Abstract: The exploitation of flow pulsation in micro- and
mini-channels is a potentially useful technique for enhancing cooling
of high-end photonics and electronics systems. It is thought that
pulsation alters the thickness of the hydrodynamic and thermal
boundary layers, and hence affects the overall thermal resistance
of the heat sink. Although the fluid mechanics and heat transfer
are inextricably linked, it can be useful to decouple the parameters
to better understand the mechanisms underlying any heat transfer
enhancement. Using two-dimensional, two-component particle image
velocimetry, the current work intends to characterize the heat transfer
mechanisms in pulsating flow with a mean Reynolds number of
48 by experimentally quantifying the hydrodynamics of a generic
liquid-cooled channel geometry. Flows circulated through the test
section by a gear pump are modulated using a controller to achieve
sinusoidal flow pulsations with Womersley numbers of 7.45 and
2.36 and an amplitude ratio of 0.75. It is found that the transient
characteristics of the measured velocity profiles are dependent on the
speed of oscillation, in accordance with the analytical solution for
flow in a rectangular channel. A large velocity overshoot is observed
close to the wall at high frequencies, resulting from the interaction
of near-wall viscous stresses and inertial effects of the main fluid
body. The steep velocity gradients at the wall are indicative of
augmented heat transfer, although the local flow reversal may reduce
the upstream temperature difference in heat transfer applications.
While unsteady effects remain evident at the lower frequency, the
annular effect subsides and retreats from the wall. The shear rate at
the wall is increased during the accelerating half-cycle and decreased
during deceleration compared to steady flow, suggesting that the flow
may experience both enhanced and diminished heat transfer during
a single period. Hence, the thickness of the hydrodynamic boundary
layer is reduced for positively moving flow during one half of the
pulsation cycle at the investigated frequencies. It is expected that the
size of the thermal boundary layer is similarly reduced during the
cycle, leading to intervals of heat transfer enhancement.
Abstract: The cumulative costs for O&M may represent as
much as 65%-90% of the turbine's investment cost. Nowadays the
cost effectiveness concept becomes a decision-making and
technology evaluation metric. The cost of energy metric accounts for
the effect replacement cost and unscheduled maintenance cost
parameters. One key of the proposed approach is the idea of
maintaining the WTs which can be captured via use of a finite state
Markov chain. Such a model can be embedded within a probabilistic
operation and maintenance simulation reflecting the action to be
done. In this paper, an approach of estimating the cost of O&M is
presented. The finite state Markov model is used for decision
problems with number of determined periods (life cycle) to predict
the cost according to various options of maintenance.
Abstract: The railway transport is considered as a one of the
most environmentally friendly mode of transport. With future
prediction of increasing of freight transport there are lines facing
problems with demanded capacity. Increase of the track capacity
could be achieved by infrastructure constructive adjustments. The
contribution shows how the travel time can be minimized and the
track capacity increased by changing some of the basic infrastructure
and operation parameters, for example, the minimal curve radius of
the track, the number of tracks, or the usable track length at stations.
Calculation of the necessary parameter changes is based on the
fundamental physical laws applied to the train movement, and
calculation of the occupation time is dependent on the changes of
controlling the traffic between the stations.
Abstract: Present paper enumerates highlights of seasonal
variation in floristic composition and ecological strategies for the
management of ‘Gujar Tal’ at Jaunpur in tropical semi-arid region of
eastern U.P. (India). Total composition of macrophytes recorded was
47 from 26 families with maximum 6 plant species of Cyperaceae
from April, 2012 to March, 2013 at certain periodic intervals.
Maximum number of plants (39) was present during winter followed
by (37) rainy and (27) summer seasons. The distribution pattern
depicted that maximum number of plants (27) was of marshy and
swampy habitats usually transitional between land and water.
Abstract: Cloud computing is a business model which provides
an easier management of computing resources. Cloud users can
request virtual machine and install additional softwares and configure
them if needed. However, user can also request virtual appliance
which provides a better solution to deploy application in much faster
time, as it is ready-built image of operating system with necessary
softwares installed and configured. Large numbers of virtual
appliances are available in different image format. User can
download available appliances from public marketplace and start
using it. However, information published about the virtual appliance
differs from each providers leading to the difficulty in choosing
required virtual appliance as it is composed of specific OS with
standard software version. However, even if user choses the
appliance from respective providers, user doesn’t have any flexibility
to choose their own set of softwares with required OS and
application. In this paper, we propose a referenced architecture for
dynamically customizing virtual appliance and provision them in an
easier manner. We also add our experience in integrating our
proposed architecture with public marketplace and Mi-Cloud, a cloud
management software.
Abstract: Nowadays, food safety is a great public concern;
therefore, robust and effective techniques are required for detecting
the safety situation of goods. Hyperspectral Imaging (HSI) is an
attractive material for researchers to inspect food quality and safety
estimation such as meat quality assessment, automated poultry
carcass inspection, quality evaluation of fish, bruise detection of
apples, quality analysis and grading of citrus fruits, bruise detection
of strawberry, visualization of sugar distribution of melons,
measuring ripening of tomatoes, defect detection of pickling
cucumber, and classification of wheat kernels. HSI can be used to
concurrently collect large amounts of spatial and spectral data on the
objects being observed. This technique yields with exceptional
detection skills, which otherwise cannot be achieved with either
imaging or spectroscopy alone. This paper presents a nonlinear
technique based on kernel Fukunaga-Koontz transform (KFKT) for
detection of fat content in ground meat using HSI. The KFKT which
is the nonlinear version of FKT is one of the most effective
techniques for solving problems involving two-pattern nature. The
conventional FKT method has been improved with kernel machines
for increasing the nonlinear discrimination ability and capturing
higher order of statistics of data. The proposed approach in this paper
aims to segment the fat content of the ground meat by regarding the
fat as target class which is tried to be separated from the remaining
classes (as clutter). We have applied the KFKT on visible and nearinfrared
(VNIR) hyperspectral images of ground meat to determine
fat percentage. The experimental studies indicate that the proposed
technique produces high detection performance for fat ratio in ground
meat.
Abstract: Asphalt pavement itself is a mixture made up of mainly aggregates, binders, and fillers that acts as a composition used for pavement construction. An experimental program was setup to determine the fatigue performance test of Asphalt with three different grades of conventional binders. Asphalt specimen has achieved the maximum optimum bulk density and air voids with a consistent bulk density of 2.3 t/m3, with an air void of 5% ± 0.5, before loading into the Asphalt Mixture Performance Tested (AMPT) for fatigue test. The number of cycles is defined as the point where phase angle drops, which is caused by the formation of cracks due to the increasing micro cracks when asphalt is undergoing repeated cycles of loading. Thus, the data collected are analyzed using the drop of phase angle as failure criteria. Based in the data analyzed, it is evident that the fatigue life of asphalt lies on the grade of binder. The result obtained shows that all specimens do experience a drop in phase angle due to macro cracks in the asphalt specimen.
Abstract: The boundary layer separation and new active flow control of a NACA 0025 airfoil were studied experimentally. This new flow control is sometimes known as a co-flow jet (cfj) airfoil. This paper presents the fluctuating velocity in a wall jet over the co-flow jet airfoil subjected to an adverse pressure gradient and a curved surface. In these results, the fluctuating velocity at the inner part increasing by increased the angle of attack up to 12o and this has due to the jet energized, while the angle of attack 20o has different. The airfoil cord based Reynolds number has 105.
Abstract: The very well-known stacked sets of numbers referred
to as Pascal’s triangle present the coefficients of the binomial
expansion of the form (x+y)n. This paper presents an approach (the
Staircase Horizontal Vertical, SHV-method) to the generalization of
planar Pascal’s triangle for polynomial expansion of the form
(x+y+z+w+r+⋯)n. The presented generalization of Pascal’s triangle
is different from other generalizations of Pascal’s triangles given in
the literature. The coefficients of the generalized Pascal’s triangles,
presented in this work, are generated by inspection, using embedded
Pascal’s triangles. The coefficients of I-variables expansion are
generated by horizontally laying out the Pascal’s elements of (I-1)
variables expansion, in a staircase manner, and multiplying them with
the relevant columns of vertically laid out classical Pascal’s elements,
hence avoiding factorial calculations for generating the coefficients
of the polynomial expansion. Furthermore, the classical Pascal’s
triangle has some pattern built into it regarding its odd and even
numbers. Such pattern is known as the Sierpinski’s triangle. In this
study, a presentation of Sierpinski-like patterns of the generalized
Pascal’s triangles is given. Applications related to those coefficients
of the binomial expansion (Pascal’s triangle), or polynomial
expansion (generalized Pascal’s triangles) can be in areas of
combinatorics, and probabilities.
Abstract: We present an approach to triangle mesh simplification
designed to be executed on the GPU. We use a quadric error metric
to calculate an error value for each vertex of the mesh and order all
vertices based on this value. This step is followed by the parallel
removal of a number of vertices with the lowest calculated error
values. To allow for the parallel removal of multiple vertices we use
a set of per-vertex boundaries that prevent mesh foldovers even when
simplification operations are performed on neighbouring vertices. We
execute multiple iterations of the calculation of the vertex errors,
ordering of the error values and removal of vertices until either a
desired number of vertices remains in the mesh or a minimum error
value is reached. This parallel approach is used to speed up the
simplification process while maintaining mesh topology and avoiding
foldovers at every step of the simplification.
Abstract: In this paper, a method has been developed to
construct the membership surfaces of row and column vectors and
arithmetic operations of imprecise matrix. A matrix with imprecise
elements would be called an imprecise matrix. The membership
surface of imprecise vector has been already shown based on
Randomness-Impreciseness Consistency Principle. The Randomness-
Impreciseness Consistency Principle leads to defining a normal law
of impreciseness using two different laws of randomness. In this
paper, the author has shown row and column membership surfaces
and arithmetic operations of imprecise matrix and demonstrated with
the help of numerical example.
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: 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: The increasing availability of information about earth
surface elevation (Digital Elevation Models DEM) generated from
different sources (remote sensing, Aerial Images, Lidar) poses the
question about how to integrate and make available to the most than
possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the
quality of data management plays a fundamental role. Due to the high
acquisition costs and the huge amount of generated data, highresolution
terrain surveys tend to be small or medium sized and
available on limited portion of earth. Here comes the need to merge
large-scale height maps that typically are made available for free at
worldwide level, with very specific high resolute datasets. One the
other hand, the third dimension increases the user experience and the
data representation quality, unlocking new possibilities in data
analysis for civil protection, real estate, urban planning, environment
monitoring, etc. The open-source 3D virtual globes, which are
trending topics in Geovisual Analytics, aim at improving the
visualization of geographical data provided by standard web services
or with proprietary formats. Typically, 3D Virtual globes like do not
offer an open-source tool that allows the generation of a terrain
elevation data structure starting from heterogeneous-resolution terrain
datasets. This paper describes a technological solution aimed to set
up a so-called “Terrain Builder”. This tool is able to merge
heterogeneous-resolution datasets, and to provide a multi-resolution
worldwide terrain services fully compatible with CesiumJS and
therefore accessible via web using traditional browser without any
additional plug-in.
Abstract: In this study, the potential benefits of playing action
video game among congenitally deaf and dumb subjects is reported in
terms of EEG ratio indices. The frontal and occipital lobes are
associated with development of motor skills, cognition, and visual
information processing and color recognition. The sixteen hours of
First-Person shooter action video game play resulted in the increase
of the ratios β/(α+θ) and β/θ in frontal and occipital lobes. This can
be attributed to the enhancement of certain aspect of cognition among
deaf and dumb subjects.
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: 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: For several hundred years, the design of railway tracks
has practically remained unchanged. Traditionally, rail tracks are
placed on a ballast layer due to several reasons, including economy,
rapid drainage, and high load bearing capacity. The primary function
of ballast is to distributing dynamic track loads to sub-ballast and
subgrade layers, while also providing lateral resistance and allowing
for rapid drainage. Upon repeated trainloads, the ballast becomes
fouled due to ballast degradation and the intrusion of fines which
adversely affects the strength and deformation behaviour of ballast.
This paper presents the use of three-dimensional discrete element
method (DEM) in studying the shear behaviour of the fouled ballast
subjected to direct shear loading. Irregularly shaped particles of
ballast were modelled by grouping many spherical balls together in
appropriate sizes to simulate representative ballast aggregates. Fouled
ballast was modelled by injecting a specified number of miniature
spherical particles into the void spaces. The DEM simulation
highlights that the peak shear stress of the ballast assembly decreases
and the dilation of fouled ballast increases with an increase level of
fouling. Additionally, the distributions of contact force chain and
particle displacement vectors were captured during shearing progress,
explaining the formation of shear band and the evolutions of
volumetric change of fouled ballast.
Abstract: Many cluster based routing protocols have been
proposed in the field of wireless sensor networks, in which a group of
nodes are formed as clusters. A cluster head is selected from one
among those nodes based on residual energy, coverage area, number
of hops and that cluster-head will perform data gathering from
various sensor nodes and forwards aggregated data to the base station
or to a relay node (another cluster-head), which will forward the
packet along with its own data packet to the base station. Here a
Game Theory based Diligent Energy Utilization Algorithm (GTDEA)
for routing is proposed. In GTDEA, the cluster head selection is done
with the help of game theory, a decision making process, that selects
a cluster-head based on three parameters such as residual energy
(RE), Received Signal Strength Index (RSSI) and Packet Reception
Rate (PRR). Finding a feasible path to the destination with minimum
utilization of available energy improves the network lifetime and is
achieved by the proposed approach. In GTDEA, the packets are
forwarded to the base station using inter-cluster routing technique,
which will further forward it to the base station. Simulation results
reveal that GTDEA improves the network performance in terms of
throughput, lifetime, and power consumption.
Abstract: Although Mobile Wireless Sensor Networks (MWSNs),
which consist of mobile sensor nodes (MSNs), can cover a wide range
of observation region by using a small number of sensor nodes, they
need to construct a network to collect the sensing data on the base
station by moving the MSNs. As an effective method, the network
construction method based on Virtual Rails (VRs), which is referred
to as VR method, has been proposed. In this paper, we propose two
types of effective techniques for the VR method. They can prolong
the operation time of the network, which is limited by the battery
capabilities of MSNs and the energy consumption of MSNs. The
first technique, an effective arrangement of VRs, almost equalizes
the number of MSNs belonging to each VR. The second technique,
an adaptive movement method of MSNs, takes into account the
residual energy of battery. In the simulation, we demonstrate that each
technique can improve the network lifetime and the combination of
both techniques is the most effective.