Efficiently classify synthesized facial images generated by different synthesis methods

2021 ◽  
Author(s):  
Wei Li ◽  
Peng Qiao ◽  
Yong Dou
Keyword(s):  
Synthesis Methods ◽  
Facial Images

Hotspots in Psychology – 2020 Edition

2020 ◽  
Vol 228 (1) ◽  
pp. 1-2
Author(s):  
Michael Bošnjak ◽  
Nadine Wedderhoff
Keyword(s):  
Systematic Reviews ◽  
Research Synthesis ◽  
Synthesis Methods ◽  
Common Denominator ◽  
The Common ◽  
Meta Analyses

Abstract. This editorial gives a brief introduction to the six articles included in the fourth “Hotspots in Psychology” of the Zeitschrift für Psychologie. The format is devoted to systematic reviews and meta-analyses in research-active fields that have generated a considerable number of primary studies. The common denominator is the research synthesis nature of the included articles, and not a specific psychological topic or theme that all articles have to address. Moreover, methodological advances in research synthesis methods relevant for any subfield of psychology are being addressed. Comprehensive supplemental material to the articles can be found in PsychArchives ( https://www.psycharchives.org ).

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Effects of Wet Chemical Oxidation on Surface Functionalization and Morphology of Highly Oriented Pyrolytic Graphite

2020 ◽  
Author(s):  
Mikhail Trought ◽  
Isobel Wentworth ◽  
Timothy Leftwich ◽  
Kathryn Perrine
Keyword(s):  
Surface Functionalization ◽  
Functional Group ◽  
Pyrolytic Graphite ◽  
Surface Oxidation ◽  
Chemical Oxidation ◽  
Synthesis Methods ◽  
Acid Solutions ◽  
Highly Oriented Pyrolytic Graphite ◽  
Wet Chemical ◽  
Surface Morphologies

The knowledge of chemical functionalization for area selective deposition (ASD) is crucial for designing the next generation heterogeneous catalysis. Surface functionalization by oxidation was studied on the surface of highly oriented pyrolytic graphite (HOPG). The HOPG surface was exposed to with various concentrations of two different acids (HCl and HNO3). We show that exposure of the HOPG surface to the acid solutions produce primarily the same -OH functional group and also significant differences the surface topography. Mechanisms are suggested to explain these strikingly different surface morphologies after surface oxidation. This knowledge can be used to for ASD synthesis methods for future graphene-based technologies.

Expectations about pain and analgesic treatment depend on medical providers’ facial appearances

2020 ◽  
Author(s):  
Elizabeth A. Necka ◽  
Carolyn Amir ◽  
Troy C. Dildine ◽  
Lauren Yvette Atlas
Keyword(s):  
Patient Outcomes ◽  
Visual Information ◽  
Healthcare Providers ◽  
Medical Procedures ◽  
Medical Providers ◽  
Analgesic Treatment ◽  
Digital Services ◽  
Receive Treatment ◽  
Facial Images ◽  
Trait Impressions

There is a robust link between patients’ expectations and clinical outcomes, as evidenced by the placebo effect. These expectations are shaped by the context surrounding treatment, including the patient-provider interaction. Prior work indicates that the provider’s behavior and characteristics, including warmth and competence, can shape patient outcomes. Yet humans rapidly form trait impressions of others prior to any in-person interaction. Here, we tested whether trait-impressions of hypothetical medical providers, based purely on facial images, influence participants’ choice of medical providers and expectations about their health following hypothetical medical procedures performed by those providers in a series of vignettes. Across five studies, participants selected providers who appeared more competent, based on facial visual information alone. Further, providers’ apparent competence predicted participants’ expectations about post-procedural pain and medication use. Participants’ perception of their similarity to providers also shaped expectations about pain and treatment outcomes. Our results suggest that humans develop expectations about their health outcomes prior to even setting foot in the clinic, based exclusively on first impressions. These findings have strong implications for health care, as individuals increasingly rely on digital services to choose healthcare providers, schedule appointments, and even receive treatment and care, a trend which is exacerbated as the world embraces telemedicine.

Nested code sequences of Barker — Mersenne — Raghavarao

2019 ◽  
pp. 71-81
Author(s):  
M. B. Sergeev ◽  
V. A. Nenashev ◽  
A. M. Sergeev
Keyword(s):  
Data Transfer ◽  
Radio Channel ◽  
Main Peak ◽  
Synthesis Methods ◽  
Orthogonal Matrices ◽  
Useful Signal ◽  
New Codes ◽  
Increase In Accuracy ◽  
Application Fields ◽  
Barker Codes

Introduction: The problem of noise-free encoding for an open radio channel is of great importance for data transfer. The results presented in this paper are aimed at stimulating scientific interest in new codes and bases derived from quasi-orthogonal matrices, as a basis for the revision of signal processing algorithms.Purpose: Search for new code sequences as combinations of codes formed from the rows of Mersenne and Raghavarao quasi-orthogonal matrices, as well as complex and more efficient Barker — Mersenne — Raghavarao codes.Results: We studied nested code sequences derived from the rows of quasi-orthogonal cyclic matrices of Mersenne, Raghavarao and Hadamard, providing estimates for the characteristics of the autocorrelation function of nested Barker, Mersenne and Raghavarao codes, and their combinations: in particular, the ratio between the main peak and the maximum positive and negative “side lobes”. We have synthesized new codes, including nested ones, formed on the basis of quasi-orthogonal matrices with better characteristics than the known Barker codes and their nested constructions. The results are significant, as this research influences the establishment and development of methods for isolation, detection and processing of useful information. The results of the work have a long aftermath because new original code synthesis methods need to be studied, modified, generalized and expanded for new application fields.Practical relevance: The practical application of the obtained results guarantees an increase in accuracy of location systems, and detection of a useful signal in noisy background. In particular, these results can be used in radar systems with high distance resolution, when detecting physical objects, including hidden ones.

Metallic Nanoparticle Synthesis by Green Chemistry

2018 ◽  
Vol 11 (6) ◽  
pp. 4287-4294
Author(s):  
Anikate Sood ◽  
Shweta Agarwal
Keyword(s):  
Green Chemistry ◽  
Green Synthesis ◽  
Biomedical Research ◽  
Metallic Nanoparticles ◽  
Nanoparticle Synthesis ◽  
Synthesis Methods ◽  
Metallic Nanoparticle ◽  
Medical Field ◽  
Advantages And Disadvantages ◽  
Gold Silver

Nanotechnology is the most sought field in biomedical research. Metallic nanoparticles have wide applications in the medical field and have gained the attention of various researchers for advanced research for their application in pharmaceutical field. A variety of metallic nanoparticles like gold, silver, platinum, palladium, copper and zinc have been developed so far. There are different methods to synthesize metallic nanoparticles like chemical, physical, and green synthesis methods. Chemical and physical approaches suffer from certain drawbacks whereas green synthesis is emerging as a nontoxic and eco-friendly approach in production of metallic nanoparticles. Green synthesis is further divided into different approaches like synthesis via bacteria, fungi, algae, and plants. These approaches have their own advantages and disadvantages. In this article, we have described various metallic nanoparticles, different modes of green synthesis and brief description about different metabolites present in plant that act as reducing agents in green synthesis of metallic nanoparticles. 

SYNTHESIS METHODS OF OPTIMAL DISCRETE CORRECTIVE FUNCTIONS

2020 ◽  
Vol 9 (9) ◽  
pp. 6467-6482
Author(s):  
A.V Kabulov ◽  
E. Urunbaev ◽  
I. Normatov ◽  
A. Ashurov
Keyword(s):  
Synthesis Methods
Sign in / Sign up

Export Citation Format

Share Document