Abstract: An experimental and numerical study has been conducted to clarify heat transfer characteristics and effectiveness of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. The tubes arrangements were employed with various angles of attack θ1,2,3 from 0° to 330° at the considered Rea range. Correlation of Nu, St, as well as the heat transfer per unit pumping power (ε) in terms of Rea, design parameters for the studied bundle were presented. The temperature fields around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the heat transfer was increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. The best thermal performance and hence η of studied bundle was occurred at the lowest Rea and/or zero angle of attack. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.
Abstract: The hospital and the health-care center of a
community, as a place for people-s life-care and health-care settings,
must provide more and better services for patients or residents. After
Establishing Electronic Medical Record (EMR) system -which is a
necessity- in the hospital, providing pervasive services is a further
step. Our objective in this paper is to use pervasive computing in a
case study of healthcare, based on EMR database that coordinates
application services over network to form a service environment for
medical and health-care. Our method also categorizes the hospital
spaces into 3 spaces: Public spaces, Private spaces and Isolated
spaces. Although, there are many projects about using pervasive
computing in healthcare, but all of them concentrate on the disease
recognition, designing smart cloths, or provide services only for
patient. The proposed method is implemented in a hospital. The
obtained results show that it is suitable for our purpose.
Abstract: In this paper, a method for deriving a group priority vector in the Fuzzy Analytic Network Process (FANP) is proposed. By introducing importance weights of multiple decision makers (DMs) based on their experiences, the Fuzzy Preferences Programming Method (FPP) is extended to a fuzzy group prioritization problem in the FANP. Additionally, fuzzy pair-wise comparison judgments are presented rather than exact numerical assessments in order to model the uncertainty and imprecision in the DMs- judgments and then transform the fuzzy group prioritization problem into a fuzzy non-linear programming optimization problem which maximize the group satisfaction. Unlike the known fuzzy prioritization techniques, the new method proposed in this paper can easily derive crisp weights from incomplete and inconsistency fuzzy set of comparison judgments and does not require additional aggregation producers. Detailed numerical examples are used to illustrate the implement of our approach and compare with the latest fuzzy prioritization method.
Abstract: This paper presents a comparative study on two most
popular control strategies for Permanent Magnet Synchronous Motor
(PMSM) drives: field-oriented control (FOC) and direct torque
control (DTC). The comparison is based on various criteria including
basic control characteristics, dynamic performance, and
implementation complexity. The study is done by simulation using
the Simulink Power System Blockset that allows a complete
representation of the power section (inverter and PMSM) and the
control system. The simulation and evaluation of both control
strategies are performed using actual parameters of Permanent
Magnet Synchronous Motor fed by an IGBT PWM inverter.
Abstract: In this study a neural network (NN) was proposed to
predict the sorption of binary mixture of copper-cobalt ions into
clinoptilolite as ion-exchanger. The configuration of the
backpropagation neural network giving the smallest mean square
error was three-layer NN with tangent sigmoid transfer function at
hidden layer with 10 neurons, linear transfer function at output layer
and Levenberg-Marquardt backpropagation training algorithm.
Experiments have been carried out in the batch reactor to obtain
equilibrium data of the individual sorption and the mixture of coppercobalt
ions. The obtained modeling results have shown that the used
of neural network has better adjusted the equilibrium data of the
binary system when compared with the conventional sorption
isotherm models.
Abstract: Access control is a critical security service in Wire- less
Sensor Networks (WSNs). To prevent malicious nodes from joining
the sensor network, access control is required. On one hand, WSN
must be able to authorize and grant users the right to access to the
network. On the other hand, WSN must organize data collected by
sensors in such a way that an unauthorized entity (the adversary)
cannot make arbitrary queries. This restricts the network access only
to eligible users and sensor nodes, while queries from outsiders will
not be answered or forwarded by nodes. In this paper we presentee
different access control schemes so as to ?nd out their objectives,
provision, communication complexity, limits, etc. Using the node
density parameter, we also provide a comparison of these proposed
access control algorithms based on the network topology which can
be flat or hierarchical.
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: 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: 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: 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: 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: 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 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: 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.
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 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.
Abstract: The challenge for software development house in
Bangladesh is to find a path of using minimum process rather than CMMI or ISO type gigantic practice and process area. The small and medium size organization in Bangladesh wants to ensure minimum
basic Software Process Improvement (SPI) in day to day operational
activities. Perhaps, the basic practices will ensure to realize their company's improvement goals. This paper focuses on the key issues in basic software practices for small and medium size software
organizations, who are unable to effort the CMMI, ISO, ITIL etc. compliance certifications. This research also suggests a basic software process practices model for Bangladesh and it will show the mapping of our suggestions with international best practice. In this IT
competitive world for software process improvement, Small and medium size software companies that require collaboration and
strengthening to transform their current perspective into inseparable global IT scenario. This research performed some investigations and analysis on some projects- life cycle, current good practice, effective approach, reality and pain area of practitioners, etc. We did some
reasoning, root cause analysis, comparative analysis of various
approach, method, practice and justifications of CMMI and real life. We did avoid reinventing the wheel, where our focus is for minimal
practice, which will ensure a dignified satisfaction between
organizations and software customer.
Abstract: An innovative tri-axes micro-power receiver is
proposed. The tri-axes micro-power receiver consists of two sets 3-D
micro-solenoids and one set planar micro-coils in which iron core is
embedded. The three sets of micro-coils are designed to be orthogonal
to each other. Therefore, no matter which direction the flux is present
along, the magnetic energy can be harvested and transformed into
electric power. Not only dead space of receiving power is mostly
reduced, but also transformation efficiency of electromagnetic energy
to electric power can be efficiently raised. By employing commercial
software, Ansoft Maxwell, the preliminary simulation results verify
that the proposed micro-power receiver can efficiently pick up the
energy transmitted by magnetic power source.
As to the fabrication process, the isotropic etching technique is
employed to micro-machine the inverse-trapezoid fillister so that the
copper wire can be successfully electroplated. The adhesion between
micro-coils and fillister is much enhanced.
Abstract: This paper aims to perform the second law analysis of
thermodynamics on the laminar film condensation of pure saturated
vapor flowing in the direction of gravity on an ellipsoid with variable
wall temperature. The analysis provides us understanding how the
geometric parameter- ellipticity and non-isothermal wall temperature
variation amplitude “A." affect entropy generation during film-wise
condensation heat transfer process. To understand of which
irreversibility involved in this condensation process, we derived an
expression for the entropy generation number in terms of ellipticity
and A. The result indicates that entropy generation increases with
ellipticity. Furthermore, the irreversibility due to finite temperature
difference heat transfer dominates over that due to condensate film
flow friction and the local entropy generation rate decreases with
increasing A in the upper half of ellipsoid. Meanwhile, the local
entropy generation rate enhances with A around the rear lower half of
ellipsoid.