Abstract: Because of the great advance in multimedia
technology, digital multimedia is vulnerable to malicious
manipulations. In this paper, a public key self-recovery block-based
video authentication technique is proposed which can not only
precisely localize the alteration detection but also recover the missing
data with high reliability. In the proposed block-based technique,
multiple description coding MDC is used to generate two codes (two
descriptions) for each block. Although one block code (one
description) is enough to rebuild the altered block, the altered block
is rebuilt with better quality by the two block descriptions. So using
MDC increases the ratability of recovering data. A block signature is
computed using a cryptographic hash function and a doubly linked
chain is utilized to embed the block signature copies and the block
descriptions into the LSBs of distant blocks and the block itself. The
doubly linked chain scheme gives the proposed technique the
capability to thwart vector quantization attacks. In our proposed
technique , anyone can check the authenticity of a given video using
the public key. The experimental results show that the proposed
technique is reliable for detecting, localizing and recovering the
alterations.
Abstract: Based on general proportional integral (GPI) observers and sliding mode control technique, a robust control method is proposed for the master-slave synchronization of chaotic systems in the presence of parameter uncertainty and with partially measurable output signal. By using GPI observer, the master dynamics are reconstructed by the observations from a measurable output under the differential algebraic framework. Driven by the signals provided by GPI observer, a sliding mode control technique is used for the tracking control and synchronization of the master-slave dynamics. The convincing numerical results reveal the proposed method is effective, and successfully accommodate the system uncertainties, disturbances, and noisy corruptions.
Abstract: This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: The classical temporal scan statistic is often used to
identify disease clusters. In recent years, this method has become as a
very popular technique and its field of application has been notably
increased. Many bioinformatic problems have been solved with this
technique. In this paper a new scan fuzzy method is proposed. The
behaviors of classic and fuzzy scan techniques are studied with
simulated data. ROC curves are calculated, being demonstrated the
superiority of the fuzzy scan technique.
Abstract: This essay presents applicative methods to reduce human exposure levels in the area around base transceiver stations in a environment with multiple sources based on ITU-T recommendation K.70. An example is presented to understand the mitigation techniques and their results and also to learn how they can be applied, especially in developing countries where there is not much research on non-ionizing radiations.
Abstract: This paper compares six approaches of object serialization
from qualitative and quantitative aspects. Those are object
serialization in Java, IDL, XStream, Protocol Buffers, Apache Avro,
and MessagePack. Using each approach, a common example is
serialized to a file and the size of the file is measured. The qualitative
comparison works are investigated in the way of checking whether
schema definition is required or not, whether schema compiler is
required or not, whether serialization is based on ascii or binary, and
which programming languages are supported. It is clear that there
is no best solution. Each solution makes good in the context it was
developed.
Abstract: The link between Gröbner basis and linear algebra was
described by Lazard [4,5] where he realized the Gr¨obner basis
computation could be archived by applying Gaussian elimination over
Macaulay-s matrix .
In this paper, we indicate how same technique may be used to
SAGBI- Gröbner basis computations in invariant rings.
Abstract: Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.
Abstract: In the paper an effective context based lossless coding
technique is presented. Three principal and few auxiliary contexts are
defined. The predictor adaptation technique is an improved CoBALP
algorithm, denoted CoBALP+. Cumulated predictor error combining
8 bias estimators is calculated. It is shown experimentally that
indeed, the new technique is time-effective while it outperforms the
well known methods having reasonable time complexity, and is
inferior only to extremely computationally complex ones.
Abstract: This paper presents the development of a wavelet
based algorithm, for distinguishing between magnetizing inrush
currents and power system fault currents, which is quite adequate,
reliable, fast and computationally efficient tool. The proposed
technique consists of a preprocessing unit based on discrete wavelet
transform (DWT) in combination with an artificial neural network
(ANN) for detecting and classifying fault currents. The DWT acts as
an extractor of distinctive features in the input signals at the relay
location. This information is then fed into an ANN for classifying
fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz
laboratory transformer connected to a 380 V power system were
simulated using ATP-EMTP. The DWT was implemented by using
Matlab and Coiflet mother wavelet was used to analyze primary
currents and generate training data. The simulated results presented
clearly show that the proposed technique can accurately discriminate
between magnetizing inrush and fault currents in transformer
protection.
Abstract: In this paper, a discrete-time SIR epidemic model with nonlinear incidence rate, time delays and impulses is investigated. Sufficient conditions for the existence and uniqueness of periodic solutions are obtained by using contraction theorem and inequality techniques. An example is employed to illustrate our results.
Abstract: In this paper, we propose a Connect6 solver which
adopts a hybrid approach based on a tree-search algorithm and image
processing techniques. The solver must deal with the complicated
computation and provide high performance in order to make real-time
decisions. The proposed approach enables the solver to be
implemented on a single Spartan-6 XC6SLX45 FPGA produced by
XILINX without using any external devices. The compact
implementation is achieved through image processing techniques to
optimize a tree-search algorithm of the Connect6 game. The tree
search is widely used in computer games and the optimal search brings
the best move in every turn of a computer game. Thus, many
tree-search algorithms such as Minimax algorithm and artificial
intelligence approaches have been widely proposed in this field.
However, there is one fundamental problem in this area; the
computation time increases rapidly in response to the growth of the
game tree. It means the larger the game tree is, the bigger the circuit
size is because of their highly parallel computation characteristics.
Here, this paper aims to reduce the size of a Connect6 game tree using
image processing techniques and its position symmetric property. The
proposed solver is composed of four computational modules: a
two-dimensional checkmate strategy checker, a template matching
module, a skilful-line predictor, and a next-move selector. These
modules work well together in selecting next moves from some
candidates and the total amount of their circuits is small. The details of
the hardware design for an FPGA implementation are described and
the performance of this design is also shown in this paper.
Abstract: Traditional Javanese classic dance is a valuable
inheritance in Java Indonesia. Nowadays, this treasure of culture is
no longer belonging to Javanese people only. Many art departments
from universities around the world already put this as a subject in
their curriculum. Nonetheless, dance is a practical skill. It needs to be
practices so often while accompanied by an instructor to get the right
technique. An interactive Computer Aided Instruction (iCAI) that can
interactively assist the student to practice is developed. By using this
software students can conduct a self practice in studio and get some
feedbacks from the software. This CAI is not intended to replace the
instructor, but to assist them in increasing the student fly-time in
practice.
Abstract: Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value
Abstract: Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.
Abstract: This paper investigates the problem of spreading
sequence and receiver code synchronization techniques for satellite
based CDMA communications systems. The performance of CDMA
system depends on the autocorrelation and cross-correlation
properties of the used spreading sequences. In this paper we propose
the uses of chaotic Lu system to generate binary sequences for
spreading codes in a direct sequence spread CDMA system. To
minimize multiple access interference (MAI) we propose the use of
genetic algorithm for optimum selection of chaotic spreading
sequences. To solve the problem of transmitter-receiver
synchronization, we use the passivity controls. The concept of
semipassivity is defined to find simple conditions which ensure
boundedness of the solutions of coupled Lu systems. Numerical
results are presented to show the effectiveness of the proposed
approach.
Abstract: Consider a mass production of HDD arms where
hundreds of CNC machines are used to manufacturer the HDD arms.
According to an overwhelming number of machines and models of
arm, construction of separate control chart for monitoring each HDD
arm model by each machine is not feasible. This research proposed a
strategy to optimize the SPC management on shop floor. The
procedure started from identifying the clusters of the machine with
similar manufacturing performance using clustering technique. The
three way control chart ( I - MR - R ) is then applied to each
clustered group of machine. This proposed research has
advantageous to the manufacturer in terms of not only better
performance of the SPC but also the quality management paradigm.
Abstract: An approach for experimental measurement of the
dynamic characteristics of linear electromagnet actuators is
presented. It uses accelerometer sensor to register the armature
acceleration. The velocity and displacement of the moving parts can
be obtained by integration of the acceleration results. The armature
movement of permanent magnet linear actuator is acquired using this
technique. The results are analyzed and the performance of the
supposed approach is compared with the most commonly used
experimental setup where the displacement of the armature vs. time
is measured instead of its acceleration.
Abstract: In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.