Search

The contact angle (CA) goniometer adaptable to a superconducting magnet was developed based on the sessile drop method. The goniometer mainly consisted of the sampling system, the supporting system, and the image acquisition system. Some improvements were taken to avoid the effects of the magnetic field (MF) on the CA measurement. As an example, the CAs of water on two substrates of silica and polymethyl methacrylate (PMMA) were measured using the goniometer. The results with and without a MF showed a good repeatability and reliability. Additionally, the MF was found to reduce the CA of water, which probably stemmed from the change of the surface tension in the MF. The CA goniometer will become an important tool which is used to study the wettability of liquids on a solid in the MF. [ABSTRACT FROM AUTHOR]

The diffusivity in the Ni-Al system with and without an alternating magnetic field (AMF) was investigated by the diffusion couple technique. It was found that the diffusion coefficient was increased with increasing AMF intensity. The enhanced diffusivity in the AMF can be ascribed to the increase in the dislocation density in the diffusion couples, which was demonstrated by the broadening of X-ray diffraction peaks. The higher dislocation density was induced by the magnetoplastic effect (MPE). The theoretical calculation based on the MPE is in agreement with the experimental values. [ABSTRACT FROM AUTHOR]

The article presents a study on the interaction of Pen-Centric computing in designing natural user interface for multimedia information in Brown University in Providence, Rhode Island. The adaptability of Pen-Centric computing to a wide spectrum of environments distinguishes itself in conceptualizing a design. It discusses the three areas from which the study is focused including math beyond recognition, chemistry and diagramming. Additionally, the researchers suggests that pen-computing is essential in augmenting, even replacing the windows, icon, menu, pointing device (WIMP) GUI interaction with more efficient mode of interaction closer to the ideal of user-interface transparency.

An instrumented data glove with a wireless interface provides convenient and natural human-computer interaction for people with speech or hearing impairments. [ABSTRACT FROM AUTHOR]

Abstract  Three dimensional human motions recorded by motion capture and hand gestures recorded by using data gloves generate variable-length data streams. These data streams usually have dozens of attributes, and have different variations for similar motions. To segment and recognize motion streams, a classification-based approach is proposed in this paper. Classification feature vectors are extracted by utilizing singular value decompositions (SVD) of motion data. The extracted feature vectors capture the dominating geometric structures of motion data as revealed by SVD. Multi-class support vector machine (SVM) classifiers with class probability estimates are explored for classifying the feature vectors in order to segment and recognize motion streams. Experiments show that the proposed approach can find patterns in motion data streams with high accuracy. [ABSTRACT FROM AUTHOR]

Fast and accurate recognition of motion data streams from gesture sensing and motion capture devices has many applications and is the focus of this article. Based on the analysis of the geometric structures revealed by singular value decompositions (SVD) of motion data, a similarity measure is proposed for simultaneously segmenting and recognizing motion streams. A direction identification approach is explored to further differentiate motions with similar data geometric structures. Experiments show that the proposed similarity measure can segment and recognize motion streams of variable lengths with high accuracy, without knowing beforehand the number of motions in a stream. [ABSTRACT FROM AUTHOR]

Multi-attribute motion data can be generated in many applications/ devices, such as motion capture devices and animations. It can have dozens of attributes, thousands of rows, and even similar motions can have different durations and different speeds at corresponding parts. There are no row-to-row correspondences between data matrices of two motions. To be classified and recognized, multi-attribute motion data of different lengths are reduced to feature vectors by using the properties of singular value decomposition (SVD) of motion data. The reduced feature vectors of similar motions are close to each other, while reduced feature vectors are different from each other if their motions are different. By applying support vector machines (SVM) to the feature vectors, we efficiently classify and recognize real-world multi-attribute motion data. With our data set of more than 300 motions with different lengths and variations, SVM outperforms classification by related similarity measures, in terms of accuracy and CPU time. The performance of our approach shows its feasibility of real-time applications to real-world data. [ABSTRACT FROM AUTHOR]

We examined the association between education and prevalent HIV-1 infection in the Rakai district, rural Uganda based on a cross-sectional analysis of a population-based cohort. In 1990, 1397 men and 1705 women aged 13 years and older, were enrolled in 31 randomly selected communities. Strata were comprised of main road trading centres, secondary road trading villages and rural villages. Sociodemographic and behavioural data were obtained by interview and serum for HIV serostatus were obtained in the home. The analysis examines the association between sex-specific prevalent HIV infection and educational attainment, categorized as secondary, primary or none. The odds ratios (ORs) and 95% confidence intervals (95% CIs) of HIV infection were estimated, using no education as the referent group. Higher levels of education were associated with a higher HIV seroprevalence in bivariate analyses (OR 2.7 for primary and 4.1 for secondary education, relative to no education). The strength of the association was diminished but remained statistically significant after multivariate adjustment for sociodemographic and behavioural variables (adjusted OR of HIV infection 1.6 (95% CI: 1.2-2.1)) for primary education and 1.5 (95% CI: 1.0-2.2) for secondary education. Stratified multivariate analyses by place of residence indicated that the association between education and HIV prevalence was statistically significant in the rural villages, but not in the main road trading centres and intermediate trading villages. Educational attainment is a significant predictor of HIV risk in rural Uganda, in part because of risk behaviours and other characteristics among better educated individuals. Preventive interventions need to focus on better educated adults and on school-aged populations. [ABSTRACT FROM AUTHOR]

Assesses the cases of human papillomavirus (HPV) infections among women between 15-59 years old in Uganda. Intensity of the infection evaluated using the relative light unit ratio; Percentage of HPV prevalence; Significance of the study in developing population-based screening to identify women at high risk of cervical neoplasia.

The undercooling behaviors of the three metal melts with different magnetisms, i.e., paramagnetic Al and Sn and diamagnetic Zn in a steady magnetic field (SMF) up to 6 T were investigated by differential thermal analysis (DTA). It was found that regardless of magnetism, the nucleation undercooling consistently increased with increasing the SMF intensity, though the melting temperatures of the three metals were hardly varied. The invariable melting temperature results from the negligible change of Gibbs free energy under the action of the SMF. The enhanced undercooling is mainly attributed to the increase of the contact angle for heterogeneous nucleation owing to the decrease in the melt/crucible interfacial free energy induced by the SMF. In addition, the reduction of the migration rates of liquid atoms due to the Lorenz force also plays an important role on the change in undercooling in the SMF. [ABSTRACT FROM AUTHOR]