Fingerprint Database Enhancement by Applying Interpolation and Regression Techniques for IoT-based Indoor Localization

Most applied indoor localization is based on distance and fingerprint techniques. The distance-based technique converts specific parameters to a distance, while the fingerprint technique stores parameters as the fingerprint database. The widely used Internet of Things (IoT) technologies, e.g., Wi-Fi and ZigBee, provide the localization parameters, i.e., received signal strength indicator (RSSI). The fingerprint technique advantages over the distance-based method as it straightforwardly uses the parameter and has better accuracy. However, the burden in database reconstruction in terms of complexity and cost is the disadvantage of this technique. Some solutions, i.e., interpolation, image-based method, machine learning (ML)-based, have been proposed to enhance the fingerprint methods. The limitations are complex and evaluated only in a single environment or simulation. This paper proposes applying classical interpolation and regression to create the synthetic fingerprint database using only a relatively sparse RSSI dataset. We use bilinear and polynomial interpolation and polynomial regression techniques to create the synthetic database and apply our methods to the 2D and 3D environments. We obtain an accuracy improvement of 0.2m for 2D and 0.13m for 3D by applying the synthetic database. Adding the synthetic database can tackle the sparsity issues, and the offline fingerprint database construction will be less burden. Doi: 10.28991/esj-2021-SP1-012 Full Text: PD

Effects of low temperature drying processing on longan fruit

In this study, the single-stage drying in tray dryer at air temperatures of 40, 50, 60, 70 and 80°C is modelled and investigated. The longan fruits, E-dor variety, are peeled and seeded before testing. The drying rate is significantly influenced by the drying techniques and temperatures. Drying rats are initialized adjustment constant rate periods at 60 70 and 80°C. The rate of moisture removal is rapidly changed drastically during the falling rate period. The Midilli model with high R2 and low χ2 and RMSE is the most suitable model for predictability of longan drying. Variation rates of quality of the water activity, the shrinkage, and the browning index are also reported

Rapid detection of hairline cracks on the surface of piezoelectric ceramics

Lead zirconate titanate, also known as PZT, is a type of piezoelectric ceramics commonly used for actuators in modern hard disk drives (HDDs). These PZT actuators are prone to hairline surface cracks, prompting detection and removal during the HDD production. Machine vision is then utilized for automatic detection of these cracks. The developed image processing approach comprises three steps: extraction of the region of interest, enhancement of crack regions, and elimination of irrelevant features. The key step, crack region enhancement, employs image filtering with a specifically designed filter kernel, capable of extracting thin crack regions from the rough surface of PZT actuators. The experiments show that the algorithm reveals cracks with high accuracy and high sensitivity, whereas the overall processing time satisfies the industrial environment.Withawat Withayachumnankul, Pichate Kunakornvong, Channarong Asavathongkul, Pitikhate Sooraks