People struggle to invent safe passwords for many of their typical online activities, leading to a variety of security problems when they use overly simple passwords or reuse them multiple times with minor modifications. Having different passwords for each service generally requires password managers or memorable (but weak) passwords, introducing other vulnerabilities [1], [2]. Recent research [3], [4] has offered multiple alternatives but those require either rote memorisation [5] or computation on a physical device[6], [7]. This paper describes a secure and usable solution to this problem that requires no assistance from any physical device. We present the Cue-Pin-Select password family scheme that requires little memorisation and allows users to create and retrieve passwords easily. It uses our natural cognitive abilities to be durable, adaptable to different password requirements, and resistant to attacks, including ones involving plain-text knowledge of some passwords from the family. We include a theoretical analysis of its security according to multiple attack models. Finally, we show the promising results of a small-scale user study that put participants in real-life conditions for multiple days.

Passphrases have many uses, such as serving as seeds for passwords. User-created passphrases are easier to remember, but tend to be less secure than ones created from words randomly chosen in a dictionary. This paper develops a way of making more memorable, more secure passphrases. It investigates the security and usability of creating a passphrase by choosing from a randomly generated set of words presented as a two-dimensional array. A usability experiment shows that participants using this method achieved 97% to 99% of the maximal theoretical entropy and commited fewer than half as many memory mistakes as a control group with assigned passphrases. It also shows that their choices are affected by word familiarity and weakly by the word's position in the array. Prompting a person with random words from a large dictionary is an effective way of helping them make a more memorable high-entropy passphrase.

We know that talking or texting while involved in a complex sensorimotor task like driving is dangerous. In such situations, interruptions from notifications can negatively impact primary task performance as well. This paper investigates the impact of attending to such notifications. In our study, participants were engaged in a primary task with varying task loads. Notifications were presented to them aurally and visually, and were mediated relative to the primary task load. Our results show that a) attending to notifications were distracting regardless of modality, b) mediation helped users comprehension of visual notifications, but did not effect their comprehension of audio notifications, and c) even though mediated notifications reduced performance degradation, users did not notice or choose it differentially.

Human performance falls off predictably with excessive task difficulty. This paper reports on a search for a task load estimation metric. Of the five physiological signals analyzed from a multitasking study, only pupil dilation measures correlated well with real-time task load. The paper introduces a novel task load estimation model based on pupil dilation measures. We demonstrate its effectiveness in a multitasking driving scenario. Autonomous mediation of notifications using this model significantly improved user task performance compared to no mediation. The model showed promise even when used outside in a car. Results were achieved using low-cost cameras and open-source measurement tools lending to its potential to be used broadly.

Mid-air gestures are initial hand poses with a subsequent movement. Existing gesture guides reveal this dynamic part of a gesture. Initial poses, however, are either revealed by space-consuming cheat sheets or time-consuming demonstration videos. Mime is a novel interaction concept that (1) reveals how to form complex hand poses and (2) teaches pose-command mappings: Mime reduces hand poses to space-efficient line figures that users mime with their hands; these abstract lines are embedded into command icons or names to create a mnemonic. We present several applications of the Mime concept, and implemented a prototype based on mid-air back-of-device interaction on off-the-shelf mobile phones. We compared both mnemonics, iconic and textual, to a baseline without embedding to test learnability and memorability of a 12-item vocabulary. Users in the iconic condition required significantly less training than both other conditions and recalled significantly more items after one week compared to the no-cue baseline.

Despite the demonstrated benefits of multi-finger input, todays gesture vocabularies offer a limited number of postures and gestures. Previous research designed several posture sets, but does not address the limited human capacity of retaining them. We present a multi-finger chord vocabulary, introduce a novel hand-centric approach to detect the identity of fingers on off-the-shelf hand-held tablets, and report on the detection accuracy. A between-subjects experiment comparing "random" to a "categorized" chord-command mapping found that users retained categorized mappings more accurately over one week than random ones. In response to the logical posture-language structure, people adapted to logical memorization strategies, such as 'exclusion', 'order', and 'category', to minimize the amount of information to retain. We conclude that structured chord-command mappings support learning, short-, and long-term retention of chord- command mappings.

This paper introduces CAMEO, a behavior-driven design approach to address commonly occurring technical and social problems in audio-only teleconference calls. Many of these problems are associated with the missing visual channel and the low bandwidth for non-verbal signals. CAMEO seeks not only to sense these problems, but also to frame and respond to them in considerate ways. These include scheduling of advisory prompts, and assistive mechanisms to augment this bandwidth-constrained medium. This paper describes their implementation in CAMEO using a blackboard architecture that shapes and define its behavior. Two experiments were conducted to evaluate CAMEO on its resolution of conversational dominance in a collaborative meeting, and its utility in reducing the effects of disruptive extraneous noise on a conference call. We show that variance in conversational dominance can significantly be reduced with proactive aural feedback. Our experiments further reveal that such feedback can also reduce the impact of extraneous noise on conversations.

When is an interface simple? Is it when it is invisible or very obvious, even intrusive? From the time TV was created, watching TV is considered as a static activity. TV audiences have very limited choices to interact with TV, such as turning on/off, increasing/decreasing volume, and traversing among different channels. This paper suggests that TV program should have social responses to people, such as affording and accepting audience’s emotional feeling with the growth of technologies. This paper presents HiTV, an Emotionally-Reactive TV system using a digitally augmented soft ball as affect-input interfaces that can amplify TV program’s video/audio signals. HiTV transforms the original video and audio into effects that intrigue and fulfill people’s emotional expectation. ACM Classification: H5.2 [Information interfaces and presentation]:

Networked appliances might make them aware of each other, but interacting with a complex network can be difficult in itself. KitchenSense is a sensor rich networked kitchen research platform that uses Common Sense reasoning to simplify control interfaces and augment interaction. The system's sensor net attempts to interpret people's intentions to create fail-soft support for safe, efficient and aesthetic activity. By considering embedded sensor data together with daily-event knowledge, a centrally-controlled system can develop a shared context across various appliances. The system is a research platform that is used to evaluate augmented intelligent support of work scenarios in physical spaces.

We demonstrate a software system that runs on the Symbian smartphone platform, and allows a group to capture the essence of a face-to-face meeting or remote conference call in a decentralized manner. We show how the users set up a meeting, record elements from the meeting, and are able to continue the collaboration after the original meeting has ended. We show how the information collected during the meeting can be used by members to analyze the collective impression of the meeting, as well view consensus or differences of opinions.

Creativity support tools is a research topic with high risk but potentially very high payoff. The goal is to develop improved software and user interfaces that empower users to be not only more productive but also more innovative. Potential users include software and other engineers, diverse scientists, product and graphic designers, architects, educators, students, and many others. Enhanced interfaces could enable more effective searching of intellectual resources, improved collaboration among teams, and more rapid discovery processes. These advanced interfaces should also provide potent support in hypothesis formation, speedier evaluation of alternatives, improved understanding through visualization, and better dissemination of results. For creative endeavors that require composition of novel artifacts (e.g., computer programs, scientific papers, engineering diagrams, symphonies, artwork), enhanced interfaces could facilitate exploration of alternatives, prevent unproductive choices, and enable easy backtracking. This U.S. National Science Foundation sponsored workshop brought together 25 research leaders and graduate students to share experiences, identify opportunities, and formulate research challenges. Two key outcomes emerged: (a) encouragement to evaluate creativity support tools through multidimensional in-depth longitudinal case studies and (b) formulation of 12 principles for design of creativity support tools.

This paper presents an exploration of user interfaces, persuasive interfaces and feedback techniques in the domain of the sink. Waterbot is a system to inform and motivate behavior at the sink for the purpose of increasing safety and functionality and ultimately motivating behavior change. Waterbot can be adapted to many current sink scenarios and demonstrates the breadth of interaction possible at the point of use of water. It functions as a platform for experimenting with safety, hygiene and water conservation in a sink. This paper presents the feedback and persuasion techniques of augmented physical interfaces with value-added design, automation, just-in-time prompts, positive and negative reinforcement, social validation and adaptive interfaces. Four design iterations are presented to affect behavior at the increasing cognitive levels of safety, functionality and behavior change.

A task-oriented space can benefit from an augmented reality interface that layers the existing tools and surfaces with useful information to make cooking more easy, safe and efficient. To serve experienced users as well as novices, augmented reality interfaces need to adapt modalities to the user's expertise and allow for multiple ways to perform tasks. We present a framework for designing an intelligent user interface that informs and choreographs multiple tasks in a single space according to a model of tasks and users. A residential kitchen has been outfitted with systems to gather data from tools and surfaces and project multi-modal interfaces back onto the tools and surfaces themselves. Based on user evaluations of this augmented reality kitchen, we propose a system to tailor information modalities based on the spatial and temporal qualities of the task, and the expertise, location and progress of the user. The intelligent augmented reality user interface choreographs multiple tasks in the same space at the same time.

This work explores the use of ambient displays in the context of interruption. A multimodal interface was created to communicate with users by using two ambient channels for interruption: heat and light. These ambient displays acted as external interruption generators designed to get users attention away from their current task; playing a game on a desktop computer. It was verified that the disruptiveness and effectiveness of interruptions varies with the interruption modality used to interrupt. The thermal modality produced a larger decrease in performance and disruptiveness on a task being interrupted than the visual modality. Our results set the initial point in providing the theory behind future self-adaptive multimodal-interruption interfaces that will employ users individual physiological responses to each interruption modality and dynamically select the modality based on effectiveness and performance metrics

This paper presents a novel way for assessing the affective qualities of natural language and a scenario for its use. Previous approaches to textual affect sensing have employed keyword spotting, lexical affinity, statistical methods, and hand-crafted models. This paper demonstrates a new approach, using large-scale real-world knowledge about the inherent affective nature of everyday situations (such as "getting into a car accident") to classify sentences into "basic" emotion categories. This commonsense approach has new robustness implications.Open Mind Commonsense was used as a real world corpus of 400,000 facts about the everyday world. Four linguistic models are combined for robustness as a society of commonsense-based affect recognition. These models cooperate and compete to classify the affect of text. Such a system that analyzes affective qualities sentence by sentence is of practical value when people want to evaluate the text they are writing. As such, the system is tested in an email writing application. The results suggest that the approach is robust enough to enable plausible affective text user interfaces.

The experience of a trusted group of colleagues can help users improve the quality and focus of their browsing and searching activities. How could a system provide such help, when and where the users need it, without disrupting their normal work activities? This paper describes Context-Aware Proxy based System (CAPS), an agent that recommends pages and annotates links to reveal their relative popularity among the users colleagues, matched with their automatically computed interest profiles. A Web proxy tracks browsing habits, so CAPS requires no explicit input from the user. We review here CAPS design principles and implementation. We tested user satisfaction with the interface and the accuracy of the ranking algorithm. These experiments indicate that CAPS has high potential to support effective ranking for quality judgment - by users

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This paper describes exploratory studies of interruption modalities and disruptiveness. Five interruption modalities were compared: heat, smell, sound, vibration, and light. Much more notable than the differences between modalities was the differences between people. We found that subjects' sensitiveness depended on their previous life exposure to the modalities. Individual differences greatly control the effect of interrupting stimuli. We show that is possible to build a multimodal adaptive interruption interface, such interfaces would dynamically select the output interruption modality to use based on its effectiveness on a particular user.

Attentive systems pay attention to what users do so that they can attend to what users need. Such systems track user behavior, model user interests, and anticipate user desires and actions. Because the general class of attentive systems is broad — ranging from human butlers to web sites that profile users — we have focused specifically on attentive information systems, which observe user actions with information resources, model user information states, and suggest information that might be helpful to users. In particular, we describe an implemented system, Simple User Interest Tracker (Suitor), that tracks computer users through multiple channels — gaze, web browsing, application focus — to determine their interests and to satisfy their information needs. By observing behavior and modeling users, Suitor finds and displays potentially relevant information that is both timely and non-disruptive to the users' ongoing activities.

This paper describes the design and implementation of the Office Assistant -- an agent that interacts with visitors at the office door and manages the office owner's schedule. We claim that rich context information about users is key to making a flexible and believable interaction. We also argue that natural face-to-face conversation is an appropriate metaphor for human-computer interaction. Keywords Human-computer Interaction, User Interface, Agent, Office Automation INTRODUCTION This paper describes the design and implementation of the Office Assistant -- an agent that interacts with visitors at the office door and manages the office owner's schedule. The agent is installed at the threshold of a high-traffic office in a noisy environment where the office owner prefers to have the door closed. The agent's goal is to facilitate informal, everyday office communication in an unobtrusive manner. One of the primary tasks of the office assistant agent is to interact with visitors, give...

No abstract available.

The explosive emergence of the Internet forces us to rethink the traditional roles for client, server, and objects. Component technology has emerged as the way objects and frameworks are packaged for flexible object integration. In particular, components allow users who are not programmers to do their own integration. Up until now, components have mainly focused on object integration on end-users desktops and on a client: compound documents, application assembly, etc.Existing component models like OpenDoc and Microsoft's OLE/OCX/COM provide function for compound documents, persistence, scripting, inking, and code management (registration). A series of Internet scenarios are emerging that demand new kinds of components. These scenarios are thin clients (Internet terminals), virtual reality/rich multimedia clients, collaboration, and business data access. Each panelist will explore one of these scenarios for it's requirements on an Internet component model.

The authors describe a conceptual model, the memory hierarchy framework, and a visual language for using the model. The model is more faithful to the structure of computers than the Von Neumann and Turing models. It addresses the issues of data movement and exposes and unifies storage mechanisms such as cache, translation lookaside buffers, main memory, and disks. The visual language presents the details of a computer's memory hierarchy in a concise drawing composed of rectangles and connecting segments. Using this framework, the authors improved the performance of a matrix multiplication algorithm by more than an order of magnitude. The framework gives insight into computer architecture and performance bottlenecks by making effective use of human visual abilities.>