Abstract: Prediction of bacterial virulent protein sequences can
give assistance to identification and characterization of novel
virulence-associated factors and discover drug/vaccine targets against
proteins indispensable to pathogenicity. Gene Ontology (GO)
annotation which describes functions of genes and gene products as a
controlled vocabulary of terms has been shown effectively for a
variety of tasks such as gene expression study, GO annotation
prediction, protein subcellular localization, etc. In this study, we
propose a sequence-based method Virulent-GO by mining informative
GO terms as features for predicting bacterial virulent proteins.
Each protein in the datasets used by the existing method
VirulentPred is annotated by using BLAST to obtain its homologies
with known accession numbers for retrieving GO terms. After
investigating various popular classifiers using the same five-fold
cross-validation scheme, Virulent-GO using the single kind of GO
term features with an accuracy of 82.5% is slightly better than
VirulentPred with 81.8% using five kinds of sequence-based features.
For the evaluation of independent test, Virulent-GO also yields better
results (82.0%) than VirulentPred (80.7%). When evaluating single
kind of feature with SVM, the GO term feature performs much well,
compared with each of the five kinds of features.
Abstract: In cellular networks, limited availability of resources
has to be tapped to its fullest potential. In view of this aspect, a
sophisticated averaging and voting technique has been discussed in
this paper, wherein the radio resources available are utilized to the
fullest value by taking into consideration, several network and radio
parameters which decide on when the handover has to be made and
thereby reducing the load on Base station .The increase in the load
on the Base station might be due to several unnecessary handover
taking place which can be eliminated by making judicious use of the
radio and network parameters.
Abstract: Emergence of smartphones brings to live the concept
of converged devices with the availability of web amenities. Such
trend also challenges the mobile devices manufactures and service
providers in many aspects, such as security on mobile phones,
complex and long time design flow, as well as higher development
cost. Among these aspects, security on mobile phones is getting more
and more attention. Microkernel based virtualization technology will
play a critical role in addressing these challenges and meeting mobile
market needs and preferences, since virtualization provides essential
isolation for security reasons and it allows multiple operating systems
to run on one processor accelerating development and cutting development
cost. However, virtualization benefits do not come for free.
As an additional software layer, it adds some inevitable virtualization
overhead to the system, which may decrease the system performance.
In this paper we evaluate and analyze the virtualization performance
cost of L4 microkernel based virtualization on a competitive mobile
phone by comparing the L4Linux, a para-virtualized Linux on top of
L4 microkernel, with the native Linux performance using lmbench
and a set of typical mobile phone applications.
Abstract: Zero inflated strict arcsine model is a newly developed
model which is found to be appropriate in modeling overdispersed
count data. In this study, we extend zero inflated strict arcsine model
to zero inflated strict arcsine regression model by taking into
consideration the extra variability caused by extra zeros and
covariates in count data. Maximum likelihood estimation method is
used in estimating the parameters for this zero inflated strict arcsine
regression model.
Abstract: In this paper, we present a simple circuit for
Manchester decoding and without using any complicated or
programmable devices. This circuit can decode 90kbps of transmitted
encoded data; however, greater than this transmission rate can be
decoded if high speed devices were used. We also present a new
method for extracting the embedded clock from Manchester data in
order to use it for serial-to-parallel conversion. All of our
experimental measurements have been done using simulation.
Abstract: The term private equity usually refers to any type of
equity investment in an asset in which the equity is not freely
tradable on a public stock market. Some researchers believe that
private equity contributed to the extent of the crisis and increased
the pace of its spread over the world. We do not agree with this.
On the other hand, we argue that during the economic recession
private equity might become an important source of funds for firms
with special needs (e.g. for firms seeking buyout financing, venture
capital, expansion capital or distress debt financing). However,
over-regulation of private equity in both the European Union and
the US can slow down this specific funding channel to the
economy and deepen credit crunch during global crises.
Abstract: This study proposes a conceptual model and
empirically tests the relationships between customers and librarians
(i.e. tangibles, responsiveness, assurance, reliability and empathy)
with a dependent variable (customer satisfaction) regarding library
services. The SERVQUAL instrument was administered to 100
respondents which comprises of staff and students at a public higher
learning institution in the Federal Territory of Labuan, Malaysia.
They were public university library users. Results revealed that all
service quality dimensions tested were significant and influenced
customer satisfaction of visitors to a public university library.
Assurance is the most important factor that influences customer
satisfaction with the services rendered by the librarian. It is
imperative for the library management to take note that the top five
service attributes that gained greatest attention from library visitors-
perspective includes employee willingness to help customers,
availability of customer representatives online for response to
queries, library staff actively and promptly provide services, signs in
the building are clear and library staff are friendly and courteous.
This study provides valuable results concerning the determinants of
the service quality and customer satisfaction of public university
library services from the users' perspective.
Abstract: Recent trends in building constructions in Libya are
more toward tall (high-rise) building projects. As a consequence, a
better estimation of the lateral loading in the design process is
becoming the focal of a safe and cost effective building industry. Byin-
large, Libya is not considered a potential earthquake prone zone,
making wind is the dominant design lateral loads. Current design
practice in the country estimates wind speeds on a mere random
bases by considering certain factor of safety to the chosen wind
speed. Therefore, a need for a more accurate estimation of wind
speeds in Libya was the motivation behind this study. Records of
wind speed data were collected from 22 metrological stations in
Libya, and were statistically analysed. The analysis of more than four
decades of wind speed records suggests that the country can be
divided into four zones of distinct wind speeds. A computer “survey"
program was manipulated to draw design wind speeds contour map
for the state of Libya.
The paper presents the statistical analysis of Libya-s recorded
wind speed data and proposes design wind speed values for a 50-year
return period that covers the entire country.
Abstract: Fermented cassava flours (lafun) sold in Ogun and Oyo
States of Nigeria were collected from 10 markets for a period of two
months and analysed to determine their safety status. The presence of
trace metals was due to high vehicular movement around the drying
sites and markets. Cyanide and moisture contents of samples were
also determined to assess the adequacy of fermentation and drying.
The result showed that sample OWO was found to have the highest
amount of 16.02±0.12mg/kg cyanide while the lowest was found in
sample OJO with 10.51±0.10mg/kg. The results also indicated that
sample TVE had the highest moisture content of 18.50±0.20% while
sample OWO had the lowest amount of 12.46±0.47%. Copper and
lead levels were found to be highest in TVE with values 28.10mg/kg
and 1.1mg/kg respectively, while sample BTS had the lowest values
of 20.6mg/kg and 0.05mg/kg respectively. High value of cyanide
indicated inadequate fermentation.
Abstract: In this paper, we propose a face recognition algorithm
using AAM and Gabor features. Gabor feature vectors which are well
known to be robust with respect to small variations of shape, scaling,
rotation, distortion, illumination and poses in images are popularly
employed for feature vectors for many object detection and
recognition algorithms. EBGM, which is prominent among face
recognition algorithms employing Gabor feature vectors, requires
localization of facial feature points where Gabor feature vectors are
extracted. However, localization method employed in EBGM is based
on Gabor jet similarity and is sensitive to initial values. Wrong
localization of facial feature points affects face recognition rate. AAM
is known to be successfully applied to localization of facial feature
points. In this paper, we devise a facial feature point localization
method which first roughly estimate facial feature points using AAM
and refine facial feature points using Gabor jet similarity-based facial
feature localization method with initial points set by the rough facial
feature points obtained from AAM, and propose a face recognition
algorithm using the devised localization method for facial feature
localization and Gabor feature vectors. It is observed through
experiments that such a cascaded localization method based on both
AAM and Gabor jet similarity is more robust than the localization
method based on only Gabor jet similarity. Also, it is shown that the
proposed face recognition algorithm using this devised localization
method and Gabor feature vectors performs better than the
conventional face recognition algorithm using Gabor jet
similarity-based localization method and Gabor feature vectors like
EBGM.
Abstract: The so-called all-pass filter circuits are commonly
used in the field of signal processing, control and measurement.
Being connected to capacitive loads, these circuits tend to loose their
stability; therefore the elaborate analysis of their dynamic behavior is
necessary. The compensation methods intending to increase the
stability of such circuits are discussed in this paper, including the socalled
lead-lag compensation technique being treated in detail. For
the dynamic modeling, a two-port network model of the all-pass filter
is being derived. The results of the model analysis show, that
effective lead-lag compensation can be achieved, alone by the
optimization of the circuit parameters; therefore the application of
additional electric components are not needed to fulfill the stability
requirement.
Abstract: This paper presents a computational methodology
based on matrix operations for a computer based solution to the
problem of performance analysis of software reliability models
(SRMs). A set of seven comparison criteria have been formulated to
rank various non-homogenous Poisson process software reliability
models proposed during the past 30 years to estimate software
reliability measures such as the number of remaining faults, software
failure rate, and software reliability. Selection of optimal SRM for
use in a particular case has been an area of interest for researchers in
the field of software reliability. Tools and techniques for software
reliability model selection found in the literature cannot be used with
high level of confidence as they use a limited number of model
selection criteria. A real data set of middle size software project from
published papers has been used for demonstration of matrix method.
The result of this study will be a ranking of SRMs based on the
Permanent value of the criteria matrix formed for each model based
on the comparison criteria. The software reliability model with
highest value of the Permanent is ranked at number – 1 and so on.
Abstract: A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.
Abstract: Manufacturing processes demand tight dimensional
tolerances. The paper concerns a transducer for precise measurement
of displacement, based on a camera containing a linescan chip.
When tests were conducted using a track of black and white stripes
with a 2mm pitch, errors in measuring on individual cycle amounted
to 1.75%, suggesting that a precision of 35 microns is achievable.
Abstract: Multiphase flow transport in porous medium is very common and significant in science and engineering applications. For example, in CO2 Storage and Enhanced Oil Recovery processes, CO2 has to be delivered to the pore spaces in reservoirs and aquifers. CO2 storage and enhance oil recovery are actually displacement processes, in which oil or water is displaced by CO2. This displacement is controlled by pore size, chemical and physical properties of pore surfaces and fluids, and also pore wettability. In this study, a technique was developed to measure the pressure profile for driving gas/liquid to displace water in pores. Through this pressure profile, the impact of pore size on the multiphase flow transport and displacement can be analyzed. The other rig developed can be used to measure the static and dynamic pore wettability and investigate the effects of pore size, surface tension, viscosity and chemical structure of liquids on pore wettability.
Abstract: Most routing protocols (DSR, AODV etc.) that have
been designed for wireless adhoc networks incorporate the broadcasting
operation in their route discovery scheme. Probabilistic broadcasting
techniques have been developed to optimize the broadcast operation
which is otherwise very expensive in terms of the redundancy
and the traffic it generates. In this paper we have explored percolation
theory to gain a different perspective on probabilistic broadcasting
schemes which have been actively researched in the recent years.
This theory has helped us estimate the value of broadcast probability
in a wireless adhoc network as a function of the size of the network.
We also show that, operating at those optimal values of broadcast
probability there is at least 25-30% reduction in packet regeneration
during successful broadcasting.
Abstract: Paper presents simple sixport principle and its frequency bandwidth. The novel multisixport approach is presented with its possibilities, typical parameters and frequency bandwidth. Practical implementation is shown with its measurement parameters and calibration. The bandwidth circa 1:100 is obtained.
Abstract: Complex engineering design problems consist of
numerous factors of varying criticalities. Considering fundamental features of design and inferior details alike will result in an extensive
waste of time and effort. Design parameters should be introduced gradually as appropriate based on their significance relevant to the
problem context. This motivates the representation of design parameters at multiple levels of an abstraction hierarchy. However, developing abstraction hierarchies is an area that is not well
understood. Our research proposes a novel hierarchical abstraction methodology to plan effective engineering designs and processes. It
provides a theoretically sound foundation to represent, abstract and stratify engineering design parameters and tasks according to causality and criticality. The methodology creates abstraction
hierarchies in a recursive and bottom-up approach that guarantees no
backtracking across any of the abstraction levels. The methodology consists of three main phases, representation, abstraction, and layering to multiple hierarchical levels. The effectiveness of the
developed methodology is demonstrated by a design problem.
Abstract: The purpose of this study is to present a non invasive
method for the marginal adaptation evaluation in class V composite
restorations. Standardized class V cavities, prepared in human
extracted teeth, were filled with Premise (Kerr) composite. The
specimens were thermo cycled. The interfaces were examined by
Optical Coherence Tomography method (OCT) combined with the
confocal microscopy and fluorescence. The optical configuration
uses two single mode directional couplers with a superluminiscent
diode as the source at 1300 nm. The scanning procedure is similar to
that used in any confocal microscope, where the fast scanning is enface
(line rate) and the depth scanning is much slower (at the frame
rate). Gaps at the interfaces as well as inside the composite resin
materials were identified. OCT has numerous advantages which
justify its use in vivo as well as in vitro in comparison with
conventional techniques.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.