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A study of violation of PEMRA code of conduct in Pakistani entertainment channels

Thesis Info

Author

Saima Saleem

Supervisor

Syed Abdul Siraj

Department

Department of Media & Communication Studies

Program

MS

Institute

International Islamic University

Institute Type

Public

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2015

Thesis Completion Status

Completed

Page

107

Subject

Media and Communication Studies

Language

English

Other

MS 174.9097 SAS

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676721475878

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پروفیسر خورشید الاسلام

پروفیسر خورشید الاسلام
پروفیسر خورشید الاسلام ۱۸؍ جون کو علی گڑھ کی خاک کا پیوند ہوگئے، اناﷲ وانا الیہ راجعون۔
وہ جولائی ۱۹۱۹؁ء میں مراد آباد اور بجنور کی سرحد پر واقع ایک گاؤں امری میں پیدا ہوئے، یہ اور مشہور شاعر اختر الایمان گہرے دوست تھے اور فتح پوری ہائی اسکول میں ساتھ ہی پڑھتے تھے اور دونوں اسکول کے مشہور ڈبیٹر اور بہترین مقرر تھے، بی اے کرنے کے بعد خورشید الاسلام صاحب کچھ عرصے رسالہ ’’آج کل‘‘ کے سب اڈیٹر رہے اور ۱۹۴۳؁ء میں ایم اے کرنے کے لیے علی گڑھ مسلم یونیورسٹی آئے، یہاں پھر اختر الایمان کا ساتھ ہوا اور دونوں ۱۹۴۴؁ء میں یونیورسٹی کی نمائندگی کے لیے حیدر آباد گئے اور ہفت روزہ اردو کانگریس میں شریک ہوئے، خورشید الاسلام صاحب ۱۹۴۵؁ء میں ایم اے کرنے کے بعد علی گڑھ یونیورسٹی کے شعبہ اردو میں لکچرر ہوگئے اور ۱۹۷۳؁ء میں پروفیسر ہوئے،اور جب پروفیسر آل احمد سرور سبکدوش ہوئے تو یہ صدر شعبہ ہوئے۔
مضمون نگاری شروع کی تو مولانا شبلی پر ہاتھ صاف کیا، مولانا پر ان کا یہ مضمون ان کی کتاب ’’تنقیدیں‘‘ میں شامل ہے، اس کا آغاز اس طرح کیا ہے ’’شبلی پہلے یونانی تھے جو مسلمانوں میں پیدا ہوئے‘‘ بعض لوگوں کا خیال ہے کہ یہ مضمون ان کی علمی شہرت کا باعث بنا اور مولانا ابوالکام آزاد نے اس کو بہت پسند کیا، ان کی سفارش پر خورشید صاحب کو لندن یونیورسٹی میں ملازمت مل گئی مگر راقم نے سنا ہے کہ مولانا نے ان کے نام ہی کو غلط قرار دیا کہ اس میں مضاف و مضاف الیہ دولسانی ہیں۔
بہرحال وہ لندن یونیورسٹی میں تدریسی خدمت پر مامور رہے اور آکسفورڈ یونیورسٹی سے شائع ہونے والی اردو انگریزی لغت کے اڈیٹر بھی مقرر ہوئے، انہوں نے یونیسکو پروجیکٹ کے تحت ’’غالبؔ۔ حیات اور...

حقوق نسواں کا عالمی معاہدہ اور شریعت اسلامیہ: تقابلی مطالعہ CEDAW

Women are confronted with a lot of problems. In different parts of the world, some social and cultural attitudes still discourage the women from getting their established and assigned rights. The factors which are responsible for this phenomenon include societal norms, orthodoxy and some social customs contrary to islamic instructions. For instance, discrimination against women could be in terms of inadequate nutrition, denial or limited access to education, health and property rights, child labor, domestic violence and forceful marriage. So far as the Islamic instructions are concerned, these are derived from Quran and Sunnah and clearly describe women’s rights but, due to some socio-religious customs and undesirable behaviors the societal status and role of women have been badly affected. An international document, the convention on the elimination of all forms of discrimination against women also lists the rights of all girls and women. CEDAW recommends that all discriminations against girls and women must be ended. In this paper, the terms have been analyzed in the context of islamic instructions and teachings, in order to provide academic material for bringing positive change in the society.

A Technique for the Design and Implementation of an Ocr for Printed Nastalique Text

This thesis presents a novel segmentation free technique for the design and implementation of an OCR (Optical Character Recognition) system for printed Nastalique text. Specific area of this thesis is document understanding and recognition which is a branch of computer vision and in turn a sub-class of Artificial Intelligence. Optical character recognition is the translation of optically scanned bitmaps of printed or hand written text into digitally editable data files. OCRs developed for many world languages are already under efficient use but none exist for Nastalique – a calligraphic adaptation of the Arabic script, just as Jawi is for Malay. More often, a single script with its basic character shapes is adapted for writing in multiple languages e.g. the Roman script for English, German and French, and the Arabic script for Persian, Sindhi, Urdu, Pashtu and Malay. Urdu has 39 characters against the Arabic 28. Each character then has two to four different shapes according to their position in the word: isolated, initial, medial and final. Many character shapes have multiple instances and are context sensitive – character shapes changing with changes in the antecedent or the precedent character. At times even the third or the fourth character may cause a similar change depicting an n-gram model in a Markov chain. Unlike the Roman script, word and character overlapping in Nastalique, makes optical recognition extremely complex. Compared to Roman script languages’ OCRs very little research work is done on Arabic Naskh OCR. Only a few Arabic Naskh OCR systems are available today and they too are far from perfect, lagging behind in accuracy as compared to Roman script OCR systems. In this perspective Nastalique is even more complicated than Naskh as it has multiple base lines, more overlapping of characters within a ligature and between adjacent ligatures, vertical stacking of characters in a ligature etc. Urdu has still not attracted researchers’ attention for the development of OCR partly due to lack of funds in this area but mainly due to the challenges the Nastalique style offers because of its cursiveness and context-sensitivity. For the same reason published research work in this area is nearly non-existent. The proposed system for Nastalique OCR does not require segmentation of a ligature into constituent character shapes. However, it does require segmentation at two levels i.e. first the text image is segmented into lines of text then each of the lines of text is further segmented into ligatures or isolated characters. The next step is a line by line cross-correlation for recognition of characters in the ligatures whereby, character codes are written into a text file in the sequence the characters are found in the ligature. As the recognition process is completed, the character codes in the text file are given to the rendering engine, which displays the recognized text in a text region. The limitation of the proposed Nastalique character recognition system is that it is font dependent: it needs the same font file for recognition which was used to write the text in. The new undertaking has greater challenges as it will aim to overcome the inherent cursiveness and context sensitivity of Nastalique style of writing. For Nastalique OCR, we develop character-based True Type Font files for a few Nastalique words. These words are written using the same character-based TTF font and an image is made of the Nastalique text. The image is then given to our Nastalique OCR. After recognition the rendering is done by using the same TTF font file to display the recognized text. The work is therefore three folds; development of character-based Nastalique True Type Font, Nastalique character recognition and rendering the recognized text using character-based Nastalique True Type Font. Since our character-based segmentation-free Nastalique OCR algorithm needs, as a ground work, a character-based Nastalique Text Processor, we have also proposed a Finite State Nastalique Text Processor Model. Implementation is not yet done so results are not reported. However this model could serve as an impetus for future research in this challenging field. Optical Character Recognition for Roman script languages is almost a solved problem for document images and researchers are now focusing on extraction and recognition of text from video scenes. This new and emerging field in character recognition is called Video OCR and has numerous applications like video annotation, indexing, retrieval, search, digital libraries, and lecture video indexing. The emerging field for character recognition is attracting research on other scripts like Chinese, but to the best of our knowledge, no work is reported as yet, on Video OCR for Arabic script languages like Arabic, Persian and Urdu. As an extension of our Nastalique OCR to Video OCR for Arabic script languages, we have also performed experiments on video text identification, localization and extraction for its recognition. We have used MACH (Maximum Average Correlation Height) filter to identify text regions in video frames, these text regions are then localized and extracted for recognition. All research and development work is done using Matlab 7.0. Experiments and results are reported in the thesis.