Abstract: Chemical stabilization is a technique commonly used
to improve the expansive soil properties. In this regard, an attempt
has been made to evaluate the influence of Calcium Chloride (CaCl2)
stabilizer on the engineering properties of expansive soil. A series of
laboratory experiments including consistency limits, free swell,
compaction, and shear strength tests were performed to investigate
the effect of CaCl2 additive with various percentages 0%, 2%, 5%,
10% and 15% for improving expansive soil. The results obtained
shows that the increase in the percentage of CaCl2decreased the
liquid limit and plasticity index leading to significant reduction in the
free swell index. This, in turn, increased the maximum dry density
and decreased the optimum moisture content which results in greater
strength. The unconfined compressive strength of soil stabilized with
5% CaCl2 increased approximately by 50% as compared to virgin
soil. It can be concluded that CaCl2 had shown promising influence
on the strength and swelling properties of expansive soil, thereby
giving an advantage in improving problematic expansive soil.
Abstract: Background: The societal impact of antibiotic resistance is a major public health concern. The increase in incidence of resistant bacteria can ultimately be fatal. Objective: To analyse the appropriateness of antibiotic prescribing in Dundee Dental Hospital, ultimately improving the safety and quality of patient care. Methods: Two examiners independently crosschecked approximately fifty consecutive prescriptions, and corresponding patient case notes, for three data collection cycles between August 2014 – September 2015. The Scottish Dental Clinical Effectiveness Program (SDCEP) Drug Prescribing for Dentistry guidelines was the standard utilised. The criteria: clinical justification, regime justification and review arrangements was measured, and compared to the standard. Results: Cycle one revealed 42% of antibiotic prescriptions were appropriate. Interventions included: multiple staff meetings, introduction of a checklist attached to the prescription pack, and production of patient leaflets explaining indications for antibiotics. Cycle two and three revealed 44%, and 30% compliance, respectively. Conclusion: The results of the audit have yet to meet target standards set out in prescribing guidelines. However, steps are being taken and change has occurred on a cultural level.
Abstract: Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.
Abstract: Municipal Solid Waste (MSW) disposed in landfill sites decompose under anaerobic conditions and produce gases which mainly contain carbon dioxide (CO2) and methane (CH4). Methane has the potential of causing global warming 25 times more than CO2, and can potentially affect human life and environment. Thus, this research aims to determine MSW generation and the annual CH4 emissions from the generated waste in Oman over the years 1971-2030. The estimation of total waste generation was performed using existing models, while the CH4 emissions estimation was performed using the intergovernmental panel on climate change (IPCC) default method. It is found that total MSW generation in Oman might be reached 3,089 Gg in the year 2030, which approximately produced 85 Gg of CH4 emissions in the year 2030.
Abstract: This paper presents the confidence intervals for the
effect size base on bootstrap resampling method. The meta-analytic
confidence interval for effect size is proposed that are easy to
compute. A Monte Carlo simulation study was conducted to compare
the performance of the proposed confidence intervals with the
existing confidence intervals. The best confidence interval method
will have a coverage probability close to 0.95. Simulation results
have shown that our proposed confidence intervals perform well in
terms of coverage probability and expected length.
Abstract: This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.
Abstract: In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.
Abstract: Approximately 10,000 different types of dyes and
pigments are being used in various industrial applications yearly,
which include the textile and printing industries. However, these dyes
are difficult to degrade naturally once they enter the aquatic system.
Their high persistency in natural environment poses a potential health
hazard to all form of life. Hence, there is a need for alternative dye
removal strategy in the environment via bioremediation. In this study,
fungi laccase is investigated via commercial agar dyes plates and
submerged fermentation to explore the application of fungi laccase in
textile dye wastewater treatment. Two locally isolated basidiomycetes
were screened for laccase activity using media added with commercial
dyes such as 2, 2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid
(ABTS), guaiacol and Remazol Brillant Blue R (RBBR). Isolate TBB3
(1.70±0.06) and EL2 (1.78±0.08) gave the highest results for ABTS
plates with the appearance of greenish halo on around the isolates.
Submerged fermentation performed on Isolate TBB3 with the
productivity 3.9067 U/ml/day, whereas the laccase activity for Isolate
EL2 was much lower (0.2097 U/ml/day). As isolate TBB3 showed
higher laccase production, it was subjected to molecular
characterization by DNA isolation, PCR amplification and sequencing
of ITS region of nuclear ribosomal DNA. After being compared with
other sequences in National Center for Biotechnology Information
(NCBI database), isolate TBB3 is probably from species Trametes
hirsutei. Further research work can be performed on this isolate by
upscale the production of laccase in order to meet the demands of the
requirement for higher enzyme titer for the bioremediation of textile
dyes.
Abstract: Hydrologic models are increasingly used as tools to
predict stormwater quantity and quality from urban catchments.
However, due to a range of practical issues, most models produce
gross errors in simulating complex hydraulic and hydrologic systems.
Difficulty in finding a robust approach for model calibration is one of
the main issues. Though automatic calibration techniques are
available, they are rarely used in common commercial hydraulic and
hydrologic modelling software e.g. MIKE URBAN. This is partly
due to the need for a large number of parameters and large datasets in
the calibration process. To overcome this practical issue, a
framework for automatic calibration of a hydrologic model was
developed in R platform and presented in this paper. The model was
developed based on the time-area conceptualization. Four calibration
parameters, including initial loss, reduction factor, time of
concentration and time-lag were considered as the primary set of
parameters. Using these parameters, automatic calibration was
performed using Approximate Bayesian Computation (ABC). ABC is
a simulation-based technique for performing Bayesian inference
when the likelihood is intractable or computationally expensive to
compute. To test the performance and usefulness, the technique was
used to simulate three small catchments in Gold Coast. For
comparison, simulation outcomes from the same three catchments
using commercial modelling software, MIKE URBAN were used.
The graphical comparison shows strong agreement of MIKE URBAN
result within the upper and lower 95% credible intervals of posterior
predictions as obtained via ABC. Statistical validation for posterior
predictions of runoff result using coefficient of determination (CD),
root mean square error (RMSE) and maximum error (ME) was found
reasonable for three study catchments. The main benefit of using
ABC over MIKE URBAN is that ABC provides a posterior
distribution for runoff flow prediction, and therefore associated
uncertainty in predictions can be obtained. In contrast, MIKE
URBAN just provides a point estimate. Based on the results of the
analysis, it appears as though ABC the developed framework
performs well for automatic calibration.
Abstract: The out-of-band impedance environment is considered
to be of paramount importance in engineering the in-band impedance
environment. Presenting the frequency independent and constant outof-
band impedances across the wide modulation bandwidth is
extremely important for reliable device characterization for future
wireless systems. This paper presents an out-of-band impedance
optimization scheme based on simultaneous engineering of
significant baseband components IF1 (twice the modulation
frequency) and IF2 (four times the modulation frequency) and higher
baseband components such as IF3 (six times the modulation
frequency) and IF4 (eight times the modulation frequency) to
engineer the in-band impedance environment. The investigations
were carried out on a 10W GaN HEMT device driven to deliver a
peak envelope power of approximately 40.5dBm under modulated
excitation. The presentation of frequency independent baseband
impedances to all the significant baseband components whilst
maintaining the optimum termination for fundamental tones as well
as reactive termination for 2nd harmonic under class-J mode of
operation has outlined separate optimum impedances for best
intermodulation (IM) linearity.
Abstract: This paper proposes an APPLE scheme that aims at providing absolute and proportional throughput guarantees, and maximizing system throughput simultaneously for wireless LANs with homogeneous and heterogenous traffic. We formulate our objectives as an optimization problem, present its exact and approximate solutions, and prove the existence and uniqueness of the approximate solution. Simulations validate that APPLE scheme is accurate, and the approximate solution can well achieve the desired objectives already.
Abstract: Digital images are widely used in computer
applications. To store or transmit the uncompressed images
requires considerable storage capacity and transmission bandwidth.
Image compression is a means to perform transmission or storage of
visual data in the most economical way. This paper explains about
how images can be encoded to be transmitted in a multiplexing
time-frequency domain channel. Multiplexing involves packing
signals together whose representations are compact in the working
domain. In order to optimize transmission resources each 4 × 4
pixel block of the image is transformed by a suitable polynomial
approximation, into a minimal number of coefficients. Less than
4 × 4 coefficients in one block spares a significant amount of
transmitted information, but some information is lost. Different
approximations for image transformation have been evaluated as
polynomial representation (Vandermonde matrix), least squares +
gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev
polynomials or singular value decomposition (SVD). Results have
been compared in terms of nominal compression rate (NCR),
compression ratio (CR) and peak signal-to-noise ratio (PSNR)
in order to minimize the error function defined as the difference
between the original pixel gray levels and the approximated
polynomial output. Polynomial coefficients have been later encoded
and handled for generating chirps in a target rate of about two
chirps per 4 × 4 pixel block and then submitted to a transmission
multiplexing operation in the time-frequency domain.
Abstract: The nutritional composition and hypoglycaemic effect
of crackers produced from blend of sprouted pigeon pea, unripe
plantain and brewers’ spent grain and fed to Alloxan induced diabetic
rat was investigated. Crackers were produced from different blends of
sprouted pigeon pea, unripe plantain and brewers’ spent grain. The
crackers were evaluated for proximate composition, amino acid
profile and antinutritional factors. Blood glucose levels of normal and
diabetic rats fed with the control sample and different formulations of
cracker were measured. The protein content of the samples were
significantly different (p
Abstract: The paper presents a method in which the expert
knowledge is applied to fuzzy inference model. Even a less
experienced person could benefit from the use of such a system, e.g.
urban planners, officials. The analysis result is obtained in a very
short time, so a large number of the proposed locations can also be
verified in a short time. The proposed method is intended for testing
of locations of car parks in a city. The paper shows selected examples
of locations of the P&R facilities in cities planning to introduce the
P&R. The analyses of existing objects are also shown in the paper
and they are confronted with the opinions of the system users, with
particular emphasis on unpopular locations. The results of the
analyses are compared to expert analysis of the P&R facilities
location that was outsourced by the city and the opinions about
existing facilities users that were expressed on social networking
sites. The obtained results are consistent with actual users’ feedback.
The proposed method proves to be good, but does not require the
involvement of a large experts team and large financial contributions
for complicated research. The method also provides an opportunity to
show the alternative location of P&R facilities. Although the results
of the method are approximate, they are not worse than results of
analysis of employed experts. The advantage of this method is ease of
use, which simplifies the professional expert analysis. The ability of
analyzing a large number of alternative locations gives a broader
view on the problem. It is valuable that the arduous analysis of the
team of people can be replaced by the model's calculation. According
to the authors, the proposed method is also suitable for
implementation on a GIS platform.
Abstract: The aim of this work is to study the numerical
implementation of the Hilbert Uniqueness Method for the exact
boundary controllability of Euler-Bernoulli beam equation. This study
may be difficult. This will depend on the problem under consideration
(geometry, control and dimension) and the numerical method used.
Knowledge of the asymptotic behaviour of the control governing the
system at time T may be useful for its calculation. This idea will
be developed in this study. We have characterized as a first step, the
solution by a minimization principle and proposed secondly a method
for its resolution to approximate the control steering the considered
system to rest at time T.
Abstract: By using a fixed point theorem of a sum operator, the
existence and uniqueness of positive solution for a class of
boundary value problem of nonlinear fractional differential equation
is studied. An iterative scheme is constructed to approximate it.
Finally, an example is given to illustrate the main result.
Abstract: This study investigated the effects of thermal
treatment on Tualang honey sample in terms of honey colour and
heat-induced small metabolites. The heating process was carried out
in a temperature controlled water batch at 90oC for 4 hours. The
honey samples were put in cylinder tubes with the dimension of 1 cm
diameter and 10 cm length for homogenous heat transfer. The results
found that the thermal treatment produced not only
hydroxylmethylfurfural, but also other harmful substances such as
phthalic anhydride and radiolytic byproducts. The degradation of
honey protein was due to the detection of free amino acids such as
cysteine and phenylalanine in heat-treated honey samples. Sugar
dehydration was also occurred because fragmented di-galactose was
identified based on the presence of characteristic ions in the mass
fragmentation pattern. The honey colour was found getting darker as
the heating duration was increased up to 4 hours. Approximately, 60
mm PFund of increment was noticed for the honey colour with the
colour change rate of 14.8 mm PFund per hour. Based on the
principal component analysis, the score plot clearly shows that the
chemical profile of Tualang honey was significantly altered after 2
hours of heating at 90oC.
Abstract: In order to utilize results from global climate models,
dynamical and statistical downscaling techniques have been
developed. For dynamical downscaling, usually a limited area
numerical model is used, with associated high computational cost.
This research proposes dynamic equation for specific space-time
regional climate downscaling from the Educational Global Climate
Model (EdGCM) for Southeast Asia. The equation is for surface air
temperature. This equation provides downscaling values of surface
air temperature at any specific location and time without running a
regional climate model. In the proposed equations, surface air
temperature is approximated from ground temperature, sensible heat
flux and 2m wind speed. Results from the application of the equation
show that the errors from the proposed equations are less than the
errors for direct interpolation from EdGCM.
Abstract: One of the global combinatorial optimization
problems in machine learning is feature selection. It concerned with
removing the irrelevant, noisy, and redundant data, along with
keeping the original meaning of the original data. Attribute reduction
in rough set theory is an important feature selection method. Since
attribute reduction is an NP-hard problem, it is necessary to
investigate fast and effective approximate algorithms. In this paper,
we proposed two feature selection mechanisms based on memetic
algorithms (MAs) which combine the genetic algorithm with a fuzzy
record to record travel algorithm and a fuzzy controlled great deluge
algorithm, to identify a good balance between local search and
genetic search. In order to verify the proposed approaches, numerical
experiments are carried out on thirteen datasets. The results show that
the MAs approaches are efficient in solving attribute reduction
problems when compared with other meta-heuristic approaches.
Abstract: We present probabilistic multinomial Dirichlet
classification model for multidimensional data and Gaussian process
priors. Here, we have considered efficient computational method that
can be used to obtain the approximate posteriors for latent variables
and parameters needed to define the multiclass Gaussian process
classification model. We first investigated the process of inducing a
posterior distribution for various parameters and latent function by
using the variational Bayesian approximations and important sampling
method, and next we derived a predictive distribution of latent
function needed to classify new samples. The proposed model is
applied to classify the synthetic multivariate dataset in order to verify
the performance of our model. Experiment result shows that our model
is more accurate than the other approximation methods.