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Journal articles on the topic 'Context-aware computing'

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Published: 4 June 2021
Last updated: 25 May 2024

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1

Chang, Edward Y. "Context-aware computing." Proceedings of the VLDB Endowment 6, no. 11 (August 27, 2013): 1172–73. http://dx.doi.org/10.14778/2536222.2536245.

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2

Zhou, Zhenji, Lifa Wu, and Zheng Hong. "Context-Aware Access Control Model for Cloud Computing." International Journal of Grid and Distributed Computing 6, no. 6 (December 31, 2013): 1–12. http://dx.doi.org/10.14257/ijgdc.2013.6.6.01.

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3

Vinh, Phan Cong. "Context-Aware Computing and Nature-Inspired Computing." Mobile Networks and Applications 26, no. 3 (May 4, 2021): 1267–69. http://dx.doi.org/10.1007/s11036-021-01766-w.

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4

Vinh, Phan Cong. "Context-Aware Computing and Nature-Inspired Computing." Mobile Networks and Applications 25, no. 3 (April 20, 2020): 1122–24. http://dx.doi.org/10.1007/s11036-020-01534-2.

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5

Yan, Zheng, Xixun Yu, and Wenxiu Ding. "Context-Aware Verifiable Cloud Computing." IEEE Access 5 (2017): 2211–27. http://dx.doi.org/10.1109/access.2017.2666839.

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6

Rohn, Eli. "Predicting context aware computing performance." Ubiquity 2003, February (February 2003): 1–17. http://dx.doi.org/10.1145/764010.764011.

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Rohn, Eli. "Predicting context aware computing performance." Ubiquity 2003, February (February 2003): 1–17. http://dx.doi.org/10.1145/764014.764011.

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8

Clarke, S., and C. Driver. "Context-aware trails [mobile computing." Computer 37, no. 8 (August 2004): 97–99. http://dx.doi.org/10.1109/mc.2004.89.

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9

B., Siva Rama Krishna, and Sreenivasa Reddy E. "Improved Context Aware PSO Task Scheduling in Cloud Computing." Webology 19, no. 1 (January 20, 2022): 3709–21. http://dx.doi.org/10.14704/web/v19i1/web19244.

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One of the major advantages of switching to the clouds is the scalability ability of the applications. Contrary to the grids, the ability to scale the cloud resources allows their real-time provisioning so as to meet the application constraints Generation of optimal schedule for given set of tasks and machines. Different experiments show that although having an optimum solution is almost impossible but having a sub-optimal solution using heuristic algorithms seems possible. In this paper, we propose a Context Aware PSO Task Scheduling scheme to analyze various scenarios with different parameters in cloud computing system corresponding to APSO In each scenario, we change one parameter and keep other parameters constant.
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10

Nykänen, Ossi Antero, and Alejandro Rivero Rodriguez. "Problems in Context-Aware Semantic Computing." International Journal of Interactive Mobile Technologies (iJIM) 8, no. 3 (June 8, 2014): 32. http://dx.doi.org/10.3991/ijim.v8i3.3870.

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11

Mohan, Pooja, and Manpreet Singh. "Formal Models for Context Aware Computing." International Journal of Computer Applications Technology and Research 2, no. 1 (February 10, 2013): 53–58. http://dx.doi.org/10.7753/ijcatr0201.1011.

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12

Svahn, Fredrik, and Ola Henfridsson. "Situated Knowledge in Context-Aware Computing." International Journal of Advanced Pervasive and Ubiquitous Computing 1, no. 3 (July 2009): 23–41. http://dx.doi.org/10.4018/japuc.2009090802.

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A central feature of ubiquitous computing applications is their capability to automatically react on context changes so as to support users in their mobility. Such context awareness relies on models of specific use contexts, embedded in ubiquitous computing environments. However, since most such models are based merely on location and identity parameters, context-aware applications seldom cater for users’ situated knowledge and experience of specific contexts. This is a general user problem in well-known, but yet dynamic, user environments. Drawing on a sequential multimethod study of in-car navigation, this paper explores the role of situated knowledge in designing and using context-aware applications. This focus is motivated by the current lack of empirical investigations of context-aware applications in actual use settings. In-car navigation systems are a type of context-aware application that includes a set of contextual parameters for supporting route guidance in a volatile context. The paper outlines a number of theoretical and practical implications for context-aware application design and use.
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13

Abowd, G. D., M. R. Ebling, H. W. Gellersen, G. Hunt, and Hui Lei. "Context-aware pervasive computing [Guest Editorial]." IEEE Wireless Communications 9, no. 5 (October 2002): 8–9. http://dx.doi.org/10.1109/mwc.2002.1043848.

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14

Pintilie, Sorin. "The ethos of context-aware computing." Interactions 22, no. 4 (June 25, 2015): 20–21. http://dx.doi.org/10.1145/2770882.

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15

Abowd, G. D., M. Ebling, G. Hung, Hui Lei, and H. W. Gellersen. "Context-aware computing [Guest Editors' Intro.]." IEEE Pervasive Computing 1, no. 3 (July 2002): 22–23. http://dx.doi.org/10.1109/mprv.2002.1037718.

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16

Dey, Anind K., Gerd Kortuem, David R. Morse, and Albrecht Schmidt. "Situated Interaction and Context-Aware Computing." Personal and Ubiquitous Computing 5, no. 1 (February 2001): 1–3. http://dx.doi.org/10.1007/pl00000013.

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17

Xu, Dong, Gang Zhu, and De Zhen Xu. "Towards Checking Bigraphical Context-Aware Models." Applied Mechanics and Materials 411-414 (September 2013): 545–48. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.545.

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Context-aware computing is an important aspect of Pervasive Computing, Cyber-physical Systems (CPS), Cloud computing, etc. Recently, few works have been reported on formal approaches for this area. Bigraph was proposed as a mathematical structure that is consist of two graphs, a place graph and a link graph, intended for modeling distributed, mobile systems, etc. Bigraphs and its corresponding Bigraphical Reactive Systems (BRSs) present a modern, graphical structure, algebra calculus for the description of the syntax and semantics of systems in accordance with the orthogonal notions of connectivity and locality. Bigraphs and BRSs have been applied in various areas. Bigraph is used to formalize context-aware models in this paper. Then, we present an approach to check the formal context-aware models. The formalisms and checking are explicitly depicted through a simple but non-trivial example.
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18

Yuanping Li, Ling Feng, and Tharam Dillon. "QACA: Quality Assured Context Acquisition in Context-Aware Computing." Journal of Convergence Information Technology 6, no. 1 (January 31, 2011): 94–107. http://dx.doi.org/10.4156/jcit.vol6.issue1.12.

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19

Syukur, Evi, and Seng Wai Loke. "Implementing context-aware regulation of context-aware mobile services in pervasive computing environments." International Journal of Web and Grid Services 2, no. 3 (2006): 260. http://dx.doi.org/10.1504/ijwgs.2006.011357.

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20

Pelc, Mariusz. "Context-aware Fuzzy Control Systems." International Journal of Software Engineering and Knowledge Engineering 24, no. 05 (June 2014): 825–56. http://dx.doi.org/10.1142/s0218194014500326.

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In this paper an example of a hierarchical context-aware run-time reconfigurable control system is presented. The context-awareness is resulting from using policy-based computing as a technology allowing the control system to replace its decision making logic in run-time in response to changing environment conditions. The proposed solution allows system experts to specify policies (AGILE policies) used in the Supervision Layer for the purpose of making decisions regarding the most appropriate controller configuration and on the other side, they can specify policies (Fuzzy Logic policies) used in the Control Layer in order to generate control signals allowing to achieve specified control goals. Novelty of the proposed solutions lays in combination of two technologies, Open Decision Point technology originating from the Software Engineering domain Policy-based Computing that is originating from the Knowledge Engineering domain in application to non-linear control systems.
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21

Dourish, Paul. "Seeking a Foundation for Context-Aware Computing." Human–Computer Interaction 16, no. 2-4 (December 2001): 229–41. http://dx.doi.org/10.1207/s15327051hci16234_07.

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22

Hong, Jason I., and James A. Landay. "An Infrastructure Approach to Context-Aware Computing." Human–Computer Interaction 16, no. 2-4 (December 2001): 287–303. http://dx.doi.org/10.1207/s15327051hci16234_11.

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23

Gelogo, Yvette, Haeng-Kon Kim, and Rhan Jung. "Context-Aware Computing for Delivering u-Healthcare." International Journal of Smart Home 9, no. 8 (August 31, 2015): 169–78. http://dx.doi.org/10.14257/ijsh.2015.9.8.18.

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24

Seuster, R., CR Leavett-Brown, K. Casteels, C. Driemel, M. Paterson, D. Ring, RJ Sobie, RP Taylor, and J. Weldon. "Context-aware distributed cloud computing using CloudScheduler." Journal of Physics: Conference Series 898 (October 2017): 052039. http://dx.doi.org/10.1088/1742-6596/898/5/052039.

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25

Anhalt, J., A. Smailagic, D. P. Siewiorek, F. Gemperle, D. Salber, S. Weber, J. Beck, and J. Jennings. "Toward context-aware computing: experiences and lessons." IEEE Intelligent Systems 16, no. 3 (May 2001): 38–46. http://dx.doi.org/10.1109/5254.940025.

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26

Mcheick, Hamid. "Modeling Context Aware Features for Pervasive Computing." Procedia Computer Science 37 (2014): 135–42. http://dx.doi.org/10.1016/j.procs.2014.08.022.

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27

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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28

Mehedy, Lenin, Sungyoung Lee, Salahuddin Muhammad Salim Zabir, and Young‐Koo Lee. "Scalable and adaptive context delivery mechanism for context‐aware computing." International Journal of Pervasive Computing and Communications 4, no. 2 (June 27, 2008): 166–84. http://dx.doi.org/10.1108/17427370810890265.

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29

Campos, Nídia G. S., Danielo G. Gomes, Flávia C. Delicato, Augusto J. V. Neto, Luci Pirmez, and José Neuman de Souza. "Autonomic Context-Aware Wireless Sensor Networks." Journal of Sensors 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/621326.

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Autonomic Computing allows systems like wireless sensor networks (WSN) to self-manage computing resources in order to extend their autonomy as much as possible. In addition, contextualization tasks can fuse two or more different sensor data into a more meaningful information. Since these tasks usually run in a single centralized context server (e.g., sink node), the massive volume of data generated by the wireless sensors can lead to a huge information overload in such server. Here we propose DAIM, a distributed autonomic inference machine distributed which allows the sensor nodes to do self-management and contextualization tasks based on fuzzy logic. We have evaluated DAIM in a real sensor network taking into account other inference machines. Experimental results illustrate that DAIM is an energy-efficient contextualization method for WSN, reducing 48.8% of the number of messages sent to the context servers while saving 19.5% of the total amount of energy spent in the network.
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30

Mousa, Afaf, Jamal Bentahar, and Omar Alam. "Multi-dimensional trust for context-aware services computing." Expert Systems with Applications 172 (June 2021): 114592. http://dx.doi.org/10.1016/j.eswa.2021.114592.

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31

Moon, Aekyung, Hyoungsun Kim, Hyun Kim, and Soowoo Lee. "Context-Aware Active Services in Ubiquitous Computing Environments." ETRI Journal 29, no. 2 (April 9, 2007): 169–78. http://dx.doi.org/10.4218/etrij.07.0106.0075.

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32

Geib, Christopher, Vikas Agrawal, Gita Sukthankar, Lokendra Shastri, and Hung Bui. "Architectures for Activity Recognition and Context-Aware Computing." AI Magazine 36, no. 2 (June 21, 2015): 3–9. http://dx.doi.org/10.1609/aimag.v36i2.2578.

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33

N, Mithraa, SASIKALA N, THENMOZHI K, and PRIYANKA G. "Survey on Context Aware Computing and IoT Environment." YMER Digital 21, no. 03 (March 18, 2022): 255–66. http://dx.doi.org/10.37896/ymer21.03/29.

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Context awareness enables the system to collect the information about the environment at any time and act according to it. It makes use of hardware as well as software to collect and analyze the data automatically. The mobile users particularly the smart phone users are mostly focused by context due to it’s pliability and is often used as a part of ubiquitous and wearable computing. The Internet and upcoming technologies combine to transform every object into smart objects. Where this can be applied to user’s activities on the device or to the physical environment in which the device is being use. Here we survey the context awareness from an IoT perspective to help users by automating the task of selecting the sensors according to the problems/tasks at hand.
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34

Yamin, Adenauer Corrêa, Jorge Victória Barbosa, Iara Augustin, Luciano Cavalheiro da Silva, Rodrigo Real, Cláudio Geyer, and Gerson Cavalheiro. "Towards Merging Context-Aware, Mobile and Grid Computing." International Journal of High Performance Computing Applications 17, no. 2 (May 2003): 191–203. http://dx.doi.org/10.1177/1094342003017002008.

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35

Banavar, Guruduth, Jay Black, Ramón Cáceres, Maria Ebling, Edie Stern, and Joseph Kannry. "Deriving Long-Term Value from Context-Aware Computing." Information Systems Management 22, no. 4 (September 2005): 32–42. http://dx.doi.org/10.1201/1078.10580530/45520.22.4.20050901/90028.4.

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36

CHEN, HARRY, TIM FININ, and ANUPAM JOSHI. "An ontology for context-aware pervasive computing environments." Knowledge Engineering Review 18, no. 3 (September 2003): 197–207. http://dx.doi.org/10.1017/s0269888904000025.

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This document describes COBRA-ONT, an ontology for supporting pervasive context-aware systems. COBRA-ONT, expressed in the Web Ontology Language OWL, is a collection of ontologies for describing places, agents and events and their associated properties in an intelligent meeting-room domain. This ontology is developed as a part of the Context Broker Architecture (CoBrA), a broker-centric agent architecture that provides knowledge sharing, context reasoning and privacy protection supports for pervasive context-aware systems. We also describe an inference engine for reasoning with information expressed using the COBRA-ONT ontology and the ongoing research in using the DAML-Time ontology for context reasoning.
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37

Khan, Atta ur Rehman, Mazliza Othman, Feng Xia, and Abdul Nasir Khan. "Context-Aware Mobile Cloud Computing and Its Challenges." IEEE Cloud Computing 2, no. 3 (May 2015): 42–49. http://dx.doi.org/10.1109/mcc.2015.62.

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38

Chen, Guanling, Ming Li, and David Kotz. "Data-centric middleware for context-aware pervasive computing." Pervasive and Mobile Computing 4, no. 2 (April 2008): 216–53. http://dx.doi.org/10.1016/j.pmcj.2007.10.001.

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39

Miraoui, Moeiz, Chakib Tadj, Jaouhar Fattahi, and Chokri Ben Amar. "Dynamic Context-Aware and Limited Resources-Aware Service Adaptation for Pervasive Computing." Advances in Software Engineering 2011 (February 2, 2011): 1–11. http://dx.doi.org/10.1155/2011/649563.

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A pervasive computing system (PCS) requires that devices be context aware in order to provide proactively adapted services according to the current context. Because of the highly dynamic environment of a PCS, the service adaptation task must be performed during device operation. Most of the proposed approaches do not deal with the problem in depth, because they are either not really context aware or the problem itself is not thought to be dynamic. Devices in a PCS are generally hand-held, that is, they have limited resources, and so, in the effort to make them more reliable, the service adaptation must take into account this constraint. In this paper, we propose a dynamic service adaptation approach for a device operating in a PCS that is both context aware and limited resources aware. The approach is then modeled using colored Petri Nets and simulated using the CPN Tools, an important step toward its validation.
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40

Bradley, Nicholas, and Mark Dunlop. "Toward a Multidisciplinary Model of Context to Support Context-Aware Computing." Human-Computer Interaction 20, no. 4 (December 1, 2005): 403–46. http://dx.doi.org/10.1207/s15327051hci2004_2.

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41

Corradi, Antonio, Mario Fanelli, and Luca Foschini. "Towards Adaptive and Scalable Context Aware Middleware." International Journal of Adaptive, Resilient and Autonomic Systems 1, no. 1 (January 2010): 58–74. http://dx.doi.org/10.4018/jaras.2010071704.

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The diffusion of portable client devices is promoting the spreading of novel mobile services, both traditional such as email and printing, and new such as social computing applications, capable of opportunistically exploiting any computing resource and any wireless connectivity encountered by roaming users. The new requirements call for novel context-aware middlewares to support and simplify the retrieval and the usage of context data. However, existing context data dissemination infrastructures still present several limitations: they are unable to adaptively exploit impromptu any wireless communication opportunity; they are unable to scale, especially in wide/densely populated environments; and they are prone to connection/device flaws. The article proposes a novel context-aware middleware that achieves adaptability, scalability, and dependability in context data dissemination through three main core guidelines: by using a distributed hierarchical architecture, by employing lightweight and adaptive context data dissemination solutions, and by adopting statistical context data/query replication techniques. The performance results, obtained by extensively testing the proposed solution in our wireless university campus testbed, have validated our design choices.
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42

Cherfia, Taha Abdelmoutaleb, and Faïza Belala. "Bigraphical Reactive Systems Based Approaches for Modeling Context-Aware Systems." International Journal of Adaptive, Resilient and Autonomic Systems 5, no. 4 (October 2014): 1–19. http://dx.doi.org/10.4018/ijaras.2014100101.

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In the past few years, context-aware computing has become one of the most promising topics of ubiquitous (pervasive) computing where computers are integrated and vanish in the background of users everyday activities. A context-aware system is a ubiquitous system, which is able to adapt its behavior automatically according to the gathered context information. However, due to the increasing complexity and diversity of such systems, the modeling process has become a major challenge for the ubiquitous computing community. In order to address this critical issue, different bigraphical reactive systems based approaches have been proposed to ease the modeling of some aspects of context-aware systems. Therefore, this paper presents a study attempting to show how bigraphs work under these approaches, and to illustrate the efficiency of our proposed approach in terms of addressing various aspects of context-aware systems.
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43

G.S., Thyagaraju, and U. P. Kulkarni. "Algorithms to Resolve Conflict in Multiuser Context Aware Ubiquitous Environment." International Journal of Advanced Pervasive and Ubiquitous Computing 4, no. 3 (July 2012): 42–62. http://dx.doi.org/10.4018/japuc.2012070103.

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Conflict resolution in context-aware computing is getting more significant attention from researchers as pervasive/ubiquitous computing environments take into account multiple users and multiple applications. In multi-user ubiquitous computing environments, conflicts among user’s contexts need to be detected and resolved. Conflicts arise when multiple users try to access or try to have a control on an application. In this paper, the authors propose a series of algorithms to resolve conflict which can be embedded in different context aware applications like context aware devices (say TV, Mobile, AC, and Fan) and Context Aware Ambient (like Meeting Room, Living Room, Restaurant, Coffee Shop, etc.). The algorithms discussed in this paper make use of different tools like Probability, Fuzzy Logic, Bayesian Network and Rough set theory. In addition the algorithms utilize various factors like social, personal and environmental. The motto of this paper is to enable context aware applications to offer socialized and personalized services to multiple users by resolving service conflicts among users.
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44

Kwon, Joon Hee, and Sung Rim Kim. "Context-Aware Recommendation Using Pattern Discovery in Ubiquitous Computing." Key Engineering Materials 277-279 (January 2005): 278–86. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.278.

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Ubiquitous computing requires an intelligent environment and context-aware recommendations. This paper describes context-aware recommendations using pattern discovery in ubiquitous computing. The proposed method recommends information that may be useful without requiring any action on the part of the user by changing the user’s context. To recommend information, we discovered interesting patterns between past experiences and the current context. We explained the process, the algorithms and gave an example. Several experiments were performed and the results showed that our method has a good recommendation performance.
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45

Townsend, Anthony. "Locative-Media Artists in the Contested-Aware City." Leonardo 39, no. 4 (August 2006): 345–47. http://dx.doi.org/10.1162/leon.2006.39.4.345.

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The adoption of mobile devices as the computers of the 21st century marks a shift away from the fixed terminals that dominated the first 50 years of computing. Associated with this shift will be a new emphasis on context-aware computing. This article examines design approaches to context-aware computing and argues that the evolution of this technology will be characterized by an interplay between top-down systems for command and control and bottom-up systems for collective action. This process will lead to the emergence of “contested-aware cities,” in which power struggles are waged in public spaces with the assistance of context-aware systems.
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46

Moran, Thomas P., and Paul Dourish. "Introduction to This Special Issue on Context-Aware Computing." Human–Computer Interaction 16, no. 2-4 (December 2001): 87–95. http://dx.doi.org/10.1207/s15327051hci16234_01.

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47

Chan, A. T. S., and Siu-Nam Chuang. "MobiPADS: a reflective middleware for context-aware mobile computing." IEEE Transactions on Software Engineering 29, no. 12 (December 2003): 1072–85. http://dx.doi.org/10.1109/tse.2003.1265522.

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48

Mehra, Pankaj. "Context-Aware Computing: Beyond Search and Location-Based Services." IEEE Internet Computing 16, no. 2 (March 2012): 12–16. http://dx.doi.org/10.1109/mic.2012.31.

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49

El Khaddar, Mehdia Ajana, Mhammed Chraibi, Hamid Harroud, Mohammed Boulmalf, Mohammed Elkoutbi, and Abdelilah Maach. "A policy-based middleware for context-aware pervasive computing." International Journal of Pervasive Computing and Communications 11, no. 1 (April 7, 2015): 43–68. http://dx.doi.org/10.1108/ijpcc-07-2014-0039.

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Purpose – This paper aims to demonstrate that a policy-based middleware solution which facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. Ubiquitous computing targets the provision of seamless services and applications by providing an environment that involves a variety of devices having different capabilities. These applications help transforming the physical spaces into computationally active and smart environments. The design of applications in these environments needs to consider the heterogeneous devices, applications preferences and rapidly changing contexts. The applications, therefore, need to be context-aware so that they can adapt to different situations in real-time. Design/methodology/approach – In this paper, we argue that a policy-based middleware solution that facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. The middleware allows applications to track items and acquire contextual information about them easily, reason about this information captured using different logics and then adapt to changing contexts. A key issue in these environments is to allow heterogeneous applications to express their business rules once, and get the preferred data once they are captured by the middleware without any intervention from the application side. Findings – Our middleware tackles this problem by using policies to define the different applications’ rules and preferences. These policies can specify rules about the middleware services to be used, type of data captured, devices used, user roles, context information and any other type of conditions. Originality/value – In this paper, we propose the design of a flexible and performant ubiquitous computing, and context-aware middleware called FlexRFID along with its evaluation results.
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50

Lee, Tae-Dong, Byung Moo Lee, and Wonjong Noh. "Hierarchical Cloud Computing Architecture for Context-Aware IoT Services." IEEE Transactions on Consumer Electronics 64, no. 2 (May 2018): 222–30. http://dx.doi.org/10.1109/tce.2018.2844724.

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