Abstract: Intelligent systems based on machine learning
techniques, such as classification, clustering, are gaining wide spread
popularity in real world applications. This paper presents work on
developing a software system for predicting crop yield, for example
oil-palm yield, from climate and plantation data. At the core of our
system is a method for unsupervised partitioning of data for finding
spatio-temporal patterns in climate data using kernel methods which
offer strength to deal with complex data. This work gets inspiration
from the notion that a non-linear data transformation into some high
dimensional feature space increases the possibility of linear
separability of the patterns in the transformed space. Therefore, it
simplifies exploration of the associated structure in the data. Kernel
methods implicitly perform a non-linear mapping of the input data
into a high dimensional feature space by replacing the inner products
with an appropriate positive definite function. In this paper we
present a robust weighted kernel k-means algorithm incorporating
spatial constraints for clustering the data. The proposed algorithm
can effectively handle noise, outliers and auto-correlation in the
spatial data, for effective and efficient data analysis by exploring
patterns and structures in the data, and thus can be used for
predicting oil-palm yield by analyzing various factors affecting the
yield.
Abstract: In this work, we derive two numerical schemes for
solving a class of nonlinear partial differential equations. The first
method is of second order accuracy in space and time directions, the
scheme is unconditionally stable using Von Neumann stability
analysis, the scheme produced a nonlinear block system where
Newton-s method is used to solve it. The second method is of fourth
order accuracy in space and second order in time. The method is
unconditionally stable and Newton's method is used to solve the
nonlinear block system obtained. The exact single soliton solution
and the conserved quantities are used to assess the accuracy and to
show the robustness of the schemes. The interaction of two solitary
waves for different parameters are also discussed.
Abstract: This article stands in the context of rural communities
in Brazil, where, like many others emerging countries, the
overwhelming increasing markets and the overcrowded cities are
leaving behind informal settlements based on obsolete agricultural
economies and techniques. The pilot project for the community of
Goiabeira reflects the attempt to imagine a development model that
privileges the actual improvement of living conditions, the education
and training, the social inclusion and participation of the dwellers of
rural communities. Through the inclusion of operative public space,
the aim is for them to become self-sustaining, encouraging the use of
local resources for appropriate architectural, ecological and energy
technologies and devices, that are efficient, affordable and foster
community participation, in the respect of the surrounding
environment.
Abstract: A Data Warehouses is a repository of information
integrated from source data. Information stored in data warehouse is
the form of materialized in order to provide the better performance
for answering the queries. Deciding which appropriated views to be
materialized is one of important problem. In order to achieve this
requirement, the constructing search space close to optimal is a
necessary task. It will provide effective result for selecting view to be
materialized. In this paper we have proposed an approach to reoptimize
Multiple View Processing Plan (MVPP) by using global
common subexpressions. The merged queries which have query
processing cost not close to optimal would be rewritten. The
experiment shows that our approach can help to improve the total
query processing cost of MVPP and sum of query processing cost
and materialized view maintenance cost is reduced as well after views
are selected to be materialized.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: This paper examines two policy spaces–the ARC and TVA–and their spatialized politics. The research observes that the regional concept informs public policy and can contribute to the formation of stable policy initiatives. Using the subsystem framework to understand the political viability of policy regimes, the authors conclude policy geographies that appeal to traditional definitions of regions are more stable over time. In contrast, geographies that fail to reflect pre-existing representations of space are engaged in more competitive subsystem politics. The paper demonstrates that the spatial practices of policy regions and their directional politics influence the political viability of programs. The paper concludes that policy spaces should institutionalize pre-existing geographies–not manufacture new ones.
Abstract: This article addresses feature selection for breast
cancer diagnosis. The present process contains a wrapper approach
based on Genetic Algorithm (GA) and case-based reasoning (CBR).
GA is used for searching the problem space to find all of the possible
subsets of features and CBR is employed to estimate the evaluation
result of each subset. The results of experiment show that the
proposed model is comparable to the other models on Wisconsin
breast cancer (WDBC) dataset.
Abstract: Both software applications and their development environment are becoming more and more distributed. This trend impacts not only the way software computes, but also how it looks. This article proposes a Human Computer Interface (HCI) template from three representative applications we have developed. These applications include a Multi-Agent System based software, a 3D Internet computer game with distributed game world logic, and a programming language environment used in constructing distributed neural network and its visualizations. HCI concepts that are common to these applications are described in abstract terms in the template. These include off-line presentation of global entities, entities inside a hierarchical namespace, communication and languages, reconfiguration of entity references in a graph, impersonation and access right, etc. We believe the metaphor that underlies an HCI concept as well as the relationships between a bunch of HCI concepts are crucial to the design of software systems and vice versa.
Abstract: Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
Abstract: In today's day and age, one of the important topics in
information security is authentication. There are several alternatives
to text-based authentication of which includes Graphical Password
(GP) or Graphical User Authentication (GUA). These methods stems
from the fact that humans recognized and remembers images better
than alphanumerical text characters. This paper will focus on the
security aspect of GP algorithms and what most researchers have
been working on trying to define these security features and
attributes. The goal of this study is to develop a fuzzy decision model
that allows automatic selection of available GP algorithms by taking
into considerations the subjective judgments of the decision makers
who are more than 50 postgraduate students of computer science. The
approach that is being proposed is based on the Fuzzy Analytic
Hierarchy Process (FAHP) which determines the criteria weight as a
linear formula.
Abstract: In this work, the physical based device model of
AlGaN/GaN high electron mobility transistors (HEMTs) has been
established and the corresponding device operation behavior has
been investigated also by using Sentaurus TCAD from Synopsys.
Advanced AlGaN/GaN hetero-structures with GaN cap layer and AlN
spacer have been considered and the GaN cap layer and AlN spacer
are found taking important roles on the gate leakage blocking and
off-state breakdown voltage enhancement.
Abstract: In this paper, the effect of atmospheric turbulence on
bit error probability in free-space optical CDMA scheme with
Sequence Inverse Keyed (SIK) optical correlator receiver is analyzed.
Here Intensity Modulation scheme is considered for transmission.
The turbulence induced fading is described by the newly introduced
gamma-gamma pdf[1] as a tractable mathematical model for
atmospheric turbulence. Results are evaluated with Gold and Kasami
code & it is shown that Gold sequence can be used for more
efficient transmission than Kasami sequence in an atmospheric
turbulence channel.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: Three alumina-supported Pt-Sn catalysts have been
prepared by means of co-impregnation and characterized by XRD and
N2 adsorption. The influence of catalyst composition and reaction
conditions on the conversion and selectivity were investigated in the
hydrogenation of acetic acid in an isothermal integral fixed bed
reactor. The experiments were performed on the temperature interval
468-548 K, liquid hourly space velocity (LHSV) of 0.3-0.7h-1,
pressures between 1.0 and 5.0Mpa. A good compromise of
0.75%Pt-1.5%Sn can act as an optimized acetic acid hydrogenation
catalyst, and the conversion and selectivity can be tuned through the
variation of reaction conditions.
Abstract: The technology usages of high speed Internet leads to
establish and start new era of online education. With the
advancement of the information technology and communication
systems new opportunities have been created. This leads universities
to have various online education channels to meet the demand of
different learners- needs. One of these channels is M-learning, which
can be used to improve the online education environment. With using
such mobile technology in learning both students and instructors can
easily access educational courses anytime from anywhere. The paper
first presents literature about mobile learning and to what extent this
approach can be utilized to enhance the overall learning system. It
provides a comparison between mobile learning and traditional elearning
showing the wide array of benefits of the new generation of
technology. The possible challenges and potential advantages of Mlearning
in the online education system are also discussed.
Abstract: The electromagnetic imaging of inhomogeneous
dielectric cylinders buried in a slab medium by transverse electric
(TE) wave illumination is investigated. Dielectric cylinders of
unknown permittivities are buried in second space and scattered a
group of unrelated waves incident from first space where the scattered
field is recorded. By proper arrangement of the various unrelated
incident fields, the difficulties of ill-posedness and nonlinearity are
circumvented, and the permittivity distribution can be reconstructed
through simple matrix operations. The algorithm is based on the
moment method and the unrelated illumination method. Numerical
results are given to demonstrate the capability of the inverse
algorithm. Good reconstruction is obtained even in the presence of
additive Gaussian random noise in measured data. In addition, the
effect of noise on the reconstruction result is also investigated.
Abstract: In the present article, effect of non-uniform excitation
of reservoir bottom on nonlinear response of concrete gravity dams is
considered. Anisotropic damage mechanics approach is used to model nonlinear behavior of mass concrete in 2D space. The tallest
monolith of Pine Flat dam is selected as a case study. The horizontal
and vertical components of 1967 Koyna earthquake is used to excite
the system. It is found that crest response and stresses within the dam body decrease significantly when the reservoir is excited nonuniformly. In addition, the crack profiles within the dam body and in vicinity of the neck decreases.
Abstract: The study of interaction among the grain, moisture,
and the surrounding space (air) is key to understanding the graindrying
process. In Iran, rice (mostly Indica type) is dried by flat
bed type dryer until the final MC reaches to 6 to 8%. The
experiments were conducted to examine the effect of application of
discharge fan with different heights of paddy on the drying
efficiency. Experiments were designed based on two different
configurations of the drying methods; with and without discharge
fan with three different heights of paddy including; 5, 10, and 15
cm. The humid heated air will be going out immediately by the
suction of discharge fan. The drying time is established upon the
average final MC to achieve about 8%. To save energy and reduce
the drying time, the distribution of temperature between layers
should be fast and uniform with minimum difference; otherwise
the difference of MC gradient between layers will be high and will
induce grain breakage. The difference of final MC between layers
in the two methods was 48-73%. The steady state of temperature
between the two methods has saved time in the range of 10-20%,
and the efficiency of temperature distribution increased 17-26% by
the use of discharge fan.
Abstract: This research details a Computational Fluid Dynamics (CFD) approach to model fluid flow in a journal bearing with 8 equispaced semi-circular axial grooves. Water is used as the lubricant and is fed from one end of the bearing to the other, under pressure. The geometry of the bearing is modeled using a commercially available modeling software GAMBIT and the flow analysis is performed using a dedicated CFD analysis software FLUENT. The pressure distribution in the bearing clearance is obtained from FLUENT for various whirl ratios and is used to calculate the hydrodynamic force components in the radial and tangential direction of the bearing. These values along with the various whirl speeds can be used to do a regression analysis to determine the stiffness and damping coefficients. The values obtained are then compared with the stiffness and damping coefficients of a 3 Axial groove water lubricated journal bearing and those obtained from a FORTRAN code for a similar bearing.
Abstract: This paper compares the heuristic Global Search
Techniques; Genetic Algorithm, Particle Swarm Optimization,
Simulated Annealing, Generalized Pattern Search, genetic algorithm
hybridized with Nelder–Mead and Generalized pattern search
technique for tuning of fuzzy PID controller for Puma 560. Since the
actual control is in joint space ,inverse kinematics is used to generate
various joint angles correspoding to desired cartesian space
trajectory. Efficient dynamics and kinematics are modeled on Matlab
which takes very less simulation time. Performances of all the tuning
methods with and without disturbance are compared in terms of ITSE
in joint space and ISE in cartesian space for spiral trajectory tracking.
Genetic Algorithm hybridized with Generalized Pattern Search is
showing best performance.