Abstract: This review emphasizes the effectiveness of men’s
participation in preventing domestic violence, and whether nonviolent
(NV) boys’ and men’s perceptions of intimate partner
violence (IPV) prevention programs affect their involvement. The
main goals of this assessment were to investigate (1) how NV men
engaged in anti-violence prevention programs that empower women,
(2) what were the possible perceptions of NV men involved in
prevention programs (3) how to identify effective approaches and
strategies that encouraged NV men to become involved in prevention
programs. This critical review also included the overview of
prevention programs such as: The Mentors in Violence Prevention
Programs (MVP), The White Ribbon Campaign (WRC), and
Domestic Violence Prevention Enhancement and Leadership through
Alliances (DELTA). The review suggested that (1) the expanding
prevention programs need to reach more macro settings such as work
place, faith-based and other community based organizations, and (2)
territory prevention programs should expand through addressing the
long-term effects of violence.
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: Physical properties of uranium dinitride (UN2) were
investigated in detail using first principle calculations based on
density functional theory (DFT). To study the strong correlation
effects due to 5f uranium valence electrons, the on-site coulomb
interaction correction U via the Hubbard-like term (DFT+U) was
employed. The UN2 structural, mechanical and thermodynamic
properties were calculated within DFT and Various U of DFT+U
approach.
The Perdew–Burke–Ernzerhof (PBE.5.2) version of the
generalized gradient approximation (GGA) is used to describe the
exchange-correlation with the projector-augmented wave (PAW)
pseudo potentials.
A comparative study shows that results are improved by using the
Hubbard formalism for a certain U value correction like the structural
parameter. For some physical properties the variation versus
Hubbard-U is strong like Young modulus but for others it is weakly
noticeable such as bulk modulus.
We noticed also that from U=7.5 eV, elastic results don’t agree
with the cubic cell because of the C44 values which turn out to be
negative.
Abstract: In this research the effects of adding silica and
alumina nanoparticles on flow ability and compressive strength of
cementitious composites based on Portland cement were investigated.
In the first stage, the rheological behavior of different samples
containing nanosilica, nanoalumina and polypropylene, polyvinyl
alcohol and polyethylene fibers were evaluated. With increasing of
nanoparticles in fresh samples, the slump flow diameter reduced.
Fibers reduced the flow ability of the samples and viscosity
increased. With increasing of the micro silica particles to cement
ratio from 2/1 to 2/2, the slump flow diameter increased. By adding
silica and alumina nanoparticles up to 3% and 2% respectively, the
compressive strength increased and after decreased. Samples
containing silica nanoparticles and fibers had the highest compressive
strength.
Abstract: Polysulfone (PSU) is a specialty engineering polymer
having various industrial applications. PSU is especially used in
waste water treatment membranes due to its good mechanical
properties, structural and chemical stability. But it is a hydrophobic
material and therefore its surface aim to pollute easily. In order to
resolve this problem and extend the properties of membrane, PSU
surface is rendered hydrophilic by addition of the sepiolite
nanofibers. Sepiolite is one of the natural clays, which is a hydrate
magnesium silicate fiber, also one of the well known layered clays of
the montmorillonites where has several unique channels and pores
within. It has also moisture durability, strength and low price.
Sepiolite channels give great capacity of absorption and good surface
properties. In this study, nanocomposites of commercial PSU and
Sepiolite were prepared by solvent mixing method. Different organic
solvents and their mixtures were used. Rheological characteristics of
PSU-Sepiolite solvent mixtures were analyzed, the solubility of
nanocomposite content in those mixtures were studied.
Abstract: Iris codes contain bits with different entropy. This
work investigates different strategies to reduce the size of iris
code templates with the aim of reducing storage requirements and
computational demand in the matching process. Besides simple subsampling
schemes, also a binary multi-resolution representation as
used in the JBIG hierarchical coding mode is assessed. We find that
iris code template size can be reduced significantly while maintaining
recognition accuracy. Besides, we propose a two-stage identification
approach, using small-sized iris code templates in a pre-selection
stage, and full resolution templates for final identification, which
shows promising recognition behaviour.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: In this paper we consider the rule reduct generation
problem. Rule Reduct Generation (RG) and Modified Rule
Generation (MRG) algorithms, that are used to solve this problem,
are well-known. Alternative to these algorithms, we develop Pruning
Rule Generation (PRG) algorithm. We compare the PRG algorithm
with RG and MRG.
Abstract: In this paper a real-time obstacle avoidance approach
for both autonomous and non-autonomous dynamical systems (DS) is
presented. In this approach the original dynamics of the controller
which allow us to determine safety margin can be modulated.
Different common types of DS increase the robot’s reactiveness in
the face of uncertainty in the localization of the obstacle especially
when robot moves very fast in changeable complex environments.
The method is validated by simulation and influence of different
autonomous and non-autonomous DS such as important
characteristics of limit cycles and unstable DS. Furthermore, the
position of different obstacles in complex environment is explained.
Finally, the verification of avoidance trajectories is described through
different parameters such as safety factor.
Abstract: In this paper, Bayesian online inference in models of
data series are constructed by change-points algorithm, which
separated the observed time series into independent series and study
the change and variation of the regime of the data with related
statistical characteristics. variation of statistical characteristics of time
series data often represent separated phenomena in the some
dynamical system, like a change in state of brain dynamical reflected
in EEG signal data measurement or a change in important regime of
data in many dynamical system. In this paper, prediction algorithm
for studying change point location in some time series data is
simulated. It is verified that pattern of proposed distribution of data
has important factor on simpler and smother fluctuation of hazard
rate parameter and also for better identification of change point
locations. Finally, the conditions of how the time series distribution
effect on factors in this approach are explained and validated with
different time series databases for some dynamical system.
Abstract: In this paper, we considered and applied parametric
modeling for some experimental data of dynamical system. In this
study, we investigated the different distribution of output
measurement from some dynamical systems. Also, with variance
processing in experimental data we obtained the region of
nonlinearity in experimental data and then identification of output
section is applied in different situation and data distribution. Finally,
the effect of the spanning the measurement such as variance to
identification and limitation of this approach is explained.
Abstract: In this paper, model order reduction method is used
for approximation in linear and nonlinearity aspects in some
experimental data. This method can be used for obtaining offline
reduced model for approximation of experimental data and can
produce and follow the data and order of system and also it can
match to experimental data in some frequency ratios. In this study,
the method is compared in different experimental data and influence
of choosing of order of the model reduction for obtaining the best and
sufficient matching condition for following the data is investigated in
format of imaginary and reality part of the frequency response curve
and finally the effect and important parameter of number of order
reduction in nonlinear experimental data is explained further.
Abstract: Performance of different filtering approaches depends
on modeling of dynamical system and algorithm structure. For
modeling and smoothing the data the evaluation of posterior
distribution in different filtering approach should be chosen carefully.
In this paper different filtering approaches like filter KALMAN,
EKF, UKF, EKS and smoother RTS is simulated in some trajectory
tracking of path and accuracy and limitation of these approaches are
explained. Then probability of model with different filters is
compered and finally the effect of the noise variance to estimation is
described with simulations results.
Abstract: Risperidone (RISP) is an antipsychotic agent and has
low water solubility and nontargeted delivery results in numerous
side effects. Hence, an attempt was made to develop SLNs hydrogel
for intranasal delivery of RISP to achieve maximum bioavailability
and reduction of side effects. RISP loaded SLNs composed of 1.65%
(w/v) lipid mass were produced by high shear homogenization (HSH)
coupled ultrasound (US) method using glycerylmonostearate (GMS)
or Imwitor 900K (solid lipid). The particles were loaded with 0.2%
(w/v) of the RISP & surface-tailored with a 2.02% (w/v) non-ionic
surfactant Tween® 80. Optimization was done using 32 factorial
design using Design Expert® software. The prepared SLNs
dispersion incorporated into Polycarbophil AA1 hydrogel (0.5%
w/v). The final gel formulation was evaluated for entrapment
efficiency, particle size, rheological properties, X ray diffraction, in
vitro diffusion, ex vivo permeation using sheep nasal mucosa and
histopathological studies for nasocilliary toxicity. The entrapment
efficiency of optimized SLNs was found to be 76 ± 2%,
polydispersity index
Abstract: A Distributed Denial of Service (DDoS) attack is a
major threat to cyber security. It originates from the network layer or
the application layer of compromised/attacker systems which are
connected to the network. The impact of this attack ranges from the
simple inconvenience to use a particular service to causing major
failures at the targeted server. When there is heavy traffic flow to a
target server, it is necessary to classify the legitimate access and
attacks. In this paper, a novel method is proposed to detect DDoS
attacks from the traces of traffic flow. An access matrix is created
from the traces. As the access matrix is multi dimensional, Principle
Component Analysis (PCA) is used to reduce the attributes used for
detection. Two classifiers Naive Bayes and K-Nearest neighborhood
are used to classify the traffic as normal or abnormal. The
performance of the classifier with PCA selected attributes and actual
attributes of access matrix is compared by the detection rate and
False Positive Rate (FPR).
Abstract: Starting in 2020, an EU-wide CO2-limitation of
95 g/km is scheduled for the average of an OEMs passenger car fleet.
Taking that into consideration additional improvement measures of
the Diesel cycle are necessary in order to reduce fuel consumption
and emissions while boosting, or at the least, keeping performance
values at the same time.
The present article deals with the possibilities of an optimized
air/water charge air cooler, also called iCAC (indirect Charge Air
Cooler) for a Diesel passenger car amongst extreme-boundary
conditions. In this context, the precise objective was to show the
impact of improved intercooling with reference to the engine working
process (fuel consumption and NOx-emissions). Several extremeboundaries
- e.g. varying ambient temperatures or mountainous
routes - that will become very important in the near future regarding
RDE (Real Driving emissions) were subject of the investigation.
With the introduction of RDE in 2017 (EU6c measure), the
controversial NEDC (New European Driving Cycle) will belong to
the past and the OEMs will have to avoid harmful emissions in any
conceivable real life situation.
This is certainly going to lead to optimization-measurements at the
powertrain, which again is going to make the implementation of
iCACs, presently solely used for the premium class, more and more
attractive for compact class cars. The investigations showed a benefit
in FC between 1 and 3% for the iCAC in real world conditions.
Abstract: Factors affecting construction unit cost vary
depending on a country’s political, economic, social and
technological inclinations. Factors affecting construction costs have
been studied from various perspectives. Analysis of cost factors
requires an appreciation of a country’s practices. Identified cost
factors provide an indication of a country’s construction economic
strata. The purpose of this paper is to identify the essential factors
that affect unit cost estimation and their breakdown using artificial
neural networks. Twenty five (25) identified cost factors in road
construction were subjected to a questionnaire survey and employing
SPSS factor analysis the factors were reduced to eight. The 8 factors
were analysed using neural network (NN) to determine the
proportionate breakdown of the cost factors in a given construction
unit rate. NN predicted that political environment accounted 44% of
the unit rate followed by contractor capacity at 22% and financial
delays, project feasibility and overhead & profit each at 11%. Project
location, material availability and corruption perception index had
minimal impact on the unit cost from the training data provided.
Quantified cost factors can be incorporated in unit cost estimation
models (UCEM) to produce more accurate estimates. This can create
improvements in the cost estimation of infrastructure projects and
establish a benchmark standard to assist the process of alignment of
work practises and training of new staff, permitting the on-going
development of best practises in cost estimation to become more
effective.
Abstract: In this research, waterglass based aerogel powder was
prepared by sol–gel process and ambient pressure drying. Inspired by
limited dust releasing, aerogel powder was introduced to the PET
electrospinning solution in an attempt to create required bulk and
surface structure for the nanofibers to improve their hydrophobic and
insulation properties. The samples evaluation was carried out by
measuring density, porosity, contact angle, heat transfer, FTIR, BET,
and SEM. According to the results, porous silica aerogel powder was
fabricated with mean pore diameter of 24 nm and contact angle of
145.9º. The results indicated the usefulness of the aerogel powder
confined into nanofibers to control surface roughness for
manipulating superhydrophobic nanowebs with water contact angle
of 147º. It can be due to a multi-scale surface roughness which was
created by nanowebs structure itself and nanofibers surface
irregularity in presence of the aerogels while a layer of fluorocarbon
created low surface energy. The wettability of a solid substrate is an
important property that is controlled by both the chemical
composition and geometry of the surface. Also, a decreasing trend in
the heat transfer was observed from 22% for the nanofibers without
any aerogel powder to 8% for the nanofibers with 4% aerogel
powder. The development of thermal insulating materials has become
increasingly more important than ever in view of the fossil energy
depletion and global warming that call for more demanding energysaving
practices.
Abstract: This work presents a new planar multiband antenna
based on fractal geometry. This structure is optimized and validated
into simulation by using CST-MW Studio. To feed this antenna we
have used a CPW line which makes it easy to be incorporated with
integrated circuits. The simulation results presents a good matching
input impedance and radiation pattern in the GSM band at 900 MHz
and ISM band at 2.4 GHz. The final structure is a dual band fractal
antenna with 70 x 70 mm² as a total area by using an FR4 substrate.
Abstract: This paper presents a novel design of a microstrip
fractal antenna based on the use of Sierpinski triangle shape, it’s
designed and simulated by using FR4 substrate in the operating
frequency bands (GPS, WiMAX), the design is a fractal antenna with
a modified ground structure. The proposed antenna is simulated and
validated by using CST Microwave Studio Software, the simulated
results presents good performances in term of radiation pattern and
matching input impedance.