Boonsang, Siridech
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Preferred name
Boonsang, Siridech
Alternative Name
Boonsang, S.
Main Affiliation
Email
siridech.bo@kmitl.ac.th
72 results
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Item type:Publication, A highly sensitive laser-EMAT imaging system for biomedical applications(2014-10-15); Dewhurst, R. J.This paper describes a novel technique using an elctromagnetic acoustic transducer (EMAT) for biomedical photoacoustic measurements. The physical principle underlying and EMAT sensor is based on the detection of electromagnetic signals, which are responses from the interaction of ultrasonic waves and magnetic fields within the electrically conductive sample surface. A recent prototype EMAT sensor has miniaturized the receiver size (1.0 cm diameter). It is incorporated with a specially designed low noise preamplifier. Calibration procedures with a Michelson interferometer revealed that the EMAT sensor detected small displacement amplitudes as low as 1.0±0.2 pm in ultrasonic frequency range using an aluminium sample. For the first time, we present the use of an EMAT sensor to detect photoacoustic pressure signals in tissue phantoms and real tissues (chicken breast) in vitro. Corresponding B-scan images were constructed by the compilation of a series of received photoacoustic signals. A B-scan image of human hairs in a chicken breast sample revealed that the lateral resolution about 1.57 mm (FWHM) was achieved. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Reflection image model for micro-ellipsometer(2019-07-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A numerical model for ultrasonic measurements of swelling and mechanical properties of a swollen PVA hydrogel(2010-08-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of multi-hop wireless sensor networks using probability propagation models(2019-01-01); ; This paper presents a formula for estimating the probability of collecting a given amount of data from a propagation model and multi-hop wireless sensor networks (WSNs) based on Monte Carlo simulation with cluster-tree topology. The probabilistic model is based on an analytical model of the IEEE 802.15.4 MAC protocol. The probability of successful node transmission is extended to the probabilities of successful collection at the cluster P(X=k) and sink node P(X ≥ k). A numerical example has been provided for comparing the probabilities. We propose a model to calculate the probability from the ratio of the collection rate to the total number of nodes and therefore provide the likeliness of complete data collection. Finally, the results from our analysis provide an estimation of the probability of achieving successful transmission in WSNs. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A computational model of magnetic fluid flow based on Maxwell's equation and Navier-Stokes equations(2006-01-01); ; Sangworasil, M.The magnetic liquids such as ferrofluids, biocompatible magnetic nanocarrier, play an important role as drug carriers in the human body. Based on Maxwell's equation and Navier-Stokes equations, a time-dependent analysis of a two-dimensional computational model of magnetic fluid flow is purposed. The FEM is applied to solve Maxwell's equation for a static magnetic field, and Navier-Stokes equations for fluid dynamics. The result of magnetic field has some influences to ferrofluid dynamic flow in blood vessel. ©2006 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An interferometric back focal plane microellipsometry for the determination of optical properties of a slider's air bearing surface(2014-02-12) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A system identification model for ultrasonic characterization of a swollen PVA hydrogel(2008-10-06) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A new magnetic configuration for a small in-plane electromagnetic acoustic transducer applied to laser-ultrasound measurements: Modelling and validation(2006-01-10); Dewhurst, R. J.This paper presents an enhanced in-plane electromagnetic acoustic transducer (EMAT) for detecting laser-generated ultrasound. Instead of using post-processing of numerical data to enhance signal-to-noise, the paper describes a new EMAT design to increase the magnetic flux density applied to the sample. The EMAT's magnetic flux density was modelled in 3D using a finite element software to predict new magnetic spatial field distributions. A configuration was found to increase the flux density by a factor of 1.8 ± 0.2, compared to magnetic configurations previously used in conventional designs. Field predictions were implemented and confirmed experimentally. As a consequence, laser-ultrasound Rayleigh waves have been used to validate the performance of this sensor system. It was found that the EMAT's in-plane sensitivity increased by a factor of 2.0 ± 0.2. © 2005 Elsevier B.V. All rights reserved. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Images Retrieval and Classification for Acute Myeloid Leukemia Blood Cell Using Deep Metric Learning(2023-01-01); ; Deep metric learning-based image retrieval systems have recently been used in medical applications because they provide clinically relevant information-based similar images based on prior knowledge. Although train examiners and deep learning models successfully analyze leukocyte cells, there are still numerous difficult challenges due to biological variation, time constraints, and a variety of image-related aspects. In this study, we propose a deep metric learning model-based image retrieval and classification system for acute myeloid leukemia blood cells to address these issues and assist physicians. The proposed model utilizes the pre-trained ResNet-34 model as the backbone network, embedding loss with multi similarity miner, and M-Per-Class sampling strategy to learn an embedding function. The five embedding losses were also applied to compare the four performances in order to determine the best loss-based model. Based on the best loss-based model, the class-wise precision and sensitivity using a neighborhood size are also presented. The results show that the contrastive loss-based deep metric learning model achieved the highest precision of 94.90%, sensitivity of 94.85%, specificity of 99.64%, and accuracy of 99.32% in model comparison. Except for a few failures in small classes, the class-wise precision and sensitivity scores looked to be impressive in all classes. Therefore, this proposed system can highly be effective in screening and diagnosing of AML-related white blood cell stages that cause serious cancer. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Uncertainty analysis of polarization interferometric measurements of hard disk drive recording head-media dynamic spacing(2012-12-01); Aroonjarernchay, WanchaiIn this paper the numerical method based on Monte-Carlo techniques is utilized for the analysis of the flying height measurement uncertainty. In the current flying height tester, the prediction of error is the main concern in order to assure the attainable precision. In previous study, a simplified analytical method is normally used and it may not provide the accurate results of the error prediction especially when the amount of the flying height values becoming as low as sub-5 nm. In this paper, instead of using the analytical method for error analysis, the numerical method based on Monte-Carlo techniques is utilized. Our simulation results show that the measurement uncertainty is mainly from the variation in the optical constants of the DLC layer. They also show that the increasing of standard deviation of the optical constants of DLC layer causes the higher measurement uncertainty. © 2012 IEEE.