This paper presents a study on the Palm oil (PO) and Rice Bran oil (RBO) as alternatives to transformer oil. The nature of biodegradability, environmental friendly and easy availability makes these oils a suitable replacement for liquid insulation in transformer. Comparative studies of AC breakdown voltage between these two oils were investigated using two different electrode configurations with a gap distance of 2.5mm. This experimental works was done according to the IEC 60156. The statistical analysis was used to find the withstand voltage and evaluate breakdown probability for both oils. The results indicated that the breakdown voltages of PO and RBO are comparable to each other under different configurations. The Weibull distribution determined the withstand voltage at 1% for RBO are higher than PO even though the average of PO is slightly higher compared to RBO.

The implementation of non-intrusive load monitoring has gained significant attention as a promising solution for disaggregating and identifying individual appliances' energy consumption within households and commercial buildings. The issue at the core of non-intrusive load monitoring is the accurate separation of the aggregated energy consumption signal into the energy contributions of distinct appliances without requiring additional sensors or invasive measurements. The erroneous implementation of non-intrusive load monitoring model leads to poor results and a waste of time where the criteria for the implementation are necessary. This paper presents an overview of non-intrusive load monitoring's implementation, addressing the stages of non-intrusive load monitoring and advancements in the field. The overview explores the various techniques, methodologies, and algorithms employed in non-intrusive load monitoring systems to achieve load identification and energy disaggregation. By addressing the problem statement and reviewing the state of the art, this paper sets the stage for understanding the significance of non-intrusive load monitoring in commercial buildings and modern energy-efficient households. Moreover, the limitations, applications, and recommended criteria for the implementation of non-intrusive load monitoring are highlighted as a contribution to the field of load disaggregation. Future research should address scalability, privacy concerns, and the integration of NILM with smart grids to propel energy disaggregation towards more efficient, accessible, and sustainable energy management systems. We envision that this endeavour can serve as a guiding beacon, offering a roadmap for researchers and professionals.

Al Quran is a divine text which represents the purest and most authentic form of the classical Arabic language. To understand the meaning of each verse, a deep knowledge of Arabic linguistic is essential. Therefore, our scholars have made their efforts by engaging themselves in the works of explaining al Quran's words, interpreting its meanings into Arabic and other languages. Currently, more people are interested in knowing the content of al-Quran, especially for non-Muslim, after 9/11 tragedy. Thus, a flexible model that can represent Qur'anic concept is required for people to understand the content of the Quran. In this research, we propose a Multi-Relational Latent Morphology-Semantic Analysis Model (MORPHOSEM) based on a combination of Arabic Semantic and six multiple relations between words, which are synonym, antonym, hypernym, hyponym, homonym and meronym, to precisely extract Qur'anic concept. The existing literatures focus only on very limited relationships between words which could not extract the in-depth concept of Qur'anic without considering the importance Arabic Semantic. Therefore, the objectives of this research are: (1) to analyses and categorize Quranic words according to Arabic Semantic patterns, (2) to propose a new model for extracting Quranic concept using MORPHOSEM, (3) to investigate semantic relationships between Qur'anic words, and (4) to validate the proposed model with Arabic linguistic, and Qur'anic experts. This research will be conducted qualitatively through content analysis approach a new innovative technological technique. It is expected that the model will come out with a precise analysis for extracting Qur'anic concept. This will be very significant in enhancing the overall Quran's understanding among the society in Malaysia and Muslim's world for sustainable society.