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1

Growth estimates of composite entire functions in the light of slowly changing functions based relative order, relative type and relative weak type

Datta S. K., Biswas T., Bhattacharyya S.

Fasciculi Mathematici

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2015

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Nr 54

59--74

EN

In the paper we prove some growth properties of maximum term and maximum modulus of composition of entire functions on the basis of relative L*-order, relative L*-type and relative L*-weak type.

2

Operating characteristics of transcritical CO2 heat pump for simultaneous water cooling and heating

Sarkar J., Bhattacharyya S.

Archives of Thermodynamics

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2012

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Vol. 33, no. 4

23-40

EN

The effects of water-side operating conditions (mass flow rates and inlet temperatures) of both evaporator and gas cooler on the experimental as well as simulated performances (cooling and heating capacities, system coefficient of performance (COP) and water outlet temperatures) of the transcritical CO2 heat pump for simultaneous water cooling and heating the are studied and revised. Study shows that both the water mass flow rate and inlet temperature have significant effect on the system performances. Test results show that the effect of evaporator water mass flow rate on the system performances and water outlet temperatures is more pronounced (COP increases by 0.6 for 1 kg/min) compared to that of gas cooler water mass flow rate (COP increases by 0.4 for 1 kg/min) and the effect of gas cooler water inlet temperature is more significant (COP decreases by 0.48 for given range) compared to that of evaporator water inlet temperature (COP increases by 0.43 for given range). Comparisons of experimental values with simulated results show the maximum deviation of 5% for cooling capacity, 10% for heating capacity and 16% for system COP.

3

Self organizing neural network (SONN) based gray scale object extractor with a multilevel sigmoidal (MUSIG) activation function

Bhattacharyya S., Dutta P., Maulik U.

Foundations of Computing and Decision Sciences

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2008

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Vol. 33, No. 2

131-165

EN

A single three layer self organizing neural network, characterized by the standard bilevel sigmoidal activation function, is efficient in extraction of binary objects from a noisy image by means of self supervision. A multilevel version of the generalized sigmoidal activation function for mapping multiscale input information into multiple scales of gray, is introduced in this article. The multilevel function is used to induce multiscaling capability in a single three layer self organizing neural network. An application of the proposed multilevel activation function for the extraction of multiscale images, is demonstrated using a synthetic and two real life multiscale images. Experiments have been conducted with different combinations of parameters of the function. The standard correlation factors between the extracted and the original images indicate the efficiency of the proposed multilevel activation function.

4

Thermodynamic optimization of irreversible heat pumps

Sarkar J., Bhattacharyya S., Ramgopal M.

Archives of Thermodynamics

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2008

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Vol. 29, no. 3

59-68

EN

The performance of an irreversible heat pump for simultaneous cooling and heating applications, for which irreversibilities results from both the finite size and finite rate of heat conduction, as well as compression and expansion, is studied. The relation between optimum system coefficient of performance and optimal rate of combined cooling and heating output has been established. Also relations for optimal cold and hot fluid temperatures have been derived and performance of irreversible heat pump has been discussed. The optimal correlations have been simplified for endoreversible cycle and compared with the relation for only cooling or hearting in the literature. Consequently, optimal relations for heat conductance inventory, residence time and mass distribution between the heat exchangers have been established.

5

Influences of a "hybrid grid" on the network's voltage quality and supply reliability

Bhattacharyya S., Myrzik J., Meeuwsen J.

Electrical Power Quality and Utilisation. Journal

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2007

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Vol. 13, nr 2

25-31

EN

The electricity is a basic need for functioning of modern society. In the deregulated electricity market, delivering quality power to the clients is a challenge for the utilities. In this paper, a "hybrid grid" is discussed that consists of centralized generations and localized distributed generations which may be comprised of small-scale conventional and sustainable sources. Energy storage option is also integrated in the hybrid-grid. Simulations are done on a test network, using "Power-Factory" software. It was found from the analysis that voltage quality and power supply availability of a hybrid-grid can be improved by proper selection of energy storage system along with protective and control devices.

6

Designing pruned neighborhood neural networks for object extraction from noisy background

Bhattacharyya S., Dutta P.

Foundations of Computing and Decision Sciences

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2006

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Vol. 31, No. 2

105-134

EN

Refinement of neural network architectures by pruning the network interconnections reduces the computational overhead associated with the tasks for which the network is employed. A fuzzy set theoretic approach for designing pruned neighborhood topology-based neural networks for efficient extraction of objects from a noisy background, is presented in this paper. Pruning of the network architecture Is achieved by means of a judicious selection of the participating nodes of the neighborhood topology-based neural network using the fuzzy cardinality measures of the object scene. An application of the proposed methodology for designing a pruned multilayer self organizing neural network for the extraction of binary and gray scale objects from noisy backgrounds with different noise levels is demonstrated. The results obtained are compared with the outputs obtained with the conventional fully connected network architecture of the same network. Comparative results show a significant reduction in the architecture of the network with increasing noise levels for both the binary and gray scale images. Moreover, the qualities of the extracted images obtained using the pruned network architecture are found to be better than those obtained using the conventional fully connected architecture.