Abstract: Due to the recovering global economy, enterprises are
increasingly focusing on logistics. Investing in logistic measures for
a production generates a large potential for achieving a good starting
point within a competitive field. Unlike during the global economic
crisis, enterprises are now challenged with investing available capital
to maximize profits. In order to be able to create an informed and
quantifiably comprehensible basis for a decision, enterprises need an
adequate model for logistically and monetarily evaluating measures
in production. The Collaborate Research Centre 489 (SFB 489) at the
Institute for Production Systems (IFA) developed a Logistic
Information System which provides support in making decisions and
is designed specifically for the forging industry. The aim of a project
that has been applied for is to now transfer this process in order to
develop a universal approach to logistically and monetarily evaluate
measures in production.
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: 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: This research contribution is drafted to present the
orbit design, orbit propagator and geomagnetic field estimator for the
nanosatellites specifically for the upcoming CUBESAT, ICUBE-1 of
the Institute of Space Technology (IST), Islamabad, Pakistan. The
ICUBE mission is designed for the low earth orbit at the approximate
height of 700KM. The presented research endeavor designs the
Keplarian elements for ICUBE-1 orbit while incorporating the
mission requirements and propagates the orbit using J2 perturbations,
The attitude determination system of the ICUBE-1 consists of
attitude determination sensors like magnetometer and sun sensor. The
Geomagnetic field estimator is developed according to the model of
International Geomagnetic Reference Field (IGRF) for comparing the
magnetic field measurements by the magnetometer for attitude
determination. The output of the propagator namely the Keplarians
position and velocity vectors and the magnetic field vectors are
compared and verified with the same scenario generated in the
Satellite Tool Kit (STK).
Abstract: The paper presents an overview of environmental
issues that may be expected with nuclear desalination. The analysis
of coupling nuclear power with desalination plants indicates that
adverse marine impacts can be mitigated with alternative intake
designs or cooling systems. The atmospheric impact of desalination
may be greatly reduced through the coupling with nuclear power,
while maximizing the socio-economic benefit for both processes. The
potential for tritium contamination of the desalinated water was
reviewed. Experience with the systems and practices related to the
radiological quality of the product water, shows no examples of
cross-contamination. Furthermore, the indicators for the public
acceptance of nuclear desalination, as one of the most important
sustainability aspects of any such large project, show a positive trend.
From the data collected, a conclusion is made that nuclear
desalination should be supported by decision-makers.
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: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
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: In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.
A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.
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 procedure for the preparation of clarified Pawpaw
Juice was developed. About 750ml Pawpaw pulp was measured into
2 measuring cylinders A & B of capacity 1 litre heated to 400C,
cooled to 200C. 30mls pectinase was added into cylinder A, while
30mls distilled water was added into cylinder B. Enzyme treated
sample (A) was allowed to digest for 5hours after which it was heated
to 900C for 15 minutes to inactivate the enzyme. The heated sample
was cooled and with the aid of a mucillin cloth the pulp was filtered
to obtain the clarified pawpaw juice. The juice was filled into 100ml
plastic bottles, pasteurized at 950C for 45 minutes, cooled and stored
at room temperature. The sample treated with 30mls distilled water
also underwent the same process. Freshly pasteurized sample was
analyzed for specific gravity, titratable acidity, pH, sugars and
ascorbic acid. The remaining sample was then stored for 2 weeks and
the above analyses repeated. There were differences in the results of
the freshly pasteurized samples and stored sample in pH and ascorbic
acid levels, also sample treated with pectinase yielded higher
volumes of juice than that treated with distilled water.
Abstract: Phishing, or stealing of sensitive information on the
web, has dealt a major blow to Internet Security in recent times. Most
of the existing anti-phishing solutions fail to handle the fuzziness
involved in phish detection, thus leading to a large number of false
positives. This fuzziness is attributed to the use of highly flexible and
at the same time, highly ambiguous HTML language. We introduce a
new perspective against phishing, that tries to systematically prove,
whether a given page is phished or not, using the corresponding
original page as the basis of the comparison. It analyzes the layout of
the pages under consideration to determine the percentage distortion
between them, indicative of any form of malicious alteration. The
system design represents an intelligent system, employing dynamic
assessment which accurately identifies brand new phishing attacks
and will prove effective in reducing the number of false positives.
This framework could potentially be used as a knowledge base, in
educating the internet users against phishing.
Abstract: Recently there has been a growing interest in the field
of bio-mimetic robots that resemble the behaviors of an insect or an
aquatic animal, among many others. One of various bio-mimetic robot
applications is to explore pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. Special
types of mobile robots are necessary for the pipeline monitoring tasks.
In order to move effectively along a pipeline, the robot-s movement
will resemble that of insects or crawling animals. When situated in
massive pipelines with complex routes, the robot places fixed sensors
in several important spots in order to complete its monitoring. This
monitoring task is to prevent a major system failure by preemptively
recognizing any minor or partial malfunctions. Areas uncovered by
fixed sensors are usually impossible to provide real-time observation
and examination, and thus are dependent on periodical offline
monitoring. This paper proposes a monitoring system that is able to
monitor the entire area of pipelines–with and without fixed
sensors–by using the bio-mimetic robot.
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: 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: 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.