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Social Media Addiction and Narcissistic Among University Students

Thesis Info

Author

Kausar Fatmi

Supervisor

Samia Wasif

Department

Department of Humanites

Program

BPY

Institute

COMSATS University Islamabad

Institute Type

Public

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2017

Thesis Completion Status

Completed

Subject

Humanites

Language

English

Added

2021-02-17 19:49:13

Modified

2023-01-06 19:20:37

ARI ID

1676720444051

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آج کا طالب علم کل کا رہنما

آج کا طالب علم کل کا رہنما
نحمدہ ونصلی علی رسولہ الکریم امّا بعد فاعوذ بااللہ من الشیطن الرجیم
بسم اللہ الرحمن الرحیم
معزز سامعین اور میرے ہم مکتب شاہینو!
آج مجھے جس موضوع پر لب کشائی کرنی ہے وہ ہے:’’آج کا طالب علم کل کا رہنما ‘‘
صدرِذی وقار!
اس کائنات رنگ و بو میں جو کچھ نظر آ رہا ہے، اس میں کسی نہ کسی کاریگر کی ضرور کاریگری ہے۔ پہاڑوں کو کاٹ کر سرنگیں نکالنا ،آبی اور فضائی راستوں کا تعین کرنا، زمین کی پیمائش کرنا،فصلوں کو کاشت کرنا پھر ان کو برداشت کرنا یہ سب کچھ ایک انسان کے ہاتھوں سرانجام پاتا ہے۔
صد رِمحترم!
یہ انسان یا تو کسی کا استاد ہوتا ہے اور یا پھر کسی کے سامنے زانوے تلمذ طے کیے ہوتا ہے۔ زندگی کے تمام شعبوں میں جو نمایاں ترقی نظر آرہی ہے یہ کسی نہ کسی شخصیت کی مرہونِ منت ہے اور وہ شخصیت یا تو معلمین کے اہم پیشے سے وابستہ ہوگی اور یا پھر کسی ماہرکی مہارت کا شاخسانہ ہوگی اور یہ عروج ان افراد ہی کی وجہ سے ہے اور یہ لوگ بنیادی طور پر طالب علم ہوتے ہیں۔
جناب صدر!
فرمانِ رسالت مآبؐ ہے کہ’’ گود سے گورتک علم حاصل کرو‘‘ یعنی تحصیل علم کے لیے کوئی عمر کی حد کاتعین نہیں کیا گیا ہے بلکہ فرما دیا گیا ہے کہ اگر کامیابی و کامرانی کے زینے طے کرنا چاہتے ہو تو ہمہ وقت حصولِ علم کی خاطر مستعد رہو، چلتے پھرتے، اٹھتے بیٹھتے، ہمیشہ یہ جدوجہد کرتے رہو کہ تمہارے علم میں اضافہ ہو۔
معزز سامعین!
آج اگر طالب علم اپنے علم کی بنیاد صحیح خطوط پر رکھے گا تو کل معاشرے کی ترقی میں اہم کردار ادا کرے گا معاشرے کا اہم رکن ثابت ہو گا۔ علمِ...

غلام رسول سعیدی ؒ کے ترجمہ قرآن کا چھ مختلف تراجم سے تقابل (ایک تحقیقی و تنقیدی جائزہ)

The Quran is the last book of Allah. The Quran was revealed in Arabic. The Qur'an was not revealed only to the Arabs. This book has been published to guide all Human beings. There for, translation of the Quran is necessary for non-Arabs. The translation of the Quran was started in the beginning of Urdu language. So far there have been many translations of the Holy Quran in Urdu . I have compared Allama Saeedi's translation of the Qur'an with other translations in this article. I have proved in this article that their translation is an extension of the Quran, the Barelvi school. Their translation is often matched by professional translation in many places. Barelvi School has original (genin), translation, Quran, Maulana Ahmad Raza Khan Barelvi and Allama Syed Mohammad Kachochvi. This work of mine is unique in its investigation  of Allama Ghulam Rasool Saeedi. In my opinion, resding the Qur’an is essential for the understanding of the Qur’an in order to understand the Qur’an but also the study of translations that have a distinct identity and they have been the study of our teachers.

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.