56. Al-Waqi’ah/The Event
I/We begin by the Blessed Name of Allah
The Immensely Merciful to all, The Infinitely Compassionate to everyone.
56:01
a. When the Inevitable Event of Doom will descend, and herald the Resurrection,
56:02
a. then there will be no belying and denying of its descent;
56:03
a. it will be degrading and humbling some humans and jinn, and exalting some others.
56:04
a. When the whole of the terrestrial world will be shaken, shaken violently in a series of massive earthquakes and volcanic eruptions,
56:05
a. and the mountains will be made to crumble, utterly crumbling,
56:06
a. so as turning it to dust, scattered in the air like puffed wool.
56:07
a. And you all will be sorted out into the following three diverse categories:
56:08
a. As for the first category:
b. the People of the right hand side – the lucky and blessed ones;
c. how lucky and blessed will be the People of the right hand side!
56:09
a. And the second category:
b. the People of the left hand side – the unlucky and wretched ones;
c. how unlucky and wretched will be the People of the left hand side!
56:10
a. And the third category:
b. those in the foremost who would have taken the lead
c. – indeed they will be the foremost in their race to seek Allah’s Countenance!
56:11
a. For those will be the ones brought near,
56:12
a. in Gardens of Perpetual Bliss - abounding in peace, tranquility, and blessings.
Qazi Ayaz Malki is a famous scholar of the west. He has written books on various sciences and arts. His famous book is Al-Shafa'ah betareef e Huqooq El Mustafa. This book has given him eternal life because of this book he has reached the highest of fame even today. The rights and particularities of the Prophet (SAW) are mentioned in this book. The topic under consideration is an introduction to Qazi Ayaz Malki's life situation and his book Al-Shafa'ah Al-Shareef Huqooq Al Mustafa. And this book talks about the objections which are been raised and their detailed answers
The breast cancer in the women is most commonly diagnosed type of cancer. The mortality rate
can be reduced if proper and early breast cancer treatment can be made. Masses and
microcalcification contain very important diagnostic information in breast cancer. There is great
variation in masses and micro-calcifications so, radiologists face difficulties in proper diagnosis
of the breast cancer. Researchers in the past developed efficient systems based on computer
aided diagnostic (CAD) systems. Moreover, relevant feature extraction plays a vital role in
proper diagnostic and prognostic. Based on the diverse nature and variations in the breast cancer
mammograms, we propose hybrid feature extraction approach including morphological, entropybased
features,
elliptic
Fourier
descriptors
(EFDs),
texture
and
scale
invariant
feature
transform
(SIFT).
For improving the detection accuracy based on the extracted features, we applied
machine learning classifiers including Support vector machine (SVM) alongwith its kernels such
as Gaussian, radial base function (RBF), polynomial; Na?ve Bayes and Decision tree (DT). The
validation was measured using 10-fold cross validation (CV) system. For a performance
evaluation, we computed different metrics including specificity, sensitivity, false positive rate
(FPR), negative predictive value (NPV), positive predictive value (PPV), and area under the
receiver operating curve (AUC). Both combination and single feature are used as an input for
classifiers. The results reveal that both single and combination of features provides higher
detection results. Thus, the new feature extracting approach is more robust in early detection of
breast cancer.