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Cuttack, India

DRIEMS is a technical college located in Tangi Cuttack district of Odisha, India, India. It has been affiliated to the Biju Patnaik University of Technology since 2004. From 1999 to 2003 it was affiliated to Utkal University. It is accredited by the National Board of Accreditation and National Assessment and Accreditation council and rated as an "A" grade institute. It is an ISO 9001:2008 certified institution. It offers the following courses: M-Tech MTM 4 year B.Tech Degree 3 year Diploma in Engineering PGDM & MBA BBA & BCA School & College of Nursing +2 Science Industrial TrainingApart from the required infrastructure the college has number of canteens, gender-based hostels, an International national-level cricket stadium, sports complex, swimming pool, High End Gymnasium, Indore-Stadium, Very big centralized library with wide range of national and international journals, guest house, auditorium, Seminar hall, Market complex with facility of Bank, ATMs, Post office, Health Centre etc. DRIEMS is having largest transportation network for students and its staff members. DRIEMS contributed many effective and dynamic alumni to different multinational and national companies, and the process is ongoing... Wikipedia.


Panda N.,Dhaneswar Rath Institute of Engineering and Management Studies | Pattanayak S.,Ravenshaw University | Choudhary R.N.P.,Siksha O' Anusandhan University
Journal of Electronic Materials | Year: 2015

Polycrystalline samples of Bi1−xPbxFe1−x(Zr0.5Ti0.5)xO3 (BPFZTO) with x = 0.0, 0.2, 0.3, and 0.4 were prepared by high-temperature solid-state reaction. Preliminary structural analysis of calcined powders of the materials by use of x-ray powder diffraction confirmed formation of single-phase systems with the tetragonal structure. Room-temperature scanning electron micrographs of the samples revealed uniform distribution of grains of low porosity and different dimensions on the surface of the samples. The frequency–temperature dependence of dielectric and electric properties was studied by use of dielectric and complex impedance spectroscopy over a wide range of frequency (1 kHz to 1 MHz) at different temperatures (25–500°C). The dielectric constant of BiFeO3 (BFO) was enhanced by substitution with Pb(Zr0.5Ti0.5)O3 (PZT) whereas the dielectric loss of the BPFZTO compounds decreased with increasing PZT content. A significant contribution of both grains and grain boundaries to the electrical response of the materials was observed. The frequency-dependence of the ac conductivity of BPFZTO followed Jonscher’s power law. Negative temperature coefficient of resistance behavior was observed for all the BPFZTO samples. Conductivity by thermally excited charge carriers and oxygen vacancies in the materials was believed to be of the Arrhenius-type. © 2015, The Minerals, Metals & Materials Society.


Das S.K.,Hi Technology Institute of Technology | Moharana J.K.,Dhaneswar Rath Institute of Engineering and Management Studies
Proceedings of 2013 International Conference on Power, Energy and Control, ICPEC 2013 | Year: 2013

The STATCOM (STATic synchronous Compensator) is being increasingly popular in power system applications. In general, reactive power compensation for power factor and stability of the utility system can be improved. A simple dq transformation and steady state and transient analysis are achieved to characterize the open loop system. A control scheme of the STATCOM has been proposed without controlling DC link voltage. The small signal scheme controls the phase angle as well as modulation index of the switching pattern and with small perturbation of reference current (reactive current of load), the DC voltage nearly remains constant. On variation of DC link voltage, the spike and overshoot of the responses have been studied and suitable DC link voltage has been selected. All responses are obtained trough MATLAB simulink tool box and presented here for clarity of the control strategy. © 2013 IEEE.


Pany P.K.,Dhaneswar Rath Institute of Engineering and Management Studies | Ghoshal S.P.,National Institute of Technology Durgapur
Neural Computing and Applications | Year: 2015

Price forecasting has become one of the main focuses of electric power market research efforts as price is the key index to evaluate the market competition efficiency and reflects the operation condition of electricity market decision making. The work presented in this paper makes use of local linear wavelet neural networks to find the market clearing price for a given period, which is based on similar days approach. The results obtained through simulation are compared to other evolutionary optimization techniques surfaced in the recent state-of-the-art literature, including wavelet neural network model. The results presented in this paper demonstrate the potential of the proposed approach and show its effectiveness for electricity price forecasting. © 2015, The Natural Computing Applications Forum.


Panda N.,Dhaneswar Rath Institute of Engineering and Management Studies | Choudhary R.N.P.,Institute of Physics, Bhubaneswar
Journal of Materials Science: Materials in Electronics | Year: 2015

The polycrystalline samples of lead titanate-modified bismuth ferrite [i.e., (BiFeO3)1−x + (PbTiO3)x with x = 0.0, 0.1, 0.2, 0.3] were synthesized by a high-temperature solid-state reaction route. The formation of the materials was confirmed through basic structural analysis using X-rays diffraction data collected at room temperature. Detailed studies of dielectric and impedance characteristics of the materials in a wide frequency (1 kHz–1 MHz) and temperature (30–500 °C) ranges using complex impedance spectroscopic method have provided many new results. The frequency dependence of ac conductivity suggests that the samples obey Jonscher’s universal power law. A strong co-relation between the micro-structural and impedance parameters was observed. The frequency-temperature dependence of electric modulus and impedance parameters of the materials shows the presence of non-Debye type of relaxation. © 2015, Springer Science+Business Media New York.


Das G.,Dhaneswar Rath Institute of Engineering and Management Studies | Pattnaik P.K.,KIIT University | Padhy S.K.,Siksha O' Anusandhan University
Expert Systems with Applications | Year: 2014

In this paper, we apply Artificial Neural Network (ANN) trained with Particle Swarm Optimization (PSO) for the problem of channel equalization. Existing applications of PSO to Artificial Neural Networks (ANN) training have only been used to find optimal weights of the network. Novelty in this paper is that it also takes care of appropriate network topology and transfer functions of the neuron. The PSO algorithm optimizes all the variables, and hence network weights and network parameters. Hence, this paper makes use of PSO to optimize the number of layers, input and hidden neurons, the type of transfer functions etc. This paper focuses on optimizing the weights, transfer function, and topology of an ANN constructed for channel equalization. Extensive simulations presented in this paper shows that, as compared to other ANN based equalizers as well as Neuro-fuzzy equalizers, the proposed equalizer performs better in all noise conditions. © 2013 Elsevier B.V. All rights reserved.

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