Augmented reality application to improve remedial student’s learning performance

A high concentration of uric acid in human blood will form a crystal that accumulates in the joints and causes inflammation and severe pain to the patient. In literature, the direct detection spectroscopy technique has been employed in uric acid detection due to its eco-friendly and rapid response features. Despite these advantages, the linearity range obtained is very limited. Therefore, to enhance the linearity range, a direct detection-based spectroscopy method in the visible light spectrum is proposed in this work. The enhancement is attributed to the relatively low molar attenuation coefficient in the visible light spectrum. This work analyzed the detection of uric acid in the visible spectrum utilizing a halogen lamp as a light source. The uric acid stock solution in this project was prepared by diluting the uric acid powder in deionized (DI) water. Then, 2, 4, 6, 8, and 10 mg/dL sample solutions were produced by diluting the stock solution based on molarity formulation. These samples were then transferred into a sample compartment for the measuring process. In measuring the samples, the output intensity spectrum was monitored as the concentration varies from 2 to 10 mg/dL. The linearity range, linearity, sensitivity, limit of detection (LoD), stability precision, and relative standard deviation (RSD) of the developed spectrophotometer were studied. The sensor performance at sample wavelengths of 600nm, 650nm, 700nm, 750nm, 800nm, 850nm, and 900nm was analyzed. The highest spectrophotometer sensitivity of 0.0515 (mg/dL)-1 was achieved at 700nm wavelength. However, this sample wavelength has a low linearity value, which is about 91%. As for the linearity performance, the best linearity was achieved at 850nm wavelength with 98% linearity value. All the sample wavelengths exhibited more than 99% precision with less than 1% RSD for 300 seconds measurement duration, which indicates a highly stable detection and good reproducibility. The selectivity of the optimal operating wavelength offers comparable linearity and sensitivity performances of the developed spectrophotometer with rapid detection and high stability performances

Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence

Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices. MAR systems enable users to interact with MAR devices, such as smartphones and head-worn wearables, and perform seamless transitions from the physical world to a mixed world with digital entities. These MAR systems support user experiences using MAR devices to provide universal access to digital content. Over the past 20 years, several MAR systems have been developed, however, the studies and design of MAR frameworks have not yet been systematically reviewed from the perspective of user-centric design. This article presents the first effort of surveying existing MAR frameworks (count: 37) and further discuss the latest studies on MAR through a top-down approach: (1) MAR applications; (2) MAR visualisation techniques adaptive to user mobility and contexts; (3) systematic evaluation of MAR frameworks, including supported platforms and corresponding features such as tracking, feature extraction, and sensing capabilities; and (4) underlying machine learning approaches supporting intelligent operations within MAR systems. Finally, we summarise the development of emerging research fields and the current state-of-the-art, and discuss the important open challenges and possible theoretical and technical directions. This survey aims to benefit both researchers and MAR system developers alike.Peer reviewe