques are
considered as the support methods for OFDM transmission systems
based on Non Binary LDPC (Low Density Parity Check) codes.
Standard frequency domain pilot aided LS (Least Squares) and
LMMSE (Linear Minimum Mean Square Error) estimators are
investigated. Furthermore, an iterative algorithm is proposed as a
solution exploiting the NB-LDPC channel decoder to improve the
performance of the LMMSE estimator. Simulation results of signals
transmitted through fading mobile channels are presented to compare
the performance of the proposed channel estimators.
Abstract: We propose a new approach on how to obtain the approximate solutions of Hamilton-Jacobi (HJ) equations. The process of the approximation consists of two steps. The first step is to transform the HJ equations into the virtual time based HJ equations (VT-HJ) by introducing a new idea of ‘virtual-time’. The second step is to construct the approximate solutions of the HJ equations through a computationally iterative procedure based on the VT-HJ equations. It should be noted that the approximate feedback solutions evolve by themselves as the virtual-time goes by. Finally, we demonstrate the effectiveness of our approximation approach by means of simulations with linear and nonlinear control problems.
Abstract: We study the semiconvergence of Gauss-Seidel iterative
methods for the least squares solution of minimal norm of rank
deficient linear systems of equations. Necessary and sufficient conditions
for the semiconvergence of the Gauss-Seidel iterative method
are given. We also show that if the linear system of equations is
consistent, then the proposed methods with a zero vector as an initial
guess converge in one iteration. Some numerical results are given to
illustrate the theoretical results.
Abstract: In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.
Abstract: This paper presents a simple approach for load
flow analysis of a radial distribution network. The proposed
approach utilizes forward and backward sweep algorithm
based on Kirchoff-s current law (KCL) and Kirchoff-s voltage
law (KVL) for evaluating the node voltages iteratively. In this
approach, computation of branch current depends only on the
current injected at the neighbouring node and the current in
the adjacent branch. This approach starts from the end nodes
of sub lateral line, lateral line and main line and moves
towards the root node during branch current computation. The
node voltage evaluation begins from the root node and moves
towards the nodes located at the far end of the main, lateral
and sub lateral lines. The proposed approach has been tested
using four radial distribution systems of different size and
configuration and found to be computationally efficient.
Abstract: The number of users supported in a DS-CDMA
cellular system is typically less than spreading factor (N), and the
system is said to be underloaded. Overloading is a technique to
accommodate more number of users than the spreading factor N. In
O/O overloading scheme, the first set is assigned to the N
synchronous users and the second set is assigned to the additional
synchronous users. An iterative multistage soft decision interference
cancellation (SDIC) receiver is used to remove high level of
interference between the two sets. Performance is evaluated in terms
of the maximum number acceptable users so that the system
performance is degraded slightly compared to the single user
performance at a specified BER. In this paper, the capacity of CDMA
based O/O overloading scheme is evaluated with SDIC receiver. It is
observed that O/O scheme using orthogonal Gold codes provides
25% channel overloading (N=64) for synchronous DS-CDMA
system on an AWGN channel in the uplink at a BER of 1e-5.For a
Rayleigh faded channel, the critical capacity is 40% at a BER of 5e-5
assuming synchronous users. But in practical systems, perfect chip
timing is very difficult to maintain in the uplink.. We have shown that
the overloading performance reduces to 11% for a timing
synchronization error of 0.02Tc for a BER of 1e-5.
Abstract: A generalized Dirichlet to Neumann map is
one of the main aspects characterizing a recently introduced
method for analyzing linear elliptic PDEs, through which it
became possible to couple known and unknown components
of the solution on the boundary of the domain without
solving on its interior. For its numerical solution, a well conditioned
quadratically convergent sine-Collocation method
was developed, which yielded a linear system of equations
with the diagonal blocks of its associated coefficient matrix
being point diagonal. This structural property, among others,
initiated interest for the employment of iterative methods for
its solution. In this work we present a conclusive numerical
study for the behavior of classical (Jacobi and Gauss-Seidel)
and Krylov subspace (GMRES and Bi-CGSTAB) iterative
methods when they are applied for the solution of the Dirichlet
to Neumann map associated with the Laplace-s equation
on regular polygons with the same boundary conditions on
all edges.
Abstract: Modularized design approach can facilitate the
modeling of complex systems and support behavior analysis and
simulation in an iterative and thus complex engineering process, by
using encapsulated submodels of components and of their interfaces.
Therefore it can improve the design efficiency and simplify the
solving complicated problem. Multi-drivers off-road vehicle is
comparatively complicated. Driving-line is an important core part to a
vehicle; it has a significant contribution to the performance of a
vehicle. Multi-driver off-road vehicles have complex driving-line, so
its performance is heavily dependent on the driving-line. A typical
off-road vehicle-s driving-line system consists of torque converter,
transmission, transfer case and driving-axles, which transfer the
power, generated by the engine and distribute it effectively to the
driving wheels according to the road condition. According to its main
function, this paper puts forward a modularized approach for
designing and evaluation of vehicle-s driving-line. It can be used to
effectively estimate the performance of driving-line during concept
design stage. Through appropriate analysis and assessment method, an
optimal design can be reached. This method has been applied to the
practical vehicle design, it can improve the design efficiency and is
convenient to assess and validate the performance of a vehicle,
especially of multi-drivers off-road vehicle.
Abstract: Masonry cavity walls are loaded by wind pressure and vertical load from upper floors. These loads results in bending moments and compression forces in the ties connecting the outer and the inner wall in a cavity wall. Large cavity walls are furthermore loaded by differential movements from the temperature gradient between the outer and the inner wall, which results in critical increase of the bending moments in the ties. Since the ties are loaded by combined compression and moment forces, the loadbearing capacity is derived from instability equilibrium equations. Most of them are iterative, since exact instability solutions are complex to derive, not to mention the extra complexity introducing dimensional instability from the temperature gradients. Using an inverse variable substitution and comparing an exact theory with an analytical instability solution a method to design tie-connectors in cavity walls was developed. The method takes into account constraint conditions limiting the free length of the wall tie, and the instability in case of pure compression which gives an optimal load bearing capacity. The model is illustrated with examples from praxis.