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Journal articles on the topic 'Adaptive interface'

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Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Hasan, Sajib. "Adaptive Fitts for Adaptive Interface." AIUB Journal of Science and Engineering (AJSE) 17, no. 2 (July 31, 2018): 51–58. http://dx.doi.org/10.53799/ajse.v17i2.9.

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Adaptive interface would enable Human Computer Interaction apply machine learning to cope with human carelessness (mistakes), understand user performance level and provide an interaction interface accordingly. This study tends to translate the theoretical issues of human task into working model by investigating and implementing the predicting equation of human psychomotor behavior to a rapid and aimed movement, developed by Paul Fitt in 1954. The study finds logarithmic speed-accuracy trade-off and predict user performance in a common task “point-select” using common input device mouse. The performance of user is visualized as an evidence and this visualization make a valuable step toward understanding the change required in user interface to make the interface adaptive and consistent. It proposed a method of calculating the amount of change required through learning; add extension to the theory of machine intelligence and increase knowledge of Fitts applicability in terms of machine learning.

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2

Gong, Qing, and Gavriel Salvendy. "Design of Skill-Based Adaptive Interface: The Effect of a Gentle Push." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 4 (October 1994): 295–99. http://dx.doi.org/10.1177/154193129403800423.

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To accommodate individual skill differences in using a computer interface, a skill adaptive interface was designed and tested. Current human-computer interaction modes can be classified into two types, recall and recognition based interfaces. They have different memory requirements and generally allow different operating speeds and learning time. However, a static combination of the two interface modes has drawbacks. The dynamic skill adaptive interface introduced in this study tries to eliminate these problems without sacrificing the advantages from either interface modes by gently ‘pushing’ users to switch to the appropriate interface mode. Experiment showed that the adaptive interface can yield significant better performances than the static hybrid interface for certain groups of users.

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3

Marsh, William E., Jonathan W. Kelly, Julie Dickerson, and James H. Oliver. "Fuzzy Navigation Engine: Mitigating the Cognitive Demands of Semi-Natural Locomotion." Presence: Teleoperators and Virtual Environments 23, no. 3 (October 1, 2014): 300–319. http://dx.doi.org/10.1162/pres_a_00195.

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Many interfaces exist for locomotion in virtual reality, although they are rarely considered fully natural. Past research has found that using such interfaces places cognitive demands on the user, with unnatural actions and concurrent tasks competing for finite cognitive resources. Notably, using semi-natural interfaces leads to poor performance on concurrent tasks requiring spatial working memory. This paper presents an adaptive system designed to track a user's concurrent cognitive task load and adjust interface parameters accordingly, varying the extent to which movement is fully natural. A fuzzy inference system is described and the results of an initial validation study are presented. Users of this adaptive interface demonstrated better performance than users of a baseline interface on several movement metrics, indicating that the adaptive interface helped users manage the demands of concurrent spatial tasks in a virtual environment. However, participants experienced some unexpected difficulties when faced with a concurrent verbal task.

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Eray, Ekin, Benjamin Sanchez, and Carl Haas. "Usage of Interface Management System in Adaptive Reuse of Buildings." Buildings 9, no. 5 (April 30, 2019): 105. http://dx.doi.org/10.3390/buildings9050105.

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Adaptive reuse of buildings is considered a superior alternative for new construction in terms of sustainability and a disruptive practice in the current capital project delivery model for the renewal of today’s built environment. In comparison to green-field construction projects, adaptive reuse projects require distinct stages, definition of interfaces, decision gates, and planning methods in order to secure the success of the building project. Unfortunately, little research has been done regarding establishing feasible systems for the planning, assessment, and management of adaptive reuse projects, leading to underperforming building projects outcomes. Interface management (IM) can improve renovation projects outcomes by defining appropriate ways to identify, record, monitor, and track project interfaces. IM has the potential of bringing cost and time benefits during adaptive reuse projects execution. The aim of this study is to develop a reference framework for implementing IM for adaptive reuse projects. First, the inefficiencies of redevelopment projects are explained inside of a circular economy (CE) context. Second, an ontology of IM for adaptive reuse projects is defined based on the current barriers to adaptive reuse and the most common interface problems in construction projects. Third, the defined ontology is expanded through a case study by showing examples of adaptive reuse barriers on a case project, and how IM could have been part of the solution for these problems. Finally, this study concludes with the suggestions on interface management systems (IMS) implementation for future adaptive reuse projects.

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5

OHTA, Tokio. "Adaptive Complexity and Interface Science." Hyomen Kagaku 18, no. 8 (1997): 510–11. http://dx.doi.org/10.1380/jsssj.18.510.

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6

Dusan, Sorin, and James Flanagan. "Adaptive interface for spoken dialog." Journal of the Acoustical Society of America 111, no. 5 (2002): 2481. http://dx.doi.org/10.1121/1.4778628.

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7

Popovic, Jelena, and Olof Runborg. "Adaptive fast interface tracking methods." Journal of Computational Physics 337 (May 2017): 42–61. http://dx.doi.org/10.1016/j.jcp.2017.02.017.

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8

Zhao, Meng, Wenjun Ying, John Lowengrub, and Shuwang Li. "An Efficient Adaptive Rescaling Scheme for Computing Moving Interface Problems." Communications in Computational Physics 21, no. 3 (February 7, 2017): 679–91. http://dx.doi.org/10.4208/cicp.oa-2016-0040.

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AbstractIn this paper, we present an efficient rescaling scheme for computing thelong-timedynamics of expanding interfaces. The idea is to design an adaptive time-space mapping such that in the new time scale, the interfaces evolves logarithmically fast at early growth stage and exponentially fast at later times. The new spatial scale guarantees the conservation of the area/volume enclosed by the interface. Compared with the original rescaling method in [J. Comput. Phys. 225(1) (2007) 554–567], this adaptive scheme dramatically improves the slow evolution at early times when the size of the interface is small. Our results show that the original three-week computation in [J. Comput. Phys. 225(1) (2007) 554–567] can be reproduced in about one day using the adaptive scheme. We then present the largest and most complicated Hele-Shaw simulation up to date.

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9

Zaman, Atif, Mudassar Ahmad, Shafique Ahamd, and Tasleem Mustafa. "Adaptive Graphical User Interface for Web Applications Using Aspect Oriented Component Engineering." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 2 (August 5, 2013): 1384–92. http://dx.doi.org/10.24297/ijct.v10i2.3304.

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Graphical User Interface (GUI) is considered to be an essential part in any web applications development. Aspect-Oriented Component Engineering (AOCE) is new approach for developing more and higher quality reusable and adaptable software or web applications components. AOCE uses the idea of providing and requiring services. Adaptable user interface for AOCE based development has not yet been considered to web applications. Simple and easy user interface facilitate users by which application or web interface can be operated effectively. The purpose of this study is to discuss popular user interfaces and suggestions for adaptable GUI designing. The example of adaptation at different levels includes architecture, presentation, extension and composition. Furthermore the AOCE common systemic aspects are discussed for web interfaces adaptivity.

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10

Bunt, Andrea, Cristina Conati, and Joanna McGrenere. "Mixed-Initiative Interface Personalization as a Case Study in Usable AI." AI Magazine 30, no. 4 (January 2, 2010): 58. http://dx.doi.org/10.1609/aimag.v30i4.2264.

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Interface personalization aims to streamline the process of working in a feature-rich application by providing the user with an adapted interface tailored specifically to his/her needs. The MICA (Mixed-Initiative Customization Assistance) system explores a middle ground between two opposing approaches to personalization: (1) an adaptable approach, where personalization is fully user controlled and (2) and adaptive approach, where personalization is fully system controlled. We overview MICA’s strategy for providing user-adaptive recommendations to help users decide how to personalize their interfaces. In doing so, we focus primarily on how MICA handles threats to usability that are often found in adaptive interfaces including obtrusiveness and lack of understandability and control. We also describe how we evaluated MICA and highlight results from these evaluations.

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11

Feng, Jiangfan, and Yanhong Liu. "Intelligent Context-Aware and Adaptive Interface for Mobile LBS." Computational Intelligence and Neuroscience 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/489793.

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Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users’ demands in a complicated environment and suggested the feasibility by the experimental results.

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12

ZHENG, H. W., X. J. LI, G. W. YANG, and C. SHU. "INTERACTION OF SHOCK WAVE WITH MULTI-FLUIDS INTERFACE USING QUADRILATERAL-BASED ADAPTIVE MESH." International Journal of Modern Physics C 23, no. 05 (May 2012): 1250033. http://dx.doi.org/10.1142/s0129183112500337.

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In this paper, the interaction of shock waves with multi-fluids interfaces is investigated by numerical simulations using unstructured quadrilateral adaptive meshes. In order to obtain a detailed structure of the interface, a solution adaptive method for compressible multi-fluid flows developed by Zheng et al. is employed. Firstly, the method is verified by a planar shock and interface interaction problem, which is compared with the front tracking method for the Richtmyer–Meshkov instability problem. Following the verification, the interaction between a circular shock and a sinusoidally perturbed circular interface in cylinder vessel is firstly investigated in our paper. The results show that the solution adaptive method can be employed to study the compressible multi-fluid cases with relatively complex geometry as well as capturing the fine details of interfacial structures of the interaction.

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13

Di, Yana. "An Adaptive Fast Interface Tracking Method." Journal of Computational Mathematics 33, no. 6 (June 2015): 576–86. http://dx.doi.org/10.4208/jcm.1503-m4532.

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14

Shakshuki, Elhadi M., Malcolm Reid, and Tarek R. Sheltami. "An Adaptive User Interface in Healthcare." Procedia Computer Science 56 (2015): 49–58. http://dx.doi.org/10.1016/j.procs.2015.07.182.

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15

Ravi, Ramya, Ashwini Kumar, Kamal Bijlani, and T. R. Sharika. "Self-Adaptive Interface for Comprehensive Authoring." Procedia Computer Science 58 (2015): 158–64. http://dx.doi.org/10.1016/j.procs.2015.08.044.

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16

Yoshikawa, H., and M. Takahashi. "Conceptual Design of Mutual Adaptive Interface." IFAC Proceedings Volumes 28, no. 23 (September 1995): 243–48. http://dx.doi.org/10.1016/s1474-6670(17)46625-0.

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17

Heger, A. Sharif, and Billy V. Koen. "KNOWBOT: An Adaptive Data Base Interface." Nuclear Science and Engineering 107, no. 2 (February 1991): 142–57. http://dx.doi.org/10.13182/nse91-a15728.

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18

Narayanan, S., Lavanya Koppaka, Narasimha Edala, Don Loritz, and Raymond Daley. "Adaptive Interface for Personalizing Information Seeking." CyberPsychology & Behavior 7, no. 6 (December 2004): 683–88. http://dx.doi.org/10.1089/cpb.2004.7.683.

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19

Howell, Colby Chambers. "The Morphing Waldo:An adaptive user interface." Performance Improvement 40, no. 7 (August 2001): 16–19. http://dx.doi.org/10.1002/pfi.4140400705.

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20

Glinert, Ephraim P., R. Lindsay Todd, and G. Bowden Wise. "The adaptive multi-interface multimodal environment." ACM Computing Surveys 28, no. 4es (December 1996): 134. http://dx.doi.org/10.1145/242224.242394.

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21

Dafali, Rachid, Jean-Philippe Diguet, and Jean-Charles Creput. "Self-Adaptive Network-on-Chip Interface." IEEE Embedded Systems Letters 5, no. 4 (December 2013): 73–76. http://dx.doi.org/10.1109/les.2013.2285175.

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22

Qu, Zheng, and Elliot L. Chaikof. "Interface between hemostasis and adaptive immunity." Current Opinion in Immunology 22, no. 5 (October 2010): 634–42. http://dx.doi.org/10.1016/j.coi.2010.08.017.

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23

Kolekar, Sucheta V., Radhika M. Pai, and Manohara Pai M. M. "Rule based adaptive user interface for adaptive E-learning system." Education and Information Technologies 24, no. 1 (August 23, 2018): 613–41. http://dx.doi.org/10.1007/s10639-018-9788-1.

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24

Ho, Anson, Catherine Maritan, Jeffery Sullivan, Eric Cheng, and Shi Cao. "Measuring Glance Legibility of Wearable Heads-Up Display Interfaces Using an Adaptive Staircase Procedure." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 2073–77. http://dx.doi.org/10.1177/1541931213601470.

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Heads-up displays (HUDs) are growing in popularity and utility, providing novel ways to interact with environments and other individuals. HUD interfaces must allow users to quickly view information without distracting them from their primary task. We test the use of an adaptive staircase as a method to investigate the glance legibility of two Google Glass heads-up display interfaces. Glance legibility refers to an interface’s legibility when viewed in short amounts of time (also known as glance-like conditions). We measure glance legibility by the minimum presentation time required to read an interface and respond correctly to a yes-no question. The applications of this research can help inform the design and evaluation of future heads-up display interfaces under glance-like conditions.

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25

Al-Nabulsi, Jamal I., and Bashar E. A. Badr. "Adaptive gender-based thermal control system." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 2 (April 1, 2021): 1200. http://dx.doi.org/10.11591/ijece.v11i2.pp1200-1207.

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A closed loop adaptive gender-based thermal control system (AG-TCS) is designed, modelled, analysed and tested. The system has the unique feature of adapting to the surrounding environment as a function of the number of humans present and the gender ratio. The operation of the system depends on a unique interface between a radio frequency identification (RFID) device and an imaging device, both of which are correlated and interfaced to a controller. Testing of the system resulted in smooth transition and shape conversion of the response curve, which proved its adaptability. Three mathematical equations describing the internal mechanisms of the AG-TCS are presented and have been proven to optimally reflect the original statistical data covering both genders.

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26

KIM, MIHUI, YUKYONG JUNG, and KIJOON CHAE. "ADAPTIVE DATA MINING APPROACH FOR FLOW REDIRECTION IN MULTIHOMED MOBILE ROUTER." International Journal of Information Technology & Decision Making 09, no. 05 (September 2010): 737–58. http://dx.doi.org/10.1142/s0219622010004081.

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On multihomed mobile router with several interfaces toward Internet, it is important to provide an efficient flow redirection (FR) method that changes the served interface according to each network status or user movement. However, currently as the mobile devices roams, the interface is selected as only the physical signal strength, thus efficient resource use or quality of service (QoS) support is not guaranteed. In this paper, we propose an adaptive data mining approach that provides the selection of influential attributes for FR and the proper FR decision model as the interface type. We analyze assuming network protocols in order to heuristically extract the FR candidate attributes for estimating the required QoS. We abstract theoretically the FR influential attributes through decision-tree algorithm, and finally obtain the proper FR decision models per each interface. Our simulation results show that our FR approach provides improved performances in comparison with current handover.

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27

Braham, Buendía, Khemaja, and Gargouri. "Generation of Adaptive Mobile Applications Based on Design Patterns for User Interfaces." Proceedings 31, no. 1 (November 20, 2019): 19. http://dx.doi.org/10.3390/proceedings2019031019.

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Generating mobile apps represents a big challenge in several areas, such as considering audience needs, adapting their user interfaces to such needs, dealing with design constraints or using different development technologies. The present work seeks to examine how design patterns can help to support the generation of this kind of adaptive mobile application. In particular, design patterns related to user interfaces are reviewed, and an ontology-based framework is proposed to manage their pattern descriptions and associated rules. Such a framework enables a more versatile and powerful organization of mobile interface items, as well as their adaptation to context changes and user requirements in specific scenarios. An example of adaptive mobile application has been developed to show the suitability of the proposed framework, and the application usability has been evaluated in terms of satisfaction, learnability, and efficiency.

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DING, L., C. SHU, and N. ZHAO. "NUMERICAL SIMULATION OF DAM BREAK BY ADAPTIVE STENCIL DIFFUSE INTERFACE METHOD." Modern Physics Letters B 23, no. 03 (January 30, 2009): 293–96. http://dx.doi.org/10.1142/s0217984909018230.

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This paper presents the application of an adaptive stencil diffuse interface method to the simulation of dam break problem. The adaptive stencil diffuse interface method is the combination of the diffuse interface method and a stencil adaptive algorithm, where the diffuse interface method is used as the solver, and the adaptive stencil refinement scheme is applied to improve the resolution around the interface so that the fine-scale interface behavior can be captured. In this paper, we use this method to simulate the dam break problem, study the dam height and leading edge position, and compare our results with the experiment data available in the literature. It is shown that the results using the adaptive stencil diffuse interface method agree very well with the experimental results.

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sci, Yanzhen Chang. "The Adaptive Immersed Interface Finite Element Method for Elasticity Interface Problems." Journal of Computational Mathematics 30, no. 6 (June 2012): 629–42. http://dx.doi.org/10.4208/jcm.1203-m3869.

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30

Miraz, Mahdi H., Maaruf Ali, and Peter S. Excell. "Adaptive user interfaces and universal usability through plasticity of user interface design." Computer Science Review 40 (May 2021): 100363. http://dx.doi.org/10.1016/j.cosrev.2021.100363.

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31

Atanasova, Margarita, and Anna Malinova. "TRANSFORMING CONCUR TASK TREES MODEL INTO AN ABSTRACT USER INTERFACE." CBU International Conference Proceedings 5 (September 24, 2017): 1036–41. http://dx.doi.org/10.12955/cbup.v5.1067.

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Business applications are difficult to use for the average user. An adaptive user interface improves employeesâ€™ productivity and is presented as a solution to this problem. However, developing user interfaces that are adapted to the needs and culture of the enterprise is time-consuming and expensive. We developed a software prototype for generating adaptive user interfaces that makes this process less time-consuming and more efficient. We propose an extension to the Cameleon Reference Framework project by Information Society Technologies, on the implementation level by adding an additional step for defining the Area of Business Operations. That way the prototype can extract business tasks for the selected industry therefore, presenting to the developer a more intelligent selection of predefined tasks. In this article, we also present a programming approach for transforming a task model, as defined by the ConcurTaskTrees notation, into an abstract user interface.

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32

Xue, Qing, Xuan Han, Mingrui Li, and Minxia Liu. "A Conceptual Architecture for Adaptive Human-Computer Interface of a PT Operation Platform Based on Context-Awareness." Discrete Dynamics in Nature and Society 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/371204.

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We present a conceptual architecture for adaptive human-computer interface of a PT operation platform based on context-awareness. This architecture will form the basis of design for such an interface. This paper describes components, key technologies, and working principles of the architecture. The critical contents covered context information modeling, processing, relationship establishing between contexts and interface design knowledge by use of adaptive knowledge reasoning, and visualization implementing of adaptive interface with the aid of interface tools technology.

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33

Ma, Xin Sheng, and Rui Zheng. "Adaptive Interface Design for Process Management System." Applied Mechanics and Materials 644-650 (September 2014): 6214–17. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.6214.

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This paper describes an adaptive interface design that is suitable for process management system which is an important component of e-government. Bayesian network model is adopted for updating the layout of modules on the interface based on the user's operating data. Not only the number of modules will change, the positions of the modules can also update according to the calculation results. The experiment is conducted on a real college scientific research management system. Response time and click rates are used for evaluating the effectiveness of the algorithm, and the result shows that the value of these indicators declines obviously. Therefore, the method is proved to work.

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34

Hancock, P. A., and M. H. Chignell. "Mental workload dynamics in adaptive interface design." IEEE Transactions on Systems, Man, and Cybernetics 18, no. 4 (July 1988): 647–58. http://dx.doi.org/10.1109/21.17382.

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35

Park, Heon, and JangMyung Lee. "Adaptive impedance control of a haptic interface." Mechatronics 14, no. 3 (April 2004): 237–53. http://dx.doi.org/10.1016/s0957-4158(03)00040-0.

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36

Hoebe, Kasper, Edith Janssen, and Bruce Beutler. "The interface between innate and adaptive immunity." Nature Immunology 5, no. 10 (October 2004): 971–74. http://dx.doi.org/10.1038/ni1004-971.

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37

Hudlicka, Eva, and John Billingsley. "Abais: Affect and Belief Adaptive Interface System." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 43, no. 3 (September 1999): 369–73. http://dx.doi.org/10.1177/154193129904300351.

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38

Berger, Helmut, Michael Dittenbach, and Dieter Merkl. "An adaptive multilingual interface for tourism information." International Journal of Electronic Business 2, no. 5 (2004): 531. http://dx.doi.org/10.1504/ijeb.2004.005903.

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39

FanJiang, Yong Yi, and Ting Fang Chueh. "Adaptive user interface for universal remote controller." International Journal of Computational Science and Engineering 10, no. 1/2 (2015): 90. http://dx.doi.org/10.1504/ijcse.2015.067060.

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40

Akiki, Pierre A., Arosha K. Bandara, and Yijun Yu. "Adaptive Model-Driven User Interface Development Systems." ACM Computing Surveys 47, no. 1 (July 2014): 1–33. http://dx.doi.org/10.1145/2597999.

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Martinel, Niki, Christian Micheloni, Claudio Piciarelli, and Gian Luca Foresti. "Camera Selection for Adaptive Human-Computer Interface." IEEE Transactions on Systems, Man, and Cybernetics: Systems 44, no. 5 (May 2014): 653–64. http://dx.doi.org/10.1109/tsmc.2013.2279661.

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42

Amirghodsi, Siamak, and Farnoud Daneshbodi. "4974191 Adaptive natural language computer interface system." Computer Languages 17, no. 2 (April 1992): i. http://dx.doi.org/10.1016/0096-0551(92)90005-8.

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43

Rosenthal, Jeffrey S. "AMCMC: An R interface for adaptive MCMC." Computational Statistics & Data Analysis 51, no. 12 (August 2007): 5467–70. http://dx.doi.org/10.1016/j.csda.2007.02.021.

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44

Germain‐Renaud, Cécile, and Vincent Néri. "Java-Based Coupling for Parallel Predictive-Adaptive Domain Decomposition." Scientific Programming 7, no. 2 (1999): 185–89. http://dx.doi.org/10.1155/1999/812589.

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Adaptive domain decomposition exemplifies the problem of integrating heterogeneous software components with intermediate coupling granularity. This paper describes an experiment where a data‐parallel (HPF) client interfaces with a sequential computation server through Java. We show that seamless integration of data‐parallelism is possible, but requires most of the tools from the Java palette: Java Native Interface (JNI), Remote Method Invocation (RMI), callbacks and threads.

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45

Sukaviriya, P. "From user interface design to the support of intelligent and adaptive interfaces: an overhaul of user interface software infrastracture." Knowledge-Based Systems 6, no. 4 (December 1993): 220–29. http://dx.doi.org/10.1016/0950-7051(93)90013-j.

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46

Ma, Teng, Fali Li, Peiyang Li, Dezhong Yao, Yangsong Zhang, and Peng Xu. "An Adaptive Calibration Framework for mVEP-Based Brain-Computer Interface." Computational and Mathematical Methods in Medicine 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/9476432.

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Electroencephalogram signals and the states of subjects are nonstationary. To track changing states effectively, an adaptive calibration framework is proposed for the brain-computer interface (BCI) with the motion-onset visual evoked potential (mVEP) as the control signal. The core of this framework is to update the training set adaptively for classifier training. The updating procedure consists of two operations, that is, adding new samples to the training set and removing old samples from the training set. In the proposed framework, a support vector machine (SVM) and fuzzy C-mean clustering (fCM) are combined to select the reliable samples for the training set from the blocks close to the current blocks to be classified. Because of the complementary information provided by SVM and fCM, they can guarantee the reliability of information fed into classifier training. The removing procedure will aim to remove those old samples recorded a relatively long time before current new blocks. These two operations could yield a new training set, which could be used to calibrate the classifier to track the changing state of the subjects. Experimental results demonstrate that the adaptive calibration framework is effective and efficient and it could improve the performance of online BCI systems.

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47

Taktak, Hajer, and Faouzi Moussa. "A service-oriented application creation process in ubiquitous environments." International Journal of Pervasive Computing and Communications 13, no. 3 (September 4, 2017): 300–330. http://dx.doi.org/10.1108/ijpcc-10-2016-0054.

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Purpose Many features constitute an adaptive system such as user model, interface specification, business functionalities and service implementation. Context awareness is an important facet of service oriented application creation dealing with the gathering, use and representation of context information. Generally, user interfaces and services communities work separately on the adaptation process and do not converge. The aim of this work is to manage the system’s functionalities and the user interface that delivers data to the relevant consumer early since the design phase until the code generation. Design/methodology/approach The authors discuss how a unified method based on a model-driven architecture for adaptive user interface and pervasive service creation eases the work of designers and developers, limits incompatibility issues and supports dynamic generation of systems adapted to different contexts of use. Findings The proposed approach is able to support a semi-automatic ubiquitous application generation with service, behavior, presentation and content adaptation. Originality/value In this paper, the authors tackle context-awareness at two levels: system functionalities and user interface generation. The authors also tackle adaptation at the specification and implementation levels.

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Heinssen, Sascha, Theodor Hillebrand, Maike Taddiken, Steffen Paul, and Dagmar Peters-Drolshagen. "On-Line Error Correction in Sensor Interface Circuits by Using Adaptive Filtering and Digital Calibration." Proceedings 2, no. 13 (November 30, 2018): 963. http://dx.doi.org/10.3390/proceedings2130963.

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Abstract:

Numerous non-ideal effects can distort the functionality of sensor interfaces and have to be considered during the design phase. In order to relax the requirements for the analog circuit components, adaptive filtering and digital calibration are used in this work to detect and correct different gain- and offset-errors. The error detection is performed by transmitting a test signal through the sensor interface continuously and in parallel to the sensor signal. In the digital domain, variations of the test signal are evaluated and present errors can be determined and eliminated. In this way, an on-line error correction is realized, which makes the sensor interface more robust against static and dynamic non-idealities. The proposed concept is demonstrated by correcting different gain- and offset-errors in a 65nm CMOS sensor interface.

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49

Menkhaus, Guido, and Wolfgang Pree. "A Hybrid Approach to Adaptive User Interface Generation." Journal of Computing and Information Technology 10, no. 3 (2002): 171. http://dx.doi.org/10.2498/cit.2002.03.04.

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50

Ishiwaka, Yuko, Hiroshi Yokoi, and Yukinori Kakazu. "EEG on-line analysis for autonomous adaptive interface." International Congress Series 1232 (April 2002): 271–75. http://dx.doi.org/10.1016/s0531-5131(01)00721-x.

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