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: 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 detection of the polymer melt state during
manufacture process is regarded as an efficient way to control the
molded part quality in advance. Online monitoring rheological
property of polymer melt during processing procedure provides an
approach to understand the melt state immediately. Rheological
property reflects the polymer melt state at different processing
parameters and is very important in injection molding process
especially. An approach that demonstrates how to calculate
rheological property of polymer melt through in-process
measurement, using injection molding as an example, is proposed in
this study. The system consists of two sensors and a data acquisition
module can process the measured data, which are used for the
calculation of rheological properties of polymer melt. The rheological
properties of polymer melt discussed in this study include shear rate
and viscosity which are investigated with respect to injection speed
and melt temperature. The results show that the effect of injection
speed on the rheological properties is apparent, especially for high
melt temperature and should be considered for precision molding
process.
Abstract: The ultrasound imaging is very popular to diagnosis
the disease because of its non-invasive nature. The ultrasound
imaging slowly produces low quality images due to the presence of
spackle noise and wave interferences. There are several algorithms to
be proposed for the segmentation of ultrasound carotid artery images
but it requires a certain limit of user interaction. The pixel in an
image is highly correlated so the spatial information of surrounding
pixels may be considered in the process of image segmentation which
improves the results further. When data is highly correlated, one pixel
may belong to more than one cluster with different degree of
membership. There is an important step to computerize the evaluation
of arterial disease severity using segmentation of carotid artery lumen
in 2D and 3D ultrasonography and in finding vulnerable
atherosclerotic plaques susceptible to rupture which can cause stroke.
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: Nic Pizzolatto’s True Detective offers profound
mythological and philosophical ramblings for audiences with literary
sensibilities. An American Sothern Gothic with its Bayon landscape
of the Gulf Coast of Louisiana, where two detectives Rustin Cohle
and Martin Hart begin investigating the isolated murder of Dora
Lange, only to discover an entrenched network of perversion and
corruption, offers an existential outlook. The proposed research paper
shall attempt to investigate the pervasive themes of gothic and
existentialism in the music of the first season of the series.
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: Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
Abstract: This paper proposes a mathematical model and
examines the performance of an exact algorithm for a location–
transportation problems in humanitarian relief. The model determines
the number and location of distribution centers in a relief network,
the amount of relief supplies to be stocked at each distribution center
and the vehicles to take the supplies to meet the needs of disaster
victims under capacity restriction, transportation and budgetary
constraints. The computational experiments are conducted on the
various sizes of problems that are generated. Branch and bound
algorithm is applied for these problems. The results show that this
algorithm can solve problem sizes of up to three candidate locations
with five demand points and one candidate location with up to twenty
demand points without premature termination.
Abstract: Cement concrete is a complex mixture of different
materials. Behaviour of concrete depends on its mix proportions and
constituents when it is subjected to elevated temperatures. Principal
effects due to elevated temperatures are loss in compressive strength,
loss in weight or mass, change in colour and spall of concrete. The
experimental results of normal concrete and high strength concrete
subjected elevated temperatures at 200°C, 400°C, 600°C, and 800°C
and different cooling regimes viz. air cooling, water quenching on
different grade of concrete are reported in this paper.
Abstract: IEEE 802.16 (WiMAX) aims to present high speed
wireless access to cover wide range coverage. The base station (BS)
and the subscriber station (SS) are the main parts of WiMAX.
WiMAX uses either Point-to-Multipoint (PMP) or mesh topologies.
In the PMP mode, the SSs connect to the BS to gain access to the
network. However, in the mesh mode, the SSs connect to each other
to gain access to the BS.
The main components of QoS management in the 802.16 standard
are the admission control, buffer management and packet scheduling.
In this paper, we use QualNet 5.0.2 to study the performance of
different scheduling schemes, such as WFQ, SCFQ, RR and SP when
the numbers of SSs increase. We find that when the number of SSs
increases, the average jitter and average end-to-end delay is increased
and the throughput is reduced.
Abstract: It is likely that robots will cross the boundaries of
industry into households over the next decades. With demographic
challenges worldwide, the future ageing populations will require the
introduction of assistive technologies capable of providing, care,
human dignity and quality of life through the aging process. Robotics
technology has a high potential for being used in the areas of social
and healthcare by promoting a wide range of activities such as
entertainment, companionship, supervision or cognitive and physical
assistance. However such close Human Robotics Interaction (HRI)
encompass a rich set of ethical scenarios that need to be addressed
before Socially Assistive Robots (SARs) reach the global markets.
Such interactions with robots may seem a worthy goal for many
technical/financial reasons but inevitably require close attention to
the ethical dimensions of such interactions. This article investigates
the current HRI benchmark of social success. It revises it according
to the ethical principles of beneficence, non-maleficence and justice
aligned with social care ethos. An extension of such benchmark is
proposed based on an empirical study of HRIs conducted with elderly
groups.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: The objective of this study was to assess whether
living in proximity to a roofing fiber cement factory in southern
Thailand was associated with physical, mental, social, and spiritual
health domains measured in a self-reported health risk assessment
(HRA) questionnaire. A cross-sectional study was conducted among
community members divided into two groups: near population (living
within 0-2km of factory) and far population (living within 2-5km of
factory) (N=198). A greater proportion of those living far from the
factory (65.34%) reported physical health problems than the near
group (51.04%) (p =0.032). This study has demonstrated that the near
population group had higher proportion of participants with positive
ratings on mental assessment (30.34%) and social health impacts
(28.42%) than far population group (10.59% and 16.67%,
respectively) (p
Abstract: Governments collect and produce large amounts of
data. Increasingly, governments worldwide have started to implement
open data initiatives and also launch open data portals to enable the
release of these data in open and reusable formats. Therefore, a large
number of open data repositories, catalogues and portals have been
emerging in the world. The greater availability of interoperable and
linkable open government data catalyzes secondary use of such data,
so they can be used for building useful applications which leverage
their value, allow insight, provide access to government services, and
support transparency. The efficient development of successful open
data portals makes it necessary to evaluate them systematic, in order
to understand them better and assess the various types of value they
generate, and identify the required improvements for increasing this
value. Thus, the attention of this paper is directed particularly to the
field of open data portals. The main aim of this paper is to compare
the selected open data portals on the national level using content
analysis and propose a new evaluation framework, which further
improves the quality of these portals. It also establishes a set of
considerations for involving businesses and citizens to create eservices
and applications that leverage on the datasets available from
these portals.
Abstract: This paper presents two types of microstrip bandpass
filter (BPF) at microwave frequencies. The first one is a tunable BPF
using planar patch resonators based on a varactor diode. The filter is
formed by a triple mode circular patch resonator with two pairs of
slots, in which the varactor diodes are connected. Indeed, this filter is
initially centered at 2.4 GHz; the center frequency of the tunable
patch filter could be tuned up to 1.8 GHz simultaneously with the
bandwidth, reaching high tuning ranges. Lossless simulations were
compared to those considering the substrate dielectric, conductor
losses and the equivalent electrical circuit model of the tuning
element in order to assess their effects. Within these variations,
simulation results showed insertion loss better than 2 dB and return
loss better than 10 dB over the passband. The second structure is a
BPF for ultra-wideband (UWB) applications based on multiple-mode
resonator (MMR) and rectangular-shaped defected ground structure
(DGS). This filter, which is compact size of 25.2 x 3.8 mm2, provides
in the pass band an insertion loss of 0.57 dB and a return loss greater
than 12 dB. The proposed filters presents good performances and the
simulation results are in satisfactory agreement with the
experimentation ones reported elsewhere.
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.
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.