Abstract: Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techniques on vessel segmentation from 3- D rotational angiography (3DRA) images is investigated and a new technique of segmentation is proposed. This method consists in: preprocessing step of image enhancement, then K-Means (KM), Fuzzy C-Means (FCM) and Expectation Maximization (EM) clustering are used to separate vessel pixels from background and artery pixels from vein pixels when possible. A post processing step of removing false-alarm components is applied before constructing a three-dimensional volume of the vessels. The proposed method was tested on six datasets along with a medical assessment of an expert. Obtained results showed encouraging segmentations.
Abstract: In this research saffron samples were prepared from
farms and sampling was done in four states contain : sampling from
fresh saffron of petal with forceps , sampling from fresh saffron of
petal by hands, sampling from dried sample by warm air in shadow,
sampling from dried sample which dried by dryer. Samples collected
and kept in sterile tubes and containers and carried to laboratory and
maintained until experiment. Microbial experiments were performed
to determine microbial load such as total count, Staphylococcus
aureus, coli form, E.coli, mold and yeast. Results showed that in
picking and drying stages the contamination amount increases in
saffron samples. There was a significant difference between the
microbial load of picked up saffron by forceps and by hands, and
also between dried saffron by warm air in shadow and by dryer.
Abstract: The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.
Abstract: In this paper, we have combined some spatial derivatives with the optimised time derivative proposed by Tam and Webb in order to approximate the linear advection equation which is given by = 0. Ôêé Ôêé + Ôêé Ôêé x f t u These spatial derivatives are as follows: a standard 7-point 6 th -order central difference scheme (ST7), a standard 9-point 8 th -order central difference scheme (ST9) and optimised schemes designed by Tam and Webb, Lockard et al., Zingg et al., Zhuang and Chen, Bogey and Bailly. Thus, these seven different spatial derivatives have been coupled with the optimised time derivative to obtain seven different finite-difference schemes to approximate the linear advection equation. We have analysed the variation of the modified wavenumber and group velocity, both with respect to the exact wavenumber for each spatial derivative. The problems considered are the 1-D propagation of a Boxcar function, propagation of an initial disturbance consisting of a sine and Gaussian function and the propagation of a Gaussian profile. It is known that the choice of the cfl number affects the quality of results in terms of dissipation and dispersion characteristics. Based on the numerical experiments solved and numerical methods used to approximate the linear advection equation, it is observed in this work, that the quality of results is dependent on the choice of the cfl number, even for optimised numerical methods. The errors from the numerical results have been quantified into dispersion and dissipation using a technique devised by Takacs. Also, the quantity, Exponential Error for Low Dispersion and Low Dissipation, eeldld has been computed from the numerical results. Moreover, based on this work, it has been found that when the quantity, eeldld can be used as a measure of the total error. In particular, the total error is a minimum when the eeldld is a minimum.
Abstract: The purpose of this research is to determine the
knowledge and skills possessed by instructional design (ID)
practitioners in Malaysia. As ID is a relatively new field in the
country and there seems to be an absence of any studies on its
community of practice, the main objective of this research is to
discover the tasks and activities performed by ID practitioners in
educational and corporate organizations as suggested by the
International Board of Standards for Training, Performance and
Instruction. This includes finding out the ID models applied in the
course of their work. This research also attempts to identify the
barriers and issues as to why some ID tasks and activities are rarely
or never conducted. The methodology employed in this descriptive
study was a survey questionnaire sent to 30 instructional designers
nationwide. The results showed that majority of the tasks and
activities are carried out frequently enough but omissions do occur
due to reasons such as it being out of job scope, the decision was
already made at a higher level, and the lack of knowledge and skills.
Further investigations of a qualitative manner should be conducted
to achieve a more in-depth understanding of ID practices in
Malaysia
Abstract: An unstructured finite volume numerical model is
presented here for simulating shallow-water flows with wetting and
drying fronts. The model is based on the Green-s theorem in
combination with Chorin-s projection method. A 2nd-order upwind
scheme coupled with a Least Square technique is used to handle
convection terms. An Wetting and drying treatment is used in the
present model to ensures the total mass conservation. To test it-s
capacity and reliability, the present model is used to solve the
Parabolic Bowl problem. We compare our numerical solutions with
the corresponding analytical and existing standard numerical results.
Excellent agreements are found in all the cases.
Abstract: European Union candidate status provides a
strong motivation for decision-making in the candidate
countries in shaping the regional development policy where
there is an envisioned transfer of power from center to the
periphery. The process of Europeanization anticipates the
candidate countries configure their regional institutional
templates in the context of the requirements of the European
Union policies and introduces new instruments of incentive
framework of enlargement to be employed in regional
development schemes. It is observed that the contribution of
the local actors to the decision making in the design of the
allocation architectures enhances the efficiency of the funds
and increases the positive effects of the projects funded under
the regional development objectives. This study aims at
exploring the performances of the three regional development
grant schemes in Turkey, established and allocated under the
pre-accession process with a special emphasis given to the
roles of the national and local actors in decision-making for
regional development. Efficiency analyses have been
conducted using the DEA methodology which has proved to
be a superior method in comparative efficiency and
benchmarking measurements. The findings of this study as
parallel to similar international studies, provides that the
participation of the local actors to the decision-making in
funding contributes both to the quality and the efficiency of
the projects funded under the EU schemes.
Abstract: This paper describes a new supervised fusion (hybrid)
electrocardiogram (ECG) classification solution consisting of a new
QRS complex geometrical feature extraction as well as a new version
of the learning vector quantization (LVQ) classification algorithm
aimed for overcoming the stability-plasticity dilemma. Toward this
objective, after detection and delineation of the major events of ECG
signal via an appropriate algorithm, each QRS region and also its
corresponding discrete wavelet transform (DWT) are supposed as
virtual images and each of them is divided into eight polar sectors.
Then, the curve length of each excerpted segment is calculated
and is used as the element of the feature space. To increase the
robustness of the proposed classification algorithm versus noise,
artifacts and arrhythmic outliers, a fusion structure consisting of
five different classifiers namely as Support Vector Machine (SVM),
Modified Learning Vector Quantization (MLVQ) and three Multi
Layer Perceptron-Back Propagation (MLP–BP) neural networks with
different topologies were designed and implemented. The new proposed
algorithm was applied to all 48 MIT–BIH Arrhythmia Database
records (within–record analysis) and the discrimination power of the
classifier in isolation of different beat types of each record was
assessed and as the result, the average accuracy value Acc=98.51%
was obtained. Also, the proposed method was applied to 6 number
of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging
to 20 different records of the aforementioned database (between–
record analysis) and the average value of Acc=95.6% was achieved.
To evaluate performance quality of the new proposed hybrid learning
machine, the obtained results were compared with similar peer–
reviewed studies in this area.
Abstract: Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.
Abstract: Information is power. Geographical information is an
emerging science that is advancing the development of knowledge to
further help in the understanding of the relationship of “place" with
other disciplines such as crime. The researchers used crime data for
the years 2004 to 2007 from the Baguio City Police Office to
determine the incidence and actual locations of crime hotspots.
Combined qualitative and quantitative research methodology was
employed through extensive fieldwork and observation, geographic
visualization with Geographic Information Systems (GIS) and Global
Positioning Systems (GPS), and data mining. The paper discusses
emerging geographic visualization and data mining tools and
methodologies that can be used to generate baseline data for
environmental initiatives such as urban renewal and rejuvenation.
The study was able to demonstrate that crime hotspots can be
computed and were seen to be occurring to some select places in the
Central Business District (CBD) of Baguio City. It was observed that
some characteristics of the hotspot places- physical design and milieu
may play an important role in creating opportunities for crime. A list
of these environmental attributes was generated. This derived
information may be used to guide the design or redesign of the urban
environment of the City to be able to reduce crime and at the same
time improve it physically.
Abstract: As networking has become popular, Web-learning
tends to be a trend while designing a tool. Moreover, five-axis
machining has been widely used in industry recently; however, it has
potential axial table colliding problems. Thus this paper aims at
proposing an efficient web-learning collision detection tool on
five-axis machining. However, collision detection consumes heavy
resource that few devices can support, thus this research uses a
systematic approach based on web knowledge to detect collision. The
methodologies include the kinematics analyses for five-axis motions,
separating axis method for collision detection, and computer
simulation for verification. The machine structure is modeled as STL
format in CAD software. The input to the detection system is the
g-code part program, which describes the tool motions to produce the
part surface. This research produced a simulation program with C
programming language and demonstrated a five-axis machining
example with collision detection on web site. The system simulates the
five-axis CNC motion for tool trajectory and detects for any collisions
according to the input g-codes and also supports high-performance
web service benefiting from C. The result shows that our method
improves 4.5 time of computational efficiency, comparing to the
conventional detection method.
Abstract: Segmentation techniques based on Active Contour
Models have been strongly benefited from the use of prior information
during their evolution. Shape prior information is captured from
a training set and is introduced in the optimization procedure to
restrict the evolution into allowable shapes. In this way, the evolution
converges onto regions even with weak boundaries. Although
significant effort has been devoted on different ways of capturing
and analyzing prior information, very little thought has been devoted
on the way of combining image information with prior information.
This paper focuses on a more natural way of incorporating the
prior information in the level set framework. For proof of concept
the method is applied on hippocampus segmentation in T1-MR
images. Hippocampus segmentation is a very challenging task, due
to the multivariate surrounding region and the missing boundary
with the neighboring amygdala, whose intensities are identical. The
proposed method, mimics the human segmentation way and thus
shows enhancements in the segmentation accuracy.
Abstract: In this paper the reference current for Voltage Source
Converter (VSC) of the Shunt Active Power Filter (SAPF) is
generated using Synchronous Reference Frame method,
incorporating the PI controller with anti-windup scheme. The
proposed method improves the harmonic filtering by compensating
the winding up phenomenon caused by the integral term of the PI
controller.
Using Reference Frame Transformation, the current is transformed
from om a - b - c stationery frame to rotating 0 - d - q frame. Using
the PI controller, the current in the 0 - d - q frame is controlled to
get the desired reference signal. A controller with integral action
combined with an actuator that becomes saturated can give some
undesirable effects. If the control error is so large that the integrator
saturates the actuator, the feedback path becomes ineffective because
the actuator will remain saturated even if the process output changes.
The integrator being an unstable system may then integrate to a very
large value, the phenomenon known as integrator windup.
Implementing the integrator anti-windup circuit turns off the
integrator action when the actuator saturates, hence improving the
performance of the SAPF and dynamically compensating harmonics
in the power network. In this paper the system performance is
examined with Shunt Active Power Filter simulation model.
Abstract: To strengthen the capital market, there is a need to
integrate the capital markets within the region by removing legal or informal restriction, specifically, stock market liberalization. Thus the paper is to investigate the effects of the subsequent stock market liberalization on stock market integration in 4 ASEAN countries (Malaysia, Indonesia, Thailand, Singapore) and Korea from 1997 to 2007. The correlation between stock market liberalization and stock
market integration are to be examined by analyzing the stock prices
and returns within the region and in comparison with the world
MSCI index. Event study method is to be used with windows of ±12
months and T-7 + T. The results show that the subsequent stock
market liberalization generally, gives minor positive effects to stock
returns, except for one or two countries. The subsequent
liberalization also integrates the markets short-run and long-run.
Abstract: Adhesively bonded joints are preferred over the
conventional methods of joining such as riveting, welding, bolting
and soldering. Some of the main advantages of adhesive joints
compared to conventional joints are the ability to join dissimilar
materials and damage-sensitive materials, better stress distribution,
weight reduction, fabrication of complicated shapes, excellent
thermal and insulation properties, vibration response and enhanced
damping control, smoother aerodynamic surfaces and an
improvement in corrosion and fatigue resistance. This paper presents
the behavior of adhesively bonded joints subjected to combined
thermal loadings, using the numerical methods. The joint
configuration considers aluminum as central adherend with six
different outer adherends including aluminum, steel, titanium, boronepoxy,
unidirectional graphite-epoxy and cross-ply graphite-epoxy
and epoxy-based adhesives. Free expansion of the joint in x
direction was permitted and stresses in adhesive layer and interfaces
calculated for different adherends.
Abstract: A new multi inner stage (MIS) cyclone was designed to
remove the acidic gas and fine particles produced from electronic
industry. To characterize gas flow in MIS cyclone, pressure and
velocity distribution were calculated by means of CFD program. Also,
the flow locus of fine particles and particle removal efficiency were
analyzed by Lagrangian method. When outlet pressure condition was
–100mmAq, the efficiency was the best in this study.
Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.
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: 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.