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73. Al-Muzzammil/The Enwrapped

73. Al-Muzzammil/The Enwrapped

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone.

73:01
a. O Al-Muzzammil!
b. O The Enwrapped - Muhammad!

73:02
a. Stay up in worshipful meditation through the late nighttime,
b. except for a little while,

73:03
a. - half of it,
b. or a little less than that, up to a third,

73:04
a. or even a little more, up to two-thirds.
b. And recite The Qur’an in a slow and distinct recitation.

73:05
a. Indeed, soon WE are going to entrust a heavy burden on you - awe-inspiring –
b. - The Qur’an.

73:06
a. Surely, the getting up by late nighttime for worshipful meditation is very demanding,
b. yet very rewarding for subduing one’s soul, and
c. making recitation more effective -

73:07
a. - for, indeed, during the daytime you have extended schedule of engagements.

73:08
a. But recite The Sacred Name of your Rabb - The Lord,
b. and devote yourself to HIM exclusively in wholesome devotion.

73:09
a. HE is Rabb - The Lord of the east and the west.
b. There is no worshipful entity except HIM.
c. So take HIM as your Guardian and Guarantor.

688 Surah 73 * Al-Muzzammil

73:10
a. And bear with patience over what they allege against you and your Divine Mission,
b. and keep a distance from them in a gracious manner.

73:11
a. And leave it to ME to deal with the beliers and deniers who have been given the good...

Peran Guru Dalam Membentuk Karakter Siswa Di SMA Swasta Katolik Bintang Laut

Saat ini dalam dunia pendidikan khususnya dalam bidang karakter yang dimiliki oleh siswa, seringkali siswa melalaikan karakter yang harusnya siswa tanamkan dalam dirinya. Dalam menyikapi hal tersebut maka peranan guru sangat penting didalamnya. Tujuan penelitian ini adalah untuk mengetahui peranan guru dalam membentuk karakter siswa di SMAS Katolik Bintang Laut, bagaimana profesionalisme guru dan budaya sekolah dapat berpengaruh dalam membentuk karakter siswa. Pendekatan yang dilakukan dalam penelitian ini adalah pendekatan kualitatif dengan jenis penelitian deskriptif. Sumber data dalam penelitian ini adalah guru di SMAS Katolik Bintang Laut, sampel 5 orang Guru sebagai responden dan 5 orang siswa sebagai informan. Teknik pengumpulan data yang dilakukan adalah melalui tahap observasi, wawancara dan dokumentasi. Analisis data yang dilakukan melalui tiga alur kegiatan (1) Reduksi data, (2) Penyajian data, (3) Penarikan kesimpulan. Hasil peneliti menunjukkan bahwa peranan guru sangat penting dalam membentuk karakter siswa di SMAS Katolik Bintang Laut, hampir semua guru profesional dalam melaksanakan tugasnya, memberikan contoh dan teladan yang baik, seperti datang tepat waktu, berpakaian rapi, bertanggungjawab atas apa yang sudah dipercayakan padanya, serta memberikan teguran dan sanksi bagi siswa yang melalaikan tanggung jawabnya, adapun budaya sekolah di SMAS Katolik Bintang Laut yaitu ada apel setiap pagi dengan bernyanyi dan berdoa bersama serta pembacaan renungan singkat, senam pagi setiap hari Jumat, dan misa awal bulan.

Gesture Recognition for Dynamic Signs for Urdu Language

Sign language is the language of gestures. It is also a way of communication for the deaf community. Sign languages use visual pattern rather than verbal communication. Sign Language Recognition (SLR) is an active research area in computer science. It has its roots in the domain of gesture recognition, robotics, gesture-based user authentication, lie detection communication, entertainment, security, art, industry, and sports. Every region has its own sign language. Pakistani Sign Language (PSL) for Urdu language is a visual-gestural language that is being used for communication by the deaf community. This research presents a robust, reliable, systematic and consistent system for both static and dynamic gestures. The present research focuses on different available solutions for gesture recognition and concludes that deep learning and convolutional neural networks give a most appropriate solution. The thesis is based on the comparison of different potential sign descriptors. Use of correlation and cross-correlation to identify gestures has led the researcher to the fact that supervised learning techniques have given a convincing performance for PSL or even any other sign language. The research has proposed 3 major ideas, it starts with proposing universal sign language and use of spelling-based gestures over word-based gestures. The research also proposes a video summarization technique for sign languages based on mean and entropy. Moreover, there is no standard dataset available for PSL, so dataset for a subset of static and dynamic signs of PSL is developed for the thesis. The research gives upto 90% accuracy when the recognition routine uses deep learning based model. The dataset is kept as small as 400 images/videos per class. The research has proven that the accuracy can be improved by increasing dataset size, image size, and number of epochs.
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