صوفیہ خام اور علمائے سوء کا علمی محاسبہ کشف المحجوب کی روشنی میں

This paper is an attempt to elaborate and highlight the attributes and qualities of leading specialists and reformative factors of Islamic society blessed with moral par-excellence known asṢūfiyā and‘Ulamā’. As unfortunately, with an exception of few, these responsible characters have gone astray following ill commanding self like a wolf in sheep’s dress hiding their harmful aspects with friendly appearance. These so-called knowledge spreading elements and spiritual mentors are also accountable to disparage the values and thought associated with Islamic system of learning and self-purification. So, it is necessary to remove the curtain in order to visit the real picture of Taṣawwaf. For this purpose, a book ‘Kashf al-Maḥjūb’ of great Sufi scholar Syed Alī bin ‘Uthmān al Hujvairī (R.A)has been selected to examine analytically how he discussed the situation in the light of Qur’ān and Sunnah elaborating the misconduct and bad behavior of under discussed. One who disguised himself instead of having conflict between his internality (self) to that of externality. The habits and attitude of imperfect Ṣūfiyā and the misleading ‘Ulamā’ and their injurious impact on society have been discussed by Alī Hujvairī (R.A) in his comprehensive treatise. The author also setout a strategy to know how to get rid of these so-called Ṣūfiyā and‘Ulamā’ and suggested various outlines and framework for recuperation in order to save the humanity from their lethal side effects.

Performance Enhancement in Cognitive Radio Sensor Networks

Wireless sensor networks (WSNs) have become the integral part of our daily life activities. These WSNs can utilize the unlicensed industrial, scientific and medical (ISM) band to communicate the sensed data. The ISM band has been already saturated due to overlaid deployment of WSNs and other wireless technologies such as WiFi etc. To solve this problem, WSNs have been powered up by cognitive radio (CR) capability and this rise to a new type of network called as cognitive radio sensor networks (CRSNs). In CRSNs, the unlicensed users can utilize the unlicensed as well as licensed band opportunistically. The licensed users are called the primary radio (PR) nodes where as the opportunistic unlicensed users are called as secondary or CRSN nodes. By using CR technique, CRSN nodes can utilize the spectrum holes opportunistically avoiding the interference with PR nodes. CRSNs can be deployed for number of purposes such as dynamic spectrum access to cognitive radio nodes, opportunistic channel access, overlaid deployments of multiple concurrent networks, and communication under different spectrum regulations. The potential applications of CRSNs include indoor sensing applications, multimedia applications, multi-class heterogeneous sensing applications, and real-time surveillance applications etc. All these applications require high bandwidth for communication along with avoiding CR-PR interference. In this regard, novel techniques are required which can provide large bandwidth to CRSN nodes to support their data requirements. Channel bonding (CB) is a technique to provide wide band channel by combining multiple contiguous channels. By using channel bonding (CB) technique, CRSN nodes attempt to find and combine contiguous channels to avail larger bandwidth. In this PhD thesis, we have made several contributions. Firstly, we have provided an extensive literature review of CB schemes, made meaningful classification of CB approaches and highlighted the applications of CB in various networks. Next, we have enhanced network simulator NS-2 and proposed a framework for simulating CRSNs in NS-2. Third, we have proposed an algorithm Primary Radio Activity aware Channel Bonding algorithm (PRACB) to perform channel bonding in CRSNs. We have implemented our proposed scheme PRACB in NS-2 and compared it with three schemes sample width algorithm (SWA), cognitive radio networks over white spaces (KNOWS) and AGILE. We then evaluated the performance of PRACB in different PR activity regimes. The simulation results show that our algorithm significantly avoids CR-PR harmful interference and CB in cognitive radio sensor networks (CRSNs) provides greater bandwidth to CRSN nodes. Next, we have proposed two remaining idle time aware channel bonding schemes RITCB and RITCB-IP, which select channels for CRSN nodes based on remaining idle time. In the end, we have performed comparison analysis of our schemes and shown that intelligent channel selection effectively improves the delivery ratio of CRSN nodes. In addition, some future research directions have also been highlighted at the end of this thesis.