Abstract: Performance control law is studied for an
interconnected fractional nonlinear system. Applying a backstepping
algorithm, a backstepping sliding mode controller (BSMC) is
developed for fractional nonlinear system. To improve control law
performance, BSMC is coupled to an adaptive sliding mode observer
have a filtered error as a sliding surface. The both architecture
performance is studied throughout the inverted pendulum mounted on
a cart. Simulation result show that the BSMC coupled to an adaptive
sliding mode observer have stable control law and eligible control
amplitude than the BSMC.
Abstract: Flood zoning studies have become more efficient in
recent years because of the availability of advanced computational
facilities and use of Geographic Information Systems (GIS). In the
present study, flood inundated areas were mapped using GIS for the
Dikrong river basin of Arunachal Pradesh, India, corresponding to
different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps
developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average
deviation of modelled flood inundation areas from reported map
inundation areas is below 5% (4.52%). Therefore, it can be said that
the modelled flood inundation areas matched satisfactorily with
reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.
Abstract: The article presents a new method for detection of
artificial objects and materials from images of the environmental
(non-urban) terrain. Our approach uses the hue and saturation (or Cb
and Cr) components of the image as the input to the segmentation
module that uses the mean shift method. The clusters obtained as the
output of this stage have been processed by the decision-making
module in order to find the regions of the image with the significant
possibility of representing human. Although this method will detect
various non-natural objects, it is primarily intended and optimized for
detection of humans; i.e. for search and rescue purposes in non-urban
terrain where, in normal circumstances, non-natural objects shouldn-t
be present. Real world images are used for the evaluation of the
method.
Abstract: Yield and Crop Water Productivity are crucial issues
in sustainable agriculture, especially in high-demand resource crops such as sweet corn. This study was conducted to investigate
agronomic responses such as plant growth, yield and soil parameters (EC and Nitrate accumulation) to several deficit irrigation treatments
(100, 75, 50, 25 and 0% of ETm) applied during vegetative growth
stage, rainfed treatment was also tested.
The finding of this research indicates that under deficit irrigation
during vegetative growth stage applying 75% of ETm lead to increasing of 19.4% in terms of fresh ear yield, 9.4% in terms of dry grain yield, 10.5% in terms of number of ears per plant, 11.5% for
the 1000 grains weight and 19% in terms of crop water productivity compared with fully irrigated treatment. While those parameters in
addition to root, shoot and plant height has been affected by deficit
irrigation during vegetative growth stage when increasing water stress degree more than 50% of ETm.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: Lectins have a good scope in current clinical
microbiology research. In the present study evaluated the
antimicrobial activities of a D-galactose binding lectin (PnL) was
purified from the annelid, Perinereis nuntia (polychaeta) by affinity
chromatography. The molecular mass of the lectin was determined to
be 32 kDa as a single polypeptide by SDS-PAGE under both reducing
and non-reducing conditions. The hemagglutinating activity of the
PnL showed against trypsinized and glutaraldehyde-fixed human
erythrocytes was specifically inhibited by D-Gal, GalNAc,
Galβ1-4Glc and Galα1-6Glc. PnL was evaluated for in vitro
antibacterial screening studies against 11 gram-positive and
gram-negative microorganisms. From the screening results, it was
revealed that PnL exhibited significant antibacterial activity against
gram-positive bacteria. Bacillus megaterium showed the highest
growth inhibition by the lectin (250 μg/disc). However, PnL did not
inhibit the growth of gram-negative bacteria such as Vibrio cholerae
and Pseudomonas sp. PnL was also examined for in vitro antifungal
activity against six fungal phytopathogens. PnL (100 μg/mL) inhibited
the mycelial growth of Alternaria alternata (24.4%). These results
indicate that future findings of lectin applications obtained from
annelids may be of importance to life sciences.
Abstract: This paper presents the research agenda that has been proposed to develop an integrated model to explain technology adoption of SMEs in Malaysia. SMEs form over 90% of all business entities in Malaysia and they have been contributing to the development of the nation. Technology adoption has been a thorn issue among SMEs as they require big outlay which might not be available to the SMEs. Although resource has been an issue among SMEs they cannot lie low and ignore the technological advancements that are taking place at a rapid pace. With that in mind this paper proposes a model to explain the technology adoption issue among SMEs.
Abstract: Chatter vibration has been a troublesome problem for a
machine tool toward the high precision and high speed machining.
Essentially, the machining performance is determined by the dynamic
characteristics of the machine tool structure and dynamics of cutting
process. Therefore the dynamic vibration behavior of spindle tool
system greatly determines the performance of machine tool. The
purpose of this study is to investigate the influences of the machine
frame structure on the dynamic frequency of spindle tool unit through
finite element modeling approach. To this end, a realistic finite
element model of the vertical milling system was created by
incorporated the spindle-bearing model into the spindle head stock of
the machine frame. Using this model, the dynamic characteristics of
the milling machines with different structural designs of spindle head
stock and identical spindle tool unit were demonstrated. The results of
the finite element modeling reveal that the spindle tool unit behaves
more compliant when the excited frequency approaches the natural
mode of the spindle tool; while the spindle tool show a higher dynamic
stiffness at lower frequency that may be initiated by the structural
mode of milling head. Under this condition, it is concluded that the
structural configuration of spindle head stock associated with the
vertical column of milling machine plays an important role in
determining the machining dynamics of the spindle unit.
Abstract: In this paper a new approach for transmission pricing
is presented. The main idea is voltage angle allocation, i.e.
determining the contribution of each contract on the voltage angle of
each bus. DC power flow is used to compute a primary solution for
angle decomposition. To consider the impacts of system non-linearity
on angle decomposition, the primary solution is corrected in different
iterations of decoupled Newton-Raphson power flow. Then, the
contribution of each contract on power flow of each transmission line
is computed based on angle decomposition. Contract-related flows
are used as a measure for “extent of use" of transmission network
capacity and consequently transmission pricing. The presented
approach is applied to a 4-bus test system and IEEE 30-bus test
system.
Abstract: In this paper a class of analog algorithms based on the
concept of Cellular Neural Network (CNN) is applied in some
processing operations of some important medical images, namely
retina images, for detecting various symptoms connected with
diabetic retinopathy. Some specific processing tasks like
morphological operations, linear filtering and thresholding are
proposed, the corresponding template values are given and
simulations on real retina images are provided.
Abstract: Obesity is frequent attendant phenomenon of patients
with endocrinological disease. Between BMI and endocrinological
diseases is close correlation. In thesis we focused on the allocation of
hormone concentration – PTH and TSH, CHOL a mineral element Ca
in a blood serum. The examined group was formed by 100
respondents (women) aged 36 – 83 years, who were divided into two
groups – control group (CG), group with diagnosed endocrine disease
(DED). The concentration of PTH and TSH, Ca and CHOL was
measured through the medium of analyzers Cobas e411 (Japan);
Cobas Integra 400 (Switzerland). At individuals was measured body
weight as well as stature and thereupon from those data we
enumerated BMI. On the basis of Student T-test in biochemical
parameter of PTH and Ca we found out significantly meaningful
difference (p
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Background noise is particularly damaging to speech
intelligibility for people with hearing loss especially for sensorineural
loss patients. Several investigations on speech intelligibility have
demonstrated sensorineural loss patients need 5-15 dB higher SNR
than the normal hearing subjects. This paper describes Discrete
Cosine Transform Power Normalized Least Mean Square algorithm
to improve the SNR and to reduce the convergence rate of the LMS
for Sensory neural loss patients. Since it requires only real arithmetic,
it establishes the faster convergence rate as compare to time domain
LMS and also this transformation improves the eigenvalue
distribution of the input autocorrelation matrix of the LMS filter.
The DCT has good ortho-normal, separable, and energy compaction
property. Although the DCT does not separate frequencies, it is a
powerful signal decorrelator. It is a real valued function and thus
can be effectively used in real-time operation. The advantages of
DCT-LMS as compared to standard LMS algorithm are shown via
SNR and eigenvalue ratio computations. . Exploiting the symmetry
of the basis functions, the DCT transform matrix [AN] can be
factored into a series of ±1 butterflies and rotation angles. This
factorization results in one of the fastest DCT implementation. There
are different ways to obtain factorizations. This work uses the fast
factored DCT algorithm developed by Chen and company. The
computer simulations results show superior convergence
characteristics of the proposed algorithm by improving the SNR at
least 10 dB for input SNR less than and equal to 0 dB, faster
convergence speed and better time and frequency characteristics.
Abstract: In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
strategies.
Abstract: Different methods containing biometric algorithms are
presented for the representation of eigenfaces detection including
face recognition, are identification and verification. Our theme of this
research is to manage the critical processing stages (accuracy, speed,
security and monitoring) of face activities with the flexibility of
searching and edit the secure authorized database. In this paper we
implement different techniques such as eigenfaces vector reduction
by using texture and shape vector phenomenon for complexity
removal, while density matching score with Face Boundary Fixation
(FBF) extracted the most likelihood characteristics in this media
processing contents. We examine the development and performance
efficiency of the database by applying our creative algorithms in both
recognition and detection phenomenon. Our results show the
performance accuracy and security gain with better achievement than
a number of previous approaches in all the above processes in an
encouraging mode.
Abstract: Empirical insights into the implementation of logistics competencies at the top management level are scarce. This paper addresses this issue with an explorative approach which is based on a dataset of 872 observations in the years 2000, 2004 and 2008 using quantitative content analysis from annual reports of the 500 publicly listed firms with the highest global research and development expenditures according to the British Department for Business Innovation and Skills. We find that logistics competencies are more pronounced in Asian companies than in their European or American counterparts. On an industrial level the results are quite mixed. Using partial point-biserial correlations we show that logistics competencies are positively related to financial performance.
Abstract: This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.
Abstract: This paper describes a research project on Year 3 primary school students in Malaysia in their use of computer-based video game to enhance learning of multiplication facts (tables) in the Mathematics subject. This study attempts to investigate whether video games could actually contribute to positive effect on children-s learning or otherwise. In conducting this study, the researchers assume a neutral stand in the investigation as an unbiased outcome of the study would render reliable response to the impact of video games in education which would contribute to the literature of technology-based education as well as impact to the pedagogical aspect of formal education. In order to conduct the study, a subject (Mathematics) with a specific topic area in the subject (multiplication facts) is chosen. The study adopts a causal-comparative research to investigate the impact of the inclusion of a computer-based video game designed to teach multiplication facts to primary level students. Sample size is 100 students divided into two i.e., A: conventional group and B conventional group aided by video games. The conventional group (A) would be taught multiplication facts (timetables) and skills conventionally. The other group (B) underwent the same lessons but with supplementary activity: a computer-based video game on multiplication which is called Timez-Attack. Analysis of marks accrued from pre-test will be compared to post- test using comparisons of means, t tests, and ANOVA tests to investigate the impact of computer games as an added learning activity. The findings revealed that video games as a supplementary activity to classroom learning brings significant and positive effect on students- retention and mastery of multiplication tables as compared to students who rely only upon formal classroom instructions.
Abstract: Many non-conventional adsorbent have been studied
as economic alternative to commercial activated carbon and mostly
agricultural waste have been introduced such as rubber leaf powder
and hazelnut shell. Microwave Incinerated Rice Husk Ash
(MIRHA), produced from the rice husk is one of the low-cost
materials that were used as adsorbent of heavy metal. The aim of
this research was to study the feasibility of using MIRHA500 and
MIRHA800 as adsorbent for the removal of Cu(II) metal ions from
aqueous solutions by the batch studies. The adsorption of Cu(II) into
MIRHA500 and MIRH800 favors Fruendlich isotherm and imply
pseudo – kinetic second order which applied chemisorptions