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Epidemiology and Economical Aspects of Hydatidosis in Different Animals, Man and Its Control in Sheep with Indigenous Plants.

Thesis Info

Author

Muhammad Shafiq

Department

Faculty of Science,Department of Zoology

Program

PhD

Institute

University of the Punjab

Institute Type

Public

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2005

Thesis Completion Status

Completed

Subject

Zoology

Language

English

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676728984958

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خیر ہی خیر سر بہ سر ہونا

خیر ہی خیر سر بہ سر ہونا
کتنا مشکل ہے بے ضرر ہونا

پوچھ اُن سے جو لوگ بے گھر ہیں
کیسا ہوتا ہے اپنا گھر ہونا

زخم نے جا لیا رگِ جاں کو
کیا ہوا تیرا چارہ گر ہونا

نہ سنے نالے آسماں نے مرے
ہائے نالوں کا بے اثر ہونا

کتنی آساں ہے خوب تر کی طلب
کتنا مشکل ہے خوب تر ہونا

دے گیا عمر بھر کے پچھتاوے
سب دعائوں کا بے ثمر ہونا

پا لیا رازِ زندگی تائبؔ
آ گیا کام در بہ در ہونا

اللّغْة في شعر إبراهيم العجلوني

This study worked on studying the language in modern Jordanian poetry, through application to the poetry of the Jordanian poet Ibrahim Al-Ajlouni through his poetic works, subjected to intertextuality in both its religious and literary parts, as well as addressing repetition in its three types, the sentence, the word, and the letter, then the study ended with the conclusion, which included the most important results that the study reached It has through studying the language of the poet.

Histopathology Image Based Breast Cancer Analysis Using Deep Neural Networks

Mitotic count is an important feature for breast cancer diagnosis but their striking resemblance with non-mitoticgures, no proper shape, and scarce number makes their detection a laborious and challenging task. This thesis presents an integrated system for automatic scoring of breast cancer Whole Slide Images. To deal with the imbalance between mitotic and non-mitoticgures a two-phase learning strategy is proposed, where therst phase informatively undersamples the majority class so that the second phase can concentrate more on hard examples. To harness the rich features extraction and mapping capabilities of Deep Neural Networks in case of small dataset, Transfer Learning based segmentation and classi cation is proposed. Finally, to tackle the large sized Whole Slide Images an e ective and e cient method is proposed for region of interest selection and scoring the slides. The integrated system comprising of region of interest selection, mitosis detection, and slide scoring achieved state-of-the-art results with a Kappa score of 0.5823 on a publicly available dataset and constituted a major step towards clinical application of Computer Assisted Diagnosis for the good of humanity.