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Superovulatory Response in Sahiwal Donors at Government Farm Okara

Thesis Info

Author

Sultan Mahmood

Supervisor

Ijaz Ahmad

Institute

Allama Iqbal Open University

Institute Type

Public

City

Islamabad

Country

Pakistan

Thesis Completing Year

2006

Thesis Completion Status

Completed

Page

80

Subject

Agriculture & Related Technologies

Language

English

Other

Call No: 636.2 SUS; Publisher: Aiou

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676710505542

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مولانا عبدالماجد دریا بادی

آہ! مولانا عبدالماجد دریابادی
معارف کے زیر نظر شمارہ کی کتابت ہوچکی تھی کہ فخر روزگار، یگانہ وقت، مجاہد العلم، رئیس القلم اور دارالمصنفین کی مجلس ارکان کے صدر نشین مولانا عبدالماجد دریاباری کی رحلت کی اچانک خبر ریڈیو سے سنی تو ع عجب اک سانحہ ہوگیا ہے۔
ان کی زندگی کی شاندار کتاب ختم ہوگئی، جس کا ہر ورق اپنی گوناگوں خوبیوں سے مزین رہا، یہ عاجز راقم گزشتہ ۴۲ سال سے ایک ادنی خورد کی حیثیت سے ان کی بزرگانہ شفقت اور علمی جلالت کے سامنے سرتسلیم خم کرتا رہا، اس مدت میں ان کی زندگی کی جو سرگرمیاں رہیں وہ متحرک تصویروں کی طرح نظروں کے سامنے گھومنے لگیں۔
گل و آئینہ کیا ، خورشید و مہ کیا
جدھر دیکھا تدھر تیرا ہی رو تھا
کیننگ کالج لکھنؤ سے بی،اے کرنے کے بعد ان کی زندگی کا آغاز الحاد وبے دینی کی وادی کی سیر سے ہوا، مگر یہیں ان کی نظر شعلۂ طور بن کر چمکی، جس کے بعد وہ توحید اور رسالت کے ایسے داعی اور مبلغ بنے کہ سندیافتہ عالم نہ ہونے کے باوجود باوقار عالم تسلیم کیے گئے، اچھے اچھے علماء ان کے سامنے جھکے، کبھی علماء کی مجلس کے سرخیل بھی منتخب ہوئے اور ان کا خاتمہ بالخیر کلام پاک کے مفسر اور شارح کی حیثیت سے ہوا، انھوں نے اردو اور انگریزی میں جو تفسیر لکھی ہے اس میں اسرائیلیات کی فتنہ سامانیاں اور توریت و انجیل کی تحریفات کی شرانگیزیوں کی راز کشائی میں جو دیدہ وری اور نکتہ وری دکھائی ہے اس سے کلام پاک کے مفسروں میں ان کا مقام ہمیشہ نمایاں رہے گا، ان کی یہ تفسیر گنجینہ معارف و تحقیق بھی سمجھی جاتی رہے گی۔
وہ کچھ دنوں تک فلسفی بھی رہے، ان کی ’’فلسفہ جذبات‘‘ اور ’’فلسفہ اجتماع‘‘ ان کی ابتدائی...

حکیم مومن خان مومن ؔ کے معاشقے

This paper aims a comprehensive investigation to identify the various (love stories) of Hakim Momin Khan Momin. Hakim was a romantic poet. His poetry depicts ideal romance. Hakim Momin Khan Momin was a very much elated person. He faced utter faliar in the art of love. He was fond of Platonic love but he always faced materialistic love from his beloved. He was fed off from the un successful love from his beloved.  For romance and true love, he left his educational career incomplete. Hakimi is fond of physical beauty. His poetry mostly consists of modesty and a slight touch of satiation.

Development of Feature Selection Algorithms for High-Dimensional Binary Data

There has been a growing interest in representing real-life applications with data sets having binary-valued features. These data sets due to the advancements in computer and data management systems consist of tens or hundreds of thousands of features. In this dissertation, we investigate two problems in machine learning which have been relatively less studied for high-dimensional binary data. The first problem is to select a subset of features useful for supervised learning applications from the entire feature set and is known as the feature selection (FS) problem. The second problem is to compare two orderings of features induced by feature ranking (FR) algorithms and to determine which one is better. For the feature selection problem, we have proposed a new feature ranking measure termed as the diff-criterion. Its distinct attribute is that it estimates the usefulness of binary features by using their probability distributions. The diff-criterion has been evaluated against two well-known FS algorithms with four widely used clas- sifiers on six binary data sets on which it has achieved up to about 99% reduction in the feature set size. To further improve the performance, we have suggested a two-stage FS algorithm. The novelty of our two-stage algorithm is that the first stage provides the second stage with a reduced subset without losing valuable in- formation about the class. Two-stage feature selection used with the diff-criterion not only significantly improves the classification accuracy but also exhibits up to about 99% reduction in the feature set size. We have also compared our proposed FS algorithms against the winning entries of the “Agnostic Learning versus Prior Knowledge” challenge. The algorithms have shown results better or comparable to the winners of the challenge. For the problem of ranking features using FR algorithms, different FR algorithms estimate the importance of features with respect to the class variable differently thus generating different orderings. To determine which ordering is better, we propose a new evaluation method termed as feature ranking evaluation strategy (FRES). It uses the individual predictive power of features for estimating howAbstract correct is an ordering of features. We found that compared to Relief and mu- tual information algorithms our proposed diff-criterion generates the most correct orderings of binary features.