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: 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: An analysis of the air tightness level is performed on a representative sample of school classrooms in Southern Spain, which allows knowing the infiltration level of these classrooms, mainly through its envelope, which can affect both energy demand and occupant's thermal comfort. By using a pressurization/depressurization equipment (Blower-Door test), a characterization of 45 multipurpose classrooms have been performed in nine non-university educational institutions of the main climate zones of Southern Spain. In spite of having two doors and a high ratio between glass surface and outer surface, it is possible to see in these classrooms that there is an adequate level of airtightness, since all the n50 values obtained are lower than 9.0 ACH, with an average value around 7.0 ACH.
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: 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: The application of recycle waste tires into civil
engineering practices, namely asphalt paving mixtures and cementbased
materials has been gaining ground across the world. This
review summarizes and compares the recent achievements in the area
of plain rubberized concrete (PRC), in details. Different treatment
methods have been discussed to improve the performance of
rubberized Portland cement concrete. The review also includes the
effects of size and amount of tire rubbers on mechanical and
durability properties of PRC. The microstructure behaviour of the
rubberized concrete was detailed.
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: Green roof system is considered a relatively new
concept in Malaysia even though it has been implemented widely in
the developed countries. Generally, green roofs provide many
benefits such as enhancing aesthetical quality of the built
environment, reduce urban heat island effect, reduce energy
consumption, improve stormwater attenuation, and reduce noise
pollution. A better understanding on the implementation of green roof
system in Malaysia is crucial, as Malaysia’s climate is different if
compared with the climate in temperate countries where most of the
green roof studies have been conducted. This study has concentrated
on the technical aspect of green roof system which focuses on i) types
of plants and method of planting; ii) engineering design for green
roof system; iii) its hydrological performance on reducing stormwater
runoff; and iv) benefits of green roofs with respect to energy.
Literature review has been conducted to identify the development and
obstacles associated with green roofs systems in Malaysia. The study
had identified the challenges and potentials of green roofs
development in Malaysia. This study also provided the
recommendations on standard design and strategies on the
implementation of green roofs in Malaysia in the near future.
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: 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: This paper looks at healing performances as
ethnographic expressions of local knowledge and culture embedded
within the Malay psyche and gemeinschaft. As society develops and
progresses, these healing performances are caught within conflicting
trajectories which become compounded by the contestations of
tradition, religious concerns, locality and modernity. As
exemplifications of the Malay ethos, these performances practice
common rituals, cater to the innate needs of the practitioners and
serve the targeted, closed, local community. This paper traces the
ethnographic methods in documenting these practices as rituals of
healing in a post-modern world. It delineates the ethnographic
concepts used to analyze these rituals, and to semiotically read the
varied binarial oppositions and juxtapositions. The paper concludes
by highlighting the reconciliatory processes involved in maintaining
these ritual performances as exemplifications of the Malay ethos
playing an important role in the re-aligning, re-balancing and healing
of the Malay community’s psyche.
Abstract: This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post-surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.
Abstract: Parental expectations often differ to that of their children and the influence and involvement of parents, at home, may affect the student performance in the classroom. This paper presents results from a survey of Asian and European background secondary school mathematics students (N=128) in Melbourne, Australia. Student responses to survey questions were analysed using confirmatory factor analysis, followed by t-tests and ANOVA. The aim of the analysis was to identify similarities and differences in parental expectations in relation to ethnicity, gender, and the year level of the students. The notable findings from the analysis showed no significant difference (at 0.05 level) in parental expectations and student performance, in relation to ethnicity or gender. Conversely, there was a significant difference in both parental expectations and student performance between year 7 and year 12 students. Further, whilst there was a significant difference in parental expectations between year 7 and year 11 students, the students’ performances were not significantly different. The results suggest further research may be needed to understand the parental expectations and student performance between the lower and upper secondary school mathematics students.
Abstract: With the strengthened regulation on the mandatory use
of recycled aggregate, development of construction materials using
recycled aggregate has recently increased. This study aimed to secure
the performance of asphalt concrete mixture by developing
recycled-modified asphalt using recycled basalt aggregate from the
Jeju area. The strength of the basalt aggregate from the Jeju area used
in this study was similar to that of general aggregate, while the specific
surface area was larger due to the development of pores. Modified
asphalt was developed using a general aggregate-recycled aggregate
ratio of 7:3, and the results indicated that the Marshall stability
increased by 27% compared to that of asphalt concrete mixture using
only general aggregate, and the flow values showed similar levels.
Also, the indirect tensile strength increased by 79%, and the toughness
increased by more than 100%. In addition, the TSR for examining
moisture resistance was 0.95 indicating that the reduction in the
indirect tensile strength due to moisture was very low (5% level), and
the developed recycled-modified asphalt could satisfy all the quality
standards of asphalt concrete mixture.
Abstract: Energy consumption data, in particular those involving
public buildings, are impacted by many factors: the building structure,
climate/environmental parameters, construction, system operating
condition, and user behavior patterns. Traditional methods for data
analysis are insufficient. This paper delves into the data mining
technology to determine its application in the analysis of building
energy consumption data including energy consumption prediction,
fault diagnosis, and optimal operation. Recent literature are reviewed
and summarized, the problems faced by data mining technology in the
area of energy consumption data analysis are enumerated, and research
points for future studies are given.
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.