Abstract: This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.
Abstract: The daily increase of organic waste materials resulting
from different activities in the country is one of the main factors for
the pollution of environment. Today, with regard to the low level of
the output of using traditional methods, the high cost of disposal
waste materials and environmental pollutions, the use of modern
methods such as anaerobic digestion for the production of biogas has
been prevailing. The collected biogas from the process of anaerobic
digestion, as a renewable energy source similar to natural gas but
with a less methane and heating value is usable. Today, with the help
of technologies of filtration and proper preparation, access to biogas
with features fully similar to natural gas has become possible. At
present biogas is one of the main sources of supplying electrical and
thermal energy and also an appropriate option to be used in four
stroke engine, diesel engine, sterling engine, gas turbine, gas micro
turbine and fuel cell to produce electricity. The use of biogas for
different reasons which returns to socio-economic and environmental
advantages has been noticed in CHP for the production of energy in
the world. The production of biogas from the technology of anaerobic
digestion and its application in CHP power plants in Iran can not only
supply part of the energy demands in the country, but it can
materialize moving in line with the sustainable development. In this
article, the necessity of the development of CHP plants with biogas
fuels in the country will be dealt based on studies performed from the
economic, environmental and social aspects. Also to prove the
importance of the establishment of these kinds of power plants from
the economic point of view, necessary calculations has been done as
a case study for a CHP power plant with a biogas fuel.
Abstract: The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.
Abstract: K-Means (KM) is considered one of the major
algorithms widely used in clustering. However, it still has some
problems, and one of them is in its initialization step where it is
normally done randomly. Another problem for KM is that it
converges to local minima. Genetic algorithms are one of the
evolutionary algorithms inspired from nature and utilized in the field
of clustering. In this paper, we propose two algorithms to solve the
initialization problem, Genetic Algorithm Initializes KM (GAIK) and
KM Initializes Genetic Algorithm (KIGA). To show the effectiveness
and efficiency of our algorithms, a comparative study was done
among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA),
and FCM [19].
Abstract: Internet Protocol version 4 (IPv4) address is decreasing and a rapid transition method to the next generation IP address (IPv6) should be established. This study aims to evaluate and select the best performance of the IPv6 address network transitionmechanisms, such as IPv4/IPv6 dual stack, transport Relay Translation (TRT) and Reverse Proxy with additional features. It is also aim to prove that faster access can be done while ensuring optimal usage of available resources used during the test and actual implementation. This study used two test methods such asInternet Control Message Protocol (ICMP)ping and ApacheBenchmark (AB) methodsto evaluate the performance.Performance metrics for this study include aspects ofaverageaccessin one second,time takenfor singleaccess,thedata transfer speed and the costof additional requirements.Reverse Proxy with Caching featureis the most efficientmechanism because of it simpler configurationandthe best performerfrom the test conducted.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: We report in this paper the procedure of a system of
automatic speech recognition based on techniques of the dynamic
programming. The technique of temporal retiming is a technique
used to synchronize between two forms to compare. We will see how
this technique is adapted to the field of the automatic speech
recognition. We will expose, in a first place, the theory of the
function of retiming which is used to compare and to adjust an
unknown form with a whole of forms of reference constituting the
vocabulary of the application. Then we will give, in the second place,
the various algorithms necessary to their implementation on machine.
The algorithms which we will present were tested on part of the
corpus of words in Arab language Arabdic-10 [4] and gave whole
satisfaction. These algorithms are effective insofar as we apply them
to the small ones or average vocabularies.
Abstract: Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
Abstract: This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.
Abstract: Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.
Abstract: Application of flexible structures has been
significantly, increased in industry and aerospace missions due to
their contributions and unique advantages over the rigid counterparts.
In this paper, vibration analysis of a flexible structure i.e., automobile
wiper blade is investigated and controlled. The wiper generates
unwanted noise and vibration during the wiping the rain and other
particles on windshield which may cause annoying noise in different
ranges of frequency. A two dimensional analytical modeled wiper
blade whose model accuracy is verified by numerical studies in
literature is considered in this study. Particle swarm optimization
(PSO) is employed in alliance with input shaping (IS) technique in
order to control or to attenuate the amplitude level of unwanted
noise/vibration of the wiper blade.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: This study was aimed to determine seasonal variations
of leaf nutrient concentrations to define nutrient needs related to
growing period and to compare irrigation programs in terms of
nutrient uptake. In this study,'Starkrimson Delicious' variety grafted
onto seedling rootstock was used during 2009-2010 growing seasons.
The study was conducted at E─ƒirdir Fruit Growing Research Station.
Leaf samples were taken in five different sample seasons (May, June,
July, August and September). Four different pan coefficients (0.50,
0.75, 1.0, 1.25) were applied during drip irrigation treatments in 7
days irrigation interval. Leaf K, Mg, Ca, P, Fe, Zn, Mn and Cu
concentrations were determined.
The results showed that among the seasonal changes, the highest
concentrations of K, Mg, P and Mn in leaves were recorded in May,
followed by a decrease in the other months, while in contrast Ca and
Fe showed the lowest concentration in May.
Results of the study demonstrate that among irrigation programs K
and Cu concentration in plants was significantly influenced. Cu
concentrations decreased with seasonal variations and different
irrigation programs. Thus, nutrient needs of 'Starkrimson Delicious'apple trees at different growth stages should be taken into
consideration before making effective fertilization program.
Abstract: Edge detection is usually the first step in medical
image processing. However, the difficulty increases when a
conventional kernel-based edge detector is applied to ultrasonic
images with a textural pattern and speckle noise. We designed an
adaptive diffusion filter to remove speckle noise while preserving the
initial edges detected by using a Sobel edge detector. We also propose
a genetic algorithm for edge selection to form complete boundaries of
the detected entities. We designed two fitness functions to evaluate
whether a criterion with a complex edge configuration can render a
better result than a simple criterion such as the strength of gradient.
The edges obtained by using a complex fitness function are thicker and
more fragmented than those obtained by using a simple fitness
function, suggesting that a complex edge selecting scheme is not
necessary for good edge detection in medical ultrasonic images;
instead, a proper noise-smoothing filter is the key.
Abstract: This study aims to initiate sustainable water management for tourist accommodations in Amphawa, Samut Songkram Province, Thailand. Wastewater generated by tourist accommodation was conducted in 10 homestays and resorts in Amphawa during August – October, 2011. The prominent parameters which are of pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Fat Oil and Grease (FOG), Nitrate (No3-), and Phosphate (PO43-) were conducted monthly. The results revealed that some parameters were over national water quality standard (Class II). Especially, 90% of tourist accommodations have been recorded that FOG was over the standard of wastewater quality from accommodation (group I: total room of accommodation less than 200 rooms). Therefore, grease trap and natural treatment should be utilized in tourist accommodations in order to reduce the discharged of fat, oil, and grease from tourism activities. In addition, number of tourists also relate statistically with BOD and Nitrate at 0.05 level of significance.
Abstract: Monitoring and control of cane sugar crystallization
processes depend on the stability of the supersaturation (σ ) state.
The most widely used information to represent σ is the electrical
conductivity κ of the solutions. Nevertheless, previous studies point
out the shortcomings of this approach: κ may be regarded as
inappropriate to guarantee an accurate estimation of σ in impure
solutions. To improve the process control efficiency, additional
information is necessary. The mass of crystals in the solution ( c m )
and the solubility (mass ratio of sugar to water / s w m m ) are relevant
to complete information. Indeed, c m inherently contains information
about the mass balance and / s w m m contains information about the
supersaturation state of the solution. The main problem is that c m
and / s w m m are not available on-line. In this paper, a model based
soft-sensor is presented for a final crystallization stage (C sugar).
Simulation results obtained on industrial data show the reliability of
this approach, c m and the crystal content ( cc ) being estimated with
a sufficient accuracy for achieving on-line monitoring in industry
Abstract: Owning to the high-speed feed rate and ultra spindle
speed have been used in modern machine tools, the tool-path
generation plays a key role in the successful application of a
High-Speed Machining (HSM) system. Because of its importance in
both high-speed machining and tool-path generation, approximating a
contour by NURBS format is a potential function in CAD/CAM/CNC
systems. It is much more convenient to represent an ellipse by
parametric form than to connect points laboriously determined in a
CNC system. A new approximating method based on optimum
processes and NURBS curves of any degree to the ellipses is presented
in this study. Such operations can be the foundation of tool-radius
compensation interpolator of NURBS curves in CNC system. All
operating processes for a CAD tool is presented and demonstrated by
practical models.
Abstract: Sickle cell anemia is a recessive genetic disease
caused by the presence in the red blood cell, of abnormal hemoglobin
called hemoglobin S. It results from the replacement in the beta chain
of the acid glutamic acid by valin at position 6. Topics may be
homozygous (SS) or heterozygous (AS) most often
asymptomatic. Other mutations result in compound heterozygous:
- Synthesis of hemoglobin C mutation in the sixth leucin codon
(heterozygous SC);
- ß-thalassemia (heterozygous S-ß thalassemia).
SS homozygous, heterozygous SC and S- ß -thalassemia are grouped
under the major sickle cell syndromes.
To make a laboratory diagnosis of hemoglobinopathies in a
portion of the population in region of Batna, our study was
conducted on 115 patients with suspected sickle cell anemia, all cases
have benefited from hematological tests as blood count (count RBC,
calculated erythrocyte indices, MCV and MCHC, measuring the
hemoglobin concentration) and a biochemical test in this case
electrophoresis CAPILLARYS HEMOGLOBIN (E).
The results showed:
27 cases of sickle cell anemia were found on 115 suspected cases,
73,03% homozygous sickle cell disease and 59,25% sickle cell trait.
Finally, the double heterozygous S/C, represent the incidence rate of
3, 70%.