Abstract: The discarded clam shell waste, fossil and edible oil
as biolubricant feedstocks create environmental impacts and food
chain dilemma, thus this work aims to circumvent these issues by
using activated saltwater clam shell waste (SCSW) as solid catalyst
for conversion of Jatropha curcas oil as non-edible sources to ester
biolubricant. The characterization of solid catalyst was done by
Differential Thermal Analysis-Thermo Gravimetric Analysis (DTATGA),
X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD),
Brunauer-Emmett-Teller (BET), Field Emission Scanning Electron
Microscopy (FESEM) and Fourier Transformed Infrared
Spectroscopy (FTIR) analysis. The calcined catalyst was used in the
transesterification of Jatropha oil to methyl ester as the first step, and
the second stage was involved the reaction of Jatropha methyl ester
(JME) with trimethylolpropane (TMP) based on the various process
parameters. The formated biolubricant was analyzed using the
capillary column (DB-5HT) equipped Gas Chromatography (GC).
The conversion results of Jatropha oil to ester biolubricant can be
found nearly 96.66%, and the maximum distribution composition
mainly contains 72.3% of triester (TE).
Abstract: For a given a simple connected graph, we present
some new bounds via a new approach for a special topological index
given by the sum of the real number power of the non-zero
normalized Laplacian eigenvalues. To use this approach presents an
advantage not only to derive old and new bounds on this topic but
also gives an idea how some previous results in similar area can be
developed.
Abstract: This entry concerned with dense silica bricks
microstructure was produced as a part of a project within the
Technology Agency of the Czech Republic which is being
implemented in cooperation of the biggest producer of refractories
the P-D Refractories CZ company with the research organisation
Brno University of Technology. The paper is focused on the
influence of mixture homogenisation and the influence of grain size
of the mineraliser on the resulting utility properties of the material as
well as its microstructure. It has a decisive influence on the durability
of the material in a building structure. This paper is a continuation of
a previously published study dealing with the suitability of various
types of mineralising agents in terms of density, strength and mineral
composition of silica brick.
The entry describes the influence of the method of mixture
homogenisation and the influence of granulometry of the applied Femineralising
agent on the resulting silica microstructure. Porosity,
density, phase composition and microstructure of the experimentally
prepared silica bricks samples were examined and the results were
discussed in context with the technology of homogenisation and
firing temperature used. The properties of silica bricks samples were
compared to the sample without any Fe-mineraliser.
Abstract: Load carrying capacity of an oil lubricated two-axial
groove journal bearing is simulated by taking into account the
viscosity variations in lubricant due to the addition of TiO2
nanoparticles as lubricant additive. Shear viscosities of TiO2
nanoparticle dispersions in oil are measured for various nanoparticle
additive concentrations. The viscosity model derived from the
experimental viscosities is employed in a modified Reynolds
equation to obtain the pressure profiles and load carrying capacity of
two-axial groove journal bearing. Results reveal an increase in load
carrying capacity of bearings operating on nanoparticle dispersions as
compared to plain oil.
Abstract: Pollution of the Klip River has caused
microorganisms inhabiting it to develop protective survival
mechanisms. This study isolated and characterized the heavy metal
resistant bacteria in the Klip River. Water and sediment samples were
collected from six sites along the course of the river. The pH,
turbidity, salinity, temperature and dissolved oxygen were measured
in-situ. The concentrations of six heavy metals (Cd, Cu, Fe, Ni, Pb
and Zn) of the water samples were determined by atomic absorption
spectroscopy. Biochemical and antibiotic profiles of the isolates were
assessed using the API 20E® and Kirby Bauer Method. Growth
studies were carried out using spectrophotometric methods. The
isolates were identified using 16SrDNA sequencing. The uppermost
part of the Klip River with the lowest pH had the highest levels of
heavy metals. Turbidity, salinity and specific conductivity increased
measurably at Site 4 (Henley on Klip Weir). MIC tests showed that
16 isolates exhibited high iron and lead resistance. Antibiotic
susceptibility tests revealed that the isolates exhibited multitolerances
to drugs such as Tetracycline, Ampicillin, and
Amoxicillin.
Abstract: Nowadays, the amounts of companies which tend to
have an Enterprise Resource Planning (ERP) application are
increasing. Although ERP projects are expensive, time consuming,
and complex, there are some successful experiences. These days,
developing countries are striving to implement ERP projects
successfully; however, there are many obstacles. Therefore, these
projects would be failed or partially failed. This paper concerns the
implementation of a successful ERP implementation, IFS, in Iran at
Dana Geophysics Company (DGC). After a short review of ERP and
ERP market in Iran, we propose a three phases deployment
methodology (phase 1: Preparation and Business Process
Management (BPM) phase 2: implementation and phase 3: testing,
golive-1 (pilot) and golive-2 (final)). Then, we present five guidelines
(Project Management, Change Management, Business Process
Management (BPM), Training& Knowledge Management, and
Technical Management), which were chose as work streams. In this
case study we present lessons learned in Project management and
Business process Management.
Abstract: Kinematic data wisely correlate vector quantities in
space to scalar parameters in time to assess the degree of symmetry
between the intact limb and the amputated limb with respect to a
normal model derived from the gait of control group participants.
Furthermore, these particular data allow a doctor to preliminarily
evaluate the usefulness of a certain rehabilitation therapy.
Kinetic curves allow the analysis of ground reaction forces (GRFs)
to assess the appropriateness of human motion.
Electromyography (EMG) allows the analysis of the fundamental
lower limb force contributions to quantify the level of gait
asymmetry. However, the use of this technological tool is expensive
and requires patient’s hospitalization. This research work suggests
overcoming the above limitations by applying artificial neural
networks.
Abstract: Red River Gum (Eucalyptus camaldulensis) is a tree
of the genus Eucalyptus widely distributed in Algeria and in the
world. The value of its aromatic secondary metabolites offers new
perspectives in the pharmaceutical industry. This strategy can
contribute to the sustainable development of our country. Preliminary
tests performed on the essential oil of Eucalyptus camendulensis
showed that this oil has antibacterial activity vis-à-vis the bacterial
strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus
microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas
aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium
graminearum). The culture medium used was nutrient broth Muller
Hinton. The interaction between the bacteria and the essential oil is
expressed by a zone of inhibition with diameters of MIC indirectly
expression of. And we used the PDA medium to determine the fungal
activity. The extraction of the aromatic fraction (essentially oilhydrolat)
of the fresh aerian part of the Eucalyptus camendulensis
was performed by hydrodistillation. The average essential oil yield is
0.99%. The antimicrobial and fungal study of the essential oil and
hydrosol showed a high inhibitory effect on the growth of pathogens.
Abstract: Estimation of a proportion has many applications in
economics and social studies. A common application is the estimation
of the low income proportion, which gives the proportion of people
classified as poor into a population. In this paper, we present this
poverty indicator and propose to use the logistic regression estimator
for the problem of estimating the low income proportion. Various
sampling designs are presented. Assuming a real data set obtained
from the European Survey on Income and Living Conditions, Monte
Carlo simulation studies are carried out to analyze the empirical
performance of the logistic regression estimator under the various
sampling designs considered in this paper. Results derived from
Monte Carlo simulation studies indicate that the logistic regression
estimator can be more accurate than the customary estimator under
the various sampling designs considered in this paper. The stratified
sampling design can also provide more accurate results.
Abstract: The measured data obtained from sensors in
continuous monitoring of civil structures are mainly used for modal
identification and damage detection. Therefore, when modal
identification analysis is carried out the quality in the identification of
the modes will highly influence the damage detection results. It is
also widely recognized that the usefulness of the measured data used
for modal identification and damage detection is significantly
influenced by the number and locations of sensors. The objective of
this study is the numerical implementation of two widely known
optimum sensor placement methods in beam-like structures.
Abstract: This paper deals with the problem of passivity
analysis for stochastic neural networks with leakage, discrete and
distributed delays. By using delay partitioning technique, free
weighting matrix method and stochastic analysis technique, several
sufficient conditions for the passivity of the addressed neural
networks are established in terms of linear matrix inequalities
(LMIs), in which both the time-delay and its time derivative can be
fully considered. A numerical example is given to show the
usefulness and effectiveness of the obtained results.
Abstract: This research proposes a novel reconstruction protocol
for restoring missing surfaces and low-quality edges and shapes in
photos of artifacts at historical sites. The protocol starts with the
extraction of a cloud of points. This extraction process is based on
four subordinate algorithms, which differ in the robustness and
amount of resultant. Moreover, they use different -but
complementary- accuracy to some related features and to the way
they build a quality mesh. The performance of our proposed protocol
is compared with other state-of-the-art algorithms and toolkits. The
statistical analysis shows that our algorithm significantly outperforms
its rivals in the resultant quality of its object files used to reconstruct
the desired model.
Abstract: This paper presents a 3D guidance scheme for
Unmanned Aerial Vehicles (UAVs). The proposed guidance scheme
is based on the sliding mode approach using nonlinear sliding
manifolds. Generalized 3D kinematic equations are considered
here during the design process to cater for the coupling between
longitudinal and lateral motions. Sliding mode based guidance
scheme is then derived for the multiple-input multiple-output
(MIMO) system using the proposed nonlinear manifolds. Instead of
traditional sliding surfaces, nonlinear sliding surfaces are proposed
here for performance and stability in all flight conditions. In the
reaching phase control inputs, the bang-bang terms with signum
functions are accompanied with proportional terms in order to reduce
the chattering amplitudes. The Proposed 3D guidance scheme is
implemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV
and simulation results are presented here for different 3D trajectories
with and without disturbances.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: The generalized wave equation models various
problems in sciences and engineering. In this paper, a new three-time
level implicit approach based on cubic trigonometric B-spline for the
approximate solution of wave equation is developed. The usual finite
difference approach is used to discretize the time derivative while
cubic trigonometric B-spline is applied as an interpolating function in
the space dimension. Von Neumann stability analysis is used to
analyze the proposed method. Two problems are discussed to exhibit
the feasibility and capability of the method. The absolute errors and
maximum error are computed to assess the performance of the
proposed method. The results were found to be in good agreement
with known solutions and with existing schemes in literature.
Abstract: From an organizational perspective, leaders are a
variation of the same talent pool in that they all score a larger than
average value on the bell curve that maps leadership behaviors and
characteristics, namely competence, vision, communication,
confidence, cultural sensibility, stewardship, empowerment,
authenticity, reinforcement, and creativity. The question that remains
unanswered and essentially unresolved is how to explain the irony
that leaders are so much alike yet their organizations diverge so
noticeably in their ability to innovate. Leadership intersects with
innovation at the point where human interactions get exceedingly
complex and where certain paradoxical forces cohabit: conflict with
conciliation, sovereignty with interdependence, and imagination with
realism. Rather than accepting that leadership is without context, we
argue that leaders are specialists of their domain and that those
effective at leading for innovation are distinct within the broader pool
of leaders. Keeping in view the extensive literature on leadership and
innovation, we carried out a quantitative study with data collected
over a five-year period involving 240 participants from across five
dissimilar companies based in the United States. We found that while
innovation and leadership are, in general, strongly interrelated (r =
.89, p = 0.0), there are five qualities that set leaders apart on
innovation. These qualities include a large radius of trust, a restless
curiosity with a low need for acceptance, an honest sense of self and
other, a sense for knowledge and creativity as the yin and yang of
innovation, and an ability to use multiple senses in the engagement
with followers. When these particular behaviors and characteristics
are present in leaders, organizations out-innovate their rivals by a
margin of 29.3 per cent to gain an unassailable edge in a business
environment that is regularly disruptive. A strategic outcome of this
study is a psychometric scale named iLeadership, proposed with the
underlying evidence, limitations, and potential for leadership and
innovation in organizations.c
Abstract: The growth of wireless devices affects the availability
of limited frequencies or spectrum bands as it has been known that
spectrum bands are a natural resource that cannot be added.
Meanwhile, the licensed frequencies are idle most of the time.
Cognitive radio is one of the solutions to solve those problems.
Cognitive radio is a promising technology that allows the unlicensed
users known as secondary users (SUs) to access licensed bands
without making interference to licensed users or primary users (PUs).
As cloud computing has become popular in recent years, cognitive
radio networks (CRNs) can be integrated with cloud platform. One of
the important issues in CRNs is security. It becomes a problem since
CRNs use radio frequencies as a medium for transmitting and CRNs
share the same issues with wireless communication systems. Another
critical issue in CRNs is performance. Security has adverse effect to
performance and there are trade-offs between them. The goal of this
paper is to investigate the performance related to security trade-off in
CRNs with supporting cloud platforms. Furthermore, Queuing
Network Models with preemptive resume and preemptive repeat
identical priority are applied in this project to measure the impact of
security to performance in CRNs with or without cloud platform. The
generalized exponential (GE) type distribution is used to reflect the
bursty inter-arrival and service times at the servers. The results show
that the best performance is obtained when security is disabled and
cloud platform is enabled.
Abstract: The construction of a new airport or the extension of
an existing one requires massive investments and many times public
private partnerships were considered in order to make feasible such
projects. One characteristic of these projects is uncertainty with
respect to financial and environmental impacts on the medium to long
term. Another one is the multistage nature of these types of projects.
While many airport development projects have been a success, some
others have turned into a nightmare for their promoters.
This communication puts forward a new approach for airport
investment risk assessment. The approach takes explicitly into
account the degree of uncertainty in activity levels prediction and
proposes milestones for the different stages of the project for
minimizing risk. Uncertainty is represented through fuzzy dual theory
and risk management is performed using dynamic programming. An
illustration of the proposed approach is provided.
Abstract: Bureaucracy reform program drives Indonesian
government to change their management to enhance their
organizational performance. Information technology became one of
strategic plan that organization tried to improve. Knowledge
management system is one of information system that supporting
knowledge management implementation in government which
categorized as people perspective, because this system has high
dependency in human interaction and participation. Strategic plan for
developing knowledge management system can be determine using
some of information system strategic methods. This research
conducted to define type of strategic method of information system,
stage of activity each method, strength and weakness. Literature
review methods used to identify and classify strategic methods of
information system, differentiate method type, categorize common
activities, strength and weakness. Result of this research are
determine and compare six strategic information system methods,
Balanced Scorecard and Risk Analysis believe as common strategic
method that usually used and have the highest excellence strength.
Abstract: Disasters are quite experienced in our days. They are
caused by floods, landslides, and building fires that is the main
objective of this study. To cope with these unexpected events,
precautions must be taken to protect human lives. The emphasis on
disposal work focuses on the resolution of the evacuation problem in
case of no-notice disaster. The problem of evacuation is listed as a
dynamic network flow problem. Particularly, we model the
evacuation problem as an earliest arrival flow problem with load
dependent transit time. This problem is classified as NP-Hard. Our
challenge here is to propose a metaheuristic solution for solving the
evacuation problem. We define our objective as the maximization of
evacuees during earliest periods of a time horizon T. The objective
provides the evacuation of persons as soon as possible. We
performed an experimental study on emergency evacuation from the
tunisian children’s hospital. This work prompts us to look for
evacuation plans corresponding to several situations where the
network dynamically changes.