استنباطِ احکام میں ضعیف حدیث کا مقام اور فقہاء کی آراء کا تجزیاتی مطالعہ Analytical study of the Status of hadith e Da’eef in the interpretation of rulings and the opinions of the jurists

There are two main sources of Islam, one is the Book of Allah and the other is the Sunnah and Sira of the Prophet (peace be upon him). The Qur'an is the final collection of 23 years of divine revelation revealed to the Holy Prophet (PBUH) whose literal and spiritual preservation was undertaken by Allah Almighty Himself. Therefore, the Qur'an is the only book in the world which has one letter, one action and one line in its original state just as it was revealed to the pure heart of the Holy Prophet (sws) and the Holy Prophet (sws). The Prophet (peace and blessings of Allaah be upon him) told the Sahaabah. That is why the greatest truth of Islam, the book is the living Qur'an. The second major basis of the reality of Islam is the pure Sira and Sunnah of the Prophet of Humanity, the Servant of the Universe. Like the Qur'an al-Hakim, every moment, every day and every angle of the life of the author of the Qur'an is in front of everyone like an open book with all its mysteries. Even in front of one's own and in front of others. A da’if hadith is a hadith which does not fulfil the conditions of the sahih or hassan hadith. Ruling: There is a difference of opinion between the ‘ulema on the ruling on acting upon weak hadiths. The reliable opinion is that weak hadiths can be acted upon for virtuous supererogatory deeds (fada’il al a’mal), for religious exhortation, and stories, and similar things that are not connected to legal rulings and tenants of belief. Keywords: Hadith, Hadith e Da’eef, Derivation of Ahkaam, Jurists, Different opinions.

Efficient Music Fingerprinting for Music Speech Segregation

Since decade, a lot of music fingerprinting and speech segregation algorithms have exhaled. Music speech segregation includes music identification and followed by speech segregation. This becomes challenging in the presences of the noisy environment and noisy sample case. A rapid development has taken place in the field of multimedia content analysis. Music information retrieval applications increased the emphases on the development of music fingerprinting algorithms. Noise affects the efficiency and accuracy of the audio information retrieval algorithms. This research thesis presents a deep analysis of music fingerprinting and speech segregation algorithms. A novel algorithm is presented for music fingerprinting which is used for efficient speech segregation in which music fingerprinting is performed over a noisy audio sample. This research work proposes a system that performs music fingerprinting in-depth evolving the speech segregation processes in presence of background noise. Noise is removed from the audio signal using layered separation model of the recurrent neural network. Music fingerprinting is performed on the basis of pitch based acoustic features classified using distributed dictionary based features learning model. The classified music is processed for speech segregation after noise removal using layered separation model. Speech is segregated using vocal based acoustic features. Features are classified using improved dictionary based fisher algorithm. Structured based classes are used for the classification process. The systematic evaluation of the proposed system for music fingerprinting and speech segregation produces competitive results for three datasets (i.e. TIMIT, MIR-1K, and MusicBrainz), and the results indicate the strength of the proposed system. The proposed system produces significantly better results when the qualitative and quantitative analysis is carried out over the standard datasets showing the better efficiency of our proposed system from the past systems.