Abstract: In text categorization problem the most used method
for documents representation is based on words frequency vectors
called VSM (Vector Space Model). This representation is based only
on words from documents and in this case loses any “word context"
information found in the document. In this article we make a
comparison between the classical method of document representation
and a method called Suffix Tree Document Model (STDM) that is
based on representing documents in the Suffix Tree format. For the
STDM model we proposed a new approach for documents
representation and a new formula for computing the similarity
between two documents. Thus we propose to build the suffix tree
only for any two documents at a time. This approach is faster, it has
lower memory consumption and use entire document representation
without using methods for disposing nodes. Also for this method is
proposed a formula for computing the similarity between documents,
which improves substantially the clustering quality. This
representation method was validated using HAC - Hierarchical
Agglomerative Clustering. In this context we experiment also the
stemming influence in the document preprocessing step and highlight
the difference between similarity or dissimilarity measures to find
“closer" documents.
Abstract: The use of polypropylene mesh devices for Pelvic
Organ Prolapse (POP) spread rapidly during the last decade, yet our
knowledge of the mesh-tissue interaction is far from complete. We
aimed to perform a thorough pathological examination of explanted
POP meshes and describe findings that may explain mechanisms of
complications resulting in product excision. We report a spectrum of
important findings, including nerve ingrowth, mesh deformation,
involvement of detrusor muscle with neural ganglia, and
polypropylene degradation. Analysis of these findings may improve
and guide future treatment strategies.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.
Abstract: Partitions can play a significant role in minimising cochannel
interference of Wireless LANs by attenuating signals across
room boundaries. This could pave the way towards higher density
deployments in home and office environments through spatial
channel reuse. Yet, due to protocol limitations, the latest incantation
of IEEE 802.11 standard is still unable to take advantage of this fact:
Despite having clearly adequate Signal to Interference Ratio (SIR)
over co-channel neighbouring networks in other rooms, its goodput
falls significantly lower than its maximum in the absence of cochannel
interferers. In this paper, we describe how this situation can
be remedied via modest modifications to the standard.
Abstract: The purpose of this study is to investigate the
efficiency of a double-layer roof in collecting solar energy as an
application to the areas such as raising high-end temperature of
organic Rankine cycle (ORC). The by-product of the solar roof is to
reduce building air-conditioning loads. The experimental apparatus
are arranged to evaluate the effects of the solar roof in absorbing solar
energy. The flow channel is basically formed by an aluminum plate on
top of a plywood plate. The geometric configurations in which the
effects of absorbing energy is analyzed include: a bare uncovered
aluminum plate, a glass-covered aluminum plate, a
glass-covered/black-painted aluminum plate, a plate with variable
lengths, a flow channel with stuffed material (in an attempt on
enhancement of heat conduction), and a flow channel with variable
slanted angles. The experimental results show that the efficiency of
energy collection varies from 0.6 % to 11 % for the geometric
configurations mentioned above. An additional study is carried out
using CFD simulation to investigate the effects of fins on the
aluminum plate. It shows that due to vastly enhanced heat conduction,
the efficiency can reach ~23 % if 50 fins are installed on the aluminum
plate. The study shows that a double-layer roof can efficiently absorb
solar energy and substantially reduce building air-conditioning
loads. On the high end of an organic Rankine cycle, a solar pond is
used to replace the warm surface water of the sea as OTEC (ocean
thermal energy conversion) is the driving energy for the ORC. The
energy collected from the double-layered solar roof can be pumped
into the pond and raise the pond temperature as the pond surface area is
equivalently increased by nearly one-fourth of the total area of the
double-layer solar roof. The effect of raising solar pond temperature is
especially prominent if the double-layer solar roofs are installed in a
community area.
Abstract: The fast growing accessibility and capability of emerging technologies have fashioned enormous possibilities of designing, developing and implementing innovative teaching methods in the classroom. The global technological scenario has paved the way to new pedagogies in teaching-learning process focusing on technology based learning environment and its impact on student achievement. The present experimental study was conducted to determine the effectiveness of technology based learning environment on student achievement in English as a foreign language. The sample of the study was 90 students of 10th grade of a public school located in Islamabad. A pretest- posttest equivalent group design was used to compare the achievement of the two groups. A Pretest and A posttest containing 50 items each from English textbook were developed and administered. The collected data were statistically analyzed. The results showed that there was a significant difference between the mean scores of Experimental group and the Control group. The performance of Experimental group was better on posttest scores that indicted that teaching through technology based learning environment enhanced the achievement level of the students. On the basis of the results, it was recommended that teaching and learning through information and communication technologies may be adopted to enhance the language learning capability of the students.
Abstract: In this paper we consider a nonlinear feedback control
called augmented automatic choosing control (AACC) using the
gradient optimization automatic choosing functions for nonlinear
systems. Constant terms which arise from sectionwise linearization
of a given nonlinear system are treated as coefficients of a stable
zero dynamics. Parameters included in the control are suboptimally
selected by expanding a stable region in the sense of Lyapunov
with the aid of the genetic algorithm. This approach is applied to
a field excitation control problem of power system to demonstrate
the splendidness of the AACC. Simulation results show that the new
controller can improve performance remarkably well.
Abstract: This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
Abstract: Study was conducted to determine the concentration of
copper, cadmium, lead and zinc in Cabomba furcata that found
abundance in Lake Chini. This aquatic plant was collected randomly
within the lake for heavy metal determination. Water quality
measurement was undertaken in situ for temperature, pH,
conductivity and dissolved oksigen using portable multi sensor probe
YSI model 556. The C. furcata was digested using wet digestion
method and heavy metal concentrations were analysed using Atomic
Absorption Spectrometer (AAS) Perkin Elmer 4100B (flame
method). Result of water quality classify Lake Chini between class II
to class III using Malaysian Water Quality Standard. According to
this standard, Lake Chini has moderate quality, which normal for
natural lake. Heavy metal concentrations in C.furcata were low and
found to be lower than the critical toxic value in aquatic plants. Oneway
ANOVA test indicated the heavy metal concentrations in
C.furcata were significantly differ between sampling location. Water
quality and heavy metal concentrations indicates that Lake Chini was
not receives anthropogenic load from nearby activities.
Abstract: In this paper we present a new approach to deal with
image segmentation. The fact that a single segmentation result do not
generally allow a higher level process to take into account all the
elements included in the image has motivated the consideration of
image segmentation as a multiobjective optimization problem. The
proposed algorithm adopts a split/merge strategy that uses the result
of the k-means algorithm as input for a quantum evolutionary
algorithm to establish a set of non-dominated solutions. The
evaluation is made simultaneously according to two distinct features:
intra-region homogeneity and inter-region heterogeneity. The
experimentation of the new approach on natural images has proved
its efficiency and usefulness.
Abstract: As mobile service's subscriber is increasing; mobile
contents services are getting more and more variables. So, mobile
contents development needs not only contents design but also
guideline for just mobile. And when mobile contents are developed, it
is important to pass the limit and restriction of the mobile. The
restrictions of mobile are small browser and screen size, limited
download size and uncomfortable navigation. So each contents of
mobile guideline will be presented for user's usability, easy of
development and consistency of rule. This paper will be proposed
methodology which is each contents of mobile guideline. Mobile web
will be developed by mobile guideline which I proposed.
Abstract: The present article comprises a theoretical study of
structures Performat radical (HCO3) with H2O molecule. We make
use of ab initio quantum chemical methods. Unrestricted Hartee-Fock
(UHF) with the basis set6-311+g(2df,2p) and density functional
theory (B3LYP) with the basis set 6-311+g(2df,2p) and also we done
atoms in molecules (AIM) theory for them. We have found four
stable geometries the PerformatRadical(HCO3) with H2O.
Abstract: Partial oxidation (POX) of light hydrocarbons (e.g.
methane) is occurred in the first part of the autothermal reformer
(ATR). The results of the detailed modeling of the reformer based on
the thermodynamic model of the POX and 1D heterogeneous
catalytic model for the fixed bed section are considered here.
According to the results, the overall performance of the ATR can be
improved by changing the important feed parameters.
Abstract: Cellular communication is being widely used by all
over the world. The users of handsets are increasing due to the
request from marketing sector. The important aspect that has to be
touch in this paper is about the security system of cellular
communication. It is important to provide users with a secure channel
for communication. A brief description of the new GSM cellular
network architecture will be provided. Limitations of cellular
networks, their security issues and the different types of attacks will
be discussed. The paper will go over some new security mechanisms
that have been proposed by researchers. Overall, this paper clarifies
the security system or services of cellular communication using
GSM. Three Malaysian Communication Companies were taken as
Case study in this paper.
Abstract: Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Abstract: Attitude Determination (AD) of a spacecraft using the
phase measurements of the Global Navigation Satellite System
(GNSS) is an active area of research. Various attitude determination
algorithms have been developed in yester years for spacecrafts using
different sensors but the last two decades have witnessed a
phenomenal increase in research related with GPS receivers as a
stand-alone sensor for determining the attitude of satellite using the
phase measurements of the signals from GNSS. The GNSS-based
Attitude determination algorithms have been experimented in many
real missions. The problem of AD algorithms using GNSS phase
measurements has two important parts; the ambiguity resolution and
the determining of attitude. Ambiguity resolution is the widely
addressed topic in literature for implementing the AD algorithm
using GNSS phase measurements for achieving the accuracy of
millimeter level. This paper broadly overviews the different
techniques for resolving the integer ambiguities encountered in AD
using GNSS phase measurements.
Abstract: System testing is actually done to the entire system
against the Functional Requirement Specification and/or the System
Requirement Specification. Moreover, it is an investigatory testing
phase, where the focus is to have almost a destructive attitude and
test not only the design, but also the behavior and even the believed
expectations of the customer. It is also intended to test up to and
beyond the bounds defined in the software/hardware requirements
specifications. In Motorola®, Automated Testing is one of the testing
methodologies uses by GSG-iSGT (Global Software Group - iDEN
TM
Subcriber Group-Test) to increase the testing volume, productivity
and reduce test cycle-time in iDEN
TM
phones testing. Testing is able
to produce more robust products before release to the market. In this
paper, iHopper is proposed as a tool to perform stress test on iDEN
TM
phonse. We will discuss the value that automation has brought to
iDEN
TM
Phone testing such as improving software quality in the
iDEN
TM
phone together with some metrics. We will also look into
the advantages of the proposed system and some discussion of the
future work as well.
Abstract: Aurein 1.2 is a 13-residue amphipathic peptide with antibacterial and anticancer activity. Aurein1.2 and its retro analog were synthesized to study the activity of the peptides in relation to their structure. The antibacterial test result showed the retro-analog is inactive. The secondary structural analysis by CD spectra indicated that both of the peptides at TFE/Water adopt alpha-helical conformation. MD simulation was performed on aurein 1.2 and retro-analog in water and TFE in order to analyse the factors that are involved in the activity difference between retro and the native peptide. The simulation results are discussed and validated in the light of experimental data from the CD experiment. Both of the peptides showed a relatively similar pattern for their hydrophobicity, hydrophilicity, solvent accessible surfaces, and solvent accessible hydrophobic surfaces. However, they showed different in directions of dipole moment of peptides. Also, Our results further indicate that the reversion of the amino acid sequence affects flexibility .The data also showed that factors causing structural rigidity may decrease the activity. Consequently, our finding suggests that in the case of sequence-reversed peptide strategy, one has to pay attention to the role of amino acid sequence order in making flexibility and role of dipole moment direction in peptide activity. KeywordsAntimicrobial peptides, retro, molecular dynamic, circular dichroism.
Abstract: A new deployment of the multiple criteria decision
making (MCDM) techniques: the Simple Additive Weighting
(SAW), and the Technique for Order Preference by Similarity to
Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in
this paper. Rather than exclusive reference to mean and variance as in
the traditional mean-variance method, the criteria used in this
demonstration are the first four moments of the portfolio distribution.
Each asset is evaluated based on its marginal impacts to portfolio
higher moments that are characterized by trapezoidal fuzzy numbers.
Then centroid-based defuzzification is applied to convert fuzzy
numbers to the crisp numbers by which SAW and TOPSIS can be
deployed. Experimental results suggest the similar efficiency of these
MCDM approaches to selecting dominant assets for an optimal
portfolio under higher moments. The proposed approaches allow
investors flexibly adjust their risk preferences regarding higher
moments via different schemes adapting to various (from
conservative to risky) kinds of investors. The other significant
advantage is that, compared to the mean-variance analysis, the
portfolio weights obtained by SAW and TOPSIS are consistently
well-diversified.
Abstract: The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.