Abstract: This article proposes an Ant Colony Optimization
(ACO) metaheuristic to minimize total makespan for scheduling a set
of jobs and assign workers for uniformly related parallel machines.
An algorithm based on ACO has been developed and coded on a
computer program Matlab®, to solve this problem. The paper
explains various steps to apply Ant Colony approach to the problem
of minimizing makespan for the worker assignment & jobs
scheduling problem in a parallel machine model and is aimed at
evaluating the strength of ACO as compared to other conventional
approaches. One data set containing 100 problems (12 Jobs, 03
machines and 10 workers) which is available on internet, has been
taken and solved through this ACO algorithm. The results of our
ACO based algorithm has shown drastically improved results,
especially, in terms of negligible computational effort of CPU, to
reach the optimal solution. In our case, the time taken to solve all 100
problems is even lesser than the average time taken to solve one
problem in the data set by other conventional approaches like GA
algorithm and SPT-A/LMC heuristics.
Abstract: The Siemens Healthcare Sector is one of the world's
largest suppliers to the healthcare industry and a trendsetter in
medical imaging and therapy, laboratory diagnostics, medical
information technology, and hearing aids.
Siemens offers its customers products and solutions for the entire
range of patient care from a single source – from prevention and
early detection to diagnosis, and on to treatment and aftercare. By
optimizing clinical workflows for the most common diseases,
Siemens also makes healthcare faster, better, and more cost effective.
The optimization of clinical workflows requires a
multidisciplinary focus and a collaborative approach of e.g. medical
advisors, researchers and scientists as well as healthcare economists.
This new form of collaboration brings together experts with deep
technical experience, physicians with specialized medical knowledge
as well as people with comprehensive knowledge about health
economics.
As Charles Darwin is often quoted as saying, “It is neither the
strongest of the species that survive, nor the most intelligent, but the
one most responsive to change," We believe that those who can
successfully manage this change will emerge as winners, with
valuable competitive advantage.
Current medical information and knowledge are some of the core
assets in the healthcare industry. The main issue is to connect
knowledge holders and knowledge recipients from various
disciplines efficiently in order to spread and distribute knowledge.
Abstract: The structural stability of the model of a nonelectroneutral current sheath is investigated. The stationary model of a current sheath represents the system of four connected nonlinear differential first-order equations and thus they should manifest structural instability property, i.e. sensitivity to the infinitesimal changes of parameters and starting conditions. Domains of existence of the solutions of current sheath type are found. Those solutions of the current sheath type are realized only in some regions of sevendimensional space of parameters of the problem. The phase volume of those regions is small in comparison with the whole phase volume of the definition range of those parameters. It is shown that the offered model of a nonelectroneutral current sheath is applicable for theoretical interpretation of the bifurcational current sheaths observed in the magnetosphere.
Abstract: This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. The experiments reveal superior results in terms of speed and convergence to achieve a solution.
Abstract: Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.
Abstract: Compensating physiological motion in the context
of minimally invasive cardiac surgery has become an attractive
issue since it outperforms traditional cardiac procedures offering
remarkable benefits. Owing to space restrictions, computer vision
techniques have proven to be the most practical and suitable solution.
However, the lack of robustness and efficiency of existing methods
make physiological motion compensation an open and challenging
problem. This work focusses on increasing robustness and efficiency
via exploration of the classes of 1−and 2−regularized optimization,
emphasizing the use of explicit regularization. Both approaches are
based on natural features of the heart using intensity information.
Results pointed out the 1−regularized optimization class as the best
since it offered the shortest computational cost, the smallest average
error and it proved to work even under complex deformations.
Abstract: Standard packaging and interconnection technologies
of power devices have difficulties meeting the increasing thermal
demands of new application fields of power electronics devices.
Main restrictions are the decreasing reliability of bond-wires and
solder layers with increasing junction temperature. In the last few
years intensive efforts have been invested in developing new
packaging and interconnection solutions which may open a path to
future application of power devices. In this paper, the main failure
mechanisms of power devices are described and principle of new
packaging and interconnection concepts and their power cycling
reliability are presented.
Abstract: There has been a growing interest in the field of
bio-mimetic robots that resemble the shape of an insect or an aquatic
animal, among many others. One bio-mimetic robot serves the
purpose of exploring pipelines, spotting any troubled areas or
malfunctions and reporting its data. Moreover, the robot is able to
prepare for and react to any abnormal routes in the pipeline. In order
to move effectively inside a pipeline, the robot-s movement will
resemble that of a lizard. When situated in massive pipelines with
complex routes, the robot places fixed sensors in several important
spots in order to complete its monitoring. This monitoring task is to
prevent a major system failure by preemptively recognizing any minor
or partial malfunctions. Areas uncovered by fixed sensors are usually
impossible to provide real-time observation and examination, and thus
are dependant on periodical offline monitoring. This paper provides
the Monitoring System that is able to monitor the entire area of
pipelines–with and without fixed sensors–by using the bio-mimetic
robot.
Abstract: Geographic Information System (GIS) is a computerbased
tool used extensively to solve various engineering problems
related to spatial data. In spite of growing popularity of GIS, its
complete potential to construction industry has not been realized. In
this paper, the summary of up-to-date work on spatial applications of
GIS technologies in construction industry is presented. GIS
technologies have the potential to solve space related problems of
construction industry involving complex visualization, integration of
information, route planning, E-commerce, cost estimation, etc. GISbased
methodology to handle time and space issues of construction
projects scheduling is developed and discussed in this paper.
Abstract: In the traditional theory of non-uniform torsion the
axial displacement field is expressed as the product of the unit twist
angle and the warping function. The first one, variable along the
beam axis, is obtained by a global congruence condition; the second
one, instead, defined over the cross-section, is determined by solving
a Neumann problem associated to the Laplace equation, as well as for
the uniform torsion problem.
So, as in the classical theory the warping function doesn-t punctually
satisfy the first indefinite equilibrium equation, the principal aim of
this work is to develop a new theory for non-uniform torsion of
beams with axial symmetric cross-section, fully restrained on both
ends and loaded by a constant torque, that permits to punctually
satisfy the previous equation, by means of a trigonometric expansion
of the axial displacement and unit twist angle functions.
Furthermore, as the classical theory is generally applied with good
results to the global and local analysis of ship structures, two beams
having the first one an open profile, the second one a closed section,
have been analyzed, in order to compare the two theories.
Abstract: This paper undertakes the problem of optimal
capacitor placement in a distribution system. The problem is how to
optimally determine the locations to install capacitors, the types and
sizes of capacitors to he installed and, during each load level,the
control settings of these capacitors in order that a desired objective
function is minimized while the load constraints,network constraints
and operational constraints (e.g. voltage profile) at different load
levels are satisfied. The problem is formulated as a combinatorial
optimization problem with a nondifferentiable objective function.
Four solution mythologies based on algorithms (GA),tabu search
(TS), and hybrid GA-SA algorithms are presented.The solution
methodologies are preceded by a sensitivity analysis to select the
candidate capacitor installation locations.
Abstract: The paper proposes an approach for design of modular
systems based on original technique for modeling and formulation of
combinatorial optimization problems. The proposed approach is
described on the example of personal computer configuration design.
It takes into account the existing compatibility restrictions between
the modules and can be extended and modified to reflect different
functional and users- requirements. The developed design modeling
technique is used to formulate single objective nonlinear mixedinteger
optimization tasks. The practical applicability of the
developed approach is numerically tested on the basis of real modules
data. Solutions of the formulated optimization tasks define the
optimal configuration of the system that satisfies all compatibility
restrictions and user requirements.
Abstract: Standards for learning objects focus primarily on
content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined
set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite
set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a
specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of
programs, is presented in this paper. The proposed definition includes
metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements
of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services
are also presented as a case study on the use of the proposed definition of programming problems as learning objects.
Abstract: The goal of this paper is to find Wardrop equilibrium
in transport networks at case of uncertainty situations, where the
uncertainty comes from lack of information. We use simulation tool
to find the equilibrium, which gives only approximate solution, but
this is sufficient for large networks as well. In order to take the
uncertainty into account we have developed an interval-based
procedure for finding the paths with minimal cost using the
Dempster-Shafer theory. Furthermore we have investigated the users-
behaviors using game theory approach, because their path choices
influence the costs of the other users- paths.
Abstract: In this study the effect of incorporation of recycled
glass-fibre reinforced polymer (GFRP) waste materials, obtained by
means of milling processes, on mechanical behaviour of polyester
polymer mortars was assessed. For this purpose, different contents of
recycled GFRP waste powder and fibres, with distinct size gradings,
were incorporated into polyester based mortars as sand aggregates
and filler replacements. Flexural and compressive loading capacities
were evaluated and found better than unmodified polymer mortars.
GFRP modified polyester based mortars also show a less brittle
behaviour, with retention of some loading capacity after peak load.
Obtained results highlight the high potential of recycled GFRP waste
materials as efficient and sustainable reinforcement and admixture for
polymer concrete and mortars composites, constituting an emergent
waste management solution.
Abstract: In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.
Abstract: Tackling emergency situations is performed based on emergency scenarios. These scenarios do not have a uniform form in the Czech Republic. They are unstructured and developed primarily in the text form. This does not allow solving emergency situations efficiently. For this reason, the paper aims at defining a Process Oriented Architecture to support and thus to improve tackling emergency situations in the Czech Republic. The innovative Process Oriented Architecture is based on the Workflow Reference Model while taking into account the options of Business Process Management Suites for the implementation of process oriented emergency scenarios. To verify the proposed architecture the Proof of Concept has been used which covers the reception of an emergency event at the district emergency operations centre. Within the particular implementation of the proposed architecture the Bonita Open Solution has been used. The architecture created in this way is suitable not only for emergency management, but also for educational purposes.
Abstract: This paper presents results obtained from the
numerical solution for the flow past an oscillating circular cylinder at
Reynolds number of 200. The frequency of oscillation was fixed to
the vortex shedding frequency from a fixed cylinder, f0, while the
amplitudes of oscillations were varied from to 1.1a, where a
represents the radius of the cylinder. The response of the flow
through the fluid forces acting on the surface of the cylinder are
investigated. The lock-on phenomenon is captured at low oscillation
amplitudes.
Abstract: In this article an evolutionary technique has been used
for the solution of nonlinear Riccati differential equations of fractional order. In this method, genetic algorithm is used as a tool for
the competent global search method hybridized with active-set algorithm for efficient local search. The proposed method has been
successfully applied to solve the different forms of Riccati
differential equations. The strength of proposed method has in its
equal applicability for the integer order case, as well as, fractional
order case. Comparison of the method has been made with standard
numerical techniques as well as the analytic solutions. It is found
that the designed method can provide the solution to the equation
with better accuracy than its counterpart deterministic approaches.
Another advantage of the given approach is to provide results on
entire finite continuous domain unlike other numerical methods
which provide solutions only on discrete grid of points.
Abstract: Optimal reactive power flow is an optimization problem
with one or more objective of minimizing the active power losses for
fixed generation schedule. The control variables are generator bus
voltages, transformer tap settings and reactive power output of the
compensating devices placed on different bus bars. Biogeography-
Based Optimization (BBO) technique has been applied to solve
different kinds of optimal reactive power flow problems subject
to operational constraints like power balance constraint, line flow
and bus voltages limits etc. BBO searches for the global optimum
mainly through two steps: Migration and Mutation. In the present
work, BBO has been applied to solve the optimal reactive power
flow problems on IEEE 30-bus and standard IEEE 57-bus power
systems for minimization of active power loss. The superiority of the
proposed method has been demonstrated. Considering the quality of
the solution obtained, the proposed method seems to be a promising
one for solving these problems.