Abstract: The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.
Abstract: This paper used an asymmetric informative concept to apply in the macroeconomic model estimation of the tourism sector in Thailand. The variables used to statistically analyze are Thailand international and domestic tourism revenues, the expenditures of foreign and domestic tourists, service investments by private sectors, service investments by the government of Thailand, Thailand service imports and exports, and net service income transfers. All of data is a time-series index which was observed between 2002 and 2015. Empirically, the tourism multiplier and accelerator were estimated by two statistical approaches. The first was the result of the Generalized Method of Moments model (GMM) based on the assumption which the tourism market in Thailand had perfect information (Symmetrical data). The second was the result of the Maximum Entropy Bootstrapping approach (MEboot) based on the process that attempted to deal with imperfect information and reduced uncertainty in data observations (Asymmetrical data). In addition, the tourism leakages were investigated by a simple model based on the injections and leakages concept. The empirical findings represented the parameters computed from the MEboot approach which is different from the GMM method. However, both of the MEboot estimation and GMM model suggests that Thailand’s tourism sectors are in a period capable of stimulating the economy.
Abstract: Frequency estimation of a sinusoid in white noise using
maximum entropy power spectral estimation has been shown to be
very sensitive to initial sinusoidal phase. This paper presents use of
wavelet transform to find an analytic signal for frequency estimation
using maximum entropy method (MEM) and compared the results
with frequency estimation using analytic signal by Hilbert transform
method and frequency estimation using real data together with MEM.
The presented method shows the improved estimation precision and
antinoise performance.
Abstract: This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.
Abstract: In this numerical work, mixed convection and entropy
generation of Cu–water nanofluid in a lid-driven square cavity have
been investigated numerically using the Lattice Boltzmann Method.
Horizontal walls of the cavity are adiabatic and vertical walls have
constant temperature but different values. The top wall has been
considered as moving from left to right at a constant speed, U0. The
effects of different parameters such as nanoparticle volume
concentration (0–0.05), Rayleigh number (104–106) and Reynolds
numbers (1, 10 and 100) on the entropy generation, flow and
temperature fields are studied. The results have shown that addition
of nanoparticles to the base fluid affects the entropy generation, flow
pattern and thermal behavior especially at higher Rayleigh and low
Reynolds numbers. For pure fluid as well as nanofluid, the increase
of Reynolds number increases the average Nusselt number and the
total entropy generation, linearly. The maximum entropy generation
occurs in nanofluid at low Rayleigh number and at high Reynolds
number. The minimum entropy generation occurs in pure fluid at low
Rayleigh and Reynolds numbers. Also at higher Reynolds number,
the effect of Cu nanoparticles on enhancement of heat transfer was
decreased because the effect of lid-driven cavity was increased. The
present results are validated by favorable comparisons with
previously published results. The results of the problem are presented
in graphical and tabular forms and discussed.
Abstract: This paper treats different aspects of entropy measure
in classical information theory and statistical quantum mechanics, it
presents the possibility of extending the definition of Von Neumann
entropy to image and array processing. In the first part, we generalize
the quantum entropy using singular values of arbitrary rectangular
matrices to measure the randomness and the quality of denoising
operation, this new definition of entropy can be implemented to
compare the performance analysis of filtering methods. In the second
part, we apply the concept of pure state in quantum formalism
to generalize the maximum entropy method for narrowband and
farfield source localization problem. Several computer simulation
results are illustrated to demonstrate the effectiveness of the proposed
techniques.
Abstract: Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
Abstract: The Maximum entropy principle in spectral analysis
was used as an estimator of Direction of Arrival (DoA) of
electromagnetic or acoustic sources impinging on an array of sensors,
indeed the maximum entropy operator is very efficient when the
signals of the radiating sources are ergodic and complex zero mean
random processes which is the case for cosmic sources. In this paper,
we present basic review of the maximum entropy method (MEM)
which consists of rank one operator but not a projector, and we
elaborate a new operator which is full rank and sum of all possible
projectors. Two dimensional Simulation results based on Monte
Carlo trials prove the resolution power of the new operator where the
MEM presents some erroneous fluctuations.
Abstract: We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.
Abstract: Droplet size distributions in the cold spray of a fuel
are important in observed combustion behavior. Specification of
droplet size and velocity distributions in the immediate downstream
of injectors is also essential as boundary conditions for advanced
computational fluid dynamics (CFD) and two-phase spray transport
calculations. This paper describes the development of a new model to
be incorporated into maximum entropy principle (MEP) formalism
for prediction of droplet size distribution in droplet formation region.
The MEP approach can predict the most likely droplet size and
velocity distributions under a set of constraints expressing the
available information related to the distribution.
In this article, by considering the mechanisms of turbulence
generation inside the nozzle and wave growth on jet surface, it is
attempted to provide a logical framework coupling the flow inside the
nozzle to the resulting atomization process. The purpose of this paper
is to describe the formulation of this new model and to incorporate it
into the maximum entropy principle (MEP) by coupling sub-models
together using source terms of momentum and energy. Comparison
between the model prediction and experimental data for a gas turbine
swirling nozzle and an annular spray indicate good agreement
between model and experiment.
Abstract: In this paper a polymer electrolyte membrane (PEM)
fuel cell power system including burner, steam reformer, heat
exchanger and water heater has been considered to meet the
electrical, heating, cooling and domestic hot water loads of
residential building which in Tehran. The system uses natural gas as
fuel and works in CHP mode. Design and operating conditions of a
PEM fuel cell system is considered in this study. The energy
requirements of residential building and the number of fuel cell
stacks to meet them have been estimated. The method involved
exergy analysis and entropy generation thorough the months of the
year. Results show that all the energy needs of the building can be
met with 12 fuel cell stacks at a nominal capacity of 8.5 kW. Exergy
analysis of the CHP system shows that the increase in the ambient air
temperature from 1oC to 40oC, will have an increase of entropy
generation by 5.73%.Maximum entropy generates for 15 hour in 15th
of June and 15th of July is estimated to amount at 12624 (kW/K).
Entropy generation of this system through a year is estimated to
amount to 1004.54 GJ/k.year.
Abstract: We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.