Abstract: Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.
Abstract: In recent years, the hair building fiber has become
popular, in other words, it is an effective method which helps people
who suffer hair loss or sparse hair since the hair building fiber is
capable to create a natural look of simulated hair rapidly. In the
markets, there are a lot of hair fiber brands that have been designed to
formulate an intense bond with hair strands and make the hair appear
more voluminous instantly. However, those products have their own
set of properties. Thus, in this report, some measurement techniques
are proposed to identify those products. Up to five different brands of
hair fiber are tested. The electrostatic and dielectric properties of the
hair fibers are macroscopically tested using design DC and high
frequency microwave techniques. Besides, the hair fibers are
microscopically analysis by magnifying the structures of the fiber
using scanning electron microscope (SEM). From the SEM photos,
the comparison of the uniformly shaped and broken rate of the hair
fibers in the different bulk samples can be observed respectively.
Abstract: This paper presents a methodology using
Gravitational Search Algorithm for optimal placement of Phasor
Measurement Units (PMUs) in order to achieve complete
observability of the power system. The objective of proposed
algorithm is to minimize the total number of PMUs at the power
system buses, which in turn minimize installation cost of the PMUs.
In this algorithm, the searcher agents are collection of masses which
interact with each other using Newton’s laws of gravity and motion.
This new Gravitational Search Algorithm based method has been
applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test
systems. Case studies reveal optimal number of PMUs with better
observability by proposed method.
Abstract: Artificial intelligence applications are commonly used
in industry in many fields in parallel with the developments in the
computer technology. In this study, a fire room was prepared for the
resistance of wooden construction elements and with the mechanism
here, the experiments of polished materials were carried out. By
utilizing from the experimental data, an artificial neural network
(ANN) was modelled in order to evaluate the final cross sections of
the wooden samples remaining from the fire. In modelling,
experimental data obtained from the fire room were used. In the
developed system, the first weight of samples (ws-gr), preliminary
cross-section (pcs-mm2), fire time (ft-minute), and fire temperature
(t-oC) as input parameters and final cross-section (fcs-mm2) as output
parameter were taken. When the results obtained from ANN and
experimental data are compared after making statistical analyses, the
data of two groups are determined to be coherent and seen to have no
meaning difference between them. As a result, it is seen that ANN
can be safely used in determining cross sections of wooden materials
after fire and it prevents many disadvantages.
Abstract: Sustainability and eco-friendly requirement of
engineering materials are sort for in recent times, thus giving rise to
the development of bio-composites. However, the natural fibres to
matrix interface interactions remain a key issue in getting the desired
mechanical properties from such composites. Treatment of natural
fibres is essential in improving matrix to filler adhesion, hence
improving its mechanical properties. In this study, investigations
were carried out to determine the effect of sodium hydroxide
treatment on the tensile, flexural, impact and hardness properties of
crushed and uncrushed Luffa cylindrica fibre reinforced recycled low
density polyethylene composites. The LC (Luffa cylindrica) fibres
were treated with 0%, 2%, 4%, 6%, 8% and 10% wt. sodium
hydroxide (NaOH) concentrations for a period of 24 hours under
room temperature conditions. A formulation ratio of 80/20 g (matrix
to reinforcement) was maintained for all developed samples. Analysis
of the results showed that the uncrushed luffa fibre samples gave
better mechanical properties compared with the crushed luffa fibre
samples. The uncrushed luffa fibre composites had a maximum
tensile and flexural strength of 7.65 MPa and 17.08 Mpa respectively
corresponding to a young modulus and flexural modulus of 21.08
MPa and 232.22 MPa for the 8% and 4% wt. NaOH concentration
respectively. Results obtained in the research showed that NaOH
treatment with the 8% NaOH concentration improved the mechanical
properties of the LC fibre reinforced composites when compared with
other NaOH treatment concentration values.
Abstract: Nature is a great source of inspiration for solving
complex problems in networks. It helps to find the optimal solution.
Metaheuristic algorithm is one of the nature-inspired algorithm which
helps in solving routing problem in networks. The dynamic features,
changing of topology frequently and limited bandwidth make the
routing, challenging in MANET. Implementation of appropriate
routing algorithms leads to the efficient transmission of data in
mobile ad hoc networks. The algorithms that are inspired by the
principles of naturally-distributed/collective behavior of social
colonies have shown excellence in dealing with complex
optimization problems. Thus some of the bio-inspired metaheuristic
algorithms help to increase the efficiency of routing in ad hoc
networks. This survey work presents the overview of bio-inspired
metaheuristic algorithms which support the efficiency of routing in
mobile ad hoc networks.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: Total hip replacement had been one of the most
successful operations in hip arthritis surgery. The purpose of this
research had been to develop a dynamic hip contact of Thai femoral
bone to analyze the stress distribution on the implant and the strain
distribution on the bone model under daily activities and compared
with the static load simulation. The results showed the different of
maximum von Mises stress 0.14 percent under walking and 0.03
percent under climbing stair condition and the different of equivalent
total strain 0.52 percent under walking and 0.05 percent under
climbing stair condition. The muscular forces should be evaluated
with dynamic condition to reduce the maximum von Mises stress and
equivalent total strain.
Abstract: The characteristic requirement for producing
rectangular shape bottles was a uniform thickness of the plastic bottle
wall. Die shaping was a good technique which controlled the wall
thickness of bottles. An advance technology which was the finite
element method (FEM) for blowing parison to be a rectangular shape
bottle was conducted to reduce waste plastic from a trial and error
method of a die shaping and parison control method. The artificial
intelligent (AI) comprised of artificial neural network and genetic
algorithm was selected to optimize the die gap shape from the FEM
results. The application of AI technique could optimize the suitable
die gap shape for the parison blow molding which did not depend on
the parison control method to produce rectangular bottles with the
uniform wall. Particularly, this application can be used with cheap
blow molding machines without a parison controller therefore it will
reduce cost of production in the bottle blow molding process.
Abstract: Many aluminum motorcycle parts produced by a high
pressure die casting. Some parts such as fuel caps were a thin and
complex shape. This part risked for porosities and blisters on surface
if it only depended on an experience of mold makers for mold design.
This research attempted to use CAST-DESIGNER software
simulated the high pressure die casting process with the same process
parameters of a motorcycle fuel cap production. The simulated results
were compared with fuel cap products and expressed the same
porosity and blister locations on cap surface. An average of absolute
difference of simulated results was obtained 0.094 mm when
compared the simulated porosity and blister defect sizes on the fuel
cap surfaces with the experimental micro photography. This
comparison confirmed an accuracy of software and will use the
setting parameters to improve fuel cap molds in the further work.
Abstract: The borate glasses are known by their structural
characterized by existence of unit’s structural composed by triangles
and tetrahedrons boron in different configurations depending on the
percentage of B2O3 in the glass chemical composition. In this paper,
effect of lithium oxide addition on the thermal and physical
properties of an alumina borate glass, was investigated. It was found
that the boron abnormality has a significant effect in the change of
glass properties according to the addition rate of lithium oxide.
Abstract: Non-linear FEM calculations are indispensable when
important technical information like operating performance of a
rubber component is desired. For example rubber bumpers built into
air-spring structures may undergo large deformations under load,
which in itself shows non-linear behavior. The changing contact
range between the parts and the incompressibility of the rubber
increases this non-linear behavior further. The material
characterization of an elastomeric component is also a demanding
engineering task.
The shape optimization problem of rubber parts led to the study of
FEM based calculation processes. This type of problems was posed
and investigated by several authors. In this paper the time demand of
certain calculation methods are studied and the possibilities of time
reduction is presented.
Abstract: Composite material based on Fe3Si micro-particles
and Mn-Zn nano-ferrite was prepared using powder metallurgy
technology. The sol-gel followed by autocombustion process was
used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically
milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano
powder system was homogenized by the Resonant Acoustic Mixing
using ResodynLabRAM Mixer. This non-invasive homogenization
technique was used to preserve spherical morphology of Fe3Si
powder particles. Uniaxial cold pressing in the closed die at pressure
600 MPa was applied to obtain a compact sample. Microwave
sintering of green compact was realized at 800°C, 20 minutes, in air.
Density of the powders and composite was measured by
Hepycnometry. Impulse excitation method was used to measure
elastic properties of sintered composite. Mechanical properties were
evaluated by measurement of transverse rupture strength (TRS) and
Vickers hardness (HV). Resistivity was measured by 4 point probe
method. Ferrite phase distribution in volume of the composite was
documented by metallographic analysis.
It has been found that nano-ferrite particle distributed among
micro- particles of Fe3Si powder alloy led to high relative density
(~93%) and suitable mechanical properties (TRS >100 MPa, HV
~1GPa, E-modulus ~140 GPa) of the composite. High electric
resistivity (R~6.7 ohm.cm) of prepared composite indicate their
potential application as soft magnetic material at medium and high
frequencies.
Abstract: Since, it is essential to provide homeless people by the
earthquake with safe, habitable accommodation repairing medium
and slight levels of damage at the connection parts should be
undertaken. In order to prove that a repaired connection was
sufficiently strong, a precast beam to column post tensioned
connection was tested in three phases. In phase one, the middle level
damage was observed at 6% drift at these connections. As a result of
the extra loads applied, little damage was observed. In the last phase,
the four connections tested in the first phase were repaired using
epoxy resin and then retested. The results from the tests on the
repaired precast and the undamaged specimens showed that the
repaired specimens were sufficiently strong, thus proving that repair
to damaged precast beam to column post tensioned connections can
be undertaken.
Abstract: Microbial fuel cells (MFCs) represent a promising
technology for simultaneous bioelectricity generation and wastewater
treatment. Catalysts are significant portions of the cost of microbial
fuel cell cathodes. Many materials have been tested as aqueous
cathodes, but air-cathodes are needed to avoid energy demands for
water aeration. The sluggish oxygen reduction reaction (ORR) rate at
air cathode necessitates efficient electrocatalyst such as carbon
supported platinum catalyst (Pt/C) which is very costly. Manganese
oxide (MnO2) was a representative metal oxide which has been
studied as a promising alternative electrocatalyst for ORR and has
been tested in air-cathode MFCs. However the single MnO2 has poor
electric conductivity and low stability. In the present work, the MnO2
catalyst has been modified by doping Pt nanoparticle. The goal of the
work was to improve the performance of the MFC with minimum Pt
loading. MnO2 and Pt nanoparticles were prepared by hydrothermal
and sol gel methods, respectively. Wet impregnation method was
used to synthesize Pt/MnO2 catalyst. The catalysts were further used
as cathode catalysts in air-cathode cubic MFCs, in which anaerobic
sludge was inoculated as biocatalysts and palm oil mill effluent
(POME) was used as the substrate in the anode chamber. The asprepared
Pt/MnO2 was characterized comprehensively through field
emission scanning electron microscope (FESEM), X-Ray diffraction
(XRD), X-ray photoelectron spectroscopy (XPS), and cyclic
voltammetry (CV) where its surface morphology, crystallinity,
oxidation state and electrochemical activity were examined,
respectively. XPS revealed Mn (IV) oxidation state and Pt (0)
nanoparticle metal, indicating the presence of MnO2 and Pt.
Morphology of Pt/MnO2 observed from FESEM shows that the
doping of Pt did not cause change in needle-like shape of MnO2
which provides large contacting surface area. The electrochemical
active area of the Pt/MnO2 catalysts has been increased from 276 to
617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The
CV results in O2 saturated neutral Na2SO4 solution showed that
MnO2 and Pt/MnO2 catalysts could catalyze ORR with different
catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode
catalyst generates a maximum power density of 165 mW/m3, which
is higher than that of MFC with MnO2 catalyst (95 mW/m3). The
open circuit voltage (OCV) of the MFC operated with MnO2 cathode
gradually decreased during 14 days of operation, whereas the MFC
with Pt/MnO2 cathode remained almost constant throughout the
operation suggesting the higher stability of the Pt/MnO2 catalyst.
Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an
efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced
performance.
Abstract: In this paper, we propose an automatic verification
technology of software patches for user virtual environments on IaaS
Cloud to decrease verification costs of patches. In these days, IaaS
services have been spread and many users can customize virtual
machines on IaaS Cloud like their own private servers. Regarding to
software patches of OS or middleware installed on virtual machines,
users need to adopt and verify these patches by themselves. This task
increases operation costs of users. Our proposed method replicates
user virtual environments, extracts verification test cases for user
virtual environments from test case DB, distributes patches to virtual
machines on replicated environments and conducts those test cases
automatically on replicated environments. We have implemented the
proposed method on OpenStack using Jenkins and confirmed the
feasibility. Using the implementation, we confirmed the effectiveness
of test case creation efforts by our proposed idea of 2-tier abstraction
of software functions and test cases. We also evaluated the automatic
verification performance of environment replications, test cases
extractions and test cases conductions.
Abstract: Newly synthesized Polypropylene-g-Polyethylene
glycol polymer was first time used for a compartment-less enzymatic
fuel cell. Working electrodes based on Polypropylene-g-Polyethylene
glycol were operated as unmediated and mediated system (with
ferrocene and gold/cobalt oxide nanoparticles). Glucose oxidase and
bilirubin oxidase was selected as anodic and cathodic enzyme,
respectively. Glucose was used as fuel in a single-compartment and
membrane-less cell. Maximum power density was obtained as 0.65
nW cm-2, 65 nW cm-2 and 23500 nW cm-2 from the unmediated,
ferrocene and gold/cobalt oxide modified polymeric film,
respectively. Power density was calculated to be ~16000 nW cm-2 for
undiluted wastewater sample with gold/cobalt oxide nanoparticles
including system.
Abstract: Vehicular Adhoc Network (VANET) is a new
technology which aims to ensure intelligent inter-vehicle
communications, seamless internet connectivity leading to improved
road safety, essential alerts, and access to comfort and entertainment.
VANET operations are hindered by mobile node’s (vehicles)
uncertain mobility. Routing algorithms use metrics to evaluate which
path is best for packets to travel. Metrics like path length (hop count),
delay, reliability, bandwidth, and load determine optimal route. The
proposed scheme exploits link quality, traffic density, and
intersections as routing metrics to determine next hop. This study
enhances Geographical Routing Protocol (GRP) using fuzzy
controllers while rules are optimized with Bee Swarm Optimization
(BSO). Simulations results are compared to conventional GRP.
Abstract: This study was developed to compare the behavior
and the ability of polymer foam composites towards sound absorption
test of Shorea leprosula wood (SL) of acid hydrolysis treatment with
particle size
Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.