Abstract: Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.
Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher
quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.
Abstract: Feature selection is an important step in many pattern
classification problems. It is applied to select a subset of features,
from a much larger set, such that the selected subset is sufficient to
perform the classification task. Due to its importance, the problem of
feature selection has been investigated by many researchers. In this
paper, a novel feature subset search procedure that utilizes the Ant
Colony Optimization (ACO) is presented. The ACO is a
metaheuristic inspired by the behavior of real ants in their search for
the shortest paths to food sources. It looks for optimal solutions by
considering both local heuristics and previous knowledge. When
applied to two different classification problems, the proposed
algorithm achieved very promising results.
Abstract: In the current Grid environment, efficient workload
management presents a significant challenge, for which there are
exorbitant de facto standards encompassing resource discovery,
brokerage, and data transfer, among others. In addition, the real-time
resource status, essential for an optimal resource allocation strategy,
is often not readily accessible. To address these issues and provide a
cleaner abstraction of the Grid with the potential of generalizing into
arbitrary resource-sharing environment, this paper proposes a new
Condor-based pilot mechanism applied in the PanDA architecture,
PanDA-PF WMS, with the goal of providing a more generic yet
efficient resource allocating strategy. In this architecture, the PanDA
server primarily acts as a repository of user jobs, responding to pilot
requests from distributed, remote resources. Scheduling decisions are
subsequently made according to the real-time resource information
reported by pilots. Pilot Factory is a Condor-inspired solution for a
scalable pilot dissemination and effectively functions as a resource
provisioning mechanism through which the user-job server, PanDA,
reaches out to the candidate resources only on demand.
Abstract: Knowledge modelling, a main activity for the development of Knowledge Based Systems, have no set standards and are mostly done in an ad hoc way. There is a lack of support for the transition from abstract level to implementation. In this paper, a methodology for the development of the knowledge model, which is inspired by both Software and Knowledge Engineering, is proposed. Use of UML which is the de-facto standard for modelling in the software engineering arena is explored for knowledge modelling. The methodology proposed, is used to develop a knowledge model of a knowledge based system for recommending suitable hotels for tourists visiting Mauritius.
Abstract: In this paper we present a new approach to deal with
image segmentation. The fact that a single segmentation result do not
generally allow a higher level process to take into account all the
elements included in the image has motivated the consideration of
image segmentation as a multiobjective optimization problem. The
proposed algorithm adopts a split/merge strategy that uses the result
of the k-means algorithm as input for a quantum evolutionary
algorithm to establish a set of non-dominated solutions. The
evaluation is made simultaneously according to two distinct features:
intra-region homogeneity and inter-region heterogeneity. The
experimentation of the new approach on natural images has proved
its efficiency and usefulness.
Abstract: Image synthesis is an important area in image processing.
To synthesize images various systems are proposed in
the literature. In this paper, we propose a bio-inspired system to
synthesize image and to study the generating power of the system, we
define the class of languages generated by our system. We call image
as array in this paper. We use a primitive called iso-array to synthesize
image/array. The operation is double splicing on iso-arrays. The
double splicing operation is used in DNA computing and we use
this to synthesize image. A comparison of the family of languages
generated by the proposed self restricted double splicing systems on
iso-arrays with the existing family of local iso-picture languages is
made. Certain closure properties such as union, concatenation and
rotation are studied for the family of languages generated by the
proposed model.
Abstract: IT infrastructures are becoming more and more
difficult. Therefore, in the first industrial IT systems, the P2P
paradigm has replaced the traditional client server and methods of
self-organization are gaining more and more importance. From the
past it is known that especially regular structures like grids may
significantly improve the system behavior and performance. This
contribution introduces a new algorithm based on a biologic
analogue, which may provide the growth of several regular structures
on top of anarchic grown P2P- or social network structures.
Abstract: This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).
Abstract: This paper covered a series of key points in terms of 2D to 3D stereoscopic conversion. A successfully applied stereoscopic conversion approach in current visual effects industry was presented. The purpose of this paper is to cover a detailed workflow and concept, which has been successfully used in 3D stereoscopic conversion for feature films in visual effects industry, and therefore to clarify the process in stereoscopic conversion production and provide a clear idea for those entry-level artists to improve an overall understanding of 3D stereoscopic in digital compositing field as well as to the higher education factor of visual effects and hopefully inspire further collaboration and participants particularly between academia and industry.
Abstract: In general architecture means the art of creating the
space. Comprehensive and complete body which is created by a
creative and purposeful thought to respond the human needs.
Professionally, architecture is the are of designing and
comprehensive planning of physical spaces that is created for
human-s productivity. The purpose of architectural design is to
respond the human needs which is appeared in physical frame.
Human in response to his needs is always looking to achieve comfort.
Throughout history of human civilization this relative comfort has
been inspired by nature and assimilating the facility and natural
achievement in the format of artifact patterns base on the nature, so
that it is achieved in this comfort level and invention of these factors.
All physical factors like regional, social and economical factors are
made available to human in order to achieve a specific goal and are
made to gain an ideal architecture to respond the functional needs and
consider the aesthetics and elemental principles and pay attention to
residents- comfort. In this study the Persian architecture with
exploiting and transforming the energies into the requisite energies of
architecture spaces and importing fuel products, utilities, etc, in order
to achieve a relative comfort level will be investigated. In this paper
the study of structural and physical specialties of traditional houses in
desert regions and Central Plateau of Iran gave us this opportunity to
being more familiar with important specialties of energy productivity
in architecture body of traditional houses in these regions specially
traditional houses of Kashan and in order to use these principles to
create modern architectures in these regions.
Abstract: In its attempt to offer new ways into autonomy for a
large population of disabled people, assistive technology has largely
been inspired by robotics engineering. Recent human-like robots
carry new hopes that it seems to us necessary to analyze by means of
a specific theory of anthropomorphism. We propose to distinguish a
functional anthropomorphism which is the one of actual wheelchairs
from a structural anthropomorphism based on a mimicking of human
physiological systems. If functional anthropomorphism offers the
main advantage of eliminating the physiological systems
interdependence issue, the highly link between the robot for disabled
people and their human-built environment would lead to privilege in
the future the anthropomorphic structural way. In this future
framework, we highlight a general interdependence principle : any
partial or local structural anthropomorphism generates new
anthropomorphic needs due to the physiological systems
interdependency, whose effects can be evaluated by means of
specific anthropomorphic criterions derived from a set theory-based
approach of physiological systems.
Abstract: The aim of this study is to show innovative techniques that describe the effectiveness of individuals diagnosed with antisocial personality disorders (ASPD). The author presents information about hate schemas regarding persons with ASPD and their understanding of the role of hate. The data of 60 prisoners with ASPD, 40 prisoners without ASPD, and 60 men without antisocial tendencies, has been analyzed. The participants were asked to describe their hate inspired by a photograph. The narrative discourse was analyzed, the three groups were compared. The results show the differences between the inmates with ASPD, those without ASPD, and the controls. The antisocial individuals describe hate as an ambivalent feeling with low emotional intensity, i.e., actors (in stories) are presented more as positives than as partners. They use different mechanisms to keep them from understanding the meaning of the emotional situation. The schema's characteristics were expressed in narratives attributed to high Psychopathy.
Abstract: In this paper, a TSK-type Neuro-fuzzy Inference
System that combines the features of fuzzy sets and neural networks
has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled
Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate
the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on
Particle Swarm Optimization algorithm (PSO) and Genetic
Algorithm (GA).
Abstract: Biological evolution has generated a rich variety of
successful solutions; from nature, optimized strategies can be
inspired. One interesting example is the ant colonies, which are able
to exhibit a collective intelligence, still that their dynamic is simple.
The emergence of different patterns depends on the pheromone trail,
leaved by the foragers. It serves as positive feedback mechanism for
sharing information.
In this paper, we use the dynamic of TASEP as a model of
interaction at a low level of the collective environment in the ant-s
traffic flow. This work consists of modifying the movement rules of
particles “ants" belonging to the TASEP model, so that it adopts with
the natural movement of ants. Therefore, as to respect the constraints
of having no more than one particle per a given site, and in order to
avoid collision within a bidirectional circulation, we suggested two
strategies: decease strategy and waiting strategy. As a third work
stage, this is devoted to the study of these two proposed strategies-
stability. As a final work stage, we applied the first strategy to the
whole environment, in order to get to the emergence of traffic flow,
which is a way of learning.
Abstract: In this paper, we consider a new particle filter inspired
by biological evolution. In the standard particle filter, a resampling
scheme is used to decrease the degeneracy phenomenon and improve
estimation performance. Unfortunately, however, it could cause the
undesired the particle deprivation problem, as well. In order to
overcome this problem of the particle filter, we propose a novel
filtering method called the genetic filter. In the proposed filter, we
embed the genetic algorithm into the particle filter and overcome the
problems of the standard particle filter. The validity of the proposed
method is demonstrated by computer simulation.
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: The study deals with the modelling of the gas flow during heliox therapy. A special model has been developed to study the effect of the helium upon the gas flow in the airways during the spontaneous breathing. Lower density of helium compared with air decreases the Reynolds number and it allows improving the flow during the spontaneous breathing. In the cases, where the flow becomes turbulent while the patient inspires air the flow is still laminar when the patient inspires heliox. The use of heliox decreases the work of breathing and improves ventilation. It allows in some cases to prevent the intubation of the patients.
Abstract: The subcellular organelles called oil bodies (OBs) are lipid-filled quasi-spherical droplets produced from the endoplasmic reticulum (ER) and then released into the cytoplasm during seed development. It is believed that an OB grows by coalescence with other OBs and that its stability depends on the composition of oleosins, major proteins inserted in the hemi membrane that covers OBs. In this study, we measured the OB-volume distribution from different genotypes of A. thaliana after 7, 8, 9, 10 and 11 days of seed development. In order to test the hypothesis of OBs dynamics, we developed a simple mathematical model using non-linear differential equations inspired from the theory of coagulation. The model describes the evolution of OB-volume distribution during the first steps of seed development by taking into consideration the production of OBs, the increase of triacylglycerol volume to be stored, and the growth by coalescence of OBs. Fitted parameters values show an increase in the OB production and coalescence rates in A. thaliana oleosin mutants compared to wild type.
Abstract: The paper attempts to elucidate the columnar structure
of the cortex by answering the following questions. (1) Why the
cortical neurons with similar interests tend to be vertically arrayed
forming what is known as cortical columns? (2) How to describe the
cortex as a whole in concise mathematical terms? (3) How to design
efficient digital models of the cortex?