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New Load Modeling Technique for Transmission Network Harmonic Analysis

Thesis Info

Author

Akhlaq Ahmad.

Department

Department of Electrical, UET

Institute

University of Engineering and Technology

Institute Type

Public

Campus Location

UET Main Campus

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

1996

Thesis Completion Status

Completed

Page

viii, 97 leaves. diagrams.;tabs.,

Subject

Engineering

Language

English

Other

Thesis ( M.Sc. Electrical Engineering ); Call No: 621.3191 A 4 N

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676712524518

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1۔ کہانی پڑھی جارہی ہے

 کہانی پڑھی جارہی ہے

(سید ماجد شاہ)

 چوک میں جہا ز کی ڈمی نصب کی جا چکی تھی۔لڑکی نے چوک سے یو ٹرن لینے کے لیے ،گاڑی کی رفتار آہستہ کی ۔جب گاڑی چوک سے نیم دائرہ بنا کر مڑ رہی تھی تو فرنٹ سیٹ پر بیٹھے ، لمبے بالوں والے لڑکے نے کہا،‘‘ میں ایک منتر نما ایکویشن سے یہ جہاز اڑا سکتا ہوں۔

 لڑکی نے کنکھیوں سے دیکھا جہاز آدھا پینٹ کیا جاچکا تھا۔

 لڑکی، جس کے جسم میں جاری تمام کیمیائی عمل بحالتِ اعتدال کام کر رہے تھے ،جیسے ایک بیس بائیس سال کی مائل بہ فربا خوشحال گھرانے کی لڑکی میں کام کرتے ہیں۔

 اس نے لڑکے کی کپکپاتی مخروطی انگلیوں کو غور سے دیکھا، جن پر سگریٹ کے سرمئی داغ ، تیز گندمی رنگ پر نمایاں تھے۔پھر لڑکی نے بائیں ہاتھ سے اپنی سرخ ٹی شرٹ کا بٹن کھولتے ہوئے پورے یقین سے کہا، ‘‘ میں اس پر اڑنا چاہوں گی۔’’

 گاڑی کا اے سی بند تھا ۔ شیشے تھوڑے نیچے کیے گئے تھے تاکہ سگریٹ کا دھواں خارج ہو سکے، اس عمل سے دھواں باہر ضرور نکل رہا تھا لیکن رد ِ عمل کے طور پر باہر کی شدید گرمی گاڑی میں بھر گئی تھی۔

 جب لڑکی یہ جملہ بول رہی تھی۔‘‘ میں اس پر اڑنا چاہوں گی۔’’تو اس کے لہجے میں مذاق کا عنصر رائی برابر بھی شامل نہیں تھا، کیونکہ جب وہ مذاق کے موڈ میں ہوتی تھی تو اس کی آنکھوں میں شرارت کی لہر ابھر کر بھوؤں کو کمان بنا دیتی اور کمانیں ماتھے پر لطیف شکنیں پیدا کردیتیں۔ اس پر ہونٹوں کے ابھار میں اضافہ اور گالوں کے تھوڑا اٹھ جانے سے اس کا...

نبی کریم ﷺ کے تعدد ازواج کے سماجی اثرات

The seerah of the Holy Prophet (SAW) is a diversified combination of various traits. Among hundreds of the aspects of seerah if analysed various such dimensions appear before us in accordance with the educational and cultural evolution and criticality of time. One of these many is the sociological aspect of the holy seerah of the Prophet (SAW). According to the teachings of the Holy Prophet SAW Islam n Society are quite compatible to each other where marital element holds foremost importance in social circles. There is complete guidance about it in the seerah. The Prophet of Islam himself provided practical model of polygamy which was subjected to severe censure by the non-believers on account of their prejudice, ignorance and dishonesty and which the research scholars of seerah responded to n refuted on logical, convincing and solid grounds. The objective of this thesis is to highlight various positive effects of the polygamy of the Prophet SAW on society and its value in eradicating a number of social evils. Among manifold positive effects of this practice of polygamy include such benefits as the well-being and social elevation of widows, the eradication of the frequent custom of adoption, the extinction of social distinction and discrimination, the removal of tribal n social enmities, the following of the Prophet's model of women's education, the recognition of social work and social workers, and the upbringing of orphans.

Decision Support System for Detection of Hypertensive Retinopathy Using Avr and Papilledema

The interior and vital part of human eye is retina whose function is to capture and send images to brain. It consists of different structures along with two types of blood vessels; veins and arteries. These retinal blood vessels are affected by number of eye diseases such as Hypertensive Retinopathy (HR) and Diabetic Retinopathy (DR). HR is a retinal disease that is caused by consistent elevated blood pressure (hypertension). Many people in the World are suffering from HR disease; however, in most of cases, HR patients are unaware of it. The automated diagnostic systems are very useful for ophthalmologists to diagnose different retinal diseases. With the help of automated systems, the ophthalmologists can monitor and make treatment plan of retinal disease. Many researchers have developed different automated HR detection systems, but no automated system exists that detects and grades HR along with Papilledema (last stage of HR). Most of existing methods only performed artery venous classification rather than complete automated method for HR detection and grading. In this thesis, an automated system is presented that detects the HR at various stages using Arteriovenous Ratio (AVR) and Papilledema (optic disc swelling) signs. The proposed system consists of two modules i.e. vascular analysis for calculation of AVR and optic nerve head region analysis for Papilledema. AVR calculating stage consists of three major modules i.e. main component extraction, Artery and Vein (A/V) classification and AVR calculation. A new set of color and statistical features have been proposed in this research for accurate A/V classification. The proposed system effectively performs A/V classification and vessels width calculation for AVR computation to diagnose and grade HR. Second module detects and grades the Papilledema through analysis of fundus retinal images. The proposed system formulates a feature set which consists of Grey-Level Co-occurrence Matrix, optic disc margin obscuration, color and vascular features. A feature vector of these features is used for classification of normal and Papilledema images using Support Vector Machine (SVM) with its Radial Basis Function (RBF) kernel. The variations in retinal blood vessels, color properties, texture deviation of optic disc and its peripapillary region, and fluctuation of obscured disc margin are effectively identified and used by the proposed system for the detection and grading of Papilledema. In this thesis, a new local dataset AVRDB containing 100 images is developed for analysis of HR and annotated with assistance of expert ophthalmologists of Armed Forces Institute of Ophthalmology (AFIO), Pakistan. The proposed methods are evaluated on the images of INSPIRE-AVR, VICAVR, STARE and newly developed HR dataset (AVRDB). The proposed HR detection method shows the average accuracies of 95.14%, 96.82% and 98.76% for INSPIRE-AVR, VICAVR and AVRDB databases, respectively. It also shows HR grading results with average accuracies of 98.65%, 98.61% and 98.92% for INSPIRE-AVR, VICAVR and AVRDB databases, respectively. The proposed Papilledema detection method shows average accuracy of 92.86% and grading results with average accuracy of 97.85% on hybrid dataset of 160 images (70 images of AVRDB database and 90 images of STARE database), respectively. These results authenticate that this research is a milestone towards automated detection and grading of HR disease.