Abstract: Wind energy offers a significant advantage such as no
fuel costs and no emissions from generation. However, wind energy
sources are variable and non-dispatchable. The utility grid is able to
accommodate the variability of wind in smaller proportion along with
the daily load. However, at high penetration levels, the variability can
severely impact the utility reserve requirements and the cost
associated with it. In this paper the impact of wind energy is
evaluated in detail in formulating the total utility cost. The objective
is to minimize the overall cost of generation while ensuring the
proper management of the load. Overall cost includes the curtailment
cost, reserve cost and the reliability cost, as well as any other penalty
imposed by the regulatory authority. Different levels of wind
penetrations are explored and the cost impacts are evaluated. As the
penetration level increases significantly, the reliability becomes a
critical question to be answered. Here we increase the penetration
from the wind yet keep the reliability factor within the acceptable
limit provided by NERC. This paper uses an economic dispatch (ED)
model to incorporate wind generation into the power grid. Power
system costs are analyzed at various wind penetration levels using
Linear Programming. The goal of this study is show how the
increases in wind generation will affect power system economics.
Abstract: Development of a method to estimate gene functions is
an important task in bioinformatics. One of the approaches for the
annotation is the identification of the metabolic pathway that genes are
involved in. Since gene expression data reflect various intracellular
phenomena, those data are considered to be related with genes’
functions. However, it has been difficult to estimate the gene function
with high accuracy. It is considered that the low accuracy of the
estimation is caused by the difficulty of accurately measuring a gene
expression. Even though they are measured under the same condition,
the gene expressions will vary usually. In this study, we proposed a
feature extraction method focusing on the variability of gene
expressions to estimate the genes' metabolic pathway accurately. First,
we estimated the distribution of each gene expression from replicate
data. Next, we calculated the similarity between all gene pairs by KL
divergence, which is a method for calculating the similarity between
distributions. Finally, we utilized the similarity vectors as feature
vectors and trained the multiclass SVM for identifying the genes'
metabolic pathway. To evaluate our developed method, we applied the
method to budding yeast and trained the multiclass SVM for
identifying the seven metabolic pathways. As a result, the accuracy
that calculated by our developed method was higher than the one that
calculated from the raw gene expression data. Thus, our developed
method combined with KL divergence is useful for identifying the
genes' metabolic pathway.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: The object of the present paper is to investigate several
general families of bilinear and bilateral generating functions with
different argument for the Gauss’ hypergeometric polynomials.
Abstract: Human leukocyte antigen (HLA) typing from next
generation sequencing (NGS) data has the potential for applications in
clinical laboratories and population genetic studies. Here we introduce
a novel technique for HLA typing from NGS data based on
read-mapping using a comprehensive reference panel containing all
known HLA alleles and de novo assembly of the gene-specific short
reads. An accurate HLA typing at high-digit resolution was achieved
when it was tested on publicly available NGS data, outperforming
other newly-developed tools such as HLAminer and PHLAT.
Abstract: The goal of image segmentation is to cluster pixels
into salient image regions. Segmentation could be used for object
recognition, occlusion boundary estimation within motion or stereo
systems, image compression, image editing, or image database lookup.
In this paper, we present a color image segmentation using
support vector machine (SVM) pixel classification. Firstly, the pixel
level color and texture features of the image are extracted and they
are used as input to the SVM classifier. These features are extracted
using the homogeneity model and Gabor Filter. With the extracted
pixel level features, the SVM Classifier is trained by using FCM
(Fuzzy C-Means).The image segmentation takes the advantage of
both the pixel level information of the image and also the ability of
the SVM Classifier. The Experiments show that the proposed method
has a very good segmentation result and a better efficiency, increases
the quality of the image segmentation compared with the other
segmentation methods proposed in the literature.
Abstract: Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
Abstract: The decision-making process is theoretically clearly
defined. Generally, it includes the problem identification and
analysis, data gathering, goals and criteria setting, alternatives
development and optimal alternative choice and its implementation.
In practice however, various modifications of the theoretical
decision-making process can occur. The managers can consider some
of the phases to be too complicated or unfeasible and thus they do not
carry them out and conversely some of the steps can be
overestimated.
The aim of the paper is to reveal and characterize the perception of
the individual phases of decision-making process by the managers.
The research is concerned with managers in the military environment
– commanders. Quantitative survey is focused cross-sectionally in the
individual levels of management of the Ministry of Defence of the
Czech Republic. On the total number of 135 respondents the analysis
focuses on which of the decision-making process phases are
problematic or not carried out in practice and which are again
perceived to be the easiest. Then it is examined the reasons of the
findings.
Abstract: This paper proposes a mathematical model and
examines the performance of an exact algorithm for a location–
transportation problems in humanitarian relief. The model determines
the number and location of distribution centers in a relief network,
the amount of relief supplies to be stocked at each distribution center
and the vehicles to take the supplies to meet the needs of disaster
victims under capacity restriction, transportation and budgetary
constraints. The computational experiments are conducted on the
various sizes of problems that are generated. Branch and bound
algorithm is applied for these problems. The results show that this
algorithm can solve problem sizes of up to three candidate locations
with five demand points and one candidate location with up to twenty
demand points without premature termination.
Abstract: In urban area, several landmarks may affect housing
price and rents, and hedonic analysis should employ distance variables
corresponding to each landmarks. Unfortunately, the effects of
distances to landmarks on housing prices are generally not consistent
with the true price. These distance variables may cause magnitude
error in regression, pointing a problem of spatial multicollinearity. In
this paper, we provided some approaches for getting the samples with
less bias and method on locating the specific sampling area to avoid
the multicollinerity problem in two specific landmarks case.
Abstract: Fluid viscous damping systems are well suited for
many air vehicles subjected to shock and vibration. These damping
system work with the principle of viscous fluid throttling through the
orifice to create huge pressure difference between compression and
rebound chamber and obtain the required damping force. One
application of such systems is its use in aircraft door system to
counteract the door’s velocity and safely stop it. In exigency
situations like crash or emergency landing where the door doesn’t
open easily, possibly due to unusually tilting of fuselage or some
obstacles or intrusion of debris obstruction to move the parts of the
door, such system can be combined with other systems to provide
needed force to forcefully open the door and also securely stop it
simultaneously within the required time i.e. less than 8 seconds. In
the present study, a hydraulic system called snubber along with other
systems like actuator, gas bottle assembly which together known as
emergency power assist system (EPAS) is designed, built and
experimentally studied to check the magnitude of angular velocity,
damping force and time required to effectively open the door.
Whenever needed, the gas pressure from the bottle is released to
actuate the actuator and at the same time pull the snubber’s piston to
operate the emergency opening of the door. Such EPAS installed in
the suspension arm of the aircraft door is studied explicitly changing
parameters like orifice size, oil level, oil viscosity and bypass valve
gap and its spring of the snubber at varying temperature to generate
the optimum design case. Comparative analysis of the EPAS at
several cases is done and conclusions are made. It is found that
during emergency condition, the system opening time and angular
velocity, when snubber with 0.3mm piston and shaft orifice and
bypass valve gap of 0.5 mm with its original spring is used, shows
significant improvement over the old ones.
Abstract: In review the generalized data about different methods
of synthesis of biological activity aminated hydroxyanthraquinones is
presented. The basic regularity of a synthesis is analyzed. Action of
temperature, pH, solubility, catalysts and other factors on a reaction
product yield is revealed.
Abstract: Organic Rankine Cycle (ORC) is the most commonly used method for recovering energy from small sources of heat. The investigation of the ORC in supercritical condition is a new research area as it has a potential to generate high power and thermal efficiency in a waste heat recovery system. This paper presents a steady state ORC model in supercritical condition and its simulations with a real engine’s exhaust data. The key component of ORC, evaporator, is modelled using finite volume method, modelling of all other components of the waste heat recovery system such as pump, expander and condenser are also presented. The aim of this paper is to investigate the effects of mass flow rate and evaporator outlet temperature on the efficiency of the waste heat recovery process. Additionally, the necessity of maintaining an optimum evaporator outlet temperature is also investigated. Simulation results show that modification of mass flow rate is the key to changing the operating temperature at the evaporator outlet.
Abstract: The effects of basil and/or chamomile seed
supplementation on the growth of Hubbard broiler chicks were
evaluated. The antioxidant effects of these supplements were also
assessed. 120 1-day-old broiler chicks were randomly divided into
four equal groups. The control group (group 1) was fed a basal diet
(BD) without supplementation. Groups 2, 3, and 4 were fed the BD
supplemented with 10g basil, 10g chamomile, and 5g basil plus 5g
chamomile per kg of food, respectively. Basil supplementation alone
or in combination with chamomile non-significantly (P≥0.05)
increased final body weight (3.2% and 0.3%, respectively) and
weight gain (3.5% and 3.6%, respectively) over the experimental
period. Chamomile supplementation alone non-significantly (P≥0.05)
reduced final body weight and weight gain over the experimental
period by 1.7% and 1.7%, respectively. In comparison to the control
group, herbal seed supplementation reduced feed intake and
improved the feed conversion and protein efficiency ratios. In
general, basil seed supplementation stimulated chicken growth and
improved the feed efficiency more effectively than chamomile seed
supplementation. The antioxidant activities of basil and/or chamomile
supplementation were examined in the thymus, bursa, and spleen. In
chickens that received supplements, the level of malondialdehyde
was significantly decreased, whereas the activities of glutathione,
superoxide dismutase, and catalase were significantly increased
(P
Abstract: Governments collect and produce large amounts of
data. Increasingly, governments worldwide have started to implement
open data initiatives and also launch open data portals to enable the
release of these data in open and reusable formats. Therefore, a large
number of open data repositories, catalogues and portals have been
emerging in the world. The greater availability of interoperable and
linkable open government data catalyzes secondary use of such data,
so they can be used for building useful applications which leverage
their value, allow insight, provide access to government services, and
support transparency. The efficient development of successful open
data portals makes it necessary to evaluate them systematic, in order
to understand them better and assess the various types of value they
generate, and identify the required improvements for increasing this
value. Thus, the attention of this paper is directed particularly to the
field of open data portals. The main aim of this paper is to compare
the selected open data portals on the national level using content
analysis and propose a new evaluation framework, which further
improves the quality of these portals. It also establishes a set of
considerations for involving businesses and citizens to create eservices
and applications that leverage on the datasets available from
these portals.
Abstract: This study investigates the cleaning performance of
high intensity 360 kHz frequency on removal of nano-dimensional
and sub-micron particles from various surfaces, uniformity of the
cleaning tank and run to run variation of cleaning process. The
uniformity of the cleaning tank was measured by two different
methods i.e. 1. ppbTM meter and 2. Liquid Particle Counting (LPC)
technique. The result indicates that the energy was distributed more
uniformly throughout the entire cleaning vessel even at the corners
and edges of the tank when megasonic sweeping technology is
applied. The result also shows that rinsing the parts with 360 kHz
frequency at final rinse gives lower particle counts, hence higher
cleaning efficiency as compared to other frequencies. When
megasonic sweeping technology is applied each piezoelectric
transducers will operate at their optimum resonant frequency and
generates stronger acoustic cavitational force and higher acoustic
streaming velocity. These combined forces are helping to enhance the
particle removal and at the same time improve the overall cleaning
performance. The multiple extractions study was also carried out for
various frequencies to measure the cleaning potential and asymptote
value.
Abstract: Nature is a great source of inspiration for solving
complex problems in networks. It helps to find the optimal solution.
Metaheuristic algorithm is one of the nature-inspired algorithm which
helps in solving routing problem in networks. The dynamic features,
changing of topology frequently and limited bandwidth make the
routing, challenging in MANET. Implementation of appropriate
routing algorithms leads to the efficient transmission of data in
mobile ad hoc networks. The algorithms that are inspired by the
principles of naturally-distributed/collective behavior of social
colonies have shown excellence in dealing with complex
optimization problems. Thus some of the bio-inspired metaheuristic
algorithms help to increase the efficiency of routing in ad hoc
networks. This survey work presents the overview of bio-inspired
metaheuristic algorithms which support the efficiency of routing in
mobile ad hoc networks.
Abstract: The characteristic requirement for producing
rectangular shape bottles was a uniform thickness of the plastic bottle
wall. Die shaping was a good technique which controlled the wall
thickness of bottles. An advance technology which was the finite
element method (FEM) for blowing parison to be a rectangular shape
bottle was conducted to reduce waste plastic from a trial and error
method of a die shaping and parison control method. The artificial
intelligent (AI) comprised of artificial neural network and genetic
algorithm was selected to optimize the die gap shape from the FEM
results. The application of AI technique could optimize the suitable
die gap shape for the parison blow molding which did not depend on
the parison control method to produce rectangular bottles with the
uniform wall. Particularly, this application can be used with cheap
blow molding machines without a parison controller therefore it will
reduce cost of production in the bottle blow molding process.
Abstract: Microbial fuel cells (MFCs) represent a promising
technology for simultaneous bioelectricity generation and wastewater
treatment. Catalysts are significant portions of the cost of microbial
fuel cell cathodes. Many materials have been tested as aqueous
cathodes, but air-cathodes are needed to avoid energy demands for
water aeration. The sluggish oxygen reduction reaction (ORR) rate at
air cathode necessitates efficient electrocatalyst such as carbon
supported platinum catalyst (Pt/C) which is very costly. Manganese
oxide (MnO2) was a representative metal oxide which has been
studied as a promising alternative electrocatalyst for ORR and has
been tested in air-cathode MFCs. However the single MnO2 has poor
electric conductivity and low stability. In the present work, the MnO2
catalyst has been modified by doping Pt nanoparticle. The goal of the
work was to improve the performance of the MFC with minimum Pt
loading. MnO2 and Pt nanoparticles were prepared by hydrothermal
and sol gel methods, respectively. Wet impregnation method was
used to synthesize Pt/MnO2 catalyst. The catalysts were further used
as cathode catalysts in air-cathode cubic MFCs, in which anaerobic
sludge was inoculated as biocatalysts and palm oil mill effluent
(POME) was used as the substrate in the anode chamber. The asprepared
Pt/MnO2 was characterized comprehensively through field
emission scanning electron microscope (FESEM), X-Ray diffraction
(XRD), X-ray photoelectron spectroscopy (XPS), and cyclic
voltammetry (CV) where its surface morphology, crystallinity,
oxidation state and electrochemical activity were examined,
respectively. XPS revealed Mn (IV) oxidation state and Pt (0)
nanoparticle metal, indicating the presence of MnO2 and Pt.
Morphology of Pt/MnO2 observed from FESEM shows that the
doping of Pt did not cause change in needle-like shape of MnO2
which provides large contacting surface area. The electrochemical
active area of the Pt/MnO2 catalysts has been increased from 276 to
617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The
CV results in O2 saturated neutral Na2SO4 solution showed that
MnO2 and Pt/MnO2 catalysts could catalyze ORR with different
catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode
catalyst generates a maximum power density of 165 mW/m3, which
is higher than that of MFC with MnO2 catalyst (95 mW/m3). The
open circuit voltage (OCV) of the MFC operated with MnO2 cathode
gradually decreased during 14 days of operation, whereas the MFC
with Pt/MnO2 cathode remained almost constant throughout the
operation suggesting the higher stability of the Pt/MnO2 catalyst.
Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an
efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced
performance.
Abstract: Newly synthesized Polypropylene-g-Polyethylene
glycol polymer was first time used for a compartment-less enzymatic
fuel cell. Working electrodes based on Polypropylene-g-Polyethylene
glycol were operated as unmediated and mediated system (with
ferrocene and gold/cobalt oxide nanoparticles). Glucose oxidase and
bilirubin oxidase was selected as anodic and cathodic enzyme,
respectively. Glucose was used as fuel in a single-compartment and
membrane-less cell. Maximum power density was obtained as 0.65
nW cm-2, 65 nW cm-2 and 23500 nW cm-2 from the unmediated,
ferrocene and gold/cobalt oxide modified polymeric film,
respectively. Power density was calculated to be ~16000 nW cm-2 for
undiluted wastewater sample with gold/cobalt oxide nanoparticles
including system.