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63. Al-Munafiqun/The Hypocrites

63. Al-Munafiqun/The Hypocrites

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone

63:01
a. When the hypocrites - disbelievers showing belief - come to you, O The Prophet, they
pretend to say:
b. ‘We bear witness that you are certainly Allah’s Messenger.’
c. And without the need for the testimony of the hypocrites, Allah knows very well that you are indeed HIS Messenger,
d. but Allah also bears witness that the hypocrites are definitely liars – saying what they do not mean.

63:02
a. They choose their swearing as a cover-up, a deceit;
b. while in reality, they obstruct people from the Way of Allah.
c. Surely they - evil indeed is what they do.

63:03
a. That is what has happened because first they believed and then inwardly they disbelieved.
b. Hence, their hearts have been sealed -
c. such that they do not comprehend the concept of truth.

63:04
a. And whenever you would look at them, you would be impressed by their physical stature,
b. and when they speak, you would listen to their speech attentively.
c. But, in fact, they are just like logs of timber/wood, stacked-up against a wall.
d. They reckon that every rebuke they hear is directed against them.
e. These are the real and bitter enemies;
f. so beware of them!
g. May Allah destroy them!
h. How deluded they are!

63:05
a. And whenever they would be asked:
b. ‘Come to offer apologies and let Allah’s Messenger seek forgiveness for you’ of hypocrisy and deceit.
c. They would twist their heads in arrogance,
d. and you would see...

مشکوٰۃ المصابیح پر شیخ عبدالحق محدث دہلوی کے کام کا جائزہ

"Mishkāt al-Maṣābīḥ" has a sound rank among the Hadith collections. Its importance can be gauged from the fact that it has been described and summarized by several scholars. The works of Sheikh Abdul Haq Muḥaddith Dehlavi over that is a great contribution and have a special place in the context of his Hadith services. He is one of the prominent muhaddithin of the Subcontinent. He was pioneer in teaching and disseminating Hadith knowledge in the subcontinent. Firstly, he described the Mishkāt al-Maṣābīḥ in the Persian language of that time, which gained immense popularity among the people and increased the taste for understanding Hadith. Secondly, He accumulated a treasure trove of mysteries and secrets in Arabic for the use of Researchers. The name of the Persian commentary is Ash‘atul Lam‘āt while the Arabic commentary is called Lam‘āt al-Tanqīh. They are more than one in usefulness, which has created a taste for reading and understanding Hadith among the people and Researchers. In the said article, an introduction and methodological study of the work done by Sheikh Abdul Haq on Mishkāt al-Maṣābīḥ will be presented.

A Framework to Improve Classification of Positive and Negative Opinions in Roman Urdu-English Code Switching Environment

In computational linguistics, sentiment analysis facilitates classification of opinion as a positive or a negative class.In last decade, the area of sentiment analysis of English language is explored largely with different techniques those have improved the overall performance.Urdu is language of sixty-six million people and largely spoken in south-asian subcontinent. Also, it is national language of Pakistan which is world sixth most populous country according to United Nations Population Division. Sentiment analysis of Urdu language is important tool to understand the behavioural aspects, cultural values and social habits of the people living in this part of world. Opinion mining is also crucial for governments, policy makers, business owners and brand ambassadors to make their decisions in accordance to sentiment of the public.However, sentiment analysis of Urdu language is not well explored as that of English language. The Urdu sentiment analysis is performed with simple Bag-of-Word (BoW) method and machine learning (ML) techniques with limited set of features. The BoW method is not sufficient to handle complex opinions. Also, the accuracy of ML techniques, with legacy features, is not comparable to the sentiment classification task of other languages. For English language, the discourse information (sub-sentence level information) boosted the performance of both BoW method and ML techniques. A theory for Urdu sentiment analysis that extract and use the discourse information at sub sentence level and also suggest a computational model to achieve more accurate and better results than the simple bag of word approach. The proposed solution segmented the sentiment into two sub-opinions, extracted discourse information (discourse relation and polarity relation), proposed an extended BoW method (rule based method) and suggested a new small subset of features for ML techniques. The results significantly enhance (p < 0.001) the performance of recall, precision and accuracy by 37.25%, 8.46%, and 24.75% respectively. The current research targeted sentiment with two sub-opinions that remain excellent until the opinions are short messages like those on Twitter, in forum comments or as Facebook status posts. The proposed technique can be extended for sentiments with more than two sub-opinions such as blogs, reviews, and TV talk shows.
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