Abstract: In this study, we addressed the problem of weak validity, implausible results, and inaccurate reporting in psychological research on different species. The theoretical basis of the study was the systems-evolutionary approach (SEA). We assumed that the root of the problem is the values and attitudes of the researchers (in particular anthropomorphism and anthropocentrism). The first aim of the study was the formulation of a research design that avoids this problem. Based on a literature review, we concluded that such design, amongst other things, should include methodics with playful components. The second aim was to conduct a series of studies on the differences in the formation of instrumental skill in rats raised and housed in different environments. As a result, we revealed that there are contradictions between some of the statements of SEA, so that it is not possible to choose one of the alternative hypotheses. We suggested that in order to get out of this problem, it is necessary to modify these provisions by aligning them with the attitude of multicentrism.
Abstract: Deoxyribonucleic Acid or DNA computing has
emerged as an interdisciplinary field that draws together chemistry,
molecular biology, computer science and mathematics. Thus, in this
paper, the possibility of DNA-based computing to solve an absolute
1-center problem by molecular manipulations is presented. This is
truly the first attempt to solve such a problem by DNA-based
computing approach. Since, part of the procedures involve with
shortest path computation, research works on DNA computing for
shortest path Traveling Salesman Problem, in short, TSP are reviewed.
These approaches are studied and only the appropriate one is adapted
in designing the computation procedures. This DNA-based
computation is designed in such a way that every path is encoded by
oligonucleotides and the path-s length is directly proportional to the
length of oligonucleotides. Using these properties, gel electrophoresis
is performed in order to separate the respective DNA molecules
according to their length. One expectation arise from this paper is that
it is possible to verify the instance absolute 1-center problem using
DNA computing by laboratory experiments.
Abstract: A feature weighting and selection method is proposed
which uses the structure of a weightless neuron and exploits the
principles that govern the operation of Genetic Algorithms and
Evolution. Features are coded onto chromosomes in a novel way
which allows weighting information regarding the features to be
directly inferred from the gene values. The proposed method is
significant in that it addresses several problems concerned with
algorithms for feature selection and weighting as well as providing
significant advantages such as speed, simplicity and suitability for
real-time systems.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.
Abstract: We present a non standard Euclidean vehicle
routing problem adding a level of clustering, and we revisit the use
of self-organizing maps as a tool which naturally handles such
problems. We present how they can be used as a main operator
into an evolutionary algorithm to address two conflicting
objectives of route length and distance from customers to bus stops
minimization and to deal with capacity constraints. We apply the
approach to a real-life case of combined clustering and vehicle
routing for the transportation of the 780 employees of an
enterprise. Basing upon a geographic information system we
discuss the influence of road infrastructures on the solutions
generated.
Abstract: The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.
Abstract: Timetabling problems are often hard and timeconsuming
to solve. Most of the methods of solving them concern
only one problem instance or class. This paper describes a universal
method for solving large, highly constrained timetabling problems
from different domains. The solution is based on evolutionary
algorithm-s framework and operates on two levels – first-level
evolutionary algorithm tries to find a solution basing on given set of
operating parameters, second-level algorithm is used to establish
those parameters. Tabu search is employed to speed up the solution
finding process on first level. The method has been used to solve
three different timetabling problems with promising results.
Abstract: Sustainable development is one of the most debated
issues, recently. In terms of providing more livable Earth continuity,
while Production activities are going on, on the other hand protecting
the environment has importance. As a strategy for sustainable
development, eco-innovation is the application of innovations to
reduce environmental burdens. Endeavors to understand ecoinnovation
processes have been affected from environmental
economics and innovation economics from neoclassical economics,
and evolutionary economics other than neoclassical economics. In
the light of case study analyses, this study aims to display activities
in this field through case studies after explaining the theoretical
framework of eco-innovations. This study consists of five sections
including introduction and conclusion. In the second part of the study
identifications of the concepts related with eco-innovation are
described and eco-innovations are classified. Third section considers
neoclassical and evolutionary approaches from neoclassical
economics and evolutionary economics, respectively. Fourth section
gives the case studies of successful eco-innovations. Last section is
the conclusion part and offers suggestions for future eco-innovation
research according to the theoretical framework and the case studies.