Relabelling Algorithms for Large Dataset Mixture Models

Mixture models are flexible tools in density estimation and classification problems. Bayesian estimation of such models typically relies on sampling from the posterior distribution using Markov chain Monte Carlo. Label switching arises because the posterior is invariant to permutations of the component parameters. Methods for dealing with label switching have been studied fairly extensively in the literature, with the most popular approaches being those based on loss functions. However, many of these algorithms turn out to be too slow in practice, and can be infeasible as the size and dimension of the data grow. In this article, we review earlier solutions which can scale up well for large data sets, and compare their performances on simulated and real datasets. In addition, we propose a new, and computationally efficient algorithm based on a loss function interpretation, and show that it can scale up well in larger problems. We conclude with some discussions and recommendations of all the methods studied

Study of Application of the Bored Pile Technology in Building Construction

Bored piles involve making pile holes in the site needing pile by mechanical drilling methods and other methods, then placing the pile made of reinforcing cage and pouring concrete inside the holes. Bored piles have smaller vibration and noise compared to sinking pile by hammer method, and are suitable for all kinds of foundations, thus getting the favour of construction enterprises in recent years and is widely used in construction engineering. However, during the process of borehole piling, the bearing capacity of the pile was severely affected by the quality of construction and it is difficult to control the quality of concrete. Hence, bored pile technology is very important. This study will mainly discuss bored pile technology in building construction

Conception, synthèse et caractérisation d'un nouveau matériau multi-stimuli-responsive à base de spiropyranne

Ce mémoire de maîtrise porte sur la conception et la synthèse de monomères polymérisables en vue d’obtenir des macromolécules sensibles à plusieurs stimulations externes : 1) la lumière, 2) le pH (ou le CO[indice inférieur 2]) et 3) l’oxydo-réduction

Determinants of the competitive advantage of dairy supply chains: Evidence from the Chinese dairy industry

In this study, we use an evidence-based approach to examine the factors that determine the competitive advantage of dairy supply chains using evidence from the Chinese dairy industry. We focus on the quality assurance of dairy products, which is considered one of the fundamental influential factors. We investigate interrelationships among the identified determinants, which include dairy production behavior, dairy cow culture model, government regulations, corporate social responsibility, and quality assurance, and examine how these determinants influence the competitive advantage of dairy supply chains. We employ the structural equation modeling approach in which grouped observable variables that represent the identified determinants are extrapolated from primary data collected through a questionnaire survey. Our key findings show that by mediating the effects of dairy production behavior and the dairy cow culture model, government regulation and corporate social responsibility significantly affect the quality assurance of dairy products. In turn, dairy production behavior and the dairy cow culture model significantly affect the competitive advantage of the dairy supply chain via the fully mediated effects of the quality assurance of dairy products. Specifically, the dairy cow culture model helps ensure the safety and quality of milk supply, allowing core dairy firms to control product quality throughout the dairy supply chain. Our empirical study shows that the identified determinants interact to assure the quality of dairy products and enhance the competitive advantage of the dairy supply chain in China

Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation

Data sharing for medical research has been difficult as open-sourcing clinical data may violate patient privacy. Traditional methods for face de-identification wipe out facial information entirely, making it impossible to analyze facial behavior. Recent advancements on whole-body keypoints detection also rely on facial input to estimate body keypoints. Both facial and body keypoints are critical in some medical diagnoses, and keypoints invariability after de-identification is of great importance. Here, we propose a solution using deepfake technology, the face swapping technique. While this swapping method has been criticized for invading privacy and portraiture right, it could conversely protect privacy in medical video: patients' faces could be swapped to a proper target face and become unrecognizable. However, it remained an open question that to what extent the swapping de-identification method could affect the automatic detection of body keypoints. In this study, we apply deepfake technology to Parkinson's disease examination videos to de-identify subjects, and quantitatively show that: face-swapping as a de-identification approach is reliable, and it keeps the keypoints almost invariant, significantly better than traditional methods. This study proposes a pipeline for video de-identification and keypoint preservation, clearing up some ethical restrictions for medical data sharing. This work could make open-source high quality medical video datasets more feasible and promote future medical research that benefits our society.Comment: Accepted for publication at the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 202

Bis[4-(1-imino­eth­yl)-3-methyl-1-phenyl-1H-pyrazol-5-olato-κ2 O,N 4]copper(II)

In the title complex, [Cu(C12H12N3O)2], the CuII ion is tetra­coordinated by two N atoms and two O atoms from two bis-chelating 4-(1-imino­eth­yl)-3-methyl-1-phenyl-1H-pyrazol-5-olate ligands in a square-planar geometry. The two N atoms and two O atoms around the CuII atom are trans to each other, as the CuII atom lies on an inversion centre. The six-membered ring composed of the Cu, an O, an N and three C atoms of the ligand and the pyrazole ring is nearly planar, the largest deviation being 0.037 (4) Å for an N atom. In the crystal, weak inter­molecular C—H⋯N hydrogen-bonding inter­actions link the mol­ecules into chains along the c axis