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: 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: This paper discusses the undesirable charge transfer
through the parasitic capacitances of the input transistors in a
multi-inputs voltage sense amplifier. Its intrinsic rail-to-rail voltage
transitions at the output nodes inevitably disturb the input sides
through the capacitive coupling between the outputs and inputs. Then,
it can possible degrade the stabilities of the reference voltage levels.
Moreover, it becomes more serious in multi-channel systems by
altering them for other channels, and so degrades the linearity of the
overall systems. In order to alleviate the internal node voltage
transition, the internal node stabilization techniques are proposed. It
achieves 45% and 40% improvements for node stabilization and input
referred disturbance, respectively.
Abstract: The research studies the behaviors based on
sufficiency economy philosophy at individual and community
levelsas well as the satisfaction of the urban community leaders by
collecting data with purposive sampling technique. For in-depth
interviews with 26 urban community leaders, the result shows that
the urban community leaders have good knowledge and
understanding about sufficiency economy philosophy. Especially in
terms of money spending, they must consider the need for living and
be economical. The activities in the community or society should not
take advantage of the others as well as colleagues. At present, most of
the urban community leaders live in sufficient way. They often spend
time with public service, but many families are dealing with debt.
Many communities have some political conflict and high family
allowances because of living in the urban communities with rapid
social and economic changes. However, there are many communities
that leaders have applied their wisdom in development for their
people by gathering and grouping the professionals to form activities
such as making chilli sauce, textile organization, making artificial
flowers to worship the sanctity. The most prominent group is the foot
massage business in Wat Pracha Rabue Tham. This professional
group is supported continuously by the government. One of the
factors in terms of satisfaction used for evaluating community leaders
is the customary administration in brotherly, interdependent way
rather than using the absolute power or controlling power, but using
the roles of leader to perform the activities with their people intently,
determinedly and having public mind for people.
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: 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: 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: 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: The main aim of this research was to investigate a
prototype bamboo shading device. There were two objectives to this
study: first, to investigate the effects of non-chemical treatments on
bamboo shading devices damaged by powder-post beetles and fungi,
and second to develop a prototype bamboo shading device. This
study of the effects of non-chemical treatments on bamboo shading
devices damage by powder-post beetles in the laboratory showed
that, among seven treatments tested, wood vinegar treatment can
protect powder-post beetles better than the original method by up to
92.91%. It was also found that wood vinegar treatment shows the
best performance in fungi protection and works better than the
original method by up to 40%. A second experiment was carried out
by constructing four bamboo shading devices and installing them on
a building for 28 days. All aspects of shading device were
investigated in terms of their beauty, durability, and ease of
construction and assembly. The final prototype was developed from
the lessons learned from the test results. In conclusion, this study
showed the effectiveness of some natural preservatives against insect
and fungi damage, and it also illustrated the characteristics of a
prototype bamboo shading device that can be constructed by rural
workers within one week.
Abstract: The organizations in the knowledge economy era have
recognized the importance of building knowledge assets for
sustainable growth and development. In comparison to other
industries, Information Technology (IT) enterprises, holds an edge in
developing an effective Knowledge Management (KM) programmethanks
to their in-house technological abilities. This paper tries to
study the various knowledge based incentive programmes and its
effect on Knowledge Sharing and Learning in the context of the
Indian IT sector. A conceptual model is developed linking KM
Incentives, Knowledge Sharing and Learning. A questionnaire study
is conducted to collect primary data from the knowledge workers of
the IT organizations located in India. The data was analysed using
Structural Equation Modeling using Partial Least Square method. The
results show a strong influence of knowledge management incentives
on knowledge sharing and an indirect influence on learning.
Abstract: In this study, we have focused our attention on
combining of molecular imprinting into nanofilms and QCM
nanosensor approaches and producing QCM nanosensor for anti-
CCP, chosen as model protein, using anti-CCP imprinted nanofilms.
The nonimprinted nanosensor was also prepared to evaluate the
selectivity of the imprinted nanosensor. Anti-CCP imprinted QCM
nanosensor was tested for real time detection of anti-CCP from
aqueous solution. The kinetic and affinity studies were determined by
using anti-CCP solutions with different concentrations. The
responses related with mass shifts (%m) and frequency shifts (%f)
were used to evaluate adsorption properties. To show the selectivity
of the anti-CCP imprinted QCM nanosensor, competitive adsorption
of anti-CCP and IgM was investigated. The results indicate that anti-
CCP imprinted QCM nanosensor has higher adsorption capabilities
for anti-CCP than for IgM, due to selective cavities in the polymer
structure.
Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
Abstract: Environmental impact assessment techniques have
been developed as a result of the worldwide efforts to reduce the
environmental impact of global warming. By using the quantification
method in the construction industry, it is now possible to manage the
greenhouse gas is to systematically evaluate the impact on the
environment over the entire construction process. In particular, the
proportion of greenhouse gas emissions at the production stage of
construction material occupied is high, and efforts are needed in
particular in the construction field.
In this research, intended for concrete products for the construction
materials, by using the LCA method, we compared the results of
environmental impact assessment and carbon emissions of developing
products that have been applied low-carbon technologies compared to
existing products. As a results, by introducing a raw material of
industrial waste, showed carbon reduction. Through a comparison of
the carbon emission reduction effect of low carbon technologies, it is
intended to provide academic data for the evaluation of greenhouse
gases in the construction sector and the development of low carbon
technologies of the future.
Abstract: The purpose of this paper is to examine the hypothesis
explaining the mechanism in the case, where the product is deleted or
reduced the fundamental function of the product through the product
concept changes in the digital camera industry. This paper points out
not owning the fundamental technology might cause the change of the
product concept. Casio could create new competitive factor so that this
paper discusses a possibility of the mechanism of changing the product
concept.
Abstract: Large-scale data stream analysis has become one of
the important business and research priorities lately. Social networks
like Twitter and other micro-blogging platforms hold an enormous
amount of data that is large in volume, velocity and variety.
Extracting valuable information and trends out of these data would
aid in a better understanding and decision-making. Multiple analysis
techniques are deployed for English content. Moreover, one of the
languages that produce a large amount of data over social networks
and is least analyzed is the Arabic language. The proposed paper is a
survey on the research efforts to analyze the Arabic content in
Twitter focusing on the tools and methods used to extract the
sentiments for the Arabic content on Twitter.
Abstract: In this paper, an analysis of some model order
reduction techniques is presented. A new hybrid algorithm for model
order reduction of linear time invariant systems is compared with the
conventional techniques namely Balanced Truncation, Hankel Norm
reduction and Dominant Pole Algorithm (DPA). The proposed hybrid
algorithm is known as Clustering Dominant Pole Algorithm (CDPA),
is able to compute the full set of dominant poles and its cluster center
efficiently. The dominant poles of a transfer function are specific
eigenvalues of the state space matrix of the corresponding dynamical
system. The effectiveness of this novel technique is shown through
the simulation results.