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: Biofuels, like biobutanol, have been recognized for
being renewable and sustainable fuels which can be produced from
lignocellulosic biomass. To convert lignocellulosic biomass to
biofuel, pretreatment process is an important step to remove
hemicelluloses and lignin to improve enzymatic hydrolysis. Dilute
acid pretreatment has been successful developed for pretreatment of
corncobs and the optimum conditions of dilute sulfuric and
phosphoric acid pretreatment were obtained at 120 °C for 5 min with
15:1 liquid to solid ratio and 140 °C for 10 min with 10:1 liquid to
solid ratio, respectively. The result shows that both of acid
pretreatments gave the content of total sugar approximately 34–35
g/l. In case of inhibitor content (furfural), phosphoric acid
pretreatment gives higher than sulfuric acid pretreatment.
Characterizations of corncobs after pretreatment indicate that both of
acid pretreatments can improve enzymatic accessibility and the better
results present in corncobs pretreated with sulfuric acid in term of
surface area, crystallinity, and composition analysis.
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: 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: 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: 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: 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.
Abstract: In this paper is presented a Geographic Information System (GIS) approach in order to qualify and monitor the broadband lines in efficient way. The methodology used for interpolation is the Delaunay Triangular Irregular Network (TIN). This method is applied for a case study in ISP Greece monitoring 120,000 broadband lines.
Abstract: In this paper, a new approach based on the extent of
friendship between the nodes is proposed which makes the nodes to
co-operate in an ad hoc environment. The extended DSR protocol is
tested under different scenarios by varying the number of malicious
nodes and node moving speed. It is also tested varying the number of
nodes in simulation used. The result indicates the achieved
throughput by extended DSR is greater than the standard DSR and
indicates the percentage of malicious drops over total drops are less
in the case of extended DSR than the standard DSR.
Abstract: Speedups from mapping four real-life DSP
applications on an embedded system-on-chip that couples coarsegrained
reconfigurable logic with an instruction-set processor are
presented. The reconfigurable logic is realized by a 2-Dimensional
Array of Processing Elements. A design flow for improving
application-s performance is proposed. Critical software parts, called
kernels, are accelerated on the Coarse-Grained Reconfigurable
Array. The kernels are detected by profiling the source code. For
mapping the detected kernels on the reconfigurable logic a prioritybased
mapping algorithm has been developed. Two 4x4 array
architectures, which differ in their interconnection structure among
the Processing Elements, are considered. The experiments for eight
different instances of a generic system show that important overall
application speedups have been reported for the four applications.
The performance improvements range from 1.86 to 3.67, with an
average value of 2.53, compared with an all-software execution.
These speedups are quite close to the maximum theoretical speedups
imposed by Amdahl-s law.
Abstract: Concerns about low levels of children-s physical activity and motor skill development, prompted the Ministry of Education to trial a physical activity pilot project (PAPP) in 16 New Zealand primary schools. The project comprised professional development and training in physical education for lead teachers and introduced four physical activity coordinators to liaise with and increase physical activity opportunities in the pilot schools. A survey of generalist teachers (128 baseline, 155 post-intervention) from these schools looked at timetabled physical activity sessions and issues related to teaching physical education. The authors calculated means and standard deviations of data relating to timetabled PE sessions and used a one-way analysis of variance to determine significant differences. Results indicated time devoted to physical activity related subjects significantly increased over the course of the intervention. Teacher-s reported improved confidence and competence, which resulted in an improvement in quality physical education delivered more often.
Abstract: Facility Layout Problem (FLP) is one of the essential
problems of several types of manufacturing and service sector. It is
an optimization problem on which the main objective is to obtain the
efficient locations, arrangement and order of the facilities. In the
literature, there are numerous facility layout problem research
presented and have used meta-heuristic approaches to achieve
optimal facility layout design. This paper presented genetic algorithm
to solve facility layout problem; to minimize total cost function. The
performance of the proposed approach was verified and compared
using problems in the literature.
Abstract: The aim of this paper to characterize a larger set of
wavelet functions for implementation in a still image compression
system using SPIHT algorithm. This paper discusses important
features of wavelet functions and filters used in sub band coding to
convert image into wavelet coefficients in MATLAB. Image quality
is measured objectively using peak signal to noise ratio (PSNR) and
its variation with bit rate (bpp). The effect of different parameters is
studied on different wavelet functions. Our results provide a good
reference for application designers of wavelet based coder.
Abstract: Independent component analysis (ICA) is a computational method for finding underlying signals or components from multivariate statistical data. The ICA method has been successfully applied in many fields, e.g. in vision research, brain imaging, geological signals and telecommunications. In this paper, we apply the ICA method to an analysis of mass spectra of oligomeric species emerged from aluminium sulphate. Mass spectra are typically complex, because they are linear combinations of spectra from different types of oligomeric species. The results show that ICA can decomposite the spectral components for useful information. This information is essential in developing coagulation phases of water treatment processes.
Abstract: The Block Sorting problem is to sort a given
permutation moving blocks. A block is defined as a substring
of the given permutation, which is also a substring of the
identity permutation. Block Sorting has been proved to be
NP-Hard. Until now two different 2-Approximation algorithms
have been presented for block sorting. These are the best known
algorithms for Block Sorting till date. In this work we present
a different characterization of Block Sorting in terms of a
transposition cycle graph. Then we suggest a heuristic,
which we show to exhibit a 2-approximation performance
guarantee for most permutations.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.