scholarly journals Emotions in texts

2020 ◽  
Vol 4 (2) ◽  
pp. 59-69
Author(s):  
Leeveshkumar Pokhun ◽  
M Yasser Chuttur
Keyword(s):  
Real World ◽  
Gold Standard ◽  
Relevant Research ◽  
Emotion Analysis ◽  
Real World Applications ◽  
Emotion Model ◽  
No Gold Standard ◽  
Further Development ◽  
Emotion Models ◽  
Common Platform

Several studies have used different techniques to detect and identify emotions expressed in various sets of texts corpora. In this paper, we review different emotion models, emotion datasets and the corresponding techniques used for emotion analysis in past studies. We observe that researchers have been using a wide variety of techniques to detect emotions in texts and that there is currently no gold standard on which dataset or which emotion model to use. Consequently, although the field of emotion analysis has gained much momentum in previous years, there seems to be little progress into relevant research with findings that may be useful in real world applications. From our analysis and findings, we urge researchers to consider the development of datasets, evaluation benchmarks and a common platform for sharing achievements in emotion analysis to see further development in the field.

Economics of Alliances: The Lessons for Collective Action

2001 ◽  
Vol 39 (3) ◽  
pp. 869-896 ◽  
Author(s):  
Todd Sandler ◽  
Keith Hartley
Keyword(s):  
Collective Action ◽  
Public Good ◽  
Real World ◽  
Pivotal Role ◽  
Burden Sharing ◽  
Empirical Knowledge ◽  
Wide Range ◽  
Real World Applications ◽  
Further Development

This essay provides an up-to-date summary of the findings of the literature on the economics of alliances. We show that the study of the economics of alliances has played a pivotal role in understanding and applying public good analysis to real-world applications. We establish that the manner in which alliances address burden sharing and allocative issues is related to strategic doctrines, weapon technology, perceived threats, and membership composition. Past contributions are evaluated, and areas needing further development are identified. The theoretical and empirical knowledge gained from the study of alliances is shown to be directly applicable to a wide range of international collectives.

Dynamic Trajectory Planning for Failure Recovery in Cable-Suspended Camera Systems

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Chiara Passarini ◽  
Damiano Zanotto ◽  
Giovanni Boschetti
Keyword(s):  
Trajectory Planning ◽  
Real World ◽  
Parallel Robots ◽  
Research Topic ◽  
Failure Recovery ◽  
Relevant Research ◽  
End Effector ◽  
Camera Systems ◽  
Real World Applications ◽  
Dynamic Trajectory

The use of cable-driven parallel robots (CDPR) in real-world applications makes safety a major concern for these devices and a relevant research topic. Cable-suspended camera systems are among the earliest and most common applications of CDPRs. In this paper, we propose a novel after-failure approach for cable-suspended camera systems. This strategy, which is applied after a cable breaks, seeks to drive the end effector, i.e., the camera, toward a safe pose, following an oscillatory trajectory that guarantees positive and bounded tensions in the remaining cables. The safe landing location is optimized to minimize the trajectory time while avoiding collisions with the physical boundaries of the workspace. Results of numerical simulations indicate the feasibility of the proposed approach.

scholarly journals CSO Classifier 3.0: a scalable unsupervised method for classifying documents in terms of research topics

2021 ◽  
Author(s):  
Angelo Salatino ◽  
Francesco Osborne ◽  
Enrico Motta
Keyword(s):  
Computer Science ◽  
Digital Libraries ◽  
Gold Standard ◽  
Research Trends ◽  
Alternative Methods ◽  
Relevant Research ◽  
Research Topics ◽  
Research Papers ◽  
Research Areas ◽  
Unsupervised Approach

AbstractClassifying scientific articles, patents, and other documents according to the relevant research topics is an important task, which enables a variety of functionalities, such as categorising documents in digital libraries, monitoring and predicting research trends, and recommending papers relevant to one or more topics. In this paper, we present the latest version of the CSO Classifier (v3.0), an unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive taxonomy of research areas in the field of Computer Science. The CSO Classifier takes as input the textual components of a research paper (usually title, abstract, and keywords) and returns a set of research topics drawn from the ontology. This new version includes a new component for discarding outlier topics and offers improved scalability. We evaluated the CSO Classifier on a gold standard of manually annotated articles, demonstrating a significant improvement over alternative methods. We also present an overview of applications adopting the CSO Classifier and describe how it can be adapted to other fields.

scholarly journals Electronic Phenomena of Transition Metal Oxides

Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 256
Author(s):  
Christian Rodenbücher ◽  
Kristof Szot
Keyword(s):  
Solid State ◽  
Transition Metal ◽  
Metal Oxides ◽  
Real World ◽  
Transition Metal Oxides ◽  
Major Research ◽  
Research Fields ◽  
Real World Applications

Transition metal oxides with ABO3 or BO2 structures have become one of the major research fields in solid state science, as they exhibit an impressive variety of unusual and exotic phenomena with potential for their exploitation in real-world applications [...]

On the robustness of latent class models for diagnostic testing with no gold standard

2021 ◽  
Author(s):  
Matthew R. Schofield ◽  
Michael J. Maze ◽  
John A. Crump ◽  
Matthew P. Rubach ◽  
Renee Galloway ◽  
...  
Keyword(s):  
Gold Standard ◽  
Latent Class ◽  
Diagnostic Testing ◽  
Latent Class Models ◽  
No Gold Standard ◽  
Class Models
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