ڈاکٹر محمد مصطفےٰ زرقاء
گزشتہ دنوں عالم عرب کے ممتاز ماہر فقہ ڈاکٹر محمد مصطفےٰ زرقاء نے بھی اس جہاں فانی کو خیر باد کہا، اناﷲ وانا الیہ راجعون۔
ڈاکٹر صاحب اسلامی فقہ وقانون میں سند کا درجہ رکھتے تھے، ان کی کتاب المدخل الفقھی العام اصول فقہ میں نہایت بلند پایہ خیال کی جاتی اور مرجع و ماخذ کی حیثیت رکھتی ہے، وہ اپنی غیر معمولی فقہی بصیرت کی بنا پر شام میں وزیر انصاف کے عہدہ پر بھی فائز ہوئے۔ ان کے عالمانہ و محققانہ مضامین کے اردو رسالوں میں ترجمے برابر چھپتے رہتے تھے معارف کو بھی ان کے مضامین کے ترجموں کی اشاعت کا فخر حاصل ہے۔ مجلہ البعث الاسلامی لکھنو میں ان کے متعدد مضامین شایع ہوئے ہیں۔ فقہ کے علاوہ دوسرے اسلامی علوم خصوصاً تفسیر و حدیث سے بھی ان کو خاص مناسبت تھی۔ الولدسرلابیہ کے مصداق ان کے فرزند ارجمند ڈاکٹر محمد انس زرقا بھی فقہ اسلامی کے ممتاز اسکالر ہیں جن کے بعض مضامین کا ترجمہ معارف میں شایع ہوچکا ہے۔ اﷲ تعالیٰ علم و دین کے اس خادم کی مغفرت فرمائے۔ آمین!! (عارف عمری، اگست ۱۹۹۹ء)
Orientalists in general have tried to smear the authentically excellent image of the Last Prophet (s. a. w.) and the Qur'an in an effort to cast doubt about the reliability of both the Prophet (s. a. w.) as the Final Messenger of Allah and the Qur'an as the revealed words of Allah. Among other issues they have touched and dwelt on one is what they allegedly refer to as Satanic Verses (praise ofgharEnEq [deities]). Some Orientalists of20th century like Karen Armstrong, Montgomery Watt, and Maxime Rodinson have paid special attention to this issue in their respective works. The very objective of their approach to this false story is to prove that the revelation of the Qur'an was not genuinely from Allah. They dishonestly ignored the very position of this incident fabrication. Many renowned Muslim scholars like Al-Qurtabi, Al-Radi, Qadi Ayaz, andIbnal-’Arab i proved the story related to Satanic Verses as totally baseless. This article analyses Orientalists' views on these called Satanic Verses and concludes that Orientalists failed to maintain their objectivity in their description of the story.
The development of high-quality software at lower cost has always been the main concern of the
developers as well as of the users. Eliminating the defects in software at the initial development
stage can increase quality and reduce the overall cost. Testing only those modules which are likely
to be defective are helpful for development team to manage and use resources effectively. Many
machine learning-based frameworks have been proposed for the prediction of software defects in
initial development stage however accuracy evaluation of proposed techniques on benchmark
datasets was lacked. In this research, we proposed a framework for the prediction of software
defects using ensemble learning and feature selection techniques by using WEKA. The accuracy
of the proposed model has been evaluated by using publicly available cleaned NASA datasets.
Moreover, the results have been compared with the widely used advanced classification
techniques. The Proposed framework consists of five stages. First stage is dealing with the
extraction of relevant dataset. Second stage is dealing with variants of base classifiers and
selection. The base classifiers include: ?Decision Tree (DT), K-nearest neighbor (kNN), Naive
Bayes (NB), Random forest (RF) and Support Vector Machine (SVM)?. Pre-processing and
feature selection have been done in third stage. In fourth stage, we used stacking technique to
create an ensemble of the classifier-variants, which have performed well in third stage. Fifth stage
deals with the results and performance evaluation by using different measures including:
?Precision, Recall, F-measure, Accuracy, MCC and ROC?.