Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: Alternative energy is any energy source that is an alternative to fossil fuel. These alternatives are intended to address concerns about such fossil fuels. Today, because of the variety of energy choices and differing goals of their advocates, defining some energy types as "alternative" is highly controversial. Most of the recent and existing alternative sources of energy are discussed below
Abstract: This work concerns the evolution and the maintenance
of an ontological resource in relation with the evolution of the corpus
of texts from which it had been built.
The knowledge forming a text corpus, especially in dynamic domains,
is in continuous evolution. When a change in the corpus occurs, the
domain ontology must evolve accordingly. Most methods manage
ontology evolution independently from the corpus from which it is
built; in addition, they treat evolution just as a process of knowledge
addition, not considering other knowledge changes. We propose a
methodology for managing an evolving ontology from a text corpus
that evolves over time, while preserving the consistency and the
persistence of this ontology.
Our methodology is based on the changes made on the corpus to
reflect the evolution of the considered domain - augmented surgery
in our case. In this context, the results of text mining techniques,
as well as the ARCHONTE method slightly modified, are used to
support the evolution process.
Abstract: Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.
Abstract: This paper was to study the clothes dryer using waste
heat from a split type air conditioner with a capacity of 12,648 btu/h.
The drying chamber had a minimum cross section area with the size
of 0.5 x 1.0 m2. The chamber was constructed by sailcloth and was
inside folded with aluminium foil. Then, it was connected to the
condensing unit of an air conditioner. The experiment was carried out
in two aspects which were the clothes drying with and without
auxiliary fan unit. The results showed that the drying rate of clothes
in the chamber installed with and without auxiliary fan unit were
2.26 and 1.1 kg/h, respectively. In case of the chamber installed with
a auxiliary fan unit, the additional power of 0.011 kWh was
consumed and the drying rate was higher than that of clothes drying
without auxiliary fan unit. Without auxiliary fan unit installation, no
energy was required but there was a portion of hot air leaks away
through the punctured holes at the wall of the drying chamber, hence
the drying rate was dropped below. The drying rate of clothes drying
using waste heat was higher than natural indoor drying and
commercial dryer which their drying rate were 0.17 and 1.9 kg/h,
respectively. It was noted that the COP of the air conditioner did not
change during the operating of clothes drying.
Abstract: Modeling and vibration of a flexible link manipulator
with tow flexible links and rigid joints are investigated which can
include an arbitrary number of flexible links. Hamilton principle and
finite element approach is proposed to model the dynamics of
flexible manipulators. The links are assumed to be deflection due to
bending. The association between elastic displacements of links is
investigated, took into account the coupling effects of elastic motion
and rigid motion. Flexible links are treated as Euler-Bernoulli beams
and the shear deformation is thus abandoned. The dynamic behavior
due to flexibility of links is well demonstrated through numerical
simulation. The rigid-body motion and elastic deformations are
separated by linearizing the equations of motion around the rigid
body reference path. Simulation results are shown on for both
position and force trajectory tracking tasks in the presence of varying
parameters and unknown dynamics remarkably well. The proposed
method can be used in both dynamic simulation and controller
design.
Abstract: Drop-in of R-22 alternatives in refrigeration and air conditioning systems requires a redesign of system components to improve system performance and reliability with the alternative refrigerants. The present paper aims at design adiabatic capillary tubes for R-22 alternatives such as R-417A, R-422D and R-438A. A theoretical model has been developed and validated with the available experimental data from literature for R-22 over a wide range of both operating and geometrical parameters. Predicted lengths of adiabatic capillary tube are compared with the lengths of the capillary tube needed under similar experimental conditions and majority of predictions are found to be within 4.4% of the experimental data. Hence, the model has been applied for R-417A, R- 422D and R-438A and capillary tube selection charts and correlations have been computed. Finally a comparison between the selected refrigerants and R-22 has been introduced and the results showed that R-438A is the closest one to R-22.
Abstract: The article presents the whole model of IS/IT
architecture exception governance. As first, the assumptions of
presented model are set. As next, there is defined a generic
governance model that serves as a basis for the architecture exception
governance. The architecture exception definition and its attributes
follow. The model respects well known approaches to the area that
are described in the text, but it adopts higher granularity in
description and expands the process view with all the next necessary
governance components as roles, principles and policies, tools to
enable the implementation of the model into organizations. The
architecture exception process is decomposed into a set of processes
related to the architecture exception lifecycle consisting of set of
phases and architecture exception states. Finally, there is information
about my future research related to this area.
Abstract: Due to heavy energy constraints in WSNs clustering is
an efficient way to manage the energy in sensors. There are many
methods already proposed in the area of clustering and research is
still going on to make clustering more energy efficient. In our paper
we are proposing a minimum spanning tree based clustering using
divide and conquer approach. The MST based clustering was first
proposed in 1970’s for large databases. Here we are taking divide and
conquer approach and implementing it for wireless sensor networks
with the constraints attached to the sensor networks. This Divide and
conquer approach is implemented in a way that we don’t have to
construct the whole MST before clustering but we just find the edge
which will be the part of the MST to a corresponding graph and
divide the graph in clusters there itself if that edge from the graph can
be removed judging on certain constraints and hence saving lot of
computation.
Abstract: Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.
Abstract: This paper presents a numerical approach for the static
and dynamic analysis of hydrodynamic radial journal bearings. In the
first part, the effect of shaft and housing deformability on pressure
distribution within oil film is investigated. An iterative algorithm that
couples Reynolds equation with a plane finite elements (FE)
structural model is solved. Viscosity-to-pressure dependency (Vogel-
Barus equation) is also included. The deformed lubrication gap and
the overall stress state are obtained. Numerical results are presented
with reference to a typical journal bearing configuration at two
different inlet oil temperatures. Obtained results show the great
influence of bearing components structural deformation on oil
pressure distribution, compared with results for ideally rigid
components. In the second part, a numerical approach based on
perturbation method is used to compute stiffness and damping
matrices, which characterize the journal bearing dynamic behavior.
Abstract: In this paper, a study on the applications of the
optimization and regression techniques for optimal calculation of
partial ratios of helical gearboxes with second-step double gear-sets
for minimal cross section dimension is introduced. From the condition
of the moment equilibrium of a mechanic system including three gear
units and their regular resistance condition, models for calculation of
the partial ratios of helical gearboxes with second-step double
gear-sets were given. Especially, by regression analysis, explicit
models for calculation of the partial ratios are introduced. These
models allow determining the partial ratios accurately and simply.
Abstract: Humic acids (HAs) have been shown to activate some
ion uptakes along with stimulating the lateral roots at effective
concentration of micronutrients. However, the effects of HA on ion
adsorption by plant roots are not easily explainable due to the
varieties of HAs that differ from origins. Therefore, this study was
aimed to investigate the effect of various concentrations of HA
obtained from the compost derived from mix manures and some
agricultural wastes on the growth of eggplant seedlings (Solanum
melongena L. cv. Chao Praya) in tissue cultures at low nutrient level.
Egg plant seeds were surfaced sterilized and germinated in ½
Murashige and Skoog medium (MS) without HA added or in ¼ MS
supplemented with 0, 25, 50, 75 and 100 ppm of HAs. Then, they
were cultured for 4 weeks under the controlled environment. The
results showed that seedlings grown on ¼MS supplemented with
HAs at the concentration of 25 and 50 ppm had the average plant
heights (2.49 and 2.28 cm, respectively) higher than the other
treatments. Both treatments also significantly showed the maximum
average fresh and dry weights (p
Abstract: Bacterial cellulose, a biopolysaccharide, is produced by the bacterium, Gluconacetobacter xylinus. Static batch fermentation for bacterial cellulose production was studied in sucrose and date syrup solutions (Bx. 10%) at 28 °C using G. xylinus (PTCC, 1734). Results showed that the maximum yields of bacterial cellulose (BC) were 4.35 and 1.69 g/l00 ml for date syrup and sucrose medium after 336 hours fermentation period, respectively. Comparison of FTIR spectrum of cellulose with BC indicated appropriate coincidence which proved that the component produced by G. xylinus was cellulose. Determination of the area under X-ray diffractometry patterns demonstrated that the crystallinity amount of cellulose (83.61%) was more than that for the BC (60.73%). The scanning electron microscopy imaging of BC and cellulose were carried out in two magnifications of 1 and 6K. Results showed that the diameter ratio of BC to cellulose was approximately 1/30 which indicated more delicacy of BC fibers relative to cellulose.
Abstract: The effect of the discontinuity of the rail ends and the
presence of lower modulus insulation material at the gap to the
variations of stresses in the insulated rail joint (IRJ) is presented. A
three-dimensional wheel – rail contact model in the finite element
framework is used for the analysis. It is shown that the maximum stress
occurs in the subsurface of the railhead when the wheel contact occurs
far away from the rail end and migrates to the railhead surface as the
wheel approaches the rail end; under this condition, the interface
between the rail ends and the insulation material has suffered
significantly increased levels of stress concentration. The ratio of the
elastic modulus of the railhead and insulation material is found to alter
the levels of stress concentration. Numerical result indicates that a
higher elastic modulus insulating material can reduce the stress
concentration in the railhead but will generate higher stresses in the
insulation material, leading to earlier failure of the insulation material
Abstract: In this paper three different approaches for person
verification and identification, i.e. by means of fingerprints, face and
voice recognition, are studied. Face recognition uses parts-based
representation methods and a manifold learning approach. The
assessment criterion is recognition accuracy. The techniques under
investigation are: a) Local Non-negative Matrix Factorization
(LNMF); b) Independent Components Analysis (ICA); c) NMF with
sparse constraints (NMFsc); d) Locality Preserving Projections
(Laplacianfaces). Fingerprint detection was approached by classical
minutiae (small graphical patterns) matching through image
segmentation by using a structural approach and a neural network as
decision block. As to voice / speaker recognition, melodic cepstral
and delta delta mel cepstral analysis were used as main methods, in
order to construct a supervised speaker-dependent voice recognition
system. The final decision (e.g. “accept-reject" for a verification
task) is taken by using a majority voting technique applied to the
three biometrics. The preliminary results, obtained for medium
databases of fingerprints, faces and voice recordings, indicate the
feasibility of our study and an overall recognition precision (about
92%) permitting the utilization of our system for a future complex
biometric card.
Abstract: In this paper, a frequency-variation based method has
been proposed for transistor parameter estimation in a commonemitter
transistor amplifier circuit. We design an algorithm to estimate
the transistor parameters, based on noisy measurements of the output
voltage when the input voltage is a sine wave of variable frequency
and constant amplitude. The common emitter amplifier circuit has
been modelled using the transistor Ebers-Moll equations and the
perturbation technique has been used for separating the linear and
nonlinear parts of the Ebers-Moll equations. This model of the amplifier
has been used to determine the amplitude of the output sinusoid as
a function of the frequency and the parameter vector. Then, applying
the proposed method to the frequency components, the transistor
parameters have been estimated. As compared to the conventional
time-domain least squares method, the proposed method requires
much less data storage and it results in more accurate parameter
estimation, as it exploits the information in the time and frequency
domain, simultaneously. The proposed method can be utilized for
parameter estimation of an analog device in its operating range of
frequencies, as it uses data collected from different frequencies output
signals for parameter estimation.
Abstract: Markov games are a generalization of Markov
decision process to a multi-agent setting. Two-player zero-sum
Markov game framework offers an effective platform for designing
robust controllers. This paper presents two novel controller design
algorithms that use ideas from game-theory literature to produce
reliable controllers that are able to maintain performance in presence
of noise and parameter variations. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. Our approach
generates an optimal control policy for the agent (controller) via a
simple Linear Program enabling the controller to learn about the
unknown environment. The controller is facing an unknown
environment, and in our formulation this environment corresponds to
the behavior rules of the noise modeled as the opponent. Proposed
controller architectures attempt to improve controller reliability by a
gradual mixing of algorithmic approaches drawn from the game
theory literature and the Minimax-Q Markov game solution
approach, in a reinforcement-learning framework. We test the
proposed algorithms on a simulated Inverted Pendulum Swing-up
task and compare its performance against standard Q learning.
Abstract: The study of the interaction between humans and
computers has been emerging during the last few years. This
interaction will be more powerful if computers are able to perceive
and respond to human nonverbal communication such as emotions. In
this study, we present the image-based approach to emotion
classification through lower facial expression. We employ a set of
feature points in the lower face image according to the particular face
model used and consider their motion across each emotive expression
of images. The vector of displacements of all feature points input to
the Adaptive Support Vector Machines (A-SVMs) classifier that
classify it into seven basic emotions scheme, namely neutral, angry,
disgust, fear, happy, sad and surprise. The system was tested on the
Japanese Female Facial Expression (JAFFE) dataset of frontal view
facial expressions [7]. Our experiments on emotion classification
through lower facial expressions demonstrate the robustness of
Adaptive SVM classifier and verify the high efficiency of our
approach.
Abstract: Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.