Abstract: The shortest path routing problem is a multiobjective
nonlinear optimization problem with constraints. This problem has
been addressed by considering Quality of service parameters, delay
and cost objectives separately or as a weighted sum of both
objectives. Multiobjective evolutionary algorithms can find multiple
pareto-optimal solutions in one single run and this ability makes them
attractive for solving problems with multiple and conflicting
objectives. This paper uses an elitist multiobjective evolutionary
algorithm based on the Non-dominated Sorting Genetic Algorithm
(NSGA), for solving the dynamic shortest path routing problem in
computer networks. A priority-based encoding scheme is proposed
for population initialization. Elitism ensures that the best solution
does not deteriorate in the next generations. Results for a sample test
network have been presented to demonstrate the capabilities of the
proposed approach to generate well-distributed pareto-optimal
solutions of dynamic routing problem in one single run. The results
obtained by NSGA are compared with single objective weighting
factor method for which Genetic Algorithm (GA) was applied.
Abstract: The main features of NPP-2006/MIR-1200 design are
described. Estimation of individual doses for population under
normal operation and accident conditions is performed for
Leningradskaya NPP – 2 as an example. The radiation effect on
population and environment doesn-t exceed the established
normative limit and is as low as reasonably achievable. NPP-
2006/MIR-1200 design meets all Russian and international
requirements for power units under construction.
Abstract: This paper deals with a delayed single population model on time scales. With the assistance of coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained. Furthermore, the better estimations for bounds of periodic solutions are established.
Abstract: The paper presents the case study of hazard
identification and sensitivity of potential resource of emergency
water supply as part of the application of methodology classifying
the resources of drinking water for emergency supply of population.
The case study has been carried out on a selected resource of
emergency water supply in one region of the Czech Republic. The
hazard identification and sensitivity of potential resource of
emergency water supply is based on a unique procedure and
developed general registers of selected types of hazards and
sensitivities. The registers have been developed with the help of the
“Fault Tree Analysis” method in combination with the “What if
method”. The identified hazards for the assessed resource include
hailstorms and torrential rains, drought, soil erosion, accidents of
farm machinery, and agricultural production. The developed registers
of hazards and vulnerabilities and a semi-quantitative assessment of
hazards for individual parts of hydrological structure and
technological elements of presented drilled wells are the basis for a
semi-quantitative risk assessment of potential resource of emergency
supply of population and the subsequent classification of such
resource within the system of crisis planning.
Abstract: Genetic algorithms (GAs) have been widely used for
global optimization problems. The GA performance depends highly
on the choice of the search space for each parameter to be optimized.
Often, this choice is a problem-based experience. The search space
being a set of potential solutions may contain the global optimum
and/or other local optimums. A bad choice of this search space
results in poor solutions. In this paper, our approach consists in
extending the search space boundaries during the GA optimization,
only when it is required. This leads to more diversification of GA
population by new solutions that were not available with fixed search
space boundaries. So, these dynamic search spaces can improve the
GA optimization performances. The proposed approach is applied to
power system stabilizer optimization for multimachine power system
(16-generator and 68-bus). The obtained results are evaluated and
compared with those obtained by ordinary GAs. Eigenvalue analysis
and nonlinear system simulation results show the effectiveness of the
proposed approach to damp out the electromechanical oscillation and
enhance the global system stability.
Abstract: Evolvable hardware (EHW) refers to a selfreconfiguration
hardware design, where the configuration is under
the control of an evolutionary algorithm (EA). A lot of research has
been done in this area several different EA have been introduced.
Every time a specific EA is chosen for solving a particular problem,
all its components, such as population size, initialization, selection
mechanism, mutation rate, and genetic operators, should be selected
in order to achieve the best results. In the last three decade a lot of
research has been carried out in order to identify the best parameters
for the EA-s components for different “test-problems". However
different researchers propose different solutions. In this paper the
behaviour of mutation rate on (1+λ) evolution strategy (ES) for
designing logic circuits, which has not been done before, has been
deeply analyzed. The mutation rate for an EHW system modifies
values of the logic cell inputs, the cell type (for example from AND
to NOR) and the circuit output. The behaviour of the mutation has
been analyzed based on the number of generations, genotype
redundancy and number of logic gates used for the evolved circuits.
The experimental results found provide the behaviour of the mutation
rate to be used during evolution for the design and optimization of
logic circuits. The researches on the best mutation rate during the last
40 years are also summarized.
Abstract: Recently, the health of retired National Football
League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature ardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar
to National Football league players which suggest that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a
unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based
questionnaire that consisted of medical history and
physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors
(response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8%
(avg 72.4 cigs/wk) whilst the percentage consuming alcohol
was high (93.1% (avg 11.2 drinks/wk). Competitors reported
the following top six chronic diseases/disorders; hypertension
(18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%),
hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with
regard to cancer (all types) and migraines. When compared to
the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a
Climstein Mike, Walsh Joe (corresponding author) and Burke Stephen
School of Exercise Science, Australian Catholic University, 25A Barker Road,
Strathfield, Sydney, NSW, 2016, Australia (e-mail:
[email protected], [email protected],
[email protected]).
John Best is with Orthosports, 160 Belmore Rd., Randwick, Sydney,NSW
2031, Australia (e-mail: [email protected]).
Heazlewood, Ian Timothy is with School of Environmental and Life
Sciences, Faculty Education, Health and Science, Charles Darwin University,
Precinct Yellow Building 2, Charles Darwin University, NT 0909, Australia
(e-mail: [email protected]).
Kettunen Jyrki Arcada University of Applied Sciences, Jan-Magnus
Janssonin aukio 1, FI-00550, Helsinki, Finland (e-mail:
[email protected]).
Adams Kent is with California State University Monterey Bay, Kinesiology Department, 100 Campus Center, Seaside, CA., 93955, USA (email: [email protected]).
DeBeliso Mark is with Department of Physical Education and Human
Performance, Southern Utah University, 351 West University Blvd, Cedar
City, Utah, USA (e-mail: [email protected]).
significantly lower incidence of anxiety (p
Abstract: In this paper, by applying Mawhin-s continuation theorem of coincidence degree theory, we study the existence of almost periodic solutions for neural multi-delay logarithmic population model and obtain one sufficient condition for the existence of positive almost periodic solution for the above equation. An example is employed to illustrate our result.
Abstract: In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.
Abstract: Response to the public health-related emergencies is analysed here for a rural university in South Africa. The structure of the designated emergency plan covers all the phases of the disaster management cycle. The plan contains elements of the vulnerability model and the technocratic model of emergency management. The response structures are vertically and horizontally integrated, while the planning contains elements of scenario-based and functional planning. The available number of medical professionals at the Rhodes University, along with the medical insurance rates, makes the staff and students potentially more medically vulnerable than the South African population. The main improvements of the emergency management are required in the tornado response and the information dissemination during health emergencies. The latter should involve the increased use of social media and e-mails, following the Taylor model of communication. Infrastructure must be improved in the telecommunication sector in the face of unpredictable electricity outages.
Abstract: Genetic Folding (GF) a new class of EA named as is
introduced for the first time. It is based on chromosomes composed
of floating genes structurally organized in a parent form and
separated by dots. Although, the genotype/phenotype system of GF
generates a kernel expression, which is the objective function of
superior classifier. In this work the question of the satisfying
mapping-s rules in evolving populations is addressed by analyzing
populations undergoing either Mercer-s or none Mercer-s rule. The
results presented here show that populations undergoing Mercer-s
rules improve practically models selection of Support Vector
Machine (SVM). The experiment is trained multi-classification
problem and tested on nonlinear Ionosphere dataset. The target of this
paper is to answer the question of evolving Mercer-s rule in SVM
addressed using either genetic folding satisfied kernel-s rules or not
applied to complicated domains and problems.
Abstract: The objective of this research is to study the people’s level of participation in activities of the community, their satisfaction towards the community, the attachment they have to the community, factors that influence the attachment, as well as the characteristics of the relationships of military families’ of the Royal Guards community of Dusit District. The method used was non-probability sampling by quota sampling according to people’s age. The determined age group was 18 years or older.
One set of a sample group was done per family. The questionnaires were conducted by 287 people. Snowball sampling was also used by interviewing people of the community, starting from the Royal Guards Community’s leader, then by 20 of the community’s well-respected persons. The data was analyzed by using descriptive statistics, such as arithmetic mean and standard deviation, as well as by inferential statistics, such as Independent - Samples T test (T-test), One-Way ANOVA (F-test), Chi-Square. Descriptive analysis according to the structure of the interview content was also used. The results of the research is that the participation of the population in the Royal Guards Community in various activities is at a medium level, with the average participation level during Mother’s and Father’s Days. The people’s general level of satisfaction towards the premises of the Royal Guards Community is at the highest level.
The people were most satisfied with the transportation within the community and in contacting with people from outside the premises. The access to the community is convenient and there are various entrances. The attachment of the people to the Royal Guards Community in general and by each category is at a high level. The feeling that the community is their home rated the highest average. Factors that influence the attachment of the people of the Royal Guards Community are age, status, profession, income, length of stay in the community, membership of social groups, having neighbors they feel close and familiar with, and as well as the benefits they receive from the community. In addition, it was found that people that participate in activities have a high level of positive relationship towards the attachment of the people to the Royal Guards Community. The satisfaction of the community has a very high level of positive relationship with the attachment of the people to the Royal Guards Community.
The characteristics of the attachment of military families’ is that they live in big houses that everyone has to protect and care for, starting from the leader of the family as well as all members. Therefore, they all love the community they live in. The characteristics that show the participation of activities within the community and the high level of satisfaction towards the premises of the community will enable the people to be more attached to the community. The people feel that everyone is close neighbors within the community, as if they are one big family.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.
Abstract: Green Forestation Plan (GFP) was expected to promote the reforestation of plains totaling 60,000 has within the first 8 years. Annual subsidies were budgeted at $120,000 per ha, and $2.4 million for 20 years. In this research we have surveyed landlords- opinions toward the GFP in an attempt to understand landlords- incentives for participating in the GFP and their levels of concern and agreement toward the policy design. Based our analysis of landlords- opinions on the policy design, we expect to derive appropriate complementary measures, establish effective promotional schemes, and raise the policy effectiveness of the GFP. According to the results of this research, there was still a relatively high proportion of population who were not aware of GFP; more than 50% of landlords were neutral or willing to participate given high reforestation subsidies; approximately 30% of landlords were unwilling to participate. In terms of the designs of GFP, more than 50% of respondents were concerned and agreed with the policy design. In terms of the period of this policy, 52.7% of respondents indicated that it should be shortened to 15 years or lower. In terms of the amount of the subsidy, 41.7% of respondents showed that it should be raised to approximately $250,000/ha. In terms of land area restrictions, 88.0% of respondents believed that the minimum should be lowered to 0.4 ha. More than 70% of respondents owned less than 0.4 has of land, and since they do not own enough land to be eligible for the program, more than 80% of landlords wished to lower the minimum requirements of land area. In addition, 59.3% of respondents were reluctant to participate in reforestation because their lands were too small to be eligible; 15.0% of respondents were reluctant because the duration was too long. Responses to the question about “how the policy can be adjusted to provide incentives for landlords- participation" revealed that almost 40% of respondents desired higher subsidies. Some policy suggestions are provided as follows: (1) many landlords are still unaware of the GFP so the government should enhance the promotion of the policy; (2) many landlords are unwilling to participate in GFP mainly because they do not own enough lands to be eligible, hence the government should consider adjusting its requirements for minimum agricultural land area; (3) for subsequent promotions on GFP, the government may consider targeting on the landlords with high income and high level of education; (4) because the subsidy of this policy alone provides limited help to landlords, the government should help the landlords to explore other revenue possibilities from afforestation in addition to the existing subsidies and raise the participation incentives.
Abstract: Rapid economic development and population growth
in Malaysia had accelerated the generation of solid waste. This issue
gives pressure for effective management of municipal solid waste
(MSW) to take place in Malaysia due to the increased cost of landfill.
This paper discusses optimal planning of waste-to-energy (WTE)
using a combinatorial simulation and optimization model through
mixed integer linear programming (MILP) approach. The proposed
multi-period model is tested in Iskandar Malaysia (IM) as case study
for a period of 12 years (2011 -2025) to illustrate the economic
potential and tradeoffs involved in this study. In this paper, 3
scenarios have been used to demonstrate the applicability of the
model: (1) Incineration scenario (2) Landfill scenario (3) Optimal
scenario. The model revealed that the minimum cost of electricity
generation from 9,995,855 tonnes of MSW is estimated as USD
387million with a total electricity generation of 50MW /yr in the
optimal scenario.
Abstract: In this article, while it is attempted to describe the
problem and its importance, transformational leadership is studied by considering leadership theories. Issues such as the definition of
transformational leadership and its aspects are compared on the basis of the ideas of various connoisseurs and then it (transformational leadership) is examined in successful and
unsuccessful companies. According to the methodology, the
method of research, hypotheses, population and statistical sample
are investigated and research findings are analyzed by using descriptive and inferential statistical methods in the framework of
analytical tables. Finally, our conclusion is provided by considering the results of statistical tests. The final result shows that
transformational leadership is significantly higher in successful companies than unsuccessful ones P
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: In order to study floristic and molecular classification
of common wild wheat (Triticum boeoticum Boiss.), an analysis was
conducted on populations of the Triticum boeoticum collected from
different regions of Iran. Considering all floristic compositions of
habitats, six floristic groups (syntaxa) within the populations were
identified. A high level of variation of T. boeoticum also detected
using SSR markers. Our results showed that molecular method
confirmed the grouping of floristic method. In other word, the results
from our study indicate that floristic classification are still useful,
efficient, and economic tools for characterizing the amount and
distribution of genetic variation in natural populations of T.
boeoticum. Nevertheless, molecular markers appear as useful and
complementary techniques for identification and for evaluation of
genetic diversity in studied populations.
Abstract: A model of a system concerning one species of demersal
(inshore) fish and one of pelagic (offshore) fish undergoing fishing
restricted by marine protected areas is proposed in this paper. This
setup was based on the FISH-BE model applied to the Tabina fishery
in Zamboanga del Sur, Philippines. The components of the model
equations have been adapted from widely-accepted mechanisms in
population dynamics. The model employs Gompertz-s law of growth
and interaction on each type of protected and unprotected subpopulation.
Exchange coefficients between protected and unprotected
areas were assumed to be proportional to the relative area of the
entry region. Fishing harvests were assumed to be proportional to
both the number of fishers and the number of unprotected fish. An
extra term was included for the pelagic population to allow for the
exchange between the unprotected area and the outside environment.
The systems were found to be bounded for all parameter values. The
equations for the steady state were unsolvable analytically but the
existence and uniqueness of non-zero steady states can be proven.
Plots also show that an MPA size yielding the maximum steady state
of the unprotected population can be found. All steady states were
found to be globally asymptotically stable for the entire range of
parameter values.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.