Social Interactive Human Video Synthesis

Abstract. In this paper, we propose a computational model for social interaction between three people in a conversation, and demonstrate results using human video motion synthesis. We utilised semi-supervised computer vision techniques to label social signals between the people, like laughing, head nod and gaze direction. Data mining is used to deduce frequently occurring patterns of social signals between a speaker and a listener in both interested and not interested social scenarios, and the mined confidence values are used as conditional probabilities to animate social responses. The human video motion synthesis is done using an appearance model to learn a multivariate probability distribution, combined with a transition matrix to derive the likelihood of motion given a pose configuration. Our system uses social labels to more accurately define motion transitions and build a texture motion graph. Traditional motion synthesis algorithms are best suited to large human movements like walking and running, where motion variations are large and prominent. Our method focuses on generating more subtle human movement like head nods. The user can then control who speaks and the interest level of the individual listeners resulting in social interactive conversational agents.

A sensitive method for the determination of gold and palladium based on dispersive liquid-liquid microextraction combined with flame atomic absorption spectrometric determination using N-(6-morpholin-4-ylpyridin-3-yl)-N '-phenylthiourea

Soylak, Mustafa/0000-0002-1017-0244WOS: 000369515500005A new method for the determination of gold and palladium was developed by dispersive liquid-liquid microextraction separation-preconcentration and flame atomic absorption spectrometry detection. In the proposed approach, N-(6-morpholin-4-ylpyridin-3-yl)-N'-phenylthiourea (MPPT) was synthesized as a complexing agent. The complexation ability of the MPPT was explored by examining the effect of a series of heavy metal ions, including Mn2+, Pd2+, Ni2+, Cd2+, Co2+, Cu2+, Au3+, Pb2+, Zn2+ and Fe3+, using the DLLME procedure. The MPPT exhibited pronounced selectivity toward Pd2+ and Au3+ ions at different pH levels. Factors influencing the extraction efficiency and complex formation were examined, i.e. the pH of the sample solution, the concentration of the chelating agent, the extraction and dispersive solvent type and volume, the sample volume, and foreign ions, etc. Optimal conditions for quantitative recoveries were pH 5.5 for gold and pH 1.5 for palladium, 125 mu L of % 0.4 MPPT, 1200 mu L of methanol and 125 mu L of carbon tetrachloride. The presented method showed a good linearity within a range of 30-230 and 25-200 mu g L-1 with the detection limits of 1.75 and 1.65 mu g L-1 for Au and Pd, respectively. The relative standard deviation (RSD) was below 2.8% at 50 mu g L-1 for both ions (n = 10). The developed method was simple, fast, cost efficient, and sensitive for the extraction and preconcentration of gold and palladium in samples of liquids (sea, stream water) and solids (stream sediment, ores, and electronic waste).Unit of the Scientific Research Projects of Karadeniz Technical University [1223]Financial support of the Unit of the Scientific Research Projects of Karadeniz Technical University (Project no: 1223) is gratefully acknowledged