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Color plays an essential role in the design of user interfaces and significantly impacts the user experience. To create aesthetically pleasing and user-friendly interfaces, the colors of the user interface should be consistent with the images. The latter can be challenging to achieve, as images often have different colors and are often changed by editors or authors who do not have sufficient design knowledge. To solve this problem, we have developed a model that automatically determines the color theme of the user interface based on a given image. The model first extracts the most prominent colors from the image and then considers both aesthetic (color harmony and compatibility with the image) and usability aspects (color contrast, color diversity, and color strength). All color calculations are performed in the perceptually uniform color space CAM02-UCS. In addition, the model can be adapted to the user's needs and requirements. To test the model, we implemented it in a web-based application in which the colors were automatically selected based on the featured image. The resulting color themes were then evaluated by the users, who were mainly professional designers. According to the results, the model generates color themes that are consistent with the image, aesthetic, and user-friendly. An important observation was also that color harmony can be achieved simply by using the most prominent colors of the image (regardless of their hue), suggesting that color harmony is strongly influenced by the context of use. The presented model holds significant practical importance as it can be utilized in various applications and tools. For instance, it can automatically choose a color theme for a user interface based on a particular image, such as a company logo or a product image. Moreover, it can dynamically adjust the colors of elements in real time based on the image that is visible simultaneously with the elements. [ABSTRACT FROM AUTHOR]

Color plays an essential role in the design of user interfaces and significantly impacts the user experience. To create aesthetically pleasing and user-friendly interfaces, the colors of the user interface should be consistent with the images. The latter can be challenging to achieve, as images often have different colors and are often changed by editors or authors who do not have sufficient design knowledge. To solve this problem, we have developed a model that automatically determines the color theme of the user interface based on a given image. The model first extracts the most prominent colors from the image and then considers both aesthetic (color harmony and compatibility with the image) and usability aspects (color contrast, color diversity, and color strength). All color calculations are performed in the perceptually uniform color space CAM02-UCS. In addition, the model can be adapted to the user’s needs and requirements. To test the model, we implemented it in a web-based application in which the colors were automatically selected based on the featured image. The resulting color themes were then evaluated by the users, who were mainly professional designers. According to the results, the model generates color themes that are consistent with the image, aesthetic, and user-friendly. An important observation was also that color harmony can be achieved simply by using the most prominent colors of the image (regardless of their hue), suggesting that color harmony is strongly influenced by the context of use. The presented model holds significant practical importance as it can be utilized in various applications and tools. For instance, it can automatically choose a color theme for a user interface based on a particular image, such as a company logo or a product image. Moreover, it can dynamically adjust the colors of elements in real time based on the image that is visible simultaneously with the elements.

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We have developed low cost interactive 3D models that improve access to architectural details of cultural sites for all, including people with vision impairments. Our approach uses rapid prototyping and 3D printing along with a very small single-board computer for automating user interaction. As a case study, we developed a prototype model of “Piazza dei Miracoli” (Pisa, Italy), the famous square where the Leaning Tower is located. The system is a combination of tactile information with audio descriptions to enable potential users to explore the artifact autonomously. We exploited low-cost and partially open-source technologies, thus rendering our system easily replicable. We evaluated the interactive system with a group of eight completely blind and partially sighted users. Our user test confirmed the validity of our approach: (1) the three-dimensional models and the tactile reproduction of details obtained via a low-cost 3D printing solution are well perceived by touch; (2) the semantic aural information activated via perceptible buttons on demand and the different content levels for the audio tracks are suitable for an interactive, autonomous and satisfying exploration. [ABSTRACT FROM AUTHOR]

The usage of markup technologies to specify knowledge to be processed according to a specific field of application is a common technique. Representation techniques based on markup language paradigm to describe various types of knowledge including graph based models is considered and details on using Knowledge Representation and Processing (KRP) Systems in education are presented. XML and VoiceXML were selected to implement smart interface for KRP systems. [ABSTRACT FROM AUTHOR]

Thermoresponsive polymer brushes are grafted on micro/nanostructured polymer substrates as new intelligent interfaces that synergistically enhance wettability changes in response to external temperature stimuli. Thermoplastic poly(styrene-co-4-vinylbenzyl chloride) [P(St-co-VBC)] is synthesized using radical polymerization and spin-coated on a glass substrate. Micro/nanopillar and hole patterns are imprinted on the P(St-co-VBC) layer using thermal nanoimprint lithography. Poly(N-isopropylacrylamide) (PIPAAm) brushes are grafted on the micro/nanostructured P(St-co-VBC) layer through surface-initiated atom-transfer radical polymerization using 4-vinylbenzyl chloride as the initiator. The imprinted micro/nanostructures and grafted PIPAAm brush chain lengths affect the surface wettability. Combinations of nanopillars or nanoholes (diameter 500 nm) and longer PIPAAm brushes enhance hydrophobic/hydrophilic changes in response to temperature changes, compared with the flat substrate. The thermoresponsive hydrophobic/hydrophilic transition is synergistically enhanced by the nanostructured surface changing from Cassie-Baxter to Wenzel states. This PIPAAm-brush-modified micro/nanostructured P(St-co-VBC) is a new intelligent interface that effectively changes wettability in response to external temperature changes. [ABSTRACT FROM AUTHOR]

The article describes the development of fundamentals of machine elements and assemblies design processes automation using artificial intelligence, and descriptions of structural elements' features in a natural language. In the proposed interactive automated design systems, computational artificial intelligence methods allow communication by speech and natural language, resulting in analyses of design engineer's messages, analyses of constructions, encoding and assessments of constructions, CAD system controlling and visualizations. The system is equipped with several adaptive intelligent layers for human biometric identification, recognition of speech and handwriting, recognition of words, analyses and recognition of messages, enabling interpretation of messages, and assessments of human reactions. The article proposes a concept of intelligent processing for analysis of descriptions of machine elements' structural features in a natural language. It also presents the developed methodology for similarity analysis between structural features of designed machine elements and corresponding antipatterns allowing normalization of parameters of the analysed structural solutions. [ABSTRACT FROM AUTHOR]

Abstract: When intelligent interfaces, such as intelligent desktop assistants, email classifiers, and recommender systems, customize themselves to a particular end user, such customizations can decrease productivity and increase frustration due to inaccurate predictions—especially in early stages when training data is limited. The end user can improve the learning algorithm by tediously labeling a substantial amount of additional training data, but this takes time and is too ad hoc to target a particular area of inaccuracy. To solve this problem, we propose new supervised and semi-supervised learning algorithms based on locally-weighted logistic regression for feature labeling by end users, enabling them to point out which features are important for a class, rather than provide new training instances. We first evaluate our algorithms against other feature labeling algorithms under idealized conditions using feature labels generated by an oracle. In addition, another of our contributions is an evaluation of feature labeling algorithms under real-world conditions using feature labels harvested from actual end users in our user study. Our user study is the first statistical user study for feature labeling involving a large number of end users (43 participants), all of whom have no background in machine learning. Our supervised and semi-supervised algorithms were among the best performers when compared to other feature labeling algorithms in the idealized setting and they are also robust to poor quality feature labels provided by ordinary end users in our study. We also perform an analysis to investigate the relative gains of incorporating the different sources of knowledge available in the labeled training set, the feature labels and the unlabeled data. Together, our results strongly suggest that feature labeling by end users is both viable and effective for allowing end users to improve the learning algorithm behind their customized applications. [Copyright &y& Elsevier]

Persuasion has been studied for more than two millennia. Basically it can be viewed as the collection of methodologies aiming at changing, by means of communication, the mental state of the receiver, in view of a certain action (or set of actions) to be performed by the receiver. Inspired by this tradition, and by the practical realizations in the world of advertising, in this article a novel generation of intelligent interfaces is introduced, based on the idea that systems will have goals of their own to pursue, as far as inducing users (or rather any audience) to believe something, do something or change their attitude. The world of leisure and of tourism can specifically be impacted by such interfaces. In the article the main concepts are introduced, as well as elements that characterize persuasion systems in general; a revisitation of the concept of promotion campaign leads to the description of research prototypes and a short analysis of prospects for tourism. [ABSTRACT FROM AUTHOR]

• Storybox methodology offers new model for rapid development of storytelling chatbots. • New framework (D-PAF) provides structure for storytelling dialog. • Small knowledge base led to convincing chatbot conversations during evaluation. • Rapid training method captured conversation from live sessions. This paper presents the Storybox Methodology which combines a novel framework for structuring knowledge and conversations around a story (D-PAF), with a live chatroom-based training approach that builds the conversation knowledge base via live chatroom interactions. Chatbots have achieved success as intelligent interfaces in education, health, sales and support, but their move towards mainstream adoption has been hindered by the large amount of development resources required, in terms of data collection, preparation, user testing and technical knowledge. The complexity of the development task often necessitates both a system author and a domain expert working effectively together, adding further complexity and risk. Overcoming these barriers could increase feasibility of chatbots in a range of expert contexts. In education, there are groups of learners who do not enjoy reading and writing. Storytelling chatbots might be able to introduce these groups to enjoyable new ways to read and write, having a beneficial impact on their education and future prospects. This paper proposes the Storybox Methodology for the rapid development of storytelling chatbots. Storybox is evaluated by creating, training and testing 'The Ghost', a chatbot enacting Hamlet's Ghost character from William Shakespeare's dramatic tragedy. The results showed that after a period of live chatbot training of only 25 training conversations, The Ghost was able to conduct convincing conversations with participants. [ABSTRACT FROM AUTHOR]

The present work proposes a methodological approach for modeling adaptation decisions and for solving the problem of integrating existing as well as acquired knowledge in the decision module of an adaptive interface. So far, most applications do not exploit in full the value of data originating from user models or knowledge acquisition engines that monitor the user and the context. The proposed decision theoretic model is represented through specifically structured influence diagrams. It provides to designers and developers a specific method to encode user and context information, as well as other crucial decision factors, to be subsequently used in the decision making process regarding user interface adaptation actions. Such a process is driven by the definition of relevant utilities referring to the design of a user interface. The proposed model guides designers and developers of an adaptive or intelligent interface to integrate, without conflicts and incoherence, design strategies, design goals, user goals, alternative constituents, user profile, context and application domain knowledge. An illustrative example of the analyzed modeling method is presented. [ABSTRACT FROM AUTHOR]

Speech and language therapists (SLTs) are faced daily with a diversity of speech and language disabilities, which are associated with a variety of conditions ranging from client groups with overall cognitive deficits to those with more specific difficulties. It is desirable that those working with such a range of problems and with such a demanding workload plan care efficiently. Therefore, the introduction of methodologies, reference models of work and tools, which significantly improve the effectiveness of therapy, are particularly welcome. This paper describes a web-based tool for diagnosis, treatment and e-Learning in the field of Language and Speech therapy. The system is an "easy to use" technology environment. It allows SLTs to find the optimum treatment for each patient, by incorporating different treatment actors. In addition, it also allows any non-specialist user!SLT, patient or helper (relative etc.)-to explore their creativity, by designing their own communication aid in an interactive manner, with the use of editors like: configuration and vocabulary. The system has been tested and piloted by potential users (SLTs and patients) in Greece and UK. [ABSTRACT FROM AUTHOR]

This article address data quality issues relating to electronic health records (EHRs). It discusses the nature of the problem of supporting EHRs at national and international levels, and examines the data quality issues. In particular, the discussion focuses on the role of intelligent interfaces, structured data entry and mobile computing within this context. The problems are then made tangible by considering the implementation of a Greek national EHR system. The article concludes by recommending an adaptation framework that will enable a stepwise approach in the development of EHRs for the Greek health system which takes into account the data quality issues considered. [ABSTRACT FROM PUBLISHER]

We aim to explore a new kind of user interface solely dedicated to presenting the global inner dynamics of Multi-Agent Systems (MASs) on a higher level. Being complex systems, MASs are often only or barely understood by their designer(s). Could we enable a particular kind of agent to tell the designer’s story about the agent- and human-interactive behaviours taking place inside the MAS in a meaningful way? Could a set of virtual actors turn this story into a ‘dynamic user-experience’? After taking a closer look at how to gain insight into complex systems and why to pick a drama-based approach, we present the three pillars of perception, interpretation and presentation, on which we base our visualisation efforts. We show how they relate to various research fields such as agent technology, human computer interaction, psychology, computer graphics, animation, drama, body language and cognitive ergonomics. Based upon these insights we introduce a conceptual model for drama-based visualisation, followed by a stepwise description of how this framework could be applied. The article closes with some reflections and conclusions. [ABSTRACT FROM AUTHOR]

One goal of research in the area of human–machine interaction is to improve the ways a human user interacts with a computer through a multimedia interface. This interaction comprises of not only text, graphical animation, stereo sounds, and live video images, but also force and haptic feedback, which can provide more “real” feeling to the user. The force feedback joystick, a human interface device is an input–output device. It not only tracks user's physical manipulation input, but also provides realistic physical sensations of force coordinated with system output. As part of our research, we have developed a multimedia computer game that assimilates images, sounds, and force feedback. We focused on the issues of how to combine these media to allow the user feel the compliance, damping, and vibration effects through the force feedback joystick. We conducted series of human subject experiments that incorporated different combinations of media, including the comparative study of the different performances of 60 human users, aiming to answer the question: What are the effects of force feedback (and associated time delays) when used in combination with visual and auditory information as part of a multi-modal interface? It is hoped that these results can be utilized in the design of enhanced multimedia systems that incorporate force feedback. [ABSTRACT FROM AUTHOR]

A problem solving environment (PSE) is a complete, integrated computing environment for composing, compiling and running applications in a specific problem area or domain. A visual programming composition environment (VPCE) is described, which serves as a user interface for a PSE, and uses Java and CORBA to provide a framework of tools to enable the construction of scientific applications from components. The VPCE consists of a component repository, from which the user can select off-the-shelf or in-house components, a graphical composition area on which components can be combined, various tools that facilitate the configuration of components, the integration of legacy codes into components and the design and building of new components. The VPCE produces output using dataflow techniques in the form of a task graph, annotated with a performance model plus constraints for each component, expressed in XML. In addition, the VPCE supports a domain specific expert system based on JESS (Ernest Friedman-Hill, JESS: The Java Expert System Shell. See web site at: http://herzberg.ca.sandia.gov/jess/, 1999) to guide the user in component selection and to perform integrity checking. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Mixed-initiative problem solving lies at the heart of knowledge- based learning environments. While learners are actively engaged in problem-solving activities, learning environments should monitor their progress and provide them with feedback in a manner that contributes to achieving the twin goals of learning effectiveness and learning efficiency. Mixed-initiative interactions are particularly critical for constructivist learning environments in which learners participate in active problem solving. We have recently begun to see the emergence of believable agents with lifelike qualities. Featured prominently in constructivist learning environments, lifelike pedagogical agents could couple key feedback functionalities with a strong visual presence by observing learners' progress and providing them with visually contextualized advice during mixed-initiative problem solving. For the past three years, we have been engaged in a large-scale research program on lifelike pedagogical agents and their role in constructivist learning environments. In the resulting computational framework, lifelike pedagogical agents are specified by (1) a behavior space containing animated and vocal behaviors, (2) a design-centered context model that maintains constructivist problem representations, multimodal advisory contexts, and evolving problem-solving tasks, and (3) a behavior sequencing engine that in realtime dynamically selects and assembles agents' actions to create pedagogically effective, lifelike behaviors. To empirically investigate this framework, it has been instantiated in a full-scale implementation of a lifelike pedagogical agent for Design-A-Plant, a learning environment developed for the domain of botanical anatomy and physiology for middle school students. Experience with focus group studies conducted with middle school students interacting with the implemented agent suggests that lifelike pedagogical agents hold much promise for mixed-initiative learning. [ABSTRACT FROM AUTHOR]

Plan recognition is an active research area in automatic reasoning, as well as a promising approach to engineering interfaces that can exploit models of user's plans and goals. Much research in the field has focused on the development of plan recognition algorithms to support particular user/system interactions, such as found in naturally occurring dialogues. However, two questions have typically remained unexamined: 1) exactly what kind of interface tasks can knowledge of a user's plans be used to support across communication modalities, and 2) how can such tasks in turn constrain development of plan recognition algorithms? In this paper we present a concrete exploration of these issues. In particular, we provide an assessment of plan recognition, with respect to the use of plan recognition in enhancing user interfaces. We clarify how use of a user model containing plans makes interfaces more intelligent and interactive (by providing an intelligent assistant that supports such tasks as advice generation, task completion, context-sensitive responses, error detection and recovery). We then show how interface tasks in turn provide constraints that must be satisfied in order for any plan recognizer to construct and represent a plan in ways that efficiently support these tasks. Finally, we survey how interfaces are fundamentally limited by current plan recognition approaches, and use these limitations to identify and motivate current research. Our research is developed in the context of CHECS, a plan-based design interface. [ABSTRACT FROM AUTHOR]