Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: The legends about “user-friendly” and “easy-to-use”
birotical tools (computer-related office tools) have been spreading
and misleading end-users. This approach has led us to the extremely
high number of incorrect documents, causing serious financial losses
in the creating, modifying, and retrieving processes. Our research
proved that there are at least two sources of this underachievement:
(1) The lack of the definition of the correctly edited, formatted
documents. Consequently, end-users do not know whether their
methods and results are correct or not. They are not aware of their
ignorance. They are so ignorant that their ignorance does not allow
them to realize their lack of knowledge. (2) The end-users’ problem
solving methods. We have found that in non-traditional programming
environments end-users apply, almost exclusively, surface approach
metacognitive methods to carry out their computer related activities,
which are proved less effective than deep approach methods.
Based on these findings we have developed deep approach
methods which are based on and adapted from traditional
programming languages. In this study, we focus on the most popular
type of birotical documents, the text based documents. We have
provided the definition of the correctly edited text, and based on this
definition, adapted the debugging method known in programming.
According to the method, before the realization of text editing, a
thorough debugging of already existing texts and the categorization
of errors are carried out. With this method in advance to real text
editing users learn the requirements of text based documents and also
of the correctly formatted text.
The method has been proved much more effective than the
previously applied surface approach methods. The advantages of the
method are that the real text handling requires much less human and
computer sources than clicking aimlessly in the GUI (Graphical User
Interface), and the data retrieval is much more effective than from
error-prone documents.
Abstract: Diffusion stills have been effective in water
desalination. The present work represents a model of the distillation
process by using vertical single-effect diffusion stills. A semianalytical
model has been developed to model the process. A
software computer code using Engineering Equation Solver EES
software has been developed to solve the equations of the developed
model. An experimental setup has been constructed, and used for the
validation of the model. The model is also validated against former
literature results. The results obtained from the present experimental
test rig, and the data from the literature, have been compared with the
results of the code to find its best range of validity. In addition, a
parametric analysis of the system has been developed using the
model to determine the effect of operating conditions on the system's
performance. The dominant parameters that affect the productivity of
the still are the hot plate temperature that ranges from (55- 90°C) and
feed flow rate in range of (0.00694-0.0211 kg/m2-s).
Abstract: Geometric and mechanical properties all influence the
resistance of RC structures and may, in certain combination of
property values, increase the risk of a brittle failure of the whole
system.
This paper presents a statistical and probabilistic investigation on
the resistance of RC beams designed according to Eurocodes 2 and 8,
and subjected to multiple failure modes, under both the natural
variation of material properties and the uncertainty associated with
cross-section and transverse reinforcement geometry. A full
probabilistic model based on JCSS Probabilistic Model Code is
derived. Different beams are studied through material nonlinear
analysis via Monte Carlo simulations. The resistance model is
consistent with Eurocode 2. Both a multivariate statistical evaluation
and the data clustering analysis of outcomes are then performed.
Results show that the ultimate load behaviour of RC beams
subjected to flexural and shear failure modes seems to be mainly
influenced by the combination of the mechanical properties of both
longitudinal reinforcement and stirrups, and the tensile strength of
concrete, of which the latter appears to affect the overall response of
the system in a nonlinear way. The model uncertainty of the
resistance model used in the analysis plays undoubtedly an important
role in interpreting results.
Abstract: Analyzing DNA microarray data sets is a great
challenge, which faces the bioinformaticians due to the complication
of using statistical and machine learning techniques. The challenge
will be doubled if the microarray data sets contain missing data,
which happens regularly because these techniques cannot deal with
missing data. One of the most important data analysis process on
the microarray data set is feature selection. This process finds the
most important genes that affect certain disease. In this paper, we
introduce a technique for imputing the missing data in microarray
data sets while performing feature selection.
Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.
Abstract: A compact UWB planar antenna fed with a
microstrip-line is proposed. The new design consist of a rectangular
patch with symmetric l-shaped slots and fed by 50 Ω microstrip
transmission line and a reduced ground-plane which have a periodic
slots with an overall size of 47 mm x 20 mm. It is intended to be used
in wireless applications that cover the ultra-wideband (UWB)
frequency band. A wider impedance bandwidth of around 116.5%
(1.875 – 7.115 GHz) with stable radiation pattern is achieved. The
proposed antenna has excellent characteristics, low profile and costeffective
compared to existing UWB antennas. The UWB antenna is
designed and analyzed using CST Microwave Studio in transient
mode to verify antenna parameters improvements.
Abstract: Logistics processes of perishable food in the supply
chain include the distribution activities and the real time temperature
monitoring to fulfil the cold chain requirements. The paper presents
the use of RFID (Radio Frequency Identification) technology as an
identification tool of receiving and shipping activities in the cold
store. At the same time, the use of RFID data loggers with
temperature sensors is presented to observe and store the
temperatures for the purpose of analyzing the processes and having
the history data available for traceability purposes and efficient recall
management.
Abstract: Modelling of the earth's surface and evaluation of
urban environment, with 3D models, is an important research topic.
New stereo capabilities of high resolution optical satellites images,
such as the tri-stereo mode of Pleiades, combined with new image
matching algorithms, are now available and can be applied in urban
area analysis. In addition, photogrammetry software packages gained
new, more efficient matching algorithms, such as SGM, as well as
improved filters to deal with shadow areas, can achieve more dense
and more precise results.
This paper describes a comparison between 3D data extracted
from tri-stereo and dual stereo satellite images, combined with pixel
based matching and Wallis filter. The aim was to improve the
accuracy of 3D models especially in urban areas, in order to assess if
satellite images are appropriate for a rapid evaluation of urban
environments.
The results showed that 3D models achieved by Pleiades tri-stereo
outperformed, both in terms of accuracy and detail, the result
obtained from a Geo-eye pair. The assessment was made with
reference digital surface models derived from high resolution aerial
photography. This could mean that tri-stereo images can be
successfully used for the proposed urban change analyses.
Abstract: This study was conducted in the area of Vlora Bay,
Albania. Data about Sea Turtles Caretta caretta and Chelonia mydas,
belonging to two periods of time (1984 – 1991; 2008 – 2014) are
given. All data gathered were analyzed using recent methodologies.
For all turtles captured (as by catch), the Curve Carapace Length
(CCL) and Curved Carapace Width (CCW) were measured. These
data were statistically analyzed, where the mean was 67.11 cm for
CCL and 57.57 cm for CCW of all individuals studied (n=13). All
untagged individuals of marine turtles were tagged using metallic
tags (Stockbrand’s titanium tag) with an Albanian address. Sex was
determined and resulted that 45.4% of individuals were females,
27.3% males and 27.3% juveniles. All turtles were studied for the
presence of the epibionts. The area of Vlora Bay is used from marine
turtles (Caretta caretta) as a migratory corridor to pass from
Mediterranean to the northern part of the Adriatic Sea.
Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.
Abstract: The study of the electrical signals produced by neural
activities of human brain is called Electroencephalography. In this
paper, we propose an automatic and efficient EEG signal
classification approach. The proposed approach is used to classify the
EEG signal into two classes: epileptic seizure or not. In the proposed
approach, we start with extracting the features by applying Discrete
Wavelet Transform (DWT) in order to decompose the EEG signals
into sub-bands. These features, extracted from details and
approximation coefficients of DWT sub-bands, are used as input to
Principal Component Analysis (PCA). The classification is based on
reducing the feature dimension using PCA and deriving the supportvectors
using Support Vector Machine (SVM). The experimental are
performed on real and standard dataset. A very high level of
classification accuracy is obtained in the result of classification.
Abstract: The well been of human beings on construction site is
very important, many man power had been lost through accidents
which kills or make workers physically unfit to carry out construction
activities, these in turn have multiple effects on the whole economy.
Thus it is necessary to put all safety items and regulations in place
before construction activities can commence. This study was carried
out in Ondo state of Nigeria to known and analyse the state of health
and safety of construction workers in the state. The study was done
using first hand observation method, 50 construction project sites
were visited in 10 major towns of Ondo state, questionnaires were
distributed and the results were analysed. The result show that
construction workers are being exposed to a lot of construction site
hazards due to lack of inadequate safety programmes and nonprovision
of appropriate safety materials for workers on site. From the
data gotten for each site visited and the statistical analysis, it can be
concluded that occurrence of accident on construction sites depends
significantly on the available safety facilities on the sites. The result of
the regression statistics show that the level of significant of the
dependence of occurrence of accident on the availability of safety
items on site is 0.0362 which is less than 0.05 maximum significant
level required. Therefore a vital way of sustaining our building
strategy is by given a detail attention to provision of adequate health
and safety items on construction sites which will reduce the
occurrence of accident, loss of man power and death of skilled
workers among others.
Abstract: The 6th version of Universal modeling method for
centrifugal compressor stage calculation is described. Identification
of the new mathematical model was made. As a result of
identification the uniform set of empirical coefficients is received.
The efficiency definition error is 0,86 % at a design point. The
efficiency definition error at five flow rate points (except a point of
the maximum flow rate) is 1,22 %. Several variants of the stage with
3D impellers designed by 6th version program and quasi threedimensional
calculation programs were compared by their gas
dynamic performances CFD (NUMECA FINE TURBO).
Performance comparison demonstrated general principles of design
validity and leads to some design recommendations.
Abstract: Ocimum americanum L (Lamiaceae) is an annual herb
that is native to tropical Africa. The in vitro and in vivo antioxidant
activity of its aqueous extract was carefully investigated by assessing
the DPPH radical scavenging activity, ABTS radical scavenging
activity and hydrogen peroxide radical scavenging activity. The
reducing power, total phenol, total flavonoids and flavonols content
of the extract were also evaluated. The data obtained revealed that the
extract is rich in polyphenolic compounds and scavenged the radicals
in a concentration dependent manner. This was done in comparison
with the standard antioxidants such as BHT and Vitamin C. Also, the
induction of oxidative damage with paracetamol (2000 mg/kg)
resulted in the elevation of lipid peroxides and significant (P < 0.05)
decrease in activities of superoxide dismutase, glutathione
peroxidase, glutathione reductase and catalase in the liver and kidney
of rats. However, the pretreatment of rats with aqueous extract of O.
americanum leaves (200 and 400 mg/kg) and silymarin (100 mg/kg)
caused a significant (P < 0.05) reduction in the values of lipid
peroxides and restored the levels of antioxidant parameters in these
organs. These findings suggest that the leaves of O. americanum have
potent antioxidant properties which may be responsible for its
acclaimed folkloric uses.
Abstract: The present study was undertaken to investigate the
effect of aging parameters (time and temperature) on the mechanical
properties of Be-and/or Zr- treated Al-Mg-Zn (7075) alloys. Ultimate
tensile strength, 0.5% offset yield strength and % elongation
measurements were carried out on specimens prepared from cast and
heat treated 7075 alloys containing Be and/or Zr. Different aging
treatment were carried out for the as solution treated (SHT)
specimens (after quenching in warm water). The specimens were
aged at different conditions; Natural and artificial aging was carried
out at room temperature, 120C, 150C, 180C and 220C for different
periods of time. Duplex aging was performed for SHT conditions
(pre-aged at different time and temperature followed by high
temperature aging). Ultimate tensile strength, yield strength and %
elongation data results as a function of different aging parameters are
analysed. A statistical design of experiments (DOE) approach using
fractional factorial design is applied to acquire an understanding of
the effects of these variables and their interactions on the mechanical
properties of Be- and/or Zr- treated 7075 alloys. Mathematical
models are developed to relate the alloy mechanical properties with
the different aging parameters.
Abstract: Speech enhancement is a long standing problem with
numerous applications like teleconferencing, VoIP, hearing aids and
speech recognition. The motivation behind this research work is to
obtain a clean speech signal of higher quality by applying the optimal
noise cancellation technique. Real-time adaptive filtering algorithms
seem to be the best candidate among all categories of the speech
enhancement methods. In this paper, we propose a speech
enhancement method based on Recursive Least Squares (RLS)
adaptive filter of speech signals. Experiments were performed on
noisy data which was prepared by adding AWGN, Babble and Pink
noise to clean speech samples at -5dB, 0dB, 5dB and 10dB SNR
levels. We then compare the noise cancellation performance of
proposed RLS algorithm with existing NLMS algorithm in terms of
Mean Squared Error (MSE), Signal to Noise ratio (SNR) and SNR
Loss. Based on the performance evaluation, the proposed RLS
algorithm was found to be a better optimal noise cancellation
technique for speech signals.
Abstract: The Standard Penetration Test (SPT) is the most
common in situ test for soil investigations. On the other hand, the
Cone Penetration Test (CPT) is considered one of the best
investigation tools. Due to the fast and accurate results that can be
obtained it complaints the SPT in many applications like field
explorations, design parameters, and quality control assessments.
Many soil index and engineering properties have been correlated to
both of SPT and CPT. Various foundation design methods were
developed based on the outcome of these tests. Therefore it is vital to
correlate these tests to each other so that either one of the tests can be
used in the absence of the other, especially for preliminary evaluation
and design purposes.
The primary purpose of this study was to investigate the
relationships between the SPT and CPT for different type of sandy
soils in Florida. Data for this research were collected from number of
projects sponsored by the Florida Department of Transportation
(FDOT), six sites served as the subject of SPT-CPT correlations. The
correlations were established between the cone resistance (qc), sleeve
friction (fs) and the uncorrected SPT blow counts (N) for various
soils.
A positive linear relationship was found between qc, fs and N for
various sandy soils. In general, qc versus N showed higher
correlation coefficients than fs versus N. qc/N ratios were developed
for different soil types and compared to literature values, the results
of this research revealed higher ratios than literature values.
Abstract: The western Tombolo of the Giens peninsula in
southern France, known as Almanarre beach, is subject to coastal
erosion. We are trying to use computer simulation in order to propose
solutions to stop this erosion. Our aim was first to determine the main
factors for this erosion and successfully apply a coupled hydrosedimentological
numerical model based on observations and
measurements that have been performed on the site for decades.
We have gathered all available information and data about waves,
winds, currents, tides, bathymetry, coastal line, and sediments
concerning the site. These have been divided into two sets: one
devoted to calibrating a numerical model using Mike 21 software, the
other to serve as a reference in order to numerically compare the
present situation to what it could be if we implemented different
types of underwater constructions.
This paper presents the first part of the study: selecting and
melting different sources into a coherent data basis, identifying the
main erosion factors, and calibrating the coupled software model
against the selected reference period.
Our results bring calibration of the numerical model with good
fitting coefficients. They also show that the winter South-Western
storm events conjugated to depressive weather conditions constitute a
major factor of erosion, mainly due to wave impact in the northern
part of the Almanarre beach. Together, current and wind impact is
shown negligible.
Abstract: The present paper summarizes the analysis of the
request for consultation of information and data on industrial
emissions made publicly available on the web site of the Ministry of
Environment, Land and Sea on integrated pollution prevention and
control from large industrial installations, the so called “AIA Portal”.
As a matter of fact, a huge amount of information on national
industrial plants is already available on internet, although it is usually
proposed as textual documentation or images.
Thus, it is not possible to access all the relevant information
through interoperability systems and also to retrieval relevant
information for decision making purposes as well as rising of
awareness on environmental issue.
Moreover, since in Italy the number of institutional and private
subjects involved in the management of the public information on
industrial emissions is substantial, the access to the information is
provided on internet web sites according to different criteria; thus, at
present it is not structurally homogeneous and comparable.
To overcome the mentioned difficulties in the case of the
Coordinating Committee for the implementation of the Agreement
for the industrial area in Taranto and Statte, operating before the
IPPC permit granting procedures of the relevant installation located
in the area, a big effort was devoted to elaborate and to validate data
and information on characterization of soil, ground water aquifer and
coastal sea at disposal of different subjects to derive a global
perspective for decision making purposes. Thus, the present paper
also focuses on main outcomes matured during such experience.