Analysis of Formant Frequencies of the Correct Pronunciation of Quranic Alphabets Between Kids and Adults

It is an obligation for a Muslim to become skilled and proficient in reciting Al-Quran considering that Al-Quran is the fundamental source of revelation from Allah SWT. In Al-Quran, there are 28 alphabets where each of them has their own unique sound. The Quranic alphabets produce sound that are characterized from their point of articulation (Makhraj) and their characteristics (Sifaat). Knowing the correct way of pronunciation through engineering perspective may help Muslim in learning Al-Quran, in the sense that the signal of the experts can be used in Quranic teaching and learning as a reference model. Since both adults and children possess different vocal tract, therefore there will be different outcomes of the pronunciation between both experts. The features identification of the pronunciation of both experts is needed to represent the actual and correct pronunciation that will be used as a reference for Quranic teaching and learning at later. In this paper, the focus was on the identification and analysis of the correct pronunciation of the Quranic alphabets on the data obtained from adults and children experts. The first and second formant frequencies (F1 and F2) were used as the features where they were used to represent the pronunciation of each alphabet for both adults and children category. The speech analysis software PRAAT was used to accomplish the pre-processing of the data using Spectral Subtraction technique and also used to measure the F1 and F2 values. Linear Discriminant Analysis (LDA) was used for classification of the signals and results shows that some of the alphabets can be identified uniquely using F1 and F2 features of the two categories

Specific detection of fungal pathogens by 18S rRNA gene PCR in microbial keratitis

<p>Abstract</p> <p>Background</p> <p>The sensitivity and specificity of 18S rRNA polymerase chain reaction (PCR) in the detection of fungal aetiology of microbial keratitis was determined in thirty patients with clinical diagnosis of microbial keratitis.</p> <p>Methods</p> <p>Corneal scrapings from patients were used for Gram stain, culture and PCR analysis. PCR was performed with primer pairs targeted to the 18S rRNA gene. The result of the PCR was compared with conventional culture and Gram staining method. The PCR positive samples were identified by DNA sequencing of the internal transcribed spacer (ITS) region of the rRNA gene. Main outcome measures were sensitivity and specificity of PCR in the detection of fungus in corneal keratitis.</p> <p>Results</p> <p>Combination of microscopy and culture gave a positive result in 11 of 30 samples of microbial keratitis. PCR detected 10 of 11 samples that were positive by conventional method. One of the 19 samples that was negative by conventional method was positive by PCR. Statistical analysis revealed that the PCR to have a sensitivity of 90.9% and specificity of 94.7% in the detection of a fungal aetiology in microbial keratitis.</p> <p>Conclusion</p> <p>PCR is a rapid, sensitive and useful method to detect fungal aetiology in microbial keratitis.</p

LIPS TRACKING IDENTIFICATION OF A CORRECT QURANIC LETTERS PRONUNCIATION FOR TAJWEED TEACHING AND LEARNING

Mastering the recitation of the holy Quran is an obligation among Muslims. It is an important task to fulfill other Ibadat like prayer, pilgrimage and zikr. However, the traditional way of teaching Quran recitation is a hard task due to the extensive training time and effort required from both teacher and learner. In fact, learning the correct pronunciation of the Quranic letters is the first step in mastering Tajweed (Rules and Guidance) in Quranic recitation. The pronunciation of Arabic letters is based on its points of articulation and the characteristics of a particular letter. In this paper we implement the lip identification technique from video signal acquired from expert to extract the movement data of the lips while pronouncing the correct Quranic letters. The extracted lip movement data from expert helps in categorizing the letters into 5 groups and in deciding the final shape of the lips. Later the technique was then tested among a public reciter and then compared for similarity verification between the public and the professional reciter. The system is able to extract the lips movement of the random user and draw the displacement graph and compared with the pronunciation of the expert. The error will be shown if the user has mistakenly pronounced the letter and suggested for improvement. More subjects with different background will be tested in very near future with feedback instructions. Machine learning techniques will be implemented at later stage for the real time application for learning process

Infaq in Times of Pandemic: the New Norm of Islamic Eschatology

This study reveals the currents social welfare which includes the uprising practice of Islamic charity, namely Infaq (voluntary alms giving), an instrument to help the unfortunate people (asnaf). It used qualitative approach involving semi-structured interviews focusing on six themes with six respondents. They engage in Infaq during the MCO or Movement Control Order. The results showed that there was a rise of contemporary fame of Infaq among Malaysian middle-class Muslims and charity body or organisation that specialise in sedekah/Infaq programmes . These parties make use of the platform of social media to record their activities and raise funds activity to help the needy who demand immediate and non-bureaucratic donations especially in a form of material help like food and daily necessities. This indeed has changed the course of how sedekah or Infaq used to be done back then. More Muslims who perform these Islamic charities display their efficiency and transparency in their donations as in Islam, sedekah is as a spiritual ‘investment' to the donors despite the hard time people face during pandemic.&nbsp