Abstract: Determination of genetic variation is useful for plant
breeding and hence production of more efficient plant species under
different conditions, like drought stress. In this study a sample of 28
recombinant inbred lines (RILs) of wheat developed from the cross of
Norstar and Zagross varieties, together with their parents, were
evaluated for two years (2010-2012) under normal and water stress
conditions using split plot design with three replications. Main plots
included two irrigation treatments of 70 and 140 mm evaporation
from Class A pan and sub-plots consisted of 30 genotypes. The effect
of genotypes and interaction of genotypes with years and water
regimes were significant for all characters. Significant genotypic
effect implies the existence of genetic variation among the lines
under study. Heritability estimates were high for 1000 grain weight
(0.87). Biomass and grain yield showed the lowest heritability values
(0.42 and 0.50, respectively). Highest genotypic and phenotypic
coefficients of variation (GCV and PCV) belonged to harvest index.
Moderate genetic advance for most of the traits suggested the
feasibility of selection among the RILs under investigation. Some
RILs were higher yielding than either parent at both environments.
Abstract: In this paper, we provided a literature survey on the
artificial stock problem (ASM). The paper began by exploring the
complexity of the stock market and the needs for ASM. ASM
aims to investigate the link between individual behaviors (micro
level) and financial market dynamics (macro level). The variety of
patterns at the macro level is a function of the AFM complexity. The
financial market system is a complex system where the relationship
between the micro and macro level cannot be captured analytically.
Computational approaches, such as simulation, are expected to
comprehend this connection. Agent-based simulation is a simulation
technique commonly used to build AFMs. The paper proceeds by
discussing the components of the ASM. We consider the roles
of behavioral finance (BF) alongside the traditionally risk-averse
assumption in the construction of agent’s attributes. Also, the
influence of social networks in the developing of agents interactions is
addressed. Network topologies such as a small world, distance-based,
and scale-free networks may be utilized to outline economic
collaborations. In addition, the primary methods for developing
agents learning and adaptive abilities have been summarized.
These incorporated approach such as Genetic Algorithm, Genetic
Programming, Artificial neural network and Reinforcement Learning.
In addition, the most common statistical properties (the stylized facts)
of stock that are used for calibration and validation of ASM are
discussed. Besides, we have reviewed the major related previous
studies and categorize the utilized approaches as a part of these
studies. Finally, research directions and potential research questions
are argued. The research directions of ASM may focus on the macro
level by analyzing the market dynamic or on the micro level by
investigating the wealth distributions of the agents.
Abstract: We used live E. coli containing synthetic genetic
oscillators to study how the degree of synchrony between the genetic
circuits of sister cells changes with temperature. We found that both
the mean and the variability of the degree of synchrony between the
fluorescence signals from sister cells are affected by temperature.
Also, while most pairs of sister cells were found to be highly
synchronous in each condition, the number of asynchronous pairs
increased with increasing temperature, which was found to be due to
disruptions in the oscillations. Finally we provide evidence that these
disruptions tend to affect multiple generations as opposed to
individual cells. These findings provide insight in how to design
more robust synthetic circuits and in how cell division can affect their
dynamics.
Abstract: This study, for its research subjects, uses patients who
had undergone total knee replacement surgery from the database of the
National Health Insurance Administration. Through the review of
literatures and the interviews with physicians, important factors are
selected after careful screening. Then using Cross Entropy Method,
Genetic Algorithm Logistic Regression, and Particle Swarm
Optimization, the weight of each factor is calculated and obtained. In
the meantime, Excel VBA and Case Based Reasoning are combined
and adopted to evaluate the system. Results show no significant
difference found through Genetic Algorithm Logistic Regression and
Particle Swarm Optimization with over 97% accuracy in both
methods. Both ROC areas are above 0.87. This study can provide
critical reference to medical personnel as clinical assessment to
effectively enhance medical care quality and efficiency, prevent
unnecessary waste, and provide practical advantages to resource
allocation to medical institutes.
Abstract: This paper proposed the comparison made between
Multi-Carrier Pulse Width Modulation, Sinusoidal Pulse Width
Modulation and Selective Harmonic Elimination Pulse Width
Modulation technique for minimization of Total Harmonic Distortion
in Cascaded H-Bridge Multi-Level Inverter. In Multicarrier Pulse
Width Modulation method by using Alternate Position of Disposition
scheme for switching pulse generation to Multi-Level Inverter.
Another carrier based approach; Sinusoidal Pulse Width Modulation
method is also implemented to define the switching pulse generation
system in the multi-level inverter. In Selective Harmonic Elimination
method using Genetic Algorithm and Particle Swarm Optimization
algorithm for define the required switching angles to eliminate low
order harmonics from the inverter output voltage waveform and
reduce the total harmonic distortion value. So, the results validate that
the Selective Harmonic Elimination Pulse Width Modulation method
does capably eliminate a great number of precise harmonics and
minimize the Total Harmonic Distortion value in output voltage
waveform in compared with Multi-Carrier Pulse Width Modulation
method, Sinusoidal Pulse Width Modulation method. In this paper,
comparison of simulation results shows that the Selective Harmonic
Elimination method can attain optimal harmonic minimization
solution better than Multi-Carrier Pulse Width Modulation method,
Sinusoidal Pulse Width Modulation method.
Abstract: In this paper we propose a computer-aided solution
with Genetic Algorithms in order to reduce the drafting of reports:
FMEA analysis and Control Plan required in the manufacture of the
product launch and improved knowledge development teams for
future projects. The solution allows to the design team to introduce
data entry required to FMEA. The actual analysis is performed using
Genetic Algorithms to find optimum between RPN risk factor and
cost of production. A feature of Genetic Algorithms is that they are
used as a means of finding solutions for multi criteria optimization
problems. In our case, along with three specific FMEA risk factors is
considered and reduce production cost. Analysis tool will generate
final reports for all FMEA processes. The data obtained in FMEA
reports are automatically integrated with other entered parameters in
Control Plan. Implementation of the solution is in the form of an
application running in an intranet on two servers: one containing
analysis and plan generation engine and the other containing the
database where the initial parameters and results are stored. The
results can then be used as starting solutions in the synthesis of other
projects. The solution was applied to welding processes, laser cutting
and bending to manufacture chassis for buses. Advantages of the
solution are efficient elaboration of documents in the current project
by automatically generating reports FMEA and Control Plan using
multiple criteria optimization of production and build a solid
knowledge base for future projects. The solution which we propose is
a cheap alternative to other solutions on the market using Open
Source tools in implementation.
Abstract: The paper develops a Non-Linear Model Predictive
Control (NMPC) of water quality in Drinking Water Distribution
Systems (DWDS) based on the advanced non-linear quality dynamics
model including disinfections by-products (DBPs). A special attention
is paid to the analysis of an impact of the flow trajectories prescribed
by an upper control level of the recently developed two-time scale
architecture of an integrated quality and quantity control in DWDS.
The new quality controller is to operate within this architecture in the
fast time scale as the lower level quality controller. The controller
performance is validated by a comprehensive simulation study based
on an example case study DWDS.
Abstract: The Economic Lot Scheduling Problem (ELSP) is a
valuable mathematical model that can support decision-makers to
make scheduling decisions. The basic period approach is effective for
solving the ELSP. The assumption for applying the basic period
approach is that a product must use its maximum production rate to be
produced. However, a product can lower its production rate to reduce
the average total cost when a facility has extra idle time. The past
researches discussed how a product adjusts its production rate under
the common cycle approach. To the best of our knowledge, no studies
have addressed how a product lowers its production rate under the
basic period approach. This research is the first paper to discuss this
topic. The research develops a simple fixed rate approach that adjusts
the production rate of a product under the basic period approach to
solve the ELSP. Our numerical example shows our approach can find a
better solution than the traditional basic period approach. Our
mathematical model that applies the fixed rate approach under the
basic period approach can serve as a reference for other related
researches.
Abstract: In a practical power system, the power plants are not
located at the same distance from the center of loads and their fuel
costs are different. Also, under normal operating conditions, the
generation capacity is more than the total load demand and losses.
Thus, there are many options for scheduling generation. In an
interconnected power system, the objective is to find the real and
reactive power scheduling of each power plant in such a way as to
minimize the operating cost. This means that the generator’s real and
reactive powers are allowed to vary within certain limits so as to meet
a particular load demand with minimum fuel cost. This is called
optimal power flow problem. In this paper, Economic Load Dispatch
(ELD) of real power generation is considered. Economic Load
Dispatch (ELD) is the scheduling of generators to minimize total
operating cost of generator units subjected to equality constraint of
power balance within the minimum and maximum operating limits of
the generating units. In this paper, genetic algorithms are considered.
ELD solutions are found by solving the conventional load flow
equations while at the same time minimizing the fuel costs.
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 grain quality of chickpea in Iran is low and
instable, which may be attributed to the evolution of cultivars with a
narrow genetic base making them vulnerable to biotic stresses. Four
chickpea varieties from diverse geographic origins were chosen and
arranged in a randomized complete block design. Mesorhizobium sp.
cicer strain SW7 was added to all the chickpea seeds. Chickpea seeds
were planted on October 9, 2013. Each genotype was sown 5 m in
length, with 35 cm inter-row spacing, in 3 rows. Weeds were
removed manually in all plots. Results showed that Analysis of
variance on the studied traits showed significant differences among
genotypes for N, P, K and Fe contents of chickpea, but there is not a
significant difference among Ca, Zn and Mg continents of chickpea.
The experimental coefficient of variation (CV) varied from 7.3 to
15.8. In general, the CV value lower than 20% is considered to be
good, indicating the accuracy of conducted experiments. The highest
grain N was observed in Hashem and Jam cultivars. The highest grain
P was observed in Jam cultivar. Phosphorus content (mg/100g)
ranged from 142.3 to 302.3 with a mean value of 221.3. The negative
correlation (-0.126) was observed between the N and P of chickpea
cultivars. The highest K and Fe contents were observed in Jam
cultivar.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: Availability of different genetic tests after completion
of Human Genome Project increases the physicians’ responsibility to
keep themselves update on the potential implementation of these
genetic tests in their daily practice. However, due to numbers of
barriers, still many of physicians are not either aware of these tests or
are not willing to offer or refer their patients for genetic tests. This
study was conducted an anonymous, cross-sectional, mailed-based
survey to develop a primary data of Malaysian physicians’ level of
knowledge and perception of gene profiling. Questionnaire had 29
questions. Total scores on selected questions were used to assess the
level of knowledge. The highest possible score was 11. Descriptive
statistics, one way ANOVA and chi-squared test was used for
statistical analysis. Sixty three completed questionnaires were
returned by 27 general practitioners (GPs) and 36 medical specialists.
Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4).
About 40% of the participants rated themselves as having poor level
of knowledge in genetics in general whilst 60% believed that they
have fair level of knowledge; however, almost half (46%) of the
respondents felt that they were not knowledgeable about available
genetic tests. A majority (94%) of the responders were not aware of
any lab or company which is offering gene profiling services in
Malaysia. Only 4% of participants were aware of using gene profiling
for detection of dosage of some drugs. Respondents perceived greater
utility of gene profiling for breast cancer (38%) compared to the
colorectal familial cancer (3%). The score of knowledge ranged from
2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score
of knowledge of GPs and specialists were observed, with score of
4.19 and 4.58 respectively. There was no significant association
between any demographic factors and level of knowledge. However,
those who graduated between years 2001 to 2005 had higher level of
knowledge. Overall, 83% of participants showed relatively high level
of perception on value of gene profiling to detect patient’s risk of
disease. However, low perception was observed for both statements
of using gene profiling for general population in order to alter their
lifestyle (25%) as well as having the full sequence of a patient
genome for the purpose of determining a patient’s best match for
treatment (18%). The lack of clinical guidelines, limited provider
knowledge and awareness, lack of time and resources to educate
patients, lack of evidence-based clinical information and cost of tests
were the most barriers of ordering gene profiling mentioned by
physicians. In conclusion Malaysian physicians who participate in
this study had mediocre level of knowledge and awareness in gene
profiling. The low exposure to the genetic questions and problems
might be a key predictor of lack of awareness and knowledge on
available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling
into practice for eligible patients.
Abstract: Family has a crucial role in maintaining the
physical, social and mental health of the children. Most of the
mental and anxiety problems of children reflect the complex
interpersonal situations among family members, especially parents.
In other words, anxiety problems of the children are correlated
with deficit relationships of family members and improper
childrearing styles. The parental child rearing styles leads to
positive and negative consequences which affect the children’s
mental health. Therefore, the present research was aimed to
compare the parental childrearing styles and anxiety of children
with stuttering and normal population. It was also aimed to study
the relationship between parental child rearing styles and anxiety
of children. The research sample included 54 boys with stuttering
and 54 normal boys who were selected from the children (boys) of
Tehran, Iran in the age range of 5 to 8 years in 2013. In order to
collect data, Baum-rind Childrearing Styles Inventory and Spence
Parental Anxiety Inventory were used. Appropriate descriptive
statistical methods and multivariate variance analysis and t test for
independent groups were used to test the study hypotheses.
Statistical data analyses demonstrated that there was a significant
difference between stuttering boys and normal boys in anxiety (t =
7.601, p< 0.01); but there was no significant difference between
stuttering boys and normal boys in parental childrearing styles (F =
0.129). There was also not found significant relationship between
parental childrearing styles and children anxiety (F = 0.135, p<
0.05). It can be concluded that the influential factors of children’s
society are parents, school, teachers, peers and media. So, parental
childrearing styles are not the only influential factors on anxiety of
children, and other factors including genetic, environment and
child experiences are effective in anxiety as well. Details are
discussed.
Abstract: The aim of this paper is to present the optimization
methodology developed in the frame of a Coastal Transport
Information System. The system will be used for the effective design
of coastal transportation lines and incorporates subsystems that
implement models, tools and techniques that may support the design
of improved networks. The role of the optimization and decision
subsystem is to provide the user with better and optimal scenarios
that will best fulfill any constrains, goals or requirements posed. The
complexity of the problem and the large number of parameters and
objectives involved led to the adoption of an evolutionary method
(Genetic Algorithms). The problem model and the subsystem
structure are presented in detail, and, its support for simulation is also
discussed.
Abstract: To study the effect of the cross direction in bead
wheat, three hybrid combinations (Babyle 113, Iratome), (Sawa,
Tamose2) and (Al Hashymya, Al Iraq) were tested for plant height,
spike and awn length, number of grains per spike, 1000-grain weight,
number of tillers/m and grain yield. The results revealed that the
direction of the crosses significantly effect on the number of
grains/spike, number of tillers/m and grain yields. Grain yield was
positively and significantly correlated with 1000-grain weight,
number of grains per spike and tillers. Depend on the results of
heritability and genetic advance it was suggested that 1000-grain
weight, number of grains per spike and tillers should be given
emphasis for future wheat yield improvement programs.
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: Power systems are operating under stressed condition
due to continuous increase in demand of load. This can lead to
voltage instability problem when face additional load increase or
contingency. In order to avoid voltage instability suitable size of
reactive power compensation at optimal location in the system is
required which improves the load margin. This work aims at
obtaining optimal size as well as location of compensation in the 39-
bus New England system with the help of Bacteria Foraging and
Genetic algorithms. To reduce the computational time the work
identifies weak candidate buses in the system, and then picks only
two of them to take part in the optimization. The objective function is
based on a recently proposed voltage stability index which takes into
account the weighted average sensitivity index is a simpler and faster
approach than the conventional CPF algorithm. BFOA has been
found to give better results compared to GA.
Abstract: The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.