Abstract: Not with standing the importance of foreign highly
skilled professionals for host economies, there is a paucity of
research studies investigating the role of the corporate social context
during the integration process. This research aims to address this
paucity by exploring the role of social capital in the integration of
foreign health professionals. It does so by using a qualitative research
approach. In this pilot study the hospital sector forms this study-s
sample and interviews were conducted with HR managers, foreign
health professionals and external HR consultants. It was found that
most of the participating hospitals had not established specific HR
practices and had only partly linked the development of
organisational social capital with a successful integration process.
This research contributes, for example, to the HR literature on the
integration of self-initiated expatriates by analysing the role of HRM
in generating organisational social capital needed for a successful
integration process.
Abstract: Fecal coliform bacteria are widely used as indicators of
sewage contamination in surface water. However, there are some
disadvantages in these microbial techniques including time consuming
(18-48h) and inability in discriminating between human and animal
fecal material sources. Therefore, it is necessary to seek a more
specific indicator of human sanitary waste. In this study, the feasibility
was investigated to apply caffeine and human pharmaceutical
compounds to identify the human-source contamination. The
correlation between caffeine and fecal coliform was also explored.
Surface water samples were collected from upstream, middle-stream
and downstream points respectively, along Rochor Canal, as well as 8
locations of Marina Bay. Results indicate that caffeine is a suitable
chemical tracer in Singapore because of its easy detection (in the range
of 0.30-2.0 ng/mL), compared with other chemicals monitored.
Relative low concentrations of human pharmaceutical compounds (<
0.07 ng/mL) in Rochor Canal and Marina Bay water samples make
them hard to be detected and difficult to be chemical tracer. However,
their existence can help to validate sewage contamination. In addition,
it was discovered the high correlation exists between caffeine
concentration and fecal coliform density in the Rochor Canal water
samples, demonstrating that caffeine is highly related to the
human-source contamination.
Abstract: Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques with classifiers such as random
forests, neural networks and support vector machines. The data sets
are from MAGIC, a Cherenkov telescope experiment. The task is to
classify gamma signals from overwhelmingly hadron and muon
signals representing a rare class classification problem. We compare
the individual classifiers with their ensemble counterparts and
discuss the results. WEKA a wonderful tool for machine learning has
been used for making the experiments.
Abstract: In developing a text-to-speech system, it is well
known that the accuracy of information extracted from a text is
crucial to produce high quality synthesized speech. In this paper, a
new scheme for converting text into its equivalent phonetic spelling
is introduced and developed. This method is applicable to many
applications in text to speech converting systems and has many
advantages over other methods. The proposed method can also
complement the other methods with a purpose of improving their
performance. The proposed method is a probabilistic model and is
based on Smooth Ergodic Hidden Markov Model. This model can be
considered as an extension to HMM. The proposed method is applied
to Persian language and its accuracy in converting text to speech
phonetics is evaluated using simulations.
Abstract: The wide increase and diffusion on telecommunication
technologies have caused a huge spread of electromagnetic sources
in most European Countries. Since the public is continuously being
exposed to electromagnetic radiation the possible health effects have
become the focus of population concerns. As a result, electromagnetic
field monitoring stations which control field strength in commercial
frequency bands are being placed on the flat roof of many buildings.
However there is no guidance on where to place them. This paper
presents an analysis of frequency, polarization and angles of incidence
of a plane wave which impinges on a flat roof security wall and its
dependence on electromagnetic field strength meters placement.
Abstract: In this paper, in addition to introducing good urban planning and its effects on globalization, some new methodologies in urban management and another urban aspects has been presented. Some new concerns in increasing of urban population , metropolitans and its relations on big problems has been focused in this paper. It is very important matter that future urban planning with based on globalization will be with full of basically changes in its management and perspectives.
Abstract: The aim of the research is to understand whether the accuracy of customer detection of employee emotional labor strategy would influence the overall service satisfaction. From path analysis, it was found that employee-s positive emotions positively influenced service quality. Service quality in turn influenced Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy. Lastly, Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy positively influenced service satisfaction. Based on the analysis results, suggestions are proposed to provide reference for human resource management and use in relative fields.
Abstract: Dual phase steels (DPS)s have a microstructure
consisting of a hard second phase called Martensite in the soft Ferrite
matrix. In recent years, there has been interest in dual-phase steels,
because the application of these materials has made significant usage;
particularly in the automotive sector Composite microstructure of
(DPS)s exhibit interesting characteristic mechanical properties such
as continuous yielding, low yield stress to tensile strength
ratios(YS/UTS), and relatively high formability; which offer
advantages compared with conventional high strength low alloy
steels(HSLAS). The research dealt with the characterization of
damage in (DPS)s. In this study by review the mechanisms of failure
due to volume fraction of martensite second phase; a new method is
introduced to identifying the mechanisms of failure in the various
phases of these types of steels. In this method the acoustic emission
(AE) technique was used to detect damage progression. These failure
mechanisms consist of Ferrite-Martensite interface decohesion and/or
martensite phase fracture. For this aim, dual phase steels with
different volume fraction of martensite second phase has provided by
various heat treatment methods on a low carbon steel (0.1% C), and
then AE monitoring is used during tensile test of these DPSs. From
AE measurements and an energy ratio curve elaborated from the
value of AE energy (it was obtained as the ratio between the strain
energy to the acoustic energy), that allows detecting important
events, corresponding to the sudden drops. These AE signals events
associated with various failure mechanisms are classified for ferrite
and (DPS)s with various amount of Vm and different martensite
morphology. It is found that AE energy increase with increasing Vm.
This increasing of AE energy is because of more contribution of
martensite fracture in the failure of samples with higher Vm. Final
results show a good relationship between the AE signals and the
mechanisms of failure.
Abstract: The hot deformation behavior of high strength low
alloy (HSLA) steels with different chemical compositions under hot
working conditions in the temperature range of 900 to 1100℃ and
strain rate range from 0.1 to 10 s-1 has been studied by performing a
series of hot compression tests. The dynamic materials model has been
employed for developing the processing maps, which show variation
of the efficiency of power dissipation with temperature and strain rate.
Also the Kumar-s model has been used for developing the instability
map, which shows variation of the instability for plastic deformation
with temperature and strain rate. The efficiency of power dissipation
increased with decreasing strain rate and increasing temperature in the
steel with higher Cr and Ti content. High efficiency of power
dissipation over 20 % was obtained at a finite strain level of 0.1 under
the conditions of strain rate lower than 1 s-1 and temperature higher
than 1050 ℃ . Plastic instability was expected in the regime of
temperatures lower than 1000 ℃ and strain rate lower than 0.3 s-1. Steel
with lower Cr and Ti contents showed high efficiency of power
dissipation at higher strain rate and lower temperature conditions.
Abstract: Injection forging is a Nett-shape manufacturing
process in which one or two punches move axially causing a radial
flow into a die cavity in a form which is prescribed by the exitgeometry,
such as pulley, flanges, gears and splines on a shaft. This
paper presents an experimental and numerical study of the injection
forging of splines in terms of load requirement and material flow.
Three dimensional finite element analyses are used to investigate the
effect of some important parameters in this process. The experiment
has been carried out using solid commercial lead billets with two
different billet diameters and four different dies.
Abstract: Fair share is one of the scheduling objectives supported on many production systems. However, fair share has been shown to cause performance problems for some users, especially the users with difficult jobs. This work is focusing on extending goaloriented parallel computer job scheduling policies to cover the fair share objective. Goal-oriented parallel computer job scheduling policies have been shown to achieve good scheduling performances when conflicting objectives are required. Goal-oriented policies achieve such good performance by using anytime combinatorial search techniques to find a good compromised schedule within a time limit. The experimental results show that the proposed goal-oriented parallel computer job scheduling policy (namely Tradeofffs( Tw:avgX)) achieves good scheduling performances and also provides good fair share performance.
Abstract: Road signs are the elements of roads with a lot of
influence in driver-s behavior. So that signals can fulfill its function,
they must overcome visibility and durability requirements,
particularly needed at night, when the coefficient of retroreflection
becomes a decisive factor in ensuring road safety. Accepting that the
visibility of the signage has implications for people-s safety, we
understand the importance to fulfill its function: to foster the highest
standards of service and safety in drivers. The usual conditions of
perception of any sign are determined by: age of the driver, reflective
material, luminosity, vehicle speed and emplacement. In this way,
this paper evaluates the different signals to increase the safety road.
Abstract: The main objective of this project is to build an
autonomous microcontroller-based mobile robot for a local robot
soccer competition. The black competition field is equipped with
white lines to serve as the guidance path for competing robots. Two
prototypes of soccer robot embedded with the Basic Stamp II
microcontroller have been developed. Two servo motors are used as
the drive train for the first prototype whereas the second prototype
uses two DC motors as its drive train. To sense the lines, lightdependent
resistors (LDRs) supply the analog inputs for the
microcontroller. The performances of both prototypes are evaluated.
The DC motor-driven robot has produced better trajectory control
over the one using servo motors and has brought the team into the
final round.
Abstract: One of the most important requirements for the
operation and planning activities of an electrical utility is the
prediction of load for the next hour to several days out, known as
short term load forecasting. This paper presents the development of
an artificial neural network based short-term load forecasting model.
The model can forecast daily load profiles with a load time of one
day for next 24 hours. In this method can divide days of year with
using average temperature. Groups make according linearity rate of
curve. Ultimate forecast for each group obtain with considering
weekday and weekend. This paper investigates effects of temperature
and humidity on consuming curve. For forecasting load curve of
holidays at first forecast pick and valley and then the neural network
forecast is re-shaped with the new data. The ANN-based load models
are trained using hourly historical. Load data and daily historical
max/min temperature and humidity data. The results of testing the
system on data from Yazd utility are reported.
Abstract: The purpose of this work is measurement of the
system presampling MTF of a variable resolution x-ray (VRX) CT
scanner. In this paper, we used the parameters of an actual VRX CT
scanner for simulation and study of effect of different focal spot sizes
on system presampling MTF by Monte Carlo method (GATE
simulation software). Focal spot size of 0.6 mm limited the spatial
resolution of the system to 5.5 cy/mm at incident angles of below 17º
for cell#1. By focal spot size of 0.3 mm the spatial resolution
increased up to 11 cy/mm and the limiting effect of focal spot size
appeared at incident angles of below 9º. The focal spot size of 0.3
mm could improve the spatial resolution to some extent but because
of magnification non-uniformity, there is a 10 cy/mm difference
between spatial resolution of cell#1 and cell#256. The focal spot size
of 0.1 mm acted as an ideal point source for this system. The spatial
resolution increased to more than 35 cy/mm and at all incident angles
the spatial resolution was a function of incident angle. By the way
focal spot size of 0.1 mm minimized the effect of magnification nonuniformity.
Abstract: The halophilic proteinase showed a maximal activity
at 50°C and pH 9~10, in 20% NaCl and was highly stabilized by
NaCl. It was able to hydrolyse natural actomyosin (NAM), collagen
and anchovy protein. For NAM hydrolysis, the myosin heavy chain
was completely digested by halophilic proteinase as evidenced by the
lowest band intensity remaining, but partially hydrolysed actin. The
SR5-3 proteinase was also capable hydrolyzing two major
components of collagen, β- and α-compounds, effectively. The
degree of hydrolysis (DH) of the halophilic proteinase and
commercial proteinases (Novozyme, Neutrase, chymotrypsin and
Flavourzyme) on the anchovy protein, were compared, and it was
found that the proteinase showed a greater degree of hydrolysis
towards anchovy protein than that from commercial proteinases. DH
of halophilic proteinase was sharply enhanced according to the
increase in the concentration of enzyme from 0.035 U to 0.105 U.
The results warranting that the acceleration of the production of fish
sauce with higher quality, may be achieved by adding of the
halophilic proteinase from this bacterium.
Abstract: The dental composites are preferably used as filling
materials due to their esthetic appearances. Nevertheless one of the
major problems, during the application of the dental composites, is
shape change named as “polymerisation shrinkage" affecting clinical
success of the dental restoration while photo-polymerisation.
Polymerisation shrinkage of composites arises basically from the
formation of a polymer due to the monomer transformation which
composes of an organic matrix phase. It was sought, throughout this
study, to detect and evaluate the structural polymerisation shrinkage
of prepared dental composites in order to optimize the effects of
various fillers included in hydroxyapatite (HA)-reinforced dental
composites and hence to find a means to modify the properties of
these dental composites prepared with defined parameters. As a
result, the shrinkage values of the experimental dental composites
were decreased by increasing the filler content of composites and the
composition of different fillers used had effect on the shrinkage of
the prepared composite systems.
Abstract: As seen in literature, about 70% of the improvement initiatives fail, and a significant number do not even get started. This paper analyses the problem of failing initiatives on Software Process Improvement (SPI), and proposes good practices supported by motivational tools that can help minimizing failures. It elaborates on the hypothesis that human factors are poorly addressed by deployers, especially because implementation guides usually emphasize only technical factors. This research was conducted with SPI deployers and analyses 32 SPI initiatives. The results indicate that although human factors are not commonly highlighted in guidelines, the successful initiatives usually address human factors implicitly. This research shows that practices based on human factors indeed perform a crucial role on successful implantations of SPI, proposes change management as a theoretical framework to introduce those practices in the SPI context and suggests some motivational tools based on SPI deployers experience to support it.
Abstract: This paper presents the applicability of artificial
neural networks for 24 hour ahead solar power generation forecasting
of a 20 kW photovoltaic system, the developed forecasting is suitable
for a reliable Microgrid energy management. In total four neural
networks were proposed, namely: multi-layred perceptron, radial
basis function, recurrent and a neural network ensemble consisting in
ensemble of bagged networks. Forecasting reliability of the proposed
neural networks was carried out in terms forecasting error
performance basing on statistical and graphical methods. The
experimental results showed that all the proposed networks achieved
an acceptable forecasting accuracy. In term of comparison the neural
network ensemble gives the highest precision forecasting comparing
to the conventional networks. In fact, each network of the ensemble
over-fits to some extent and leads to a diversity which enhances the
noise tolerance and the forecasting generalization performance
comparing to the conventional networks.
Abstract: In over deployed sensor networks, one approach
to Conserve energy is to keep only a small subset of sensors
active at Any instant. For the coverage problems, the monitoring
area in a set of points that require sensing, called demand points, and
consider that the node coverage area is a circle of range R, where R
is the sensing range, If the Distance between a demand point and
a sensor node is less than R, the node is able to cover this point. We
consider a wireless sensor network consisting of a set of sensors
deployed randomly. A point in the monitored area is covered if it is
within the sensing range of a sensor. In some applications, when the
network is sufficiently dense, area coverage can be approximated by
guaranteeing point coverage. In this case, all the points of wireless
devices could be used to represent the whole area, and the working
sensors are supposed to cover all the sensors. We also introduce
Hybrid Algorithm and challenges related to coverage in sensor
networks.