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Journal articles on the topic 'Context awareness'

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Author: Grafiati

Published: 4 June 2021

Last updated: 8 June 2024

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1

Pinheiro, Manuele Kirsch, and Carine Souveyet. "Is Group-Awareness Context-Awareness?" International Journal of e-Collaboration 15, no. 3 (July 2019): 1–19. http://dx.doi.org/10.4018/ijec.2019070101.

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This article discusses the interest of emerging a unified view for group awareness and context information on groupware and context-aware systems. Group awareness corresponds to an important concept on Groupware applications, allowing individual users to be kept aware of group's activities and status. Context is defined by ubiquitous computing as any relevant information that can be used to characterize the situation of an entity. We assume that group awareness information should be considered as context information and handled as such. Group awareness information is often employed for decision making, contributing to users' activities and decisions, but it gives also an important clue about user's context, characterizing individual's actions regarding the group. As such, group awareness may be used for adaptation purposes, adapting the system behavior, the supplied content or its services. Besides, architectural concerns adopted on context-aware system should also be considered when developing new groupware applications that are more and more designed as context-aware systems.

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2

Lukowicz, Paul, Tanzeem Choudhury, and Hans Gellersen. "Beyond Context Awareness." IEEE Pervasive Computing 10, no. 4 (April 2011): 15–17. http://dx.doi.org/10.1109/mprv.2011.67.

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3

Chihani, Bachir, Emmanuel Bertin, and Noël Crespi. "Programmable context awareness framework." Journal of Systems and Software 92 (June 2014): 59–70. http://dx.doi.org/10.1016/j.jss.2013.07.046.

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4

SANDRONI, STEPHEN. "Context of Social Awareness." Southern Medical Journal 82, no. 12 (December 1989): 1545–46. http://dx.doi.org/10.1097/00007611-198912000-00019.

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5

Jo, Sun-Moon, Guijung Kim, and Jungsoo Han. "Convergence P2P context awareness." Peer-to-Peer Networking and Applications 9, no. 3 (November 2, 2015): 461–64. http://dx.doi.org/10.1007/s12083-015-0419-y.

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6

Bardram, Jakob E., and Thomas R. Hansen. "Context-Based Workplace Awareness." Computer Supported Cooperative Work (CSCW) 19, no. 2 (March 25, 2010): 105–38. http://dx.doi.org/10.1007/s10606-010-9110-2.

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7

Traynor, Declan, Ermai Xie, and Kevin Curran. "Context-Awareness in Ambient Intelligence." International Journal of Ambient Computing and Intelligence 2, no. 1 (January 2010): 13–23. http://dx.doi.org/10.4018/jaci.2010010102.

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Ambient Intelligence (AmI) deals with the issue of how we can create context-aware, electronic environments which foster seamless human-computer interaction. Ambient Intelligence encompasses the fields of ubiquitous computing, artificially intelligent systems, and context awareness among others. This paper discusses context-awareness and examines how discoveries in this area will be key in propelling the development of true AmI environments. This will be done by examining the background and reasoning behind this particular strand of AmI research along with an overview of the technologies being explored alongside possible applications of context awareness in computing as well as technological and socio- ethical challenges in this field.

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8

Pan, Z. A., and J. X. Zhu. "Context Awareness on Mobile Devices." Applied Mechanics and Materials 743 (March 2015): 742–47. http://dx.doi.org/10.4028/www.scientific.net/amm.743.742.

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Context aware computing is important for applications to provide smarter and safer<br />service to mobile users, especially when users’ context changing rapidly or regularly. In this paper,<br />we propose a context aware model for mobile devices based on audio and location. The information<br />can easily obtained from sensors, e.g., microphones and GPS. Thus, exploiting the MFCC features<br />and the location, a Bayes Net is trained and built and will be used for context classifying in the<br />real-time classification. The results of experiments implemented on Android 4.0 platform<br />demonstrate promising performance, which indicates that the model is able to support real<br />applications.

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9

Riboni, Daniele. "Special Issue on Context Awareness." Information 9, no. 3 (March 18, 2018): 67. http://dx.doi.org/10.3390/info9030067.

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10

O’Grady, M. J., G. M. P. O’Hare, and C. Donaghey. "Delivering adaptivity through context-awareness." Journal of Network and Computer Applications 30, no. 3 (August 2007): 1007–33. http://dx.doi.org/10.1016/j.jnca.2005.12.008.

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11

Ljungstrand, Peter. "Context Awareness and Mobile Phones." Personal and Ubiquitous Computing 5, no. 1 (February 28, 2001): 58–61. http://dx.doi.org/10.1007/s007790170032.

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12

Reggiani, Luca, Jocelyn Fiorina, Sinan Gezici, Simone Morosi, and Montse Najar. "Radio Context Awareness and Applications." Journal of Sensors 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/491092.

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The context refers to “any information that can be used to characterize the situation of an entity, where an entity can be a person, place, or physical object.” Radio context awareness is defined as the ability of detecting and estimating a system state or parameter, either globally or concerning one of its components, in a radio system for enhancing performance at the physical, network, or application layers. In this paper, we review the fundamentals of context awareness and the recent advances in the main radio techniques that increase the context awareness and smartness, posing challenges and renewed opportunities to added-value applications in the context of the next generation of wireless networks.

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13

Cong Vinh, Phan, and Nguyen Thanh Tung. "Coalgebraic Aspects of Context-Awareness." Mobile Networks and Applications 18, no. 3 (August 26, 2012): 391–97. http://dx.doi.org/10.1007/s11036-012-0404-0.

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14

Al-Fedaghi, Sabah. "Awareness of context and privacy." Bulletin of the American Society for Information Science and Technology 38, no. 2 (January 13, 2012): 40–48. http://dx.doi.org/10.1002/bult.2012.1720380211.

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15

Lee, Jung-Eun, Tae-Bok Yoon, and Jee-Hyong Lee. "User Intention-Awareness System for Goal-oriented Context-Awareness Service." International Journal of Fuzzy Logic and Intelligent Systems 7, no. 2 (June 1, 2007): 154–58. http://dx.doi.org/10.5391/ijfis.2007.7.2.154.

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16

Botchkaryov, Alexey. "Task sequence planning by intelligent agent with context awareness." Computer systems and network 4, no. 1 (December 16, 2022): 12–20. http://dx.doi.org/10.23939/csn2022.01.012.

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The problem of context-aware task sequence planning for independent or weakly related tasks by an intelligent agent has been considered. The principle of matching the task to the context is analyzed. The structure of the context-aware task sequence planning module as part of an intelligent agent and the corresponding algorithm are proposed. In the structure of the planning module, three main groups of blocks are implemented: operations with tasks, operations with the context, determining the relevance of tasks to the context. The article also proposes an algorithm for calculating the dynamic priority of a task, an algorithm for determining the relevance of a task to the context, and an algorithm for adapting a set of rules for matching the task to the context. The value of the dynamic priority depends on the static priority of the task, which is assigned when a new task is added, and the degree of correspondence of the task to the context, taking into account the context vector. Two modes of starting the planning algorithm are allowed: when the intelligent agent requests a new task and when the context vector changes. The dynamic priority calculation algorithm is performed independently for each task. As a result, its software implementation has a large parallelization resource. To adapt the set of rules for matching tasks to the context, a scheme of reinforcement learning in a contextual multi-armed bandit was used. For each matching rule, a separate instance of the reinforcement learning procedure is performed. The reinforcement learning method used in the article is Upper-Confidence-Bound Action Selection. The functional scheme of the reinforcement learning procedure, implemented in the prototype of the context-aware task sequence planning module has been proposed. The functional scheme of the reinforcement learning procedure allows the use of data decomposition and functional decomposition to parallelize the corresponding calculations.

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17

Mannweiler, C., A. Klein, J. Schneider, and H. D. Schotten. "Context-awareness for heterogeneous access management." Advances in Radio Science 8 (November 17, 2010): 257–62. http://dx.doi.org/10.5194/ars-8-257-2010.

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Abstract. The increasing availability of both static and dynamic context information has steadily been driving the development of context-aware communication systems. Adapting system behavior according to current context of the network, the user, and the terminal can yield significant end-to-end performance improvements. In this paper, we present a concept for how to use context information, in particular location information and movement prediction, for Heterogeneous Access Management (HAM). In a first step, we outline the functional architecture of a distributed and extensible context management system (CMS) that defines the roles, tasks, and interfaces of all modules within such a system for large-scale context acquisition and dissemination. In a second step, we depict how the available context information can be exploited for optimizing terminal handover decisions to be made in a multi-RAT (radio access technology) environment. In addition, the utilized method for predicting terminal location as well as the objective functions used for evaluating and comparing system performance are described. Finally, we present preliminary simulation results demonstrating that HAM systems that include current and future terminal context information in the handover decision process clearly outperform conventional systems.

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18

Ntalasha, Derrick, Renfa Li, and Yongheng Wang. "Internet of Thing Context Awareness Model." EAI Endorsed Transactions on Context-aware Systems and Applications 3, no. 7 (February 12, 2016): 151084. http://dx.doi.org/10.4108/eai.12-2-2016.151084.

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19

Lee, Karen, Tom Lunney, Kevin Curran, and Jose Santos. "Ambient Middleware for Context-Awareness (AMiCA)." International Journal of Ambient Computing and Intelligence 1, no. 3 (July 2009): 66–78. http://dx.doi.org/10.4018/jaci.2009070105.

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20

Rodis, Panteleimon. "On defining and modeling context-awareness." International Journal of Pervasive Computing and Communications 14, no. 2 (June 4, 2018): 111–23. http://dx.doi.org/10.1108/ijpcc-d-18-00003.

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Purpose This paper aims to present a methodology for defining and modeling context-awareness and describing efficiently the interactions between systems, applications and their context. Also, the relation of modern context-aware systems with distributed computation is investigated. Design/methodology/approach On this purpose, definitions of context and context-awareness are developed based on the theory of computation and especially on a computational model for interactive computation which extends the classical Turing Machine model. The computational model proposed here encloses interaction and networking capabilities for computational machines. Findings The definition of context presented here develops a mathematical framework for working with context. Also, the modeling approach of distributed computing enables us to build robust, scalable and detailed models for systems and application with context-aware capabilities. Also, it enables us to map the procedures that support context-aware operations providing detailed descriptions about the interactions of applications with their context and other external sources. Practical implications A case study of a cloud-based context-aware application is examined using the modeling methodology described in the paper so as to demonstrate the practical usage of the theoretical framework that is presented. Originality/value The originality on the framework presented here relies on the connection of context-awareness with the theory of computation and distributed computing.

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21

Aguilar, Jose, Marxjhony Jerez, and Taniana Rodríguez. "CAMeOnto: Context awareness meta ontology modeling." Applied Computing and Informatics 14, no. 2 (July 2018): 202–13. http://dx.doi.org/10.1016/j.aci.2017.08.001.

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22

Xu, Jiake, Yanheng Liu, Jian Wang, Weiwen Deng, and Thierry Ernst. "VIKE: vehicular IKE for context-awareness." Wireless Networks 21, no. 4 (November 25, 2014): 1343–62. http://dx.doi.org/10.1007/s11276-014-0856-1.

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23

Anagnostopoulos, Christos B., Athanasios Tsounis, and Stathes Hadjiefthymiades. "Context Awareness in Mobile Computing Environments." Wireless Personal Communications 42, no. 3 (November 15, 2006): 445–64. http://dx.doi.org/10.1007/s11277-006-9187-6.

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24

Maran, Vinícius, Alencar Machado, Guilherme Medeiros Machado, Iara Augustin, and José Palazzo M. de Oliveira. "Domain content querying using ontology-based context-awareness in information systems." Data & Knowledge Engineering 115 (May 2018): 152–73. http://dx.doi.org/10.1016/j.datak.2018.03.003.

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25

Rad, Dana, Valentina Balas, Ramona Lile, Edgar Demeter, Tiberiu Dughi, and Gavril Rad. "Statistical Properties of a New Social Media Context Awareness Scale (SMCA)—A Preliminary Investigation." Sustainability 12, no. 12 (June 25, 2020): 5201. http://dx.doi.org/10.3390/su12125201.

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In the Internet of Things era, or in the digitalization and mediatization of everything paradigm, where context awareness computing is on the rise, people are also facing a new challenge, that of being aware of the digital contexts, in all situations when surfing the internet’s ocean of row information. The emerging social media context awareness competency refers to a new emerging skill regarding the trust load people give to a specific social media context they encounter. Since it is an emergent competence, it cannot be understood as standalone. If the digital context would not be available, we would not develop such a competence. Being a competence, it must be defined by three core elements: Knowledge, skills, and attitudes. Consequently, we have operationalized the competence of social media context awareness in terms of social media literacy, social media communication process understanding, social media content impact awareness, and social media confidence. An online questionnaire was created under the Erasmus+ project Hate’s Journey, addressing a convenience sample of 206 online youth respondents from Turkey, Spain, Latvia, and Romania. Our team has computed a reliability analysis on the social media context awareness scale designed with four items referring to social media literacy (m = 3.79, SD = 1), social media communication process understanding (m = 3.77, SD = 0.9), social media content impact awareness (m = 3.88, SD = 1), and social media confidence (m = 3.45, SD = 1). Cronbach’s alpha coefficient and the Exploratory Factor Analysis demonstrated the acceptable reliability of the SMCA scale, α = 0.87. Conclusions, implications, and limitations are discussed in the context of social sustainability.

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26

Wang, Liudi, Shan Zhang, Xishuo Li, and Hongbin Luo. "Age-constrained dynamic content replacing and delivering for UAV-assisted context awareness." China Communications 19, no. 7 (July 2022): 277–93. http://dx.doi.org/10.23919/jcc.2022.07.021.

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27

Michalakis, Konstantinos, and George Caridakis. "Context Awareness in Cultural Heritage Applications: A Survey." Journal on Computing and Cultural Heritage 15, no. 2 (June 30, 2022): 1–31. http://dx.doi.org/10.1145/3480953.

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Cultural Heritage Institutions fueled by the advances in Information Technology are exploiting new ways to present their content to visitors. The emergence of the Internet of Things paradigm has shifted their efforts into a more personalized and adaptable experience that takes into consideration the visitor profile and behavior, in respect to presented artifacts and environmental parameters. Context-awareness allows the understanding of the situation and the optimization of the delivered cultural User Experience. In this article, we survey context awareness in cultural heritage applications. After presenting the background of Context Awareness and its features to cultural environments, a subset of research projects that incorporate context aware traits in a cultural scenario is reviewed. Each prototype is analysed in respect to several criteria that include context sensing, middleware, and incorporation methods. Finally, based on the review, lessons learnt, and directions for the development of similar prototypes are highlighted.

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28

Lee, Bong-Keun, Jae-Du Chung, and Keun-Ho Ryu. "An Intelligent NPC Framework for Context Awareness." Journal of the Korea Academia-Industrial cooperation Society 10, no. 9 (September 30, 2009): 2361–68. http://dx.doi.org/10.5762/kais.2009.10.9.2361.

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29

Wasilewska, Malgorzata, Adrian Kliks, Hanna Bogucka, Krzysztof Cichon, Julius Ruseckas, Gediminas Molis, Ausra Mackute-Varoneckiene, and Tomas Krilavicius. "Artificial Intelligence for Radio Communication Context-Awareness." IEEE Access 9 (2021): 144820–56. http://dx.doi.org/10.1109/access.2021.3119524.

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30

Abdulrazak, Bessam, Patrice Roy, Charles Gouin-Vallerand, Yacine Belala, and Sylvain Giroux. "Micro Context-Awareness for Autonomic Pervasive Computing." International Journal of Business Data Communications and Networking 7, no. 2 (April 2011): 48–68. http://dx.doi.org/10.4018/jbdcn.2011040104.

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Context-aware software provides adapted services to users or other software components. On the other hand, Autonomic Pervasive Computing uses context to reduce the complexity of pervasive system utilization, management and maintenance. This paper describes two context-awareness models, the macro and micro approaches, that define and integrate contextual views of individual pervasive components (micro level) and global knowledge of the system (macro level), and provides a more detailed overview of a micro Context-aware programming model for open smart space problems. These models are presented and compared with respect to their ability to meet the requirements of the Autonomic Pervasive Computing concept of the four selves.

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31

Lee, Hyung-Ok, Yong-Wan Kwak, Seung-Chul Son, and Ji-Seung Nam. "Context-awareness Based SVC Multimedia Broadcast Service." Journal of Korean Institute of Communications and Information Sciences 36, no. 9B (September 30, 2011): 1098–107. http://dx.doi.org/10.7840/kics.2011.36b.9.1098.

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32

MA, Jun, Xian-Ping TAO, Huai-Hong ZHU, and Jian LÜ. "Enhancing Multi-Agent System with Context-Awareness." Journal of Software 23, no. 11 (January 23, 2014): 2905–22. http://dx.doi.org/10.3724/sp.j.1001.2012.04301.

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33

Jeong, Hwa-Young, Yang Xiao, Yuh-Shyan Chen, and Xiaohong Peng. "Ubiquitous Context-Awareness and Wireless Sensor Networks." International Journal of Distributed Sensor Networks 10, no. 7 (January 2014): 614023. http://dx.doi.org/10.1155/2014/614023.

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34

Lijuan, Luo, Lv Tingjie, and Chen Xia. "Network selection based on context-awareness services." China Communications 10, no. 12 (December 2013): 50–56. http://dx.doi.org/10.1109/cc.2013.6723878.

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35

Suh, Joohee, and Chong-Woo Woo. "A Development of Intelligent Context-Awareness Middleware." Journal of the Korea society of IT services 11, sup (November 30, 2012): 165–76. http://dx.doi.org/10.9716/kits.2012.11.sup.165.

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36

Persuh, M., T. A. Emmanouil, and T. Ro. "Color assimilation without awareness of color context." Journal of Vision 14, no. 10 (August 22, 2014): 996. http://dx.doi.org/10.1167/14.10.996.

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37

Aaltonen, Antti, Pertti Huuskonen, and Juha Lehikoinen. "Context Awareness Perspectives for Mobile Personal Media." Information Systems Management 22, no. 4 (September 2005): 43–55. http://dx.doi.org/10.1201/1078.10580530/45520.22.4.20050901/90029.5.

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38

Bulling, Andreas, Daniel Roggen, and Gerhard Tröster. "What's in the Eyes for Context-Awareness?" IEEE Pervasive Computing 10, no. 2 (April 2011): 48–57. http://dx.doi.org/10.1109/mprv.2010.49.

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39

Lukowicz, P., S. Pentland, and A. Ferscha. "From Context Awareness to Socially Aware Computing." IEEE Pervasive Computing 11, no. 1 (2012): 32–41. http://dx.doi.org/10.1109/mprv.2011.82.

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40

Zheng, Yanlin, Luyi Li, Hiroaki Ogata, and Yoneo Yano. "Support online social interaction with Context-Awareness." International Journal of Continuing Engineering Education and Life-Long Learning 17, no. 2/3 (2007): 160. http://dx.doi.org/10.1504/ijceell.2007.013662.

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41

Bickmore, Timothy W., Daniel Mauer, and Thomas Brown. "Context awareness in a handheld exercise agent." Pervasive and Mobile Computing 5, no. 3 (June 2009): 226–35. http://dx.doi.org/10.1016/j.pmcj.2008.05.004.

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42

Ceri, Stefano, Florian Daniel, Federico M. Facca, and Maristella Matera. "Model-driven Engineering of Active Context-awareness." World Wide Web 10, no. 4 (March 2, 2007): 387–413. http://dx.doi.org/10.1007/s11280-006-0014-5.

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43

Hilding-Rydevik, Tuija, and Holmfridur Bjarnadóttir. "Context awareness and sensitivity in SEA implementation." Environmental Impact Assessment Review 27, no. 7 (October 2007): 666–84. http://dx.doi.org/10.1016/j.eiar.2007.05.009.

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44

Philpott, Carolyn. "Promoting Environmental Awareness through Context-based Composition." Organised Sound 23, no. 1 (December 26, 2017): 39–50. http://dx.doi.org/10.1017/s1355771817000267.

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Cheryl E. Leonard is a San Francisco-based composer, performer and instrument maker who utilises sounds from natural objects and field recordings to create innovative compositions that are aesthetically appealing and also promote environmental awareness. This article examines Leonard’s workAntarctica: Music from the Ice(2009–2014), which comprises ten context-based pieces created from sounds produced with natural objects (such as penguin bones, rocks and shells) and field recordings the composer collected during her visit to Antarctica in 2008–9. In particular, the article focuses on the piecesLullaby for E Seals,White on White,Greater than 20 KnotsandAblation Zone, showing how Leonard draws attention to pertinent environmental issues through her work, while at the same time producing compositions that are aurally pleasing and engaging for performers and listeners alike.

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45

Bricon-Souf, Nathalie, and Conrad R. Newman. "Context awareness in health care: A review." International Journal of Medical Informatics 76, no. 1 (January 2007): 2–12. http://dx.doi.org/10.1016/j.ijmedinf.2006.01.003.

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46

Zhang, Daqiang, Hongyu Huang, Chin-Feng Lai, Xuedong Liang, Qin Zou, and Minyi Guo. "Survey on context-awareness in ubiquitous media." Multimedia Tools and Applications 67, no. 1 (November 29, 2011): 179–211. http://dx.doi.org/10.1007/s11042-011-0940-9.

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47

Baidouri, Hicham, Hatim Hafiddi, Mahmoud Nassar, and Abdelaziz Kriouile. "Enabling Context-Awareness for Dynamic Service Composition." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 1 (January 2015): 17–29. http://dx.doi.org/10.4018/ijapuc.2015010102.

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One of the main observed gains of Service Oriented Architectures (SOA) is the ability to compose new services to achieve high level functionalities. Thus, it is necessary to organize services in a manner to achieve this goal automatically and easily. Furthermore, the emergence of wireless technologies and intelligent mobile devices has enabled the creation of a new kind of services called context-aware composite services. With such services, context plays a great role in their design and development process in order to produce the most appropriate response. In this paper, the authors aim to present their Context-Aware Composite Service (CACS) metamodel for design and development of these services, and, a dedicated tool called MA2C (A Mediator Architecture for Context-aware Composition) responsible of their dynamic generation and execution.

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48

Chihani, Bachir, Emmanuel Bertin, Irsalina Salsabila Suprapto, Julien Zimmermann, and Noël Crespi. "Enhancing Existing Communication Services with Context Awareness." Journal of Computer Networks and Communications 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/493261.

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Context aware communication services rely on information sources and sensors, to derive users’ current situation and potential needs, and to adapt their communication services accordingly. If extensive studies have been driven on context awareness by industrials and researchers from academia, the design of such systems without modifying uses and manners of underlying communication services—while keeping them simple, intuitive, and reactive—remains a challenge. In this work, we introduce a context aware communication system that takes into account user’s preferences, workload, and situation to customize telephony services. In this implementation, we use IMS for communication management. The benefits of this implementation are the enhancement of IMS with context awareness features, and the coupling of user preferences with contextual information to provide improved service customization, without modifying the user experience.

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49

Wrzeszcz, Michal, Renata Slota, and Jacek Kitowski. "TOWARDS TRANSPARENT DATA ACCESS WITH CONTEXT AWARENESS." Computer Science 19, no. 2 (2018): 201. http://dx.doi.org/10.7494/csci.2018.19.2.2844.

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50

Korpip��, Panu, Miika Koskinen, Johannes Peltola, Satu-Marja M�kel�, and Tapio Sepp�nen. "Bayesian approach to sensor-based context awareness." Personal and Ubiquitous Computing 7, no. 2 (July 1, 2003): 113–24. http://dx.doi.org/10.1007/s00779-003-0237-8.

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