27. Al-Naml/The Ant
I/We begin by the Blessed Name of Allah
The Immensely Merciful to all, The Infinitely Compassionate to everyone.
27:01
a. Ta. Sin.
b. These are the Messages of The Divine Qur’an, and, a Clear Book.
27:02
a. It is a Guidance, and,
b. a source of good news for the believers.
27:03
a. The believers are those who:
- establish the Salat/Prayers, and
- pay out the Zakat/annual charity, and
- it is they who believe with certainty in the realm of the Hereafter.
27:04
a. Surely, as for those who do not believe in the realm of the Hereafter,
b. WE have made their evil deeds appear enticing to them,
c. so that they wander confused in their worldly lives.
27:05
a. It is they for whom is going to be an awful punishment,
b. and it is they who are going to be the worst losers in the realm of the Hereafter.
27:06
a. And, for sure, you - O The Prophet – are receiving the Qur’an from the One WHO is
All-Wise, All-Knowing.
27:07
a. And visualize the time when Moses said to his family:
b. ‘I believe - I perceive a fire on the mountain.
c. You wait here I will go and bring you some information from there, or at least a firebrand
- so you may warm up yourselves.’
27:08
a. So when he came close to it, a Voice called out:
b. ‘Blessed be WHOEVER is within the Fire, and whoever is around it!
c. And Exalted be Allah - Rabb - The Lord...
Hazrat Maulana Syed Zawwar Hussain Shah is the knowledgeable and spiritual personality of the fourteenth century Hijra. There are diverse aspects of his qualities and perfections. A matchless diversity can easily be found in his services related to his scholarly work and reformation of Muslim Ummah. Not only a Translator, Biographer or Poet but he, at the same time, was also an expert of Islamic Jurisprudence and held the position of a Sheikh of Islamic Sufi order of Naqshbandi Mujaddiah. Shah Sahib authored and compiled 13 books. The study of translated works ( Mabda wa Ma’ad, Muarif-e-Ludniya, Maktoobat-e-Masoomia, Maktoobat Imam Rabbani) of Shah Sahib's and discussion on its importance is the prime focus of this article.
The rapid proliferation of wireless networks poses a great challenge to effective coexistence management amongst a plethora of wireless communication protocol users that are co-located and contending for the ever-scarce spectrum available. In particular, low-powered ad-hoc networks such as WSNs which are an integral part of the Internet of Things (IoT) and Industrial Internet of Things (IIoT) landscape, will be highly susceptible to cross-technology interference. This jeopardizes the envisaged performance and reliability of IoT and IIoT applications comprising many safety and mission-critical applications. For effective spectrum utilization and optimum performance of existing wireless networks and the realization of new wireless networks, coexistence management of the wireless spectrum is the key to ensuring the optimal performance of multiple wireless networks operating in close proximity.
We propose a two-step approach to attaining coexistence starting with wireless interference identification as spectrum awareness would be of keen importance in identifying concurrent transmission and subsequently applying suitable interference mitigation techniques to ensure coexistence and prevent communication blackout.
Our work uses deep learning to identify the presence of WSN, WiFi and Bluetooth single-label signals. Furthermore, we aim to identify multi-label concurrent signal transmissions that are significant in the context of interference management.
Moreover, a wireless coexistence management framework for WSNs is proposed which is an interference-aware and coexistence-friendly modification inspired by the WSN LEACH architecture that uses the proposed wireless interference identification for detection of the type of interference and the affected nodes. Depending upon the interference type, the coexistence framework assigns specific countermeasures that best counter the interference with good throughput and optimal energy consumption. In this work, we have proposed a coping mechanism against WiFi interference using an adaptive backoff time period and an in-depth study of the node interference levels