Abstract: Mechanical stress has a strong effect on the magnitude
of the Barkhausen-noise in structural steels. Because the
measurements are performed at the surface of the material, for a
sample sheet, the full effect can be described by a biaxial stress field.
The measured Barkhausen-noise is dependent on the orientation of
the exciting magnetic field relative to the axis of the stress tensor.
The sample inhomogenities including the residual stress also
modifies the angular dependence of the measured Barkhausen-noise.
We have developed a laboratory device with a cross like specimen
for bi-axial bending. The measuring head allowed performing
excitations in two orthogonal directions. We could excite the two
directions independently or simultaneously with different amplitudes.
The simultaneous excitation of the two coils could be performed in
phase or with a 90 degree phase shift. In principle this allows to
measure the Barkhausen-noise at an arbitrary direction without
moving the head, or to measure the Barkhausen-noise induced by a
rotating magnetic field if a linear superposition of the two fields can
be assumed.
Abstract: Constructing a portfolio of investments is one of the
most significant financial decisions facing individuals and
institutions. In accordance with the modern portfolio theory
maximization of return at minimal risk should be the investment goal
of any successful investor. In addition, the costs incurred when
setting up a new portfolio or rebalancing an existing portfolio must
be included in any realistic analysis.
In this paper rebalancing an investment portfolio in the presence of
transaction costs on the Croatian capital market is analyzed. The
model applied in the paper is an extension of the standard portfolio
mean-variance optimization model in which transaction costs are
incurred to rebalance an investment portfolio. This model allows
different costs for different securities, and different costs for buying
and selling. In order to find efficient portfolio, using this model, first,
the solution of quadratic programming problem of similar size to the
Markowitz model, and then the solution of a linear programming
problem have to be found. Furthermore, in the paper the impact of
transaction costs on the efficient frontier is investigated. Moreover, it
is shown that global minimum variance portfolio on the efficient
frontier always has the same level of the risk regardless of the amount
of transaction costs. Although efficient frontier position depends of
both transaction costs amount and initial portfolio it can be concluded
that extreme right portfolio on the efficient frontier always contains
only one stock with the highest expected return and the highest risk.
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: A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.
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 performance and analysis of speech recognition
system is illustrated in this paper. An approach to recognize the
English word corresponding to digit (0-9) spoken by 2 different
speakers is captured in noise free environment. For feature extraction,
speech Mel frequency cepstral coefficients (MFCC) has been used
which gives a set of feature vectors from recorded speech samples.
Neural network model is used to enhance the recognition
performance. Feed forward neural network with back propagation
algorithm model is used. However other speech recognition
techniques such as HMM, DTW exist. All experiments are carried
out on Matlab.
Abstract: In this paper, an effective non-destructive, noninvasive
approach for leak detection was proposed. The process relies
on analyzing thermal images collected by an IR viewer device that
captures thermo-grams. In this study a statistical analysis of the
collected thermal images of the ground surface along the expected
leak location followed by a visual inspection of the thermo-grams
was performed in order to locate the leak. In order to verify the
applicability of the proposed approach the predicted leak location
from the developed approach was compared with the real leak
location. The results showed that the expected leak location was
successfully identified with an accuracy of more than 95%.
Abstract: The Ombudsman is a procedural mechanism that
provides a different approach of dispute resolution. The ombudsman
primarily deals with specific grievances from the public against
governmental injustice and misconduct. The ombudsman theory is
considered an important instrument to any democratic government.
This is true since it improves the transparency of the governmental
activities in a world in which executive power are rising. Many
countries have adopted the concept of Ombudsman but under
different terminologies. This paper will provide the different types of
Ombudsman and the common activities/processes of fulfilling their
mandates.
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: Formal verification is proposed to ensure the
correctness of the design and make functional verification more
efficient. As cache plays a vital role in the design of System on Chip
(SoC), and cache with Memory Management Unit (MMU) and cache
memory unit makes the state space too large for simulation to verify,
then a formal verification is presented for such system design. In the
paper, a formal model checking verification flow is suggested and a
new cache memory model which is called “exhaustive search model”
is proposed. Instead of using large size ram to denote the whole cache
memory, exhaustive search model employs just two cache blocks. For
cache system contains data cache (Dcache) and instruction cache
(Icache), Dcache memory model and Icache memory model are
established separately using the same mechanism. At last, the novel
model is employed to the verification of a cache which is module of a
custom-built SoC system that has been applied in practical, and the
result shows that the cache system is verified correctly using the
exhaustive search model, and it makes the verification much more
manageable and flexible.
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 this study, an experiment was executed related to
the strength of wooden materials which have been commonly used
both in the past and present against pressure and whether fire
retardant materials used against fire have any effects or not. Totally
81 samples which included 3 different wood species, 3 different
sizes, 2 different fire retardants and 2 unprocessed samples were
prepared. Compressive pressure tests were applied to the prepared
samples, their variance analyses were executed in accordance with
the obtained results and it was aimed to determine the most
convenient wooden materials and fire-retardant coating material. It
was also determined that the species of wood and the species of
coating caused the decrease and/or increase in the resistance against
pressure.
Abstract: The Blue Nile Basin is the most important tributary of
the Nile River. Egypt and Sudan are almost dependent on water
originated from the Blue Nile. This multi-dependency creates
conflicts among the three countries Egypt, Sudan, and Ethiopia
making the management of these conflicts as an international issue.
Good assessment of the water resources of the Blue Nile is an
important to help in managing such conflicts. Hydrological models
are good tool for such assessment. This paper presents a critical
review of the nature and variability of the climate and hydrology of
the Blue Nile Basin as a first step of using hydrological modeling to
assess the water resources of the Blue Nile. Many several attempts
are done to develop basin-scale hydrological modeling on the Blue
Nile. Lumped and semi distributed models used averages of
meteorological inputs and watershed characteristics in hydrological
simulation, to analyze runoff for flood control and water resource
management. Distributed models include the temporal and spatial
variability of catchment conditions and meteorological inputs to
allow better representation of the hydrological process. The main
challenge of all used models was to assess the water resources of the
basin is the shortage of the data needed for models calibration and
validation. It is recommended to use distributed model for their
higher accuracy to cope with the great variability and complexity of
the Blue Nile basin and to collect sufficient data to have more
sophisticated and accurate hydrological modeling.
Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.
Abstract: In this article a comparison was made between Cu and
TiO2 supported catalysts on activated carbon for ozone
decomposition reaction. The activated carbon support in the case of
TiO2/AC sample was prepared by physicochemical pyrolysis and for
Cu/AC samples the supports are chemically modified carbons. The
prepared catalysts were synthesized by impregnation method. The
samples were annealed in two different regimes- in air and under
vacuum. To examine adsorption efficiency of the samples BET
method was used. All investigated catalysts supported on chemically
modified carbons have higher specific surface area compared to the
specific surface area of TiO2 supported catalysts, varying in the range
590÷620 m2/g. The method of synthesis of the precursors had
influenced catalytic activity.
Abstract: Sound exposure effects have been investigated by
broadcasting a group of broilers with sound of Quran verses (Group
B) whereas the other group is the control broilers (Group C). The
growth rate comparisons in terms of weight and raw meat texture
measured by shear force have been investigated. Twenty-seven
broilers were randomly selected from each group on Day 24 and
weight measurement was carried out every week till the harvest day
(Day 39).Group B showed a higher mean weight on Day 24 (1.441 ±
0.013 kg) than Group C. Significant difference in the weight on Day
39 existed for Group B compared to Group C (p < 0.05). However,
there was no significant (p >0.05) difference of shear force in the
same muscles (breast and drumstick raw meat) of both groups but the
shear force of the breast meat for Group B and C broilers was lower
(p < 0.05) than that of their drumstick meat. Thus, broadcasting the
sound of Quran verses in the coop can be applied to improve the
growth rate of broilers for producing better quality poultry.
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: Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.
Abstract: In recent years, the hair building fiber has become
popular, in other words, it is an effective method which helps people
who suffer hair loss or sparse hair since the hair building fiber is
capable to create a natural look of simulated hair rapidly. In the
markets, there are a lot of hair fiber brands that have been designed to
formulate an intense bond with hair strands and make the hair appear
more voluminous instantly. However, those products have their own
set of properties. Thus, in this report, some measurement techniques
are proposed to identify those products. Up to five different brands of
hair fiber are tested. The electrostatic and dielectric properties of the
hair fibers are macroscopically tested using design DC and high
frequency microwave techniques. Besides, the hair fibers are
microscopically analysis by magnifying the structures of the fiber
using scanning electron microscope (SEM). From the SEM photos,
the comparison of the uniformly shaped and broken rate of the hair
fibers in the different bulk samples can be observed respectively.