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تضمین بر مشہورِ زمانہ نعت بہ قلمِ نصیر احمد اخترؔ
دمِ عیسیٰؑ نہیں دیکھا ! یدِ بیضا نہیں دیکھا !
جہاں میں چشمِ جبرائیلؑ نے کیا کیا نہیں دیکھا
جمالِ ماہِ کنعاؑں کا حسیں جلوہ نہیں دیکھا! !
جہاں دیدہ نگا ہوں نے بہت ڈھونڈا نہیں دیکھا
زمانے میں محمد مصطفیٰؐ جیسا نہیں دیکھا
ستاروں کی ضیاؤں سے زمینِ ثور کہتی ہے
قمر کی دلکشی پر خوب کر کے غور ، کہتی ہے
فلک پرکہکشاں پھر پھیل کر ہر طور کہتی ہے
نگاہِ آسماںؐ لیتی ہے بوسے اور کہتی ہے
بہت دیکھے ہیں لیکن اُنؐ سا نقشِ پا نہیں دیکھاا
فلک کی عظمتیں قربان اس کے ذرّے ذرّے پر
قطار اندر قطار آتے ہیں قدسی آستانے پر
فدا ہے رفعتِ سدرہ اسی پرنور خطّے پر
فرشتے سر نگوں پائے گئے آقاؐ کے روضے پر
رسولوں میں بھی کوئی اُنؐ کا ہم پایہ نہیں دیکھا
کوئی عنصر نہیں دوئی کا اس منظر سہانے میں
کرن سورج کی ہے ناکام اس کی مثل لانے میں
زمیں پر چلنے پھرنے میں’ دنیٰ ‘‘تک آنے جانے میں
مُسلم آپؐ کی یکتائی ہے سارے زمانے میں
کہیں چشمِ فلک نے آپؐ کا سایہ نہیں دیکھا
Fiqh Islami or Islamic Jurisprudence is Muslim sacred law based on primary Islamic sources i. E. Quran and Sunnali and which provides code ofconduct to Muslims in all spheres of life. Manu Dharam Shastra or laws of Manu is one of the standard books of Hindu religious law. This article aims at comparative study of 'lawsuit in Hinduism and Islam' in light ofFiqh Islamic and Manu Dharam Shastra.
Computer, the humongous giant of technology, has brought innovative changes in every aspect of life, especially in applications imitating humans. Currently, it is used in every field of life to facilitate human endeavor. One such application is character recognition. Character recognition is an important offshoot of pattern recognition problems. It imitates a human’s ability to read, using a machine. It has been a field of intensive, if exotic, research since the early days of the computer. This task becomes more complex and demanding in case of handwritten and cursive text. Arabic script-based languages, which are used by almost a quarter of the world’s population [Belaid et. al, 2010], are cursive, rich in diacritical marks and variety of writing styles present a challenging task for the researchers. Urdu is an Arabic script based languages however the Urdu character set is the superset of all Arabic script-based languages. Character recognition has been performed either through segmentation free or segmentation based approaches. There are numerous issues with a segmentation free approach, and it is very difficult to train using a large dataset. On the other hand in Urdu, a segmentation based approach has a large overhead and has less accuracy for cursive script as compared to segmentation free methods. In terms of classification, this thesis presents two approaches for Urdu character recognition: segmentation free method based on a hybrid approach (HMM and fuzzy logic), and bio-inspired character recognition system that uses fuzzy logics. Fuzzy is used as inner and outer shells for preprocessing and post processing of HMM. Biologically inspired multilayered fuzzy rules based system has been presented. Using the human visual concept, a layered approach has been suggested where the diacritical marks are separated from the ghost characters and mapped onto the primary ligature in the final layer. The proposed technique also caters to Multilanguage character recognition system for all Arabic script-based languages like Arabic, Persian, Urdu, Punjabi etc. The presented multilayered bio-inspired approach recognizes the ligature by extracting the features and combining them to find new premises in a bottom up fashion and it provided accuracy of 87.4%.