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Subfields of Valued Field and Galois Theory of Transcendental Extensions

Thesis Info

Access Option

External Link

Author

Naseem, Asim

Program

PhD

Institute

Government College University

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2008

Thesis Completion Status

Completed

Subject

Mathemaics

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/5971/1/3444H.pdf

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676727412476

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ڈاکٹر محمد زبیر صدیقی

ڈاکٹرمحمد زبیر صدیقی
علمی اور اسلامی حلقے ڈاکٹر محمد زبیر صدیقی سے خوب واقف ہیں، ان کا عربی زبان اور اسلامی علوم کا مطالعہ بہت وسیع تھا۔ ان کے مقالات اور کتابیں اہلِ علم کے حلقہ میں قدر کی نظر سے دیکھی جاتی تھیں، تدوین حدیث پر ان کی کتاب السیر الحثیث بڑی محققانہ سمجھی جاتی ہے، تصنیف و تالیف کے ساتھ ان کی زندگی کا بڑا حصہ تعلیم و تدریس میں گزرا، پہلے کئی برس لکھنؤ یونیورسٹی کے شعبۂ عربی سے وابستہ رہے، پھر کلکتہ چلے گئے، اور تقریباً ۳۳ سال تک اسلامی تاریخ و تہذیب اور عربی و فارسی زبانوں کی تدریس و تحقیق میں مصروف رہے، عرصہ تک مدرسۂ عالیہ کے صدر، ایشیاٹک سوسائٹی کے نائب صدر اور ملک کی بہت سی یونیورسٹیوں اور علمی اداروں کے رکن بھی رہے، افسوس کے ۱۸؍ مارچ کو علم کا یہ چراغ گل ہوگیا، اﷲ تعالیٰ انہیں اپنی رحمتوں اور نوازشوں سے سرفراز فرمائے، اور ان کے عزیزوں، دوستوں اور شاگردوں کو صبر عطا فرمائے، اور ان کی راہ پر چلنے کی توفیق عطا فرمائے۔ (عبد السلام قدوائی ندوی، اپریل ۱۹۷۶ء)

ڈاکٹر محمد زبیر صدیقی
( پروفیسر مسعود حسن)
ایتھا النفس اجملی جزعا اِن ماتخذرین قد وقعا
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ڈاکٹر صاحب ایک متبحر عالم قرآن و حدیث کے بالغ نظر نکتہ شناس وسیع النظر محقق، تجربہ کار ماہر تعلیم، بے مثل، استاد اور بلند مرتبت اور پروقار شخصیت کے انسان تھے۔
مرحوم بیماری اور کبرسنی کی وجہ سے بے حد کمزور ہوگئے تھے، اور کئی سال سے خانہ نشین تھے، گزشتہ سال اپریل میں ان کی حالت ایسی تشویش ناک ہوگئی تھی کہ نرسنگ ہوم میں داخل کرنا پڑا،...

Socio-Economic Conditions of Home-Based Working Women: A Qualitative Study in Hyderabad, Sindh

This research paper focuses on socio-economic conditions of home-based working women in Hyderabad Division, of Sindh Pakistan. Main objectives of this research are (i) to analyze the Socio-economic condition of home-based working women (ii) to assess the poverty and home-based work (iii) to find out the illiteracy and home-based work (iv) to investigate the role of handicrafts and home-based work in cultural and economic development (v) to unearth the Sindhi culture of handicrafts in Hyderabad Division. To achieve research objectives qualitative research approach is adopted and data is collected by four case studies in Hyderabad division. All cases are selected randomly and analyzed by using thematic analysis method. Present study concluded that researched area is rich in handicrafts business. Women engaged themselves in home-based work due to poverty, unemployment and poor financial conditions of their families. This business has very low profit but female preferred this work due less skills and education required to carry handicrafts business. Home-based workers felt empowered due to having their own income and took part in decision making. In last it is recommended for policy makers and government agencies to give priority to this business because it has potential. It is necessary for economic development of families, culture and country.

Retinal Image Analysis & Hybrid Classifier for Screening of Diabetic Retinopathy

Medical image analysis is very popular research area these days in which digital images are analyzed for the diagnosis and screening of different medical problems. Diabetic retinopathy (DR) is an eye disease caused by the increase of insulin in blood and may cause blindness if not treated in time. Healthy retina contains blood vessels, optic disc and macula as main components but abnormal retina may contain other components and signs as well. An au- tomated system for early detection of DR can save patient’s vision and can also help the ophthalmologists in screening of DR. In this thesis, we develop algorithms for retinal image analysis based on image processing and pattern classification. Image processing techniques are used for retinal image enhancement and pattern recognition is used for classification of DR stages. The proposed system consists of different stages such as preprocessing, compo- nent extraction, candidate region detection, feature extraction and finally the classification. The first phase consists of input retinal image enhancement, noise removal, extraction of main retinal components and candidate lesions detection. We apply Gabor wavelets and Gabor filter banks for lesion detection. The system then extracts features from candidate lesions using four main properties, i.e. shape, color, gray level and statistical. Finally the classifier takes the feature vectors as inputs and grades the input retinal image into dif- ferent stages of DR. We present a hybrid classifier which combines the Gaussian Mixture Model (GMM), Support Vector Machine (SVM) and an extension of multimodel mediod based modeling approach in an ensemble to improve the accuracy of classification. The im- plemented algorithms are tested and evaluated on publicly available retinal image databases using performance parameters such as sensitivity, specificity, positive predictive value and accuracy. The performance improvement of our proposed system is demonstrated by com- paring them with recently proposed and published methods.