Abstract: It has been established that microRNAs (miRNAs) play
an important role in gene expression by post-transcriptional regulation
of messengerRNAs (mRNAs). However, the precise relationships
between microRNAs and their target genes in sense of numbers,
types and biological relevance remain largely unclear. Dissecting the
miRNA-target relationships will render more insights for miRNA
targets identification and validation therefore promote the understanding
of miRNA function. In miRBase, miRanda is the key
algorithm used for target prediction for Zebrafish. This algorithm
is high-throughput but brings lots of false positives (noise). Since
validation of a large scale of targets through laboratory experiments
is very time consuming, several computational methods for miRNA
targets validation should be developed. In this paper, we present an
integrative method to investigate several aspects of the relationships
between miRNAs and their targets with the final purpose of extracting
high confident targets from miRanda predicted targets pool. This is
achieved by using the techniques ranging from statistical tests to
clustering and association rules. Our research focuses on Zebrafish.
It was found that validated targets do not necessarily associate with
the highest sequence matching. Besides, for some miRNA families,
the frequency of their predicted targets is significantly higher in the
genomic region nearby their own physical location. Finally, in a case
study of dre-miR-10 and dre-miR-196, it was found that the predicted
target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR-
10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar
characteristics as validated target genes and therefore represent high
confidence target candidates.
Abstract: In this paper, Steam Assisted Gravity Drainage
(SAGD) is introduced and its advantages over ordinary steam
injection is demonstrated. A simple simulation model is built and
three scenarios of natural production, ordinary steam injection, and
SAGD are compared in terms of their cumulative oil production and
cumulative oil steam ratio. The results show that SAGD can
significantly enhance oil production in quite a short period of time.
However, since the distance between injection and production wells
is short, the oil to steam ratio decreases gradually through time.
Abstract: A new code synchronization algorithm is proposed in
this paper for the secondary cell-search stage in wideband CDMA
systems. Rather than using the Cyclically Permutable (CP) code in the
Secondary Synchronization Channel (S-SCH) to simultaneously
determine the frame boundary and scrambling code group, the new
synchronization algorithm implements the same function with less
system complexity and less Mean Acquisition Time (MAT). The
Secondary Synchronization Code (SSC) is redesigned by splitting into
two sub-sequences. We treat the information of scrambling code group
as data bits and use simple time diversity BCH coding for further
reliability. It avoids involved and time-costly Reed-Solomon (RS)
code computations and comparisons. Analysis and simulation results
show that the Synchronization Error Rate (SER) yielded by the new
algorithm in Rayleigh fading channels is close to that of the
conventional algorithm in the standard. This new synchronization
algorithm reduces system complexities, shortens the average
cell-search time and can be implemented in the slot-based cell-search
pipeline. By taking antenna diversity and pipelining correlation
processes, the new algorithm also shows its flexible application in
multiple antenna systems.
Abstract: The objective of this work is to show a procedure for
mesh generation in a fluidized bed using large eddy simulations
(LES) of a filtered two-fluid model. The experimental data were
obtained by [1] in a laboratory fluidized bed. Results show that it is
possible to use mesh with less cells as compared to RANS turbulence
model with granular kinetic theory flow (KTGF). Also, the numerical
results validate the experimental data near wall of the bed, which
cannot be predicted by RANS.model.
Abstract: In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.
Abstract: Multi-loop (De-centralized) Proportional-Integral-
Derivative (PID) controllers have been used extensively in process
industries due to their simple structure for control of multivariable
processes. The objective of this work is to design multiple-model
adaptive multi-loop PID strategy (Multiple Model Adaptive-PID)
and neural network based multi-loop PID strategy (Neural Net
Adaptive-PID) for the control of multivariable system. The first
method combines the output of multiple linear PID controllers,
each describing process dynamics at a specific level of operation.
The global output is an interpolation of the individual multi-loop
PID controller outputs weighted based on the current value of the
measured process variable. In the second method, neural network
is used to calculate the PID controller parameters based on the
scheduling variable that corresponds to major shift in the process
dynamics. The proposed control schemes are simple in structure with
less computational complexity. The effectiveness of the proposed
control schemes have been demonstrated on the CSTR process,
which exhibits dynamic non-linearity.
Abstract: This paper describes a novel monitoring scheme to
minimize total active power in digital circuits depend on the demand
frequency, by adjusting automatically both supply voltage and
threshold voltages based on circuit operating conditions such as
temperature, process variations, and desirable frequency. The delay
monitoring results, will be control and apply so as to be maintained at
the minimum value at which the chip is able to operate for a given
clock frequency. Design details of power monitor are examined using
simulation framework in 32nm BTPM model CMOS process.
Experimental results show the overhead of proposed circuit in terms
of its power consumption is about 40 μW for 32nm technology;
moreover the results show that our proposed circuit design is not far
sensitive to the temperature variations and also process variations.
Besides, uses the simple blocks which offer good sensitivity, high
speed, the continuously feedback loop. This design provides up to
40% reduction in power consumption in active mode.
Abstract: In this paper, gate leakage current has been mitigated
by the use of novel nanoscale MOSFET with Source/Drain-to-Gate
Non-overlapped and high-k spacer structure for the first time. A
compact analytical model has been developed to study the gate
leakage behaviour of proposed MOSFET structure. The result
obtained has found good agreement with the Sentaurus Simulation.
Fringing gate electric field through the dielectric spacer induces
inversion layer in the non-overlap region to act as extended S/D
region. It is found that optimal Source/Drain-to-Gate Non-overlapped
and high-k spacer structure has reduced the gate leakage current to
great extent as compared to those of an overlapped structure. Further,
the proposed structure had improved off current, subthreshold slope
and DIBL characteristic. It is concluded that this structure solves the
problem of high leakage current without introducing the extra series
resistance.
Abstract: ZnS nanoparticles of different size have been
synthesized using a colloidal particles method. Zns nanoparticles
prepared with capping agent (mercaptoethanol) then were
characterized using X-ray diffraction (XRD) and UV-Vis
spectroscopy. The particle size of the nanoparticles calculated from
the XRD patterns has been found in the range 1.85-2.44nm.
Absorption spectra have been obtained using UV-Vis
spectrophotometer to find the optical band gap and the obtained
values have been founded to being range 3.83-4.59eV. It was also
found that energy band gap increase with the increase in molar
capping agent solution.
Abstract: This paper present a new method for design of power
system stabilizer (PSS) based on sliding mode control (SMC)
technique. The control objective is to enhance stability and improve
the dynamic response of the multi-machine power system. In order to
test effectiveness of the proposed scheme, simulation will be carried
out to analyze the small signal stability characteristics of the system
about the steady state operating condition following the change in
reference mechanical torque and also parameters uncertainties. For
comparison, simulation of a conventional control PSS (lead-lag
compensation type) will be carried out. The main approach is
focusing on the control performance which later proven to have the
degree of shorter reaching time and lower spike.
Abstract: The requirements analysis, modeling, and simulation have consistently been one of the main challenges during the development of complex systems. The scenarios and the state machines are two successful models to describe the behavior of an interactive system. The scenarios represent examples of system execution in the form of sequences of messages exchanged between objects and are a partial view of the system. In contrast, state machines can represent the overall system behavior. The automation of processing scenarios in the state machines provide some answers to various problems such as system behavior validation and scenarios consistency checking. In this paper, we propose a method for translating scenarios in state machines represented by Discreet EVent Specification and procedure to detect implied scenarios. Each induced DEVS model represents the behavior of an object of the system. The global system behavior is described by coupling the atomic DEVS models and validated through simulation. We improve the validation process with integrating formal methods to eliminate logical inconsistencies in the global model. For that end, we use the Z notation.
Abstract: Authentication of multimedia contents has gained much attention in recent times. In this paper, we propose a secure semi-fragile watermarking, with a choice of two watermarks to be embedded. This technique operates in integer wavelet domain and makes use of semi fragile watermarks for achieving better robustness. A self-recovering algorithm is employed, that hides the image digest into some Wavelet subbands to detect possible malevolent object manipulation undergone by the image (object replacing and/or deletion). The Semi-fragility makes the scheme tolerant for JPEG lossy compression as low as quality of 70%, and locate the tempered area accurately. In addition, the system ensures more security because the embedded watermarks are protected with private keys. The computational complexity is reduced using parameterized integer wavelet transform. Experimental results show that the proposed scheme guarantees the safety of watermark, image recovery and location of the tempered area accurately.
Abstract: Open urban public spaces comprise an important
element for the development of social, cultural and economic
activities of the population in the modern cities. These spaces are also
considered regulators of the region-s climate conditions, providing
better thermal, visual and auditory conditions which can be optimized
by the application of appropriate strategies of bioclimatic design. The
paper focuses on the analysis and evaluation of the recent unification
of the open spaces in the centre of Xanthi, a medium – size city in
northern Greece, from a bioclimatic perspective, as well as in the
creation of suitable methodology. It is based both on qualitative
observation of the interventions by fieldwork research and
assessment and on quantitative analysis and modeling of the research
area.
Abstract: Reentry trajectory optimization is a multi-constraints
optimal control problem which is hard to solve. To tackle it, we
proposed a new algorithm named CDEN(Constrained Differential
Evolution Newton-Raphson Algorithm) based on Differential Evolution(
DE) and Newton-Raphson.We transform the infinite dimensional
optimal control problem to parameter optimization which is finite
dimensional by discretize control parameter. In order to simplify
the problem, we figure out the control parameter-s scope by process
constraints. To handle constraints, we proposed a parameterless constraints
handle process. Through comprehensive analyze the problem,
we use a new algorithm integrated by DE and Newton-Raphson to
solve it. It is validated by a reentry vehicle X-33, simulation results
indicated that the algorithm is effective and robust.
Abstract: The Expert Witness Testimony in the Battered
Woman Syndrome Expert witness testimony (EWT) is a kind of
information given by an expert specialized in the field (here in BWS)
to the jury in order to help the court better understand the case. EWT
does not always work in favor of the battered women. Two main
decision-making models are discussed in the paper: the Mathematical
model and the Explanation model. In the first model, the jurors
calculate ″the importance and strength of each piece of evidence″
whereas in the second model they try to integrate the EWT with the
evidence and create a coherent story that would describe the crime.
The jury often misunderstands and misjudges battered women for
their action (or in this case inaction). They assume that these women
are masochists and accept being mistreated for if a man abuses a
woman constantly, she should and could divorce him or simply leave
at any time. The research in the domain found that indeed, expert
witness testimony has a powerful influence on juror’s decisions thus
its quality needs to be further explored. One of the important factors
that need further studies is a bias called the dispositionist worldview
(a belief that what happens to people is of their own doing). This
kind of attributional bias represents a tendency to think that a
person’s behavior is due to his or her disposition, even when the
behavior is clearly attributed to the situation. Hypothesis The
hypothesis of this paper is that if a juror has a dispositionist
worldview then he or she will blame the rape victim for triggering the
assault. The juror would therefore commit the fundamental
attribution error and believe that the victim’s disposition caused the
rape and not the situation she was in. Methods The subjects in the
study were 500 randomly sampled undergraduate students from
McGill, Concordia, Université de Montréal and UQAM.
Dispositional Worldview was scored on the Dispositionist
Worldview Questionnaire. After reading the Rape Scenarios, each
student was asked to play the role of a juror and answer a
questionnaire consisting of 7 questions about the responsibility,
causality and fault of the victim. Results The results confirm the
hypothesis which states that if a juror has a dispositionist worldview
then he or she will blame the rape victim for triggering the assault.
By doing so, the juror commits the fundamental attribution error
because he will believe that the victim’s disposition, and not the
constraints or opportunities of the situation, caused the rape scenario.
Abstract: Orthogonal frequency division multiplexing (OFDM)
has developed into a popular scheme for wideband digital
communications used in consumer applications such as digital broadcasting, wireless networking and broadband internet access. In
the OFDM system, carrier frequency offset (CFO) causes intercarrier
interference (ICI) which significantly degrades the system error performance. In this paper we provide an exact evaluation method for error performance analysis of arbitrary 2-D modulation OFDM systems with CFO, and analyze the effect of CFO on error performance.
Abstract: Estimation of stormwater pollutants is a pre-requisite
for the protection and improvement of the aquatic environment and
for appropriate management options. The usual practice for the
stormwater quality prediction is performed through water quality
modeling. However, the accuracy of the prediction by the models
depends on the proper estimation of model parameters. This paper
presents the estimation of model parameters for a catchment water
quality model developed for the continuous simulation of stormwater
pollutants from a catchment to the catchment outlet. The model is
capable of simulating the accumulation and transportation of the
stormwater pollutants; suspended solids (SS), total nitrogen (TN) and
total phosphorus (TP) from a particular catchment. Rainfall and water
quality data were collected for the Hotham Creek Catchment (HTCC),
Gold Coast, Australia. Runoff calculations from the developed model
were compared with the calculated discharges from the widely used
hydrological models, WBNM and DRAINS. Based on the measured
water quality data, model water quality parameters were calibrated
for the above-mentioned catchment. The calibrated parameters are
expected to be helpful for the best management practices (BMPs)
of the region. Sensitivity analyses of the estimated parameters were
performed to assess the impacts of the model parameters on overall
model estimations of runoff water quality.
Abstract: In contrast to existing of calculation of temperature field of a profile part a blade with convective cooling which are not taking into account multi connective in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM AND FDM) numerical methods from the point of view of a realization on the PC. The theoretical substantiation of these methods is proved by the appropriate theorems.
Abstract: Let M be an almost split quaternionic manifold on
which its almost split quaternionic structure is defined by a three
dimensional subbundle V of ( T M) T (M)
*
Ôèù and
{F,G,H} be a local basis for V . Suppose that the (global)
(1, 2) tensor field defined[V ,V ]is defined by
[V,V ] = [F,F]+[G,G] + [H,H], where [,] denotes
the Nijenhuis bracket. In ref. [7], for the almost split-hypercomplex
structureH = J α,α =1,2,3, and the Obata
connection ÔêçH
vanishes if and only if H is split-hypercomplex.
In this study, we give a prof, in particular, prove that if either
M is a split quaternionic Kaehler manifold, or if M is a splitcomplex
manifold with almost split-complex structure F , then the
vanishing [V ,V ] is equivalent to that of all the Nijenhuis brackets
of {F,G,H}. It follows that the bundle V is trivial if and only if
[V ,V ] = 0 .
Abstract: Two seperate experiments by barley and alfalfa were
conducted to a 2×8 factorial completely randomised design, with four
replicates. Factors were inoculation (M) with Gomus mosseae or uninoculation
(M0) and seven levels of contaminants (Co, Cd, Pb and
combinations) plus an uncontaminated control treatment (C). Heavy
metals in plant tissues and soil were quantified by Inductively
Coupled Plasma Optical Emission Spectrometer (ICP-OES) (Variant-
Liberty 150AX Turbo). Phytoextraction coefficient of contaminants
calculated by concentration of heavy metals in the shoot (mgkg-1) /
concentration of heavy metals in soil (mgkg-1). In the barley, the
highest rate of phytoextraction coefficient of Pb, Cd and Co was in
M0Pb, M0PbCoCd and MCo, respectively (P