Abstract: In this study, a comparative analysis of the approaches
associated with the use of neural network algorithms for effective
solution of a complex inverse problem – the problem of identifying
and determining the individual concentrations of inorganic salts in
multicomponent aqueous solutions by the spectra of Raman
scattering of light – is performed. It is shown that application of
artificial neural networks provides the average accuracy of
determination of concentration of each salt no worse than 0.025 M.
The results of comparative analysis of input data compression
methods are presented. It is demonstrated that use of uniform
aggregation of input features allows decreasing the error of
determination of individual concentrations of components by 16-18%
on the average.
Abstract: The article presents the results of the application of
artificial neural networks to separate the fluorescent contribution of
nanodiamonds used as biomarkers, adsorbents and carriers of drugs
in biomedicine, from a fluorescent background of own biological
fluorophores. The principal possibility of solving this problem is
shown. Use of neural network architecture let to detect fluorescence
of nanodiamonds against the background autofluorescence of egg
white with high accuracy - better than 3 ug/ml.
Abstract: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: A method is proposed for stable detection of
seismoacoustic sources in C-OTDR systems that guarantee given
upper bounds for probabilities of type I and type II errors. Properties
of the proposed method are rigorously proved. The results of
practical applications of the proposed method in a real C-OTDRsystem
are presented.
Abstract: Concerns on corrosion and effective coating
protection of double hull tankers and bulk carriers in service have
been raised especially in water ballast tanks (WBTs). Test
protocols/methodologies specifically that which is incorporated in the
International Maritime Organisation (IMO), Performance Standard
for Protective Coatings for Dedicated Sea Water ballast tanks (PSPC)
are being used to assess and evaluate the performance of the coatings
for type approval prior to their application in WBTs. However, some
of the type approved coatings may be applied as very thick films to
less than ideally prepared steel substrates in the WBT. As such films
experience hygrothermal cycling from operating and environmental
conditions, they become embrittled which may ultimately result in
cracking. This embrittlement of the coatings is identified as an
undesirable feature in the PSPC but is not mentioned in the test
protocols within it. There is therefore renewed industrial research
aimed at understanding this issue in order to eliminate cracking and
achieve the intended coating lifespan of 15 years in good condition.
This paper will critically review test protocols currently used for
assessing and evaluating coating performance, particularly the IMO
PSPC.
Abstract: In many communication and signal processing
systems, it is highly desirable to implement an efficient narrow-band
filter that decimate or interpolate the incoming signals. This paper
presents hardware efficient compensated CIC filter over a narrow
band frequency that increases the speed of down sampling by using
multiplierless decimation filters with polyphase FIR filter structure.
The proposed work analyzed the performance of compensated CIC
filter on the bases of the improvement of frequency response with
reduced hardware complexity in terms of no. of adders and
multipliers and produces the filtered results without any alterations.
CIC compensator filter demonstrated that by using compensation
with CIC filter improve the frequency response in passed of interest
26.57% with the reduction in hardware complexity 12.25%
multiplications per input sample (MPIS) and 23.4% additions per
input sample (APIS) w.r.t. FIR filter respectively.
Abstract: This study models the use of transcutaneous electrical
nerve stimulation on skin with a disk electrode in order to simulate
tissue damage. The current density distribution above a disk electrode
is known to be a dynamic and non-uniform quantity that is intensified
at the edges of the disk. The non-uniformity is subject to change
through using various electrode geometries or stimulation methods.
One of these methods known as edge-retarded stimulation has shown
to reduce this edge enhancement. Though progress has been made in
modeling the behavior of a disk electrode, little has been done to test
the validity of these models in simulating the actual heat transfer
from the electrode. This simulation uses finite element software to
couple the injection of current from a disk electrode to heat transfer
described by the Pennesbioheat transfer equation. An example
application of this model is studying an experimental form of
stimulation, known as edge-retarded stimulation. The edge-retarded
stimulation method will reduce the current density at the edges of the
electrode. It is hypothesized that reducing the current density edge
enhancement effect will, in turn, reduce temperature change and
tissue damage at the edges of these electrodes. This study tests this
hypothesis as a demonstration of the capabilities of this model. The
edge-retarded stimulation proved to be safer after this simulation. It is
shown that temperature change and the fraction of tissue necrosis is
much greater in the square wave stimulation. These results bring
implications for changes of procedures in transcutaneous electrical
nerve stimulation and transcutaneous spinal cord stimulation as well.
Abstract: In this paper the issue of dimensionality reduction is
investigated in finger vein recognition systems using kernel Principal
Component Analysis (KPCA). One aspect of KPCA is to find the
most appropriate kernel function on finger vein recognition as there
are several kernel functions which can be used within PCA-based
algorithms. In this paper, however, another side of PCA-based
algorithms -particularly KPCA- is investigated. The aspect of
dimension of feature vector in PCA-based algorithms is of
importance especially when it comes to the real-world applications
and usage of such algorithms. It means that a fixed dimension of
feature vector has to be set to reduce the dimension of the input and
output data and extract the features from them. Then a classifier is
performed to classify the data and make the final decision. We
analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in
this paper and investigate the optimal feature extraction dimension in
finger vein recognition using KPCA.
Abstract: The purposes of this study were to design and find
users’ satisfaction after using the decision support system for tourism
northern part of Thailand, which can provide tourists touristic
information and plan their personal voyage. Such information can be
retrieved systematically based on personal budget and provinces. The
samples of this study were five experts and users 30 persons white
collars in Bangkok. This decision support system was designed via
ASP.NET. Its database was developed by using MySQL, for
administrators are able to effectively manage the database. The
application outcome revealed that the innovation works properly as
sought in objectives. Specialists and white collars in Bangkok have
evaluated the decision support system; the result was satisfactorily
positive.
Abstract: Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”
Abstract: Roof top rainwater harvesting (RWH) has been
carried out worldwide to provide an inexpensive source of water for
many people. This research aims at evaluating the potential of roof
top rain water harvesting as a resource in Jordan. For the purpose of
this work, two case studies at Al-Jubiha and Shafa-Badran districts in
Amman city were selected. All existing rooftops in both districts
were identified by digitizing 2012 satellite images of the two districts
using Google earth and ArcGIS tools. Rational method was used to
estimate the potential volume of rainwater that can be harvested from
the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr
can be harvested in Al-Jubiha and Shafa-Badran districts,
respectively. This study should increase the attention to the
importance of implementing RWH technique in Jordanian residences
as a viable alternative for ensuring a continued source of non-potable
water.
Abstract: This paper analyzes innovation trends in South Korea
by means of the number of patent applications filed by residents and
nonresidents during the period 1965 to 2012. Making use of patent
data released by the World Intellectual Property Organization
(WIPO), we search for the presence of multiple structural changes in
patent application series in this country. These changes may suggest
that firms’ innovative activity has been modified as a result of
implementing some science, technology and innovation (STI)
policies. Accordingly, the new regulations implemented in this
country in the last decades have influenced its innovative activity.
The question conducting this research is thus how STI policies in
South Korea have influenced its innovation activity. The results
confirm the existence of multiple structural changes in the series of
patent applications resulting from alternative STI policies
implemented during these years.
Abstract: This paper presents the application of finite dynamic
programming, specifically the "Markov Chain" model, as part of the
decision making process of a company in the cosmetics sector located
in the vicinity of Bogota DC. The objective of this process was to
decide whether the company should completely reconstruct its
wastewater treatment plant or instead optimize the plant through the
addition of equipment. The goal of both of these options was to make
the required improvements in order to comply with parameters
established by national legislation regarding the treatment of waste
before it is released into the environment. This technique will allow
the company to select the best option and implement a solution for
the processing of waste to minimize environmental damage and the
acquisition and implementation costs.
Abstract: We have studied a method to widen the spectrum
of optical pulses that pass through an InGaAsP waveguide for
application to broadband optical communication. In particular, we
have investigated the competitive effect between spectral broadening
arising from nonlinear refraction (optical Kerr effect) and shrinking
due to two photon absorption in the InGaAsP waveguide with
χ(3) nonlinearity. The shrunk spectrum recovers broadening by
the enhancement effect of the nonlinear refractive index near the
bandgap of InGaAsP with a bandgap wavelength of 1490 nm. The
broadened spectral width at around 1525 nm (196.7 THz) becomes
10.7 times wider than that at around 1560 nm (192.3 THz) without
the enhancement effect, where amplified optical pulses with a pulse
width of ∼ 2 ps and a peak power of 10 W propagate through a
1-cm-long InGaAsP waveguide with a cross-section of 4 (μm)2.
Abstract: In remote sensing, shadow causes problems in many
applications such as change detection and classification. It is caused
by objects which are elevated, thus can directly affect the accuracy of
information. For these reasons, it is very important to detect shadows
particularly in urban high spatial resolution imagery which created a
significant problem. This paper focuses on automatic shadow
detection based on a new spectral index for multispectral imagery
known as Shadow Detection Index (SDI). The new spectral index
was tested on different areas of WorldView-2 images and the results
demonstrated that the new spectral index has a massive potential to
extract shadows with accuracy of 94% effectively and automatically.
Furthermore, the new shadow detection index improved road
extraction from 82% to 93%.
Abstract: We present our approach on using continuous delivery
pattern for release management. One of the key practices of agile and
lean teams is the continuous delivery of new features to stakeholders.
The main benefits of this approach lie in the ability to release new
applications rapidly which has real strategic impact on the
competitive advantage of an organization. Organizations that
successfully implement Continuous Delivery have the ability to
evolve rapidly to support innovation, provide stable and reliable
software in more efficient ways, decrease the amount of resources
need for maintenance, and lower the software delivery time and costs.
One of the objectives of this paper is to elaborate a case study where
IT division of Central Securities Depository Institution (MKK) of
Turkey apply Continuous Delivery pattern to improve release
management process.
Abstract: Artificial Neural Networks (ANN) trained using backpropagation
(BP) algorithm are commonly used for modeling
material behavior associated with non-linear, complex or unknown
interactions among the material constituents. Despite multidisciplinary
applications of back-propagation neural networks
(BPNN), the BP algorithm possesses the inherent drawback of
getting trapped in local minima and slowly converging to a global
optimum. The paper present a hybrid artificial neural networks and
genetic algorithm approach for modeling slump of ready mix
concrete based on its design mix constituents. Genetic algorithms
(GA) global search is employed for evolving the initial weights and
biases for training of neural networks, which are further fine tuned
using the BP algorithm. The study showed that, hybrid ANN-GA
model provided consistent predictions in comparison to commonly
used BPNN model. In comparison to BPNN model, the hybrid ANNGA
model was able to reach the desired performance goal quickly.
Apart from the modeling slump of ready mix concrete, the synaptic
weights of neural networks were harnessed for analyzing the relative
importance of concrete design mix constituents on the slump value.
The sand and water constituents of the concrete design mix were
found to exhibit maximum importance on the concrete slump value.
Abstract: The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.
Abstract: Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.
Abstract: In this paper, we apply the Exp-function method to
Rosenau-Kawahara and Rosenau-KdV equations. Rosenau-Kawahara
equation is the combination of the Rosenau and standard Kawahara
equations and Rosenau-KdV equation is the combination of the
Rosenau and standard KdV equations. These equations are nonlinear
partial differential equations (NPDE) which play an important role
in mathematical physics. Exp-function method is easy, succinct and
powerful to implement to nonlinear partial differential equations
arising in mathematical physics. We mainly try to present an
application of Exp-function method and offer solutions for common
errors wich occur during some of the recent works.