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: 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: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
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: Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Abstract: The aim of irrigation is to recharge the available water
in the soil. Quality of irrigation water is essential for the yield and
quality of crops produced, maintenance of soil productivity and
protection of the environment. The analysis of irrigation water arises
as a need to know the impact of irrigation water on the yield of crops,
the effect, and the necessary control measures to rectify the effect of
this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water
with its performance on crop planted, in Josepdam irrigation scheme
Bacita, Nigeria. Field visits were undertaken to identify and locate
water supply sources and collect water samples from these sources;
X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory
experiments were then undertaken to determine the quality of raw
water from these sources. The analysis was carried for various parameters namely; physical
and chemical analyses after water samples have been taken from four
sources. The samples were tested in laboratory. Results showed that
the raw water sources shows no salinity tendencies with SAR values
less than 1me/l and Ecvaules at Zero while the pH were within the
recommended range by FAO, there are increase in potassium and
sulphate content contamination in three of the location. From this, it
is recommended that there should be proper monitoring of the
scheme by conducting analysis of water and soil in the environment,
preferable test should be carried out at least one year to cover the
impact of seasonal variations and to determine the physical and
chemical analysis of the water used for irrigation at the scheme.
Abstract: Aerobic dance has becoming a popular mode of
exercise especially among women due to its fun nature. With a catchy
music background and joyful dance steps, aerobic dancers would be
able to have fun while sweating out. Depending on its level of
aggressiveness, aerobic may also improve and maintain
cardiorespiratory fitness other than being a great tool for weight loss.
This study intends to prove that aerobic dance activity can bring the
same, if not better impacts on health than other types of
cardiovascular exercise such as jogging and cycling. The objective of
this study was to evaluate and identify the effect of six weeks aerobic
dance on cardiovascular fitness and weight loss among women. This
study, which was held in Seremban Fit Challenge, used a quasiexperimental
design. The subjects selected include a total of 14
women (n = 14) with age (32.4 years old ± 9.1), weight (65.93 kg ±
11.24) and height (165.36 ± 3.46) who joined the Seremban Fit
Challenge Season 13. The subjects were asked to join an aerobic
dance class with a duration of one hour for six weeks in a row. As for
the outcome, cardiovascular fitness was measured with a 1-mile run
test while any changes on weight were measured using the weighing
scale. The result showed that there was a significant difference
between pre and post-test for cardiovascular fitness when p = 0.02
Abstract: Torrefaction of biomass pellets is considered as a
useful pretreatment technology in order to convert them into a high
quality solid biofuel that is more suitable for pyrolysis, gasification,
combustion, and co-firing applications. In the course of torrefaction,
the temperature varies across the pellet, and therefore chemical
reactions proceed unevenly within the pellet. However, the
uniformity of the thermal distribution along the pellet is generally
assumed. The torrefaction process of a single cylindrical pellet is
modeled here, accounting for heat transfer coupled with chemical
kinetics. The drying sub-model was also introduced. The nonstationary
process of wood pellet decomposition is described by the
system of non-linear partial differential equations over the
temperature and mass. The model captures well the main features of
the experimental data.
Abstract: This paper proposes a method of learning topics for
broadcasting contents. There are two kinds of texts related to
broadcasting contents. One is a broadcasting script, which is a series of
texts including directions and dialogues. The other is blogposts, which
possesses relatively abstracted contents, stories, and diverse
information of broadcasting contents. Although two texts range over
similar broadcasting contents, words in blogposts and broadcasting
script are different. When unseen words appear, it needs a method to
reflect to existing topic. In this paper, we introduce a semantic
vocabulary expansion method to reflect unseen words. We expand
topics of the broadcasting script by incorporating the words in
blogposts. Each word in blogposts is added to the most semantically
correlated topics. We use word2vec to get the semantic correlation
between words in blogposts and topics of scripts. The vocabularies of
topics are updated and then posterior inference is performed to
rearrange the topics. In experiments, we verified that the proposed
method can discover more salient topics for broadcasting contents.
Abstract: This paper outlines the development of an
experimental technique in quantifying supersonic jet flows, in an
attempt to avoid seeding particle problems frequently associated with
particle-image velocimetry (PIV) techniques at high Mach numbers.
Based on optical flow algorithms, the idea behind the technique
involves using high speed cameras to capture Schlieren images of the
supersonic jet shear layers, before they are subjected to an adapted
optical flow algorithm based on the Horn-Schnuck method to
determine the associated flow fields. The proposed method is capable
of offering full-field unsteady flow information with potentially
higher accuracy and resolution than existing point-measurements or
PIV techniques. Preliminary study via numerical simulations of a
circular de Laval jet nozzle successfully reveals flow and shock
structures typically associated with supersonic jet flows, which serve
as useful data for subsequent validation of the optical flow based
experimental results. For experimental technique, a Z-type Schlieren
setup is proposed with supersonic jet operated in cold mode,
stagnation pressure of 4 bar and exit Mach of 1.5. High-speed singleframe
or double-frame cameras are used to capture successive
Schlieren images. As implementation of optical flow technique to
supersonic flows remains rare, the current focus revolves around
methodology validation through synthetic images. The results of
validation test offers valuable insight into how the optical flow
algorithm can be further improved to improve robustness and
accuracy. Despite these challenges however, this supersonic flow
measurement technique may potentially offer a simpler way to
identify and quantify the fine spatial structures within the shock shear
layer.
Abstract: The present study investigates the effectiveness of
newly designed clayey pellets (fired clay pellets diameter sizes of 5
and 8 mm, and unfired clay pellets with the diameter size of 15 mm)
as the beds in the column adsorption process. The adsorption
experiments in the batch mode were performed before the column
experiment with the purpose to determine the order of adsorbent
package in the column which was to be designed in the investigation.
The column experiment was performed by using a known mass of the
clayey beds and the volume of the waste printing developer, which
was purified. The column was filled in the following order: fired clay
pellets of the diameter size of 5 mm, fired clay pellets of the diameter
size of 8 mm, and unfired clay pellets of the diameter size of 15 mm.
The selected order of the adsorbents showed a high removal
efficiency for zinc (97.8%) and copper (81.5%) ions. These
efficiencies were better than those in the case of the already existing
mode adsorption. The obtained experimental data present a good
basis for the selection of an appropriate column fill, but further
testing is necessary in order to obtain more accurate results.
Abstract: Landfill waste is a common problem as it has an
economic and environmental impact even if it is closed. Landfill
waste contains a high density of various persistent compounds such
as heavy metals, organic and inorganic materials. As persistent
compounds are slowly-degradable or even non-degradable in the
environment, they often produce sublethal or even lethal effects on
aquatic organisms. The aims of the present study were to estimate
sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“,
23°23‘28.4“) leachate on the locomotor activity of rainbow trout
Oncorhynchus mykiss juveniles using the original system package
developed in our laboratory for automated monitoring, recording and
analysis of aquatic organisms’ activity, and to determine patterns of
fish behavioral response to sublethal effects of leachate. Four
different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and
1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50,
respectively). Locomotor activity was measured after 5, 10 and 30
minutes of exposure during 1-minute test-periods of each fish (7 fish
per treatment). The threshold-effect-concentration amounted to 0.18
mL/L (0.0036 parts of 96-hour LC50). This concentration was found
to be even 2.8-fold lower than the concentration generally assumed to
be “safe” for fish. At higher concentrations, the landfill leachate
solution elicited behavioral response of test fish to sublethal levels of
pollutants. The ability of the rainbow trout to detect and avoid
contaminants occurred after 5 minutes of exposure. The intensity of
locomotor activity reached a peak within 10 minutes, evidently
decreasing after 30 minutes. This could be explained by the
physiological and biochemical adaptation of fish to altered
environmental conditions. It has been established that the locomotor
activity of juvenile trout depends on leachate concentration and
exposure duration. Modeling of these parameters showed that the
activity of juveniles increased at higher leachate concentrations, but
slightly decreased with the increasing exposure duration. Experiment
results confirm that the behavior of rainbow trout juveniles is a
sensitive and rapid biomarker that can be used in combination with
the system for fish behavior monitoring, registration and analysis to
determine sublethal concentrations of pollutants in ambient water.
Further research should be focused on software improvement aimed
to include more parameters of aquatic organisms’ behavior and to
investigate the most rapid and appropriate behavioral responses in
different species. In practice, this study could be the basis for the
development and creation of biological early-warning systems
(BEWS).
Abstract: At the Savonia University of Applied Sciences (UAS),
curriculum and studies have been improved by applying an Open
Innovation Space approach (OIS). It is based on multidisciplinary
action learning. The key elements of OIS-ideology are work-life
orientation, and student-centric communal learning. In this approach,
every participant can learn from each other and innovations will be
created. In this social innovation educational approach, all practices
are carried out in close collaboration with enterprises in real-life
settings, not in classrooms. As an example, in this paper, Savonia
UAS’s Future Food RDI hub (FF) shows how OIS practices are
implemented by providing food product development and consumer
research services for enterprises in close collaboration with
academicians, students and consumers. In particular one example of
OIS experimentation in the field is provided by a consumer research
carried out utilizing verbal analysis protocol combined with audiovisual
observation (VAP-WAVO). In this case, all co-learners were
acting together in supermarket settings to collect the relevant data for
a product development and the marketing department of a company.
The company benefitted from the results obtained, students were
more satisfied with their studies, educators and academicians were
able to obtain good evidence for further collaboration as well as
renewing curriculum contents based on the requirements of working
life. In addition, society will benefit over time as young university
adults find careers more easily through their OIS related food science
studies. Also this knowledge interaction model re-news education
practices and brings working-life closer to educational research
institutes.
Abstract: In the present study, a numerical approach to describe the pyrolysis of a single solid particle of wood is used to study the influence of various conditions such as particle size, heat transfer coefficient, reactor temperature and heating rate. The influence of these parameters in the change of the duration of the pyrolysis cycle was studied. Mathematical modeling was employed to simulate the heat, mass transfer, and kinetic processes inside the reactor. The evolutions of the mass loss as well as the evolution of temperature inside the thick piece are investigated numerically. The elaborated model was also employed to study the effect of the reactor temperature and the rate of heating on the change of the temperature and the local loss of the mass inside the piece of wood. The obtained results are in good agreement with the experimental data available in the literature.
Abstract: Concrete is an essential building material which is
widely used in construction industry all over the world due to its
compressible strength. Curing of concrete plays a vital role in
durability and other performance necessities. Improper curing can
affect the concrete performance and durability easily. When areas
like scarcity of water, structures is not accessible by humans external
curing cannot be performed, so we opt for internal curing. Internal
curing (or) self curing plays a major role in developing the concrete
pore structure and microstructure. The concept of internal curing is to
enhance the hydration process to maintain the temperature uniformly.
The evaporation of water in the concrete is reduced by self curing
agent (Super Absorbing Polymer – SAP) there by increasing the
water retention capacity of the concrete. The research work was
carried out to reduce water, which is prime material used for concrete
in the construction industry. Concrete curing plays a major role in
developing hydration process. Concept of self curing will reduce the
evaporation of water from concrete. Self curing will increase water
retention capacity as compared to the conventional concrete. Proper
self curing (or) internal curing increases the strength, durability and
performance of concrete. Super absorbing Polymer (SAP) used as
internal curing agent. In this study 0.2% to 0.4% of SAP was varied
in different grade of high strength concrete. In the experiment
replacement of cement by silica fumes with 5%, 10% and 15% are
studied. It is found that replacement of silica fumes by 10 % gives
more strength and durability when compared to others.
Abstract: The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.
Abstract: Electro-osmosis in clayey soils and sediments, for
purposes of clay consolidation, dewatering, or cleanup, and electro
injection in porous media is widespread recent decades. It is
experimentally found that the chemical properties of porous media
especially PH change the characteristics of media. Electro-osmotic
conductivity is a function of soil and grout material chemistry,
altering with time. Many numerical approaches exist to simulate the
of electro kinetic flow rate considering chemical changes. This paper
presents a simplified analytical solution for constant flow rate based
on varying electro osmotic conductivity and time dependent viscosity
for injection of colloidal silica.
Abstract: In order to study the Mutual effect of genotype ×
environment for the percent of oil index in sunflower items, an
experiment was accomplished form complete random block designs
in four iteration and was four diverse researching station comprising
Esfahan, Birjand, Sari, and Karaj. Complex variance analysis showed
that there is an important diversity between the items under
investigation. The results relevant the coefficient variation of items
Azargol and Vidoc has respectively allocated the minimum
coefficient of variations. According to the results extrapolated from
Shokla stability variance, the Items Brocar, Allison and Fabiola, are
among the stable genotypes for oil percent respectively. In the biplot
GGE, the location under investigations divided in two superenvironments,
first one comprised of locations naming Esfahan,
Karaj, and Birjand, and second one were such a location as Sari. By
this point of view, in the first super-environment, the Item Fabiola
and in the second Almanzor item was among the best items and
crops.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: Nanofibers are defined as fibers with diameters less
than 100 nanometers. In this study, behaviours of activated carbon
nanofiber (ACNF), carbon nanofiber (CNF), polyacrylonitrile/ carbon
nanotube (PAN/CNT), polyvinyl alcohol/nanosilver (PVA/Ag) in
proton exchange membrane (PEM) fuel cells are investigated
experimentally. This material was used as gas diffusion layer (GDL)
in PEM fuel cells. In this study, the electrical conductivities of
nanofiber and nanofiber/nanoparticles have been studied to
understand their effects on PEM fuel cell performance. According to
the experimental results, the maximum electrical conductivity
performance of the fuel cell with nanofiber was found to be at
PVA/Ag (at UConn condition). The electrical conductivities of CNF,
ACNF, PAN/CNT are lower for PEM. The resistance of cell with
PVA/Ag is lower than the resistance of cell with PAN/CNT, ACNF,
CNF.