Abstract: Radio Frequency Identification (RFID) has become a
key technology in the emerging concept of Internet of Things (IoT).
Naturally, business applications would require the deployment of
various RFID systems developed by different vendors that use
different data formats and structures. This heterogeneity poses a
challenge in developing real-life IoT systems with RFID, as
integration is becoming very complex and challenging. Semantic
integration is a key approach to deal with this challenge. To do so,
ontology for RFID systems need to be developed in order to
annotated semantically RFID systems, and hence, facilitate their
integration. Accordingly, in this paper, we propose ontology for
RFID systems. The proposed ontology can be used to semantically
enrich RFID systems, and hence, improve their usage and reasoning.
Abstract: Polycyclic Aromatic Hydrocarbons (PAHs) are
formed mainly because of incomplete combustion of organic
materials during industrial, domestic activities or natural occurrence.
Their toxicity and contamination of terrestrial and aquatic ecosystem
have been established. However, with limited validity index, previous
research has focused on PAHs isomer pair ratios of variable
physicochemical properties in source identification. The objective of
this investigation was to determine the empirical validity of Pearson
Correlation Coefficient (PCC) and Cluster Analysis (CA) in PAHs
source identification along soil samples of different land uses.
Therefore, 16 PAHs grouped, as Endocrine Disruption Substances
(EDSs) were determined in 10 sample stations in top and sub soils
seasonally. PAHs was determined the use of Varian 300 gas
chromatograph interfaced with flame ionization detector. Instruments
and reagents used are of standard and chromatographic grades
respectively. PCC and CA results showed that the classification of
PAHs along pyrolitic and petrogenic organics used in source
signature is about the predominance PAHs in environmental matrix.
Therefore, the distribution of PAHs in the studied stations revealed
the presence of trace quantities of the vast majority of the sixteen
PAHs, which may ultimately inhabit the actual source signature
authentication. Therefore, factors to be considered when evaluating
possible sources of PAHs could be; type and extent of bacterial
metabolism, transformation products/substrates, and environmental
factors such as salinity, pH, oxygen concentration, nutrients, light
intensity, temperature, co-substrates, and environmental medium are
hereby recommended as factors to be considered when evaluating
possible sources of PAHs.
Abstract: The paper is focused to the evaluation railway tracks
in the Slovakia by using Multi-Criteria method. Evaluation of railway
tracks has important impacts for the assessment of investment in
technical equipment. Evaluation of railway tracks also has an
important impact for the allocation of marshalling yards. Marshalling
yards are in transport model as centers for the operation assigned
catchment area. This model is one of the effective ways to meet the
development strategy of the European Community's railways. By
applying this model in practice, a transport company can guarantee a
higher quality of service and then expect an increase in performance.
The model is also applicable to other rail networks. This model
supplements a theoretical problem of train formation problem of new
ways of looking at evaluation of factors affecting the organization of
wagon flows.
Abstract: The article includes the results and conclusions from
empirical researches that had been done. The research focuses on the
impact of investments made in small and medium-sized enterprises
financed from EU funds on the competitiveness of these companies.
The researches includes financial results in sales revenue and net
income, expenses, and many other new products/services on offer,
higher quality products and services, more modern methods of
production, innovation in management processes, increase in the
number of customers, increase in market share, increase in
profitability of production and provision of services. The main
conclusions are that, companies with direct investments under this
measure shall apply the modern methods of production. The
consequence of this is to increase the quality of our products and
services. Furthermore, both small and medium-sized enterprises have
introduced new products and services. Investments were carried out,
thus enabling better work organization in enterprises. Entrepreneurs
would guarantee higher quality of service, which would result in
better relationships with their customers, what is more, noting the rise
in number of clients. More than half of the companies indicated that
the investments contributed to the increase in market share. Same
thing as for market reach and brand recognition of particular
company. An interesting finding is that, investments in small
enterprises were more effective than medium-sized enterprises.
Abstract: Brain-Computer Interfaces (BCIs) measure brain
signals activity, intentionally and unintentionally induced by users,
and provides a communication channel without depending on the
brain’s normal peripheral nerves and muscles output pathway.
Feature Selection (FS) is a global optimization machine learning
problem that reduces features, removes irrelevant and noisy data
resulting in acceptable recognition accuracy. It is a vital step
affecting pattern recognition system performance. This study presents
a new Binary Particle Swarm Optimization (BPSO) based feature
selection algorithm. Multi-layer Perceptron Neural Network
(MLPNN) classifier with backpropagation training algorithm and
Levenberg-Marquardt training algorithm classify selected features.
Abstract: Wireless Sensor Networks (WSNs), which sense
environmental data with battery-powered nodes, require multi-hop
communication. This power-demanding task adds an extra workload
that is unfairly distributed across the network. As a result, nodes run
out of battery at different times: this requires an impractical
individual node maintenance scheme. Therefore we investigate a new
Cooperative Sensing approach that extends the WSN operational life
and allows a more practical network maintenance scheme (where all
nodes deplete their batteries almost at the same time). We propose a
novel cooperative algorithm that derives a piecewise representation
of the sensed signal while controlling approximation accuracy.
Simulations show that our algorithm increases WSN operational life
and spreads communication workload evenly. Results convey a
counterintuitive conclusion: distributing workload fairly amongst
nodes may not decrease the network power consumption and yet
extend the WSN operational life. This is achieved as our cooperative
approach decreases the workload of the most burdened cluster in the
network.
Abstract: In this paper genetic based test data compression is
targeted for improving the compression ratio and for reducing the
computation time. The genetic algorithm is based on extended pattern
run-length coding. The test set contains a large number of X value
that can be effectively exploited to improve the test data
compression. In this coding method, a reference pattern is set and its
compatibility is checked. For this process, a genetic algorithm is
proposed to reduce the computation time of encoding algorithm. This
coding technique encodes the 2n compatible pattern or the inversely
compatible pattern into a single test data segment or multiple test data
segment. The experimental result shows that the compression ratio
and computation time is reduced.
Abstract: NiFe2O4 (nickel ferrite), ZnFe2O4 (zinc ferrite) and
Ni0.5Zn0.5Fe2O4 (nickel-zinc ferrite) were prepared by
mechanochemical route in a planetary ball mill starting from mixture
of the appropriate quantities of the Ni(OH)2/Fe(OH)3,
Zn(OH)2/Fe(OH)3 and Ni(OH)2/Zn(OH)2/Fe(OH)3 hydroxide
powders. In order to monitor the progress of chemical reaction and
confirm phase formation, powder samples obtained after 25 h, 18 h
and 10 h of milling were characterized by X-ray diffraction (XRD),
transmission electron microscopy (TEM), IR, Raman and Mössbauer
spectroscopy. It is shown that the soft mechanochemical method, i.e.
mechanochemical activation of hydroxides, produces high quality
single phase ferrite samples in much more efficient way. From the IR
spectroscopy of single phase samples it is obvious that energy of
modes depends on the ratio of cations. It is obvious that all samples
have more than 5 Raman active modes predicted by group theory in
the normal spinel structure. Deconvolution of measured spectra
allows one to conclude that all complex bands in the spectra are made
of individual peaks with the intensities that vary from spectrum to
spectrum. The deconvolution of Raman spectra allows to separate
contributions of different cations to a particular type of vibration and
to estimate the degree of inversion.
Abstract: Recent investigations have demonstrated the global
sea level rise due to climate change impacts. In this study, climate
changes study the effects of increasing water level in the strait of
Hormuz. The probable changes of sea level rise should be
investigated to employ the adaption strategies. The climatic output
data of a GCM (General Circulation Model) named CGCM3 under
climate change scenario of A1b and A2 were used. Among different
variables simulated by this model, those of maximum correlation
with sea level changes in the study region and least redundancy
among themselves were selected for sea level rise prediction by using
stepwise regression. One of models (Discrete Wavelet artificial
Neural Network) was developed to explore the relationship between
climatic variables and sea level changes. In these models, wavelet
was used to disaggregate the time series of input and output data into
different components and then ANN was used to relate the
disaggregated components of predictors and input parameters to each
other. The results showed in the Shahid Rajae Station for scenario
A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea
level rise is among 90 t0 105 cm. Furthermore, the result showed a
significant increase of sea level at the study region under climate
change impacts, which should be incorporated in coastal areas
management.
Abstract: The paper is focused on the operational model for
transport the single wagon consignments on railway network by
using two different models of train formation. The paper gives an
overview of possibilities of improving the quality of transport
services. Paper deals with two models used in problematic of train
formatting - time continuously and time discrete. By applying these
models in practice, the transport company can guarantee a higher
quality of service and expect increasing of transport performance.
The models are also applicable into others transport networks. The
models supplement a theoretical problem of train formation by new
ways of looking to affecting the organization of wagon flows.
Abstract: The ultimate purpose of this investigation was to
determine the teachers’ opinions as well as students’ opinions
towards the Adapted English Lessons. The subjects of the study were
5 Thai teachers, who teach English, and 85 Grade 10 mixed-ability
students at Triamudom Suksa Pattanakarn Ratchada School,
Bangkok, Thailand. The research instruments included questionnaires
and the informal interview. The data from the research instruments
was collected and analyzed concerning linguistic principles of
minimal pair and articulatory phonetics as well as teaching
techniques of mimicry-memorization; vocabulary substitution drills,
language pattern drills, reading comprehension exercise, practicing
listening, speaking and writing skill and communicative activities;
informal talk and free writing. The data was statistically compiled
according to an arithmetic percentage. The results showed that the
teachers and students have very highly positive opinions towards
adapting linguistic principles for teaching and learning phonological
accuracy. Teaching techniques provided in the Adapted English
Lessons can be used efficiently in the classroom. The teachers and
students have positive opinions towards them too.
Abstract: Targeted drug delivery is a method of delivering
medication to a patient in a manner that increases the concentration
of the medication in some parts of the body relative to others.
Targeted drug delivery seeks to concentrate the medication in the
tissues of interest while reducing the relative concentration of the
medication in the remaining tissues. This improves efficacy of the
while reducing side effects. In the present work, we investigate the
effect of magnetic field, flow rate and particle concentration on the
capturing of magnetic particles transported in a stent implanted
fluidic channel. Iron oxide magnetic nanoparticles (Fe3O4)
nanoparticles were synthesized via co-precipitation method. The
synthesized Fe3O4 nanoparticles were added in the de-ionized (DI)
water to prepare the Fe3O4 magnetic particle suspended fluid. This
fluid is transported in a cylindrical tube of diameter 8 mm with help
of a peristaltic pump at different flow rate (25-40 ml/min). A
ferromagnetic coil of SS 430 has been implanted inside the
cylindrical tube to enhance the capturing of magnetic nanoparticles
under magnetic field. The capturing of magnetic nanoparticles was
observed at different magnetic magnetic field, flow rate and particle
concentration. It is observed that capture efficiency increases from
47-67% at magnetic field 2-5kG, respectively at particle
concentration 0.6mg/ml and at flow rate 30 ml/min. However, the
capture efficiency decreases from 65 to 44% by increasing the flow
rate from 25 to 40 ml/min, respectively. Furthermore, it is observed
that capture efficiency increases from 51 to 67% by increasing the
particle concentration from 0.3 to 0.6 mg/ml, respectively.
Abstract: The objective of this study was to synthesize and
characterize the poly(alkenoic acid)s with different molecular
structures, use these polymers to formulate a dental cement
restorative, and study the effect of molecular structures on reaction
kinetics, viscosity, and mechanical strengths of the formed polymers
and cement restoratives. In this study, poly(alkenoic acid)s with
different molecular structures were synthesized. The purified
polymers were formulated with commercial Fuji II LC glass fillers to
form the experimental cement restoratives. The reaction kinetics was
studied via 1HNMR spectroscopy. The formed restoratives were
evaluated using compressive strength, diametral tensile strength,
flexural strength, hardness and wear-resistance tests. Specimens were
conditioned in distilled water at 37oC for 24 h prior to testing. Fuji II
LC restorative was used as control. The results show that the higher
the arm number and initiator concentration, the faster the reaction
was. It was also found that the higher the arm number and branching
that the polymer had, the lower the viscosity of the polymer in water
and the lower the mechanical strengths of the formed restorative. The
experimental restoratives were 31-53% in compressive strength, 37-
55% in compressive modulus, 80-126% in diametral tensile strength,
76-94% in flexural strength, 4-21% in fracture toughness and 53-96%
in hardness higher than Fuji II LC. For wear test, the experimental
restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional
wear depths of Fuji II LC in each wear cycle. The aging study also
showed that all the experimental restoratives increased their strength
continuously during 30 days, unlike Fuji II LC. It is concluded that
polymer molecular structures have significant and positive impact on
mechanical properties of dental cement restoratives.
Abstract: In this paper, a novel fuzzy approach is developed
while solving the Dynamic Routing and Wavelength Assignment
(DRWA) problem in optical networks with Wavelength Division
Multiplexing (WDM). In this work, the effect of nonlinear and linear
impairments such as Four Wave Mixing (FWM) and amplifier
spontaneous emission (ASE) noise are incorporated respectively. The
novel algorithm incorporates fuzzy logic controller (FLC) to reduce
the effect of FWM noise and ASE noise on a requested lightpath
referred in this work as FWM aware fuzzy dynamic routing and
wavelength assignment algorithm. The FWM crosstalk products and
the static FWM noise power per link are pre computed in order to
reduce the set up time of a requested lightpath, and stored in an
offline database. These are retrieved during the setting up of a
lightpath and evaluated online taking the dynamic parameters like
cost of the links into consideration.
Abstract: Cancer is still one of the serious diseases threatening
the lives of human beings. How to have an early diagnosis and
effective treatment for tumors is a very important issue. The animal
carcinoma model can provide a simulation tool for the studies of
pathogenesis, biological characteristics, and therapeutic effects.
Recently, drug delivery systems have been rapidly developed to
effectively improve the therapeutic effects. Liposome plays an
increasingly important role in clinical diagnosis and therapy for
delivering a pharmaceutic or contrast agent to the targeted sites.
Liposome can be absorbed and excreted by the human body, and is
well known that no harm to the human body. This study aimed to
compare the therapeutic effects between encapsulated (doxorubicin
liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox)
anti-tumor drugs using magnetic resonance imaging (MRI).
Twenty-four New Zealand rabbits implanted with VX2 carcinoma at
left thighs were classified into three groups: control group (untreated),
Dox-treated group, and LipoDox-treated group, 8 rabbits for each
group. MRI scans were performed three days after tumor implantation.
A 1.5T GE Signa HDxt whole body MRI scanner with a high
resolution knee coil was used in this study. After a 3-plane localizer
scan was performed, three-dimensional (3D) fast spin echo (FSE)
T2-weighted Images (T2WI) was used for tumor volumetric
quantification. Afterwards, two-dimensional (2D) spoiled gradient
recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was
used for tumor perfusion evaluation. DCE-MRI was designed to
acquire four baseline images, followed by contrast agent Gd-DOTA
injection through the ear vein of rabbit. A series of 32 images were
acquired to observe the signals change over time in the tumor and
muscle. The MRI scanning was scheduled on a weekly basis for a
period of four weeks to observe the tumor progression longitudinally.
The Dox and LipoDox treatments were prescribed 3 times in the first
week immediately after the first MRI scan; i.e. 3 days after VX2 tumor
implantation. ImageJ was used to quantitate tumor volume and time
course signal enhancement on DCE images. The changes of tumor size
showed that the growth of VX2 tumors was effectively inhibited for
both LipoDox-treated and Dox-treated groups. Furthermore, the tumor
volume of LipoDox-treated group was significantly lower than that of
Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is
significantly lower than that of the other two groups, which implies
that targeted therapeutic drug remained in the tumor tissue. This study
provides a radiation-free and non-invasive MRI method for
therapeutic monitoring of targeted liposome on an animal tumor
model.
Abstract: Underwater acoustic networks have attracted great
attention in the last few years because of its numerous applications.
High data rate can be achieved by efficiently modeling the physical
layer in the network protocol stack. In Acoustic medium,
propagation speed of the acoustic waves is dependent on many
parameters such as temperature, salinity, density, and depth.
Acoustic propagation speed cannot be modeled using standard
empirical formulas such as Urick and Thorp descriptions. In this
paper, we have modeled the acoustic channel using real time data of
temperature, salinity, and speed of Bay of Bengal (Indian Coastal
Region). We have modeled the acoustic channel by using Mackenzie
speed equation and real time data obtained from National Institute of
Oceanography and Technology. It is found that acoustic propagation
speed varies between 1503 m/s to 1544 m/s as temperature and
depth differs. The simulation results show that temperature, salinity,
depth plays major role in acoustic propagation and data rate
increases with appropriate data sets substituted in the simulated
model.
Abstract: Hydraulic fracturing is one of the most important
stimulation techniques available to the petroleum engineer to extract
hydrocarbons in tight gas sandstones. It allows more oil and gas
production in tight reservoirs as compared to conventional means.
The main aim of the study is to optimize the hydraulic fracturing as
technique and for this purpose three multi-zones layer formation is
considered and fractured contemporaneously. The three zones are
named as Zone1 (upper zone), Zone2 (middle zone) and Zone3
(lower zone) respectively and they all occur in shale rock. Simulation was performed with Mfrac integrated software which
gives a variety of 3D fracture options. This simulation process
yielded an average fracture efficiency of 93.8%for the three
respective zones and an increase of the average permeability of the
rock system. An average fracture length of 909 ft with net height
(propped height) of 210 ft (average) was achieved. Optimum
fracturing results was also achieved with maximum fracture width of
0.379 inches at an injection rate of 13.01 bpm with 17995 Mscf of
gas production.
Abstract: In this paper, we describe an application for face
recognition. Many studies have used local descriptors to characterize
a face, the performance of these local descriptors remain low by
global descriptors (working on the entire image). The application of
local descriptors (cutting image into blocks) must be able to store
both the advantages of global and local methods in the Discrete
Cosine Transform (DCT) domain. This system uses neural network
techniques. The letter method provides a good compromise between
the two approaches in terms of simplifying of calculation and
classifying performance. Finally, we compare our results with those
obtained from other local and global conventional approaches.
Abstract: The relationship dependence between RSS and distance
in an enclosed environment is an important consideration because it is
a factor that can influence the reliability of any localization algorithm
founded on RSS. Several algorithms effectively reduce the variance of
RSS to improve localization or accuracy performance. Our proposed
algorithm essentially avoids this pitfall and consequently, its high
adaptability in the face of erratic radio signal. Using 3 anchors in
close proximity of each other, we are able to establish that RSS can be
used as reliable indicator for localization with an acceptable degree of
accuracy. Inherent in this concept, is the ability for each prospective
anchor to validate (guarantee) the position or the proximity of the
other 2 anchors involved in the localization and vice versa. This
procedure ensures that the uncertainties of radio signals due to
multipath effects in enclosed environments are minimized. A major
driver of this idea is the implicit topological relationship among
sensors due to raw radio signal strength. The algorithm is an area
based algorithm; however, it does not trade accuracy for precision
(i.e the size of the returned area).
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.