Sound absorption coefficient of oil palm trunk was explored using an impedance tube. Palm samples were taken from the central part of oil palm trunks with cut directions parallel and perpendicular to vascular bundles. Sound absorption was evaluated for palm panels with blind-holes with multiple radii and depths, as well as perforated and grooved panels and a panel with perforated holes at different distances from a solid backing. Measurements of sound absorption within the frequency range of 300-2000 Hz indicated that the sound absorption coefficient of the cross-cut biomass, ~0.15, was slightly greater than that of the parallel-cut panel, ~0.10. Samples with different depths of blind holes showed slight improvements in sound absorption coefficients as compared to the unmodified cross-cut panel. There was a significant improvement for 5-mm hole diameter with 10-mm depth, ~25% improvement as compared to that of 5-mm depth. The combination of the through-hole panel and grooved board allowed ~80% of sound to be absorbed for 1750 to 2000 Hz. Finally, the grooved board was removed and an air cavity backing was introduced by placing the through-hole panel 2-, 4-, and 6-mm away from the tube end. The sound absorption coefficients were then measured to be greater than 80% near the resonance frequencies, as calculated using the distributed Helmholtz resonator model.

Video analysis is carried out for one-dimensional motion and collision experiments using Tracker. Physical variables, i.e. displacement, time, and velocity, can be deducted from the analysis and allows one to connect them to the equation of motion and energy conservation. Corresponding equations of motions are given without neglecting the effect of friction and air resistance. Their solutions are used as models for data-fitting purposes. The fitting results allow one to find the surface friction coefficient and the air resistance parameter for the first experiment and friction for the second experiment. These experiments and analyses can be implemented for at least sophomore-level physics in a university. However, if simplified by removing all resistant parts, they can be used for high-school or first-year students in a university. The video files can be distributed to students for online courses that are prevalently ongoing worldwide due to the COVID pandemic. Students can observe the experiments and analyse data at home. With scheduled online consulting sessions, students can conduct the analysis with helps from instructors.

This study explored the use of top-view movies of propagating gravity water waves to reconstruct the underwater bed profile of shallow water bodies. Water waves of 2.8 and 3.1 Hz were generated by a microcontroller-driven flat flap in a wave flume of dimensions 0.48 × 1.80 × 0.40 m $^{3}$ . Three different bed profiles, i.e., sloped, stepped, and split surfaces, were used to imitate typical seabeds near shorelines. Top-view movies of the propagating waves were recorded and converted to spatial phase-speed images via video analysis. The phase speed images can be used to reconstruct the underwater bed profile using the dispersion relation of linear water waves. We also proposed a demodulation method to correct the phase-speed alteration due to wave interference. The correction method helped improve the mean average percentage error for depth profile predictions from 15% to 10% for the sloped profile and from 45% to 15% for the stepped profile. However, the approach was inferior for the split profile due to wall effects and complex interference patterns. This study suggests the proposed approach can determine the depth level around shorelines using time-evolution or video data with an adequate accuracy of 10% with minimal interference.

The Old Historical Wall, located in Bo Yang, Songkhla Province, Thailand, is an archaeological icon believed to have been constructed during the reign of Rama III, as indicated in the royal archives, around 1837–1840 CE. However, the recorded age is the result of unofficial documentation. The establishment was based on speculation from circumstantial evidence and local stories. The wall is made of bricks that underwent a heating process before being used for the construction. We therefore propose the use of the thermoluminescence technique for dating the wall. The samples include brick rubble from three excavation sites next to the wall. To determine the age, we estimate the radiation dose rate and the accumulated dose for each sample. The dose rate of the sample is determined using gamma spectroscopy with a high-purity germanium detector. For the accumulated dose, we employ the additive dose method using Co-60 with a dose range of 0–100 Gy. Glow curves are then deconvoluted using the general-order kinetics model. The results yield three superposition glow peaks at three different temperature ranges. Plateau tests are also carried out to find a proper temperature for dating purposes. Comparing the plateau test and the result of deconvolution, we find that the glow curve temperature suitable for dating was within 200–310 °C. The accumulated doses are then evaluated using the area under the curve of the peak temperature. The date is then determined as the ratio between the accumulated dose and the dose rate. The results indicate that the age is approximately 174–192 years, so that the wall was built around 1827–1841 CE, with one standard deviation interval. The duration is in agreement with the recorded age of the wall inscribed in the country's historical archives.

This exploratory case study examines the feasibility of integrating generative artificial intelligence (AI) into a low-cost Kundt’s tube activity in pre-service science teacher education. The proposed Do-It-With-AI framework comprises four phases: conceptual exploration, design development, troubleshooting, and extension to real-world applications. Scopus AI was used to support the literature-oriented conceptual exploration, while ChatGPT-4 and ChatGPT-5 supported the generation of design alternatives, troubleshooting hypotheses, and possible extensions. Three pre-service teachers constructed and tested the apparatus, and successive configurations were evaluated through resonance measurements and estimation of the speed of sound. The case illustrates how AI-generated suggestions can be incorporated into an iterative design–test–verification process in which proposed modifications are examined against physical principles and experimental evidence. The four-phase sequence is therefore presented as a feasible framework for integrating generative AI with hands-on experimentation, with instructor-guided verification serving as an essential component. Because the present study focuses on feasibility and process rather than educational outcomes, further investigation with larger cohorts and explicit measures of student reasoning, learning, collaboration, and AI literacy is required. The principal contribution of the Kundt’s tube case is to demonstrate a structured and empirically grounded use of generative AI in low-cost experimental development within pre-service science teacher education.