Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: From an organizational perspective, leaders are a
variation of the same talent pool in that they all score a larger than
average value on the bell curve that maps leadership behaviors and
characteristics, namely competence, vision, communication,
confidence, cultural sensibility, stewardship, empowerment,
authenticity, reinforcement, and creativity. The question that remains
unanswered and essentially unresolved is how to explain the irony
that leaders are so much alike yet their organizations diverge so
noticeably in their ability to innovate. Leadership intersects with
innovation at the point where human interactions get exceedingly
complex and where certain paradoxical forces cohabit: conflict with
conciliation, sovereignty with interdependence, and imagination with
realism. Rather than accepting that leadership is without context, we
argue that leaders are specialists of their domain and that those
effective at leading for innovation are distinct within the broader pool
of leaders. Keeping in view the extensive literature on leadership and
innovation, we carried out a quantitative study with data collected
over a five-year period involving 240 participants from across five
dissimilar companies based in the United States. We found that while
innovation and leadership are, in general, strongly interrelated (r =
.89, p = 0.0), there are five qualities that set leaders apart on
innovation. These qualities include a large radius of trust, a restless
curiosity with a low need for acceptance, an honest sense of self and
other, a sense for knowledge and creativity as the yin and yang of
innovation, and an ability to use multiple senses in the engagement
with followers. When these particular behaviors and characteristics
are present in leaders, organizations out-innovate their rivals by a
margin of 29.3 per cent to gain an unassailable edge in a business
environment that is regularly disruptive. A strategic outcome of this
study is a psychometric scale named iLeadership, proposed with the
underlying evidence, limitations, and potential for leadership and
innovation in organizations.c
Abstract: Three dimensional non-Interlaced carbon fibre
reinforced silicon carbide (3-D-Cf/SiC) composites with pyrocarbon
interphase were fabricated using isothermal chemical vapor
infiltration (ICVI) combined with polymer impregnation pyrolysis
(PIP) process. Polysilazane (PSZ) is used as a preceramic polymer to
obtain silicon carbide matrix. Thermo gravimetric analysis (TGA),
Infrared spectroscopic analysis (IR) and X-ray diffraction (XRD)
analysis were carried out on PSZ pyrolysed at different temperatures
to understand the pyrolysis and obtaining the optimum pyrolysing
condition to yield β-SiC phase. The density of the composites was
1.94 g cm-3 after the 3-D carbon preform was SiC infiltrated for 280 h
with one intermediate polysilazane pre-ceramic PIP process.
Mechanical properties of the composite materials were investigated
under tensile, flexural, shear and impact loading. The values of
tensile strength were 200 MPa at room temperature (RT) and 195
MPa at 500°C in air. The average RT flexural strength was 243 MPa.
The lower flexural strength of these composites is because of the
porosity. The fracture toughness obtained from single edge notched
beam (SENB) technique was 39 MPa.m1/2. The work of fracture
obtained from the load-displacement curve of SENB test was 22.8
kJ.m-2. The composites exhibited excellent impact resistance and the
dynamic fracture toughness of 44.8 kJ.m-2 is achieved as determined
from instrumented Charpy impact test. The shear strength of the
composite was 93 MPa, which is significantly higher compared 2-D
Cf/SiC composites. Microstructure evaluation of fracture surfaces
revealed the signatures of fracture processes and showed good
support for the higher toughness obtained.
Abstract: This work presents the modelling and simulation of
saponification of ethyl acetate in the presence of sodium hydroxide in
a plug flow reactor using Aspen Plus simulation software. Plug flow
reactors are widely used in the industry due to the non-mixing
property. The use of plug flow reactors becomes significant when
there is a need for continuous large scale reaction or fast reaction.
Plug flow reactors have a high volumetric unit conversion as the
occurrence for side reactions is minimum. In this research Aspen Plus
V8.0 has been successfully used to simulate the plug flow reactor. In
order to simulate the process as accurately as possible HYSYS Peng-
Robinson EOS package was used as the property method. The results
obtained from the simulation were verified by the experiment carried
out in the EDIBON plug flow reactor module. The correlation
coefficient (r2) was 0.98 and it proved that simulation results
satisfactorily fit for the experimental model. The developed model
can be used as a guide for understanding the reaction kinetics of a
plug flow reactor.
Abstract: Lead (Pb) poisoning is one of the most common and
preventable environmental health problems. There are different
sources of environmental pollution with lead as lead alkyl additives
in petrol and manufacturing processes. Pb in the atmosphere can be
deposited in urban soils, and may then be re-suspended to re-enter the
atmosphere. This could increase human exposure to Pb and cause
long-term health effects. Thus, monitoring Pb pollution is considered
one of the major tasks in controlling pollution. Scalp hair can be
utilized for the determination of lead (Pb) concentration. It provides a
lasting record of metal intakes of weeks or even months, and for most
metals, their accumulation in hair reflects their accumulation in the
whole body. This work was conducted to investigate the
concentration of lead in male scalp hair of Cairo (residential-traffic
and residential-industrial) and rural residents after twenty years of
phasing out of leaded gasoline. Results indicated that the mean
concentration of lead in hair of residential-traffic (9.7552 μg/g ±0.71)
and residential-industrial (12.3288 μg/g ±1.13) was significantly
higher than that in rural residents (4.7327 μg/g ±0.67). The mean
concentration of lead in hair of resident’s industrial areas was the
highest among Cairo residents and not the traffic areas as it was
before phasing out of leaded gasoline. Twenty years of phasing out of
leaded gasoline in Cairo has greatly improved the lead pollution
among residents of traffic areas, but industrial areas residents were
still suffering from lead pollution, which needs more efforts to
control the sources of lead pollution.
Abstract: Roof top rainwater harvesting (RWH) has been
carried out worldwide to provide an inexpensive source of water for
many people. This research aims at evaluating the potential of roof
top rain water harvesting as a resource in Jordan. For the purpose of
this work, two case studies at Al-Jubiha and Shafa-Badran districts in
Amman city were selected. All existing rooftops in both districts
were identified by digitizing 2012 satellite images of the two districts
using Google earth and ArcGIS tools. Rational method was used to
estimate the potential volume of rainwater that can be harvested from
the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr
can be harvested in Al-Jubiha and Shafa-Badran districts,
respectively. This study should increase the attention to the
importance of implementing RWH technique in Jordanian residences
as a viable alternative for ensuring a continued source of non-potable
water.
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: Osteoporosis is a common multifactorial disease with
a strong genetic component characterized by reduced bone mass and
increased risk of fractures. Genetic factors play an important role in
the pathogenesis of osteoporosis. The aim of our study was to
identify the genotype and allele distribution of T245G polymorphism
in OPG gene in Slovak postmenopausal women. A total of 200
unrelated Slovak postmenopausal women with diagnosed
osteoporosis and 200 normal controls were genotyped for T245G
(rs3134069) polymorphism of OPG gene. Genotyping was performed
using the Custom Taqman®SNP Genotyping assays. Genotypes and
alleles frequencies showed no significant differences (p=0.5551;
p=0.6022). The results of the present study confirm the importance of
T245G polymorphism in OPG gene in the pathogenesis of
osteoporosis.
Abstract: Control of a semi-batch polymerization reactor using
an adaptive radial basis function (RBF) neural network method is
investigated in this paper. A neural network inverse model is used to
estimate the valve position of the reactor; this method can identify the
controlled system with the RBF neural network identifier. The
weights of the adaptive PID controller are timely adjusted based on
the identification of the plant and self-learning capability of RBFNN.
A PID controller is used in the feedback control to regulate the actual
temperature by compensating the neural network inverse model
output. Simulation results show that the proposed control has strong
adaptability, robustness and satisfactory control performance and the
nonlinear system is achieved.
Abstract: Al-Si-Mg-Ni(-Cu) alloys are widely used in the automotive industry. They have the advantage of low weight associated with low coefficient of thermal expansion and excellent mechanical properties – mainly at high temperatures. The corrosion resistance of these alloys in coastal area, particularly sea water, however is not yet known. In this investigation, electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization have been used to evaluate the corrosion resistance of Al-6Si-0.5Mg-2Ni (-2Cu) alloys in simulated sea water environments. The potentiodynamic polarization curves reveal that 2 wt% Cu content alloy (Alloy-2) is more prone to corrosion than the Cu free alloy (Alloy-1). But the EIS test results showed that corrosion resistance or charge transfer resistance (Rct) increases with the addition of Cu. Due to addition of Cu and thermal treatment, the magnitude of open circuit potential (OCP), corrosion potential (Ecorr) and pitting corrosion potential (Epit) of Al-6Si-0.5Mg-2Ni alloy in NaCl solution were shifted to the more noble direction.
Abstract: This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.
Abstract: The study investigated the implementation of the
Neural Network (NN) techniques for prediction of the loading of Cu
ions onto clinoptilolite. The experimental design using analysis of
variance (ANOVA) was chosen for testing the adequacy of the
Neural Network and for optimizing of the effective input parameters
(pH, temperature and initial concentration). Feed forward, multi-layer
perceptron (MLP) NN successfully tracked the non-linear behavior of
the adsorption process versus the input parameters with mean squared
error (MSE), correlation coefficient (R) and minimum squared error
(MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed
that NN modeling techniques could effectively predict and simulate
the highly complex system and non-linear process such as ionexchange.
Abstract: Metal matrix composites (MMCs) have gained a
considerable interest in the last three decades. Conventional powder
metallurgy production route often involves the addition of reinforcing
phases into the metal matrix directly, which leads to poor wetting
behavior between ceramic phase and metal matrix and the
segregation of reinforcements. The commonly used elements for
ceramic phase formation in iron based MMCs are Ti, Nb, Mo, W, V
and C, B. The aim of the present paper is to investigate the effect of
sintering temperature and V-B addition on densification, phase
development, microstructure, and hardness of Fe–V-B composites
(Fe-(5-10) wt. %B – 25 wt. %V alloys) prepared by powder
metallurgy process. Metal powder mixes were pressed uniaxial and
sintered at different temperatures (ranging from 1300 to 1400ºC) for
1h. The microstructure of the (V, B) Fe composites was studied with
the help of high magnification optical microscope and XRD.
Experimental results show that (V, B) Fe composites can be produced
by conventional powder metallurgy route.
Abstract: Advances in the field of image processing envision a
new era of evaluation techniques and application of procedures in
various different fields. One such field being considered is the
biomedical field for prognosis as well as diagnosis of diseases. This
plethora of methods though provides a wide range of options to select
from, it also proves confusion in selecting the apt process and also in
finding which one is more suitable. Our objective is to use a series of
techniques on bone scans, so as to detect the occurrence of
rheumatoid arthritis (RA) as accurately as possible. Amongst other
techniques existing in the field our proposed system tends to be more
effective as it depends on new methodologies that have been proved
to be better and more consistent than others. Computer aided
diagnosis will provide more accurate and infallible rate of
consistency that will help to improve the efficiency of the system.
The image first undergoes histogram smoothing and specification,
morphing operation, boundary detection by edge following algorithm
and finally image subtraction to determine the presence of
rheumatoid arthritis in a more efficient and effective way. Using preprocessing
noises are removed from images and using segmentation,
region of interest is found and Histogram smoothing is applied for a
specific portion of the images. Gray level co-occurrence matrix
(GLCM) features like Mean, Median, Energy, Correlation, Bone
Mineral Density (BMD) and etc. After finding all the features it
stores in the database. This dataset is trained with inflamed and noninflamed
values and with the help of neural network all the new
images are checked properly for their status and Rough set is
implemented for further reduction.
Abstract: The Indian subcontinent is facing a massive challenge with regards to energy security in its member countries; to provide reliable electricity to facilitate development across various sectors of the economy and consequently achieve the developmental targets. The instability of the current precarious situation is observable in the frequent system failures and blackouts.
The deployment of interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the Indian sub-continent is proposed in this paper. Not only enabling energy security in the subcontinent it will also provide a platform for Renewable Energy Sources (RES) integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on Voltage Source High Voltage Direct Current (VSC- HVDC) converters for the Supergrid modeling. Various control schemes for the control of voltage and power are utilized for the regulation of the network parameters. A 3 terminal Multi Terminal Direct Current (MTDC) network is used for the simulations.
Abstract: In this study, a liquid phase microextraction by hollow fiber (HF-LPME) combined with high performance liquid chromatography-UV detector was applied to preconcentrate and determine trace levels of Cyproheptadine in human urine and plasma samples. Cyproheptadine was extracted from 10 mL alkaline aqueous solution (pH: 9.81) into an organic solvent (n-octnol) which was immobilized in the wall pores of a hollow fiber. Then was back-extracted into an acidified aqueous solution (pH: 2.59) located inside the lumen of the hollow fiber. This method is simple, efficient and cost-effective. It is based on pH gradient and differences between two aqueous phases. In order to optimize the HF-LPME some affecting parameters including the pH of donor and acceptor phases, the type of organic solvent, ionic strength, stirring rate, extraction time and temperature were studied and optimized. Under optimal conditions enrichment factor, limit of detection (LOD) and relative standard deviation (RSD(%), n=3) were up to 112, 15 μg.L−1 and 2.7, respectively.
Abstract: Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.
Abstract: This study presents the numerical simulation of three-dimensional incompressible steady and laminar fluid flow and conjugate heat transfer of a trapezoidal microchannel heat sink using water as a cooling fluid in a silicon substrate. Navier-Stokes equations with conjugate energy equation are discretized by finite-volume method. We perform numerical computations for a range of 50 ≦ Re ≦ 600, 0.05W ≦ P ≦ 0.8W, 20W/cm2 ≦q"≦ 40W/cm2. The present study demonstrates the numerical optimization of a trapezoidal microchannel heat sink design using the response surface methodology (RSM) and the genetic algorithm method (GA). The results show that the average Nusselt number increases with an increase in the Reynolds number or pumping power, and the thermal resistance decreases as the pumping power increases. The thermal resistance of a trapezoidal microchannel is minimized for a constant heat flux and constant pumping power.
Abstract: Castor (Ricinus communis L.) is one of the important
non-edible oilseed crops having immense industrial and medicinal
value. Oil yield per unit area is the ultimate target in growing oilseed
plants and sowing date is one of the important factors which have a
clear role on production of active substances particularly in oilseeds.
This study was conducted to evaluate the effect of sowing date on the
seed and oil yield of castor in Central Anatolia of Turkey in 2011.
The field experiment was set up in a completely randomized block
design with three replications. Black Diamond-2 castor cultivar was
used as plant material. The treatment was four sowing dates of May
10, May 25, June 10, June 25. In this research; seed yield, oil content
and oil yield were investigated. Results showed that the effect of
different sowing dates were significant on all of characteristics. In
general; delayed sowing dates, resulted in decreased seed yield, oil
content and oil yield. The highest value of seed yield, oil content and
oil yield (respectively, 2523.7 kg ha-1, 51.18% and 1292.2 kg ha-1)
were obtained from the first sowing date (May 10) while the lowest
seed yield, oil content and oil yield (respectively, 1550 kg ha-1,
43.67%, 677.3 kg ha-1) were recorded from the latest sowing date
(June 25). Therefore, it can be concluded that early May could be
recommended as an appropriate sowing date in the studied location
and similar climates for achieved high oil yield of castor.
Abstract: The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.