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پنڈت کشن پرشاد کول

پنڈت کشن پرشاد کول
پنڈت کشن پرشاد کول کی وفات ایک بڑا ادبی اور تہذیبی سانحہ ہے، وہ اردو کے ممتاز ادیب اس کے شیدائی اور ہماری پرانی تہذیب و شرافت کی ایک اہم یادگار تھے، ان میں خدمت کا جذبہ ابتداء سے تھا، چنانچہ آج سے تقریباً نصف صدی پیشتر اس زمانہ میں جب کہ ہر تعلیم یافتہ نوجوان سرکاری عہدوں کی جانب لپکتا تھا، انھوں نے دنیاوی دولت و وجاہت کے مقابلہ میں ملک و قوم کی خدمت کو ترجیح دی اور سرونٹ آف انڈیا سوسائٹی کے ممبر ہوگئے، جو اس زمانہ میں سادگی اور قناعت کے ساتھ قومی خدمت کی تربیت گاہ تھی، اور ساری عمر ایک وضع میں گزار دی، وہ لکھنؤ کے پرانے کانگریسی لیڈر بابو گنگا پرشاد ورما کے سیاسی شاگرد اور ان کے شریک کار تھے، ان کے بعد ان کے اخبار ’’ہندوستانی‘‘ کو سنبھالا اور کئی سال تک اس کو چلاتے رہے اس کے بعد پنڈت چکبست کے ساتھ مشہور رسالہ ’’صبح امید‘‘ نکالا، گنگا پرشاد میموریل لائبریری قائم ہونے کے بعد اس کے آنریری سکریٹری ہوگئے اور آخر عمر تک اس خدمت کو انجام دیتے رہے۔
وہ طبعاً سیاسی آدمی نہ تھے، ان کا اصلی ذوق علمی و ادبی تھا، اس لیے ہنگامہ خیز سیاست سے دور رہے اور پوری زندگی علم و ادب کی خدمت میں بسر کی، اردو تہذیب اور اردو زبان سے ان کو عشق تھا، اس فرقہ پرستی کے دور میں جبکہ بڑے بڑے اردو نوازوں کے قدم ڈگمگائے گئے، انہوں نے جس جرأت کے ساتھ اردو کی حمایت، اس کا حق منوانے کے لئے علمی جدوجہد اور اردو علاقائی زبان کی تحریک کی رہنمائی کی وہ ان ہی کا حصہ ہے اردو میں ان کے متعدد ناول، افسانے، خطبۂ صدارت اور ادبی و تنقیدی مضامین وغیرہ ان کی یادگار اور ان کی ادبی...

مشکل الحدیث کے حل میں ملا علی قاری ؒ کا منہج۔ایک تجزیاتی مطالعہ

The Problematic narration has always been under the special focus of the commentators of Hadith. This important branch of Hadith sciences, in fact, removes all objections that arise on the text of an authentic narration of the Holy Prophet (S.A.W). Mulla Ali Al-qari, being a famous commentator has opted for a comprehensive pattern in solving such problematic narrations in his famous commentar0y on Mishqat Al-masabih named Mirqat Al-mafatih. This article is an effort to explore his style by presenting ten examples from this voluminous commentary. Qari has at first, investigated the authenticity of such narration. He has tried to present the views and interpretations of his predecessor scholars such as Nawavi, Ibne-Hajar, Khattabi, etc. He seems to owe a clear viewpoint about this kind of narration that prophetic sayings after being confirmed and authentic as per principles set in Hadith Sciences, must be interpreted in a way that testifies the sanctity of that narration. This research concludes that problematic narrations have been interpreted by Muslim scholars of every age according to the knowledge they possessed. In this modern age of Science and technology, if any such narration has multi interpretations only one may be preferred which is supported by the available modern research It will surely make non-believers inclined to Islam and its eternal teachings.

Customer Churn Prediction in Telecommunication Using Computational Intelligence

Telecommunication industry has grown rapidly during the last decade. The number of cellular subscribers is approaching about 96% of total population of the world. In such a fierce competition, telecom service providers are facing saturated markets with little room for penetration. Therefore, telecom companies are focusing more on customer retention, which is considered cost effective as compared to adding new customers. Moreover, customer retention is more economical as it does not involve any additional marketing expense. Long term customers are also considered as easier to serve, contribute more toward stable profitability, and introduce new referrals as well. On the other hand, new customers are hard to be attracted in competitive markets and take little longer for establishing loyalties with the new service providers. Therefore, telecom industry requires a reliable churn prediction system, which accurately identifies the customers who are about to switch over to another service provider. The role of customer churn prediction system has become pivotal in retaining customers expected to churn by luring them with the improved service packages. This preceding knowledge of customers‟ churning would enable service providers to avoid sizeable revenue losses. Consequently for churn prediction, researchers have investigated many interesting data mining techniques that can meet the specific demands of telecom industry. However, the telecom churn prediction is still a challenging tak because of the the big size, imbalanced class distribution, and high dimensionality of telecom datasets. The main focus of this thesis is to identify discriminative feature extraction techniques and effective sampling methods to cater for the enormous nature of telecom datasets. Additionally, investigations are made to develop a churn prediction system with better classification and interpreting capabilities. This thesis makes the following contributions in the area of telecom churn prediction: 1) Analysis of minimum redundancy and maximum relevance (mRMR) method for extracting relevant and meaningful features, 2) Exploiting Genetic Algorithm based wrapper method to remove any redundant features from selected features, 3) Analysis of PSO xvi based intelligent sampling technique and its comparison to conventional undersampling techniques, 4) Constructing efficient churn prediction systems using computational intelligence based ensemble classification approaches (CP-MRF, Chr-mRF FEW-ChrP), 5) Employing novel GP-AdaBoost based ensemble classifier to develop an efficient churn prediction system with the additional capability of identifying factors responsible for churning, 6) Attaining highest churn prediction performance of 0.862 AUC and 0.910 AUC on Orange and Cell2Cell telecom datasets, respectively. 7) Extracting 47 useful features from 260 original features of Orange dataset and 35 features from 76 original features of Cell2Cell dataset. In short, under this research work extensive simulations are performed to examine the prediction performance of the proposed churn prediction systems distinguishing churners from non-churners.
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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