Learning Complex Events from Sequences with Informed Gaps

2015 ◽  
Author(s):  
Pablo Gay ◽  
Beatriz Lopez ◽  
Joaquim Melendez
Keyword(s):  
Complex Events

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

Chaos in Social Theory: Explaining Complex Events with Simple Ideas

1998 ◽  
Vol 31 (4) ◽  
pp. 357-372
Author(s):  
Robert K. Shelly ◽  
David G. Wagner
Keyword(s):  
Social Theory ◽  
Complex Events

scholarly journals Person-level Action Recognition in Complex Events via TSD-TSM Networks

2020 ◽  
Author(s):  
Yanbin Hao ◽  
Zi-Niu Liu ◽  
Hao Zhang ◽  
Bin Zhu ◽  
Jingjing Chen ◽  
...  
Keyword(s):  
Action Recognition ◽  
Complex Events

A Formal Framework for Complex Event Recognition

2021 ◽  
Vol 46 (4) ◽  
pp. 1-49
Author(s):  
Alejandro Grez ◽  
Cristian Riveros ◽  
Martín Ugarte ◽  
Stijn Vansummeren
Keyword(s):  
Query Languages ◽  
Event Recognition ◽  
Distributed Data ◽  
Performance Guarantees ◽  
Selection Strategies ◽  
Trade Offs ◽  
Formal Framework ◽  
Linear Delay ◽  
Complex Events ◽  
Complex Event Recognition

Complex event recognition (CER) has emerged as the unifying field for technologies that require processing and correlating distributed data sources in real time. CER finds applications in diverse domains, which has resulted in a large number of proposals for expressing and processing complex events. Existing CER languages lack a clear semantics, however, which makes them hard to understand and generalize. Moreover, there are no general techniques for evaluating CER query languages with clear performance guarantees. In this article, we embark on the task of giving a rigorous and efficient framework to CER. We propose a formal language for specifying complex events, called complex event logic (CEL), that contains the main features used in the literature and has a denotational and compositional semantics. We also formalize the so-called selection strategies, which had only been presented as by-design extensions to existing frameworks. We give insight into the language design trade-offs regarding the strict sequencing operators of CEL and selection strategies. With a well-defined semantics at hand, we discuss how to efficiently process complex events by evaluating CEL formulas with unary filters. We start by introducing a formal computational model for CER, called complex event automata (CEA), and study how to compile CEL formulas with unary filters into CEA. Furthermore, we provide efficient algorithms for evaluating CEA over event streams using constant time per event followed by output-linear delay enumeration of the results.

Educational Experiences: Voices of Incarcerated Male Youth & School-to-Prison Pipeline

2021 ◽  
pp. 54-72
Author(s):  
Everett Singleton
Keyword(s):  
School Violence ◽  
Educational Experiences ◽  
Academic Failure ◽  
Incarcerated Youth ◽  
Male Youth ◽  
Personal Lives ◽  
Parental Neglect ◽  
Indirect Impact ◽  
Complex Events ◽  
Personal Challenges

Youth who experience academic failure are at a greater risk for involvement in delinquency. While studies have revealed a myriad of factors for such failure, the perceptions of these youth regarding their educational experiences have proven to be one of the most valuable resources regarding the systematic barriers to academic achievement. The purpose of this study was to understand how incarcerated male youth perceive their educational experiences. Results indicated that some incarcerated youth make meaning of their educational experiences through a series of complex events, changes, and circumstances occurring in their school and personal lives. Some of these were positive, while others often exposed them to unhealthy environments, substance abuse, and criminal elements. Although their experiences varied, it was clear that failure was an ongoing occurrence throughout their academic journey. Their stories were also rife with suspensions, expulsion, truancy, retention, academic failure, school violence, poverty, and parental neglect; furthermore, youth revealed personal challenges that had a direct or indirect impact on their academic journey, including feeling of inferiority due to their academic shortcomings.

scholarly journals Disaster Metrics: A Comprehensive Framework for Disaster Evaluation Typologies

2017 ◽  
Vol 32 (5) ◽  
pp. 501-514 ◽  
Author(s):  
Diana F. Wong ◽  
Caroline Spencer ◽  
Lee Boyd ◽  
Frederick M. Burkle ◽  
Frank Archer
Keyword(s):  
Grey Literature ◽  
Evidence Base ◽  
International Level ◽  
Publication Type ◽  
Mortality And Morbidity ◽  
Constructive Dialogue ◽  
Complex Events ◽  
Future Events ◽  
Two Phases ◽  
Comprehensive Framework

AbstractIntroductionThe frequency of disasters is increasing around the world with more people being at risk. There is a moral imperative to improve the way in which disaster evaluations are undertaken and reported with the aim of reducing preventable mortality and morbidity in future events. Disasters are complex events and undertaking disaster evaluations is a specialized area of study at an international level.Hypothesis/ProblemWhile some frameworks have been developed to support consistent disaster research and evaluation, they lack validation, consistent terminology, and standards for reporting across the different phases of a disaster. There is yet to be an agreed, comprehensive framework to structure disaster evaluation typologies.The aim of this paper is to outline an evolving comprehensive framework for disaster evaluation typologies. It is anticipated that this new framework will facilitate an agreement on identifying, structuring, and relating the various evaluations found in the disaster setting with a view to better understand the process, outcomes, and impacts of the effectiveness and efficiency of interventions.MethodsResearch was undertaken in two phases: (1) a scoping literature review (peer-reviewed and “grey literature”) was undertaken to identify current evaluation frameworks and typologies used in the disaster setting; and (2) a structure was developed that included the range of typologies identified in Phase One and suggests possible relationships in the disaster setting.ResultsNo core, unifying framework to structure disaster evaluation and research was identified in the literature. The authors propose a “Comprehensive Framework for Disaster Evaluation Typologies” that identifies, structures, and suggests relationships for the various typologies detected.ConclusionThe proposed Comprehensive Framework for Disaster Evaluation Typologies outlines the different typologies of disaster evaluations that were identified in this study and brings them together into a single framework. This unique, unifying framework has relevance at an international level and is expected to benefit the disaster, humanitarian, and development sectors. The next step is to undertake a validation process that will include international leaders with experience in evaluation, in general, and disasters specifically. This work promotes an environment for constructive dialogue on evaluations in the disaster setting to strengthen the evidence base for interventions across the disaster spectrum. It remains a work in progress.WongDF,SpencerC,BoydL,BurkleFMJr.,ArcherF.Disaster metrics: a comprehensive framework for disaster evaluation typologies.Prehosp Disaster Med.2017;32(5):501–514.

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