Abstract: This paper contributes to the debate on the proximate
causes of climate change. Also, it discusses the impact of the global
temperature increases since the beginning of the twentieth century
and the effectiveness of climate change models in isolating the
primary cause (anthropogenic influences or natural variability in
temperature) of the observed temperature increases that occurred
within this period. The paper argues that if climate scientist and
policymakers ignore the anthropogenic influence (greenhouse gases)
on global warming on the pretense of lack of agreement among
various climate models and their inability to account for all the
necessary factors of global warming at all levels the current efforts of
greenhouse emissions control and global warming as a whole could
be exacerbated.
Abstract: Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.
Abstract: Competing risks survival data that comprises of more
than one type of event has been used in many applications, and one
of these is in clinical study (e.g. in breast cancer study). The
decision tree method can be extended to competing risks survival
data by modifying the split function so as to accommodate two or
more risks which might be dependent on each other. Recently,
researchers have constructed some decision trees for recurrent
survival time data using frailty and marginal modelling. We further
extended the method for the case of competing risks. In this paper,
we developed the decision tree method for competing risks survival
time data based on proportional hazards for subdistribution of
competing risks. In particular, we grow a tree by using deviance
statistic. The application of breast cancer data is presented. Finally,
to investigate the performance of the proposed method, simulation
studies on identification of true group of observations were executed.
Abstract: In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: The microbial production of ethanol from biodiesel¬derived crude glycerol by Enterobacter aerogenes TISTR1468, under micro-aerobic and anaerobic conditions, was investigated. The experimental results showed that micro-aerobic conditions were more favorable for cellular growth (4.0 g/L DCW), ethanol production (20.7 g/L) as well as the ethanol yield (0.47 g/g glycerol) than anaerobic conditions (1.2 g/L DCW, 6.3 g/L ethanol and 0.72 g/g glycerol, respectively). Crude glycerol (100 g/L) was consumed completely with the rate of 1.80 g/L/h. Two-stage fermentation (combination of micro-aerobic and anaerobic condition) exhibited higher ethanol production (24.5 g/L) than using one-stage fermentation (either micro-aerobic or anaerobic condition. The two- stage configuration, exhibited slightly higher crude glycerol consumption rate (1.81 g/L/h), as well as ethanol yield (0.56 g/g) than the one-stage configuration. Therefore, two-stage process was selected for ethanol production from E. aerogenes TISTR1468 in scale-up studies.
Abstract: Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.
Abstract: The usefulness of weaning foods to meet the nutrient
needs of children is well recognized, and most of them are precooked
roller dried mixtures of cereal and/or legume flours which posses a
high viscosity and bulk when reconstituted. The objective of this study
was to formulate composite weaning foods using cereals, malted
legumes and vegetable powders and analyze them for nutrients,
functional properties and sensory attributes. Selected legumes (green
gram and lentil) were germinated, dried and dehulled. Roasted wheat,
rice, carrot powder and skim milk powder also were used. All the
ingredients were mixed in different proportions to get four
formulations, made into 30% slurry and dried in roller drier. The
products were analyzed for proximate principles, mineral content,
functional and sensory qualities. The results of analysis showed
following range of constituents per 100g of formulations on dry
weight basis, protein, 18.1-18.9 g ; fat, 0.78-1.36 g ; iron, 5.09-6.53
mg; calcium, 265-310 mg. The lowest water absorption capacity was
in case of wheat green gram based and the highest was in rice lentil
based sample. Overall sensory qualities of all foods were graded as
“good" and “very good" with no significant differences. The results
confirm that formulated weaning foods were nutritionally superior,
functionally appropriate and organoleptically acceptable.
Abstract: In this paper, LDPC Codes based on defected fullerene
graphs have been generated. And it is found that the codes generated
are fast in encoding and better in terms of error performance on
AWGN Channel.
Abstract: This paper reports on a survey of state-of-the-art
application scenarios for smart office environments. Based on an
analysis of ongoing research activities and industry projects,
functionalities and services of future office systems are extracted. In
a second step, these results are used to identify the key characteristics
of emerging products.
Abstract: In contrast to conventional generators, self-excited induction generators are found to be most suitable machines for wind energy conversion in remote and windy areas due to many advantages over grid connected machines. This papers presents a Self-Excited Induction Generator (SEIG) driven by wind turbine and supplying an induction motor which is coupled to a centrifugal pump. A method to describe the steady state performance based on nodal analysis is presented. Therefore the advanced knowledge of the minimum excitation capacitor value is required. The effects of variation of excitation capacitance on system and rotor speed under different loading conditions have been analyzed and considered to optimize induction motor pump performances.
Abstract: A DC-to-DC converter for applications involving a
source with widely varying voltage conditions with loads requiring
constant voltage from full load down to no load is presented.
The switching regulator considered is a Buck converter with Pulse
Skipping Modulation control whereby pulses applied to the switch
are blocked or released on output voltage crossing a predetermined
value. Results of the study on the performance of regulator circuit
are presented. The regulator regulates over a wide input voltage range
with slightly higher ripple content and good transient response. Input
current spectrum indicates a good EMI performance with crowding
of components at low frequency range.
Abstract: this paper focuses on designing of PSS and SVC
controller based on chaos and PSO algorithms to improve the
stability of power system. Single machine infinite bus (SMIB) system
with SVC located at the terminal of generator has been considered to
evaluate the proposed controllers where both SVC and PSS have the
same controller. The coefficients of PSS and SVC controller have
been optimized by chaos and PSO algorithms. Finally the system
with proposed controllers has been simulated for the special
disturbance in input power of generator, and then the dynamic
responses of generator have been presented. The simulation results
showed that the system composed with recommended controller has
outstanding operation in fast damping of oscillations of power system.
Abstract: This article investigated the validity of C-test and Cloze test which purport to measure general English proficiency. To provide empirical evidence pertaining to the validity of the interpretations based on the results of these integrative language tests, their criterion-related validity was investigated. In doing so, the test of English as a foreign language (TOEFL) which is an established, standardized, and internationally administered test of general English proficiency was used as the criterion measure. Some 90 Iranian English majors participated in this study. They were seniors studying English at a university in Tehran, Iran. The results of analyses showed that there is a statistically significant correlation among participants- scores on Cloze test, C-test, and the TOEFL. Building on the findings of the study and considering criterion-related validity as the evidential basis of the validity argument, it was cautiously deducted that these tests measure the same underlying trait. However, considering the limitations of using criterion measures to validate tests, no absolute claims can be made as to the construct validity of these integrative tests.
Abstract: In this article the influence of higher frequency effects
in addition to a special damper design on the electrical behavior of a
synchronous generator main exciter machine is investigated. On the
one hand these machines are often highly stressed by harmonics from
the bridge rectifier thus facing additional eddy current losses. On the
other hand the switching may cause the excitation of dangerous
voltage peaks in resonant circuits formed by the diodes of the
rectifier and the commutation reactance of the machine. Therefore
modern rotating exciters are treated like synchronous generators
usually modeled with a second order equivalent circuit. Hence the
well known Standstill Frequency Response Test (SSFR) method is
applied to a test machine in order to determine parameters for the
simulation. With these results it is clearly shown that higher
frequencies have a strong impact on the conventional equivalent
circuit model. Because of increasing field displacement effects in the
stranded armature winding the sub-transient reactance is even smaller
than the armature leakage at high frequencies. As a matter of fact this
prevents the algorithm to find an equivalent scheme. This issue is
finally solved using Laplace transfer functions fully describing the
transient behavior at the model ports.
Abstract: In this paper, a technique is proposed to implement
an artificial voltage-controlled capacitance or inductance which can
replace the well-known varactor diode in many applications. The
technique is based on injecting the current of a voltage-controlled
current source onto a fixed capacitor or inductor. Then, by controlling
the transconductance of the current source by an external bias voltage,
a voltage-controlled capacitive or inductive reactance is obtained.
The proposed voltage-controlled reactance devices can be designed
to work anywhere in the frequency spectrum. Practical circuits for the
proposed voltage-controlled reactances are suggested and simulated.
Abstract: Permeability reduction induced by asphaltene
precipitation during gas injection is one of the serious problems in
the oil industry. This problem can lead to formation damage and
decrease the oil production rate. In this work, Malaysian light oil
sample has been used to investigate the effect CO2 injection and
Water Alternating Gas (WAG) injection on permeability reduction.
In this work, dynamic core flooding experiments were conducted to
study the effect of CO2 and WAG injection on the amount of
asphaltene precipitated. Core properties after displacement were
inspected for any permeability reduction to study the effect of
asphaltene precipitation on rock properties.
The results showed that WAG injection gave less asphaltene
precipitation and formation damage compared to CO2 injection. The
study suggested that WAG injection can be one of the important
factors of managing asphaltene precipitation.
Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: The influence of twist arrangement on the temperature
distribution in an annular diffuser fitted with twisted rectangular hub
is investigated. Different pitches (Y = 120 mm, 100 mm, 80 mm, and
60 mm) for the twist arrangements are simulated to be compared. The
geometry of the annular diffuser and the inlet condition for the hub
arrangements are kept constant. The result reveals that using twisted
rectangular hub insert with different pitches will force the
temperature to distribute in a circular direction. However,
temperature distribution will be enhanced with the length pitch
increases.
Abstract: One of the robust fault detection filter (RFDF)
designing method is based on sliding-mode theory. The main purpose
of our study is to introduce an innovative simplified reference
residual model generator to formulate the RFDF as a sliding-mode
observer without any manipulation package or transformation matrix,
through which the generated residual signals can be evaluated. So the
proposed design is more explicit and requires less design parameters
in comparison with approaches requiring changing coordinates. To
the best author's knowledge, this is the first time that the sliding
mode technique is applied to detect actuator and sensor faults in a
real boiler. The designing procedure is proposed in a drum boiler in
Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable
and strongly coupled system. It is demonstrated that both sensor and
actuator faults can robustly be detected. Also sensor faults can be
diagnosed and isolated through this method.