Abstract: We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.
Abstract: Reducing the risk of information leaks is one of
the most important functions of identity management systems. To
achieve this purpose, Dey et al. have already proposed an account
management method for a federated login system using a blind
signature scheme. In order to ensure account anonymity for the
authentication provider, referred to as an IDP (identity provider),
a blind signature scheme is utilized to generate an authentication
token on an authentication service and the token is sent to an IDP.
However, there is a problem with the proposed system. Malicious
users can establish multiple accounts on an IDP by requesting such
accounts. As a measure to solve this problem, in this paper, the
authors propose an account checking method that is performed before
account generation.
Abstract: None of the processing models in the software
development has explained the software systems performance
evaluation and modeling; likewise, there exist uncertainty in the
information systems because of the natural essence of requirements,
and this may cause other challenges in the processing of software
development. By definition an extended version of UML (Fuzzy-
UML), the functional requirements of the software defined
uncertainly would be supported. In this study, the behavioral
description of uncertain information systems by the aid of fuzzy-state
diagram is crucial; moreover, the introduction of behavioral diagrams
role in F-UML is investigated in software performance modeling
process. To get the aim, a fuzzy sub-profile is used.
Abstract: This paper presents an exact analytical model for
optimizing stability of thin-walled, composite, functionally graded
pipes conveying fluid. The critical flow velocity at which divergence
occurs is maximized for a specified total structural mass in order to
ensure the economic feasibility of the attained optimum designs. The
composition of the material of construction is optimized by defining
the spatial distribution of volume fractions of the material
constituents using piecewise variations along the pipe length. The
major aim is to tailor the material distribution in the axial direction so
as to avoid the occurrence of divergence instability without the
penalty of increasing structural mass. Three types of boundary
conditions have been examined; namely, Hinged-Hinged, Clamped-
Hinged and Clamped-Clamped pipelines. The resulting optimization
problem has been formulated as a nonlinear mathematical
programming problem solved by invoking the MatLab optimization
toolbox routines, which implement constrained function
minimization routine named “fmincon" interacting with the
associated eigenvalue problem routines. In fact, the proposed
mathematical models have succeeded in maximizing the critical flow
velocity without mass penalty and producing efficient and economic
designs having enhanced stability characteristics as compared with
the baseline designs.
Abstract: The exploration of this paper will focus on the Cshaped
transition curve. This curve is designed by using the concept
of circle to circle where one circle lies inside other. The degree of
smoothness employed is curvature continuity. The function used in
designing the C-curve is Bézier-like cubic function. This function has
a low degree, flexible for the interactive design of curves and
surfaces and has a shape parameter. The shape parameter is used to
control the C-shape curve. Once the C-shaped curve design is
completed, this curve will be applied to design spur gear tooth. After
the tooth design procedure is finished, the design will be analyzed by
using Finite Element Analysis (FEA). This analysis is used to find
out the applicability of the tooth design and the gear material that
chosen. In this research, Cast Iron 4.5 % Carbon, ASTM A-48 is
selected as a gear material.
Abstract: The usage of internet is rapidly increasing and the usage of mobile agent technology in internet environment has a great demand. The security issue one of main obstacles that restrict the mobile agent technology to spread. This paper proposes Secure-Image Mechanism (SIM) as a new mechanism to protect mobile agents against malicious hosts. . SIM aims to protect mobile agent by using the symmetric encryption and hash function in cryptography science. This mechanism can prevent the eavesdropping and alteration attacks. It assists the mobile agents to continue their journey normally incase attacks occurred.
Abstract: In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.
Abstract: This paper describes the development of an electronic
instrument that looks like a flute, which is able to sense the basic musical notes being executed by a specific user. The principal function of the instrument is to teach how to play a flute. This device
will generate a significant academic impact, in a field of virtual reality interactive that combine art and technology. With this example is expected to contribute in research and implementation of teaching devices around the world.
Abstract: Levan, an exopolysaccharide, was produced by
Microbacterium laevaniformans and its yield was characterized as a
function of concentrations of date syrup, sucrose and the fermentation
time. The optimum condition for levan production from sucrose was
at concentration of 20% sucrose for 48 h and for date syrup was 25%
for 48 h. The results show that an increase in fermentation time
caused a decrease in the levan production at all concentrations of date
syrup tested. Under these conditions after 48 h in sucrose medium,
levan production reached 48.9 g/L and for date syrup reached 10.48
g/L . The effect of pH on the yield of the purified levan was examined
and the optimum pH for levan production was determined to be 6.0.
Levan was composed mainly of fructose residues when analyzed by
TLC and FT-IR spectroscopy. Date syrup is a cheap substrate widely
available in Iran and has potential for levan production. The thermal
stability of levan was assessed by Thermo Gravimetric Analysis
(TGA) that revealed the onset of decomposition near to 49°C for the
levan produced from sucrose and 51°C for the levan from date syrup.
DSC results showed a single Tg at 98°C for levan produced from
sucrose and 206 °C for levan from date syrup.
Abstract: This paper provides an in-depth study of Wireless
Sensor Network (WSN) application to monitor and control the
swiftlet habitat. A set of system design is designed and developed
that includes the hardware design of the nodes, Graphical User
Interface (GUI) software, sensor network, and interconnectivity for
remote data access and management. System architecture is proposed
to address the requirements for habitat monitoring. Such applicationdriven
design provides and identify important areas of further work
in data sampling, communications and networking. For this
monitoring system, a sensor node (MTS400), IRIS and Micaz radio
transceivers, and a USB interfaced gateway base station of Crossbow
(Xbow) Technology WSN are employed. The GUI of this monitoring
system is written using a Laboratory Virtual Instrumentation
Engineering Workbench (LabVIEW) along with Xbow Technology
drivers provided by National Instrument. As a result, this monitoring
system is capable of collecting data and presents it in both tables and
waveform charts for further analysis. This system is also able to send
notification message by email provided Internet connectivity is
available whenever changes on habitat at remote sites (swiftlet farms)
occur. Other functions that have been implemented in this system
are the database system for record and management purposes; remote
access through the internet using LogMeIn software. Finally, this
research draws a conclusion that a WSN for monitoring swiftlet
habitat can be effectively used to monitor and manage swiftlet
farming industry in Sarawak.
Abstract: Non-viral gene carriers composed of biodegradable
polymers or lipids have been considered as a safer alternative for gene
carriers over viral vectors. We have developed multi-functional
nano-micelles for both drug and gene delivery application.
Polyethyleneimine (PEI) was modified by grafting stearic acid (SA)
and formulated to polymeric micelles (PEI-SA) with positive surface
charge for gene and drug delivery. Our results showed that PEI-SA
micelles provided high siRNA binding efficiency. In addition, siRNA
delivered by PEI-SA carriers also demonstrated significantly high
cellular uptake even in the presence of serum proteins. The
post-transcriptional gene silencing efficiency was greatly improved by
the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic
structure of PEI-SA micelles provided advantages for multifunctional
tasks; where the hydrophilic shell modified with cationic charges can
electrostatically interact with DNA or siRNA, and the hydrophobic
core can serve as payloads for hydrophobic drugs, making it a
promising multifunctional vehicle for both genetic and chemotherapy
application.
Abstract: Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: We aimed to investigate how can target and optimize
pulmonary delivery distribution by changing physicochemical
characteristics of instilled liquid.Therefore, we created a new liquids
group:
a. eligible for desired distribution within lung because of
assorted physicochemical characteristics
b. capable of being augmented with a broad range of
chemicals inertly
c. no interference on respiratory function
d. compatible with airway surface liquid
We developed forty types of new liquid,were composed of
Carboxymethylcellulose sodium,Glycerin and different types of
Polysorbates.Viscosity was measured using a Programmable
Rheometer and surface tension by KRUSS Tensiometer.We
subsequently examined the liquids and delivery protocols by simple
and branched glass capillary tube models of airways.Eventually,we
explored pulmonary distribution of liquids being augmented with
technetium-99m in mechanically ventilated rabbits.We used a single
head large field of view gamma camera.Kinematic viscosity between
0.265Stokes and 0.289Stokes,density between 1g/cm3 and 1.5g/cm3
and surface tension between 25dyn/cm and 35dyn/cm were the most
acceptable.
Abstract: In recent years, scanning probe atomic force
microscopy SPM AFM has gained acceptance over a wide spectrum
of research and science applications. Most fields focuses on physical,
chemical, biological while less attention is devoted to manufacturing
and machining aspects. The purpose of the current study is to assess
the possible implementation of the SPM AFM features and its
NanoScope software in general machining applications with special
attention to the tribological aspects of cutting tool. The surface
morphology of coated and uncoated as-received carbide inserts is
examined, analyzed, and characterized through the determination of
the appropriate scanning setting, the suitable data type imaging
techniques and the most representative data analysis parameters
using the MultiMode SPM AFM in contact mode. The NanoScope
operating software is used to capture realtime three data types
images: “Height", “Deflection" and “Friction". Three scan sizes are
independently performed: 2, 6, and 12 μm with a 2.5 μm vertical
range (Z). Offline mode analysis includes the determination of three
functional topographical parameters: surface “Roughness", power
spectral density “PSD" and “Section". The 12 μm scan size in
association with “Height" imaging is found efficient to capture every
tiny features and tribological aspects of the examined surface. Also,
“Friction" analysis is found to produce a comprehensive explanation
about the lateral characteristics of the scanned surface. Configuration
of many surface defects and drawbacks has been precisely detected
and analyzed.
Abstract: In this paper, to resolve the problem of existing
schemes, an alternative fast handover Proxy Mobile IPv6 (PMIPv6)
scheme using the IEEE 802.21 Media Independent Handover (MIH)
function is proposed for heterogeneous wireless networks. The proposed
scheme comes to support fast handover for the mobile node
(MN) irrespective of the presence or absence of MIH functionality
as well as L3 mobility functionality, whereas the MN in existing
schemes has to implement MIH functionality. That is, the proposed
scheme does not require the MN to be involved in MIH related signaling
required for handover procedure. The base station (BS) with MIH
functionality performs handover on behalf of the MN. Therefore, the
proposed scheme can reduce burden and power consumption of MNs
with limited resource and battery power since MNs are not required
to be involved for the handover procedure. In addition, the proposed
scheme can reduce considerably traffic overhead over wireless links
between MN and BS since signaling messages are reduced.
Abstract: This study presents a new approach based on Tanaka's
fuzzy linear regression (FLP) algorithm to solve well-known power
system economic load dispatch problem (ELD). Tanaka's fuzzy linear
regression (FLP) formulation will be employed to compute the
optimal solution of optimization problem after linearization. The
unknowns are expressed as fuzzy numbers with a triangular
membership function that has middle and spread value reflected on
the unknowns. The proposed fuzzy model is formulated as a linear
optimization problem, where the objective is to minimize the sum of
the spread of the unknowns, subject to double inequality constraints.
Linear programming technique is employed to obtain the middle and
the symmetric spread for every unknown (power generation level).
Simulation results of the proposed approach will be compared with
those reported in literature.
Abstract: The proposed system identifies the species of the wood
using the textural features present in its barks. Each species of a wood
has its own unique patterns in its bark, which enabled the proposed
system to identify it accurately. Automatic wood recognition system
has not yet been well established mainly due to lack of research in this
area and the difficulty in obtaining the wood database. In our work, a
wood recognition system has been designed based on pre-processing
techniques, feature extraction and by correlating the features of those
wood species for their classification. Texture classification is a problem
that has been studied and tested using different methods due to its
valuable usage in various pattern recognition problems, such as wood
recognition, rock classification. The most popular technique used
for the textural classification is Gray-level Co-occurrence Matrices
(GLCM). The features from the enhanced images are thus extracted
using the GLCM is correlated, which determines the classification
between the various wood species. The result thus obtained shows a
high rate of recognition accuracy proving that the techniques used in
suitable to be implemented for commercial purposes.
Abstract: Obfuscation is a low cost software protection
methodology to avoid reverse engineering and re engineering of
applications. Source code obfuscation aims in obscuring the source
code to hide the functionality of the codes. This paper proposes an
Array data transformation in order to obfuscate the source code
which uses arrays. The applications using the proposed data
structures force the programmer to obscure the logic manually. It
makes the developed obscured codes hard to reverse engineer and
also protects the functionality of the codes.
Abstract: This paper describes an optimal approach for feature
subset selection to classify the leaves based on Genetic Algorithm
(GA) and Kernel Based Principle Component Analysis (KPCA). Due
to high complexity in the selection of the optimal features, the
classification has become a critical task to analyse the leaf image
data. Initially the shape, texture and colour features are extracted
from the leaf images. These extracted features are optimized through
the separate functioning of GA and KPCA. This approach performs
an intersection operation over the subsets obtained from the
optimization process. Finally, the most common matching subset is
forwarded to train the Support Vector Machine (SVM). Our
experimental results successfully prove that the application of GA
and KPCA for feature subset selection using SVM as a classifier is
computationally effective and improves the accuracy of the classifier.