Abstract: The Markov decision process (MDP) based
methodology is implemented in order to establish the optimal
schedule which minimizes the cost. Formulation of MDP problem
is presented using the information about the current state of pipe,
improvement cost, failure cost and pipe deterioration model. The
objective function and detailed algorithm of dynamic programming
(DP) are modified due to the difficulty of implementing the
conventional DP approaches. The optimal schedule derived from
suggested model is compared to several policies via Monte
Carlo simulation. Validity of the solution and improvement in
computational time are proved.
Abstract: This paper discusses the design and analysis of a
hybrid PV-Fuel cell energy system destined to power a DC load. The
system is composed of a photovoltaic array, a fuel cell, an
electrolyzer and a hydrogen tank. HOMER software is used in this
study to calculate the optimum capacities of the power system
components that their combination allows an efficient use of solar
resource to cover the hourly load needs. The optimal system sizing
allows establishing the right balance between the daily electrical
energy produced by the power system and the daily electrical energy
consumed by the DC load using a 28 KW PV array, a 7.5 KW fuel
cell, a 40KW electrolyzer and a 270 Kg hydrogen tank. The variation
of powers involved into the DC bus of the hybrid PV-fuel cell system
has been computed and analyzed for each hour over one year: the
output powers of the PV array and the fuel cell, the input power of
the elctrolyzer system and the DC primary load. Equally, the annual
variation of stored hydrogen produced by the electrolyzer has been
assessed. The PV array contributes in the power system with 82%
whereas the fuel cell produces 18%. 38% of the total energy
consumption belongs to the DC primary load while the rest goes to
the electrolyzer.
Abstract: Cemented carbide balls are usually implemented in
industry under the environment of high speed, high temperature,
corrosiveness and strong collisions. However, its application is limited
due to high fabrication cost, processing efficiency and quality. A novel
eccentric lapping method with two rotatable lapping plates was
proposed in this paper. A mathematical model was constructed to
analyze the influence of each design parameter on this lapping method.
To validate this new lapping method, an orthogonal experiment was
conducted with cemented carbide balls (YG6). The simulation model
was verified and the optimal lapping parameters were derived. The
results show that the surface roundness of the balls reaches to 0.65um
from 2um in 1 hour using this lapping method. So, using this novel
lapping method, it can effectively improve the machining precision
and efficiency of cemented carbide balls.
Abstract: The thermal behavior of a large-scale, phase change material (PCM) enhanced building envelope system was studied in regard to the need for pre-fabricated construction in subtropical regions. The proposed large-scale envelope consists of a reinforced aluminum skin, insulation core, phase change material and reinforced gypsum board. The PCM impact on an energy efficiency of an enveloped room was resolved by validation of the EnergyPlus numerical scheme and optimization of a smart material location in the core. The PCM location was optimized by a minimization method of a cooling energy demand. It has been shown that there is good agreement between the test and simulation results. The optimal location of the PCM layer in Hong Kong summer conditions has been then recomputed for core thicknesses of 40, 60 and 80 mm. A non-dimensional value of the optimal PCM location was obtained to be same for all the studied cases and the considered external and internal conditions.
Abstract: Power systems are operating under stressed condition
due to continuous increase in demand of load. This can lead to
voltage instability problem when face additional load increase or
contingency. In order to avoid voltage instability suitable size of
reactive power compensation at optimal location in the system is
required which improves the load margin. This work aims at
obtaining optimal size as well as location of compensation in the 39-
bus New England system with the help of Bacteria Foraging and
Genetic algorithms. To reduce the computational time the work
identifies weak candidate buses in the system, and then picks only
two of them to take part in the optimization. The objective function is
based on a recently proposed voltage stability index which takes into
account the weighted average sensitivity index is a simpler and faster
approach than the conventional CPF algorithm. BFOA has been
found to give better results compared to GA.
Abstract: Poly vinyl acetate (PVA)-based titania (TiO2)–carbon
nanotube composite nanofibers (PVA-TCCNs) with various
PVA-to-solvent ratios and PVA-based TiO2 composite nanofibers
(PVA-TN) were synthesized using an electrospinning process,
followed by thermal treatment. The photocatalytic activities of these
nanofibers in the degradation of airborne monocyclic aromatics under
visible-light irradiation were examined. This study focuses on the
application of these photocatalysts to the degradation of the target
compounds at sub-part-per-million indoor air concentrations. The
characteristics of the photocatalysts were examined using scanning
electron microscopy, X-ray diffraction, ultraviolet-visible
spectroscopy, and Fourier-transform infrared spectroscopy. For all the
target compounds, the PVA-TCCNs showed photocatalytic
degradation efficiencies superior to those of the reference PVA-TN.
Specifically, the average photocatalytic degradation efficiencies for
benzene, toluene, ethyl benzene, and o-xylene (BTEX) obtained using
the PVA-TCCNs with a PVA-to-solvent ratio of 0.3 (PVA-TCCN-0.3)
were 11%, 59%, 89%, and 92%, respectively, whereas those observed
using PVA-TNs were 5%, 9%, 28%, and 32%, respectively.
PVA-TCCN-0.3 displayed the highest photocatalytic degradation
efficiency for BTEX, suggesting the presence of an optimal
PVA-to-solvent ratio for the synthesis of PVA-TCCNs. The average
photocatalytic efficiencies for BTEX decreased from 11% to 4%, 59%
to 18%, 89% to 37%, and 92% to 53%, respectively, when the flow
rate was increased from 1.0 to 4.0 L min1. In addition, the average
photocatalytic efficiencies for BTEX increased 11% to ~0%, 59% to
3%, 89% to 7%, and 92% to 13%, respectively, when the input
concentration increased from 0.1 to 1.0 ppm. The prepared
PVA-TCCNs were effective for the purification of airborne aromatics
at indoor concentration levels, particularly when the operating
conditions were optimized.
Abstract: This article deals with geographical conditions in
terrain and their effect on the movement of vehicles, their effect on
speed and safety of movement of people and vehicles. Finding of the
optimal routes outside the communication is studied in the Army
environment, but it occur in civilian as well, primarily in crisis
situation, or by the provision of assistance when natural disasters
such as floods, fires, storms etc., have happened. These movements
require the optimization of routes when effects of geographical
factors should be included. The most important factor is the surface
of a terrain. It is based on several geographical factors as are slopes,
soil conditions, micro-relief, a type of surface and meteorological
conditions. Their mutual impact has been given by coefficient of
deceleration. This coefficient can be used for the commander`s
decision. New approaches and methods of terrain testing,
mathematical computing, mathematical statistics or cartometric
investigation are necessary parts of this evaluation.
Abstract: The aim of this paper is to select the most accurate
forecasting method for predicting the future values of the
unemployment rate in selected European countries. In order to do so,
several forecasting techniques adequate for forecasting time series
with trend component, were selected, namely: double exponential
smoothing (also known as Holt`s method) and Holt-Winters` method
which accounts for trend and seasonality. The results of the empirical
analysis showed that the optimal model for forecasting
unemployment rate in Greece was Holt-Winters` additive method. In
the case of Spain, according to MAPE, the optimal model was double
exponential smoothing model. Furthermore, for Croatia and Italy the
best forecasting model for unemployment rate was Holt-Winters`
multiplicative model, whereas in the case of Portugal the best model
to forecast unemployment rate was Double exponential smoothing
model. Our findings are in line with European Commission
unemployment rate estimates.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.
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 presents a methodology using
Gravitational Search Algorithm for optimal placement of Phasor
Measurement Units (PMUs) in order to achieve complete
observability of the power system. The objective of proposed
algorithm is to minimize the total number of PMUs at the power
system buses, which in turn minimize installation cost of the PMUs.
In this algorithm, the searcher agents are collection of masses which
interact with each other using Newton’s laws of gravity and motion.
This new Gravitational Search Algorithm based method has been
applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test
systems. Case studies reveal optimal number of PMUs with better
observability by proposed method.
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: Vehicular Adhoc Network (VANET) is a new
technology which aims to ensure intelligent inter-vehicle
communications, seamless internet connectivity leading to improved
road safety, essential alerts, and access to comfort and entertainment.
VANET operations are hindered by mobile node’s (vehicles)
uncertain mobility. Routing algorithms use metrics to evaluate which
path is best for packets to travel. Metrics like path length (hop count),
delay, reliability, bandwidth, and load determine optimal route. The
proposed scheme exploits link quality, traffic density, and
intersections as routing metrics to determine next hop. This study
enhances Geographical Routing Protocol (GRP) using fuzzy
controllers while rules are optimized with Bee Swarm Optimization
(BSO). Simulations results are compared to conventional GRP.
Abstract: Every machine plays roles of client and server
simultaneously in a peer-to-peer (P2P) network. Though a P2P
network has many advantages over traditional client-server models
regarding efficiency and fault-tolerance, it also faces additional
security threats. Users/IT administrators should be aware of risks
from malicious code propagation, downloaded content legality, and
P2P software’s vulnerabilities. Security and preventative measures
are a must to protect networks from potential sensitive information
leakage and security breaches. Bit Torrent is a popular and scalable
P2P file distribution mechanism which successfully distributes large
files quickly and efficiently without problems for origin server. Bit
Torrent achieved excellent upload utilization according to
measurement studies, but it also raised many questions as regards
utilization in settings, than those measuring, fairness, and Bit
Torrent’s mechanisms choice. This work proposed a block selection
technique using Fuzzy ACO with optimal rules selected using ACO.
Abstract: The objective of this study was to identify the optimal
level of partial replacement of Portland cement by the ashes
originating from burning straw and bagasse from sugar cane (ASB).
Order to this end, were made five series of flat plates and cylindrical
bodies: control and others with the partial replacement in 20, 30, 40
and 50% of ASB in relation to the mass of the Ordinary Portland
cement, and conducted a mechanical testing of simple axial
compression (cylindrical bodies) and the four-point bending (flat
plates) and determined water absorption (WA), bulk density (BD)
and apparent void volume (AVV) on both types of specimens. Based
on the data obtained, it may be noted that the control treatment
containing only Portland cement, obtained the best results. However,
the cylindrical bodies with 20% ashes showed better results
compared to the other treatments. And in the formulations plates, the
treatment which showed the best results was 30% cement
replacement by ashes.
Abstract: Biofuels production has come forth as a future
technology to combat the problem of depleting fossil fuels. Bio-based
ethanol production from enzymatic lignocellulosic biomass
degradation serves an efficient method and catching the eye of
scientific community. High cost of the enzyme is the major obstacle
in preventing the commercialization of this process. Thus main
objective of the present study was to optimize composition of
medium components for enhancing cellulase production by newly
isolated strain of Bacillus tequilensis. Nineteen factors were taken
into account using statistical Plackett-Burman Design. The significant
variables influencing the cellulose production were further employed
in statistical Response Surface Methodology using Central
Composite Design for maximizing cellulase production. The
optimum medium composition for cellulase production was: peptone
(4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L),
Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride
(0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at
37oC. Analysis of variance (ANOVA) revealed high coefficient of
determination (R2) of 0.99. Maximum cellulase productivity of 11.5
IU/ml was observed against the model predicted value of 13 IU/ml.
This was found to be optimally active at 60oC and pH 5.5.
Abstract: For the treatment of acute and chronic lung diseases it is preferred to deliver medicaments by inhalation. The drug is delivered directly to tracheobronchial tree. This way allows the given medicament to get directly into the place of action and it makes rapid onset of action and maximum efficiency. The transport of aerosol particles in the particular part of the lung is influenced by their size, anatomy of the lungs, breathing pattern and airway resistance. This article deals with calculation of airway resistance in the lung model of Horsfield. It solves the problem of determination of the pressure losses in bifurcation and thus defines the pressure drop at a given location in the bronchial tree. The obtained data will be used as boundary conditions for transport of aerosol particles in a central part of bronchial tree realized by Computational Fluid Dynamics (CFD) approach. The results obtained from CFD simulation will allow us to provide information on the required particle size and optimal inhalation technique for particle transport into particular part of the lung.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: Speech enhancement is a long standing problem with
numerous applications like teleconferencing, VoIP, hearing aids and
speech recognition. The motivation behind this research work is to
obtain a clean speech signal of higher quality by applying the optimal
noise cancellation technique. Real-time adaptive filtering algorithms
seem to be the best candidate among all categories of the speech
enhancement methods. In this paper, we propose a speech
enhancement method based on Recursive Least Squares (RLS)
adaptive filter of speech signals. Experiments were performed on
noisy data which was prepared by adding AWGN, Babble and Pink
noise to clean speech samples at -5dB, 0dB, 5dB and 10dB SNR
levels. We then compare the noise cancellation performance of
proposed RLS algorithm with existing NLMS algorithm in terms of
Mean Squared Error (MSE), Signal to Noise ratio (SNR) and SNR
Loss. Based on the performance evaluation, the proposed RLS
algorithm was found to be a better optimal noise cancellation
technique for speech signals.
Abstract: The progress of industry integrated circuits in recent
years has been pushed by continuous miniaturization of transistors.
With the reduction of dimensions of components at 0.1 micron and
below, new physical effects come into play as the standard simulators
of two dimensions (2D) do not consider. In fact the third dimension
comes into play because the transverse and longitudinal dimensions
of the components are of the same order of magnitude. To describe
the operation of such components with greater fidelity, we must
refine simulation tools and adapted to take into account these
phenomena. After an analytical study of the static characteristics of
the component, according to the different operating modes, a
numerical simulation is performed of field-effect transistor with
submicron gate MESFET GaInP. The influence of the dimensions of
the gate length is studied. The results are used to determine the
optimal geometric and physical parameters of the component for their
specific applications and uses.