Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).
Abstract: Measurements of capacitance C and dissipation
factor tand of the stator insulation system provide useful information
about internal defects within the insulation. The index k is defined as
the proportionality constant between the changes at high voltage of
capacitance DC and of the dissipation factor Dtand . DC and
Dtand values were highly correlated when small flat defects were
within the insulation and that correlation was lost in the presence of
large narrow defects like electrical treeing. The discrimination
between small and large defects is made resorting to partial discharge
PD phase angle analysis. For the validation of the results, C and tand
measurements were carried out in a 15MVA 4160V steam turbine
turbogenerator placed in a sugar mill. In addition, laboratory test
results obtained by other authors were analyzed jointly. In such
laboratory tests, model coil bars subjected to thermal cycling resulted
highly degraded and DC and Dtand values were not correlated. Thus,
the index k could not be calculated.
Abstract: In this paper, we propose a hybrid machine learning
system based on Genetic Algorithm (GA) and Support Vector
Machines (SVM) for stock market prediction. A variety of indicators
from the technical analysis field of study are used as input features.
We also make use of the correlation between stock prices of different
companies to forecast the price of a stock, making use of technical
indicators of highly correlated stocks, not only the stock to be
predicted. The genetic algorithm is used to select the set of most
informative input features from among all the technical indicators.
The results show that the hybrid GA-SVM system outperforms the
stand alone SVM system.
Abstract: This paper presents an effective traffic lights detection
method at the night-time. First, candidate blobs of traffic lights are
extracted from RGB color image. Input image is represented on the
dominant color domain by using color transform proposed by Ruta,
then red and green color dominant regions are selected as candidates.
After candidate blob selection, we carry out shape filter for noise
reduction using information of blobs such as length, area, area of
boundary box, etc. A multi-class classifier based on SVM (Support
Vector Machine) applies into the candidates. Three kinds of features
are used. We use basic features such as blob width, height, center
coordinate, area, area of blob. Bright based stochastic features are also
used. In particular, geometric based moment-s values between
candidate region and adjacent region are proposed and used to improve
the detection performance. The proposed system is implemented on
Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the
urban and rural road videos. Through the test, we show that the
proposed method using PF, BMF, and GMF reaches up to 93 % of
detection rate with computation time of in average 15 ms/frame.
Abstract: A new hybrid coding method for compressing
animated polygonal meshes is presented. This paper assumes
the simplistic representation of the geometric data: a temporal
sequence of polygonal meshes for each discrete frame of the
animated sequence. The method utilizes a delta coding and an
octree-based method. In this hybrid method, both the octree
approach and the delta coding approach are applied to each
single frame in the animation sequence in parallel. The
approach that generates the smaller encoded file size is chosen
to encode the current frame. Given the same quality
requirement, the hybrid coding method can achieve much
higher compression ratio than the octree-only method or the
delta-only method. The hybrid approach can represent 3D
animated sequences with higher compression factors while
maintaining reasonable quality. It is easy to implement and have
a low cost encoding process and a fast decoding process, which
make it a better choice for real time application.
Abstract: Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.
Abstract: The scattering effect of light in fog improves the
difficulty in visibility thus introducing disturbances in transport
facilities in urban or industrial areas causing fatal accidents or public
harassments, therefore, developing an enhanced fog vision system
with radio wave to improvise the way outs of these severe problems
is really a big challenge for researchers. Series of experimental
studies already been done and more are in progress to know the
weather effect on radio frequencies for different ranges. According to
Rayleigh scattering Law, the propagating wavelength should be
greater than the diameter of the particle present in the penetrating
medium. Direct wave RF signal thus have high chance of failure to
work in such weather for detection of any object. Therefore an
extensive study was required to find suitable region in the RF band
that can help us in detecting objects with proper shape. This paper
produces some results on object detection using 912 MHz band with
successful detection of the persistence of any object coming under the
trajectory of a vehicle navigating in indoor and outdoor environment.
The developed images are finally transformed to video signal to
enable continuous monitoring.
Abstract: The purpose of this study was to examine to what
extend classroom management efficacy, marital status, gender, and
teaching experience predict burnout among primary school teachers.
Participants of this study were 523 (345 female, 178 male) teachers
who completed inventories. The results of multiple regression
analysis indicated that three dimensions of teacher burnout
(Emotional Exhaustion, Depersonalization, Personal
Accomplishment) were affected differently from four predictor
variables. Findings indicated that for the emotional exhaustion,
classroom management efficacy, marital status and teaching
experience; for depersonalization dimension, classroom management
efficacy and marital status and finally for the personal
accomplishment dimension, classroom management efficacy, gender,
and teaching experience were significant predictors.
Abstract: FW4 is a newly developed hot die material widely
used in Forging Dies manufacturing. The right selection of the
machining conditions is one of the most important aspects to take
into consideration in the Electrical Discharge Machining (EDM) of
FW4. In this paper an attempt has been made to develop
mathematical models for relating the Material Removal Rate (MRR),
Tool Wear Ratio (TWR) and surface roughness (Ra) to machining
parameters (current, pulse-on time and voltage). Furthermore, a study
was carried out to analyze the effects of machining parameters in
respect of listed technological characteristics. The results of analysis
of variance (ANOVA) indicate that the proposed mathematical
models, can adequately describe the performance within the limits of
the factors being studied.
Abstract: The Institute of Product Development is dealing
with the development, design and dimensioning of micro components
and systems as a member of the Collaborative Research
Centre 499 “Design, Production and Quality Assurance of
Molded micro components made of Metallic and Ceramic Materials".
Because of technological restrictions in the miniaturization
of conventional manufacturing techniques, shape and
material deviations cannot be scaled down in the same proportion
as the micro parts, rendering components with relatively
wide tolerance fields. Systems that include such components
should be designed with this particularity in mind, often requiring
large clearance. On the end, the output of such systems
results variable and prone to dynamical instability. To save
production time and resources, every study of these effects
should happen early in the product development process and
base on computer simulation to avoid costly prototypes. A
suitable method is proposed here and exemplary applied to a
micro technology demonstrator developed by the CRC499. It
consists of a one stage planetary gear train in a sun-planet-ring
configuration, with input through the sun gear and output
through the carrier. The simulation procedure relies on ordinary
Multi Body Simulation methods and subsequently adds
other techniques to further investigate details of the system-s
behavior and to predict its response. The selection of the relevant
parameters and output functions followed the engineering
standards for regular sized gear trains. The first step is to
quantify the variability and to reveal the most critical points of
the system, performed through a whole-mechanism Sensitivity
Analysis. Due to the lack of previous knowledge about the system-s
behavior, different DOE methods involving small and
large amount of experiments were selected to perform the SA.
In this particular case the parameter space can be divided into
two well defined groups, one of them containing the gear-s profile
information and the other the components- spatial location.
This has been exploited to explore the different DOE techniques
more promptly. A reduced set of parameters is derived for
further investigation and to feed the final optimization process,
whether as optimization parameters or as external perturbation
collective. The 10 most relevant perturbation factors and 4 to 6
prospective variable parameters are considered in a new, simplified
model. All of the parameters are affected by the mentioned
production variability. The objective functions of interest
are based on scalar output-s variability measures, so the
problem becomes an optimization under robustness and reliability constrains. The study shows an initial step on the development
path of a method to design and optimize complex micro
mechanisms composed of wide tolerated elements accounting
for the robustness and reliability of the systems- output.
Abstract: Protein residue contact map is a compact
representation of secondary structure of protein. Due to the
information hold in the contact map, attentions from researchers in
related field were drawn and plenty of works have been done
throughout the past decade. Artificial intelligence approaches have
been widely adapted in related works such as neural networks,
genetic programming, and Hidden Markov model as well as support
vector machine. However, the performance of the prediction was not
generalized which probably depends on the data used to train and
generate the prediction model. This situation shown the importance
of the features or information used in affecting the prediction
performance. In this research, support vector machine was used to
predict protein residue contact map on different combination of
features in order to show and analyze the effectiveness of the
features.
Abstract: This paper proposes an efficient method to classify
inverse synthetic aperture (ISAR) images. Because ISAR images can
be translated and rotated in the 2-dimensional image place, invariance
to the two factors is indispensable for successful classification. The
proposed method achieves invariance to translation and rotation of
ISAR images using a combination of two-dimensional Fourier
transform, polar mapping and correlation-based alignment of the
image. Classification is conducted using a simple matching score
classifier. In simulations using the real ISAR images of five scaled
models measured in a compact range, the proposed method yields
classification ratios higher than 97 %.
Abstract: Dilated cardiomyopathy (DCM) is a severe
cardiovascular disorder characterized by progressive systolic
dysfunction due to cardiac chamber dilatation and inefficient
myocardial contractility often leading to chronic heart failure.
Recently, a genome-wide association studies (GWASs) on DCM
indicate that the ZBTB17 gene rs10927875 single nucleotide
polymorphism is associated with DCM. The aim of the study was to
identify the distribution of ZBTB17 gene rs10927875 polymorphism
in 50 Slovak patients with DCM and 80 healthy control subjects
using the Custom Taqman®SNP Genotyping assays. Risk factors
detected at baseline in each group included age, sex, body mass
index, smoking status, diabetes and blood pressure. The mean age of
patients with DCM was 52.9±6.3 years; the mean age of individuals
in control group was 50.3±8.9 years. The distribution of investigated
genotypes of rs10927875 polymorphism within ZBTB17 gene in the
cohort of Slovak patients with DCM was as follows: CC (38.8%), CT
(55.1%), TT (6.1%), in controls: CC (43.8%), CT (51.2%), TT
(5.0%). The risk allele T was more common among the patients with
dilated cardiomyopathy than in normal controls (33.7% versus
30.6%). The differences in genotype or allele frequencies of ZBTB17
gene rs10927875 polymorphism were not statistically significant
(p=0.6908; p=0.6098). The results of this study suggest that ZBTB17
gene rs10927875 polymorphism may be a risk factor for
susceptibility to DCM in Slovak patients with DCM. Studies of
numerous files and additional functional investigations are needed to
fully understand the roles of genetic associations.
Abstract: The objective of this research was to study influence
parameters affecting to mechanical property of austenitic stainless
steel grade 304 (AISI 304) with Gas Metal Arc Welding (GMAW).
The research was applying factorial design experiment, which have
following interested parameters: welding current at 80, 90, and 100
Amps, welding speeds at 250, 300, and 350 mm/min, and shield gas
of 75% Ar + 25% CO2, 70% Ar + 25% CO2 + 5% O2 and 69.5% Ar +
25% CO2 + 5% O2 + 0.5% He gas. The study was done in following
aspects: ultimate tensile strength and elongation. A research study of
ultimate tensile strength found that main factor effect, which had the
highest strength to AISI 304 welding was shield gas of 70% Ar +
25% CO2 + 5% O2 at average of 954.81 N/mm2. Result of the highest
elongation was showed significantly different at interaction effect
between shield gas of 69.5%Ar+25%CO2+5%O2+.5%He and
welding speed at 250 mm/min at 47.94%.
Abstract: Many water supply systems in Australia are currently
undergoing significant reconfiguration due to reductions in long term
average rainfall and resulting low inflows to water supply reservoirs
since the second half of the 20th century. When water supply systems
undergo change, it is necessary to develop new operating rules,
which should consider climate, because the climate change is likely
to further reduce inflows. In addition, water resource systems are
increasingly intended to be operated to meet complex and multiple
objectives representing social, economic, environmental and
sustainability criteria. This is further complicated by conflicting
preferences on these objectives from diverse stakeholders. This paper
describes a methodology to develop optimum operating rules for
complex multi-reservoir systems undergoing significant change,
considering all of the above issues. The methodology is demonstrated
using the Grampians water supply system in northwest Victoria,
Australia. Initial work conducted on the project is also presented in
this paper.
Abstract: Rainfall records of rainfall station including the
rainfall potential per hour and rainfall mass of five heavy storms are
explored, respectively from 2001 to 2010. The rationalization formula
is to investigate the capability of flood peak duration of flood
detention pond in different rainfall conditions. The stable flood
detention model is also proposed by using system dynamic control
theory to get the message of flood detention pond in this research.
When rainfall frequency of one hour rainfall duration is more than
100-year frequency which exceeds the flood detention standard of
20-year frequency for the flood detention pond, the flood peak
duration of flood detention pond is 1.7 hours at most even though the
flood detention pond with maximum drainage potential about 15.0
m3/s of pumping system is constructed. If the rainfall peak current is
more than maximum drainage potential, the flood peak duration of
flood detention pond is about 1.9 hours at most. The flood detention
pond is the key factor of stable drainage control and flood prevention.
The critical factors of flood disaster is not only rainfall mass, but also
rainfall frequency of heavy storm in different rainfall duration and
flood detention frequency of flood detention system.
Abstract: Among neural models the Support Vector Machine
(SVM) solutions are attracting increasing attention, mostly because
they eliminate certain crucial questions involved by neural network
construction. The main drawback of standard SVM is its high
computational complexity, therefore recently a new technique, the
Least Squares SVM (LS–SVM) has been introduced. In this paper we
present an extended view of the Least Squares Support Vector
Regression (LS–SVR), which enables us to develop new
formulations and algorithms to this regression technique. Based on
manipulating the linear equation set -which embodies all information
about the regression in the learning process- some new methods are
introduced to simplify the formulations, speed up the calculations
and/or provide better results.
Abstract: At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.
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: 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.