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14 سدھراں ماری

سدھراں ماری

 

                ایہہ فوٹو رضیہ دی منگنی دی اے۔ رضیہ شرمائی ہوئی نمھا جہیا ھاسا بلھیاں اتے سجائی، نیویاں نظراں کیتاں ہوئیاں بہت ای سوہنی لگ رہی سی۔ علی رضیہ ول ویکھ کے ہس رہیا سی۔ ایہہ فوٹو اوس ویلے کچھی گئی سی جدوں علی نے منگنی دی مندری رضیہ دے گورے گورے ہتھ دی کومل تے نازک انگلی وچ پائی۔ رضیہ دی حیاتی دی شاید ایہہ پہلی تے آخری خوشی سی۔ کیوں جے رضیہ ہمیش ای ساڈے نال اپنی بدقسمتی دارونا روندی سی۔ ہمیش آکھدی ’’میری قسمت ہمیشہ مینوں ہرا دیندی اے۔ جیویں شیشہ پتھر نال ٹکڑاکے چور چور ہوجاندا اے ایویں ای میری حیاتی وی شیشے وانگ بدقسمتی دے پتھر نال کھیہ کھیہ کے دن بدن مکدی جارہی اے۔‘‘

                رضیہ اپنے طالب علمی دے زمانے وچ ہمیش اپنیاں کلاس فیلوز توں اگے نکلنا چاہندی سی۔ پر کسے نہ کسے کارن اوہ اجہیا نہ کر سکی جیویں پچھلے سال نویں جماعت دے شروع وچ ای اوہنے کلاس وچ فسٹ آون لئی ات دی محنت شروع کردتی۔ پر امتحاناں توں ایک مہینا پہلاں اوہ اینی بیمار ہوئی کہ کتاباں تاں اک پاسے اوس دے بچن دی امید وی ختم ہوندی جاپی۔ پرجدوں امتحان مک گئے تاں ہولی ہولی اوہدی صحت بحال ہوئی تے کلاس وچ اوہ اٹھویں نمبر تے آئی۔ ایویں دسویں جماعت...

فتوی کا اسلامی منہج: مجموع فتاوی ابن تیمیہ کے تناظر میں

Im฀m Ibn Taymiyyah is a well-known scholar of Muslims. He was an ocean of knowledge and wisdom. His books prove his excellence He was born in 661 Hijrah in Harr฀n (Syria). He learned every kind of knowledge especially religious knowledge i. E knowledge of Qur’฀n, Tafs฀r, Had฀th, Fiqh, Jurisprudence, philosophy, inheritance law, mathematics, grammar, literature, and poetry etc. He wrote hundreds of books about the above mentioned fields. He was permitted to give Fatw฀ (verdict) in his early age. He was successful in achieving the position of Ijtih฀d (authoritative interpretation of Islamic Law). Ibn Taymiyyah Studied the Profound Books of religions and sects. Then he analyzed the works in the light of senior Imams and Qur฀n and Sunnah. He is an extra ordinary person in his knowledge and writings. In brief we can say the fatw฀s of Imam Ibn Taymiyyah have printed in thirty seven volumes. His first ratiocination in Fatwa is from the Holy Qur฀n. He presents the arguments from the Hadith and Sunnah of the Holy Prophet (S. A. W). He considered Ijm฀ ‘ (consensus of Muslim opinion) as a proof of Shar฀‘ah. He presents the point of view of various schools of thought, He trusted in the books of ancient scholars. He also answers the anticipating ambiguity and complication. A few of his fatwas begin with all praise to Allah. His fatw฀s are concordant with the life of the Muslims. In this article a deep study of fatwa of Ibn Taymiyyah has been taken as a guideline for fatwa in Islamic methodology.

Fuzzy Logic and Neural Network Application in Medical Information

Medical practitioner often makes decisions based on incomplete, vague, or uncertain information. Recently fuzzy based techniques have shown a more promising way to handle imprecise data. The approach consists in using the capacities of the commercial database management system while adding a supplementary layer assuring the interface between fuzzy queries. Such a fuzzy relational database management system (FRDBMS) deals more effectively in many applications enhancing the efficiency of processing fuzzy queries even in relational database management system (RDBMS). The implementation from RDBMS to FRDBMS requires knowledge of legacy database, knowledge about fuzzy logic and mapping from crisp to fuzzy values. Software layer is used with RDBMS to convert to FRDBMS, where fuzzy information is to be designed with care. The main feature of FRDBMS is linguistic fuzzy modeling, where the interpretability of the obtained model is the main requirement, together with its accuracy. The research of moving from RDBMS to FRDBMS is limited and not much work has been carried out. The research work presented in this thesis shows fuzzy RDBMS implementation using our developed FDSL Tool, where input to this tool is fuzzy SQL query and output is fuzzy linguistic value results. The FDSL Tool can be used with many fuzzy expert system applications. The developed Fuzzy Model is tested successfully on heart and diabetes datasets. Our implementation achieved an accuracy higher than other contemporary setups working on the same datasets as considered in this work. The improved results were attributed due to the incorporation of linguistic data and its implementation in metadata function.
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