Abstract: Multiple-input multiple-output (MIMO) systems are
widely in use to improve quality, reliability of wireless transmission
and increase the spectral efficiency. However in MIMO systems,
multiple copies of data are received after experiencing various
channel effects. The limitations on account of complexity due to
number of antennas in case of conventional decoding techniques have
been looked into. Accordingly we propose a modified sphere decoder
(MSD-1) algorithm with lower complexity and give rise to system
with high spectral efficiency. With the aim to increase signal
diversity we apply rotated quadrature amplitude modulation (QAM)
constellation in multi dimensional space. Finally, we propose a new
architecture involving space time trellis code (STTC) concatenated
with space time block code (STBC) using MSD-1 at the receiver for
improving system performance. The system gains have been verified
with channel state information (CSI) errors.
Abstract: Machine tools are improved capacity remarkably during the 20th century. Improving the precision of machine tools are related with precision of products and accurate processing is always associated with the subject of interest. There are a lot of the elements that determine the precision of the machine, as guides, motors, structure, control, etc. In this paper we focused on the phenomenon that vertical movement system has worse precision than horizontal movement system even they were made up with same components. The vertical movement system needs to be studied differently from the horizontal movement system to develop its precision. The vertical movement system has load on its transfer direction and it makes the movement system weak in precision than the horizontal one. Some machines have mechanical counter balance, hydraulic or pneumatic counter balance to compensate the weight of the machine head. And there is several type of compensating the weight. It can push the machine head and also can use chain or wire lope to transfer the compensating force from counter balance to machine head. According to the type of compensating, there could be error from friction, pressure error of hydraulic or pressure control error. Also according to what to use for transferring the compensating force, transfer error of compensating force could be occur.
Abstract: This paper describes a new method of unequal error
protection (UEP) for region of interest (ROI) with embedded zerotree
wavelet algorithm (EZW). ROI technique is important in applications
with different parts of importance. In ROI coding, a chosen ROI is
encoded with higher quality than the background (BG). Unequal
error protection of image is provided by different coding techniques.
In our proposed method, image is divided into two parts (ROI, BG)
that consist of more important bytes (MIB) and less important bytes
(LIB). The experimental results verify effectiveness of the design.
The results of our method demonstrate the comparison of the unequal
error protection (UEP) of image transmission with defined ROI and
the equal error protection (EEP) over multiple noisy channels.
Abstract: This paper describes the use of artificial neural
networks (ANN) for predicting non-linear layer moduli of flexible
airfield pavements subjected to new generation aircraft (NGA)
loading, based on the deflection profiles obtained from Heavy
Weight Deflectometer (HWD) test data. The HWD test is one of the
most widely used tests for routinely assessing the structural integrity
of airport pavements in a non-destructive manner. The elastic moduli
of the individual pavement layers backcalculated from the HWD
deflection profiles are effective indicators of layer condition and are
used for estimating the pavement remaining life. HWD tests were
periodically conducted at the Federal Aviation Administration-s
(FAA-s) National Airport Pavement Test Facility (NAPTF) to
monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test
gear trafficking on the structural condition of flexible pavement
sections. In this study, a multi-layer, feed-forward network which
uses an error-backpropagation algorithm was trained to approximate
the HWD backcalculation function. The synthetic database generated
using an advanced non-linear pavement finite-element program was
used to train the ANN to overcome the limitations associated with
conventional pavement moduli backcalculation. The changes in
ANN-based backcalculated pavement moduli with trafficking were
used to compare the relative severity effects of the aircraft landing
gears on the NAPTF test pavements.
Abstract: Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.
Abstract: The underground shopping mall has the constructional
problem of the fire evacuation. Also, the people sometimes lose their
direction and information of current time in the mall. If the
emergencies such as terrorist explosions or gas explosions are
happened, they have to go out soon. Under such circumstances, inside
of the mall has high risk for life. In this research, the authors propose a
way that he/she can go out from the underground shopping mall
quickly. If the narrow exits are discovered by using active RFID
(Radio Frequency Identification) tags and using cellular phones, they
can evacuate as soon as possible. To verify this hypothesis, the authors
design the model and carry out the agent-based simulation. They treat,
as a case study, the Tenjin mall in Fukuoka Prefecture in Japan. The
result of the simulation is that the case of the pedestrian with using
active RFID tags and cellular phones reduced the amount of time to
spend on the evacuation. Even if the diffusion of RFID tags and
cellular phones was not perfect, they could show the effectiveness of
reducing the time of evacuation.
Abstract: According to the majority and to stereotypes in a simple everyman religious processes in the world in general, and Kazakhstan in particular, have only negative trends. The main reason for the author's opinion is seen in the fact that the media in the pursuit of ratings and sensation, more inclined to highlight the negative aspects of events in the country and the world of processes forgetting or casually mentioning the positive initiatives and achievements. That is why the article is mainly revealed positive trends in mind that the problems of fanaticism, terrorism and the confrontation of society on various issues, a lot has been written and detailed. This article describes the stages in the development of relations between religion and state, as well as institutionalization, networking and assistance in the correct orientation of religious activities in the country.
Abstract: An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
Abstract: The focus in this work is to assess which method
allows a better forecasting of malaria cases in Bujumbura ( Burundi)
when taking into account association between climatic factors and
the disease. For the period 1996-2007, real monthly data on both
malaria epidemiology and climate in Bujumbura are described and
analyzed. We propose a hierarchical approach to achieve our
objective. We first fit a Generalized Additive Model to malaria cases
to obtain an accurate predictor, which is then used to predict future
observations. Various well-known forecasting methods are compared
leading to different results. Based on in-sample mean average
percentage error (MAPE), the multiplicative exponential smoothing
state space model with multiplicative error and seasonality performed
better.
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 analyzes the linkage between migration,
economic globalization and terrorism concerns. On a broad level, I
analyze Canadian economic and political considerations, searching
for causal relationships between political and economic actors on the
one hand, and Canadian immigration law on the other. Specifically,
the paper argues that there are contradictory impulses affecting state
sovereignty. These impulses are are currently being played out in the
field of Canadian immigration law through several proposed changes
to Canada-s Immigration and Refugee Protection Act (IRPA). These
changes reflect an ideological conception of sovereignty that is
intrinsically connected with decision-making capacity centered on an
individual. This conception of sovereign decision-making views
Parliamentary debate and bureaucratic inefficiencies as both equally
responsible for delaying essential decisions relating to the protection
of state sovereignty, economic benefits and immigration control This
paper discusses these concepts in relation to Canadian immigration
policy under Canadian governments over the past twenty five years.
Abstract: In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.
Abstract: System development life cycle (SDLC) is a
process uses during the development of any system. SDLC
consists of four main phases: analysis, design, implement and
testing. During analysis phase, context diagram and data flow
diagrams are used to produce the process model of a system.
A consistency of the context diagram to lower-level data flow
diagrams is very important in smoothing up developing
process of a system. However, manual consistency check from
context diagram to lower-level data flow diagrams by using a
checklist is time-consuming process. At the same time, the
limitation of human ability to validate the errors is one of the
factors that influence the correctness and balancing of the
diagrams. This paper presents a tool that automates the
consistency check between Data Flow Diagrams (DFDs)
based on the rules of DFDs. The tool serves two purposes: as
an editor to draw the diagrams and as a checker to check the
correctness of the diagrams drawn. The consistency check
from context diagram to lower-level data flow diagrams is
embedded inside the tool to overcome the manual checking
problem.
Abstract: Image compression plays a vital role in today-s
communication. The limitation in allocated bandwidth leads to
slower communication. To exchange the rate of transmission in the
limited bandwidth the Image data must be compressed before
transmission. Basically there are two types of compressions, 1)
LOSSY compression and 2) LOSSLESS compression. Lossy
compression though gives more compression compared to lossless
compression; the accuracy in retrievation is less in case of lossy
compression as compared to lossless compression. JPEG, JPEG2000
image compression system follows huffman coding for image
compression. JPEG 2000 coding system use wavelet transform,
which decompose the image into different levels, where the
coefficient in each sub band are uncorrelated from coefficient of
other sub bands. Embedded Zero tree wavelet (EZW) coding exploits
the multi-resolution properties of the wavelet transform to give a
computationally simple algorithm with better performance compared
to existing wavelet transforms. For further improvement of
compression applications other coding methods were recently been
suggested. An ANN base approach is one such method. Artificial
Neural Network has been applied to many problems in image
processing and has demonstrated their superiority over classical
methods when dealing with noisy or incomplete data for image
compression applications. The performance analysis of different
images is proposed with an analysis of EZW coding system with
Error Backpropagation algorithm. The implementation and analysis
shows approximately 30% more accuracy in retrieved image
compare to the existing EZW coding system.
Abstract: The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis.
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.
Abstract: This paper deals with a high-order accurate Runge
Kutta Discontinuous Galerkin (RKDG) method for the numerical
solution of the wave equation, which is one of the simple case of a
linear hyperbolic partial differential equation. Nodal DG method is
used for a finite element space discretization in 'x' by discontinuous
approximations. This method combines mainly two key ideas which
are based on the finite volume and finite element methods. The
physics of wave propagation being accounted for by means of
Riemann problems and accuracy is obtained by means of high-order
polynomial approximations within the elements. High order accurate
Low Storage Explicit Runge Kutta (LSERK) method is used for
temporal discretization in 't' that allows the method to be nonlinearly
stable regardless of its accuracy. The resulting RKDG
methods are stable and high-order accurate. The L1 ,L2 and L∞ error
norm analysis shows that the scheme is highly accurate and effective.
Hence, the method is well suited to achieve high order accurate
solution for the scalar wave equation and other hyperbolic equations.
Abstract: The angular distribution of Compton scattering of two
quanta originating in the annihilation of a positron with an electron
is investigated as a quantum key distribution (QKD) mechanism in
the gamma spectral range. The geometry of coincident Compton
scattering is observed on the two sides as a way to obtain partially
correlated readings on the quantum channel. We derive the noise
probability density function of a conceptually equivalent prepare
and measure quantum channel in order to evaluate the limits of the
concept in terms of the device secrecy capacity and estimate it at
roughly 1.9 bits per 1 000 annihilation events. The high error rate
is well above the tolerable error rates of the common reconciliation
protocols; therefore, the proposed key agreement protocol by public
discussion requires key reconciliation using classical error-correcting
codes. We constructed a prototype device based on the readily
available monolithic detectors in the least complex setup.
Abstract: It is well known that the channel capacity of Multiple-
Input-Multiple-Output (MIMO) system increases as the number of
antenna pairs between transmitter and receiver increases but it suffers
from multiple expensive RF chains. To reduce the cost of RF chains,
Antenna Selection (AS) method can offer a good tradeoff between
expense and performance. In a transmitting AS system, Channel
State Information (CSI) feedback is necessarily required to choose
the best subset of antennas in which the effects of delays and errors
occurred in feedback channels are the most dominant factors
degrading the performance of the AS method. This paper presents the
concept of AS method using CSI from channel reciprocity instead of
feedback method. Reciprocity technique can easily archive CSI by
utilizing a reverse channel where the forward and reverse channels
are symmetrically considered in time, frequency and location. In this
work, the capacity performance of MIMO system when using AS
method at transmitter with reciprocity channels is investigated by
own developing Testbed. The obtained results show that reciprocity
technique offers capacity close to a system with a perfect CSI and
gains a higher capacity than a system without AS method from 0.9 to
2.2 bps/Hz at SNR 10 dB.