Abstract: Developing a stable early warning system (EWS)
model that is capable to give an accurate prediction is a challenging
task. This paper introduces k-nearest neighbour (k-NN) method
which never been applied in predicting currency crisis before with the
aim of increasing the prediction accuracy. The proposed k-NN
performance depends on the choice of a distance that is used where in
our analysis; we take the Euclidean distance and the Manhattan as a
consideration. For the comparison, we employ three other methods
which are logistic regression analysis (logit), back-propagation neural
network (NN) and sequential minimal optimization (SMO). The
analysis using datasets from 8 countries and 13 macro-economic
indicators for each country shows that the proposed k-NN method
with k = 4 and Manhattan distance performs better than the other
methods.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible thermal multi-component gas
mixture flows in pipes. The set of the mass, momentum and enthalpy
conservation equations for gas phase is solved. Thermo-physical
properties of multi-component gas mixture are calculated by solving
the Equation of State (EOS) model. The Soave-Redlich-Kwong
(SRK-EOS) model is chosen. Gas mixture viscosity is calculated on
the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical
analysis on rapid decompression in conventional dry gases is
performed by using the proposed mathematical model. The model is
validated on measured values of the decompression wave speed in
dry natural gas mixtures. All predictions show excellent agreement
with the experimental data at high and low pressure. The presented
model predicts the decompression in dry natural gas mixtures much
better than GASDECOM and OLGA codes, which are the most
frequently-used codes in oil and gas pipeline transport service.
Abstract: The ever growing sentiment of environmentalism across the globe has made many people think on the green lines. But most of such ideas halt short of implementation because of the short term economic viability issues with the concept of going green. In this paper we have tried to amalgamate the green concept with social entrepreneurship for solving a variety of issues faced by the society today. In addition the paper also tries to ensure that the short term economic viability does not act as a deterrent. The paper comes up three sustainable models of social entrepreneurship which tackle a wide assortment of issues such as nutrition problem, land problems, pollution problems and employment problems. The models described fall under the following heads: - Spirulina cultivation: The model addresses nutrition, land and employment issues. It deals with cultivation of a blue green alga called Spirulina which can be used as a very nutritious food. Also, the implementation of this model would bring forth employment to the poor people of the area. - Biocomposites: The model comes up with various avenues in which biocomposites can be used in an economically sustainable manner. This model deals with the environmental concerns and addresses the depletion of natural resources. - Packaging material from empty fruit bunches (EFB) of oil palm: This one deals with air and land pollution. It is intended to be a substitute for packaging materials made from Styrofoam and plastics which are non-biodegradable. It takes care of the biodegradability and land pollution issues. It also reduces air pollution as the empty fruit bunches are not incinerated. All the three models are sustainable and do not deplete the natural resources any further. This paper explains each of the models in detail and deals with the operational/manufacturing procedures and cost analysis while also throwing light on the benefits derived and sustainability aspects.
Abstract: In the present work an investigation of the effects of
the air frontal velocity, relative humidity and dry air temperature on
the heat transfer characteristics of plain finned tube evaporator has
been conducted. Using an appropriate correlation for the air side heat
transfer coefficient the temperature distribution along the fin surface
was calculated using a dimensionless temperature distribution. For a
constant relative humidity and bulb temperature, it is found that the
temperature distribution decreases with increasing air frontal
velocity. Apparently, it is attributed to the condensate water film
flowing over the fin surface. When dry air temperature and face
velocity are being kept constant, the temperature distribution
decreases with the increase of inlet relative humidity. An increase in
the inlet relative humidity is accompanied by a higher amount of
moisture on the fin surface. This results in a higher amount of latent
heat transfer which involves higher fin surface temperature. For the
influence of dry air temperature, the results here show an increase in
the dimensionless temperature parameter with a decrease in bulb
temperature. Increasing bulb temperature leads to higher amount of
sensible and latent heat transfer when other conditions remain
constant.
Abstract: In this paper we propose the study of a centrifugal pump control system driven by a three-phase induction motor, which is supplied by a PhotoVoltaic PV generator. The system includes solar panel, a DC / DC converter equipped with its MPPT control, a voltage inverter to three-phase Pulse Width Modulation - PWM and a centrifugal pump driven by a three phase induction motor. In order to control the flow of the centrifugal pump, a Direct Torque Control - DTC of the induction machine is used. To illustrate the performances of the control, simulation results are carried out using Matlab/Simulink.
Abstract: In this paper, the influencing parameters of a novel
purely mechanical wireless in-mould injection moulding sensor
were investigated. The sensor is capable of detecting the melt
front at predefined locations inside the mould. The sensor comprises
a movable pin which acts as the sensor element generating
structure-borne sound triggered by the passing melt front. Due to
the sensor design, melt pressure is the driving force. For pressure
level measurement during pin movement a pressure transducer
located at the same position as the movable pin. By deriving
a mathematical model for the mechanical movement, dominant
process parameters could be investigated towards their impact
on the melt front detection characteristic. It was found that the
sensor is not affected by the investigated parameters enabling it
for reliable melt front detection. In addition, it could be proved
that the novel sensor is in comparable range to conventional melt
front detection sensors.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: In this study, a minimal submaximal element of LIT(X) (the lattice of all intuitionistic topologies for X, ordered by inclusion) is determined. Afterwards, a new contractive property, intuitionistic mega-connectedness, is defined. We show that the submaximality and mega-connectedness are not complementary intuitionistic topological invariants by identifying those members of LIT(X) which are intuitionistic mega-connected.
Abstract: One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.
Abstract: Physical and mechanical properties of Russian olive
fruits were measured at moisture content of 14.43% w.b. The results
revealed that the mean length, width and thickness of Russian olive
fruits were 20.72, 15.73 and 14.69mm, respectively. Mean mass and
volume of Russian olive fruits were measured as 1.45 g and 2.55 cm3,
respectively. The sphericity, aspect ratio and surface area were
calculated as 0.81, 0.72 and 8.96 cm2, respectively, while arithmetic
mean diameter, geometric mean diameter and equivalent diameter of
Russian olive fruits were 17.05, 16.83 and 16.84 mm, respectively.
Whole fruit density, bulk density and porosity of jujube fruits were
measured and found to be 1.01 g/cm3, 0.29 g/cm3 and 69.5%,
respectively. The values of static coefficient of friction on three
surfaces of glass, galvanized iron and plywood were 0.35, 0.36 and
0.43, respectively. The skin color (L*, a*, b*) varied from 9.92 to
16.08; 2.04 to 3.91 and 1.12 to 3.83, respectively. The values of
rupture force, deformation, energy absorbed and hardness were found
to be between 12.14-16.85 N, 2.16-4.25 mm, 3.42-6.99 N mm and
17.1-23.85 N/mm.
Abstract: Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: The need for multilingual communication in Japan has
increased due to an increase in the number of foreigners in the
country. When people communicate in their nonnative language,
the differences in language prevent mutual understanding among
the communicating individuals. In the medical field, communication
between the hospital staff and patients is a serious problem. Currently,
medical translators accompany patients to medical care facilities, and
the demand for medical translators is increasing. However, medical
translators cannot necessarily provide support, especially in cases in
which round-the-clock support is required or in case of emergencies.
The medical field has high expectations from information technology.
Hence, a system that supports accurate multilingual communication is
required. Despite recent advances in machine translation technology,
it is very difficult to obtain highly accurate translations. We have
developed a support system called M3 for multilingual medical
reception. M3 provides support functions that aid foreign patients in
the following respects: conversation, questionnaires, reception procedures,
and hospital navigation; it also has a Q&A function. Users
can operate M3 using a touch screen and receive text-based support.
In addition, M3 uses accurate translation tools called parallel texts
to facilitate reliable communication through conversations between
the hospital staff and the patients. However, if there is no parallel
text that expresses what users want to communicate, the users cannot
communicate. In this study, we have developed a circulating support
environment for multilingual medical communication using parallel
texts. The proposed environment can circulate necessary parallel texts
through the following procedure: (1) a user provides feedback about
the necessary parallel texts, following which (2) these parallel texts
are created and evaluated.
Abstract: In this paper, we have presented the effect of varying
time-delays on performance and stability in the single-channel multirate
sampled-data system in hard real-time (RT-Linux) environment.
The sampling task require response time that might exceed the
capacity of RT-Linux. So a straight implementation with RT-Linux is
not feasible, because of the latency of the systems and hence,
sampling period should be less to handle this task. The best sampling
rate is chosen for the sampled-data system, which is the slowest rate
meets all performance requirements. RT-Linux is consistent with its
specifications and the resolution of the real-time is considered 0.01
seconds to achieve an efficient result. The test results of our
laboratory experiment shows that the multi-rate control technique in
hard real-time operating system (RTOS) can improve the stability
problem caused by the random access delays and asynchronization.
Abstract: Data Mining aims at discovering knowledge out of
data and presenting it in a form that is easily comprehensible to
humans. One of the useful applications in Egypt is the Cancer
management, especially the management of Acute Lymphoblastic
Leukemia or ALL, which is the most common type of cancer in
children.
This paper discusses the process of designing a prototype that can
help in the management of childhood ALL, which has a great
significance in the health care field. Besides, it has a social impact
on decreasing the rate of infection in children in Egypt. It also
provides valubale information about the distribution and
segmentation of ALL in Egypt, which may be linked to the possible
risk factors.
Undirected Knowledge Discovery is used since, in the case of this
research project, there is no target field as the data provided is
mainly subjective. This is done in order to quantify the subjective
variables. Therefore, the computer will be asked to identify
significant patterns in the provided medical data about ALL. This
may be achieved through collecting the data necessary for the
system, determimng the data mining technique to be used for the
system, and choosing the most suitable implementation tool for the
domain.
The research makes use of a data mining tool, Clementine, so as to
apply Decision Trees technique. We feed it with data extracted from
real-life cases taken from specialized Cancer Institutes. Relevant
medical cases details such as patient medical history and diagnosis
are analyzed, classified, and clustered in order to improve the disease
management.
Abstract: There are many real world problems in which
parameters like the arrival time of new jobs, failure of resources, and
completion time of jobs change continuously. This paper tackles the
problem of scheduling jobs with random due dates on multiple
identical machines in a stochastic environment. First to assign jobs to
different machine centers LPT scheduling methods have been used,
after that the particular sequence of jobs to be processed on the
machine have been found using simple stochastic techniques. The
performance parameter under consideration has been the maximum
lateness concerning the stochastic due dates which are independent
and exponentially distributed. At the end a relevant problem has been
solved using the techniques in the paper..
Abstract: The objective of this research is to study the technical
and economic performance of wind/diesel/battery (W/D/B) system
supplying a remote small gathering of six families using HOMER
software package. The electrical energy is to cater for the basic needs
for which the daily load pattern is estimated. Net Present Cost (NPC)
and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and
economic parameters are defined to estimate the feasibility of the
system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites
as the price of generated electricity is about 0.308 $/kWh, without
taking external benefits into considerations. W/D/B systems are more
economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.
Abstract: In this work, several ASP solutions were flooded into
fractured models initially saturated with heavy oil at a constant flow
rate and different geometrical characteristics of fracture. The ASP
solutions are constituted from 2 polymers i.e. a synthetic polymer,
hydrolyzed polyacrylamide as well as a biopolymer, a surfactant and
2types of alkaline. The results showed that using synthetic
hydrolyzed polyacrylamide polymer increases ultimate oil recovery;
however, type of alkaline does not play a significant rule on oil
recovery. In addition, position of the injection well respect to the
fracture system has remarkable effects on ASP flooding. For instance
increasing angle of fractures with mean flow direction causes more
oil recovery and delays breakthrough time. This work can be
accounted as a comprehensive survey on ASP flooding which
considers most of effective factors in this chemical EOR method.
Abstract: The deviation between the target state variable and the
practical state variable should be used to form the state tending factor
of complex systems, which can reflect the process for the complex
system to tend rationalization. Relating to the system of basic
equations of complete factor synergetics consisting of twenty
nonlinear stochastic differential equations, the two new models are
considered to set, which should be called respectively the
rationalizing tendency model and the non- rationalizing tendency
model. Therefore we can extend the theory of programming with the
objective function & constraint condition suitable only for the realm
of man-s activities into the new analysis with the tendency function &
constraint condition suitable for all the field of complex system.
Abstract: A novel nanofinishing process using improved ball
end magnetorheological (MR) finishing tool was developed for finishing of flat as well as 3D surfaces of ferromagnetic and non ferromagnetic workpieces. In this process a magnetically controlled
ball end of smart MR polishing fluid is generated at the tip surface of
the tool which is used as a finishing medium and it is guided to
follow the surface to be finished through computer controlled 3-axes
motion controller. The experiments were performed on ferromagnetic
workpiece surface in the developed MR finishing setup to study the effect of finishing time on final surface roughness. The performance
of present finishing process on final finished surface roughness was studied. The surface morphology was observed under scanning
electron microscopy and atomic force microscope. The final surface finish was obtained as low as 19.7 nm from the initial surface
roughness of 142.9 nm. The outcome of newly developed finishing process can be found useful in its applications in aerospace,
automotive, dies and molds manufacturing industries, semiconductor and optics machining etc.