Results 41 to 50 of about 1,603 (207)

Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches

Advanced Physics Research, EarlyView.
Two methods for the optimization of chiral reflection by a metamaterial made of either GaP/Air or PMMA/Air interfaces are compared, showing approaches towards fast design exploration and high‐performance results: a neural‐network pipeline and a genetic algorithm. The structures considered are characterized by a periodic, chiral texturation with a shape
Davide Filippozzi, Alexandre Mayer, Nicolas Roy, Wei Fang, Arash Rahimi‐Iman   +4 more
wiley   +1 more source

Clean Kinematic Samples in Dwarf Spheroidals: An Algorithm for Evaluating Membership and Estimating Distribution Parameters When Contamination is Present

, 2008
(abridged) We develop an algorithm for estimating parameters of a distribution sampled with contamination, employing a statistical technique known as ``expectation maximization'' (EM).
Bell ., Belokurov ., Bodhisattva Sen, Cayrel, Dempster, den Hartog, Edward W. Olszewski, Gilbert, Irwin, Koch, Mario Mateo, Mateo, Matthew G. Walker, Michael Woodroofe, Muñoz ., Robertson, Sen, Simon, Walker, Walker   +19 more
core   +1 more source

Immunoinformatics‐Based Design of a Multi‐Epitope Vaccine Targeting a Conserved Copper–Associated Protein in Neisseria gonorrhoeae

Biotechnology and Applied Biochemistry, EarlyView.
ABSTRACT Neisseria gonorrhoeae poses an urgent public health challenge due to rapidly increasing antimicrobial resistance and the absence of an effective vaccine. Targeting conserved bacterial pathways involved in essential physiological processes may provide new opportunities for vaccine antigen discovery.
Sinethemba H. Yakobi, Uchechukwu U. Nwodo   +1 more
wiley   +1 more source

Efficient regularized isotonic regression with application to gene--gene interaction search

, 2012
Isotonic regression is a nonparametric approach for fitting monotonic models to data that has been widely studied from both theoretical and practical perspectives.
Luss, Ronny, Rosset, Saharon, Shahar, Moni   +2 more
core   +1 more source

Sailing From Penalties to Accountability: Business Strategies and Governance for Firms to Innovate After Environmental Misconduct

Business Strategy and the Environment, EarlyView.
ABSTRACT Firms' continuous pursuit of making a profit in the competitive market may ignore the actions related to environmental responsibilities. This set of actions for financial gains constitutes environmental misconduct, which not only harms ecosystems and communities but also brings reputational damage. Negative press and social media amplification
Ashutosh Singh, Salwa Saleh Almasabi, Ajay Kumar Patel, Priyanka Malik   +3 more
wiley   +1 more source

Optimized Risk Assessment in Forensic Practice: A Comparison of Machine Learning and Manual Scoring Approaches

Behavioral Sciences &the Law, EarlyView.
ABSTRACT As correctional jurisdictions and risk instrument developers look to optimize scoring for specific population needs, an open question remains ‐ which method is optimal. Popular scoring methods range from manual simple scoring approaches (e.g., Burgess) to more complex machine learning algorithms (e.g., random forests).
Danielle J. Rieger, Ralph C. Serin, Shelley L. Brown   +2 more
wiley   +1 more source

Measuring Consumer Aversion Toward AI in Marketing Communication and Assessing Its Relationship to Brand Perceptions and Purchase Intention

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Some consumers exhibit aversion toward artificial intelligence (AI), particularly when it is embedded in persuasive marketing communication (MarCom). Here, we developed and validated a measure of consumer aversion to AI in MarCom and examined its downstream consequences for brand perceptions and purchase intention.
Louvins Pierre, Viviana Carolina Zambrano Rodriguez, Jiayi (Joy) Wang   +2 more
wiley   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source

Convergence analysis of generalized iteratively reweighted least squares algorithms on convex function spaces [PDF]

The computation of robust regression estimates often relies on minimization of a convex functional on a convex set. In this paper we discuss a general technique for a large class of convex functionals to compute the minimizers iteratively which is ...
Bissantz, Nicolai, Dümbgen, Lutz, Munk, Axel, Stratmann, Bernd   +3 more
core  

Non‐negative Gaussian estimation of variance components in random effects models

Canadian Journal of Statistics, EarlyView.
Abstract When used to estimate variance components (VCs), confidence intervals (CIs) can be truncated at zero, have a point estimate not in the quoted CI, be empty with positive probability, or be all‐inclusive. This is because they have conflicting dual roles, since they are considered to cover the parameter with a specified probability while also ...
André Plante, Michael Plante
wiley   +1 more source