scholarly journals Global-local attention for emotion recognition

2021 ◽  
Author(s):  
Nhat Le ◽  
Khanh Nguyen ◽  
Anh Nguyen ◽  
Bac Le
Keyword(s):  
Emotion Recognition ◽  
State Of The Art ◽  
Contextual Information ◽  
Research Area ◽  
The Past ◽  
Current State ◽  
Substantial Progress ◽  
Human Emotions ◽  
Active Research ◽  
Active Research Area

AbstractHuman emotion recognition is an active research area in artificial intelligence and has made substantial progress over the past few years. Many recent works mainly focus on facial regions to infer human affection, while the surrounding context information is not effectively utilized. In this paper, we proposed a new deep network to effectively recognize human emotions using a novel global-local attention mechanism. Our network is designed to extract features from both facial and context regions independently, then learn them together using the attention module. In this way, both the facial and contextual information is used to infer human emotions, therefore enhancing the discrimination of the classifier. The intensive experiments show that our method surpasses the current state-of-the-art methods on recent emotion datasets by a fair margin. Qualitatively, our global-local attention module can extract more meaningful attention maps than previous methods. The source code and trained model of our network are available at https://github.com/minhnhatvt/glamor-net.

scholarly journals Gaussian Transformer: A Lightweight Approach for Natural Language Inference

2019 ◽  
Vol 33 ◽  
pp. 6489-6496 ◽  
Author(s):  
Maosheng Guo ◽  
Yu Zhang ◽  
Ting Liu
Keyword(s):  
Neural Networks ◽  
Natural Language ◽  
State Of The Art ◽  
Research Area ◽  
High Order Interaction ◽  
Training Time ◽  
Attention Networks ◽  
Local Dependency ◽  
Active Research ◽  
Active Research Area

Natural Language Inference (NLI) is an active research area, where numerous approaches based on recurrent neural networks (RNNs), convolutional neural networks (CNNs), and self-attention networks (SANs) has been proposed. Although obtaining impressive performance, previous recurrent approaches are hard to train in parallel; convolutional models tend to cost more parameters, while self-attention networks are not good at capturing local dependency of texts. To address this problem, we introduce a Gaussian prior to selfattention mechanism, for better modeling the local structure of sentences. Then we propose an efficient RNN/CNN-free architecture named Gaussian Transformer for NLI, which consists of encoding blocks modeling both local and global dependency, high-order interaction blocks collecting the evidence of multi-step inference, and a lightweight comparison block saving lots of parameters. Experiments show that our model achieves new state-of-the-art performance on both SNLI and MultiNLI benchmarks with significantly fewer parameters and considerably less training time. Besides, evaluation using the Hard NLI datasets demonstrates that our approach is less affected by the undesirable annotation artifacts.

A Study on the WAN Network Traffic Monitoring

2014 ◽  
Vol 556-562 ◽  
pp. 6419-6422
Author(s):  
Hao Li Ren ◽  
Xiao Peng Liang ◽  
Kong Yang Peng
Keyword(s):  
Anomaly Detection ◽  
Network Traffic ◽  
Traffic Monitoring ◽  
Research Area ◽  
Network Services ◽  
The Past ◽  
Monitoring Tools ◽  
Network Traffic Monitoring ◽  
Active Research ◽  
Active Research Area

Network traffic monitoring, analysis, and anomaly detection have become a very active research area in the networking community over the past few years. Traffic monitoring and analysis is essential in order to more effectively troubleshoot and resolve issues when they occur, so as to not bring network services to a stand still for extended periods of time. This paper discusses router based monitoring techniques in the WAN traffic monitoring. It gives an overview of the two most widely used router based network monitoring tools available (SNMP, cisco netflow), and provides an example about the netflow technology.

Organocatalysed Synthesis of Selenium Containing Scaffolds

2020 ◽  
Vol 07 ◽  
Author(s):  
Amol D. Sonawane ◽  
Mamoru Koketsu
Keyword(s):  
Transition Metal ◽  
Asymmetric Catalysis ◽  
Research Area ◽  
Biological Properties ◽  
Organoselenium Compounds ◽  
The Past ◽  
Organic Chemist ◽  
Active Research ◽  
Active Research Area ◽  
Diaryl Selenide

: The synthesis of organoselenium compounds continues to be a very active research area, due to their distinct chemical, physical and biological properties. Selenium-based methods have developed rapidly over the past few years and organoselenium chemistry has become a very powerful tool in the hands of organic chemist. This review describes the synthesis of organocatalysed bioactive selenium scaffolds especially including transition metal-catalysed diaryl selenide synthesis, Cu-catalysed selenium scaffolds, Pd-catalysed selenium scaffolds, asymmetric catalysis, Nickel catalysed selenium scaffolds and Rh-catalysed selenium scaffolds.

Machine Translation

2016 ◽  
Author(s):  
Lucia Specia ◽  
Yorick Wilks
Keyword(s):  
Machine Translation ◽  
Language Processing ◽  
State Of The Art ◽  
Research Area ◽  
Rule Based ◽  
Active Research ◽  
Translation Methods ◽  
The Cost ◽  
Translation Systems ◽  
Active Research Area

Machine Translation (MT) is and always has been a core application in the field of natural-language processing. It is a very active research area and it has been attracting significant commercial interest, most of which has been driven by the deployment of corpus-based, statistical approaches, which can be built in a much shorter time and at a fraction of the cost of traditional, rule-based approaches, and yet produce translations of comparable or superior quality. This chapter aims at introducing MT and its main approaches. It provides a historical overview of the field, an introduction to different translation methods, both rationalist (rule-based) and empirical, and a more in depth description of state-of-the-art statistical methods. Finally, it covers popular metrics to evaluate the output of machine translation systems.

A Person-Centered Design Framework for Serious Games for Dementia

2020 ◽  
Vol 64 (1) ◽  
pp. 18-22
Author(s):  
Bella Yigong Zhang ◽  
Mark Chignell
Keyword(s):  
Theoretical Basis ◽  
Serious Games ◽  
Aging Population ◽  
Research Area ◽  
Design Framework ◽  
Strategic Design ◽  
Health And Wellbeing ◽  
Initial Design ◽  
Active Research ◽  
Active Research Area

With the rapidly aging population and the rising number of people living with dementia (PLWD), there is an urgent need for programming and activities that can promote the health and wellbeing of PLWD. Due to staffing and budgetary constraints, there is considerable interest in using technology to support this effort. Serious games for dementia have become a very active research area. However, much of the work is being done without a strong theoretical basis. We incorporate a Montessori approach with highly tactile interactions. We have developed a person-centered design framework for serious games for dementia with initial design recommendations. This framework has the potential to facilitate future strategic design and development in the field of serious games for dementia.

scholarly journals Digitization and Visualization of Folk Dances in Cultural Heritage: A Review

Inventions ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 72 ◽  
Author(s):  
Iris Kico ◽  
Nikos Grammalidis ◽  
Yiannis Christidis ◽  
Fotis Liarokapis
Keyword(s):  
Performance Evaluation ◽  
Cultural Heritage ◽  
Computer Science ◽  
Learning Process ◽  
Research Area ◽  
Active Research ◽  
Active Research Area

According to UNESCO, cultural heritage does not only include monuments and collections of objects, but also contains traditions or living expressions inherited from our ancestors and passed to our descendants. Folk dances represent part of cultural heritage and their preservation for the next generations appears of major importance. Digitization and visualization of folk dances form an increasingly active research area in computer science. In parallel to the rapidly advancing technologies, new ways for learning folk dances are explored, making the digitization and visualization of assorted folk dances for learning purposes using different equipment possible. Along with challenges and limitations, solutions that can assist the learning process and provide the user with meaningful feedback are proposed. In this paper, an overview of the techniques used for the recording of dance moves is presented. The different ways of visualization and giving the feedback to the user are reviewed as well as ways of performance evaluation. This paper reviews advances in digitization and visualization of folk dances from 2000 to 2018.

scholarly journals Multifaceted origins of sex differences in the brain

2016 ◽  
Vol 371 (1688) ◽  
pp. 20150106 ◽  
Author(s):  
Margaret M. McCarthy
Keyword(s):  
Sex Differences ◽  
State Of The Art ◽  
Human Subjects ◽  
Special Issue ◽  
Molecular Analyses ◽  
The Past ◽  
Current State ◽  
Biological Variable ◽  
Males And Females ◽  
The Brain

Studies of sex differences in the brain range from reductionistic cell and molecular analyses in animal models to functional imaging in awake human subjects, with many other levels in between. Interpretations and conclusions about the importance of particular differences often vary with differing levels of analyses and can lead to discord and dissent. In the past two decades, the range of neurobiological, psychological and psychiatric endpoints found to differ between males and females has expanded beyond reproduction into every aspect of the healthy and diseased brain, and thereby demands our attention. A greater understanding of all aspects of neural functioning will only be achieved by incorporating sex as a biological variable. The goal of this review is to highlight the current state of the art of the discipline of sex differences research with an emphasis on the brain and to contextualize the articles appearing in the accompanying special issue.

scholarly journals Enhancing Big Data Auditing

2018 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Sara Alomari ◽  
Mona Alghamdi ◽  
Fahd S. Alotaibi
Keyword(s):  
Big Data ◽  
Research Area ◽  
Provable Data Possession ◽  
Integrity Verification ◽  
The Core ◽  
Outsourced Data ◽  
Active Research ◽  
Data Auditing ◽  
Active Research Area ◽  
Proof Of Retrievability

The auditing services of the outsourced data, especially big data, have been an active research area recently. Many schemes of remotely data auditing (RDA) have been proposed. Both categories of RDA, which are Provable Data Possession (PDP) and Proof of Retrievability (PoR), mostly represent the core schemes for most researchers to derive new schemes that support additional capabilities such as batch and dynamic auditing. In this paper, we choose the most popular PDP schemes to be investigated due to the existence of many PDP techniques which are further improved to achieve efficient integrity verification. We firstly review the work of literature to form the required knowledge about the auditing services and related schemes. Secondly, we specify a methodology to be adhered to attain the research goals. Then, we define each selected PDP scheme and the auditing properties to be used to compare between the chosen schemes. Therefore, we decide, if possible, which scheme is optimal in handling big data auditing.

scholarly journals Fluorescent Chemosensors for Ion and Molecule Recognition: The Next Chapter

2021 ◽  
Vol 2 ◽  
Author(s):  
Kai-Cheng Yan ◽  
Axel Steinbrueck ◽  
Adam C. Sedgwick ◽  
Tony D. James
Keyword(s):  
State Of The Art ◽  
Fluorescent Chemosensors ◽  
Distant Future ◽  
The Past ◽  
Current Trends ◽  
Current State ◽  
Future Challenges ◽  
Molecule Recognition

Over the past 30 years fluorescent chemosensors have evolved to incorporate many optical-based modalities and strategies. In this perspective we seek to highlight the current state of the art as well as provide our viewpoint on the most significant future challenges remaining in the area. To underscore current trends in the field and to facilitate understanding of the area, we provide the reader with appropriate contemporary examples. We then conclude with our thoughts on the most probable directions that chemosensor development will take in the not-too-distant future.

scholarly journals E-Mail Usage in South Pacific Distance Education

2005 ◽  
pp. 1034-1039
Author(s):  
Jonathan Frank ◽  
Janet Toland ◽  
Karen D. Schenk
Keyword(s):  
Learning Styles ◽  
Research Area ◽  
Web Based ◽  
Group Interactions ◽  
Face To Face ◽  
Web Based Learning ◽  
Active Research ◽  
The Impact ◽  
E Mail ◽  
Active Research Area

The impact of cultural diversity on group interactions through technology is an active research area. Current research has found that a student’s culture appears to influence online interactions with teachers and other students (Freedman & Liu, 1996). Students from Asian and Western cultures have different Web-based learning styles (Liang & McQueen, 1999), and Scandinavian students demonstrate a more restrained online presence compared to their more expressive American counterparts (Bannon, 1995). Differences were also found across cultures in online compared to face-to-face discussions (Warschauer, 1996). Student engagement, discourse, and interaction are valued highly in “western” universities. With growing internationalization of western campuses, increasing use of educational technology both on and off campus, and rising distance learning enrollments, intercultural frictions are bound to increase.

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