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مدر ٹریسا

مدرٹریسا
مدر ٹریسا بھی۵/ستمبر۱۹۹۷ء بروزجمعہ کوانتقال کرگئیں۔ان کے انتقال سے عیسائی دنیا کو بڑاگہرا دھچکا لگاہے۔ کہنے کو وہ ایک ہمدرد،غمگسار انسانیت تھیں لیکن ان کی تمام خدمات بباطن عیسائیت کی تبلیغ ونشرواشاعت کی معین تھیں اسی وجہ سے انھیں نوبل انعام سے بھی نوازا گیا اورنوبل انعام انھیں کیوں نہ ملتا جبکہ اس کے دینے والے عیسائی مذہب کے پیروکار ہی ہیں۔ ہم مسلمانوں کے لیے ان کی شخصیت میں جودیکھنے کی بات ہے وہ ہے ایمانداری، شرافت جذبۂ خدمت خلق، قربانی، ایثار ہے۔ اپنے مذہب کی تبلیغ انھوں نے اسی جذبہ وایثار اورقربانی کے ساتھ خدمت خلق کے راستے سے کی جوایک سعی میں شامل ہے۔اپنا بچپن،اپنی جوانی، اپنی رشتہ داری عزیز داری سب کچھ اس ایثار کی تئیں خاتون نے اپنے مذہب کے لیے نچھاور کردیا۔۱۹۱۰ء میں پیدا ہوئی یہ خاتون۱۹۲۸ء میں مکمل طورپر اپنے آپ کو خدمت خلق وانسانیت کے راستے سے اپنے مذہب کے سپرد کرچکی تھی۔ اپنی تمام خواہشات اپنی تمام تمنائیں اس نیک خاتون نے اپنے مذہب کو دے دیں۔یہ بہت بڑا مجاہدہ ہے اس خاتون کا، اپنے مذہب پرسچے دل سے قربانی نے انھیں ہماری طرف سے خراج عقیدت کامستحق بنادیاہے۔
[ستمبر۱۹۹۷ء]

 

حد الزاني البكر و المحصن

Islam is a complete code of life and it provides complete guidance in every field of life. Islamic law provides protection to the human wisdom, race and respect. Spiritual purity, sacred heart and environmental cleanliness, is one of the important persistence of Islamic sharia. Every act which leads us towards ignorance, contradiction, ambiguity and vulgarity is prohibiting in human societies. Zina has destroyed the spiritual values of individuals, families, societies and even nations. This ruthless deed is not only prohibited and sentenced in Islam, but also rather detested by other heavenly religions as well. Without discrimination of any religion, many scholars considered this hated act as the source of unrest and anarchy. Physically, ethically, medically, socially and even religiously zina has infinite hindrances in the society. Islam has provided various teachings and precautions to shun from this major sin for the protection of greatness and superiority of humanity. One of the important teachings is punishment for committing this sin, which is known as “Hadd” in Islamic sharia. In the current book, the punishments of married and unmarried (Fornicator) zani have been described in the light of Sunnah and Quran. The important purpose of Qisas and Hadd is the correction of societies, protection of life, respect and wealth, not the humiliation of people. To punish the criminals is the source of rectification for others.

Ant Colony Optimization Based Emerging Pattern Discovery for Supervised Learning

With the growth of internet and advance in computing technologies, large volume of data is generated and processed on daily bases. The situation is very appealing for sophisticated tools and techniques to process and get the insight of such a large data ubiquitous in every domain. Classi - cation and pattern recognition is an important technique in data mining task tond unexplored knowledge within the data. Emerging Pattern (EP) based technique is used to discover an abrupt change in across the datasets. Emerging pattern based classi ers are very e cient innd- ing patterns inherently exist among the collection of large datasets in hand. Nevertheless, the discovery of emerging patterns is a challenging and non-trivial task due to the inherent complexity of datasets. More- over, in contemporary literature plethora of work is available tond a hidden emerging pattern. Among these techniques,tree-based approach is commonly utilized for the discovery of emerging pattern. However, a tree-based approach follows greedy search technique, su ers various limitations i.e. tree size grows with problem size up to the level where tree-based computation is not cost e ective. In this dissertation, a novel approach for discovering emerging patterns has been proposed. The pro- posed approach exploited Ant Colony Optimization (ACO) technique for the exploration of high quality emerging patterns in the classi cation problem. Furthermore, in contrast to the deterministic approach used in tree-based classi ers, the proposed probabilistic method provides com- petitive classi ers. The proposed approach is capable to e ciently avoid an exhaustive search of tree-based approach and obtain comparatively better accuracy to discover strong jumping emerging patterns. The pro- posed approach has been evaluated on various benchmark datasets for accuracy and robustness. Additionally, most of the classi ers are work with discrete data only and Discretization methods are used to change continuous data into discrete before input to a particular classi er. To evaluate the performance of proposed approach on di erent discretiza- tion methods several experiments are carried out to evaluate the robust- ness. Experimental results show that proposed approach provides better performance on di erent datasets in comparison with the state-of-the-art techniques.
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