Event Chain Methodology: Managing Event Chains

2017 ◽  
pp. 121-136
Keyword(s):  
Event Chains

scholarly journals Defying chronology: Crosslinguistic variation in reverse order reports

Linguistics ◽  
2020 ◽  
Vol 58 (2) ◽  
pp. 569-603
Author(s):  
Norbert Vanek ◽  
Barbara Mertins
Keyword(s):  
Native Speakers ◽  
Reverse Order ◽  
Natural Occurrence ◽  
Grammatical Aspect ◽  
Language Structure ◽  
Temporal Sequencing ◽  
Crosslinguistic Variation ◽  
Event Chains ◽  
Frequency Counts ◽  
Dynamic Interplay

AbstractMuch of how we sequence events in speech mirrors the order of their natural occurrence. While event chains that conform to chronology may be easier to process, languages offer substantial freedom to manipulate temporal order. This article explores to what extent digressions from chronology are attributable to differences in grammatical aspect systems. We compared reverse order reports (RORs) in event descriptions elicited from native speakers of four languages, two with (Spanish, Modern Standard Arabic [MSA]) and two without grammatical aspect (German, Hungarian). In the Arabic group, all participants were highly competent MSA speakers from Palestine and Jordan. Standardized frequency counts showed significantly more RORs expressed by non-aspect groups than by aspect groups. Adherence to chronology changing as a function of contrast in grammatical aspect signal that languages without obligatory marking of ongoingness may provide more flexibility for event reordering. These findings bring novel insights about the dynamic interplay between language structure and temporal sequencing in the discourse stream.

scholarly journals Promoting Metro Operation Safety by Exploring Metro Operation Accident Network

2021 ◽  
Vol 9 (4) ◽  
pp. 455-468
Author(s):  
Qi Suo ◽  
Liyuan Wang ◽  
Tianzi Yao ◽  
Zihao Wang
Keyword(s):  
Network Theory ◽  
Operation System ◽  
Causal Factors ◽  
Cascading Effects ◽  
Complex Network Theory ◽  
Facility Type ◽  
Safety Studies ◽  
Topological Characteristics ◽  
Event Chains ◽  
Global And Local

Abstract Understanding the causation of accidents is essential to promote metro operation safety. In terms of 243 reported metro operation accident cases in China, a directed weighted network was constructed based on complex network theory, where nodes and directed edges denotes factors and event chains respectively. To reveal the key causal factors, the topological characteristics of metro operation accident network (MOAN) were analyzed from both global and local views. The results show that facility-type factors are more closely related to the occurrence of the accidents from the perspectives of average path length and cascading effects. Accident types like train delay and train suspension are the great risk recipients. Key causal factors with large out-degree, out-strength, betweenness centrality and cluster coefficient, such as communication and signal failure, vehicle failure and piling into the train should be noticed. The research framework proposed in the paper is not only applicable to China’s metro operation system, but also appropriate for other transportation system safety studies.

scholarly journals Constructing Narrative Event Evolutionary Graph for Script Event Prediction

2018 ◽  
Author(s):  
Zhongyang Li ◽  
Xiao Ding ◽  
Ting Liu
Keyword(s):  
New York ◽  
Large Scale ◽  
New York Times ◽  
Inference Problem ◽  
Candidate Event ◽  
Event Prediction ◽  
Subsequent Event ◽  
Narrative Event ◽  
Event Chains ◽  
Event Representations

Script event prediction requires a model to predict the subsequent event given an existing event context. Previous models based on event pairs or event chains cannot make full use of dense event connections, which may limit their capability of event prediction. To remedy this, we propose constructing an event graph to better utilize the event network information for script event prediction. In particular, we first extract narrative event chains from large quantities of news corpus, and then construct a narrative event evolutionary graph (NEEG) based on the extracted chains. NEEG can be seen as a knowledge base that describes event evolutionary principles and patterns. To solve the inference problem on NEEG, we present a scaled graph neural network (SGNN) to model event interactions and learn better event representations. Instead of computing the representations on the whole graph, SGNN processes only the concerned nodes each time, which makes our model feasible to large-scale graphs. By comparing the similarity between input context event representations and candidate event representations, we can choose the most reasonable subsequent event. Experimental results on widely used New York Times corpus demonstrate that our model significantly outperforms state-of-the-art baseline methods, by using standard multiple choice narrative cloze evaluation.

scholarly journals How to consider history in landscape ecology: patterns, processes, and pathways

2020 ◽  
Author(s):  
Ulrike Tappeiner ◽  
Georg Leitinger ◽  
Anita Zariņa ◽  
Matthias Bürgi
Keyword(s):  
Landscape Ecology ◽  
Landscape Change ◽  
Path Dependence ◽  
Complete Analysis ◽  
The Past ◽  
Natural Landscapes ◽  
Patterns And Processes ◽  
Event Chains ◽  
Over Time

Abstract Context Landscape ecology early on developed the awareness that central objects of investigation are not stable over time and therefore the historical dimension must be included, or at least considered. Objectives This paper considers the importance of history in landscape ecology in terms of its impact on patterns and processes and proposes to complement these with the notion of pathways in order to provide a comprehensive analysis of landscape change. Methods We develop a conceptual framework distinguishing between legacy effects, which include pattern and processes, and path dependence, with a focus of development pathways and we illustrate these perspectives by empirical examples. Results Combined short- to long-lasting imprints and legacies of historical patterns and processes reveal how present patterns and processes are in various ways influenced by legacies of the past. The focus on inherent dynamics of development pathways sheds light on the process of change itself, and its trajectories, and reveals the role of event chains and institutional reproduction. Conclusions Understanding patterns, processes, and pathways over time, allows a more complete analysis of landscape change, and forms the base to preserve vital ecosystem services of both human-made and natural landscapes for the future.

scholarly journals Accurate and Efficient Modeling of 802.15.4 Unslotted CSMA/CA through Event Chains Computation

2016 ◽  
Vol 15 (12) ◽  
pp. 2954-2968 ◽  
Author(s):  
Domenico De Guglielmo ◽  
Francesco Restuccia ◽  
Giuseppe Anastasi ◽  
Marco Conti ◽  
Sajal K. Das
Keyword(s):  
Event Chains ◽  
Efficient Modeling

A Method for Measuring the Constraint Complexity of Components in Automotive Embedded Software Systems

2019 ◽  
Vol 29 (01) ◽  
pp. 1-21
Author(s):  
Mohit Garg ◽  
Richard Lai
Keyword(s):  
Real Time ◽  
Unified Modeling Language ◽  
Embedded Software ◽  
Software Systems ◽  
Structural Constraints ◽  
Timing Constraints ◽  
Object Constraint Language ◽  
Complexity Measures ◽  
Automotive Embedded Software ◽  
Event Chains

The rapid growth of software-based functionalities has made automotive Electronic Control Units (ECUs) significantly complex. Factors affecting the software complexity of components embedded in an ECU depend not only on their interface and interaction properties, but also on the structural constraints characterized by a component’s functional semantics and timing constraints described by AUTomotive Open System ARchitecture (AUTOSAR) languages. Traditional constraint complexity measures are not adequate for the components in embedded software systems as they do not yet sufficiently provide a measure of the complexity due to timing constraints which are important for quantifying the dynamic behavior of components at run-time. This paper presents a method for measuring the constraint complexity of components in automotive embedded software systems at the specification level. It first enables system designers to define non-deterministic constraints on the event chains associated with components using the AUTOSAR-based Modeling and Analysis of Real-Time and Embedded systems (MARTE)-UML and Timing Augmented Description Language (TADL). Then, system analysts use Unified Modeling Language (UML)-compliant Object Constraint Language (OCL) and its Real-time extension (RT-OCL) to specify the structural and timing constraints on events and event chains and estimate the constraint complexity of components using a measure we have developed. A preliminary version of the method was presented in M. Garg and R. Lai, Measuring the constraint complexity of automotive embedded software systems, in Proc. Int. Conf. Data and Software Engineering, 2014, pp. 1–6. To demonstrate the usefulness of our method, we have applied it to an automotive Anti-lock Brake System (ABS).

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