Search Results (4)

Effective vessel design is crucial for the viability and practicality of microalgae cultivation, aiming for high biomass production. This study tested two different 5-litre vessel designs for cultivating Chlorella vulgaris, aiming to produce a high biomass and evaluate lipid production. The study varied pH medium (6.5–10.5), light intensity (200–1000 lux), and CO₂ concentrations (5–15%) to assess each reactor’s performance. The aerated vessel (tubular shape) produced 21.05% lipid concentration, while the fabricated vessel (oval shape) produced 20.14% at optimum conditions. The aerated vessel performed best at pH 10.5, 5% CO₂, and 1000 lux light intensity, whereas the fabricated vessel’s optimum conditions were pH 10.5, 15% CO₂, and a white LED system. The highest biomass was 0.432 g/L in aerated tubular vessels and 0.281 g/L in fabricated oval-shaped vessels. Both systems performed well and are suitable for further study with other microalgae types. Full article

Choosing the best attribute from a dataset is a crucial step in effective logic mining since it has the greatest impact on improving the performance of the induced logic. This can be achieved by removing any irrelevant attributes that could become a logical rule. Numerous strategies are available in the literature to address this issue. However, these approaches only consider low-order logical rules, which limit the logical connection in the clause. Even though some methods produce excellent performance metrics, incorporating optimal higher-order logical rules into logic mining is challenging due to the large number of attributes involved. Furthermore, suboptimal logical rules are trained on an ineffective discrete Hopfield neural network, which leads to suboptimal induced logic. In this paper, we propose higher-order logic mining incorporating a log-linear analysis during the pre-processing phase, the multi-unit 3-satisfiability-based reverse analysis with a log-linear approach. The proposed logic mining also integrates a multi-unit discrete Hopfield neural network to ensure that each 3-satisfiability logic is learned separately. In this context, our proposed logic mining employs three unique optimization layers to improve the final induced logic. Extensive experiments are conducted on 15 real-life datasets from various fields of study. The experimental results demonstrated that our proposed logic mining method outperforms state-of-the-art methods in terms of widely used performance metrics. Full article

In this article, two great world religions, Islam and Buddhism, are compared. The purpose is to highlight similarities and differences between the two religions. Additionally, this article aims to project elements and teachings that are deemed important by their followers. A neutral stance on their beliefs is especially important in a multicultural society. The study was conducted to promote the harmony and betterment of Malaysian society, and the nation at large; a value process of understanding of each religion is recommended, which can then lead to acceptance, respect and tolerance among the population, and form the basis for developing a paradigmatic Malaysian society that has unity in diversity. This study adopted document analysis as the research method for data collection and data analysis. The conclusions drawn are that, although the two religions appear rather different in terms of principles and practices, the core values of avoiding evil and doing good are similar. In addition, the study proposes that without prejudice and pride, the basics of all commonly practiced religions in Malaysia should be introduced to all Malaysians, with the objective of all understanding, but not necessarily embracing, each other’s religion. Full article

Diabetes has become a major health problem in society. Invasive glucometers, although precise, only provide discrete measurements at specific times and are unsuitable for long-term monitoring due to the injuries caused on skin and the prohibitive cost of disposables. Remote, continuous, self-monitoring of blood sugar levels allows for active and better management of diabetics. In this work, we present a radio frequency (RF) sensor based on a stepped impedance resonator for remote blood glucose monitoring. When placed on top of a human hand, this RF interdigital sensor allows detection of variation in blood sugar levels by monitoring the changes in the dielectric constant of the material underneath. The designed stepped impedance resonator operates at 3.528 GHz with a Q factor of 1455. A microfluidic device structure that imitates the blood veins in the human hand was fabricated in PDMS to validate that the sensor can measure changes in glucose concentrations. To test the RF sensor, glucose solutions with concentrations ranging from 0 to 240 mg/dL were injected into the fluidic channels and placed underneath the RF sensor. The shifts in the resonance frequencies of the RF sensor were measured using a network analyzer via its S₁₁ parameters. Based on the change in resonance frequencies, the sensitivity of the biosensor was found to be 264.2 kHz/mg·dL⁻¹ and its LOD was calculated to be 29.89 mg/dL. Full article