Abstract: Potassium borates, which are widely used in welding
and metal refining industry, as a lubricating oil additive, cement
additive, fiberglass additive and insulation compound, are one of the
important groups of borate minerals. In this study the production of a
potassium borate mineral via hydrothermal method is aimed. The
potassium source of potassium nitrate (KNO3) was used along with a
sodium source of sodium hydroxide (NaOH) and boron source of
boric acid (H3BO3). The constant parameters of reaction temperature
and reaction time were determined as 80°C and 1 h, respectively. The
molar ratios of 1:1:3 (as KNO3:NaOH:H3BO3), 1:1:4, 1:1:5, 1:1:6
and 1:1:7 were used. Following the synthesis the identifications of
the produced products were conducted by X-Ray Diffraction (XRD),
Fourier Transform Infrared Spectroscopy (FT-IR) and Raman
Spectroscopy. The results of the experiments and analysis showed in
the ratio of 1:1:6, the Santite mineral with powder diffraction file
number (pdf no.) of 01-072-1688, which is known as potassium
pentaborate (KB5O8·4H2O) was synthesized as best.
Abstract: The purpose of the paper is to estimate the US small
wind turbines market potential and forecast the small wind turbines
sales in the US. The forecasting method is based on the application of
the Bass model and the generalized Bass model of innovations
diffusion under replacement purchases. In the work an exponential
distribution is used for modeling of replacement purchases. Only one
parameter of such distribution is determined by average lifetime of
small wind turbines. The identification of the model parameters is
based on nonlinear regression analysis on the basis of the annual
sales statistics which has been published by the American Wind
Energy Association (AWEA) since 2001 up to 2012. The estimation
of the US average market potential of small wind turbines (for
adoption purchases) without account of price changes is 57080
(confidence interval from 49294 to 64866 at P = 0.95) under average
lifetime of wind turbines 15 years, and 62402 (confidence interval
from 54154 to 70648 at P = 0.95) under average lifetime of wind
turbines 20 years. In the first case the explained variance is 90,7%,
while in the second - 91,8%. The effect of the wind turbines price
changes on their sales was estimated using generalized Bass model.
This required a price forecast. To do this, the polynomial regression
function, which is based on the Berkeley Lab statistics, was used. The
estimation of the US average market potential of small wind turbines
(for adoption purchases) in that case is 42542 (confidence interval
from 32863 to 52221 at P = 0.95) under average lifetime of wind
turbines 15 years, and 47426 (confidence interval from 36092 to
58760 at P = 0.95) under average lifetime of wind turbines 20 years.
In the first case the explained variance is 95,3%, while in the second
– 95,3%.
Abstract: Due to the continuous increment of the load demand,
identification of weaker buses, improvement of voltage profile and
power losses in the context of the voltage stability problems has
become one of the major concerns for the larger, complex,
interconnected power systems. The objective of this paper is to
review the impact of Flexible AC Transmission System (FACTS)
controller in Wind generators connected electrical network for
maintaining voltage stability. Wind energy could be the growing
renewable energy due to several advantages. The influence of wind
generators on power quality is a significant issue; non uniform power
production causes variations in system voltage and frequency.
Therefore, wind farm requires high reactive power compensation; the
advances in high power semiconducting devices have led to the
development of FACTS. The FACTS devices such as for example
SVC inject reactive power into the system which helps in maintaining
a better voltage profile. The performance is evaluated on an IEEE 14
bus system, two wind generators are connected at low voltage buses
to meet the increased load demand and SVC devices are integrated at
the buses with wind generators to keep voltage stability. Power
flows, nodal voltage magnitudes and angles of the power network are
obtained by iterative solutions using MIPOWER.
Abstract: Durian is the flagship fruit of Mindanao and there is
an abundance of several cultivars with many confusing identities/
names.
The project was conducted to develop procedure for reliable and
rapid detection and sorting of durian planting materials. Moreover, it
is also aimed to establish specific genetic or DNA markers for routine
testing and authentication of durian cultivars in question.
The project developed molecular procedures for routine testing.
SSR primers were also screened and identified for their utility in
discriminating durian cultivars collected.
Results of the study showed the following accomplishments:
1. Twenty (29) SSR primers were selected and identified based on
their ability to discriminate durian cultivars,
2. Optimized and established standard procedure for identification
and authentication of Durian cultivars
3. Genetic profile of durian is now available at Biotech Unit
Our results demonstrate the relevance of using molecular
techniques in evaluating and identifying durian clones. The most
polymorphic primers tested in this study could be useful tools for
detecting variation even at the early stage of the plant especially for
commercial purposes. The process developed combines the efficiency
of the microsatellites development process with the optimization of
non-radioactive detection process resulting in a user-friendly protocol
that can be performed in two (2) weeks and easily incorporated into
laboratories about to start microsatellite development projects. This
can be of great importance to extend microsatellite analyses to other
crop species where minimal genetic information is currently
available. With this, the University can now be a service laboratory
for routine testing and authentication of durian clones.
Abstract: The secondary alloy A226 is used for many
automotive casting produced by mould casting and high pressure die
casting. This alloy has excellent castability, good mechanical
properties and cost-effectiveness. Production of primary aluminium
alloys belong to heavy source fouling of life environs. The European
Union calls for the emission reduction and reduction in energy
consumption therefore increase production of recycled (secondary)
aluminium cast alloys. The contribution is deal with influence of
recycling on the quality of the casting made from A226 in automotive
industry. The properties of the casting made from secondary
aluminium alloys were compared with the required properties of
primary aluminium alloys. The effect of recycling on microstructure
was observed using combination different analytical techniques (light
microscopy upon black-white etching, scanning electron microscopy
- SEM upon deep etching and energy dispersive X-ray analysis -
EDX). These techniques were used for the identification of the
various structure parameters, which was used to compare secondary
alloy microstructure with primary alloy microstructure.
Abstract: Polymer Electrolyte Membrane Fuel Cell (PEMFC) is
such a time-vary nonlinear dynamic system. The traditional linear
modeling approach is hard to estimate structure correctly of PEMFC
system. From this reason, this paper presents a nonlinear modeling of
the PEMFC using Neural Network Auto-regressive model with
eXogenous inputs (NNARX) approach. The multilayer perception
(MLP) network is applied to evaluate the structure of the NNARX
model of PEMFC. The validity and accuracy of NNARX model are
tested by one step ahead relating output voltage to input current from
measured experimental of PEMFC. The results show that the obtained
nonlinear NNARX model can efficiently approximate the dynamic
mode of the PEMFC and model output and system measured output
consistently.
Abstract: The article presents two mathematical models of the
interaction between a rotating shaft and an incompressible fluid. The
mathematical model includes both the journal bearings and the
axially traversed hydrodynamic sealing gaps of hydraulic machines.
A method is shown for the identification of additional effects of the
fluid acting on the rotor of the machine, both for a linear and a nonlinear
model. The interaction is expressed by matrices of mass,
stiffness and damping.
Abstract: In the present work, Electrochemical Impedance
Spectrocopy (EIS) is applied to study the transport of different metal
cations through a cation-exchange membrane. This technique enables
the identification of the ionic-transport characteristics and to
distinguish between different transport mechanisms occurring at
different current density ranges. The impedance spectra are
dependent on the applied dc current density, on the type of cation and
on the concentration.
When the applied dc current density increases, the diameter of the
impedance spectra loops increases because all the components of
membrane system resistance increase. The diameter of the impedance
plots decreases in the order of Na(I), Ni(II) and Cr(III) due to the
increased interactions between the negatively charged sulfonic
groups of the membrane and the cations with greater charge. Nyquist
plots are shifted towards lower values of the real impedance, and its
diameter decreases with the increase of concentration due to the
decrease of the solution resistance.
Abstract: The authors propose the identification, analysis and
prognosis of the quantitative and qualitative evolution of the elderly
population in the functional urban areas. The present paper takes into
account the analysis of some representative indicators (the weight of
the elderly population, ageing index, dynamic index of economic
ageing of productive population etc.) and the elaboration of an
integrated indicator that would help differentiate the population
ageing forms in the 48 functional urban areas that were defined based
on demographic and social-economic criteria for all large and
medium cities in Romania.
Abstract: A total of 115 yeast strains isolated from local cassava
processing wastes were measured for crude protein content. Among
these strains, the strain MSY-2 possessed the highest protein
concentration (>3.5 mg protein/mL). By using molecular
identification tools, it was identified to be a strain of Pichia
kudriavzevii based on similarity of D1/D2 domain of 26S rDNA
region. In this study, to optimize the protein production by MSY-2
strain, Response Surface Methodology (RSM) was applied. The
tested parameters were the carbon content, nitrogen content, and
incubation time. Here, the value of regression coefficient (R2) =
0.7194 could be explained by the model which is high to support the
significance of the model. Under the optimal condition, the protein
content was produced up to 3.77 g per L of the culture and MSY-2
strain contains 66.8 g protein per 100 g of cell dry weight. These
results revealed the plausibility of applying the novel strain of yeast
in single-cell protein production.
Abstract: The paper presents a new method for efficient
innovation process management. Even though the innovation
management methods, tools and knowledge are well established and
documented in literature, most of the companies still do not manage it
efficiently. Especially in SMEs the front end of innovation - problem
identification, idea creation and selection - is often not optimally
performed. Our eMIPS methodology represents a sort of "umbrella
methodology" - a well-defined set of procedures, which can be
dynamically adapted to the concrete case in a company. In daily
practice, various methods (e.g. for problem identification and idea
creation) can be applied, depending on the company's needs. It is
based on the proactive involvement of the company's employees
supported by the appropriate methodology and external experts. The
presented phases are performed via a mixture of face-to-face
activities (workshops) and online (eLearning) activities taking place
in eLearning Moodle environment and using other e-communication
channels. One part of the outcomes is an identified set of
opportunities and concrete solutions ready for implementation. The
other also very important result is connected to innovation
competences for the participating employees related with concrete
tools and methods for idea management. In addition, the employees
get a strong experience for dynamic, efficient and solution oriented
managing of the invention process. The eMIPS also represents a way
of establishing or improving the innovation culture in the
organization. The first results in a pilot company showed excellent
results regarding the motivation of participants and also as to the
results achieved.
Abstract: The paper is focused on the identification of limiting
environmental factors of individual industrial floors on which newly
developed polymer protection and repair systems with the use of
secondary raw materials will be used. These mainly include floors
with extreme stresses and special requirements for materials used. In
relation to the environment of a particular industrial floor, it is
necessary to ensure, for example, chemical stability, resistance to
higher temperatures, resistance to higher mechanical stress, etc. for
developed materials, which is reflected in the demands for the
developed material systems. The paper describes individual
environments and, in relation to them, also requirements for
individual components of the developed materials and for the
developed materials as a whole.
Abstract: This paper presents a part of the project solving which
is dedicated to the identification of the hazardous waste with the most
critical production within the Czech Republic with the aim to study
and find the optimal composition of the cement matrix that will
ensure maximum content disposal of chosen hazardous waste. In the
first stage of project solving – which represents this paper – a specific
hazardous waste was chosen, its properties were identified and
suitable solidification agents were chosen. Consequently
solidification formulas and testing methodology was proposed.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: Soil quality monitoring is a science-based soil
management tool that assesses soil ecosystem health.
A soil monitoring program in Auckland, New Zealand’s largest
city extends from 1995 to the present. The objective of this study was
to firstly determine changes in soil parameters (basic soil properties
and heavy metals) that were assessed from rural land in 1995-2000
and repeated in 2008-2012. The second objective was to determine
differences in soil parameters across various land uses including
native bush, rural (horticulture, pasture and plantation forestry) and
urban land uses using soil data collected in more recent years (2009-
2013).
Across rural land, mean concentrations of Olsen P had
significantly increased in the second sampling period and was
identified as the indicator of most concern, followed by soil
macroporosity, particularly for horticultural and pastoral land. Mean
concentrations of Cd were also greatest for pastoral and horticultural
land and a positive correlation existed between these two parameters,
which highlights the importance of analysing basic soil parameters in
conjunction with heavy metals. In contrast, mean concentrations of
As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites
had the lowest concentrations of heavy metals and were used to
calculate a ‘pollution index’ (PI). The mean PI was classified as high
(PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As and Hg,
indicating high levels of heavy metal pollution across both rural and
urban soils. From a land use perspective, the mean ‘integrated
pollution index’ was highest for urban sites at 2.9 followed by
pasture, horticulture and plantation forests at 2.7, 2.6 and 0.9,
respectively.
It is recommended that soil sampling continues over time because
a longer spanning record will allow further identification of where
soil problems exist and where resources need to be targeted in the
future. Findings from this study will also inform policy and science
direction in regional councils.
Abstract: The key role in phenomenological modelling of cyclic
plasticity is good understanding of stress-strain behaviour of given
material. There are many models describing behaviour of materials
using numerous parameters and constants. Combination of individual
parameters in those material models significantly determines whether
observed and predicted results are in compliance. Parameter
identification techniques such as random gradient, genetic algorithm
and sensitivity analysis are used for identification of parameters using
numerical modelling and simulation. In this paper genetic algorithm
and sensitivity analysis are used to study effect of 4 parameters of
modified AbdelKarim-Ohno cyclic plasticity model. Results
predicted by Finite Element (FE) simulation are compared with
experimental data from biaxial ratcheting test with semi-elliptical
loading path.
Abstract: This work deals with parameter identification of
permanent magnet motors, a class of ac motor which is particularly
important in industrial automation due to characteristics like
applications high performance, are very attractive for applications
with limited space and reducing the need to eliminate because they
have reduced size and volume and can operate in a wide speed range,
without independent ventilation. By using experimental data and
genetic algorithm we have been able to extract values for both the
motor inductance and the electromechanical coupling constant, which
are then compared to measured and/or expected values.
Abstract: Due to the rapid increase of Internet, web opinion
sources dynamically emerge which is useful for both potential
customers and product manufacturers for prediction and decision
purposes. These are the user generated contents written in natural
languages and are unstructured-free-texts scheme. Therefore, opinion
mining techniques become popular to automatically process customer
reviews for extracting product features and user opinions expressed
over them. Since customer reviews may contain both opinionated and
factual sentences, a supervised machine learning technique applies
for subjectivity classification to improve the mining performance. In
this paper, we dedicate our work is the task of opinion
summarization. Therefore, product feature and opinion extraction is
critical to opinion summarization, because its effectiveness
significantly affects the identification of semantic relationships. The
polarity and numeric score of all the features are determined by
Senti-WordNet Lexicon. The problem of opinion summarization
refers how to relate the opinion words with respect to a certain
feature. Probabilistic based model of supervised learning will
improve the result that is more flexible and effective.
Abstract: Development of a method to estimate gene functions is
an important task in bioinformatics. One of the approaches for the
annotation is the identification of the metabolic pathway that genes are
involved in. Since gene expression data reflect various intracellular
phenomena, those data are considered to be related with genes’
functions. However, it has been difficult to estimate the gene function
with high accuracy. It is considered that the low accuracy of the
estimation is caused by the difficulty of accurately measuring a gene
expression. Even though they are measured under the same condition,
the gene expressions will vary usually. In this study, we proposed a
feature extraction method focusing on the variability of gene
expressions to estimate the genes' metabolic pathway accurately. First,
we estimated the distribution of each gene expression from replicate
data. Next, we calculated the similarity between all gene pairs by KL
divergence, which is a method for calculating the similarity between
distributions. Finally, we utilized the similarity vectors as feature
vectors and trained the multiclass SVM for identifying the genes'
metabolic pathway. To evaluate our developed method, we applied the
method to budding yeast and trained the multiclass SVM for
identifying the seven metabolic pathways. As a result, the accuracy
that calculated by our developed method was higher than the one that
calculated from the raw gene expression data. Thus, our developed
method combined with KL divergence is useful for identifying the
genes' metabolic pathway.