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Language Variation Across Pakistani Textbooks in English

Thesis Info

Author

Muhammad Ijaz

Supervisor

Muhammad Ijaz

Program

Mphil

Institute

Riphah International University

Institute Type

Private

Campus Location

Faisalabad Campus

City

Faisalabad

Province

Punjab

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Page

87 . : ill. ; 29 cm.

Subject

Linguistics

Language

English

Other

Thesis (Phil English Linguistic)--Riphah International University, 2019; English; Call No: 415 IJA

Added

2021-02-17 19:49:13

Modified

2023-02-19 12:33:56

ARI ID

1676712006744

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محمد امین مسعود صدیقی

محمد امین مسعود صدیقی
(ریاض الرحمن شروانی)
حبیب منزل، میرس روڈ، علی گڑھ،
۲۰۰۱-۳-۲۷ء۔
مکرمی و محترمی! السلام علیکم ورحمۃ اﷲ،
لکھنؤ سے کل ۲۵؍ مارچ کا ’’جدید مرکز‘‘ آیا تو اس میں محمد امین مسعود صدیقی صاحب کی اچانک وفات کی خبر پڑھ کر دلی صدمہ ہوا، اخبار میں اس خبر کی سرخی ’’مولانا آزادؒ کے عاشق تھے مسعود صدیقی‘‘ چھپی ہے اور اس سے بہتر سرخی کوئی اور نہیں ہوسکتی تھی۔ کیا عجیب عشق تھا کہ چاہتے تھے ہر فرد، ہر اخبار اور رسالہ اور ہر ادارہ اس عشق میں ان کا شریک ہوجائے۔ ہر ممکن طریقے سے مولانا آزادؒ کے پیغام کی اشاعت کے لئے سرگرداں رہتے تھے۔
ان میں اور بھی بہت سی خوبیاں تھیں، بہت دین دار، مخلص، متحرک اور بے نفس انسان تھے، میرا بہت لحاظ کرتے تھے۔ میں کسی معاملے میں ان سے اختلاف کرتا تھا تو خاموش ہوجاتے تھے، کبھی بحث نہیں کرتے تھے۔ مولانا آزادؒ پر کہیں کوئی چیز ان کی نظر سے گزرتی تھی تو اس کی فوٹو کاپی مجھے بھیج دیتے تھے۔ میں لکھنؤ جاتا تو انہیں مطلع کردیتا اور میرا جہاں کہیں قیام ہوتا وہ وہاں آکر مجھ سے ضرور ملتے تھے۔ مجھے ان کا آخری خط جو ۲۵؍ فروری کا لکھا ہوا تھا، ۲۸؍ کو ملا تھا۔ اس میں انہوں نے لکھا تھا: ’’معارف کا فروری ۲۰۰۱؁ء کا شمارہ آپ کو مل گیا ہوگا۔ اس میں اس ناچیز کا ایک مراسلہ شائع ہوا ہے۔ اس مراسلے پر حواشی میں جو باتیں تحریر فرمائی گئی ہیں۔ اس (کذا) سے نفس کی اصلاح کا موقع ملا ہے‘‘۔ ملاحظہ فرمایا آپ نے کس طرح اپنی کوتاہی کا اعتراف کیا ہے۔ میں نے کچھ غلط تو نہیں لکھا کہ کیسے بے نفس انسان تھے۔ اﷲ تعالیٰ مغفرت فرمائے اور درجات بلند کرے۔ بہت جلدی چلے گئے۔
امید ہے...

اسلامی تعلیمات کی روشنی میں مروجہ پاکستانی ٹریفک قوانین کی پاسداری کی اہمیت

Islam is a comprehensive code of conduct which encompasses to each sphere of human life. This also owns and endorses those manmade rules which serve the cause of humanity and not entering to its fundamentals. Adherence to Pakistani Traffic rules also falls under the preview of the same doctrine. It is very pertinent to note here, that the same traffic rules such as fastening of seat built, proper use of indicators, speed control etc. Have been devised to ensure the safety which starts from a pedestrian and ends up to a rider of any vehicle class. Any violation of traffic rules is an indirect breech of divine discipline imposed by Allah the Almighty. If the violation costs any damage, injury or fatal accident, this will directly be dealt under the principles set by Islam. This study aims at highlighting the significance of adherence to traffic rules which is directly linked to the ground safety. This ultimately serves the main purpose of saving any precious human life. If the same is ensured, no doubt the purpose of the holy verse would be fulfilled

A Framework for Mining Emerging Trends in Web Clickstreams With Particle Swarm Optimization

The expansion of World Wide Web (WWW) in its size and exponential growth of its users has made the web most powerful and dynamic medium for information dissemination, storage, and retrieval. Moreover, the improvements in data storage technology have also made it possible to capture the huge amount of the user interactions (clickstreams) with the websites. The availability of such a huge amount of web user clickstreams has opened the new challenges for researchers to explore the weblog for the identification of hidden knowledge. For the last decade, web usage mining is playing a crucial role in the identification of trends from user clickstreams such as web personalization; user profiling; and user behavior analysis. These trends are beneficial in many ways such as information retrieval, website administration and improvement; customer relationship management; e-marketing; and recommender systems. The plenty of techniques are available in the literature, however, the accuracy, correctness and validity of the generated trends is totally relying on the proper selection of web mining process such as web sessionization, which is the benchmark for the later web usage mining stages. For the promising and optimized results, weblog sessionization is the eventual choice. Moreover, the extraction of proper, accurate and noise free sessionization is a demanding and challenging job in the presence of huge web clickstreams. The sessionization problem may fail to identify the focused and visualized groups from clickstreams records with high coverage and precision. Even though the well-known web session similarity measures such as Euclidean, Cosine, and Jaccard are prevalent in literature for mining process at the early learning stages. The web sessionization must take account of the validity of generated trends, which entirely depends upon the correctness and credibility of web sessions. To overcome the limitations of existing web sessionization techniques, we propose a Framework for Mining Trends (F MET) that empowers us to gauge the user activities on the website through evolutionary hierarchical Sessionization. Hierarchical Sessionization enhances the visualization of user click data to improve the business logic and mines the focused groups for scalable tracking of user activities. The foundation of the proposed framework is the swarm based optimized clustering technique along with a proposed web session similarity measure ST Index to address the Hierarchical Sessionization problem. The proposed web session similarity measure ST Index for hierarchical sessionization overcomes the limitations of Euclidean, Cosine and Jaccard measures, which may have failed to explicitly seek the proper and accurate trends. The Euclidean measures are of numerical in nature while the weblog data is of mixed nature. Moreover, existing measures are best for independent and isolated clustering groups. The proposed similarity measure ST Index computes the similarity among the user sessions through the common features (pages) shared among the sessions while assigning weight to uncommon features among the given sessions along with the minimum time shared by the given sessions time ratio. We validated and verify the proposed framework on three different datasets. The proposed ST Index measure produced the accurate and valid relationship among the sessions against common web session similarity measures. Furthermore, framework also produced the correct, accurate and valid trends. The performance of the proposed framework is validated against the well-known data analysis metrics such as VC (visitor coherence), accuracy, coverage and F1 Measures. The results show the significance improvements over the existing techniques of hierarchical Sessionization