Facial Expression Synthesis Based on Imitation

[[abstract]]It is an interesting and challenging problem to synthesise vivid facial expression images. In this paper, we propose a facial expression synthesis system which imitates a reference facial expression image according to the difference between shape feature vectors of the neutral image and expression image. To improve the result, two stages of postprocessing are involved. We focus on the facial expressions of happiness, sadness, and surprise. Experimental results show vivid and flexible results.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Low-complexity face-assisted video coding

[[abstract]]This paper presents a novel face-assisted video coding scheme to enhance the visual quality of the face regions in video telephony applications. A skin-color based face detection and tracking scheme is proposed to locate the face regions in real-time. After classifying the macroblocks into the face and non-face regions, we present a dynamic distortion weighting adjustment (DDWA) scheme to drop the static non-face macroblocks, and the saved bits are used to compensate the face region by adjusting the distortion weighting of the face macroblocks. The quality of face regions will thus be enhanced. Moreover, the computation originally required for the skipped macroblocks can also be saved. The experimental results show that the proposed method can significantly improve the PSNR and the subjective quality of face regions, while the degradation introduced on the non-face areas is relatively insensitive to human perception. The proposed algorithm is fully compatible with the H.263 standard, and the low complexity feature makes it well suited to implement for real-time applications[[fileno]]2030144030041[[department]]電機工程學

Rapid analysis of triclosan in water samples using an in-tube ultrasonication assisted emulsification microextraction coupled with gas chromatography-electron capture detection

In this study, a new in-tube based ultrasound-assisted emulsification microextraction (IT-USAEME) technique coupled with gas chromatography-micro-electron capture detection (GC-μECD) was developed for the efficient and rapid analysis of triclosan in environmental water samples. In this extraction procedure, the aqueous sample was taken in an indigenously fabricated home-made glass extraction device (an 8 mL glass tube inbuilt with a self-scaled capillary tip) and extraction solvent (low density organic solvent) was added to it followed by ultrasonication. After extraction, the upper extractant layer was narrowed into the self-scaled capillary tip by pushing the plunger plug; thus making the collection and measurement of the upper organic solvent layer simple and convenient. Parameters affecting the extraction efficiency such as selection of extraction solvent, extraction solvent volume, ultrasonication time, pH and ionic strength were thoroughly investigated and optimized. Under optimal conditions, the method showed good linearity in the concentration range from 20–2000 ng L−1 with a correlation coefficient of 0.9982 for the target analyte. The limit of detection was 4 ng L−1 and the enrichment factor obtained was 331. The method was validated with real water samples and the relative recoveries of environmental water samples ranged between 91.2 and 97.3% and relative standard deviations ranged between 2.8 and 5.4%, making the proposed method highly reliable. Moreover, the present approach avoids the usage of chlorinated organic extraction solvents and derivatization processes for triclosan determination. The proposed method provides a simple, rapid, sensitive, low cost, easy to handle (in-tube set-up for USAEME) and eco-friendly procedure to determine triclosan in aqueous samples

A Comparative Study for 2D and 3D Computer-aided Diagnosis Methods for Solitary Pulmonary Nodules

Many computer-aided diagnosis (CAD) methods, including 2D and 3D approaches, have been proposed for solitary pulmonary nodules (SPNs). However, the detection and diagnosis of SPNs remain challenging in many clinical circumstances. One goal of this work is to investigate the relative diagnostic accuracy of 2D and 3D methods. An additional goal is to develop a two-stage approach that combines the simplicity of 2D and the accuracy of 3D methods. The experimental results show statistically significant differences between the diagnostic accuracy of 2D and 3D methods. The results also show that with a very minor drop in diagnostic performance the two-stage approach can significantly reduce the number of nodules needed to be processed by the 3D method, streamlining the computational demand

Gender Determination using Fingerprint Features

Several previous studies have investigated the gender difference of the fingerprint features. However, regarding to the statistical significance of such differences, inconsistent results have been obtained. To resolve this problem and to develop a method for gender determination, this work proposes and tests three fingertip features for gender determination. Fingerprints were obtained from 115 normal healthy adults comprised of 57 male and 58 female volunteers. All persons were born in Taiwan and were of Han nationality. The age range was18-35 years. The features of this study are ridge count, ridge density, and finger size, all three of which can easily be determined by counting and calculation. Experimental results show that the tested ridge density features alone are not very effective for gender determination. However, the proposed ridge count and finger size features of left little fingers are useful, achieving a classification accuracy of 75% (P-valu

GPER-induced signaling is essential for the survival of breast cancer stem cells.

G protein-coupled estrogen receptor-1 (GPER), a member of the G protein-coupled receptor (GPCR) superfamily, mediates estrogen-induced proliferation of normal and malignant breast epithelial cells. However, its role in breast cancer stem cells (BCSCs) remains unclear. Here we showed greater expression of GPER in BCSCs than non-BCSCs of three patient-derived xenografts of ER- /PR+ breast cancers. GPER silencing reduced stemness features of BCSCs as reflected by reduced mammosphere forming capacity in vitro, and tumor growth in vivo with decreased BCSC populations. Comparative phosphoproteomics revealed greater GPER-mediated PKA/BAD signaling in BCSCs. Activation of GPER by its ligands, including tamoxifen (TMX), induced phosphorylation of PKA and BAD-Ser118 to sustain BCSC characteristics. Transfection with a dominant-negative mutant BAD (Ser118Ala) led to reduced cell survival. Taken together, GPER and its downstream signaling play a key role in maintaining the stemness of BCSCs, suggesting that GPER is a potential therapeutic target for eradicating BCSCs

The collaboration of noise reduction and human vision system models for a visible watermarking algorithm

ABSTRACT A novel visible watermarking algorithm based on noise reduction and Human Visible System (HVS) model approach is presented in this study. In order to get the best tradeoff between the embedding energy of watermark and the perceptual translucence for visible watermark, the composite coefficients using global and local characteristics of the host image in the discrete wavelet transform (DWT) domain is considered. The application of the perceptual model of contrast-sensitive function (CSF) with the noise reduction of the visibility thresholds for HVS in DWT domain achieves the goal of fine tuning of the perceptual weights according to the basis function amplitudes for the best quality of perceptual translucence. Instead of three types of block classification-textures, edges and smooth areas, the computation of Noise Visibility Function (NVF) characterizes the local image properties to determine the optimal watermark locations and strength at the watermark embedding stage. The experimental results demonstrate that the proposed technique improves the PSNR values and visual quality than the CSF only based algorithms