Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: Image fusion aims to enhance the perception
of a scene by combining important information captured by
different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been
thouroughly investigated for image fusion, since it takes advantages
of approximate shift invariance and direction selectivity. But it can
only handle limited direction information. To allow a more flexible
directional expansion for images, we propose a novel fusion scheme,
referred to as complex contourlet transform (CCT). It successfully
incorporates directional filter banks (DFB) into DT-CWT. As a result
it efficiently deal with images containing contours and textures,
whereas it retains the property of shift invariance. Experimental
results demonstrated that the method features high quality fusion
performance and can facilitate many image processing applications.
Abstract: Performance of a dual maximal ratio combining
receiver has been analyzed for M-ary coherent and non-coherent
modulations over correlated Nakagami-m fading channels with nonidentical
and arbitrary fading parameter. The classical probability
density function (PDF) based approach is used for analysis.
Expressions for outage probability and average symbol error
performance for M-ary coherent and non-coherent modulations have
been obtained. The obtained results are verified against the special
case published results and found to be matching. The effect of the
unequal fading parameters, branch correlation and unequal input
average SNR on the receiver performance has been studied.
Abstract: In this paper present a sensorless maximum wind power extraction for variable speed constant frequency (VSCF) wind power generation systems with a doubly-fed induction generators (DFIG), to ensure stability and to impose the ideal feedback control solution despite of model uncertainties , using the principles of an active and reactive power controller (DPC) a robust sliding mode power control has been proposed to guarantees fast response times and precise control actions for control the active and reactive power independently. The simulation results in MATLAB/Simulink platform confirmed the good dynamic performance of power control approach for DFIGbased variable speed wind turbines.
Abstract: Landfill gas, particularly methane is one of the
greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from
simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy
soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor
followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at
acidification stage as indicated by the leachate quality with COD as
high as 55,511 mg/L and pH as low as 5.1. However, methanogenic
environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation.
Leachate degradation took place as the leachate moved through the
sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas
production from landfill by an in-situ degradation of leachate in the
sand at the bottom of the landfill.
Abstract: Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.
Abstract: There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.
Abstract: We report the electronic structure and optical
properties of NdF3 compound. Our calculations are based on density
functional theory (DFT) using the full potential linearized augmented
plane wave (FPLAPW) method with the inclusion of spin orbit
coupling. We employed the local spin density approximation (LSDA)
and Coulomb-corrected local spin density approximation, known for
treating the highly correlated 4f electrons properly, is able to
reproduce the correct insulating ground state. We find that the
standard LSDA approach is incapable of correctly describing the
electronic properties of such materials since it positions the f-bands
incorrectly resulting in an incorrect metallic ground state. On the
other hand, LSDA + U approximation, known for treating the highly
correlated 4f electrons properly, is able to reproduce the correct
insulating ground state. Interestingly, however, we do not find any
significant differences in the optical properties calculated using
LSDA, and LSDA + U suggesting that the 4f electrons do not play a
decisive role in the optical properties of these compounds. The
reflectivity for NdF3 compound stays low till 7 eV which is
consistent with their large energy gaps. The calculated energy gaps
are in good agreement with experiments. Our calculated reflectivity
compares well with the experimental data and the results are analyzed
in the light of band to band transitions.
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Abstract: Radiolabeled cyclic RGD peptides targeting integrin αvβ3 are reported as promising agents for the early diagnosis of metastatic tumors. With an aim to improve tumor uptake and retention of the peptide, cyclic RGD peptide dimer E[c (RGDfK)] 2 (E = Glutamic acid, f = phenyl alanine, K = lysine) coupled to the bifunctional chelator DOTA was custom synthesized and radiolabelled with 68Ga. Radiolabelling of cyclic RGD peptide dimer with 68Ga was carried out using HEPES buffer and biological evaluation of the complex was done in nude mice bearing HT29 tumors.
Abstract: The objective of the present paper is a numerical
analysis of the flow forces acting on spool surfaces of a pressure
regulated valve. The transient, compressible and turbulent flow
structures inside the valve are simulated using ANSYS FLUENT
coupled with a special UDF. Here, valve inlet pressure is varied in a
stepwise manner. For every value of inlet pressure, transient analysis
leads to a quasi-static flow through the valve. Spool forces are
calculated based on different pressures at inlet. From this information
of spool forces, pressure characteristic of the passive control circuit
has been derived.
Abstract: In this document, we have proposed a robust
conceptual strategy, in order to improve the robustness against the manufacturing defects and thus the reliability of logic CMOS circuits. However, in order to enable the use of future CMOS
technology nodes this strategy combines various types of design:
DFR (Design for Reliability), techniques of tolerance: hardware
redundancy TMR (Triple Modular Redundancy) for hard error
tolerance, the DFT (Design for Testability. The Results on largest ISCAS and ITC benchmark circuits show that our approach improves
considerably the reliability, by reducing the key factors, the area costs and fault tolerance probability.
Abstract: Waste management is now a global concern due to its
high environmental impact on climate change. Because of generating
huge amount of waste through our daily activities, managing waste in
an efficient way has become more important than ever. Alternative
Waste Technology (AWT), a new category of waste treatment
technology has been developed for energy recovery in recent years to
address this issue. AWT describes a technology that redirects waste
away from landfill, recovers more useable resources from the waste
flow and reduces the impact on the surroundings. Australia is one of
the largest producers of waste per-capita. A number of AWTs are
using in Australia to produce energy from waste. Presently, it is vital
to identify an appropriate AWT to establish a sustainable waste
management system in Australia. Identification of an appropriate
AWT through Multi-criteria analysis (MCA) of four AWTs by using
five key decision making criteria is presented and discussed in this
paper.
Abstract: Well-being has been given special emphasis in quality
of life. It involves living a meaningful, life satisfaction, stability and
happiness in life. Well-being also concerns the satisfaction of
physical, psychological, social needs and demands of an individual.
The purpose of this study was to validate three-factor measurement
model of well-being using structural equation modeling (SEM). The
conceptions of well-being measured such dimensions as physical,
psychological and social well-being. This study was done based on a
total sample of 650 adolescents from east-coast of peninsular
Malaysia. The Well-Being Scales which was adapted from [1] was
used in this study. The items were hypothesized a priori to have nonzero
loadings on all dimensions in the model. The findings of the
SEM demonstrated that it is a good fitting model which the proposed
model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998;
TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR)
was .93 and average variance extracted (AVE) was 58%. The model
in this study fits with the sample of data and well-being is important
to bring sustainable development to the mainstream.
Abstract: In this project electrical and optical properties of
BaZrO3 have been accomplished through the full-potential
linear augmented plane wave (FP-LAPW) by applying Wein2k
software. In this study band structure, density of state, gap energy,
refractive index and optical conduction have been studied. The results
of calculations show that BaZrO3 is an insulator with an indirect gap
in which 3.2 ev and studied refractive index equal 2.07. These results
are in accordance with the ones obtained in experimental researches.
Abstract: Hearing impairment is the number one chronic
disability affecting many people in the world. Background noise is
particularly damaging to speech intelligibility for people with
hearing loss especially for sensorineural loss patients. Several
investigations on speech intelligibility have demonstrated
sensorineural loss patients need 5-15 dB higher SNR than the normal
hearing subjects. This paper describes Discrete Hartley Transform
Power Normalized Least Mean Square algorithm (DHT-LMS) to
improve the SNR and to reduce the convergence rate of the Least
Means Square (LMS) for sensorineural loss patients. The DHT
transforms n real numbers to n real numbers, and has the convenient
property of being its own inverse. It can be effectively used for noise
cancellation with less convergence time. The simulated result shows
the superior characteristics by improving the SNR at least 9 dB for
input SNR with zero dB and faster convergence rate (eigenvalue ratio
12) compare to time domain method and DFT-LMS.
Abstract: Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.
Abstract: The objectives of this study are to determine the
effects of soil cover type on characteristics of leachates generated
from landfill lysimeters. Four lysimeters with diameter and height
of 0.15 and 3.00 m, respectively, were prepared. Three lysimeters
were filled with municipal waste and three different cover soil types
i.e. sandy loam soil, silty loam soil and clay soil while another
lysimeter was filled solely with municipal waste. The study was
conducted in the rainy season. Leachate quantities were measured
every day and leachate characteristics were determined once a week.
The cumulative leachate quantity from the lysimeter filled solely
with municipal waste was found to be around 27% higher than the
lysimeters using cover soils. There were no any differences of the
cumulative leachate amounts generated from the lysimeters using
three types of soils. The comparison of the total mass of pollutants
generated from all lysimeters showed that the lysimeter filled solely
with municipal waste generated the maximum quantities of
pollutants. Among the lysimeters using different types of soils, the
lysimeter using sandy loam soil generated the lowest amount of most
of pollutants, compared with the lysimeters using silty loam and clay
soils. It can be concluded that in term of pollutant attenuation in the
leachate, a sandy loam is the most suitable soil to be used as a cover
soil in the landfill.
Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).
Abstract: Aim of this work was to compare the efficacy of two
loading methods of proteins onto polymeric nanocarriers: adsorption
and encapsulation methods. Preliminary studies of protein loading
were done using Bovine Serum Albumin (BSA) as model protein.
Nanocarriers were prepared starting from polylactic co-glycolic acid
(PLGA) polymer; production methods used are two different variants
of emulsion evaporation method. Nanoparticles obtained were
analyzed in terms of dimensions by Dynamic Light Scattering and
Loading Efficiency of BSA by Bradford Assay. Loaded
nanoparticles were then submitted to in-vitro protein dissolution test
in order to study the effect of the delivery system on the release rate
of the protein.