An intelligent humidity control system for mushroom growing house by using beam-switching antennas with artificial neural networks

An automatic humidity control system for mushroom growing house based on the free-space technique is presented. The novelty of this work is the modified free-space technique by measuring the amplitude only of transmission coefficient |S21| that reflected from mushroom by using beam-switching antenna with artificial neural networks (ANNs) as a humidity sensor to control quantity and time of water misting nozzle. In the proposed system, the antenna is designed to act as the transmitting antenna at the frequency of 2.45 GHz. Its radiation patterns can be switched to 4 directions covering all corners of mushroom growing house. The measured |S21| from each direction are converted to direct current (DC) voltage by a radio frequency (RF) detector; then are trained with ANNs in the humidity range of 60-85%. The optimized ANNs structure consists of 4 input nodes, two layers of 5 hidden nodes, and 3 output nodes. To verify the proposed system, experiments were set up in controlled humidity mushroom growing house at the humidity level of 75-80% for 120 hours. The results showed that there was slightly average standard deviation (S.D.) of humidity level 1.36. Consequently, the performance of sensor system assures that it is able to apply for humidity control in large growing house

Bandwidth enhancement of dual-band bi-directional microstrip antenna using complementary split ring resonator with defected structure for 3/5 GHz applications

This paper presents a bandwidth enhancement of a dual-band bi-directional rectangular microstrip patch antenna. The novelty of this work lies in the modification of conventional rectangular microstip patch antenna by using the combination of two techniques: a complementary split ring resonator (CSRR) and a defected patch structure (DPS). The structure of antenna was studied and investigated via computer simulation technology (CST). The dimension and position of CSRR on the ground plane was optimized to achieve dual bandwidth and bi-directional radiation pattern characteristics. In addition, the bandwidths were enhanced by defecting suitable shape incorporated in the microstrip patch. A prototype with overall dimension of 70.45×63.73 mm2 has been fabricated on FR-4 substrate. To verify the proposed design, the impedance bandwidth, gain, and radiation patterns were carried out in measurements. The measured impedance bandwidths were respectively 560 MHz (3.08-3.64 GHz) and 950 GHz (4.64-5.59 GHz) while the measured gains of each bandwidth were respectively 4.28 dBi and 4.63 dBi. The measured radiation patterns were in good agreement with simulated ones. The proposed antenna achieves wide dual bandwidth and bi-directional radiation patterns performances. Consequently, it is a promising candidate for Wi-Fi or 5G communications in specific areas such as tunnel, corridor, or transit and rail

A Comparative Review of Contour and Raster Based Methods for the Prediction of Surface Water Flow from DEM Data

A water management strategy to cope with severe climate change needs an efficient streamline model to play the important role of predicting the direction of flood-water. Generally a model is constructed using various image processing techniques which, depending on the particular area, can be quite complicated. In this paper two conceptually different approaches for determining streamlines from DEM data, in raster and vector forms, are reviewed. The advantages and limitations of both approaches are considered and compared using the numerical results of streamlines for the geometrically complex region containing Khao Luang National Park

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure

<p>Abstract</p> <p>Background</p> <p>The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis.</p> <p>Results</p> <p>A new heuristic called EigenDev for detecting population structure is presented. When tested on simulated data, this heuristic is robust to sample size. In contrast, the TW statistic was found to be susceptible to type I error, especially for large population samples. EigenDev is thus better-suited for analysis of large datasets containing many individuals, in which spurious patterns are likely to exist and could be incorrectly interpreted as population stratification. EigenDev was applied to the iterative pruning PCA (ipPCA) method, which resolves the underlying subpopulations. This subpopulation information was used to supervise STRUCTURE analysis to infer patterns of ancestry at an unprecedented level of resolution. To validate the new approach, a bovine and a large human genetic dataset (3945 individuals) were analyzed. We found new ancestry patterns consistent with the subpopulations resolved by ipPCA.</p> <p>Conclusions</p> <p>The EigenDev heuristic is robust to sampling and is thus superior for detecting structure in large datasets. The application of EigenDev to the ipPCA algorithm improves the estimation of the number of subpopulations and the individual assignment accuracy, especially for very large and complex datasets. Furthermore, we have demonstrated that the structure resolved by this approach complements parametric analysis, allowing a much more comprehensive account of population structure. The new version of the ipPCA software with EigenDev incorporated can be downloaded from <url>http://www4a.biotec.or.th/GI/tools/ippca</url>.</p