Abstract: In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..
Abstract: Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.
Abstract: A novel physico-chemical route to produce few layer graphene nanoribbons with atomically smooth edges is reported, via acid treatment (H2SO4:HNO3) followed by characteristic thermal shock processes involving extremely cold substances. Samples were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. This method demonstrates the importance of having the nanotubes open ended for an efficient uniform unzipping along the nanotube axis. The average dimensions of these nanoribbons are approximately ca. 210 nm wide and consist of few layers, as observed by transmission electron microscopy. The produced nanoribbons exhibit different chiralities, as observed by high resolution transmission electron microscopy. This method is able to provide graphene nanoribbons with atomically smooth edges which could be used in various applications including sensors, gas adsorption materials, composite fillers, among others.
Abstract: Alzheimer is known as the loss of mental functions
such as thinking, memory, and reasoning that is severe enough to
interfere with a person's daily functioning. The appearance of
Alzheimer Disease symptoms (AD) are resulted based on which part
of the brain has a variety of infection or damage. In this case, the
MRI is the best biomedical instrumentation can be ever used to
discover the AD existence. Therefore, this paper proposed a fusion
method to distinguish between the normal and (AD) MRIs. In this
combined method around 27 MRIs collected from Jordanian
Hospitals are analyzed based on the use of Low pass -morphological
filters to get the extracted statistical outputs through intensity
histogram to be employed by the descriptive box plot. Also, the
artificial neural network (ANN) is applied to test the performance of
this approach. Finally, the obtained result of t-test with confidence
accuracy (95%) has compared with classification accuracy of ANN
(100 %). The robust of the developed method can be considered
effectively to diagnose and determine the type of AD image.
Abstract: In this study, we used shape memory alloys as
actuators to build a biomorphic robot which can imitate the motion of
an earthworm. The robot can be used to explore in a narrow space.
Therefore we chose shape memory alloys as actuators. Because of the
small deformation of a wire shape memory alloy, spiral shape memory
alloys are selected and installed both on the X axis and Y axis (each
axis having two shape memory alloys) to enable the biomorphic robot
to do reciprocating motion. By the mechanism we designed, the robot
can increase the distance as it moves in a duty cycle. In addition, two
shape memory alloys are added to the robot head for controlling right
and left turns. By sending pulses through the I/O card from the
controller, the signals are then amplified by a driver to heat the shape
memory alloys in order to make the SMA shrink to pull the mechanism
to move.
Abstract: Neural processors have shown good results for
detecting a certain character in a given input matrix. In this paper, a
new idead to speed up the operation of neural processors for character
detection is presented. Such processors are designed based on cross
correlation in the frequency domain between the input matrix and the
weights of neural networks. This approach is developed to reduce the
computation steps required by these faster neural networks for the
searching process. The principle of divide and conquer strategy is
applied through image decomposition. Each image is divided into
small in size sub-images and then each one is tested separately by
using a single faster neural processor. Furthermore, faster character
detection is obtained by using parallel processing techniques to test the
resulting sub-images at the same time using the same number of faster
neural networks. In contrast to using only faster neural processors, the
speed up ratio is increased with the size of the input image when using
faster neural processors and image decomposition. Moreover, the
problem of local subimage normalization in the frequency domain is
solved. The effect of image normalization on the speed up ratio of
character detection is discussed. Simulation results show that local
subimage normalization through weight normalization is faster than
subimage normalization in the spatial domain. The overall speed up
ratio of the detection process is increased as the normalization of
weights is done off line.
Abstract: Studying literature theme in the fields of tourism and
sustainable development and its importance in today world and their
criteria in architecture, here in this article we will also study the area
where the selected site is located; beside the Aab-Ask Village located
in Larijan region in Mazandaran province on the way to Haraz – one
of the tourism routes of Iran. After these studies by analyzing the
site, its strong potentials – such as mineral water springs (hot
springs), geothermal, landscapes and ideal climate - as a tourist
attraction spot in the region, and considering sustainable
development criteria – with regard to limits and available facilities –
a plan was offered that could change the region to provide the needs
of local people and in addition change it to a place where tourism
services is offered to the visitors and make it an acceptable sample of
stable building in Iran. Finally the reason to make design for this
complex is recovery of natural and historical values of Aab-Ask area
regarding development and sustainable architecture criteria in the
form of a functional sample which can be a suitable place to fulfill
this goal for having lots of strong points in attracting cultural and
sustainable tourist.
Abstract: Toxic and bloom-forming cyanobacterium Microcystis
aeruginosa was exposed to antialgal allelochemical gramine (0, 0.5, 1,
2, 4, 8 mg·L-1), The effects of gramine on photosynthetic pigments
(lipid soluble: chlorophyll a and β-carotene; water soluble:
phycocyanin, allophycocyanin, phycoerythrin, and total phycobilins)
and absorption spectra were studied in order to identify the most
sensitive pigment probe implicating the crucial suppression site on
photosynthetic apparatus. The results obtained indicated that all
pigment parameters were decreased with gramine concentration
increasing and exposure time extending. The above serious bleaching
of pigments was also reflected on the scanning results of absorption
spectra. Phycoerytherin exhibited the highest sensitivity to gramine
added, following by the largest relative decrease. It was concluded that
gramine seriously influenced algal photosynthetic activity by
destroying photosynthetic pigments and phycoerythrin most sensitive
to gramine might be contributed to its placing the outside of
phycobilins.
Abstract: A son in every Hindu society pays his own father the debt and he owes him for his own life whereas a girl child is treated as a burden mainly in case of first child. Even today in India we have many societies which does not welcome girl child. Although there is an increase in overall sex ratio, there is a continuous decline in child sex ratio. This paper focuses on issues of sex selective abortion in Rajasthan based on secondary data. It is found that 90.0 percentages of women in Rajasthan wants at least one son. Around 34.3 percentages of women wants more sons than daughters and only 1.5 percentages of women wants more daughters than sons. It is very common among the rich and educated people.
Abstract: Clusters of microcalcifications in mammograms are an
important sign of breast cancer. This paper presents a complete
Computer Aided Detection (CAD) scheme for automatic detection of
clustered microcalcifications in digital mammograms. The proposed
system, MammoScan μCaD, consists of three main steps. Firstly
all potential microcalcifications are detected using a a method for
feature extraction, VarMet, and adaptive thresholding. This will also
give a number of false detections. The goal of the second step,
Classifier level 1, is to remove everything but microcalcifications.
The last step, Classifier level 2, uses learned dictionaries and sparse
representations as a texture classification technique to distinguish
single, benign microcalcifications from clustered microcalcifications,
in addition to remove some remaining false detections. The system
is trained and tested on true digital data from Stavanger University
Hospital, and the results are evaluated by radiologists. The overall
results are promising, with a sensitivity > 90 % and a low false
detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).
Abstract: Power Factor (PF) is one of the most important parameters in the electrical systems, especially in the water pumping station. The low power factor value of the water pumping stations causes penalty for the electrical bill. There are many methods use for power factor improvement. Each one of them uses a capacitor on the electrical power network. The position of the capacitors is varied depends on many factors such as; voltage level and capacitors rating. Adding capacitors on the motor terminals increase the supply power factor from 0.8 to more than 0.9 but these capacitors cause some problems for the electrical grid network, such as increasing the harmonic contents of the grid line voltage. In this paper the effects of using capacitors in the water pumping stations to improve the power factor value on the harmonic contents of the electrical grid network are studied. One of large water pumping stations in Kafr El-Shikh Governorate in Egypt was used, as a case study. The effect of capacitors on the line voltage harmonic contents is measured. The station uses capacitors to improve the PF values at the 1 lkv grid network. The power supply harmonics values are measured by a power quality analyzer at different loading conditions. The results showed that; the capacitors improved the power factor value of the feeder and its value increased than 0.9. But the THD values are increased by adding these capacitors. The harmonic analysis showed that; the 13th, 17th, and 19th harmonics orders are increased also by adding the capacitors.
Abstract: The RK5GL3 method is a numerical method for solving
initial value problems in ordinary differential equations, and is based
on a combination of a fifth-order Runge-Kutta method and 3-point
Gauss-Legendre quadrature. In this paper we describe the propagation
of local errors in this method, and show that the global order of
RK5GL3 is expected to be six, one better than the underlying Runge-
Kutta method.
Abstract: In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.
Abstract: The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease.
Abstract: This paper addresses the controller synthesis problem of discrete-time switched positive systems with bounded time-varying delays. Based on the switched copositive Lyapunov function approach, some necessary and sufficient conditions for the existence of state-feedback controller are presented as a set of linear programming and linear matrix inequality problems, hence easy to be verified. Another advantage is that the state-feedback law is independent on time-varying delays and initial conditions. A numerical example is provided to illustrate the effectiveness and feasibility of the developed controller.
Abstract: The work presents a development of EN338 strength classes for Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum Nigerian timber species. The specimens for experimental measurements were obtained from the timber-shed at the famous Panteka market in Kaduna in the northern part of Nigeria. Laboratory experiments were conducted to determine the physical and mechanical properties of the selected timber species in accordance with EN 13183-1 and ASTM D193. The mechanical properties were determined using three point bending test. The generated properties were used to obtain the characteristic values of the material properties in accordance with EN384. The selected timber species were then classified according to EN 338. Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum were assigned to strength classes D40, C14, D40 and D24 respectively. Other properties such as tensile and compressive strengths parallel and perpendicular to grains, shear strength as well as shear modulus were obtained in accordance with EN 338.
Abstract: Sufficient linear matrix inequalities (LMI) conditions for regularization of discrete-time singular systems are given. Then a new class of regularizing stabilizing controllers is discussed. The proposed controllers are the sum of predictive and memoryless state feedbacks. The predictive controller aims to regularizing the singular system while the memoryless state feedback is designed to stabilize the resulting regularized system. A systematic procedure is given to calculate the controller gains through linear matrix inequalities.
Abstract: In most study fields, a phenomenon may not be
studied directly but it will be examined indirectly by phenomenon
model. Making an accurate model of system, there is attained new
information from modeled phenomenon without any charge, danger,
etc... there have been developed more solutions for describing and
analyzing the recent complicated systems but few of them have
analyzed the performance in the range of system description. Petri
nets are of limited solutions which may make such union. Petri nets
are being applied in problems related to modeling and designing the
systems. Theory of Petri nets allow a system to model
mathematically by a Petri net and analyzing the Petri net can then
determine main information of modeled system-s structure and
dynamic. This information can be used for assessing the performance
of systems and suggesting corrections in the system. In this paper,
beside the introduction of Petri nets, a real case study will be studied
in order to show the application of generalized stochastic Petri nets in
modeling a resource sharing production system and evaluating the
efficiency of its machines and robots. The modeling tool used here is
SHARP software which calculates specific indicators helping to
make decision.
Abstract: The control of oxygen flow rate during growth of
titanium dioxide by mass flow controller in DC plasma sputtering
growth system is studied. The impedance of TiO2 films for inductance
effect is influenced by annealing time and oxygen flow rate. As
annealing time is increased, the inductance of TiO2 film is the more.
The growth condition of optimum and maximum inductance for TiO2
film to serve as sensing device are oxygen flow rate of 15 sccm and
large annealing time. The large inductance of TiO2 film will be
adopted to fabricate the biosensor to obtain the high sensitivity of
sensing in biology.
Abstract: This paper describes reactive neural control used to
generate phototaxis and obstacle avoidance behavior of walking
machines. It utilizes discrete-time neurodynamics and consists of
two main neural modules: neural preprocessing and modular neural
control. The neural preprocessing network acts as a sensory fusion
unit. It filters sensory noise and shapes sensory data to drive the
corresponding reactive behavior. On the other hand, modular neural
control based on a central pattern generator is applied for locomotion
of walking machines. It coordinates leg movements and can generate
omnidirectional walking. As a result, through a sensorimotor loop this
reactive neural controller enables the machines to explore a dynamic
environment by avoiding obstacles, turn toward a light source, and
then stop near to it.