Context-Aware Adaptive Applications: Fault Patterns and Their Automated Identification

2010 ◽  
Vol 36 (5) ◽  
pp. 644-661 ◽  
Author(s):  
Michele Sama ◽  
Sebastian Elbaum ◽  
Franco Raimondi ◽  
David S. Rosenblum ◽  
Zhimin Wang
Keyword(s):  
Context Aware ◽  
Automated Identification ◽  
Adaptive Applications

scholarly journals ContextErlang: A language for distributed context-aware self-adaptive applications

2015 ◽  
Vol 102 ◽  
pp. 20-43 ◽  
Author(s):  
Guido Salvaneschi ◽  
Carlo Ghezzi ◽  
Matteo Pradella
Keyword(s):  
Context Aware ◽  
Adaptive Applications ◽  
Self Adaptive

Multi-layer faults in the architectures of mobile, context-aware adaptive applications

2010 ◽  
Vol 83 (6) ◽  
pp. 906-914 ◽  
Author(s):  
Michele Sama ◽  
David S. Rosenblum ◽  
Zhimin Wang ◽  
Sebastian Elbaum
Keyword(s):  
Context Aware ◽  
Adaptive Applications ◽  
Mobile Context

scholarly journals A context management architecture for m-commerce applications

2012 ◽  
Vol 2 (2) ◽  
Author(s):  
Benou Poulcheria ◽  
Vassilakis Costas
Keyword(s):  
User Interface ◽  
Building Design ◽  
Dynamic Environments ◽  
Mobile Services ◽  
Context Aware ◽  
Context Management ◽  
Design Models ◽  
Adaptive Applications ◽  
Management Architecture ◽  
Class Diagrams

AbstractMobile commerce applications operate in highly dynamic environments with diverse characteristics and interesting challenges. The characteristics and conditions of these environments -called context-, can be exploited to provide adaptive mobile services, in terms of user interface, functionality and content, in order to offer more effective m-commerce. Today, building adaptive mobile services is a complex and time-consuming task due to the lack of standardized methods, tools and architectures for the identification, representation and management of the context. Addressing some of these issues, recent works have provided formal extensions for various stages of the m-commerce application lifecycle, such as extended UML class diagrams for building design models and have used context parameters in order to offer adaptive applications. Using these works as the basis, in this paper we propose a context management architecture, which accommodates the requirements that have been identified for m-commerce applications. The proposed architecture is evaluated in terms of completeness, complexity, performance and utility, and compared against other approaches proposed in the literature regarding its suitability for supporting context-aware m-commerce applications.

Analyzing Language in Suicide Notes and Legacy Tokens

Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Michael J. Egnoto ◽  
Darrin J. Griffin
Keyword(s):  
Text Analysis ◽  
Low Cost ◽  
Computer Software ◽  
Student Writing ◽  
Computer Assisted ◽  
Automated Identification ◽  
Completed Suicide ◽  
Suicide Notes ◽  
Self Harm ◽  
Harm To Others

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.

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