Abstract: L-system is a tool commonly used for modeling and simulating the growth of fractal plants. The aim of this paper is to join some problems of the computational geometry with the fractal geometry by using the L-system technique to generate fractal plant in 3D. L-system constructs the fractal structure by applying rewriting rules sequentially and this technique depends on recursion process with large number of iterations to get different shapes of 3D fractal plants. Instead, it was reiterated a specific number of iterations up to three iterations. The vertices generated from the last stage of the Lsystem rewriting process are used as input to the triangulation algorithm to construct the triangulation shape of these vertices. The resulting shapes can be used as covers for the architectural objects and in different computer graphics fields. The paper presents a gallery of triangulation forms which application in architecture creates an alternative for domes and other traditional types of roofs.
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: For over a decade, the Pulse Coupled Neural Network
(PCNN) based algorithms have been successfully used in image
interpretation applications including image segmentation. There are
several versions of the PCNN based image segmentation methods,
and the segmentation accuracy of all of them is very sensitive to the
values of the network parameters. Most methods treat PCNN
parameters like linking coefficient and primary firing threshold as
global parameters, and determine them by trial-and-error. The
automatic determination of appropriate values for linking coefficient,
and primary firing threshold is a challenging problem and deserves
further research. This paper presents a method for obtaining global as
well as local values for the linking coefficient and the primary firing
threshold for neurons directly from the image statistics. Extensive
simulation results show that the proposed approach achieves
excellent segmentation accuracy comparable to the best accuracy
obtainable by trial-and-error for a variety of images.
Abstract: In 1990 [1] the subband-DFT (SB-DFT) technique was proposed. This technique used the Hadamard filters in the decomposition step to split the input sequence into low- and highpass sequences. In the next step, either two DFTs are needed on both bands to compute the full-band DFT or one DFT on one of the two bands to compute an approximate DFT. A combination network with correction factors was to be applied after the DFTs. Another approach was proposed in 1997 [2] for using a special discrete wavelet transform (DWT) to compute the discrete Fourier transform (DFT). In the first step of the algorithm, the input sequence is decomposed in a similar manner to the SB-DFT into two sequences using wavelet decomposition with Haar filters. The second step is to perform DFTs on both bands to obtain the full-band DFT or to obtain a fast approximate DFT by implementing pruning at both input and output sides. In this paper, the wavelet-based DFT (W-DFT) with Haar filters is interpreted as SB-DFT with Hadamard filters. The only difference is in a constant factor in the combination network. This result is very important to complete the analysis of the W-DFT, since all the results concerning the accuracy and approximation errors in the SB-DFT are applicable. An application example in spectral analysis is given for both SB-DFT and W-DFT (with different filters). The adaptive capability of the SB-DFT is included in the W-DFT algorithm to select the band of most energy as the band to be computed. Finally, the W-DFT is extended to the two-dimensional case. An application in image transformation is given using two different types of wavelet filters.
Abstract: This work presents a neural network model for the
clustering analysis of data based on Self Organizing Maps (SOM).
The model evolves during the training stage towards a hierarchical
structure according to the input requirements. The hierarchical structure
symbolizes a specialization tool that provides refinements of the
classification process. The structure behaves like a single map with
different resolutions depending on the region to analyze. The benefits
and performance of the algorithm are discussed in application to the
Iris dataset, a classical example for pattern recognition.
Abstract: Fixed-point simulation results are used for the performance measure of inverting matrices using a reconfigurable processing element. Matrices are inverted using the Cholesky decomposition algorithm. The reconfigurable processing element is capable of all required mathematical operations. The fixed-point word length analysis is based on simulations of different condition numbers and different matrix sizes.
Abstract: Scheduling for the flexible job shop is very important
in both fields of production management and combinatorial
optimization. However, it quit difficult to achieve an optimal solution
to this problem with traditional optimization approaches owing to the
high computational complexity. The combining of several
optimization criteria induces additional complexity and new
problems. In this paper, a Pareto approach to solve the multi
objective flexible job shop scheduling problems is proposed. The
objectives considered are to minimize the overall completion time
(makespan) and total weighted tardiness (TWT). An effective
simulated annealing algorithm based on the proposed approach is
presented to solve multi objective flexible job shop scheduling
problem. An external memory of non-dominated solutions is
considered to save and update the non-dominated solutions during
the solution process. Numerical examples are used to evaluate and
study the performance of the proposed algorithm. The proposed
algorithm can be applied easily in real factory conditions and for
large size problems. It should thus be useful to both practitioners and
researchers.
Abstract: In this paper, an image adaptive, invisible digital
watermarking algorithm with Orthogonal Polynomials based
Transformation (OPT) is proposed, for copyright protection of digital
images. The proposed algorithm utilizes a visual model to determine
the watermarking strength necessary to invisibly embed the
watermark in the mid frequency AC coefficients of the cover image,
chosen with a secret key. The visual model is designed to generate a
Just Noticeable Distortion mask (JND) by analyzing the low level
image characteristics such as textures, edges and luminance of the
cover image in the orthogonal polynomials based transformation
domain. Since the secret key is required for both embedding and
extraction of watermark, it is not possible for an unauthorized user to
extract the embedded watermark. The proposed scheme is robust to
common image processing distortions like filtering, JPEG
compression and additive noise. Experimental results show that the
quality of OPT domain watermarked images is better than its DCT
counterpart.
Abstract: In this paper, RSA encryption algorithm and its hardware
implementation in Xilinx-s Virtex Field Programmable Gate
Arrays (FPGA) is analyzed. The issues of scalability, flexible performance,
and silicon efficiency for the hardware acceleration of
public key crypto systems are being explored in the present work.
Using techniques based on the interleaved math for exponentiation,
the proposed RSA calculation architecture is compared to existing
FPGA-based solutions for speed, FPGA utilization, and scalability.
The paper covers the RSA encryption algorithm, interleaved multiplication,
Miller Rabin algorithm for primality test, extended Euclidean
math, basic FPGA technology, and the implementation details of
the proposed RSA calculation architecture. Performance of several
alternative hardware architectures is discussed and compared. Finally,
conclusion is drawn, highlighting the advantages of a fully flexible
& parameterized design.
Abstract: Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.
Abstract: This paper presents a ray tracing simulation technique for characterize the radiowave propagation inside building. The implementation of an algorithm capable of enumerating a large number of propagation paths in interactive time for the special case of 2.5D. The effective dielectric constants of the building structure in the simulations are indicated. The study describes an efficient 2.5D model of ray tracing algorithm were compared with 3D model. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A detailed analysis of the dependence of the indoor wave on the wideband characteristics of the channel: root mean square (RMS) delay spread characteristics and Mean excess delay, is also investigated.
Abstract: the cursive nature of the Arabic writing makes it
difficult to accurately segment characters or even deal with the whole
word efficiently. Therefore, in this paper, a printed Arabic sub-word
recognition system is proposed. The suggested algorithm utilizes
geometrical moments as descriptors for the separated sub-words.
Three types of moments are investigated and applied to the printed
sub-word images after dividing each image into multiple parts using
windowing. Since moments are global descriptors, the windowing
mechanism allows the moments to be applied to local regions of the
sub-word. The local-global mixture of the proposed scheme increases
the discrimination power of the moments while keeping the
simplicity and ease of use of moments.
Abstract: In this paper a hybrid technique of Genetic Algorithm
and Simulated Annealing (HGASA) is applied for Fractal Image
Compression (FIC). With the help of this hybrid evolutionary
algorithm effort is made to reduce the search complexity of matching
between range block and domain block. The concept of Simulated
Annealing (SA) is incorporated into Genetic Algorithm (GA) in order
to avoid pre-mature convergence of the strings. One of the image
compression techniques in the spatial domain is Fractal Image
Compression but the main drawback of FIC is that it involves more
computational time due to global search. In order to improve the
computational time along with acceptable quality of the decoded
image, HGASA technique has been proposed. Experimental results
show that the proposed HGASA is a better method than GA in terms
of PSNR for Fractal image Compression.
Abstract: Microarray experiments are information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. For biologists, a key aim when analyzing microarray data is to group genes based on the temporal patterns of their expression levels. In this paper, we used an iterative clustering method to find temporal patterns of gene expression. We evaluated the performance of this method by applying it to real sporulation data and simulated data. The patterns obtained using the iterative clustering were found to be superior to those obtained using existing clustering algorithms.
Abstract: Wrist pulse analysis for identification of health status
is found in Ancient Indian as well as Chinese literature. The preprocessing
of wrist pulse is necessary to remove outlier pulses and
fluctuations prior to the analysis of pulse pressure signal. This paper
discusses the identification of irregular pulses present in the pulse
series and intricacies associated with the extraction of time domain
pulse features. An approach of Dynamic Time Warping (DTW) has
been utilized for the identification of outlier pulses in the wrist pulse
series. The ambiguity present in the identification of pulse features is
resolved with the help of first derivative of Ensemble Average of
wrist pulse series. An algorithm for detecting tidal and dicrotic notch
in individual wrist pulse segment is proposed.
Abstract: Flow-shop scheduling problem (FSP) deals with the
scheduling of a set of jobs that visit a set of machines in the same
order. The FSP is NP-hard, which means that an efficient algorithm
for solving the problem to optimality is unavailable. To meet the
requirements on time and to minimize the make-span performance of
large permutation flow-shop scheduling problems in which there are
sequence dependent setup times on each machine, this paper
develops one hybrid genetic algorithms (HGA). Proposed HGA
apply a modified approach to generate population of initial
chromosomes and also use an improved heuristic called the iterated
swap procedure to improve initial solutions. Also the author uses
three genetic operators to make good new offspring. The results are
compared to some recently developed heuristics and computational
experimental results show that the proposed HGA performs very
competitively with respect to accuracy and efficiency of solution.
Abstract: In the current study we present a system that is
capable to deliver proxy based differentiated service. It will help the
carrier service node to sell a prepaid service to clients and limit the
use to a particular mobile device or devices for a certain time. The
system includes software and hardware architecture for a mobile
device with moderate computational power, and a secure protocol for
communication between it and its carrier service node. On the
carrier service node a proxy runs on a centralized server to be
capable of implementing cryptographic algorithms, while the mobile
device contains a simple embedded processor capable of executing
simple algorithms. One prerequisite is needed for the system to run
efficiently that is a presence of Global Trusted Verification Authority
(GTVA) which is equivalent to certifying authority in IP networks.
This system appears to be of great interest for many commercial
transactions, business to business electronic and mobile commerce,
and military applications.
Abstract: In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.
Abstract: Using bottom-up image processing algorithms to predict human eye fixations and extract the relevant embedded information in images has been widely applied in the design of active machine vision systems. Scene text is an important feature to be extracted, especially in vision-based mobile robot navigation as many potential landmarks such as nameplates and information signs contain text. This paper proposes an edge-based text region extraction algorithm, which is robust with respect to font sizes, styles, color/intensity, orientations, and effects of illumination, reflections, shadows, perspective distortion, and the complexity of image backgrounds. Performance of the proposed algorithm is compared against a number of widely used text localization algorithms and the results show that this method can quickly and effectively localize and extract text regions from real scenes and can be used in mobile robot navigation under an indoor environment to detect text based landmarks.
Abstract: The National Blood Center, Thai Red Cross Society is
responsible for providing blood to hospitals all over the country.
When any hospital needs blood, it will have to send the vehicle to
pick up at the NBC. There are a lot of vehicles to pick up blood at the
NBC every day. Each vehicle is usually empty for inbound trip and a
little loaded for outbound. The NBC realized such waste or loss and
there have been the third party offered to distribute blood and charge
for fee. This paper proposes to apply the vehicle routing problem
(VRP) for estimating the fair price. The idea is tested with the real
data during seven-day period of 6 – 12 July 2010 to estimate the fair
price for transporting blood in Bangkok Metropolitan Region.