Abstract: This research involved the use of word distributions
and morphological knowledge by speakers of Arabic learning English
connected different allomorphs in order to realize how the
morphology and syntax of English gives meaning through using
interactive crossword puzzles (ICP). Fifteen chapters covered with a
class of nine learners over an academic year of an intensive English
program were reviewed using the ICP. Learners were questioned
about how the use of this gaming element enhanced and motivated
their learning of English. The findings were positive indicating a
successful implementation of ICP both at creational and user levels.
This indicated a positive role technology had when learning and
teaching English through adopting an interactive gaming element for
learning English.
Abstract: Dan C. Lortie’s Schoolteacher: A sociological study is
one of the best works on the sociology of teaching since W. Waller’s
classic study. It is a book worthy of review. Following the tradition of
symbolic interactionists, Lortie demonstrated the qualities who studied
the occupation of teaching. Using several methods to gather effective
data, Lortie has portrayed the ethos of the teaching profession.
Therefore, the work is an important book on the teaching profession
and teacher culture. Though outstanding, Lortie’s work is also flawed
in that his perspectives and methodology were adopted largely from
symbolic interactionism. First, Lortie in his work analyzed many
points regarding teacher culture; for example, he was interested in
exploring “sentiment,” “cathexis,” and “ethos.” Thus, he was more a
psychologist than a sociologist. Second, symbolic interactionism led
him to discern the teacher culture from a micro view, thereby missing
the structural aspects. For example, he did not fully discuss the issue of
gender and he ignored the issue of race. Finally, following the
qualitative sociological tradition, Lortie employed many qualitative
methods to gather data but only foucused on obtaining and presenting
interview data. Moreover, he used measurement methods that were too
simplistic for analyzing quantitative data fully.
Abstract: Many embankment dams have suffered failures during
earthquakes due to the increase of pore water pressure under seismic
loading. After analyzing of the behavior of embankment dams under
severe earthquakes, major advances have been attained in the
understanding of the seismic action on dams. The present study concerns numerical analysis of the seismic
response of earth dams. The procedure uses a nonlinear stress-strain
relation incorporated into the code FLAC2D based on the finite
difference method. This analysis provides the variation of the pore
water pressure and horizontal displacement.
Abstract: While the feature sizes of recent Complementary Metal
Oxid Semiconductor (CMOS) devices decrease the influence of static
power prevails their energy consumption. Thus, power savings that
benefit from Dynamic Frequency and Voltage Scaling (DVFS) are
diminishing and temporal shutdown of cores or other microchip
components become more worthwhile. A consequence of powering off unused parts of a chip is that the
relative difference between idle and fully loaded power consumption
is increased. That means, future chips and whole server systems gain
more power saving potential through power-aware load balancing,
whereas in former times this power saving approach had only
limited effect, and thus, was not widely adopted. While powering
off complete servers was used to save energy, it will be superfluous
in many cases when cores can be powered down. An important
advantage that comes with that is a largely reduced time to respond
to increased computational demand. We include the above developments in a server power model
and quantify the advantage. Our conclusion is that strategies from
datacenters when to power off server systems might be used in the
future on core level, while load balancing mechanisms previously
used at core level might be used in the future at server level.
Abstract: Flash flood is occurred in short time rainfall interval:
from 1 hour to 12 hours in small and medium basins. Flash floods
typically have two characteristics: large water flow and big flow
velocity. Flash flood is occurred at hill valley site (strip of lowland of
terrain) in a catchment with large enough distribution area, steep
basin slope, and heavy rainfall. The risk of flash floods is determined
through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash
Flood Potential Index (FFPI) is determined through terrain slope
flash flood index, soil erosion flash flood index, land cover flash
floods index, land use flash flood index, rainfall flash flood index.
Determining GBFFPI, each cell in a map can be considered as outlet
of a water accumulation basin. GBFFPI of the cell is determined as
basin average value of FFPI of the corresponding water accumulation
basin. Based on GIS, a tool is developed to compute GBFFPI using
ArcObjects SDK for .NET. The maps of GBFFPI are built in two
types: GBFFPI including rainfall flash flood index (real time flash
flood warning) or GBFFPI excluding rainfall flash flood index.
GBFFPI Tool can be used to determine a high flash flood potential
site in a large region as quick as possible. The GBFFPI is improved
from conventional FFPI. The advantage of GBFFPI is that GBFFPI is
taking into account the basin response (interaction of cells) and
determines more true flash flood site (strip of lowland of terrain)
while conventional FFPI is taking into account single cell and does
not consider the interaction between cells. The GBFFPI Map of
QuangNam, QuangNgai, DaNang, Hue is built and exported to
Google Earth. The obtained map proves scientific basis of GBFFPI.
Abstract: Mumbai, being traditionally the epicenter of India's
trade and commerce, the existing major ports such as Mumbai and
Jawaharlal Nehru Ports (JN) situated in Thane estuary are also
developing its waterfront facilities. Various developments over the
passage of decades in this region have changed the tidal flux
entering/leaving the estuary. The intake at Pir-Pau is facing the
problem of shortage of water in view of advancement of shoreline,
while jetty near Ulwe faces the problem of ship scheduling due to
existence of shallower depths between JN Port and Ulwe Bunder. In
order to solve these problems, it is inevitable to have information
about tide levels over a long duration by field measurements.
However, field measurement is a tedious and costly affair;
application of artificial intelligence was used to predict water levels
by training the network for the measured tide data for one lunar tidal
cycle. The application of two layered feed forward Artificial Neural
Network (ANN) with back-propagation training algorithms such as
Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to
predict the yearly tide levels at waterfront structures namely at Ulwe
Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe,
and Vashi for a period of lunar tidal cycle (2013) was used to train,
validate and test the neural networks. These trained networks having
high co-relation coefficients (R= 0.998) were used to predict the tide
at Ulwe, and Vashi for its verification with the measured tide for the
year 2000 & 2013. The results indicate that the predicted tide levels
by ANN give reasonably accurate estimation of tide. Hence, the
trained network is used to predict the yearly tide data (2015) for
Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was
predicted by using the neural network which was trained with the
help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The
measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is
maximum amplification of tide by about 10-20 cm with a phase lag
of 10-20 minutes with reference to the tide at Apollo Bunder
(Mumbai). LM training algorithm is faster than GD and with increase
in number of neurons in hidden layer and the performance of the
network increases. The predicted tide levels by ANN at Pir-Pau and
Ulwe provides valuable information about the occurrence of high and
low water levels to plan the operation of pumping at Pir-Pau and
improve ship schedule at Ulwe.
Abstract: The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.
Abstract: Open jet testing is a valuable testing technique which
provides the desired results with reasonable accuracy. It has been
used in past for the airships and now has recently been applied for the
hybrid ones, having more non-buoyant force coming from the wings,
empennage and the fuselage. In the present review work, an effort
has been done to review the challenges involved in open jet testing.
In order to shed light on the application of this technique, the
experimental results of two different configurations are presented.
Although, the aerodynamic results of such vehicles are unique to its
own design; however, it will provide a starting point for planning any
future testing. Few important testing areas which need more attention
are also highlighted. Most of the hybrid buoyant aerial vehicles are
unconventional in shape and there experimental data is generated,
which is unique to its own design.
Abstract: Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).
Abstract: Magnetic Resonance Imaging Contrast Agents
(MRI-CM) are significant in the clinical and biological imaging as
they have the ability to alter the normal tissue contrast, thereby
affecting the signal intensity to enhance the visibility and detectability
of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles,
coated with dextran or carboxydextran are currently available for
clinical MR imaging of the liver. Most SPIO contrast agents are
T2 shortening agents and Resovist (Ferucarbotran) is one of a
clinically tested, organ-specific, SPIO agent which has a low
molecular carboxydextran coating. The enhancement effect of
Resovist depends on its relaxivity which in turn depends on factors
like magnetic field strength, concentrations, nanoparticle properties,
pH and temperature. Therefore, this study was conducted to
investigate the impact of field strength and different contrast
concentrations on enhancement effects of Resovist. The study
explored the MRI signal intensity of Resovist in the physiological
range of plasma from T2-weighted spin echo sequence at three
magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4,
r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast
concentrations by a mathematical simulation. Relaxivities of r1 and r2
(L mmol-1 Sec-1) were obtained from a previous study and the selected
concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were
simulated using TR/TE ratio as 2000 ms /100 ms. According to the
reference literature, with increasing magnetic field strengths, the
r1 relaxivity tends to decrease while the r2 did not show any
systematic relationship with the selected field strengths. In parallel,
this study results revealed that the signal intensity of Resovist at lower
concentrations tends to increase than the higher concentrations. The
highest reported signal intensity was observed in the low field strength
of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T
were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L,
respectively. Furthermore, it was revealed that, the concentrations
higher than the above, the signal intensity was decreased
exponentially. An inverse relationship can be found between the field
strength and T2 relaxation time, whereas, the field strength was
increased, T2 relaxation time was decreased accordingly. However,
resulted T2 relaxation time was not significantly different between
0.47 T and 1.5 T in this study. Moreover, a linear correlation of
transverse relaxation rates (1/T2, s–1) with the concentrations of
Resovist can be observed. According to these results, it can conclude
that the concentration of SPIO nanoparticle contrast agents and the
field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR
imaging those two parameters should be considered prudently.
Abstract: The process of human resources management in the structures of corporate groups demonstrates certain specificity, resulting from the division of decision-making and executive competencies, which occurs within these structures between a parent company and its subsidiaries. The subprocess of employee assessment is considered crucial, since it provides information for the implementation of personnel function. The empirical studies conducted in corporate groups, within which at least one company is located in Poland, confirmed the critical significance of employee assessment systems in the process of human resources management in corporate groups. Parent companies, most often, retain their decision-making authority within the framework of the discussed process and introduce uniform employee assessment and personnel controlling systems to subsidiary companies. However, the instruments for employee assessment applied in corporate groups do not present such specificity.
Abstract: With 40% of total world energy consumption,
building systems are developing into technically complex large
energy consumers suitable for application of sophisticated power
management approaches to largely increase the energy efficiency
and even make them active energy market participants. Centralized
control system of building heating and cooling managed by
economically-optimal model predictive control shows promising
results with estimated 30% of energy efficiency increase. The research
is focused on implementation of such a method on a case study
performed on two floors of our faculty building with corresponding
sensors wireless data acquisition, remote heating/cooling units and
central climate controller. Building walls are mathematically modeled
with corresponding material types, surface shapes and sizes. Models
are then exploited to predict thermal characteristics and changes in
different building zones. Exterior influences such as environmental
conditions and weather forecast, people behavior and comfort
demands are all taken into account for deriving price-optimal climate
control. Finally, a DC microgrid with photovoltaics, wind turbine,
supercapacitor, batteries and fuel cell stacks is added to make the
building a unit capable of active participation in a price-varying
energy market. Computational burden of applying model predictive
control on such a complex system is relaxed through a hierarchical
decomposition of the microgrid and climate control, where the
former is designed as higher hierarchical level with pre-calculated
price-optimal power flows control, and latter is designed as lower
level control responsible to ensure thermal comfort and exploit
the optimal supply conditions enabled by microgrid energy flows
management. Such an approach is expected to enable the inclusion
of more complex building subsystems into consideration in order to
further increase the energy efficiency.
Abstract: This paper describes a simple way to control the speed
of PMBLDC motor using Fuzzy logic control method. In the
conventional PI controller the performance of the motor system is
simulated and the speed is regulated by using PI controller. These
methods used to improve the performance of PMSM drives, but in
some cases at different operating conditions when the dynamics of
the system also vary over time and it can change the reference speed,
parameter variations and the load disturbance. The simulation is
powered with the MATLAB program to get a reliable and flexible
simulation. In order to highlight the effectiveness of the speed control
method the FLC method is used. The proposed method targeted in
achieving the improved dynamic performance and avoids the
variations of the motor drive. This drive has high accuracy, robust
operation from near zero to high speed. The effectiveness and
flexibility of the individual techniques of the speed control method
will be thoroughly discussed for merits and demerits and finally
verified through simulation and experimental results for comparative
analysis.
Abstract: 21st century has transformed the labor market
landscape in a way of posing new and different demands on
university graduates as well as university lecturers, which means that
the knowledge and academic skills students acquire in the course of
their studies should be applicable and transferable from the higher
education context to their future professional careers. Given the
context of the Languages for Specific Purposes (LSP) classroom, the
teachers’ objective is not only to teach the language itself, but also to
prepare students to use that language as a medium to develop generic
skills and competences. These include media and information
literacy, critical and creative thinking, problem-solving and analytical
skills, effective written and oral communication, as well as
collaborative work and social skills, all of which are necessary to
make university graduates more competitive in everyday professional
environments. On the other hand, due to limitations of time and large
numbers of students in classes, the frequently topic-centered syllabus
of LSP courses places considerable focus on acquiring the subject
matter and specialist vocabulary instead of sufficient development of
skills and competences required by students’ prospective employers.
This paper intends to explore some of those issues as viewed both by
LSP lecturers and by business professionals in their respective
surveys. The surveys were conducted among more than 50 LSP
lecturers at higher education institutions in Croatia, more than 40 HR
professionals and more than 60 university graduates with degrees in
economics and/or business working in management positions in
mainly large and medium-sized companies in Croatia. Various elements of LSP course content have been taken into
consideration in this research, including reading and listening
comprehension of specialist texts, acquisition of specialist vocabulary
and grammatical structures, as well as presentation and negotiation
skills. The ability to hold meetings, conduct business correspondence,
write reports, academic texts, case studies and take part in debates
were also taken into consideration, as well as informal business
communication, business etiquette and core courses delivered in a
foreign language. The results of the surveys conducted among LSP
lecturers will be analyzed with reference to what extent those
elements are included in their courses and how consistently and
thoroughly they are evaluated according to their course requirements.
Their opinions will be compared to the results of the surveys
conducted among professionals from a range of industries in Croatia
so as to examine how useful and important they perceive the same
elements of the LSP course content in their working environments.
Such comparative analysis will thus show to what extent the syllabi
of LSP courses meet the demands of the employment market when it
comes to the students’ language skills and competences, as well as
transferable skills. Finally, the findings will also be compared to the
observations based on practical teaching experience and the relevant
sources that have been used in this research. In conclusion, the ideas and observations in this paper are merely
open-ended questions that do not have conclusive answers, but might
prompt LSP lecturers to re-evaluate the content and objectives of
their course syllabi.
Abstract: This paper presents the performance characteristics of
Darrieus-type vertical axis wind turbine (VAWT) with NACA airfoil
blades. The performance of Darrieus-type VAWT can be
characterized by torque and power. There are various parameters
affecting the performance such as chord length, helical angle, pitch
angle and rotor diameter. To estimate the optimum shape of Darrieustype
wind turbine in accordance with various design parameters, we
examined aerodynamic characteristics and separated flow occurring
in the vicinity of blade, interaction between flow and blade, and
torque and power characteristics derived from it. For flow analysis,
flow variations were investigated based on the unsteady RANS
(Reynolds-averaged Navier-Stokes) equation. Sliding mesh algorithm
was employed in order to consider rotational effect of blade. To
obtain more realistic results we conducted experiment and numerical
analysis at the same time for three-dimensional shape. In addition,
several parameters (chord length, rotor diameter, pitch angle, and
helical angle) were considered to find out optimum shape design and
characteristics of interaction with ambient flow. Since the NACA
airfoil used in this study showed significant changes in magnitude of
lift and drag depending on an angle of attack, the rotor with low drag,
long cord length and short diameter shows high power coefficient in
low tip speed ratio (TSR) range. On the contrary, in high TSR range,
drag becomes high. Hence, the short-chord and long-diameter rotor
produces high power coefficient. When a pitch angle at which airfoil
directs toward inside equals to -2° and helical angle equals to 0°,
Darrieus-type VAWT generates maximum power.
Abstract: The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.
Abstract: Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
Abstract: This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.
Abstract: Data fusion technology can be the best way to extract
useful information from multiple sources of data. It has been widely
applied in various applications. This paper presents a data fusion
approach in multimedia data for event detection in twitter by using
Dempster-Shafer evidence theory. The methodology applies a mining
algorithm to detect the event. There are two types of data in the
fusion. The first is features extracted from text by using the bag-ofwords
method which is calculated using the term frequency-inverse
document frequency (TF-IDF). The second is the visual features
extracted by applying scale-invariant feature transform (SIFT). The
Dempster - Shafer theory of evidence is applied in order to fuse the
information from these two sources. Our experiments have indicated
that comparing to the approaches using individual data source, the
proposed data fusion approach can increase the prediction accuracy
for event detection. The experimental result showed that the proposed
method achieved a high accuracy of 0.97, comparing with 0.93 with
texts only, and 0.86 with images only.
Abstract: In the aviation industry, many faults may occur frequently during the maintenance processes and assembly operations of complex structured aircrafts because of their high dependencies of components. These faults affect the quality of aircraft parts or developed modules adversely. Technical employee requires long time and high labor force while checking the correctness of each component. In addition, the person must be trained regularly because of the ever-growing and changing technology. Generally, the cost of this training is very high. Augmented Reality (AR) technology reduces the cost of training radically and improves the effectiveness of the training. In this study, the usage of AR technology in the aviation industry has been investigated and the effectiveness of AR with heads-up display glasses has been examined. An application has been developed for comparison of production process with AR and manual one.