scholarly journals Review of Automatic Microexpression Recognition in the Past Decade

2021 ◽  
Vol 3 (2) ◽  
pp. 414-434
Author(s):  
Liangfei Zhang ◽  
Ognjen Arandjelović
Keyword(s):  
Facial Expressions ◽  
Emotional State ◽  
Small Range ◽  
Regular Expressions ◽  
Data Sets ◽  
Comprehensive Overview ◽  
Psychological States ◽  
Facial Movements ◽  
The Past ◽  
Current State

Facial expressions provide important information concerning one’s emotional state. Unlike regular facial expressions, microexpressions are particular kinds of small quick facial movements, which generally last only 0.05 to 0.2 s. They reflect individuals’ subjective emotions and real psychological states more accurately than regular expressions which can be acted. However, the small range and short duration of facial movements when microexpressions happen make them challenging to recognize both by humans and machines alike. In the past decade, automatic microexpression recognition has attracted the attention of researchers in psychology, computer science, and security, amongst others. In addition, a number of specialized microexpression databases have been collected and made publicly available. The purpose of this article is to provide a comprehensive overview of the current state of the art automatic facial microexpression recognition work. To be specific, the features and learning methods used in automatic microexpression recognition, the existing microexpression data sets, the major outstanding challenges, and possible future development directions are all discussed.

scholarly journals Web Application for Emotion-based Music Player

2021 ◽  
Vol 9 (12) ◽  
pp. 11-14
Author(s):  
Kamal Naina Soni
Keyword(s):  
Computer Vision ◽  
Human Brain ◽  
Facial Expressions ◽  
Web Application ◽  
Emotional State ◽  
Current State ◽  
The Face ◽  
Current Mood ◽  
The Individual ◽  
Music Player

Abstract: Human expressions play an important role in the extraction of an individual's emotional state. It helps in determining the current state and mood of an individual, extracting and understanding the emotion that an individual has based on various features of the face such as eyes, cheeks, forehead, or even through the curve of the smile. A survey confirmed that people use Music as a form of expression. They often relate to a particular piece of music according to their emotions. Considering these aspects of how music impacts a part of the human brain and body, our project will deal with extracting the user’s facial expressions and features to determine the current mood of the user. Once the emotion is detected, a playlist of songs suitable to the mood of the user will be presented to the user. This can be a big help to alleviate the mood or simply calm the individual and can also get quicker song according to the mood, saving time from looking up different songs and parallel developing a software that can be used anywhere with the help of providing the functionality of playing music according to the emotion detected. Keywords: Music, Emotion recognition, Categorization, Recommendations, Computer vision, Camera

Identification of Facial Expressions using Deep Neural Networks

2020 ◽  
pp. 22-30
Author(s):  
Harsh .. ◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Facial Expressions ◽  
Deep Neural Networks ◽  
Good Accuracy ◽  
Data Sets ◽  
Learning Method ◽  
Complex Environments ◽  
Facial Movements ◽  
Modern Methods ◽  
Deep Layers ◽  
The Given

Detecting and analyzing emotions from human facial movements is a problem defined and developed over many years for the benefits it brings. During playback when developing data sets, data sets with methods become more and more complex and accuracy and difficulty increase gradually. In the given paper, we will use a deep structured learned network using the two mechanisms - Vgg and Resnet50 with deep layers to classify emotions based on input images in complex environments, besides that we also use learning methods combining many modern models to increase accuracy. Experimental results show that the two proposed methods have better results than some modern methods in emotional recognition problems for complex input images and some results reported in scientific studies. Particularly combined learning method gives good accuracy - 66.15% on the dataset FER2013

scholarly journals Hierarchially Distributed Data Matrix Scheme for Big Data Processing

2019 ◽  
Vol 8 (12) ◽  
pp. 4161-4165
Keyword(s):  
Big Data ◽  
Data Stream ◽  
Data Matrix ◽  
Data Sets ◽  
Distributed Data ◽  
Data Dependency ◽  
The Past ◽  
Current State ◽  
Matrix Scheme ◽  
Consequent Improvement

MapReduce is a programming paradigm and an affiliated Design for processing and making substantial data sets. It operates on a large cluster of specialty machines and is extremely scalable Across the past years, MapReduce and Spark have been offered to facilitate the job of generating big data programs and utilization. However, the tasks in these structures are roughly described and packaged as executable jars externally any functionality being presented or represented. This means that extended roles are not natively composable and reusable for consequent improvement. Moreover, it also impedes the capacity for employing optimizations on the data stream of job orders and pipelines. In this article, we offer the Hierarchically Distributed Data Matrix (HDM), which is a practical, strongly-typed data description for writing composable big data appeals. Along with HDM, a runtime composition is presented to verify the performance of HDM applications on dispersed infrastructures. Based on the practical data dependency graph of HDM, various optimizations are employed to develop the appearance of performing HDM jobs. The empirical outcomes show that our optimizations can deliver increases of between 10% to 60% of the Job-Completion-Time for various types of applications when associated with the current state of the art, Apache Spark.

scholarly journals Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight

2021 ◽  
Vol 9 ◽  
Author(s):  
Dongchuan Yang ◽  
Ju-e Guo ◽  
Jie Li ◽  
Shouyang Wang ◽  
Shaolong Sun
Keyword(s):  
Power Systems ◽  
Demand Forecasting ◽  
Cooperative Networks ◽  
Electricity Demand ◽  
Knowledge Mapping ◽  
Comprehensive Overview ◽  
The Past ◽  
Electricity Demand Forecasting ◽  
Current State ◽  
Emerging Trends

Electricity demand forecasting plays a fundamental role in the operation and planning procedures of power systems, and the publications related to electricity demand forecasting have attracted more and more attention in the past few years. To have a better understanding of the knowledge structure in the field of electricity demand forecasting, we applied scientometric methods to analyze the current state and the emerging trends based on the 831 publications from the Web of Science Core Collection during the past 20 years (1999–2018). Employing statistical description analysis, cooperative network analysis, keyword co-occurrence analysis, co-citation analysis, cluster analysis, and emerging trend analysis techniques, this study gives a comprehensive overview of the most critical countries, institutions, journals, authors, and publications in this field, cooperative networks relationships, research hotspots, and emerging trends. The results can provide meaningful guidance and helpful insights for researchers to enhance the understanding of crucial research, emerging trends, and new developments in electricity demand forecasting.

scholarly journals Analysis of Micro Facial Expression by Machine and Deep Learning Methods: Haar, CNN, and RNN

2021 ◽  
Vol 16 (1) ◽  
pp. 95-101
Author(s):  
Dibakar Raj Pant ◽  
Rolisha Sthapit
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Facial Expression ◽  
Facial Expressions ◽  
Recurrent Neural Network ◽  
Test Accuracy ◽  
Data Sets ◽  
Learning Methods ◽  
Facial Movements ◽  
Casme Ii

Facial expressions are due to the actions of the facial muscles located at different facial regions. These expressions are two types: Macro and Micro expressions. The second one is more important in computer vision. Analysis of micro expressions categorized by disgust, happiness, anger, sadness, surprise, contempt, and fear are challenging because of very fast and subtle facial movements. This article presents one machine learning method: Haar and two deep learning methods: Convolution Neural Network (CNN) and Recurrent Neural Network (RNN) to perform recognition of micro-facial expression analysis. First, Haar Cascade Classifier is used to detect the face as a pre-image-processing step. Secondly, those detected faces are passed through series of Convolutional Neural Network (CNN) layers for the features extraction. Thirdly, the Recurrent Neural Network (RNN) classifies micro facial expressions. Two types of data sets are used for training and testing of the proposed method: Chinese Academy of Sciences Micro-Expression II (CSAME II) and Spontaneous Actions and Micro-Movements (SAMM) database. The test accuracy of SAMM and CASME II are obtained as 84.76%, and 87% respectively. In addition, the distinction between micro facial expressions and non- micro facial expressions are analyzed by the ROC curve.

Current state and main directions of preservation and strengthening of health of the working population of Russia

2020 ◽  
pp. 527-532 ◽  
Author(s):  
I. V. Bukhtiyarov
Keyword(s):  
Working Conditions ◽  
Russian Federation ◽  
Production Environment ◽  
Working Population ◽  
Industrial Enterprises ◽  
The Past ◽  
Production Factors ◽  
Current State ◽  
The Russian Federation

The article presents the results of the analysis of health, working conditions and prevalence of adverse production factors, the structure of the detected occupational pathology in the working population of the Russian Federation. The article presents Statistical data on the dynamics of the share of workplaces of industrial enterprises that do not meet hygienic standards, occupational morbidity in 2015-2018 for the main groups of adverse factors of the production environment and the labor process. The indicators of occupational morbidity over the past 6 years in the context of the main types of economic activity, individual subjects of the Russian Federation, classes of working conditions, levels of specialized occupational health care. The role of the research Institute of occupational pathology and occupational pathology centers in solving organizational, methodological and practical tasks for the detection, treatment, rehabilitation and prevention of occupational diseases is shown. The basic directions of activity in the field of preservation and strengthening of health of workers, and also safety at a workplace are defined.

Phytochemical and Pharmacological Review on Two Herbs of Baijiangcao: Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss

2020 ◽  
Vol 17 (5) ◽  
pp. 496-517
Author(s):  
Yangcheng Liu ◽  
Wei Liu ◽  
Jiaqi Wang ◽  
Yang Liu ◽  
Changlan Chen ◽  
...  
Keyword(s):  
Chemical Constituents ◽  
Volatile Components ◽  
Research Papers ◽  
Pharmacological Activities ◽  
Comprehensive Review ◽  
Scientific Databases ◽  
The Past ◽  
Current State ◽  
Patrinia Scabiosaefolia ◽  
Antiviral Activities

Patrinia scabiosaefolia Fisch. Trev. and Patrinia villosa (Thunb.) Juss, are two species of Patrinia recorded in the Chinese Pharmacopoeia with the same Chinese name “Baijiangcao” and similar therapeutic effect in traditional Chinese medicine. The present article is the first comprehensive review on the chemical composition and pharmacological activities of these herbs. In this review, data on chemical constituents and pharmacological profile of the two herbs are provided. This review discusses all the classes of the 223 compounds (phenylpropanoids, flavonoids, terpenes, saponins and volatile components, etc.) detected in the two herbs providing information on the current state of knowledge of the phytochemicals present in them. In the past three years, our research group has isolated and identified about more than 100 ingredients from the two herbs. Therefore, we published a systematic review of our research papers and studies on the two herbs were carried out using resources such as classic books about Chinese herbal medicine and scientific databases including Pubmed, Web of Science, SciFinder, CNKI. etc. The present review discusses the most thoroughly studied pharmacological activities (antioxidant, anti-inflammatory, immunomodulatory, antimicrobial, antitumor and antiviral activities) of the two herbs. This comprehensive review will be informative for scientists searching for new properties of these herbs and will be important and significant for the discovery of bioactive compounds from the two herbs and in complete utilization of Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss.

Movie Envy

2019 ◽  
pp. 70-80
Author(s):  
Olivier Asselin
Keyword(s):  
Point Of View ◽  
Digital Revolution ◽  
The Past ◽  
Current State ◽  
Movie Theatre ◽  
The Relationship

“Canadian cinema.” The term may appear self-evident but is problematic. First, one may question the value of national approaches to culture, especially here, in Quebec and Canada, where the debates over the Nation seem interminable, and especially now, in an era of globalization. Next, one may question the value of media-centered approaches to culture, especially when the successive waves of the “digital revolution” have blurred the boundaries between technologies and among artistic practices. Rather than try to survey “important” fiction films for theatres in Quebec or Canada, this essay adopts another point of view to examine the presence of cinema in Montreal museums over the past few years by focusing on three singular exhibitions. It may well be symptomatic of the current state of film in Quebec and Canada—but also, paradoxically, everywhere else—and says much about the relationship between medium and nation, the expansion of cinema beyond the movie theatre, and the internationalization of culture.

scholarly journals Augmented Reality in Orthopedic Surgery Is Emerging from Proof of Concept Towards Clinical Studies: a Literature Review Explaining the Technology and Current State of the Art

2021 ◽  
Author(s):  
Fabio A. Casari ◽  
Nassir Navab ◽  
Laura A. Hruby ◽  
Philipp Kriechling ◽  
Ricardo Nakamura ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Orthopedic Surgery ◽  
Relevant Literature ◽  
Comprehensive Overview ◽  
Basic Principles ◽  
Clinical Procedures ◽  
Current State ◽  
Tremendous Progress ◽  
Orthopedic Oncology ◽  
Technological Developments

Abstract Purpose of Review Augmented reality (AR) is becoming increasingly popular in modern-day medicine. Computer-driven tools are progressively integrated into clinical and surgical procedures. The purpose of this review was to provide a comprehensive overview of the current technology and its challenges based on recent literature mainly focusing on clinical, cadaver, and innovative sawbone studies in the field of orthopedic surgery. The most relevant literature was selected according to clinical and innovational relevance and is summarized. Recent Findings Augmented reality applications in orthopedic surgery are increasingly reported. In this review, we summarize basic principles of AR including data preparation, visualization, and registration/tracking and present recently published clinical applications in the area of spine, osteotomies, arthroplasty, trauma, and orthopedic oncology. Higher accuracy in surgical execution, reduction of radiation exposure, and decreased surgery time are major findings presented in the literature. Summary In light of the tremendous progress of technological developments in modern-day medicine and emerging numbers of research groups working on the implementation of AR in routine clinical procedures, we expect the AR technology soon to be implemented as standard devices in orthopedic surgery.

scholarly journals Depression following traumatic brain injury: a comprehensive overview

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Marc Fakhoury ◽  
Zaynab Shakkour ◽  
Firas Kobeissy ◽  
Nada Lawand
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Health Concern ◽  
First Year ◽  
Comprehensive Overview ◽  
Symptoms Of Depression ◽  
Current State ◽  
Post Traumatic ◽  
Brain Changes

Abstract Traumatic brain injury (TBI) represents a major health concern affecting the neuropsychological health; TBI is accompanied by drastic long-term adverse complications that can influence many aspects of the life of affected individuals. A substantial number of studies have shown that mood disorders, particularly depression, are the most frequent complications encountered in individuals with TBI. Post-traumatic depression (P-TD) is present in approximately 30% of individuals with TBI, with the majority of individuals experiencing symptoms of depression during the first year following head injury. To date, the mechanisms of P-TD are far from being fully understood, and effective treatments that completely halt this condition are still lacking. The aim of this review is to outline the current state of knowledge on the prevalence and risk factors of P-TD, to discuss the accompanying brain changes at the anatomical, molecular and functional levels, and to discuss current approaches used for the treatment of P-TD.

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