Abstract: This paper provides a quantitative measure of the
time-varying multiunit neuronal spiking activity using an entropy
based approach. To verify the status embedded in the neuronal activity
of a population of neurons, the discrete wavelet transform (DWT) is
used to isolate the inherent spiking activity of MUA. Due to the
de-correlating property of DWT, the spiking activity would be
preserved while reducing the non-spiking component. By evaluating
the entropy of the wavelet coefficients of the de-noised MUA, a
multiresolution Shannon entropy (MRSE) of the MUA signal is
developed. The proposed entropy was tested in the analysis of both
simulated noisy MUA and actual MUA recorded from cortex in rodent
model. Simulation and experimental results demonstrate that the
dynamics of a population can be quantified by using the proposed
entropy.
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: In medical investigations, uncertainty is a major
challenging problem in making decision for doctors/experts to
identify the diseases with a common set of symptoms and also has
been extensively increasing in medical diagnosis problems. The
theory of cross entropy for intuitionistic fuzzy sets (IFS) is an
effective approach in coping uncertainty in decision making for
medical diagnosis problem. The main focus of this paper is to
propose a new intuitionistic fuzzy cross entropy measure (IFCEM),
which aid in reducing the uncertainty and doctors/experts will take
their decision easily in context of patient’s disease. It is shown that
the proposed measure has some elegant properties, which
demonstrates its potency. Further, it is also exemplified in detail the
efficiency and utility of the proposed measure by using a real life
case study of diagnosis the disease in medical science.
Abstract: The thermal control in many systems is widely
accomplished applying mixed convection process due to its low cost,
reliability and easy maintenance. Typical applications include the
aircraft electronic equipment, rotating-disc heat exchangers, turbo
machinery, and nuclear reactors, etc. Natural convection in an inclined
square enclosure heated via wall heater has been studied numerically.
Finite volume method is used for solving momentum and energy
equations in the form of stream function–vorticity. The right and left
walls are kept at a constant temperature, while the other parts are
adiabatic. The range of the inclination angle covers a whole revolution.
The method is validated for a vertical cavity. A general power law
dependence of the Nusselt number with respect to the Rayleigh
number with the coefficient and exponent as functions of the
inclination angle is presented. For a fixed Rayleigh number, the
inclination angle increases or decreases is found.
Abstract: This paper presents powerful techniques for the
development of a new monitoring method based on multi-scale
entropy (MSE) in order to characterize the behaviour of the
concentrations of different gases present in the synthesis of Ammonia
and soft-sensor based on Principal Component Analysis (PCA).
Abstract: A Motzkin shift is a mathematical model for constraints
on genetic sequences. In terms of the theory of symbolic dynamics,
the Motzkin shift is nonsofic, and therefore, we cannot use the Perron-
Frobenius theory to calculate its topological entropy. The Motzkin
shift M(M,N) which comes from language theory, is defined to be the
shift system over an alphabet A that consists of N negative symbols,
N positive symbols and M neutral symbols. For an x in the full shift,
x will be in the Motzkin subshift M(M,N) if and only if every finite
block appearing in x has a non-zero reduced form. Therefore, the
constraint for x cannot be bounded in length. K. Inoue has shown that
the entropy of the Motzkin shift M(M,N) is log(M + N + 1). In this
paper, a new direct method of calculating the topological entropy of
the Motzkin shift is given without any measure theoretical discussion.
Abstract: Iris codes contain bits with different entropy. This
work investigates different strategies to reduce the size of iris
code templates with the aim of reducing storage requirements and
computational demand in the matching process. Besides simple subsampling
schemes, also a binary multi-resolution representation as
used in the JBIG hierarchical coding mode is assessed. We find that
iris code template size can be reduced significantly while maintaining
recognition accuracy. Besides, we propose a two-stage identification
approach, using small-sized iris code templates in a pre-selection
stage, and full resolution templates for final identification, which
shows promising recognition behaviour.
Abstract: In this article is reported a construction and some
properties of the 5iD viewer, the system recording simultaneously
5 views of a given experimental object. Properties of the system
are demonstrated on the analysis of fish schooling behaviour. It
is demonstrated the method of instrument calibration which allows
inclusion of image distortion and it is proposed and partly tested
also the method of distance assessment in the case that only two
opposite cameras are available. Finally, we demonstrate how the state
trajectory of the behaviour of the fish school may be constructed from
the entropy of the system.
Abstract: Supply chain (SC) is an operational research (OR)
approach and technique which acts as catalyst within central nervous
system of business today. Without SC, any type of business is at
doldrums, hence entropy. SC is the lifeblood of business today
because it is the pivotal hub which provides imperative competitive
advantage. The paper present a conceptual framework dubbed as
Homomorphic Conceptual Framework for Effective Supply Chain
Strategy (HCEFSC).The term Homomorphic is derived from abstract
algebraic mathematical term homomorphism (same shape) which
also embeds the following mathematical application sets:
monomorphisms, isomorphism, automorphisms, and endomorphism.
The HCFESC is intertwined and integrated with wide and broad sets
of elements.
Abstract: In this work, a polyaniline/Iron oxide (PANI/Fe2O3)
composite was chemically prepared by oxidative polymerization of
aniline in acid medium, in presence of ammonium persulphate as an
oxidant and amount of Fe2O3. The composite was characterized by a
scanning electron microscopy (SEM). The prepared composite has
been used as adsorbent to remove Tartrazine dye form aqueous
solutions.
The effects of initial dye concentration and temperature on the
adsorption capacity of PANI/Fe2O3 for Tartrazine dye have been
studied in this paper.
The Langmuir and Freundlich adsorption models have been used
for the mathematical description of adsorption equilibrium data. The
best fit is obtained using the Freundlich isotherm with an R2 value of
0.998. The change of Gibbs energy, enthalpy, and entropy of
adsorption has been also evaluated for the adsorption of Tartrazine
onto PANI/ Fe2O3. It has been proved according the results that the
adsorption process is endothermic in nature.
Abstract: A computational fluid dynamics simulation is done for
non-Newtonian fluid in a baffled stirred tank. The CMC solution is
taken as non-Newtonian shear thinning fluid for simulation. The
Reynolds Average Navier Stocks equation with steady state multi
reference frame approach is used to simulate flow in the stirred tank.
The turbulent flow field is modelled using realizable k-ε turbulence
model. The simulated velocity profiles of Rushton turbine is
validated with literature data. Then, the simulated flow field of CD-6
impeller is compared with the Rushton turbine. The flow field
generated by CD-6 impeller is less in magnitude than the Rushton
turbine. The impeller global parameter, power number and flow
number, and entropy generation due to viscous dissipation rate is also
reported.
Abstract: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.
Abstract: This paper presents feature level image fusion using Haar lifting wavelet transform. Feature fused is edge and boundary information, which is obtained using wavelet transform modulus maxima criteria. Simulation results show the superiority of the result as entropy, gradient, standard deviation are increased for fused image as compared to input images. The proposed methods have the advantages of simplicity of implementation, fast algorithm, perfect reconstruction, and reduced computational complexity. (Computational cost of Haar wavelet is very small as compared to other lifting wavelets.)
Abstract: One of the main biomedical problem lies in detecting dependencies in semi structured data. Solution includes biomedical portal and algorithms (integral rating health criteria, multidimensional data visualization methods). Biomedical portal allows to process diagnostic and research data in parallel mode using Microsoft System Center 2012, Windows HPC Server cloud technologies. Service does not allow user to see internal calculations instead it provides practical interface. When data is sent for processing user may track status of task and will achieve results as soon as computation is completed. Service includes own algorithms and allows diagnosing and predicating medical cases. Approved methods are based on complex system entropy methods, algorithms for determining the energy patterns of development and trajectory models of biological systems and logical–probabilistic approach with the blurring of images.
Abstract: This paper carries out a performance analysis based on
the first and second laws of thermodynamics for heat recovery vapor
generator (HRVG) of ammonia-water mixture when the heat source is
low-temperature energy in the form of sensible heat. In the analysis,
effects of the ammonia mass concentration and mass flow ratio of the
binary mixture are investigated on the system performance including
the effectiveness of heat transfer, entropy generation, and exergy
efficiency. The results show that the ammonia concentration and the
mass flow ratio of the mixture have significant effects on the system
performance of HRVG.
Abstract: The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.
Abstract: In this short paper, new properties of transition matrix were introduced. Eigen values for small order transition matrices are calculated in flexible method. For benefit of these properties applications of these properties were studied in the solution of Markov's chain via steady state vector, and information theory via channel entropy. The implemented test examples were promised for usages.
Abstract: Non linear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy normal sinus rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.
Abstract: Cascade refrigeration systems employ series of single stage vapor compression units which are thermally coupled with evaporator/condenser cascades. Different refrigerants are used in each of the circuit depending on the optimum characteristics shown by the refrigerant for a particular application. In the present research study, a steady state thermodynamic model is developed which simulates the working of an actual cascade system. The model provides COP and all other system parameters e.g. total compressor work, temperature, pressure, enthalpy and entropy at different state points. The working fluid in low temperature circuit (LTC) is CO2 (R744) while Ammonia (R717), Propane (R290), Propylene (R1270), R404A and R12 are the refrigerants in high temperature circuit (HTC). The performance curves of Ammonia, Propane, Propylene, and R404A are compared with R12 to find its nearest substitute. Results show that Ammonia is the best substitute of R12.