Abstract: The necessity of updating the numerical models inputs, because of geometrical and resistive variations in rivers subject to solid transport phenomena, requires detailed control and monitoring activities. The human employment and financial resources of these activities moves the research towards the development of expeditive methodologies, able to evaluate the outflows through the measurement of more easily acquirable sizes. Recent studies highlighted the dependence of the entropic parameter on the kinematical and geometrical flow conditions. They showed a meaningful variability according to the section shape, dimension and slope. Such dependences, even if not yet well defined, could reduce the difficulties during the field activities, and also the data elaboration time. On the basis of such evidences, the relationships between the entropic parameter and the geometrical and resistive sizes, obtained through a large and detailed laboratory experience on steady free surface flows in conditions of macro and intermediate homogeneous roughness, are analyzed and discussed.
Abstract: Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.
Abstract: This paper presents the impact study of GTO Controlled Series Capacitor (GCSC) parameters on measured impedance (Zseen) by MHO distance relays for single transmission line high voltage 220 kV in the presence of single phase to earth fault with fault resistance (RF). The study deals with a 220 kV single electrical transmission line of Eastern Algerian transmission networks at Group Sonelgaz (Algerian Company of Electrical and Gas) compensated by series Flexible AC Transmission System (FACTS) i.e. GCSC connected at midpoint of the transmission line. The transmitted active and reactive powers are controlled by three GCSC-s. The effects of maximum reactive power injected as well as injected maximum voltage by GCSC on distance relays measured impedance is treated. The simulations results investigate the effects of GCSC injected parameters: variable reactance (XGCSC), variable voltage (VGCSC) and reactive power injected (QGCSC) on measured resistance and reactance in the presence of earth fault with resistance fault varied between 5 to 50 Ω for three cases study.
Abstract: This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).
Abstract: Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.
Abstract: Temperature rise in a transformer depends on variety
of parameters such as ambient temperature, output current and type
of the core. Considering these parameters, temperature rise estimation
is still complicated procedure. In this paper, we present a new model
based on simple electrical equivalent circuit. This method avoids the
complication associated to accurate estimation and is in very good
agreement with practice.
Abstract: Basic objective of this study is to create a regression
analysis method that can estimate the length of a plastic hinge which
is an important design parameter, by making use of the outcomes of
(lateral load-lateral displacement hysteretic curves) the experimental
studies conducted for the reinforced square concrete columns. For
this aim, 170 different square reinforced concrete column tests results
have been collected from the existing literature. The parameters
which are thought affecting the plastic hinge length such as crosssection
properties, features of material used, axial loading level,
confinement of the column, longitudinal reinforcement bars in the
columns etc. have been obtained from these 170 different square
reinforced concrete column tests. In the study, when determining the
length of plastic hinge, using the experimental test results, a
regression analysis have been separately tested and compared with
each other. In addition, the outcome of mentioned methods on
determination of plastic hinge length of the reinforced concrete
columns has been compared to other methods available in the
literature.
Abstract: Analytical expression for maximum power transfer
through a transmission line limited by voltage stability has been
formulated using exact representation of transmission line with
ABCD parameters. The expression has been used for plotting PV
curve at different power factors of a radial transmission line.
Limiting values of reactive power have been obtained.
Abstract: Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.
Abstract: This investigation examines the effect of the sintering
temperature curve in manufactured nickel powder capillary structure
(wick) for a loop heat pipe (LHP). The sintering temperature curve is
composed of a region of increasing temperature; a region of constant
temperature and a region of declining temperature. The most important
region is that in which the temperature increases, as an index in the
stage in which the temperature increases. The wick of nickel powder is
manufactured in the stage of fixed sintering temperature and the time
between the stage of constant temperature and the stage of falling
temperature. When the slope of the curve in the region of increasing
temperature is unity (equivalent to 10 °C/min), the structure of the
wick is complete and the heat transfer performance is optimal. The
result of experiment test demonstrates that the heat transfer
performance is optimal at 320W; the minimal total thermal resistance
is approximately 0.18°C/W, and the heat flux is 17W/cm2; the internal
parameters of the wick are an effective pore radius of 3.1 μm, a
permeability of 3.25×10-13m2 and a porosity of 71%.
Abstract: In this paper back-propagation artificial neural
network (BPANN) with Levenberg–Marquardt algorithm is
employed to predict the limiting drawing ratio (LDR) of the deep
drawing process. To prepare a training set for BPANN, some finite
element simulations were carried out. die and punch radius, die arc
radius, friction coefficient, thickness, yield strength of sheet and
strain hardening exponent were used as the input data and the LDR
as the specified output used in the training of neural network. As a
result of the specified parameters, the program will be able to
estimate the LDR for any new given condition. Comparing FEM and
BPANN results, an acceptable correlation was found.
Abstract: In this work we study the reflection of circularly
polarised light from a nano-structured biological material found in
the exocuticle of scarabus beetles. This material is made of a stack
of ultra-thin (~5 nm) uniaxial layers arranged in a left-handed
helicoidal stack, which resonantly reflects circularly polarized light.
A chirp in the layer thickness combined with a finite absorption
coefficient produce a broad smooth reflectance spectrum. By
comparing model calculations and electron microscopy with
measured spectra we can explain our observations and quantify most
relevant structural parameters.
Abstract: As days go by, we hear more and more about HIV,
Ebola, Bird Flu and other dreadful viruses which were unknown a
few decades ago. In both detecting and fighting viral diseases
ordinary methods have come across some basic and important
difficulties. Vaccination is by a sense introduction of the virus to the
immune system before the occurrence of the real case infection. It is
very successful against some viruses (e.g. Poliomyelitis), while
totally ineffective against some others (e.g. HIV or Hepatitis-C). On
the other hand, Anti-virus drugs are mostly some tools to control and
not to cure a viral disease. This could be a good motivation to try
alternative treatments. In this study, some key features of possible
physical-based alternative treatments for viral diseases are presented.
Electrification of body parts or fluids (especially blood) with micro
electric signals with adjusted current or frequency is also studied. The
main approach of this study is to find a suitable energy field, with
appropriate parameters that are able to kill or deactivate viruses. This
would be a lengthy, multi-disciplinary research which needs the
contribution of virology, physics, and signal processing experts. It
should be mentioned that all the claims made by alternative cures
researchers must be tested carefully and are not advisable at the time
being.
Abstract: The research study evaluated the performance of
irrigation system by using special scientific tools like Remote
Sensing and GIS technology, so that proper measurements could be
taken for the sustainable agriculture and water management.
Different performance evaluation parameters had been calculated for
the purposed data was gathered from field investigation and different
government and private organizations. According to the calculations,
organic matter ranges from 0.19% (low value) to 0.76% (high value).
In flat irrigation system for wheat yield ranges from 3347.16 to
5260.39 kg/ha, while the total water applied to wheat crop ranges
from 252.94 to 279.19 mm and WUE ranges from 13.07 to 18.37
kg/ha/mm. For rice yield ranges from 3347.47 to 5433.07 kg/ha with
total water supplied to rice crop ranges from 764.71 to 978.15 mm
and WUE ranges from 3.49 to 5.71 kg/ha/mm. Similarly, in raised
bed system wheat yield ranges from 4569.13 to 6008.60 kg/ha, total
water supplied ranges from 158.87 to 185.09 mm and WUE ranges
from 27.20 to 33.54 kg/ha/mm while in rice crop, yield ranges from
5285.04 to 6716.69 kg/ha, total water supplied ranges from 600.72 to
755.06 mm and WUE ranges from 6.41 to 10.05 kg/ha/mm. Almost
51.3% water saving is observed in bed irrigation system as compared
to flat system. Less water supplied to beds is more affective as its
WUE value is higher than flat system where more water is supplied
in both the seasons. Similarly, RWS values show that maximum
water deficit while minimum area is getting adequate water supply.
Greater yield is recorded in bed system as plant per square meter is
more in bed system in comparison of flat system Thus, the integration
of GIS tools to regularly compute performance indices could provide
irrigation managers with the means for managing efficiently the
irrigation system.
Abstract: This study deals with Computational Fluid Dynamics
(CFD) studies of the interactions between the air flow and louvered
fins which equipped the automotive heat exchangers. 3D numerical
simulation results are obtained by using the ANSYS Fluent 13.0 code
and compared to experimental data. The paper studies the effect of
louver angle and louver pitch geometrical parameters, on overall
thermal hydraulic performances of louvered fins.
The comparison between CFD simulations and experimental data
show that established 3-D CFD model gives a good agreement. The
validation agrees, with about 7% of deviation respectively of friction
and Colburn factors to experimental results. As first, it is found that
the louver angle has a strong influence on the heat transfer rate. Then,
louver angle and louver pitch variation of the louvers and their effects
on thermal hydraulic performances are studied. In addition to this
study, it is shown that the second half of the fin takes has a
significant contribution on pressure drop increase without any
increase in heat transfer.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: This paper simulates the ad-hoc mesh network in rural areas, where such networks receive great attention due to their cost, since installing the infrastructure for regular networks in these areas is not possible due to the high cost. The distance between the communicating nodes is the most obstacles that the ad-hoc mesh network will face. For example, in Terranet technology, two nodes can communicate if they are only one kilometer far from each other. However, if the distance between them is more than one kilometer, then each node in the ad-hoc mesh networks has to act as a router that forwards the data it receives to other nodes. In this paper, we try to find the critical number of nodes which makes the network fully connected in a particular area, and then propose a method to enhance the intermediate node to accept to be a router to forward the data from the sender to the receiver. Much work was done on technological changes on peer to peer networks, but the focus of this paper will be on another feature which is to find the minimum number of nodes needed for a particular area to be fully connected and then to enhance the users to switch on their phones and accept to work as a router for other nodes. Our method raises the successful calls to 81.5% out of 100% attempt calls.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
Abstract: Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.
Abstract: In this paper, by exploiting a single semiconductor
optical amplifier-Mach Zehnder Interferometer (SOA-MZI), an
integratable all-optical flip-flop (AOFF) is proposed. It is composed
of a SOA-MZI with a bidirectional coupler at the output. Output
signals of both bar and crossbar of the SOA-MZI is fed back to SOAs
located in the arms of the Mach-Zehnder Interferometer (MZI). The
injected photon-rates to the SOAs are modulated by feedback signals
in order to form optical flip-flop. According to numerical analysis,
Gaussian optical pulses with the energy of 15.2 fJ and 20 ps duration
with the full width at half-maximum criterion, can switch the states of
the SR-AOFF. Also simulation results show that the SR-AOFF has
the contrast ratio of 8.5 dB between two states with the transition
time of nearly 20 ps.