An adaptive approach for image organisation and retrieval

We propose and evaluate an adaptive approach towards content-based image retrieval (CBIR), which is based on the Ostensive Model of developing information needs. We use ostensive relevance to capture the user's current interest and tailor the retrieval accordingly. Our approach supports content-assisted browsing, by incorporating an adaptive query learning scheme based on implicit feedback from the user. Textual and colour features are employed to characterise images. Evidence from these features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, task-oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. Its strengths are considered to lie in its ability to adapt to the user's need, and its very intuitive and fluid way of operation

An adaptive technique for content-based image retrieval

We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs—a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search

Evaluation of an adaptive game that uses EEG measures validated during the design process as inputs to a Biocybernetic Loop

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed

Situated play in a tangible interface and adaptive audio museum guide

This paper explores the design issues of 9 situated play within a museum through the study of a 10 museum guide prototype that integrates a tangible interface, audio display, and adaptive modeling. We discuss our use of design ethnography in order to situate our interaction and to investigate the liminal and engagement qualities of a museum visit. The paper provides an overview of our case study and analysis of our user evaluation. We discuss the implications including degrees of balance in the experience design of play in interaction; the challenge in developing a discovery-based information model, and the need for a better understanding of the contextual aspects of tangible user interfaces (TUIs). We conclude that learning effectiveness and functionality can be balanced productively with playful interaction through an adaptive audio and TUI if designers balance the engagement between play and the environment, and the space between imagination and interpretation that links the audio content to the artifacts

Adaptive physical human-robot interaction (PHRI) with a robotic nursing assistant.

Recently, more and more robots are being investigated for future applications in health-care. For instance, in nursing assistance, seamless Human-Robot Interaction (HRI) is very important for sharing workspaces and workloads between medical staff, patients, and robots. In this thesis we introduce a novel robot - the Adaptive Robot Nursing Assistant (ARNA) and its underlying components. ARNA has been designed specifically to assist nurses with day-to-day tasks such as walking patients, pick-and-place item retrieval, and routine patient health monitoring. An adaptive HRI in nursing applications creates a positive user experience, increase nurse productivity and task completion rates, as reported by experimentation with human subjects. ARNA has been designed to include interface devices such as tablets, force sensors, pressure-sensitive robot skins, LIDAR and RGBD camera. These interfaces are combined with adaptive controllers and estimators within a proposed framework that contains multiple innovations. A research study was conducted on methods of deploying an ideal HumanMachine Interface (HMI), in this case a tablet-based interface. Initial study points to the fact that a traded control level of autonomy is ideal for tele-operating ARNA by a patient. The proposed method of using the HMI devices makes the performance of a robot similar for both skilled and un-skilled workers. A neuro-adaptive controller (NAC), which contains several neural-networks to estimate and compensate for system non-linearities, was implemented on the ARNA robot. By linearizing the system, a cross-over usability condition is met through which humans find it more intuitive to learn to use the robot in any location of its workspace, A novel Base-Sensor Assisted Physical Interaction (BAPI) controller is introduced in this thesis, which utilizes a force-torque sensor at the base of the ARNA robot manipulator to detect full body collisions, and make interaction safer. Finally, a human-intent estimator (HIE) is proposed to estimate human intent while the robot and user are physically collaborating during certain tasks such as adaptive walking. A NAC with HIE module was validated on a PR2 robot through user studies. Its implementation on the ARNA robot platform can be easily accomplished as the controller is model-free and can learn robot dynamics online. A new framework, Directive Observer and Lead Assistant (DOLA), is proposed for ARNA which enables the user to interact with the robot in two modes: physically, by direct push-guiding, and remotely, through a tablet interface. In both cases, the human is being “observed” by the robot, then guided and/or advised during interaction. If the user has trouble completing the given tasks, the robot adapts their repertoire to lead users toward completing goals. The proposed framework incorporates interface devices as well as adaptive control systems in order to facilitate a higher performance interaction between the user and the robot than was previously possible. The ARNA robot was deployed and tested in a hospital environment at the School of Nursing of the University of Louisville. The user-experience tests were conducted with the help of healthcare professionals where several metrics including completion time, rate and level of user satisfaction were collected to shed light on the performance of various components of the proposed framework. The results indicate an overall positive response towards the use of such assistive robot in the healthcare environment. The analysis of these gathered data is included in this document. To summarize, this research study makes the following contributions: Conducting user experience studies with the ARNA robot in patient sitter and walker scenarios to evaluate both physical and non-physical human-machine interfaces. Evaluation and Validation of Human Intent Estimator (HIE) and Neuro-Adaptive Controller (NAC). Proposing the novel Base-Sensor Assisted Physical Interaction (BAPI) controller. Building simulation models for packaged tactile sensors and validating the models with experimental data. Description of Directive Observer and Lead Assistance (DOLA) framework for ARNA using adaptive interfaces

An adaptive user interface model for contact centres

Contact centres (CC), are the primary interaction point between a company and its customers and these are rapidly expanding in terms of both workforce and economic scope. An important challenge for today's CC solutions is to increase the speed at which CCAs retrieve information to answer customer queries. CCAs, however, differ in their ability to respond to these queries and do not interact with the computer user interface (UI) in the same way as they each have different capabilities, experience and expertise. Studies have provided empirical support that user performance can be increased when the computer UI characteristics match the user skill level. Adaptive user interfaces (AUIs) are the key to creating personalised systems. Their sole task is to provide an interface most suitable to users' needs whilst facilitating the users' varying skill levels. The aim of this research was to develop an AUI model for CCs to support and improve the expertise level of CCAs. A literature review of CCs, user expertise, AUIs and existing AUI models resulted in the proposal of an AUI model for CCs. The proposed AUI model was described in terms of its architecture, component-level and interface design. An AUI prototype was developed as a proof-of-concept of the proposed AUI model. A literature review on existing AUI evaluation approaches resulted in an evaluation strategy for the proposed AUI model. The AUI prototype was evaluated according to the evaluation strategy that was identified. User testing incorporating eye-tracking and a post-test questionnaire was used to determine the usefulness and usability of the AUI prototype. Significant results were found with regards to user satisfaction ratings, the learnability of the AUI prototype and its effectiveness. This dissertation makes an important contribution in the design of an AUI model that supports and improves the expertise level of CCAs. The model could be used to assist the development of CC applications incorporating AUIs. Future research is however needed to evaluate the effect of the proposed AUI model in a larger CC environment

An adaptive user interface model for contact centres

Contact centres (CC), are the primary interaction point between a company and its customers and these are rapidly expanding in terms of both workforce and economic scope. An important challenge for today's CC solutions is to increase the speed at which CCAs retrieve information to answer customer queries. CCAs, however, differ in their ability to respond to these queries and do not interact with the computer user interface (UI) in the same way as they each have different capabilities, experience and expertise. Studies have provided empirical support that user performance can be increased when the computer UI characteristics match the user skill level. Adaptive user interfaces (AUIs) are the key to creating personalised systems. Their sole task is to provide an interface most suitable to users' needs whilst facilitating the users' varying skill levels. The aim of this research was to develop an AUI model for CCs to support and improve the expertise level of CCAs. A literature review of CCs, user expertise, AUIs and existing AUI models resulted in the proposal of an AUI model for CCs. The proposed AUI model was described in terms of its architecture, component-level and interface design. An AUI prototype was developed as a proof-of-concept of the proposed AUI model. A literature review on existing AUI evaluation approaches resulted in an evaluation strategy for the proposed AUI model. The AUI prototype was evaluated according to the evaluation strategy that was identified. User testing incorporating eye-tracking and a post-test questionnaire was used to determine the usefulness and usability of the AUI prototype. Significant results were found with regards to user satisfaction ratings, the learnability of the AUI prototype and its effectiveness. This dissertation makes an important contribution in the design of an AUI model that supports and improves the expertise level of CCAs. The model could be used to assist the development of CC applications incorporating AUIs. Future research is however needed to evaluate the effect of the proposed AUI model in a larger CC environment

Dynamic exploration of helicopter reconnaissance through agent-based modeling

This thesis uses Multi-Agent System modeling to develop a simulation of tactical helicopter performance while conducting armed reconnaissance. It focuses on creating a model to support planning for the Test and Evaluation phas of the Comanche helicopter acquisition cycle. The model serves as an initial simulation laboratory for scenario planning, requirements forecasting, and platform comparison analyses. The model implements adaptive tactical movement with agent sensory and weaponry system characteristics. Agents are able to determine their movement direction and paths based on their perceived environment, attributes, and movement personalities. The model incorporates a three-dimensional aspect to properly simulate aerial reconnaissance. An integrated Graphical User Interface enables the user to create environments, instantiate agent propensities and attributes, set simulation parameters, and analyze statistical output. The resulting model demonstrates the ability to represent helicopter reconnaissance behavior. It captures simulation summary statistics that illustrate enemy performance, helicopter performance, and logistical requirements. The model establishes an initial simulation tool to further explore Comanche operational requirements and planning foi its Test and Evaluation phase. 14. SUBJECT TERMS 15. NUMBER OF Multi-Agent System, Agent- Based Modeling, Helicopter Reconnaissance, Comanche, Adaptive PAGES 140 Behavior, Modeling and Simulationhttp://www.archive.org/details/dynamicexplorati00unraU.S. Army (USA) autho

User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

Accessible user interface support for multi-device ubiquitous applications: architectural modifiability considerations

The market for personal computing devices is rapidly expanding from PC, to mobile, home entertainment systems, and even the automotive industry. When developing software targeting such ubiquitous devices, the balance between development costs and market coverage has turned out to be a challenging issue. With the rise of Web technology and the Internet of things, ubiquitous applications have become a reality. Nonetheless, the diversity of presentation and interaction modalities still drastically limit the number of targetable devices and the accessibility toward end users. This paper presents webinos, a multi-device application middleware platform founded on the Future Internet infrastructure. Hereto, the platform's architectural modifiability considerations are described and evaluated as a generic enabler for supporting applications, which are executed in ubiquitous computing environments