A generalized algorithm and reconfigurable

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Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
A Generalized Algorithm and Reconfigurable
Architecture for Efficient and Scalable
Orthogonal Approximation of DCT
Abstract—Approximation of discrete cosine transform (DCT) is useful for
reducing its computational complexity without significant impact on its coding
performance. Most of the existing algorithms for approximation of the DCT target
only the DCT of small transform lengths, and some of them are non-
orthogonal.This paper presents a generalized recursive algorithm to obtain
orthogonal approximation of DCT where an approximate DCT of length could be
derived from a pair of DCTs of lengthat the cost of additions for input
preprocessing. We perform recursive sparse matrix decomposition and make use of
the symmetries of DCT basis vectors for deriving the proposedapproximation
algorithm. Proposed algorithm is highly scalablefor hardware as well as software
implementation of DCT of higherlengths, and it can make use of the existing
approximation of 8-point DCT to obtain approximate DCT of any power of two
length, .We demonstrate that the proposed approximationof DCT provides
comparable or better image and video compression performance than the existing
approximation methods. It is shown that proposed algorithm involves lower
arithmetic complexity compared with the other existing approximation algorithms.
We have presented a fully scalable reconfigurable parallel architecture for the
computation of approximate DCT based on the proposed algorithm. One uniquely
interesting feature of the proposed design is that it could be configured for the

computation of a 32-point DCT or for parallel computation of two 16-point DCTs
or four 8-point DCTs with a marginal control overhead. The proposed architecture
is found to offer many advantages in terms of hardware complexity, regularity and
modularity. Experimental results obtained from FPGA implementation show the
advantage of the proposed method.
SOFTWARE REQUIREMENT:
 ModelSim6.4c.
 Xilinx 9.1/13.2.
HARDWARE REQUIREMENT:
 FPGA Spartan 3.
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement (Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (NearMaruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Mail: logicmindtech@gmail.com

Electrical, Electronics and Computer Engineering, Information Engineering and Technology, Mechanical, Industrial and Manufacturing Engineering, Automation and Mechatronics Engineering, Material and Chemical Engineering, Civil and Architecture Engineering, Biotechnology and Bio Engineering, Environmental Engineering, Petroleum and Mining Engineering, Marine and Agriculture engineering, Aerospace Engineering.

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Power plants release a large amount of water vapor into the atmosphere through the stack. The flue gas can be a potential source for obtaining much needed cooling water for a power plant. If a power plant could recover and reuse a portion of this moisture, it could reduce its total cooling water intake requirement. One of the most practical way to recover water from flue gas is to use a condensing heat exchanger. The power plant could also recover latent heat due to condensation as well as sensible heat due to lowering the flue gas exit temperature. Additionally, harmful acids released from the stack can be reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation. Condensation of vapors in flue gas is a complicated phenomenon since heat and mass transfer of water vapor and various acids simultaneously occur in the presence of noncondensable gases such as nitrogen and oxygen. Design of a condenser depends on the knowledge and understanding of the heat and mass transfer processes. A computer program for numerical simulations of water (H2O) and sulfuric acid (H2SO4) condensation in a flue gas condensing heat exchanger was developed using MATLAB. Governing equations based on mass and energy balances for the system were derived to predict variables such as flue gas exit temperature, cooling water outlet temperature, mole fraction and condensation rates of water and sulfuric acid vapors. The equations were solved using an iterative solution technique with calculations of heat and mass transfer coefficients and physical properties.

Water Industry Process Automation and Control Monthly - May 2024.pdf

Water Industry Process Automation & Control

Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control. In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.

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Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering. This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom. Author: Robbie Edward Sayers Collaborators and co editors: Charlie Sims and Connor Healey. (C) 2024 Robbie E. Sayers

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A generalized algorithm and reconfigurable

1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 A Generalized Algorithm and Reconfigurable Architecture for Efficient and Scalable Orthogonal Approximation of DCT Abstract—Approximation of discrete cosine transform (DCT) is useful for reducing its computational complexity without significant impact on its coding performance. Most of the existing algorithms for approximation of the DCT target only the DCT of small transform lengths, and some of them are non- orthogonal.This paper presents a generalized recursive algorithm to obtain orthogonal approximation of DCT where an approximate DCT of length could be derived from a pair of DCTs of lengthat the cost of additions for input preprocessing. We perform recursive sparse matrix decomposition and make use of the symmetries of DCT basis vectors for deriving the proposedapproximation algorithm. Proposed algorithm is highly scalablefor hardware as well as software implementation of DCT of higherlengths, and it can make use of the existing approximation of 8-point DCT to obtain approximate DCT of any power of two length, .We demonstrate that the proposed approximationof DCT provides comparable or better image and video compression performance than the existing approximation methods. It is shown that proposed algorithm involves lower arithmetic complexity compared with the other existing approximation algorithms. We have presented a fully scalable reconfigurable parallel architecture for the computation of approximate DCT based on the proposed algorithm. One uniquely interesting feature of the proposed design is that it could be configured for the

2. computation of a 32-point DCT or for parallel computation of two 16-point DCTs or four 8-point DCTs with a marginal control overhead. The proposed architecture is found to offer many advantages in terms of hardware complexity, regularity and modularity. Experimental results obtained from FPGA implementation show the advantage of the proposed method. SOFTWARE REQUIREMENT:  ModelSim6.4c.  Xilinx 9.1/13.2. HARDWARE REQUIREMENT:  FPGA Spartan 3. PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (NearMaruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Mail: logicmindtech@gmail.com

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