Abstract: To measure the thickness of the subcutaneous adipose
tissue layer, a non-invasive optical measurement system (λ=1300 nm)
is introduced. Animal and human subjects are used for the
experiments. The results of human subjects are compared with the data
of ultrasound device measurements, and a high correlation (r=0.94 for
n=11) is observed. There are two modes in the corresponding signals
measured by the optical system, which can be explained by
two-layered and three-layered tissue models. If the target tissue is
thinner than the critical thickness, detected data using diffuse
reflectance method follow the three-layered tissue model, so the data
increase as the thickness increases. On the other hand, if the target
tissue is thicker than the critical thickness, the data follow the
two-layered tissue model, so they decrease as the thickness increases.
Abstract: The purpose of this paper is to provide an overview on methodological aspects of the information technology outsourcing (ITO) surveys, in an attempt to improve the data quality and reporting in survey research. It is based on a review of thirty articles on ITO surveys and focuses on two commonly explored dimensions of ITO, namely what are outsourced and why should there be ITO. This study highlights weaknesses in ITO surveys including lack of a clear definition of population, lack of information regarding the sampling method used, not citing the response rate, no information pertaining to pilot testing of survey instrument and absence of information on internal validity in the use or reporting of surveys. This study represents an attempt with a limited scope to point to shortfalls in the use survey methodology in ITO, and thus raise awareness among researchers in enhancing the reliability of survey findings.
Abstract: In this paper we use quintic non-polynomial
spline functions to develop numerical methods for approximation
to the solution of a system of fourth-order boundaryvalue
problems associated with obstacle, unilateral and contact
problems. The convergence analysis of the methods has been
discussed and shown that the given approximations are better
than collocation and finite difference methods. Numerical
examples are presented to illustrate the applications of these
methods, and to compare the computed results with other
known methods.
Abstract: Data compression is used operationally to reduce bandwidth and storage requirements. An efficient method for achieving lossless weather radar data compression is presented. The characteristics of the data are taken into account and the optical linear prediction is used for the PPI images in the weather radar data in the proposed method. The next PPI image is identical to the current one and a dramatic reduction in source entropy is achieved by using the prediction algorithm. Some lossless compression methods are used to compress the predicted data. Experimental results show that for the weather radar data, the method proposed in this paper outperforms the other methods.
Abstract: This paper presents a design method of self-tuning
Quantitative Feedback Theory (QFT) by using improved deadbeat
control algorithm. QFT is a technique to achieve robust control with
pre-defined specifications whereas deadbeat is an algorithm that
could bring the output to steady state with minimum step size.
Nevertheless, usually there are large peaks in the deadbeat response.
By integrating QFT specifications into deadbeat algorithm, the large
peaks could be tolerated. On the other hand, emerging QFT with
adaptive element will produce a robust controller with wider
coverage of uncertainty. By combining QFT-based deadbeat
algorithm and adaptive element, superior controller that is called selftuning
QFT-based deadbeat controller could be achieved. The output
response that is fast, robust and adaptive is expected. Using a grain
dryer plant model as a pilot case-study, the performance of the
proposed method has been evaluated and analyzed. Grain drying
process is very complex with highly nonlinear behaviour, long delay,
affected by environmental changes and affected by disturbances.
Performance comparisons have been performed between the
proposed self-tuning QFT-based deadbeat, standard QFT and
standard dead-beat controllers. The efficiency of the self-tuning QFTbased
dead-beat controller has been proven from the tests results in
terms of controller’s parameters are updated online, less percentage
of overshoot and settling time especially when there are variations in
the plant.
Abstract: The present study has been taken to explore the
screening of in vitro antimicrobial activities of D-galactose-binding
sponge lectin (HOL-30). HOL-30 was purified from the marine
demosponge Halichondria okadai by affinity chromatography. The
molecular mass of the lectin was determined to be 30 kDa with a
single polypeptide by SDS-PAGE under non-reducing and reducing
conditions. HOL-30 agglutinated trypsinized and glutaraldehydefixed
rabbit and human erythrocytes with preference for type O
erythrocytes. The lectin was subjected to evaluation for inhibition of
microbial growth by the disc diffusion method against eleven human
pathogenic gram-positive and gram-negative bacteria. The lectin
exhibited strong antibacterial activity against gram-positive bacteria,
such as Bacillus megaterium and Bacillus subtilis. However, it did
not affect against gram-negative bacteria such as Salmonella typhi
and Escherichia coli. The largest zone of inhibition was recorded of
Bacillus megaterium (12 in diameter) and Bacillus subtilis (10 mm in
diameter) at a concentration of the lectin (250 μg/disc). On the other
hand, the antifungal activity of the lectin was investigated against six
phytopathogenic fungi based on food poisoning technique. The lectin
has shown maximum inhibition (22.83%) of mycelial growth of
Botrydiplodia theobromae at a concentration of 100 μg/mL media.
These findings indicate that the lectin may be of importance to
clinical microbiology and have therapeutic applications.
Abstract: This paper presents a system for tracking the movement of laparoscopic instruments which is based on an orthogonal system of webcams and video image processing. The movements are captured with two webcams placed orthogonally inside of the physical trainer. On the image, the instruments were detected by using color markers placed on the distal tip of each instrument. The 3D position of the tip of the instrument within the work space was obtained by linear triangulation method. Preliminary results showed linearity and repeatability in the motion tracking with a resolution of 0.616 mm in each axis; the accuracy of the system showed a 3D instrument positioning error of 1.009 ± 0.101 mm. This tool is a portable and low-cost alternative to traditional tracking devices and a trustable method for the objective evaluation of the surgeon’s surgical skills.
Abstract: Evaluation of contact pressure, surface and
subsurface contact stresses are essential to know the functional
response of surface coatings and the contact behavior mainly depends
on surface roughness, material property, thickness of layer and the
manner of loading. Contact parameter evaluation of real rough
surface contacts mostly relies on statistical single asperity contact
approaches. In this work, a three dimensional layered solid rough
surface in contact with a rigid flat is modeled and analyzed using
finite element method. The rough surface of layered solid is
generated by FFT approach. The generated rough surface is exported
to a finite element method based ANSYS package through which the
bottom up solid modeling is employed to create a deformable solid
model with a layered solid rough surface on top. The discretization
and contact analysis are carried by using the same ANSYS package.
The elastic, elastoplastic and plastic deformations are continuous in
the present finite element method unlike many other contact models.
The Young-s modulus to yield strength ratio of layer is varied in the
present work to observe the contact parameters effect while keeping
the surface roughness and substrate material properties as constant.
The contacting asperities attain elastic, elastoplastic and plastic states
with their continuity and asperity interaction phenomena is inherently
included. The resultant contact parameters show that neighboring
asperity interaction and the Young-s modulus to yield strength ratio
of layer influence the bulk deformation consequently affect the
interface strength.
Abstract: This paper examines and compares several of the most common real time methods. These methods are CORE, YSM, MASCOT, JSD, DARTS, RTSAD, ADARTS, CODARTS, HOOD, HRT-HOOD, ROOM, UML, UML-RT. The methods are compared using attributes like i) usability, ii) compositionality and iii) proper RT notations available. Finally some comparison results are given and discussed.
Abstract: This paper presents the optimal design and development
of an axial flux motor for blood pump application. With the design
objective of maximizing the motor efficiency and torque, different
topologies of AFPM machine has been examined. Selection of
optimal magnet fraction, Halbach arrangement of rotor magnets and
the use of Soft Magnetic Composite (SMC) material for the stator
core results in a novel motor with improved efficiency and torque
profile. The results of the 3D Finite element analysis for the novel
motor have been shown.
Abstract: This paper presents a method for determining the
uniaxial tensile properties such as Young-s modulus, yield strength
and the flow behaviour of a material in a virtually non-destructive
manner. To achieve this, a new dumb-bell shaped miniature
specimen has been designed. This helps in avoiding the removal of
large size material samples from the in-service component for the
evaluation of current material properties. The proposed miniature
specimen has an advantage in finite element modelling with respect
to computational time and memory space. Test fixtures have been
developed to enable the tension tests on the miniature specimen in a
testing machine. The studies have been conducted in a chromium
(H11) steel and an aluminum alloy (AR66). The output from the
miniature test viz. load-elongation diagram is obtained and the finite
element simulation of the test is carried out using a 2D plane stress
analysis. The results are compared with the experimental results. It is
observed that the results from the finite element simulation
corroborate well with the miniature test results. The approach seems
to have potential to predict the mechanical properties of the
materials, which could be used in remaining life estimation of the
various in-service structures.
Abstract: A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.
Abstract: Based on Traub-s methods for solving nonlinear
equation f(x) = 0, we develop two families of third-order
methods for solving system of nonlinear equations F(x) = 0. The
families include well-known existing methods as special cases.
The stability is corroborated by numerical results. Comparison
with well-known methods shows that the present methods are
robust. These higher order methods may be very useful in the
numerical applications requiring high precision in their computations
because these methods yield a clear reduction in number of iterations.
Abstract: In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
Abstract: Ethanol has been known for a long time, being
perhaps the oldest product obtained through traditional biotechnology
fermentation. Agriculture waste as substrate in fermentation is vastly
discussed as alternative to replace edible food and utilization of
organic material. Pineapple peel, highly potential source as substrate
is a by-product of the pineapple processing industry. Bio-ethanol
from pineapple (Ananas comosus) peel extract was carried out by
controlling fermentation without any treatment. Saccharomyces
ellipsoides was used as inoculum in this fermentation process as it is
naturally found at the pineapple skin. In this study, the capability of
Response Surface Methodology (RSM) for optimization of ethanol
production from pineapple peel extract using Saccharomyces
ellipsoideus in batch fermentation process was investigated. Effect of
five test variables in a defined range of inoculum concentration 6-
14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix),
temperature (24-32°C) and time of incubation (30-54 hrs) on the
ethanol production were evaluated. Data obtained from experiment
were analyzed with RSM of MINITAB Software (Version 15)
whereby optimum ethanol concentration of 8.637% (v/v) was
determined. The optimum condition of 14% (v/v) inoculum
concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The
significant regression equation or model at the 5% level with
correlation value of 99.96% was also obtained.
Abstract: In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefaces
Abstract: The main goal of this paper is to establish a
methodology for testing and optimizing GPRS performance over
Libya GSM network as well as to propose a suitable optimization
technique to improve performance. Some measurements of
download, upload, throughput, round-trip time, reliability, handover,
security enhancement and packet loss over a GPRS access network
were carried out. Measured values are compared to the theoretical
values that could be calculated beforehand. This data should be
processed and delivered by the server across the wireless network to
the client. The client on the fly takes those pieces of the data and
process immediately. Also, we illustrate the results by describing the
main parameters that affect the quality of service. Finally, Libya-s
two mobile operators, Libyana Mobile Phone and Al-Madar al-
Jadeed Company are selected as a case study to validate our
methodology.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).
Abstract: Using the animations video of teaching materials is an
effective learning method. However, we thought that more effective learning method is to produce the teaching video by learners
themselves. The learners who act as the producer must learn and understand well to produce and present video of teaching materials to
others. The purpose of this study is to propose the project based learning (PBL) technique by co-producing video of IT (information
technology) teaching materials. We used the T2V player to produce
the video based on TVML a TV program description language. By
proposed method, we have assigned the learners to produce the
animations video for “National Examination for Information
Processing Technicians (IPA examination)" in Japan, in order to get
them learns various knowledge and skill on IT field. Experimental
result showed that learning effect has occurred at the video production
process that useful for IT personnel resources development.
Abstract: The fuzzy technique is an operator introduced in order
to simulate at a mathematical level the compensatory behavior in
process of decision making or subjective evaluation. The following
paper introduces such operators on hand of computer vision
application.
In this paper a novel method based on fuzzy logic reasoning
strategy is proposed for edge detection in digital images without
determining the threshold value. The proposed approach begins by
segmenting the images into regions using floating 3x3 binary matrix.
The edge pixels are mapped to a range of values distinct from each
other. The robustness of the proposed method results for different
captured images are compared to those obtained with the linear Sobel
operator. It is gave a permanent effect in the lines smoothness and
straightness for the straight lines and good roundness for the curved
lines. In the same time the corners get sharper and can be defined
easily.