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Design of a 24 GHz pattern reconfigurable slotted Yagi-Uda antenna on substrate integrated waveguide
(2013-09-02)
Limpiti, T.
;
Krairiksh, M.
This paper presents the design of a linearly polarized pattern reconfigurable antenna whose configuration employs a single feed and a low profile cavity backed slot antenna. The grounded coplanar waveguide feed is adopted to excite the slotted Yagi-Uda structure which is constructed on the substrate integrated waveguide (SIW). The whole antenna is thus completely constructed on a single layer of a printed circuit board (PCB) substrate. The concept of pattern reconfiguration is based on switching function between the director- and the reflector-parasitic slots of PIN diodes. This antenna is designed to operate at the frequency of 24 GHz that there are various applications, e.g., Doppler sensor in automotive and industrial applications, security applications, and communication applications. The simulation results show good matching and interesting performance in reconfiguring the radiation patterns. © 2013 IEEE.
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Improved iterative pruning principal component analysis with graph-theoretic hierarchical clustering
(2012-10-02)
Amornbunchornvej, C.
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Limpiti, T.
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Assawamakin, A.
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Intarapanich, A.
;
Tongsima, S.
Various unsupervised clustering algorithms have been used to infer population structure in genetic data. The goals are to separate individuals of similar genetic characteristics into clusters and to estimate the number of clusters within each dataset. Among them, a framework called iterative pruning principal component analysis (ipPCA) have been developed. It performs PCA iteratively on subsets of data samples and clusters them using fuzzy c-mean. We believe that the choice of model-based clustering method affects the individual assignments and cluster quality, as well as the estimated number of clusters. Thus, in this paper we introduce a hierarchical tree clustering concept from graph theory, whose performance is independent of cluster shapes, into the ipPCA framework. We also add a PCA-based feature selection technique as a data pre-processing step to reduce data dimension and increase computational efficiency. The resulting algorithm is called HiClust-ipPCA. We illustrate the improved clustering results of the HiClust-ipPCA algorithm using 47-breed bovine and 28-breed sheep datasets. © 2012 IEEE.
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Iterative Neighbor-Joining tree clustering algorithm for genotypic data
(2012-01-01)
Amornbunchornvej, C.
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Limpiti, T.
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Assawamakin, A.
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Intarapanich, A.
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Tongsima, S.
Issues to explore in genotypic datasets include the number and characteristic patterns of subpopulations and, possibly, relationships among them. Model-based clustering methods have been adopted to find a number of clusters and the individual assignments. However, they cannot infer genetic relationships among subpopulations the way phylogenetic trees, e.g., the widely-used Neighbor-Joining (NJ) tree, can. In this paper we propose an unsupervised, iterative clustering framework called iNJclust. It performs clustering on an NJ tree with a graph-based partitioning technique. The iterative process enhances the zooming ability and corrects the topology of the final NJ trees. Inference on genetic similarities between subpopulations is also possible. As final outputs, the iNJclust algorithm provides an estimate of the number of clusters, individual assignments, a population tree, as well as sub-trees of the terminal nodes. We illustrate the superior clustering performance of the proposed algorithm using Human 27 populations, bovine 47 breeds, and sheep 28 breeds datasets. © 2012 ICPR Org Committee.
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Time-frequency analysis for cancer detection using proteomic MS-spectra
(2011-12-01)
Limpiti, T.
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Assawamakin, A.
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Intarapanich, A.
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Tongsima, S.
Mass spectrum data is proven useful in cancer detection and biomarker discovery. Nevertheless, existing methods which analyze peaks of mass spectrum data still have some limitations, including variation in peak locations among individual samples, noisy data, irreproducibility of peak profiles, and computational burden. We introduce a simple algorithm in this paper which alleviate these drawbacks. Our approach is to analyze the mass spectrum data using time-frequency analysis. The data is transformed to features in the time-frequency domain. Informative features are then selected and subsequently used for detection or classification. To assess the efficacy of the proposed algorithm, we apply our algorithm to cancer detection problem. The performance of the algorithm is evaluated on real ovarian and prostate cancer datasets. The promising detection results with high sensitivity and specificity confirm the potential of our method in cancer detection. The algorithm is also applicable to multi-class classification and biomarker identification problems. © 2011 IEEE.
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Iterative PCA for population structure analysis
(2011-08-18)
Limpiti, T.
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Intarapanich, A.
;
Assawamakin, A.
;
Wangkumhang, P.
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Tongsima, S.
An extension of principal component analysis called ipPCA has been proposed earlier for analyzing structure in genetic data. This non-parametric framework iteratively classifies individuals into subpopulations. However, it is prone to false positives when dealing with large datasets and mixed-type genetic markers. We address these shortcomings by introducing a unified encoding scheme and suggesting a new terminating criterion for ipPCA. To validate the improvements, simulated datasets as well as real bovine and large human genetic datasets are analyzed. It is observed that the estimation of the number of subpopulations and the individual assignment accuracy have been improved. Furthermore, the structure resolved by this approach can be used to identify subset of individuals for further parametric population structure analysis. © 2011 IEEE.
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A handheld moisture content sensor using coupled-dipole antennas
(2010-07-01)
Mearnchu, J.
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Limpiti, T.
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Torrungrueng, D.
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Akkaraekthalin, P.
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Krairiksh, M.
This paper presents an analysis and design of a handheld moisture content sensor. A dielectric property determination technique was used to measure the magnitudes of the reflection and the coupling coefficients of coupled-dipole antennas. These coefficients were plotted and their intersection determined to obtain the values of ε' <inf>r</inf> and ε" <inf>r</inf> (ε' <inf>r</inf> and ε" <inf>r</inf>, respectively, are the real and imaginary parts of the relative complex permittivity of the dielectric of interest). Moisture content measurements for paddy at various moisture content levels are shown. Comparison of measurements made by this technique with those made by conventional transmission measurement technique yielded a compensation scheme for error reduction. This sensor is useful for controlling the quality of paddy dried in a continuous microwave drying system process.
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Complex permittivity determination by measuring magnitude of mutual coupling between Co and cross polarized dipoles
(2007-12-01)
Limpiti, T.
;
Krairiksh, M.
A new technique for determining the complex permittivity of a material is proposed. This proposed technique considers only the magnitude of mutual coupling obtained from co and cross polarized dipoles. According to this technique, the complex permittivity can be determined by measuring magnitude of mutual coupling from the two cases, first is parallel-in-echelon dipoles and another case is perpendicular dipoles. To prove this technique, the complex permittivity of distilled water at the frequency of 2.45 GHz has been compared with the simulation results obtained from this technique. The antenna length of halfwave in dielectric which dielectric constant close to the measured material provides more accurate results than that of different from the measured one.

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