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Item Medical image compression with lossless region of interest using new method: image to text compression(UMT, Lahore, 2015) MUHAMMAD ANAS JAVAIDThe rapid development in medical imaging provided us new knowledge about diseases and complex structure of human body. New technology is being developed to help improve global healthcare system. The aim of this research is to develop an efficient algorithm to compress grayscale medical images at the cost of speed and memory. We have developed lossless, lossy and hybrid image compression algorithms. A group of MRI, X-Ray, CT-scan, Ultra sound, Angiograms and Mammograms images were used for experiments. The performance of purposed algorithm was compared with a state of art JPEG2000 compression technique. The lossy compression technique follows some JPEG base line standard. The overall compression ratio is 2 times better than JPEG with same PSNR. The lossless technique shows 1.2 times better compression ratio than PNG. In medical images only a small portion is diagnostically important hence in ROI diagnostically important area is compressed lossless and remaining area is compressed lossy. Hybrid compression is based on Region of Interest (ROI) coding technique. The overall compression ratio is 4 times better than JPEG and 9 times better than JPEG2000 with same PSNR. Proposed techniques perform well regarding to the compression ratio and quality of reconstructed image, making them suitable for medical purposes.Item Analysis of distribution substation using facts devices(UMT, Lahore, 2015) Hafiz Fuad UsmanElectrical energy has a dynamic role in our society as it is very important in the economic development of any country. In order to fulfill the demand there must be balance between power generation and load demand. In electric power systems, non-linear loads produce harmonics due to which the system undergoes high line losses and un-stability. For power system stability and reliability, static var compensators (SVCs) and Harmonic Filter (HF) are used to eliminate the problem arising due to under voltages and non-linearity at the loaded busbars. The model is developed and analyzed using Electrical Transient Analyzer Program (ETAP). The results clearly show the effectiveness of SVCs and HF in making power distribution system reliable.Item Design and simulation of a demand side management algorithm in a proposed smart grid environment for Pakistan(UMT, Lahore, 2015) MAJID ALIThe electrical energy cannot be stored in large scale because we have no resource to store it in bulk. It has to be produced, transmitted, distributed and used instantly. However the nature of the load is variable with respect to time. The power generating plants are designed for maximum demand. It means the gap between peak load and the average load is high which results in greater per unit cost. The peak load increases suddenly in peak hours so we need to install large power generating plants to meet peak demand. It is not possible for developing countries to install such large power generating units due to limited financial resources. The proposed solution of this problem is Demand Side Management (DSM) technique. In Demand Side Management (DSM) technique the load is shifted to off peak hours which results in financial benefit to residential customers. DSM is an important part of Smart Grid (SG) which is used to shift load to off peak timings as well as reshape load curve. As a result, importance of SG increases and there is a decrease in per unit energy cost. However this research thesis revolves around DSM load shifting techniques for only flexible devices. The flexible devices should be shifted to off peak period. “The Day Ahead Shifting” technique is proposed in this research thesis to minimize the above said problem significantly. Mathematical modelling and simulation in this research thesis are based on residential load during the spring season in Pakistan. This algorithm is developed in Matlab software. The findings of this thesis suggest that DSM approach attains significant energy savings and objective curve.