Abstract: Oxygen and carbon isotopes records of multi-species planktonic, benthic foraminifera and bulk carbonate sample from Central Java Indonesia demonstrate that warm sea surface temperature occurred during the Miocene. Planktonic δ18O values from this study consistently lighter (-4 to -3 ‰PDB) than previous studies that indicate sea surface temperature during Miocene in this area was warm than tropical/equatorial localities. A surprising decrease of oxygen isotopic composition was recorded at ±14 Ma where the maximum of δ18O values is -4.87 ‰PDB for Orbulina universa, -5.02 ‰PDB for Globigerinoides sacculifer and -4.30 ‰PDB for Globoquadrina dehiscens, this event we predict as Middle Miocene Optimum. Warming of sea surface temperature we interpret as related to the development of Western Pacific Warm Pool where warm water from Pacific Ocean through the Indonesian seaway appears to remain during Miocene. Our result also show increasing suddenly of oxygen isotope values of planktic, benthic and bulk carbonate sample from ± 12 Ma, the increasing cooled surface water relatively high degree with Late Miocene global cooling climate or we predict that due to closing of Indonesian Gateway.
Abstract: Analytical procedure was carried out in this paper to
calculate the ultimate load capacity of reinforced concrete corbels
strengthened or repaired externally with CFRP sheets. Strut and tie
method and shear friction method proposed earlier for analyzing
reinforced concrete corbels were modified to incorporate the effect of
external CFRP sheets bonded to the corbel. The points of weakness
of any method that lead to an inaccuracy, especially when
overestimating test results were checked and discussed. Comparison
of prediction with the test data indicates that the ratio of test /
calculated ultimate load is 0.82 and 1.17 using strut and tie method
and shear friction method, respectively. If the limits of maximum
shear stress is followed, the calculated ultimate load capacity using
shear friction method was found to underestimates test data
considerably.
Abstract: The measurement of aerodynamic forces and moments
acting on an aircraft model is important for the development of wind
tunnel measurement technology to predict the performance of the full
scale vehicle. The potentials of an aircraft model with and without
winglet and aerodynamic characteristics with NACA wing No. 65-3-
218 have been studied using subsonic wind tunnel of 1 m × 1 m
rectangular test section and 2.5 m long of Aerodynamics Laboratory
Faculty of Engineering (University Putra Malaysia). Focusing on
analyzing the aerodynamic characteristics of the aircraft model, two
main issues are studied in this paper. First, a six component wind
tunnel external balance is used for measuring lift, drag and pitching
moment. Secondly, Tests are conducted on the aircraft model with
and without winglet of two configurations at Reynolds numbers
1.7×105, 2.1×105, and 2.5×105 for different angle of attacks. Fuzzy
logic approach is found as efficient for the representation,
manipulation and utilization of aerodynamic characteristics.
Therefore, the primary purpose of this work was to investigate the
relationship between lift and drag coefficients, with free-stream
velocities and angle of attacks, and to illustrate how fuzzy logic
might play an important role in study of lift aerodynamic
characteristics of an aircraft model with the addition of certain
winglet configurations. Results of the developed fuzzy logic were
compared with the experimental results. For lift coefficient analysis,
the mean of actual and predicted values were 0.62 and 0.60
respectively. The coreelation between actual and predicted values
(from FLS model) of lift coefficient in different angle of attack was
found as 0.99. The mean relative error of actual and predicted valus
was found as 5.18% for the velocity of 26.36 m/s which was found to
be less than the acceptable limits (10%). The goodness of fit of
prediction value was 0.95 which was close to 1.0.
Abstract: Many studies have focused on the nonlinear analysis
of electroencephalography (EEG) mainly for the characterization of
epileptic brain states. It is assumed that at least two states of the
epileptic brain are possible: the interictal state characterized by a
normal apparently random, steady-state EEG ongoing activity; and
the ictal state that is characterized by paroxysmal occurrence of
synchronous oscillations and is generally called in neurology, a
seizure.
The spatial and temporal dynamics of the epileptogenic process is
still not clear completely especially the most challenging aspects of
epileptology which is the anticipation of the seizure. Despite all the
efforts we still don-t know how and when and why the seizure
occurs. However actual studies bring strong evidence that the
interictal-ictal state transition is not an abrupt phenomena. Findings
also indicate that it is possible to detect a preseizure phase.
Our approach is to use the neural network tool to detect interictal
states and to predict from those states the upcoming seizure ( ictal
state). Analysis of the EEG signal based on neural networks is used
for the classification of EEG as either seizure or non-seizure. By
applying prediction methods it will be possible to predict the
upcoming seizure from non-seizure EEG.
We will study the patients admitted to the epilepsy monitoring
unit for the purpose of recording their seizures. Preictal, ictal, and
post ictal EEG recordings are available on such patients for analysis
The system will be induced by taking a body of samples then
validate it using another. Distinct from the two first ones a third body
of samples is taken to test the network for the achievement of
optimum prediction. Several methods will be tried 'Backpropagation
ANN' and 'RBF'.
Abstract: The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.
Abstract: This paper examines the influence of communication
form on employee uncertainty during mergers and acquisitions
(M&As). Specifically, the author uses narrative theory to analyze
how narrative organizational communication affects the three
components of uncertainty – decreased predictive, explanatory, and
descriptive ability. It is hypothesized that employees whose
organizations use narrative M&A communication will have greater
predictive, explanatory, and descriptive abilities than employees of
organizations using non-narrative M&A communication. This paper
contributes to the stream of research examining uncertainty during
mergers and acquisitions and argues that narratives are an effective
means of managing uncertainty in the mergers and acquisitions
context.
Abstract: This work presents an approach for the measurement
of mutual inductance on near field inductive coupling. The mutual
inductance between inductive circuits allows the simulation of energy
transfer from reader to tag, that can be used in RFID and powerless
implantable devices. It also allows one to predict the maximum
voltage in the tag of the radio-frequency system.
Abstract: Cosmic showers, during the transit through space, produce
sub - products as a result of interactions with the intergalactic
or interstellar medium which after entering earth generate secondary
particles called Extensive Air Shower (EAS). Detection and analysis
of High Energy Particle Showers involve a plethora of theoretical and
experimental works with a host of constraints resulting in inaccuracies
in measurements. Therefore, there exist a necessity to develop a
readily available system based on soft-computational approaches
which can be used for EAS analysis. This is due to the fact that soft
computational tools such as Artificial Neural Network (ANN)s can be
trained as classifiers to adapt and learn the surrounding variations. But
single classifiers fail to reach optimality of decision making in many
situations for which Multiple Classifier System (MCS) are preferred
to enhance the ability of the system to make decisions adjusting
to finer variations. This work describes the formation of an MCS
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN) with data inputs
from correlation mapping Self Organizing Map (SOM) blocks and
the output optimized by another SOM. The results show that the setup
can be adopted 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: In this paper, a semi empirical formula is presented based on the experimental results to predict the first pick (maximum force) value in the instantaneous folding force- axial distance diagram of a square column. To achieve this purpose, the maximum value of the folding force was assumed to be a function of the average folding force. Using the experimental results, the maximum value of the force necessary to initiate the first fold in a square column was obtained with respect to the geometrical quantities and material properties. Finally, the results obtained from the semi empirical relation in this paper, were compared to the experimental results which showed a good correlation.
Abstract: Tubular linear induction motor (TLIM) can be used as a capsule pump in a large pneumatic capsule pipeline (PCP) system. Parametric performance evaluation of the designed 1-meter diameter PCP-TLIM system yields encouraging results for practical implementation. The capsule thrust and speed inside the TLIM pump can be calculated from the combination of the PCP fluid mechanics and the TLIM equations. The TLIM equivalent circuits derived from those of the conventional three-phase induction motor are used as a model to predict the static test results of a small-scale PCP-TLIM system. In this paper, additional dynamic tests are performed on the same small-scale PCP-TLIM system with two capsules of different diameters. The behaviors of the capsule inside the pump are observed and analyzed. The dynamic performances from the dynamic tests are compared with the theoretical predictions based on the TLIM equivalent circuit model.
Abstract: Since primary school trips usually start from home,
attention by many scholars have been focused on the home end for
data gathering. Thereafter category analysis has often been relied
upon when predicting school travel demands. In this paper, school
end was relied on for data gathering and multivariate regression for
future travel demand prediction. 9859 pupils were surveyed by way
of questionnaires at 21 primary schools. The town was divided into 5
zones. The study was carried out in Skudai Town, Malaysia. Based
on the hypothesis that the number of primary school trip ends are
expected to be the same because school trips are fixed, the choice of
trip end would have inconsequential effect on the outcome. The
study compared empirical data for home and school trip end
productions and attractions. Variance from both data results was
insignificant, although some claims from home based family survey
were found to be grossly exaggerated. Data from the school trip ends
was relied on for travel demand prediction because of its
completeness. Accessibility, trip attraction and trip production were
then related to school trip rates under daylight and dry weather
conditions. The paper concluded that, accessibility is an important
parameter when predicting demand for future school trip rates.
Abstract: Natural ventilation is an important means to improve indoor thermal comfort and reduce the energy consumption. A solar chimney system is an enhancing natural draft device, which uses solar radiation to heat the air inside the chimney, thereby converting the thermal energy into kinetic energy. The present study considered some parameters such as chimney width and solar intensity, which were believed to have a significant effect on space ventilation. Fluent CFD software was used to predict buoyant air flow and flow rates in the cavities. The results were compared with available published experimental and theoretical data from the literature. There was an acceptable trend match between the present results and the published data for the room air change per hour, ACH. Further, it was noticed that the solar intensity has a more significant effect on ACH.
Abstract: The effects of dynamic subgrid scale (SGS) models are
investigated in variational multiscale (VMS) LES simulations of bluff
body flows. The spatial discretization is based on a mixed finite
element/finite volume formulation on unstructured grids. In the VMS
approach used in this work, the separation between the largest and the
smallest resolved scales is obtained through a variational projection
operator and a finite volume cell agglomeration. The dynamic version
of Smagorinsky and WALE SGS models are used to account for
the effects of the unresolved scales. In the VMS approach, these
effects are only modeled in the smallest resolved scales. The dynamic
VMS-LES approach is applied to the simulation of the flow around a
circular cylinder at Reynolds numbers 3900 and 20000 and to the flow
around a square cylinder at Reynolds numbers 22000 and 175000. It
is observed as in previous studies that the dynamic SGS procedure
has a smaller impact on the results within the VMS approach than in
LES. But improvements are demonstrated for important feature like
recirculating part of the flow. The global prediction is improved for
a small computational extra cost.
Abstract: In this paper, a theoretical formula is presented to
predict the instantaneous folding force of the first fold creation in a
square column under axial loading. Calculations are based on analysis
of “Basic Folding Mechanism" introduced by Wierzbicki and
Abramowicz. For this purpose, the sum of dissipated energy rate under
bending around horizontal and inclined hinge lines and dissipated
energy rate under extensional deformations are equated to the work rate
of the external force on the structure. Final formula obtained in this
research, reasonably predicts the instantaneous folding force of the first
fold creation versus folding distance and folding angle and also predicts
the instantaneous folding force instead of the average value. Finally,
according to the calculated theoretical relation, instantaneous folding
force of the first fold creation in a square column was sketched
versus folding distance and was compared to the experimental results
which showed a good correlation.
Abstract: The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation.
Abstract: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.
Abstract: In this paper, for the first time, a two-dimensional
(2D) analytical drain current model for sub-100 nm multi-layered
gate material engineered trapezoidal recessed channel (MLGMETRC)
MOSFET: a novel design is presented and investigated using
ATLAS and DEVEDIT device simulators, to mitigate the large gate
leakages and increased standby power consumption that arise due to
continued scaling of SiO2-based gate dielectrics. The twodimensional
(2D) analytical model based on solution of Poisson-s
equation in cylindrical coordinates, utilizing the cylindrical
approximation, has been developed which evaluate the surface
potential, electric field, drain current, switching metric: ION/IOFF
ratio and transconductance for the proposed design. A good
agreement between the model predictions and device simulation
results is obtained, verifying the accuracy of the proposed analytical
model.
Abstract: Subcritical water extraction was investigated as a
novel and alternative technology in the food and pharmaceutical
industry for the separation of Mannitol from olive leaves and its
results was compared with those of Soxhlet extraction. The effects of
temperature, pressure, and flow rate of water and also momentum
and mass transfer dimensionless variables such as Reynolds and
Peclet Numbers on extraction yield and equilibrium partition
coefficient were investigated. The 30-110 bars, 60-150°C, and flow
rates of 0.2-2 mL/min were the water operating conditions. The
results revealed that the highest Mannitol yield was obtained at
100°C and 50 bars. However, extraction of Mannitol was not
influenced by the variations of flow rate. The mathematical modeling
of experimental measurements was also investigated and the model is
capable of predicting the experimental measurements very well. In
addition, the results indicated higher extraction yield for the
subcritical water extraction in contrast to Soxhlet method.
Abstract: In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.
Abstract: In this paper, an ultra low power and low jitter 12bit
CMOS digitally controlled oscillator (DCO) design is presented.
Based on a ring oscillator implemented with low power Schmitt
trigger based inverters. Simulation of the proposed DCO using 32nm
CMOS Predictive Transistor Model (PTM) achieves controllable
frequency range of 550MHz~830MHz with a wide linearity and high
resolution. Monte Carlo simulation demonstrates that the time-period
jitter due to random power supply fluctuation is under 31ps and the
power consumption is 0.5677mW at 750MHz with 1.2V power
supply and 0.53-ps resolution. The proposed DCO has a good
robustness to voltage and temperature variations and better linearity
comparing to the conventional design.