Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: Certifications such as the Passive House Standard aim to reduce the final space heating energy demand of residential buildings. Space conditioning, notably heating, is responsible for nearly 70% of final residential energy consumption in Europe. There is therefore significant scope for the reduction of energy consumption through improvements to the energy efficiency of residential buildings. However, these certifications totally overlook the energy embodied in the building materials used to achieve this greater operational energy efficiency. The large amount of insulation and the triple-glazed high efficiency windows require a significant amount of energy to manufacture. While some previous studies have assessed the life cycle energy demand of passive houses, including their embodied energy, these rely on incomplete assessment techniques which greatly underestimate embodied energy and can lead to misleading conclusions. This paper analyses the embodied and operational energy demands of a case study passive house using a comprehensive hybrid analysis technique to quantify embodied energy. Results show that the embodied energy is much more significant than previously thought. Also, compared to a standard house with the same geometry, structure, finishes and number of people, a passive house can use more energy over 80 years, mainly due to the additional materials required. Current building energy efficiency certifications should widen their system boundaries to include embodied energy in order to reduce the life cycle energy demand of residential buildings.
Abstract: The main purpose of this study is to provide a detailed
statistical overview of the time and regional distribution, relative
timing occurrence of economic crises and government changes in 51
economies over the 1990–2007 periods. At the same time, the
predictive power of the economic crises on set government changes
will be examined using “signal approach".
The result showed that the percentage of government changes is
highest in transition economies (86 percent of observations) and
lowest in Latin American economies (39 percent of observations).
The percentages of government changes are same in both developed
and developing countries (43 percent of observations). However,
average crises per year (frequency of crises) are higher (lower) in
developing (developed) countries than developed (developing)
countries. Also, the predictive power of economic crises about the
onset of a government change is highest in Transition economies (81
percent) and lowest in Latin American countries (30 percent). The
predictive power of economic crises in developing countries (43
percent) is lower than developed countries (55 percent).
Abstract: The symmetric solution set Σ sym is the set of all solutions to the linear systems Ax = b, where A is symmetric and lies between some given bounds A and A, and b lies between b and b. We present a contractor for Σ sym, which is an iterative method that starts with some initial enclosure of Σ sym (by means of a cartesian product of intervals) and sequentially makes the enclosure tighter. Our contractor is based on polyhedral approximation and solving a series of linear programs. Even though it does not converge to the optimal bounds in general, it may significantly reduce the overestimation. The efficiency is discussed by a number of numerical experiments.
Abstract: RF performance of SOI CMOS device has attracted
significant amount of interest recently. In order to improve RF
parameters, Strained Si/Relaxed Si0.8Ge0.2 investigated as a
replacement for Si technology .Enhancement of carrier mobility
associated with strain engineering makes Strained Si a promising
candidate for improving RF performance of CMOS technology.
From the simulation, the cut-off frequency is estimated to be 224
GHZ, whereas in SOI at similar bias is about 188 GHZ. Therefore,
Strained Si exhibits 19% improvement in cut-off frequency over
similar Si counterpart. In this paper, Ion/Ioff ratio is studied as one of
the key parameters in logic and digital application. Strained Si/SiGe
demonstrates better Ion/Ioff characteristic than SOI, in similar channel
length of 100 nm.Another important key analog figures of merit such
as Early Voltage (VEA) ,transconductance vs drain current (gm /Ids)
are studied. They introduce the efficiency of the devices to convert
dc power into ac frequency.
Abstract: The modern telecommunication industry demands
higher capacity networks with high data rate. Orthogonal frequency
division multiplexing (OFDM) is a promising technique for high data
rate wireless communications at reasonable complexity in wireless
channels. OFDM has been adopted for many types of wireless
systems like wireless local area networks such as IEEE 802.11a, and
digital audio/video broadcasting (DAB/DVB). The proposed research
focuses on a concatenated coding scheme that improve the
performance of OFDM based wireless communications. It uses a
Redundant Residue Number System (RRNS) code as the outer code
and a convolutional code as the inner code. Here, a direct conversion
of analog signal to residue domain is done to reduce the conversion
complexity using sigma-delta based parallel analog-to-residue
converter. The bit error rate (BER) performances of the proposed
system under different channel conditions are investigated. These
include the effect of additive white Gaussian noise (AWGN),
multipath delay spread, peak power clipping and frame start
synchronization error. The simulation results show that the proposed
RRNS-Convolutional concatenated coding (RCCC) scheme provides
significant improvement in the system performance by exploiting the
inherent properties of RRNS.
Abstract: Selection of maize (Zea mays) hybrids with wide adaptability across diverse farming environments is important, prior to recommending them to achieve a high rate of hybrid adoption. Grain yield of 14 maize hybrids, tested in a randomized completeblock design with four replicates across 22 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and mega-environment identification. The objectives of this study were (i) identification of suitable hybrids with both high mean performance and high stability (ii) to determine mega-environments for maize production in Iran. Biplot analysis identifies two mega-environments in this study. The first mega-environments included KRM, KSH, MGN, DZF A, KRJ, DRB, DZF B, SHZ B, and KHM, where G10 hybrid was the best performing hybrid. The second mega-environment included ESF B, ESF A, and SHZ A, where G4 hybrid was the best hybrid. According to the ideal-hybrid biplot, G10 hybrid was better than all other hybrids, followed by the G1 and G3 hybrids. These hybrids were identified as best hybrids that have high grain yield and high yield stability. GGE biplot analysis provided a framework for identifying the target testing locations that discriminates genotypes that are high yielding and stable.
Abstract: Crucial information barely visible to the human eye is
often embedded in a series of low resolution images taken of the
same scene. Super resolution reconstruction is the process of
combining several low resolution images into a single higher
resolution image. The ideal algorithm should be fast, and should add
sharpness and details, both at edges and in regions without adding
artifacts. In this paper we propose a super resolution blind
reconstruction technique for linearly degraded images. In our
proposed technique the algorithm is divided into three parts an image
registration, wavelets based fusion and an image restoration. In this
paper three low resolution images are considered which may sub
pixels shifted, rotated, blurred or noisy, the sub pixel shifted images
are registered using affine transformation model; A wavelet based
fusion is performed and the noise is removed using soft thresolding.
Our proposed technique reduces blocking artifacts and also
smoothens the edges and it is also able to restore high frequency
details in an image. Our technique is efficient and computationally
fast having clear perspective of real time implementation.
Abstract: The operation performance of a valveless micro-pump
is strongly dependent on the shape of connected nozzle/diffuser and
Reynolds number. The aims of present work are to compare the
performance curves of micropump with the original straight
nozzle/diffuser and contoured nozzle/diffuser under different back
pressure conditions. The tested valveless micropumps are assembled
of five pieces of patterned PMMA plates with hot-embracing
technique. The structures of central chamber, the inlet/outlet
reservoirs and the connected nozzle/diffuser are fabricated with laser
cutting machine. The micropump is actuated with circular-type PZT
film embraced on the bottom of central chamber. The deformation of
PZT membrane with various input voltages is measured with a
displacement laser probe. A simple testing facility is also constructed
to evaluate the performance curves for comparison.
In order to observe the evaluation of low Reynolds number
multiple vortex flow patterns within the micropump during suction
and pumping modes, the unsteady, incompressible laminar
three-dimensional Reynolds-averaged Navier-Stokes equations are
solved. The working fluid is DI water with constant thermo-physical
properties. The oscillating behavior of PZT film is modeled with the
moving boundary wall in way of UDF program. With the dynamic
mesh method, the instants pressure and velocity fields are obtained
and discussed.Results indicated that the volume flow rate is not
monotony increased with the oscillating frequency of PZT film,
regardless of the shapes of nozzle/diffuser. The present micropump
can generate the maximum volume flow rate of 13.53 ml/min when
the operation frequency is 64Hz and the input voltage is 140 volts.
The micropump with contoured nozzle/diffuser can provide 7ml/min
flow rate even when the back pressure is up to 400 mm-H2O. CFD
results revealed that the flow central chamber was occupied with
multiple pairs of counter-rotating vortices during suction and
pumping modes. The net volume flow rate over a complete
oscillating periodic of PZT
Abstract: In this paper we present a novel approach for human
Body configuration based on the Silhouette. We propose to address
this problem under the Bayesian framework. We use an effective
Model based MCMC (Markov Chain Monte Carlo) method to solve
the configuration problem, in which the best configuration could be
defined as MAP (maximize a posteriori probability) in Bayesian
model. This model based MCMC utilizes the human body model to
drive the MCMC sampling from the solution space. It converses the
original high dimension space into a restricted sub-space constructed
by the human model and uses a hybrid sampling algorithm. We
choose an explicit human model and carefully select the likelihood
functions to represent the best configuration solution. The
experiments show that this method could get an accurate
configuration and timesaving for different human from multi-views.
Abstract: This study was investigated on sampling and
analyzing water quality in water reservoir & water tower installed in
two kind of residential buildings and school facilities. Data of water
quality was collected for correlation analysis with frequency of
sanitization of water reservoir through questioning managers of
building about the inspection charts recorded on equipment for water
reservoir. Statistical software packages (SPSS) were applied to the
data of two groups (cleaning frequency and water quality) for
regression analysis to determine the optimal cleaning frequency of
sanitization. The correlation coefficient (R) in this paper represented
the degree of correlation, with values of R ranging from +1 to -1.After
investigating three categories of drinking water users; this study found
that the frequency of sanitization of water reservoir significantly
influenced the water quality of drinking water. A higher frequency of
sanitization (more than four times per 1 year) implied a higher quality
of drinking water. Results indicated that sanitizing water reservoir &
water tower should at least twice annually for achieving the aim of
safety of drinking water.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: We have measured the pressure drop and convective
heat transfer coefficient of water – based AL(25nm),AL2O3(30nm)
and CuO(50nm) Nanofluids flowing through a uniform heated
circular tube in the fully developed laminar flow regime. The
experimental results show that the data for Nanofluids friction factor
show a good agreement with analytical prediction from the Darcy's
equation for single-phase flow. After reducing the experimental
results to the form of Reynolds, Rayleigh and Nusselt numbers. The
results show the local Nusselt number and temperature have
distribution with the non-dimensional axial distance from the tube
entry. Study decided that thenNanofluid as Newtonian fluids through
the design of the linear relationship between shear stress and the rate
of stress has been the study of three chains of the Nanofluid with
different concentrations and where the AL, AL2O3 and CuO – water
ranging from (0.25 - 2.5 vol %). In addition to measuring the four
properties of the Nanofluid in practice so as to ensure the validity of
equations of properties developed by the researchers in this area and
these properties is viscosity, specific heat, and density and found that
the difference does not exceed 3.5% for the experimental equations
between them and the practical. The study also demonstrated that the
amount of the increase in heat transfer coefficient for three types of
Nano fluid is AL, AL2O3, and CuO – Water and these ratios are
respectively (45%, 32%, 25%) with insulation and without insulation
(36%, 23%, 19%), and the statement of any of the cases the best
increase in heat transfer has been proven that using insulation is
better than not using it. I have been using three types of Nano
particles and one metallic Nanoparticle and two oxide Nanoparticle
and a statement, whichever gives the best increase in heat transfer.
Abstract: This paper presents an advance in monitoring and
process control of surface roughness in CNC machine for the turning
and milling processes. An integration of the in-process monitoring
and process control of the surface roughness is proposed and
developed during the machining process by using the cutting force
ratio. The previously developed surface roughness models for turning
and milling processes of the author are adopted to predict the inprocess
surface roughness, which consist of the cutting speed, the
feed rate, the tool nose radius, the depth of cut, the rake angle, and
the cutting force ratio. The cutting force ratios obtained from the
turning and the milling are utilized to estimate the in-process surface
roughness. The dynamometers are installed on the tool turret of CNC
turning machine and the table of 5-axis machining center to monitor
the cutting forces. The in-process control of the surface roughness
has been developed and proposed to control the predicted surface
roughness. It has been proved by the cutting tests that the proposed
integration system of the in-process monitoring and the process
control can be used to check the surface roughness during the cutting
by utilizing the cutting force ratio.
Abstract: 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) catalyzes the conversion of HMG-CoA to mevalonate using NADPH and the enzyme is involved in rate-controlling step of mevalonate. Inhibition of HMGR is considered as effective way to lower cholesterol levels so it is drug target to treat hypercholesterolemia, major risk factor of cardiovascular disease. To discover novel HMGR inhibitor, we performed structure-based pharmacophore modeling combined with molecular dynamics (MD) simulation. Four HMGR inhibitors were used for MD simulation and representative structure of each simulation were selected by clustering analysis. Four structure-based pharmacophore models were generated using the representative structure. The generated models were validated used in virtual screening to find novel scaffolds for inhibiting HMGR. The screened compounds were filtered by applying drug-like properties and used in molecular docking. Finally, four hit compounds were obtained and these complexes were refined using energy minimization. These compounds might be potential leads to design novel HMGR inhibitor.
Abstract: The problem of robust stability and robust stabilization for a class of discrete-time uncertain systems with time delay is investigated. Based on Tchebychev inequality, by constructing a new augmented Lyapunov function, some improved sufficient conditions ensuring exponential stability and stabilization are established. These conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. Compared with some previous results derived in the literature, the new obtained criteria have less conservatism. Two numerical examples are provided to demonstrate the improvement and effectiveness of the proposed method.
Abstract: This paper explores the effectiveness of machine
learning techniques in detecting firms that issue fraudulent financial
statements (FFS) and deals with the identification of factors
associated to FFS. To this end, a number of experiments have been
conducted using representative learning algorithms, which were
trained using a data set of 164 fraud and non-fraud Greek firms in the
recent period 2001-2002. The decision of which particular method to
choose is a complicated problem. A good alternative to choosing
only one method is to create a hybrid forecasting system
incorporating a number of possible solution methods as components
(an ensemble of classifiers). For this purpose, we have implemented
a hybrid decision support system that combines the representative
algorithms using a stacking variant methodology and achieves better
performance than any examined simple and ensemble method. To
sum up, this study indicates that the investigation of financial
information can be used in the identification of FFS and underline the
importance of financial ratios.
Abstract: In this paper we propose a family of algorithms based
on 3rd and 4th order cumulants for blind single-input single-output
(SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR)
channel estimation driven by non-Gaussian signal. The input signal
represents the signal used in 10GBASE-T (or IEEE 802.3an-2006)
as a Tomlinson-Harashima Precoded (THP) version of random
Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The
proposed algorithms are tested using three non-minimum phase
channel for different Signal-to-Noise Ratios (SNR) and for different
data input length. Numerical simulation results are presented to
illustrate the performance of the proposed algorithms.
Abstract: Grid composite structures have many applications in aerospace industry in which deal with transverse loadings abundantly. In present paper a stiffened composite cylindrical shell with clamped-free boundary condition under transverse end load experimentally and numerically was studied. Some electrical strain gauges were employed to measure the strains. Also a finite element analysis was done for validation of experimental result. The FEM software used was ANSYS11. In addition, the results between stiffened composite shell and unstiffened composite shell were compared. It was observed that intersection of two stiffeners has an important effect in decrease of stress in the shell. Fairly good agreements were observed between the numerical and the measured results. According to recent studies about grid composite structures, it should be noted that any investigation like this research has not been reported.
Abstract: System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.