A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sundari, G.
- Steroidogenic Gene Expression in the Brain of an Indian Major Carp, Labeo rohita (HAM.)
Authors
1 Endocrinology Unit, Department of Zoology, Madras Christian College, Tambaram, Chennai-600059, IN
Source
Indian Journal of Science and Technology, Vol 4, No S8 (2011), Pagination: 47-48Abstract
No AbstractReferences
- Costa, E., Paul, S. (eds). 1991. Neurosteroids and brain function. Fidia Research Foundation symposium series. Thieme New York, Vol 8.
- Ebner, M.J., Corol, D.I., Havlikova, H., Honour, J.W., Fry, J.P. 2000. Identification of Neuroactive steroids and Their precursors and metabolites in adult male rat brain. Endocrinology, 147: 179-190.
- Kazuyoshi Tsutsui, 2006. Biosynthesis, mode of action and functional significance of neurosteroids in the developing Purkinje cell. J. Steroid Biochem. Mol. Biol. 102: 187–194.
- Performance Analysis of Rate Control Scheme in H.264 Video Coding
Authors
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 ECE Department, Sathyabama University, Chennai - 600119, Tamil Nadu, IN
3 Robotics Division, CVRDE, Avadi, Chennai – 600054, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 30 (2016), Pagination:Abstract
Background/Objectives: Digital Video streams represent huge amount of data at high definition resolution. The video in its original size needs more time and large storage space, which necessitates video compression. To surpass the challenges in video compression those appear in terms of latency, the rate control scheme is the best method. To provide an efficient video coding based on H.264/AVC at substantially low bit rate. This ensures higher performance in terms of compression ratio, lower complexity and video reconstruction. Methods/Statistical Analysis: The cost estimation technique is complex and takes considerable time for computation. In an attempt to make it simple, rate distortion baseline profile encoder is parallelized, which makes the R-D cost calculation feasible. Findings: In this work, the performance analysis of Rate control scheme with optimized Quantization parameter value is carried out. This rate-control scheme in the macro-block layer of H.264 baseline encoder with bit-stream calculation and distortion evaluate can potentially contribute to efficient video transcoding systems. In this proposed work, the rate control for the prediction frame done after encoding the I-frames. Here QP estimation happens between the encoder interface and the user interface. The rate distortion model is attached to the P-frame to perform the rate control for prediction and encoding the P-frames by estimating the QP values, thus making the algorithm less complex. This method achieved the better quality with the optimized quantization parameter. Applications/Improvements: The Quantization parameter is varied to regulate the coded bit streams to achieve good perceptual quality that is suitable for surveillance applications.
Keywords
Bit Rate, Cost Estimation, Compression Ratio, Rate Control Scheme, Rate Distortion Modeling.- Generator Auto Load Power Control in Power Generating Station
Authors
1 Embedded System, Sathyabama University, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai – 600119, Tamil Nadu, IN
2 Instrumentation-II, Ennore Thermal Power Station, Kathivakkam High Road, Girija Nagar, Ennore, Chennai – 600057, Tamil Nadu, IN
3 Department of Electronics and Communication Engineering, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai – 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 11, No 23 (2018), Pagination: 1-8Abstract
In Thermal power plant, Automatic Generation Control (AGC) is a system for adjusting the output power of multiple generators at different power plants, in response to load changes. Since a power grid requires load generation and closely balancing load moment by moment, frequent adjustments to the output of generators are mandatory. The balance can be predicted by measuring the system frequency; if it is rises, more power is being generated than used, which causes all the machines in the system to rise and accelerate. If the frequency of the system is decreasing, more supply of load is on the system than the instantaneous generation can provide, which causes all generators to slow down Load following power plants run during the day hours and early evening. They either shut down or greatly minimize the output during the night and early morning, when the demand for electricity is the lowest. The exact hours of operation depend on various factors. One of the most necessary factors for a particular plant is how efficiently it can convert fuel into electricity. The most efficient plants, which are almost invariably the less cost to run per kilowatt-hour produced, are brought online first. As demand increases, the next most efficient plants are brought on line and so on. The status of the electrical power grid in that particular region, especially how much is the capacity of base load generation. It has, and the variation in demand is also very crucial. An additional factor for operational variability is that excess demand does not deviate just between night and day. There are also significant variations in the time of year and day of the week. A region that has large variations in demand will require a huge load following or peaking power plant capacity because base load power plants can only cover the capacity equal to that needed during times of lowest demand.References
- Power system stability and control. New York: Mc-Graw-Hill; 1994.
- Noguchi S, Shimomura M, Paserba J. Improvement to a high side voltage control. IEEE Transactions on Power Systems. 2006 May; 21(2):683–92. Crossref.
- da Silva E, Hedgecock J, Mell J, da Luz JF. Practical cost-based approach for the voltage ancillary service. IEEE Transactions on Power Systems. 2001 Nov; 16(4):806–12. Crossref.
- Dong F, Chowdhury BH. Improving voltage stability by reactive power reserve management. IEEE Transactions on Power Systems. 2005 Feb; 20:338–45. Crossref.
- Elberly TW, Schaefer RC. Voltage versus VAR/power factor regulation on synchronous generators. IEEE Transactions on Industry Applications; 2002. p. 37–43.
- Milijanovic R. Grupno upravljanje agregatima u elektrani. Nikola Tesla. Beograd, Monografija, Elektrotehnicki institute; 1986.
- Dragosavac J, Janda Z, Ninkovic P, Pejovic J, Dobricic S, Gajic T. Grupni regulator pobude i aktivne snage u TE “Nikola Tesla”—Obrenovac, Nikola Tesla. Beograd, Projekat, Elektrotehnicki institute; 2009.
- Dragosavac J, Janda Z, Milanovic JV, Mihailovic L. Coordinated Q-V regualtion in steam power plant—Design of real time simulator. 7th Mediterranean Conference on Power Generation, Transmission and Distribution, MedPower 2010 (CD-ROM), Agia Napa, Cyprus, 2010 Nov 7–10; 2010.
- Dragosavac J, Janda Z, Milanovic JV. Coordinated regulation of reactive power in multi-generator steam power plant. Energija.
- IEEE Guide for Synchronous Generator Modeling Practices in Stability Analyses, IEEE Std. 1110-1991, Mar; 1991.
- Saccomanno F. Electric power systems. Piscataway, NJ: IEEE Press/Wiley Interscience; 2003. Crossref.
- Martins N, Pellanda PC, Rommes J. Computation of transfer function dominant zeros with application to oscillation damping control of large poser systems. IEEE Transactions on Power Systems. 2007 Nov; 22(4):1657–64. Crossref.
- Corsi S, Pozzi M, Sabelli C, Serrani A. The coordinated automatic voltage control of the Italian transmission Grid—Part I: Reasons of the choice and overview of the consolidated hierarchical system. IEEE Transactions on Power Systems. 2004 Nov; 19(4):1723–32. Crossref. Crossref.
- Van Cutsem T, Vournas C. Voltage stability of electric power system. New York: Springer; 1998.
- van de Vegte J. Feedback control systems. Englewood Cliffs, NJ: Prentice-Hall; 1986.