PGT-Net: Progressive Guided Multi-task Neural Network for Small-area Wet Fingerprint Denoising and Recognition

Fingerprint recognition on mobile devices is an important method for identity verification. However, real fingerprints usually contain sweat and moisture which leads to poor recognition performance. In addition, for rolling out slimmer and thinner phones, technology companies reduce the size of recognition sensors by embedding them with the power button. Therefore, the limited size of fingerprint data also increases the difficulty of recognition. Denoising the small-area wet fingerprint images to clean ones becomes crucial to improve recognition performance. In this paper, we propose an end-to-end trainable progressive guided multi-task neural network (PGT-Net). The PGT-Net includes a shared stage and specific multi-task stages, enabling the network to train binary and non-binary fingerprints sequentially. The binary information is regarded as guidance for output enhancement which is enriched with the ridge and valley details. Moreover, a novel residual scaling mechanism is introduced to stabilize the training process. Experiment results on the FW9395 and FT-lightnoised dataset provided by FocalTech shows that PGT-Net has promising performance on the wet-fingerprint denoising and significantly improves the fingerprint recognition rate (FRR). On the FT-lightnoised dataset, the FRR of fingerprint recognition can be declined from 17.75% to 4.47%. On the FW9395 dataset, the FRR of fingerprint recognition can be declined from 9.45% to 1.09%

Investigation of Novel Noncontacting Measurement Method by the Design of Loop-Type Probe and Reconstruction of Radiation Modeling

Because the ICs’ application frequency and speed become higher and trends of system packaging and device under test request higher reliability, a novel technology combining noncontacting measurement method and reconstructing radiation model was proposed to solve signal deliveries in system packages or PCBs. In this study, a novel noncontacting method for the ICs’ measurements was investigated by the design of loop-type near-field probe and reconstructed the radiation model to substitute the traditional measurement methods, such as using probes and SMA connectors. A near-field probe was used to receive the coupling signal. The assessing circuit modeling could be completed by some synthesized theorems. According to the study’s results, frequency responses of reconstruction model developed by theorems, radiation measurements, and simulated by EM methods were highly curve fitting

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Improving Image Quality Assessment Based on the Combination of the Power Spectrum of Fingerprint Images and Prewitt Filter

The assessment of fingerprint image quality is critical for most fingerprint applications. It has an impact on the performance and compatibility of fingerprint recognition, authentication, and built-in cryptosystems. This paper developed an improved fingerprint image quality assessment derived from the image power spectrum approach and combined it with the Prewitt filter and an improved weighting method. The conventional image power spectrum approach and our proposed approach were implemented for accuracy and reliability tests using good, faulty, and blurred fingerprint images. The experimental results showed the proposed algorithm accurately identified the sharpness of fingerprint images and improved the average difference in FIQMs to 61% between three different levels of blurred fingerprints compared with that achieved by a conventional algorithm

Are we ready for the global emergence of multidrug-resistant Candida auris in Taiwan?

Candida auris is a recently identified multi-resistant Candida species, first reported in Japan in 2009, and poses a serious global health threat. Lack of awareness of this new Candida species and difficulties with laboratory identification have impacted significantly on outbreak detection and management, and compromised patient outcome. Accordingly, there is an urgent need to raise awareness of healthcare personnel to this emerging pathogen and determine its prevalence, impact, and challenges to the Taiwan healthcare system. Enhanced laboratory testing strategies are needed to differentiate C. auris from other Candida species to provide accurate diagnosis and implement control measures early enough to prevent hospital outbreaks. In this report, we review the key epidemiological, microbiological and clinical characteristics of C. auris and provide the results of a multicenter surveillance study of C. auris in Taiwan. We also conducted a web-based survey to determine awareness of the medical community to C. auris and the capability of Taiwanese hospital laboratories to identify this microorganism. C. auris has not yet been isolated from humans in Taiwan, but the unique features of this microorganism and its ability to reach across international boundaries justify the importance of these initiatives in Taiwan. Keywords: Candida auris, Laboratory, Identification, Epidemiology, Taiwa