Equilibrium problems on Riemannian manifolds with applications

We study the equilibrium problem on general Riemannian manifolds. The results on existence of solutions and on the convex structure of the solution set are established. Our approach consists in relating the equilibrium problem to a suitable variational inequality problem on Riemannian manifolds, and is completely different from previous ones on this topic in the literature. As applications, the corresponding results for the mixed variational inequality and the Nash equilibrium are obtained. Moreover, we formulate and analyze the convergence of the proximal point algorithm for the equilibrium problem. In particular, correct proofs are provided for the results claimed in J. Math. Anal. Appl. 388, 61-77, 2012 (i.e., Theorems 3.5 and 4.9 there) regarding the existence of the mixed variational inequality and the domain of the resolvent for the equilibrium problem on Hadamard manifolds.National Natural Science Foundation of ChinaNatural Science Foundation of Guizhou Province (China)Dirección General de Enseñanza SuperiorJunta de AndalucíaNational Science Council of Taiwa

Learning Deep Latent Spaces for Multi-Label Classification

Multi-label classification is a practical yet challenging task in machine learning related fields, since it requires the prediction of more than one label category for each input instance. We propose a novel deep neural networks (DNN) based model, Canonical Correlated AutoEncoder (C2AE), for solving this task. Aiming at better relating feature and label domain data for improved classification, we uniquely perform joint feature and label embedding by deriving a deep latent space, followed by the introduction of label-correlation sensitive loss function for recovering the predicted label outputs. Our C2AE is achieved by integrating the DNN architectures of canonical correlation analysis and autoencoder, which allows end-to-end learning and prediction with the ability to exploit label dependency. Moreover, our C2AE can be easily extended to address the learning problem with missing labels. Our experiments on multiple datasets with different scales confirm the effectiveness and robustness of our proposed method, which is shown to perform favorably against state-of-the-art methods for multi-label classification.Comment: published in AAAI-201

Proximal point algorithms on Hadamard manifolds: linear convergence and finite termination

In the present paper, we consider inexact proximal point algorithms for finding singular points of multivalued vector fields on Hadamard manifolds. The rate of convergence is shown to be linear under the mild assumption of metric subregularity. Furthermore, if the sequence of parameters associated with the iterative scheme converges to 0, then the convergence rate is superlinear. At the same time, the finite termination of the inexact proximal point algorithm is also provided under a weak sharp minima-like condition. Applications to optimization problems are provided. Some of our results are new even in Euclidean spaces, while others improve and/or extend some known results in Euclidean spaces. As a matter of fact, in the case of exact proximal point algorithm, our results improve the corresponding results in [G. C. Bento and J. X. Cruz Neto, Optim., 63 (2014), pp. 1281–1288]. Finally, several examples are provided to illustrate that our results are applicable while the corresponding results in the Hilbert space setting are not.National Natural Science Foundation of ChinaZhejiang Provincial Natural Science Foundation of ChinaDirección General de Enseñanza SuperiorJunta de AndalucíaNational Science Council of Taiwa

Realtime object extraction and tracking with an active camera using image mosaics

[[abstract]]Moving object extraction plays a key role in applications such as object-based videoconference, surveillance, and so on. The dimculties of moving object segmentation lie in the fact that physical objects are normally not homogeneous with to low-level features and it's usually tough to segment them accnrately and efficiently. Object segmentation based on prestored background information has proved to be effective and efficient in several applications such as videophone, video conferencing, and surveillance, etc. The previous works, however, were mainly concentrated on object segmentation with a static camera and in a stationary background. In this paper, we propose a robust and fast segmentation algorithm and a reliable tracking strategy without knowing the shape of the object in advance. The proposed system can real-time extract the foreground from the background and track the moving object with an active (pan-tilt) camera such that the moving object always stays around the center of images.[[fileno]]2030144030033[[department]]電機工程學

Association between health examination items and body mass index among school children in Hualien, Taiwan

BACKGROUND: To assess the prevalence of obesity and major physical examination items including dental caries, myopia, pinworm, hematuria, and proteinuria among school children in Hualien, Taiwan. In addition, the health status differences between gender, grader, levels of residence urbanization, and body mass index (BMI) were examined. METHODS: Cross-sectional studies with a total of 11,080 students (age, 7–14 years) in grades 1, 4, and 7 were evaluated for weight, height, routine physical examination, and urine analysis during the 2010 Student Health Examination in Hualien. Frequencies, Chi-square test, and logistic regression were conducted using SPSS. RESULTS: Of the 11,080 students evaluated, 1357 (12.2%) were overweight, and 1421 (12.8%) were obese. There were significant differences in overweight/obese prevalence by gender, by grader, and by levels of residence urbanization. Dental caries, myopia, and obesity were the most prevalent health problems among these students (75.6%, 33.0%, and 12.8%, respectively). In crude and adjusted analyses, research results showed that there were significant differences in the prevalence of major physical examination items between different gender, grader, levels of residence urbanization, and BMI groups. Girls had a higher prevalence of dental caries, myopia, and hematuria than boys (all p < 0.01), whereas boys had a higher prevalence of pinworm than girls (p = 0.02). Students in higher grades had significantly higher prevalence of myopia, hematuria, and proteinuria (all p < 0.01), whereas students in lower grades had higher prevalence of dental caries and pinworm (p < 0.01). Students with abnormal BMI had lower prevalence of pinworm (p < 0.01). Students residing in suburban and rural areas had higher prevalence of dental caries, pinworm, and hematuria (all p < 0.01), and lower prevalence of myopia than students residing in urban areas (all p < 0.01). CONCLUSION: Routine health examination provides an important way to detect students’ health problems. Our study elucidated major health problems among school children in Hualien, Taiwan. In addition, the results also indicated that the prevalence of health problems had a significant relationship with gender, grader, levels of residence urbanization, and BMI. It is suggested that school health interventions should consider students’ health profiles along with their risk factors status in planning

Dexamethasone Down-regulates Osteocalcin in Bone Cells through Leptin Pathway

Glucocorticoid therapy, especially at higher doses, is associated with significantadverse side effects including osteoporosis. Leptin, secreted from adipose tissue, has diverse effects on bone tissue regulation. As glucocorticoids stimulate leptin synthesis and secretion directly in adipose tissue we hypothesised that dexamethasone (DEX) induced osteoporosis may, in part, be mediated by an osteoblast dependent leptin-leptin receptor pathway. Human bone cells expressed leptin and leptin receptors (Ob-Ra and Ob-Rb). DEX increased leptin, Ob-Ra and Ob-Rb expression in a dose-dependent manner while decreasing expression of osteocalcin. In the presence of leptin, Cbfa1 and osteonectin expression showed no significant change, whereas osteocalcin expression was decreased. Recombinant human quadruple antagonist leptin suppressed DEX-induced osteocalcin downregulation. The signaling pathway involved up-regulation of JAK2. In conclusion, upregulation of leptin and Ob-Rb in human bone cells by DEX is associated with own-regulation of osteocalcin expression. The down regulation of osteocalcin by DEX was partially through a leptin autocrine/paracrine loop. Adverse effects of DEX on the skeleton may be modified by targeting leptin signaling pathways