Question: Swarm: Enhanced awareness, micro-coordination, and intelligent convergence via mobile group text messaging.

In the realm of mobile telephony, location-based services (LBS) have become increasingly prevalent, prompting a critical examination of users' privacy concerns regarding their location data. This paper delves into the dichotomy of LBS, distinguishing between location-tracking services, where a third party monitors the user's location, and position-aware services, which utilize the device's self-awareness of its location for functionality. An empirical study was conducted to gauge the level of privacy concern among users in relation to the use of location-based services. The findings revealed a significant disparity in privacy apprehension; while the perceived utility of both service types was comparable, location-tracking services elicited notably greater privacy concerns compared to position-aware services. This discrepancy suggests a strategic development focus on position-aware services, which are perceived as less invasive, while location-tracking services may still find success if accompanied by straightforward mechanisms for users to disable location tracking, thus addressing privacy concerns head-on.

Twitter, a popular microblogging service, has received much attention recently. An important characteristic of Twitter is its real-time nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence promptly, simply by observing the tweets. As described in this paper, we investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering, which are widely used for location estimation in ubiquitous/pervasive computing. The particle filter works better than other comparable methods for estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (96% of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and sends e-mails to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.

The thought of developing this proposed model comes from social responsibility towards the society. Lack of immediate First Aid and Emergency medical services during accident are prime cause of death in majority of cases of accidents. The one of the main reasons for this may be late arrival of ambulance, no person at place of accident to give information to the ambulance. This thought of taking responsibility of society resulted in our proposed model “Microcontroller based smart helmet using GSM & GPRS”. The aim of this proposed model design is to inform the responsible persons at the earliest about the accident so that they can take required actions to save the life of the injured person. Our proposed system consists of Arduino as Microcontroller, GSM for calling purpose, GPRS for tracking purpose and mainly Sensors to detect the accident. Our proposed system detects the accident and sends text message along with a voice message within a minute to the registered number.

Twitter presents an unparalleled opportunity for researchers from various ï¬elds to gather valuable and genuine textual data from millions of people. However, the collection pro-cess, as well as the analysis of these data require different kinds of skills (e.g. programing, data mining) which can be an obstacle for people who do not have this background. In this paper we present CATS, an open source, scalable, Web application designed to support researchers who want to carry out studies based on tweets. The purpose of CATS is twofold: (i) allow people to collect tweets (ii) enable them to analyze these tweets thanks to efï¬cient tools (e.g. event detection, named-entity recognition, topic modeling, word-clouds). What is more, CATS relies on a distributed imple-mentation which can deal with massive data streams.

In mobile cloud computing, mobile devices can rely on cloud computing and information storage resource to perform computationally intensive operations such as searching, data mining, and multimedia processing. In addition to providing traditional computation services, mobile cloud also enhances the operation of traditional ad hoc network by treating mobile devices as service nodes, e.g., sensing services. The sensed information, such as location coordinates, health related information, should be processed and stored in a secure fashion to protect user's privacy in the cloud. To this end, we present a new mobile cloud data processing framework through trust management and private data isolation. Finally, an implementation pilot for improving teenagers' driving safety, which is called FocusDrive, is presented to demonstrate the solution.

Instant Messaging (IM) is being widely adopted by teenagers. In a study of 16 teenage IM users, we explore IM as an emerging feature of teen life, focusing our questions on its support of interpersonal communication and its role and salience in everyday life. We qualitatively describe the teens' IM use interpersonally, as well as its place in the domestic ecology. We also identify technology adoption conditions and discuss behaviors around privacy management. In this initial investigation, we found differences in the nature of use between high school and college teens, differences we propose are accounted for by teens' degree of autonomy as a function of domestic and scholastic obligations, the development of independent work practices, Internet connectivity access, and even transportation access. Moreover, while teen IM use is in part characterized as an optimizing choice between multiple communications media, practice is also tied to concerns around peer pressure, peer group membership and creating additional opportunities to socialize.

Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information processing over networks. However for many topologies that are realistic for wireless ad-hoc and sensor networks (like grids and random geometric graphs), the standard nearest-neighbor gossip converges very slowly. A recently proposed algorithm called geographic gossip improves gossip efficiency by a p n/ log n factor for random geometric graphs, by exploiting geographic information of node locations. In this paper we prove that a variation of geographic gossip that averages along routed paths, improves efficiency by an additional p n/ log n factor and is order optimal for grids and random geometric graphs. Our analysis provides some general techniques and can be used to provide bounds on the performance of randomized message passing algorithms operating over various graph topologies.

Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity). Since it was proposed about a decade ago, many researchers have studied this topic and built several context-aware applications to demonstrate the usefulness of this new technology. Context-aware applications (or the system infrastructure to support them), however, have never been widely available to everyday users. In this survey of research on context-aware systems and applications, we looked in depth at the types of context used and models of context information, at systems that support collecting and disseminating context, and at applications that adapt to the changing context. Through this survey, it is clear that context-aware research is an old but rich area for research. The difficulties and possible solutions we outline serve as guidance for researchers hoping to make context-aware computing a reality.

Text-based counseling and support systems have seen an increasing proliferation in the past decade. We present Fathom, a natural language interface to help crisis counselors on Crisis Text Line, a new 911-like crisis hotline that takes calls via text messaging rather than voice. Text messaging opens up the opportunity for software to read the messages as well as people, and to provide assistance for human counselors who give clients emotional and practical support. Crisis counseling is a tough job that requires dealing with emotionally stressed people in possibly life-critical situations, under time constraints. Fathom is a system that provides topic modeling of calls and graphical visualization of topic distributions, updated in real time. We develop a mixed-initiative paradigm to train coherent topic and word distributions and use them to power real-time visualizations aimed at reducing counselor cognitive overload. We believe Fathom to be the first real-time computational framework to assist in crisis counseling.

Text messaging through the Internet or cellular phones has become a major medium of personal and commercial communication. In the same time, flames (such as rants, taunts, and squalid phrases) are offensive/abusive phrases which might attack or offend the users for a variety of reasons. An automatic discriminative software with a sensitivity parameter for flame or abusive language detection would be a useful tool. Although a human could recognize these sorts of useless annoying texts among the useful ones, it is not an easy task for computer programs. In this paper, we describe an automatic flame detection method which extracts features at different conceptual levels and applies multilevel classification for flame detection. While the system is taking advantage of a variety of statistical models and rule-based patterns, there is an auxiliary weighted pattern repository which improves accuracy by matching the text to its graded entries.

Intelligent conversational assistants, such as Apple’s Siri, Microsoft’s Cortana, and Amazon’s Echo, have quickly become a part of our digital life. However, these assistants have major limitations, which prevents users from conversing with them as they would with human dialog partners. This limits our ability to observe how users really want to interact with the underlying system. To address this problem, we developed a crowd-powered conversational assistant, Chorus, and deployed it to see how users and workers would interact together when mediated by the system. Chorus sophisticatedly converses with end users over time by recruiting workers on demand, which in turn decide what might be the best response for each user sentence. Up to the first month of our deployment, 59 users have held conversations with Chorus during 320 conversational sessions. In this paper, we present an account of Chorus’ deployment, with a focus on four challenges: (i) identifying when conversations are over, (ii) malicious users and workers, (iii) on-demand recruiting, and (iv) settings in which consensus is not enough. Our observations could assist the deployment of crowd-powered conversation systems and crowd-powered systems in general.


Question: Swarm: Enhanced Situational Awareness, Precise Micro-Coordination, and Intelligent Convergence utilizing Mobile Group Text Messaging.

Beyond Location: A Comprehensive Model for Context in Ultra-Mobile Computing

Context, a crucial element in human-computer interaction, encapsulates the environmental details that imbue meaning in computing scenarios. In the realm of mobile computing, location has often been the primary parameter utilized to approximate context and to facilitate context-aware applications. However, ultra-mobile computing, characterized by devices that remain operational during movement—such as PDAs, mobile phones, and wearable computers—stands to gain significantly from a more expansive definition of context. This paper introduces a working model for context, explores mechanisms for acquiring context beyond location, and discusses the application of context-awareness in ultra-mobile computing environments.

To enhance context-awareness, we delve into the potential of sensors beyond location-based ones. Two prototypes are showcased: a light-sensitive display and an orientation-aware PDA interface, demonstrating the utility of sensors in enriching context recognition. We then extend this concept to a model for sensor fusion, allowing for the sophisticated recognition of complex contexts. An experimental implementation of this model is described, validating its feasibility. Additionally, we explore the fusion of multiple sensors to acquire information on more nuanced contexts.

The introduction of context in ultra-mobile computing marks a significant shift from location transparency towards an increased focus on the user's immediate environment. Ultra-mobile devices, defined by their operational capability during movement and their transition from general-purpose computing to task-specific support, require a deeper understanding of context. This encompasses not only the physical environment but also the user's preferences, activities, and the status of their interaction with the device.

A primary challenge in context-awareness for mobile computing is the accurate perception of the user's surroundings. Traditionally, this has been addressed through location-awareness, using technologies such as global positioning systems or proximity beacons. However, a more comprehensive model of context, incorporating various sensory inputs, promises a more sophisticated and adaptable interaction between ultra-mobile devices and their users.

In summary, this paper advocates for a broader conception of context in ultra-mobile computing, emphasizing the role of sensors and sensor fusion in enhancing context-awareness. Through experimental implementations and theoretical discussions, it showcases the potential for ultra-mobile devices to offer more personalized and responsive computing experiences.

BACKGROUND
A dramatic rise in health-tracking apps for mobile phones has occurred recently. Rich user interfaces make manual logging of users' behaviors easier and more pleasant, and sensors make tracking effortless. To date, however, feedback technologies have been limited to providing overall statistics, attractive visualization of tracked data, or simple tailoring based on age, gender, and overall calorie or activity information. There are a lack of systems that can perform automated translation of behavioral data into specific actionable suggestions that promote healthier lifestyle without any human involvement.

OBJECTIVE
MyBehavior, a mobile phone app, was designed to process tracked physical activity and eating behavior data in order to provide personalized, actionable, low-effort suggestions that are contextualized to the user's environment and previous behavior. This study investigated the technical feasibility of implementing an automated feedback system, the impact of the suggestions on user physical activity and eating behavior, and user perceptions of the automatically generated suggestions.

METHODS
MyBehavior was designed to (1) use a combination of automatic and manual logging to track physical activity (eg, walking, running, gym), user location, and food, (2) automatically analyze activity and food logs to identify frequent and nonfrequent behaviors, and (3) use a standard machine-learning, decision-making algorithm, called multi-armed bandit (MAB), to generate personalized suggestions that ask users to either continue, avoid, or make small changes to existing behaviors to help users reach behavioral goals. We enrolled 17 participants, all motivated to self-monitor and improve their fitness, in a pilot study of MyBehavior. In a randomized two-group trial, investigators randomly assigned participants to receive either MyBehavior's personalized suggestions (n=9) or nonpersonalized suggestions (n=8), created by professionals, from a mobile phone app over 3 weeks. Daily activity level and dietary intake was monitored from logged data. At the end of the study, an in-person survey was conducted that asked users to subjectively rate their intention to follow MyBehavior suggestions.

RESULTS
In qualitative daily diary, interview, and survey data, users reported MyBehavior suggestions to be highly actionable and stated that they intended to follow the suggestions. MyBehavior users walked significantly more than the control group over the 3 weeks of the study (P=.05). Although some MyBehavior users chose lower-calorie foods, the between-group difference was not significant (P=.15). In a poststudy survey, users rated MyBehavior's personalized suggestions more positively than the nonpersonalized, generic suggestions created by professionals (P<.001).

CONCLUSIONS
MyBehavior is a simple-to-use mobile phone app with preliminary evidence of efficacy. To the best of our knowledge, MyBehavior represents the first attempt to create personalized, contextualized, actionable suggestions automatically from self-tracked information (ie, manual food logging and automatic tracking of activity). Lessons learned about the difficulty of manual logging and usability concerns, as well as future directions, are discussed.

TRIAL REGISTRATION
ClinicalTrials.gov NCT02359981; https://clinicaltrials.gov/ct2/show/NCT02359981 (Archived by WebCite at http://www.webcitation.org/6YCeoN8nv).

Social reporting is based on the idea that the members of a location-based social network observe real-world events and publish reports about their observations. Application scenarios include crisis management, bird watching or even some sorts of mobile games. A major issue in social reporting is the quality of the reports. We propose an approach to the quality problem that is based on the reciprocal confirmation of reports by other reports. This contrasts with approaches that require users to verify reports, that is, to explicitly evaluate their veridicality. We propose to use spatio-termporal proximity as a first criterion for confirmation and social distance as a second one. By combining these two measures we construct a graph containing the reports as nodes connected by confirmation edges that can adopt positive as well as negative values. This graph builds the basis for the computation of confirmation values for individual reports by different aggregation measures. By applying our approach to two use cases, we show the importance of a weighted combination, since the meaningfulness of the constituent measures varies between different contexts.

This paper presents a new approach to the cooperative localization problem, namely distributed multi-robot localization. A group of M robots is viewed as a single system composed of robots that carry, in general, di erent sensors and have di erent positioning capabilities. A single Kalman lter is formulated to estimate the position and orientation of all the members of the group. This centralized schema is capable of fusing information provided by the sensors distributed on the individual robots while accommodating independencies and interdependencies among the collected data. In order to allow for distributed processing, the equations of the centralized Kalman lter are treated so that this lter can be decomposed into M modi ed Kalman lters each running on a separate robot. The distributed localization algorithm is applied to a group of 3 robots and the improvement in localization accuracy is presented.

As data becomes dynamic, large, and distributed, there is increasing demand for what have become known as distributed stream algorithms. Since continuously collecting the data to a central server and processing it there is infeasible, a common approach is to define local conditions at the distributed nodes, such that—as long as they are maintained—some desirable global condition holds.
 Previous methods derived local conditions focusing on communication efficiency. While proving very useful for reducing the communication volume, these local conditions often suffer from heavy computational burden at the nodes. The computational complexity of the local conditions affects both the runtime and the energy consumption. These are especially critical for resource-limited devices like smartphones and sensor nodes. Such devices are becoming more ubiquitous due to the recent trend toward smart cities and the Internet of Things. To accommodate for high data rates and limited resources of these devices, it is crucial that the local conditions be quickly and efficiently evaluated.
 Here we propose a novel approach, designated CB (for Convex/Concave Bounds). CB defines local conditions using suitably chosen convex and concave functions. Lightweight and simple, these local conditions can be rapidly checked on the fly. CB’s superiority over the state-of-the-art is demonstrated in its reduced runtime and power consumption, by up to six orders of magnitude in some cases. As an added bonus, CB also reduced communication overhead in all the tested application scenarios.

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC) – an initiative to collect unique, longitudinal smartphone data set for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC; describe the specific data sets used in each of them; discuss the key design and implementation aspects introduced in order to generate privacypreserving and scientifically relevant mobile data resources for wider use by the research community; and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Creating context-aware ad hoc collaborative systems remains to be one of the primary hurdles hampering the ubiquitous deployment of IT and communication services. Especially under mission-critical scenarios, these services must often adhere to strict timing deadlines. We believe empowering such realtime collaboration systems requires context-aware application platforms working in conjunction with ultra-low latency data transmissions. In this paper, we make a strong case that this could be accomplished by combining the novel communication architectures being proposed for 5G with the principles of Mobile Edge Computing (MEC). We show that combining 5G with MEC would enable inter- and intra-domain use cases that are otherwise not feasible.

We discuss findings from an ethnographic study of instant messaging (IM) in the workplace and its implications for media theory. We describe how instant messaging supports a variety of informal communication tasks. We document the affordances of IM that support flexible, expressive communication. We describe some unexpected uses of IM that highlight aspects of communication which are not part of current media theorizing. They pertain to communicative processes people use to connect with each other and to manage communication, rather than to information exchange. We call these processes "outeraction". We discuss how outeractional aspects of communication affect media choice and patterns of media use.

Raising audience awareness over the creation and evolution of a cultural participatory digital platform is a critical point for its acceptance. The proposed platform adopts user involvement in the content collection level through the implementation of a mobile application easily downloadable to the user’s smartphone and the use of a web portal application. Complementary web portal permits the management of the collected content in a trustworthy manner adopting an extended role-based access control model for authorization purposes. Users can formulate private groups to contribute and share content. Platform guarantees the soundness of contributed content through an auditing procedure requested by the contributors and conducted by experts selected randomly. In order to stress the applicability of our platform to various cultural environments, we present a number of usage scenarios targeting various stakeholders from specialists and museum curators to students, teachers and simple enthusiasts aiming in the devel‐ opment of coherent narrations.

Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-ranging conversation among social media users, whereas the vast majority of them receive little or no attention. I argue that advocacy organizations are more likely to inspire comments from new social media audiences if they create "cultural bridges," or produce messages that combine conversational themes within an advocacy field that are seldom discussed together. I use natural language processing, network analysis, and a social media application to analyze how cultural bridges shaped public discourse about autism spectrum disorders on Facebook over the course of 1.5 years, controlling for various characteristics of advocacy organizations, their social media audiences, and the broader social context in which they interact. I show that organizations that create substantial cultural bridges provoke 2.52 times more comments about their messages from new social media users than those that do not, controlling for these factors. This study thus offers a theory of cultural messaging and public deliberation and computational techniques for text analysis and application-based survey research.

Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain. Understanding and exploiting the features of mobile data from a social network perspective will be extremely beneficial to wireless networks, from planning, operation, and maintenance to optimization and marketing.


Question: Swarm: Enhanced Awareness, Fine-Grained Coordination, and Intelligent Convergence via Mobile Group Text Messaging

This paper introduces the Cyberguide project, a pioneering endeavor in developing mobile, context-aware applications designed to function as a personal tour guide. In the evolving landscape of computing, users are no longer tethered to desktop environments, necessitating the creation of applications that can harness contextual data, including location information, to enhance user experience. The Cyberguide system is envisioned to offer services akin to those provided by a human tour guide, leveraging the user's current and historical location data. The paper elaborates on the design and functionalities of various Cyberguide prototypes, which have been created for both indoor and outdoor use across different handheld devices. Additionally, the authors delve into the broader research challenges that have arisen during the development of context-aware applications for mobile environments, underscoring the complexities and opportunities in this field. The Cyberguide's innovative use of context and mobility demonstrates the potential for smart, adaptive, and user-centric applications in the realm of mobile computing.

Participatory sensing is now becoming more popular and has shown its great potential in various applications. It was originally proposed to recruit ordinary citizens to collect and share massive amounts of sensory data using their portable smart devices. By attracting participants and paying rewards as a return, incentive mechanisms play an important role to guarantee a stable scale of participants and to improve the accuracy/coverage/timeliness of the sensing results. Along this direction, a considerable amount of research activities have been conducted recently, ranging from experimental studies to theoretical solutions and practical applications, aiming at providing more comprehensive incentive procedures and/or protecting benefits of different system stakeholders. To this end, this paper surveys the literature over the period of 2004-2014 from the state of the art of theoretical frameworks, applications and system implementations, and experimental studies of the incentive strategies used in participatory sensing by providing up-to-date research in the literature. We also point out future directions of incentive strategies used in participatory sensing.

Increasing number of social media content shared across the globe in real time creates a fascinating area of research. For most events, social media users act as collective sensors by sharing important information about events of any scale. Due to its real time nature, social media is much quicker to respond to such events relative to conventional news media. This paper proposes an event detection system which provides 5W1H (What, Where, When, Why, Who, How) analysis for each detected event. We make use of a myriad of techniques such as anomaly detection, named entity recognition, automatic summary generation, user link analysis. Our experimental results for the system indicate a faster event detection performance compared to conventional news sources. Event analysis results are also in line with the corresponding news articles about detected events.

Social persuasion to influence the actions, beliefs, and behaviors of individuals, embedded in a social network, has been widely studied. It has been applied to marketing, healthcare, sustainability, political campaigns, and public policy. Traditionally, there has been a separation between physical (offline) and cyber (online) worlds. While persuasion methods in the physical world focused on strong interpersonal trust and design principles, persuasion methods in the online world were rich on data-driven analysis and algorithms. Recent trends including Internet of Things, “big data,” and smartphone adoption point to the blurring divide between the cyber world and the physical world in the following ways. Fine grained data about each individual's location, situation, social ties, and actions are collected and merged from different sources. The messages for persuasion can be transmitted through both worlds at suitable times and places. The impact of persuasion on each individual is measurable. Hence, we posit that the social persuasion will soon be able to span seamlessly across these worlds and will be able to employ computationally and empirically rigorous methods to understand and intervene in both cyber and physical worlds. Several early examples indicate that this will impact the fundamental facets of persuasion including who, how, where, and when, and pave way for multiple opportunities as well as research challenges.

School of Computing and Mathematics, Faculty of Engineering, University of Ulster at Jordanstown, Shore Road, Newtownabbey, County Antrim BT37 0QB, Northern Ireland, UK The Applied Software Systems Laboratory (TASSL), Electrical and Computer Engineering, Rutgers, The State University of New Jersey, 94 Brett Road, Piscataway, NJ 08854-8058, USA School of Computing and Mathematical Sciences, The SRIF/SHEFC Centre for Virtual Organization Technology Enabling Research (VOTER), Glasgow Caledonian University, 70 Cowcaddens Road, Glasgow G4 0BA, UK Institute for Computer Science and Business Information Systems (ICB), University of Duisburg-Essen, Schützenbahn 70, 45117 Essen, Germany

Text messaging through the Internet or cellular phones has become a major medium of personal and commercial communication. In the same time, flames (such as rants, taunts, and squalid phrases) are offensive/abusive phrases which might attack or offend the users for a variety of reasons. An automatic discriminative software with a sensitivity parameter for flame or abusive language detection would be a useful tool. Although a human could recognize these sorts of useless annoying texts among the useful ones, it is not an easy task for computer programs. In this paper, we describe an automatic flame detection method which extracts features at different conceptual levels and applies multilevel classification for flame detection. While the system is taking advantage of a variety of statistical models and rule-based patterns, there is an auxiliary weighted pattern repository which improves accuracy by matching the text to its graded entries.

This research draws on longitudinal network data from an online community to examine patterns of users’ behavior and social interaction, and infer the processes underpinning dynamics of system use. The online community represents a prototypical example of a complex evolving social network in which connections between users are established over time by online messages. We study the evolution of a variety of properties since the inception of the system, including how users create, reciprocate, and deepen relationships with one another, variations in users’ gregariousness and popularity, reachability and typical distances among users, and the degree of local redundancy in the system. Results indicate that the system is a “small world”characterized by the emergence, in its early stages,of a hub-dominated structure with heterogeneity in users’ behavior. We investigate whether hubs are responsible for holding the system together and facilitating information flow, examine first-mover advantages underpinning users’ability to rise to system prominence, and uncover gender differences in users’ gregariousness, popularity, and local redundancy. We discuss the implications of the results for research on system use and evolving social networks, and for a host of applications, including information diffusion, communities of practice, and the security and robustness of information systems.

The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behaviors in urban environments. Cities can leverage such knowledge in order to provide better services (e.g., public transport planning, optimized resource allocation) and safer cities. Call Detail Record (CDR) data represents a practical data source to detect and monitor unusual events considering the high level of mobile phone penetration, compared with GPS equipped and open devices. In this paper, we provide a methodology that is able to detect unusual events from CDR data that typically has low accuracy in terms of space and time resolution. Moreover, we introduce a concept of unusual event that involves a large amount of people who expose an unusual mobility behavior. Our careful consideration of the issues that come from coarse-grained CDR data ultimately leads to a completely general framework that can detect unusual crowd events from CDR data effectively and efficiently. Through extensive experiments on real-world CDR data for a large city in Africa, we demonstrate that our method can detect unusual events with 16% higher recall and over 10 times higher precision, compared to stateof-the-art methods. We implement a visual analytics prototype system to help end users analyze detected unusual crowd events to best suit different application scenarios. To the best of our knowledge, this is the first work on the detection of unusual events from CDR data with considerations of its temporal and spatial sparseness and distinction between user unusual activities and daily routines.

The possibility of anonymity and lack of effective ways to identify inappropriate messages have resulted in a significant amount of online interaction data that attempt to harass, bully, or offend the recipient. In this work, we perform a preliminary linguistic study on messages exchanged using one such popular web/smartphone application—Sarahah, that allows friends to exchange messages anonymously. Since messages exchanged via Sarahah are private, we collect them when the recipient shares it on Twitter. We then perform an analysis of the different kinds of messages exchanged through this application. Our linguistic analysis reveals that a significant number of these messages (∼ 20%) include inappropriate, hurtful, or profane language intended to embarrass, offend, or bully the recipient. Our analysis helps in understanding the different ways in which anonymous message exchange platforms are used and the different types of bullying present in such exchanges.

Mobile devices are playing an increasingly intimate role in everyday life. However, users can be surprised when informed of the data collection and distribution activities of apps they install. We report on two studies of smartphone users in western European countries, in which users were confronted with app behaviors and their reactions assessed. Users felt their personal space had been violated in "creepy" ways. Using Altman's notions of personal space and territoriality, and Nissenbaum's theory of contextual integrity, we account for these emotional reactions and suggest that they point to important underlying issues, even when users continue using apps they find creepy.

Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.


Question: Swarm: achieving hyper-awareness, micro-coordination, and intelligent convergence through mobile group text messaging.

This paper outlines a groundbreaking system for tracking individuals within office settings, termed the Active Badge Location System. Employees are equipped with badges that emit signals, which are then captured by a network of sensors, allowing a centralized service to determine their location. The paper delves into various location tracking methodologies, critical design considerations, and potential applications, with a specific focus on enhancing telephone call routing efficiency. Addressing the inherent privacy concerns associated with such location tracking systems, the paper also discusses measures to protect individual privacy rights.

Secure instant messaging is utilized in two variants: one-to-one communication and group communication. While the first variant has received much attention lately (Frosch et al., EuroS Cohn-Gordon et al., EuroS Kobeissi et al., EuroS&P17), little is known about the cryptographic mechanisms and security guarantees of secure group communication in instant messaging. To approach an investigation of group instant messaging protocols, we first provide a comprehensive and realistic security model. This model combines security and reliability goals from various related literature to capture relevant properties for communication in dynamic groups. Thereby the definitions consider their satisfiability with respect to the instant delivery of messages. To show its applicability, we analyze three widely used real-world protocols: Signal, WhatsApp, and Threema. By applying our model, we reveal several shortcomings with respect to the security definition. Therefore we propose generic countermeasures to enhance the protocols regarding the required security and reliability goals. Our systematic analysis reveals that (1) the communications' integrity – represented by the integrity of all exchanged messages – and (2) the groups' closeness – represented by the members' ability of managing the group – are not end-to-end protected. We additionally show that strong security properties, such as Future Secrecy which is a core part of the one-to-one communication in the Signal protocol, do not hold for its group communication.

Open-source software, usually created by volunteer programmers dispersed worldwide, now competes with that developed by software firms. This achievement is particularly impressive as open-source programmers rarely meet. They rely heavily on electronic media, which preclude the benefits of face-to-face contact that programmers enjoy within firms. In this paper, we describe findings that address this paradox based on observation, interviews and quantitative analyses of two open-source projects. The findings suggest that spontaneous work coordinated afterward is effective, rational organizational culture helps achieve agreement among members and communications media moderately support spontaneous work. These findings can imply a new model of dispersed collaboration.

Social media constitute a challenging new source of information for intelligence gathering and decision making. Twitter is one of the most popular social media sites and often becomes the primary source of information. Twitter messages are short and well suited for knowledge discovery. Twitter provides both researchers and practitioners a free Application Programming Interface (API) which allows them to gather and analyse large data sets of tweets. Twitter information aren't solely tweet texts, as Twitter’s API provides a lot of info to perform attention-grabbing analysis studies. The paper concisely describes method of knowledge gathering and therefore the main areas of knowledge mining, information discovery and information visual image from Twitter information. In this paper we can create a twitter app from which we can fetch the real time twitter tweets on a particular topic and stored it into R and then we can apply several text mining steps on the tweets to pre-process the tweets text and than we

Social reporting is based on the idea that the members of a location-based social network observe real-world events and publish reports about their observations. Application scenarios include crisis management, bird watching or even some sorts of mobile games. A major issue in social reporting is the quality of the reports. We propose an approach to the quality problem that is based on the reciprocal confirmation of reports by other reports. This contrasts with approaches that require users to verify reports, that is, to explicitly evaluate their veridicality. We propose to use spatio-termporal proximity as a first criterion for confirmation and social distance as a second one. By combining these two measures we construct a graph containing the reports as nodes connected by confirmation edges that can adopt positive as well as negative values. This graph builds the basis for the computation of confirmation values for individual reports by different aggregation measures. By applying our approach to two use cases, we show the importance of a weighted combination, since the meaningfulness of the constituent measures varies between different contexts.

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, an open-source, low cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only $14 worth of parts and takes 5 min to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems. We demonstrate the capabilities of the Kilobot as a collective robot, by using a small robot test collective to implement four popular swarm behaviors: foraging, formation control, phototaxis, and synchronization. © 2013 Elsevier B.V. All rights reserved.

As a component of the intelligent transportation system (ITS) and one of the concrete applications of mobile ad hoc networks, inter-vehicle communication (IVC) has attracted research attention from both the academia and industry of, notably, US, EU, and Japan. The most important feature of IVC is its ability to extend the horizon of drivers and on-board devices (e.g., radar or sensors) and, thus, to improve road traffic safety and efficiency. This paper surveys IVC with respect to key enabling technologies ranging from physical radio frequency to group communication primitives and security issues. The mobility models used to evaluate the feasibility of these technologies are also briefly described. We focus on the discussion of various MAC protocols that seem to be indispensable components in the network protocol stack of IVC. By analyzing the application requirements and the protocols built upon the MAC layer to meet these requirements, we also advocate our perspective that ad hoc routing protocols and group communication primitives migrated from wired networks might not be an efficient way to support the envisioned applications, and that new coordination algorithms directly based on MAC could be designed for this purpose.

Awareness of the emotion of those who communicate with others is a fundamental challenge in building affective intelligent systems. Emotion is a complex state of the mind influenced by external events, physiological changes, or relationships with others. Because emotions can represent a user's internal context or intention, researchers suggested various methods to measure the user's emotions from analysis of physiological signals, facial expressions, or voice. However, existing methods have practical limitations to be used with consumer devices, such as smartphones; they may cause inconvenience to users and require special equipment such as a skin conductance sensor. Our approach is to recognize emotions of the user by inconspicuously collecting and analyzing user-generated data from different types of sensors on the smartphone. To achieve this, we adopted a machine learning approach to gather, analyze and classify device usage patterns, and developed a social network service client for Android smartphones which unobtrusively find various behavioral patterns and the current context of users. Also, we conducted a pilot study to gather real-world data which imply various behaviors and situations of a participant in her/his everyday life. From these data, we extracted 10 features and applied them to build a Bayesian Network classifier for emotion recognition. Experimental results show that our system can classify user emotions into 7 classes such as happiness, surprise, anger, disgust, sadness, fear, and neutral with a surprisingly high accuracy. The proposed system applied to a smartphone demonstrated the feasibility of an unobtrusive emotion recognition approach and a user scenario for emotion-oriented social communication between users.

This study of mobile persuasion system explores the use of a mobile phone, when attached to an everyday object used by an everyday behavior, becomes a tool to sense and influence that behavior. This mobile persuasion system, called Playful Bottle system, makes use of a mobile phone attached to an everyday drinking mug and motivates office workers to drink healthy quantities of water. A camera and accelerometer sensors in the phone are used to build a vision/motion-based water intake tracker to detect the amount and regularity of water consumed by the user. Additionally, the phone includes hydration games in which natural drinking actions are used as game input. Two hydration games are developed: a single-user TreeGame with automated computer reminders and a multi-user ForestGame with computer-mediated social reminders from members of the group playing the game. Results from 7-week user study with 16 test subjects suggest that both hydration games are effective for encouraging adequate and regular water intake by users. Additionally, results of this study suggest that adding social reminders to the hydration game is more effective than system reminders alone.

This research draws on longitudinal network data from an online community to examine patterns of users’ behavior and social interaction, and infer the processes underpinning dynamics of system use. The online community represents a prototypical example of a complex evolving social network in which connections between users are established over time by online messages. We study the evolution of a variety of properties since the inception of the system, including how users create, reciprocate, and deepen relationships with one another, variations in users’ gregariousness and popularity, reachability and typical distances among users, and the degree of local redundancy in the system. Results indicate that the system is a “small world”characterized by the emergence, in its early stages,of a hub-dominated structure with heterogeneity in users’ behavior. We investigate whether hubs are responsible for holding the system together and facilitating information flow, examine first-mover advantages underpinning users’ability to rise to system prominence, and uncover gender differences in users’ gregariousness, popularity, and local redundancy. We discuss the implications of the results for research on system use and evolving social networks, and for a host of applications, including information diffusion, communities of practice, and the security and robustness of information systems.

Context-awareness is a critical aspect of safe navigation especially for the blind and visually impaired in unfamiliar environments. Existing mobile devices for context-aware navigation fall short in many cases due to their dependence on specific infrastructure requirements as well as having limited access to resources that could provide a wealth of contextual clues. In this paper, we propose a mobile-cloud collaborative approach for context-aware navigation by exploiting the computational power of resources made available by Cloud Computing providers as well as the wealth of location-specific resources available on the Internet. We propose an extensible system architecture that minimizes reliance on infrastructure, thus allowing for wide usability. We present a traffic light detector that we developed as an initial application component of the proposed system. We present preliminary results of experiments performed to test the appropriateness for the real-time nature of the application.


Question: Organizing content within the Façade interactive drama framework.

This paper delves into the integration of plot and character within the realm of interactive drama, focusing on the creation of compelling virtual worlds populated by computer-controlled personas that the user, or player, can engage with from a first-person viewpoint (Bates, 1992). The past decade has seen significant advancements in the field of believable agents—autonomous characters endowed with nuanced personalities, emotional depth, and sophisticated social dynamics (Mateas, 1997; Bates, Loyall, & Reilly, 1992; Blumberg, 1996; Hayes-Roth, van Gent, & Huber, 1997; Lester & Stone, 1997; Stern, Frank, & Resner, 1998). However, there has been a notable gap in research regarding the amalgamation of the immediate, reactive behaviors of these believable agents with the broader, more contemplative aspects of a story's plot, to construct interactive and dramatic environments (Weyrauch, 1997; Blumberg & Galyean, 1995). Our ongoing collaborative endeavor, spanning a period of two to three years, is centered on constructing an interactive narrative universe that seamlessly merges believable agents with interactive plotlines. This paper offers a concise overview of the project's objectives and design criteria, delves into the issue of autonomy within the context of story-driven believable agents, and ultimately presents an architectural framework that utilizes the dramatic beat as a foundational element to harmonize plot and character.

We investigate how presentation in a free-form medium stimulates free-form thinking and discussion in the classroom. Most classroom presentations utilize slideware (e.g. PowerPoint). Yet, slides add intrusive segregations that obstruct the flow of information. In contrast, in a free-form medium of presentation, content is not separated into rigid slide compartments. Instead, it is visually arranged and transformed in a continuous space.
 We develop a case study that investigates student experiences authoring, presenting, viewing, and discussing free-form presentations in a graduate seminar class. We analyze interviews, present a sampling of student presentations, and develop findings: free-form presentation stimulates free-form thinking, spontaneous discussion, and emergent ideation.

UI on the Fly is a system that dynamically presents coordinated multimodal content through natural language and a small-screen graphical user interface. It adapts to the user’s preferences and situation. Multimodal Functional Unification Grammar (MUG) is a unification-based formalism that uses rules to generate content that is coordinated across several communication modes. Faithful variants are scored with a heuristic function.

We describe OctoPocus, an example of a dynamic guide that combines on-screen feedforward and feedback to help users learn, execute and remember gesture sets. OctoPocus can be applied to a wide range of single-stroke gestures and recognition algorithms and helps users progress smoothly from novice to expert performance. We provide an analysis of the design space and describe the results of two experi-ments that show that OctoPocus is significantly faster and improves learning of arbitrary gestures, compared to con-ventional Help menus. It can also be adapted to a mark-based gesture set, significantly improving input time compared to a two-level, four-item Hierarchical Marking menu.

This paper is a reflection on the emerging genre of narrative visualization, a creative response to the need to share complex data engagingly with the public. In it, we explain how narrative visualization offers authors the opportunity to communicate more effectively with their audience by reproducing and sharing an experience of insight similar to their own. To do so, we propose a two part model, derived from previous literature, in which insight is understood as both an experience and also the product of that experience. We then discuss how the design of narrative visualization should be informed by attempts elsewhere to track the provenance of insights and share them in a collaborative setting. Finally, we present a future direction for research that includes using EEG technology to record neurological patterns during episodes of insight experience as the basis for evaluation.

During the Ottoman period, Taslihan was the largest accommodation complex in Sarajevo, Bosnia and Herzegovina. Today, only one wall remains as a memento of its existence. In this paper, we compare user appreciation of an interactive digital story about this building and of a serious game about Taslihan to see which application offers more knowledge and immersion while bringing this monument to life in the collective memory of the people.

We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between an action and its reaction by observing time sequences. We apply this method to analyze human interaction and to subsequently synthesize human behaviour. Using a time series of perceptual measurements, a system automatically uncovers a mapping between gestures from one human participant (an action) and a subsequent gesture (a reaction) from another participant. A probabilistic model is trained from data of the human interaction using a novel estimation technique, Conditional Expectation Maximization (CEM). The system drives a graphical interactive character which probabilistically predicts the most likely response to the user's behaviour and performs it interactively. Thus, after analyzing human interaction in a pair of participants, the system is able to replace one of them and interact with a single remaining user.

Serious games receive increasing interest in the area of e-learning. Their development, however, is often still a demanding, specialized and arduous process, especially when regarding reasonable non-player character behaviour. Reinforcement learning and, since recently, also deep reinforcement learning have proven to automatically generate successful AI behaviour to a certain degree. These methods are computationally expensive and hardly scalable to various complex serious game scenarios. For this reason, we introduce a new approach of augmenting the application of deep reinforcement learning methods by interactively making use of domain experts' knowledge to guide the learning process. Thereby, we aim to create a synergistic combination of experts and emergent cognitive systems. We call this approach interactive deep reinforcement learning and point out important aspects regarding realization within a framework.

Traditional fog screens are 2D. We propose a new design of fog screen that can generate fog at different depth positions and at only where necessary. Our approach applies projection mapping onto a non-planar and reconfigurable fog screen, thus enabling interactive visual contents to be displayed at multiple depth levels. Viewers can perceive the three-dimensionality naturally, and interact with the unencumbered images by touching them directly in mid-air. The display can be used in mixed reality settings where physical objects co-exist and interact with the 3D imagery in physical space.

This course presents a collection of state-of-the-art approaches for modeling and editing of 3D models for virtual worlds, simulations, and entertainment, in addition to real-world applications. The first contribution of this course is a coherent review of inverse procedural modeling (IPM) (i.e., proceduralization of provided 3D content). We describe different formulations of the problem as well as solutions based on those formulations. We show that although the IPM framework seems under-constrained, the state-of-the-art solutions actually use simple analogies to convert the problem into a set of fundamental computer science problems, which are then solved by corresponding algorithms or optimizations. The second contribution includes a description and categorization of results and applications of the IPM frameworks. Moreover, a substantial part of the course is devoted to summarizing different domain IPM frameworks for practical content generation in modeling and animation.

We present LSCitter, an implemented framework for supporting human interaction on social networks with formal models of interaction, designed as a generic tool for creating social machines on existing infrastructure. Interaction models can be used to choreograph distributed systems, providing points of coordination and communication between multiple interacting actors. While existing social networks specify how interactions happen---who messages go to and when, the effects of carrying out actions---these are typically implicit, opaque and non user-editable. Treating interaction models as first class objects allows the creation of electronic institutions, on which users can then choose the kinds of interaction they wish to engage in, with protocols which are explicit, visible and modifiable. However, there is typically a cost to users to engage with these institutions. In this paper we introduce the notion of "shadow institutions", where actions on existing social networks are mapped onto formal interaction protocols, allowing participants access to computational intelligence in a seamless, zero-cost manner to carry out computation and store information.


Question: Organizing content within the Façade interactive drama framework.

This paper outlines a comprehensive strategy for crafting believable, emotionally intelligent agents within interactive dramas. A pivotal component in elevating the quality of interactive narratives is the development of compelling, interactive characters, often referred to as believable agents. Two critical facets of these agents are their emotional expressiveness and their proficiency in social interactions. The methodology proposed here hinges on a broad agent architecture and a minimalist approach to modeling other agents within the environment. This philosophy is rooted in a deep appreciation of the artistic essence of character creation. To empower designers (artists) in constructing emotionally resonant agents, a versatile framework for emotional agent construction is provided, alongside default emotion-processing rules and insights into the creation of high-quality, emotionally charged characters. The framework's potency is significantly amplified by its integration within a wide-ranging agent architecture. The premise is straightforward: the richer the emotional landscape of an agent, the more elements it has to feel emotions about and the more varied the means to express them. This focus on breadth has allowed for the development of straightforward emotion models that prioritize perception and motivation over intricate cognitive processes and detailed modeling of other agents. To facilitate the creation of social behaviors for these believable agents, a methodology has been devised, offering guidelines for integrating personality into social actions and suggesting strategies for representing other agents in the environment. The proposed approach to modeling other agents advocates for a judicious amount of representation—just enough to elicit the intended behavior. This technique has proven successful in constructing robust social behaviors with minimal representation. A series of social behaviors, including negotiation and friendship formation, have been developed using this methodology. Three simulations featuring seven agents have been crafted to pilot and refine this approach. User studies have been conducted to validate that these agents are perceived as emotional beings capable of sophisticated social interactions while maintaining distinct, well-defined personalities.

Although the current paradigm for expanded participatory storytellling is the "transmedia" exploitation of the same storyworld on multiple platforms, it can be more productive to think of the digital medium as a single platform, combining all the functionalities we now associate with networked computers, game consoles, and conventionally delivered episodic television to enhance the traditional strengths and cultural functions of television. By looking at the how the four affordances of the digital medium the procedural, participatory, encyclopedic, and spatial apply to three core characteristics of television moving images, sustained storytelling, and individual viewing in the presence of a mass audience -- we can identify areas of emerging conventions and widening opportunity for design innovation

This paper describes an augmented reality (AR) environment that allows multiple participants or multi-user to interact with 2D and 3D data. AR simply can provide a collaborative interactive AR environment for urban simulation, where users can interact naturally and intuitively. In addition, the collaborative AR makes multi-user in urban simulation to share simultaneously a real world and virtual world. The fusion between real and virtual world, existed in AR environment by see-through HMDs, achieves higher interactivity as a key features of collaborative AR. In real-time, precise registration between both worlds and multiuser are crucial for the collaborations. Collaborative AR allow multi-user to simultaneously share a real world surrounding them and a virtual world. Common problems in AR environment will be discussed and major issues in collaborative AR will be explained details in this paper. The features of collaboration in AR environment are will be identified and the requirements of collaborative AR will be defined. This paper will give an overview on collaborative AR environment for multi-user in urban studies and planning. The work will also cover numerous systems of collaborative AR environments for multi-user.

The use of educational games in an academic context seems to be a superb alternative to traditional learning activities, such as drill-type exercises, in order to engage 21st-century students. Consequently, this work tries to raise the following objectives: analyze the effectiveness of game-based learning, characterize game elements that may contribute to create playing experiences, comprehend how different player types interact with games and, finally, design interactive games which may create challenges, set goals and provide feedback on progress while motivating learners to study physics and chemistry in a foreign language in the second cycle of Secondary Education (4th E.S.O. that corresponds to the age of 15-16 years old). Specifically, we have used several Web 2.0 tools (Hot Potatoes, Scratch, What2Learn and SMART Notebook 11) and applications (Microsoft PowerPoint and Microsoft Excel) in order to create the games; and these games are based on the successive contents: laboratory safety, laboratory equipment, stoichiometry, atomic structure, electronic configuration, the periodic table, forces, motion and energy.

Video summaries provide condensed and succinct representations of the content of a video stream through a combination of still images, video segments, graphical representations and textual descriptors. This paper presents a conceptual framework for video summarisation derived from the research literature and used as a means for surveying the research literature. The framework distinguishes between video summarisation techniques (the methods used to process content from a source video stream to achieve a summarisation of that stream) and video summaries (outputs of video summarisation techniques). Video summarisation techniques are considered within three broad categories: internal (analyse information sourced directly from the video stream), external (analyse information not sourced directly from the video stream) and hybrid (analyse a combination of internal and external information). Video summaries are considered as a function of the type of content they are derived from (object, event, perception or feature based) and the functionality offered to the user for their consumption (interactive or static, personalised or generic). It is argued that video summarisation would benefit from greater incorporation of external information, particularly user based information that is unobtrusively sourced, in order to overcome longstanding challenges such as the semantic gap and providing video summaries that have greater relevance to individual users. 2007 Elsevier Inc. All rights reserved.

Serious games receive increasing interest in the area of e-learning. Their development, however, is often still a demanding, specialized and arduous process, especially when regarding reasonable non-player character behaviour. Reinforcement learning and, since recently, also deep reinforcement learning have proven to automatically generate successful AI behaviour to a certain degree. These methods are computationally expensive and hardly scalable to various complex serious game scenarios. For this reason, we introduce a new approach of augmenting the application of deep reinforcement learning methods by interactively making use of domain experts' knowledge to guide the learning process. Thereby, we aim to create a synergistic combination of experts and emergent cognitive systems. We call this approach interactive deep reinforcement learning and point out important aspects regarding realization within a framework.

The field of computational narratology has produced many efforts aimed at generating narrative by computational means. In recent times, a number of such efforts have considered the task of modelling how a reader might consume the story. Whereas all these approaches are clearly different aspects of the task of generating narrative, so far the efforts to model them have occurred as separate and disjoint initiatives. There is an enormous potential for improvement if a way was found to combine results from these initiatives with one another. The present position paper provides a breakdown of the activity of creating stories into five stages that are conceptually different from a computational point of view and represent important aspects of the overall process as observed either in humans or in existing systems. These stages include a feedback loop that builds interpretations of an ongoing composition and provides feedback based on these to inform the composition process. This model provides a theoretical framework that can be employed first to understand how the various aspects of the task of generating narrative relate to one another, second to identify which of these aspects are being addressed by the different existing research efforts, and finally to point the way towards possible integrations of these aspects within progressively more complex systems.

A s computers grow more powerful, less expensive , and more widely available, people are expecting them not only to perform obvious computational tasks, but also to assist in people-oriented tasks, such as writing , drawing, and designing. This shift is causing some user-interface (UI) researchers to rethink the traditional reliance on methods that are more machine-oriented and to look at ways to support properties like ambiguity, creativity, and informal communication. The idea is to bend computers to people's way of interacting , not the other way around. This flexibility is particularly important in the early stages of UI design itself, when designers need the freedom to sketch rough design ideas quickly, the ability to test designs by interacting with them, and the flexibility to fill in the design details as they make choices. 1 Tools at this stage must support conceptual design, which is characterized by ambiguity and the need to create several design variations quickly, as the " Why Sketching Is Important " sidebar describes. Unfortunately , with current UI tools, designers tend to focus on issues such as colors, fonts, and alignment, which are more appropriate later in the design. Thus, most UI designers resort to sketching ideas on paper, but these are hard to edit and inconvenient for user evaluations. (CMU) have designed, implemented, and evaluated SILK (Sketching Interfaces Like Krazy), an informal sketching tool that combines many of the benefits of paper-based sketching with the merits of current electronic tools. With SILK, designers can quickly sketch an interface using an electronic pad and stylus, and SILK recognizes widgets and other interface elements as the designer draws them. Unlike paper-based sketching, however, designers can exercise these elements in their sketchy state. For example, a sketched scrollbar is likely to contain an elevator or thumbnail, the small rectangle a user drags with a mouse. In a paper sketch, the elevator would just sit there, but in a SILK sketch, designers can drag it up and down, which lets them test the components' or widgets' behavior. SILK also supports the creation of storyboards—the arrangement of sketches to show how design elements behave, such as how a dialog box appears when the user activates a button. Storyboards are important because they give designers a way to show colleagues, customers, or end users early on how an interface will behave. Designers can test the interface at any point, not just …

Most interactive computer graphics appear on a screen separate from the real world and the user's surroundings. However this does not always have to be the case. In augmented reality (AR) interfaces, three-dimensional virtual images appear superimposed over real objects. AR applications typically use head-mounted or handheld displays to make computer graphics appear in the user's environment.

In this paper, we propose ICrafter, a framework for services and their user interfaces in a class of ubiquitous computing environments. The chief objective of ICrafter is to let users flexibly interact with the services in their environment using a variety of modalities and input devices. We extend existing service frameworks in three ways. First, to offload services and user input devices, ICrafter provides infrastructure support for UI selection, generation, and adaptation. Second, ICrafter allows UIs to be associated with service patterns for on-the-fly aggregation of services. Finally, ICrafter facilitates the design of service UIs that are portable but still reflect the context of the local environment. In addition, we also focus on the system properties such as incremental deployability and robustness that are critical for ubiquitous computing environments. We describe the goals and architecture of ICrafter, a prototype implementation that validates its design, and the key lessons learnt from our

Despite the availability of high-quality graphics systems, architects and designers still build scaled physical models of buildings and products. These physical models have many advantages, however they are typically static in structure and surface characteristics. They are inherently lifeless. In contrast, high-quality graphics systems are tremendously flexible, allowing viewers to see alternative structures, facades, textures, cut-away views, and even dynamic effects such as changing lighting, moving automobiles, people, etc. We introduce a combination of these approaches that builds on our previously-published projector-based Spatially-Augmented Reality techniques. The basic idea is to aim multiple ceiling-mounted light projectors inward to graphically augment table-top scaled physical models of buildings or products. This approach promises to provide very compelling hybrid visualizations that afford the benefits of both traditional physical models, and modern computer graphics, effectively "bringing to life" table-top


Question: Organizing content within the Façade interactive drama framework.

This document explores the foundational principles guiding the development of interactive dramas and believable agents, focusing on the Oz Project, a decade-long research initiative at Carnegie Mellon University (CMU). Believable agents are defined as autonomous entities that display intricate and nuanced personalities, while interactive dramas unfold in virtual environments populated by these characters, enabling audience participation and engagement in unfolding narratives or plot arcs. The document offers a comprehensive overview of the Oz Project's research philosophy, which has been instrumental in advancing the field of believable agents and interactive drama. It also provides a critical review of contemporary research efforts from the Oz Project's unique vantage point. It's important to note that the research detailed in this document was partly funded by Intel Corporation, although the opinions and conclusions expressed herein are solely those of the author and do not necessarily reflect Intel's official policies or positions, either stated or inferred.

Video summaries provide condensed and succinct representations of the content of a video stream through a combination of still images, video segments, graphical representations and textual descriptors. This paper presents a conceptual framework for video summarisation derived from the research literature and used as a means for surveying the research literature. The framework distinguishes between video summarisation techniques (the methods used to process content from a source video stream to achieve a summarisation of that stream) and video summaries (outputs of video summarisation techniques). Video summarisation techniques are considered within three broad categories: internal (analyse information sourced directly from the video stream), external (analyse information not sourced directly from the video stream) and hybrid (analyse a combination of internal and external information). Video summaries are considered as a function of the type of content they are derived from (object, event, perception or feature based) and the functionality offered to the user for their consumption (interactive or static, personalised or generic). It is argued that video summarisation would benefit from greater incorporation of external information, particularly user based information that is unobtrusively sourced, in order to overcome longstanding challenges such as the semantic gap and providing video summaries that have greater relevance to individual users. 2007 Elsevier Inc. All rights reserved.

Free viewpoint video (FVV) is one of the new trends in the development of advanced visual media type that aims to provide a new immersive user experience and interactivity that goes beyond higher image quality (HD/4K TV) and higher realism (3D TV). Potential applications include interactive personal visualization and free viewpoint navigation. The goal of this paper is to provide an overview of the FVV system and some target application scenarios. Associated standardization activities and technological barriers to overcome are also described. This paper is organized as follows: a general description of the FVV system and functionalities is given in Section I. Since an FVV system is composed of a chain of processing modules, an in-depth functional description of each module is provided in Section II. Examples of emerging FVV applications and use cases are given in Section III. A summary of technical challenges to overcome for wider usage and market penetration of FVV is given in Section IV.

We describe OctoPocus, an example of a dynamic guide that combines on-screen feedforward and feedback to help users learn, execute and remember gesture sets. OctoPocus can be applied to a wide range of single-stroke gestures and recognition algorithms and helps users progress smoothly from novice to expert performance. We provide an analysis of the design space and describe the results of two experi-ments that show that OctoPocus is significantly faster and improves learning of arbitrary gestures, compared to con-ventional Help menus. It can also be adapted to a mark-based gesture set, significantly improving input time compared to a two-level, four-item Hierarchical Marking menu.

This article describes My Science Tutor (MyST), an intelligent tutoring system designed to improve science learning by students in 3rd, 4th, and 5th grades (7 to 11 years old) through conversational dialogs with a virtual science tutor. In our study, individual students engage in spoken dialogs with the virtual tutor Marni during 15 to 20 minute sessions following classroom science investigations to discuss and extend concepts embedded in the investigations. The spoken dialogs in MyST are designed to scaffold learning by presenting open-ended questions accompanied by illustrations or animations related to the classroom investigations and the science concepts being learned. The focus of the interactions is to elicit self-expression from students. To this end, Marni applies some of the principles of Questioning the Author, a proven approach to classroom conversations, to challenge students to think about and integrate new concepts with prior knowledge to construct enriched mental models that can be used to explain and predict scientific phenomena. In this article, we describe how spoken dialogs using Automatic Speech Recognition (ASR) and natural language processing were developed to stimulate students' thinking, reasoning and self explanations. We describe the MyST system architecture and Wizard of Oz procedure that was used to collect data from tutorial sessions with elementary school students. Using data collected with the procedure, we present evaluations of the ASR and semantic parsing components. A formal evaluation of learning gains resulting from system use is currently being conducted. This paper presents survey results of teachers' and children's impressions of MyST.

The field of Shape-Changing Interfaces explores the qualities of physically dynamic artifacts. At furniture-scale, such artifacts have the potential of changing the ways we collaborate and engage with interiors and physical spaces. Informed by theories of proxemics, empirical studies of informal meetings and design work with shape-changing furniture, we develop the notion of proxemic transitions. We present three design aspects of proxemic transitions: transition speed, stepwise reconfiguration, and radical shifts. The design aspects focus on how to balance between physical and digital transformations in designing for proxemic transitions. Our contribution is three-fold: 1) the notion of proxemic transitions, 2) three design aspects to consider in designing for proxemic transitions, and 3) initial exploration of how these design aspects might generate designs of dynamic furniture. These contributions outline important aspects to consider when designing shape-changing furniture for informal workplace meetings.

Interactive video in an e-learning system allows proactive and random access to video content. Our empirical study examined the influence of interactive video on learning outcome and learner satisfaction in e-learning environments. Four different settings were studied: three were e-learning environments—with interactive video, with non-interactive video, and without video. The fourth was the traditional classroom environment. Results of the experiment showed that the value of video for learning effectiveness was contingent upon the provision of interactivity. Students in the e-learning environment that provided interactive video achieved significantly better learning performance and a higher level of learner satisfaction than those in other settings. However, students who used the e-learning environment that provided non-interactive video did not improve either. The findings suggest that it may be important to integrate interactive instructional video into e-learning systems. # 2005 Elsevier B.V. All rights reserved.

The problem of recommending items from some fixed database has been studied extensively, and two main paradigms have emerged. In content-based recommendation one tries to recommend items similar to those a given user has liked in the past, whereas in collaborative recommendation one identifies users whose tastes are similar to those of the given user and recommends items they have liked. Our approach in Fab has been to combine these two methods. Here, we explain how a hybrid system can incorporate the advantages of both methods while inheriting the disadvantages of neither. In addition to what one might call the “generic advantages” inherent in any hybrid system, the particular design of the Fab architecture brings two additional benefits. First, two scaling problems common to all Web services are addressed—an increasing number of users and an increasing number of documents. Second, the system automatically identifies emergent communities of interest in the user population, enabling enhanced group awareness and communications. Here we describe the two approaches for contentbased and collaborative recommendation, explain how a hybrid system can be created, and then describe Fab, an implementation of such a system. For more details on both the implemented architecture and the experimental design the reader is referred to [1]. The content-based approach to recommendation has its roots in the information retrieval (IR) community, and employs many of the same techniques. Text documents are recommended based on a comparison between their content and a user profile. Data

Mobile phones are an ideal platform for augmented reality. In this paper we describe how they can also be used to support face to face collaborative AR gaming. We have created a custom port of the ARToolKit library to the Symbian mobile phone operating system and then developed a sample collaborative AR game based on this. We describe the game in detail and user feedback from people who have played the game. We also provide general design guidelines that could be useful for others who are developing mobile phone collaborative AR applications.

Most textbooks in HCI and CSCW do not offer a coherent and over–arching understanding of social and technological issues. They present a variety of techniques and technologies, and outline a little history, but offer little in terms of theory that addresses the complexity of collaborative systems’ structure and use. The majority of practitioners and researchers do not see theory as one of the things that they do. Immersed in their craft, focusing on technological innovation or ethnomethodological detail, they do not engage in theoretical abstraction. Technologists contentedly explore new tools and devices, with little heed to older disciplines or deeper discussion about the limits and assumptions inherent in their craft. The area of sociology most influential in CSCW, ethnomethodology, deliberately keeps theorising and generalisation at a distance, seeing abstraction as brutish and creativity as foreign. In our field, theory is like the public library. If asked, most of us would say that we are glad that it is around—but few of us actually go there. Most see it as a haven for the old, the unemployed and the eccentric. Paul Dourish is a card–carrying member, however. He reads avidly and widely, but is also a skilful system designer and developer. The result is a book that is deep, accessible and useful, which is a rare thing nowadays. In the introduction, Dourish lays out the structure of the book. He describes and reflects on two current trends in system design: tangible and social computing. By looking at the usually hidden assumptions in system design, he makes his later theoretical discussion more relevant and accessible to a computer science audience. He does not develop new philosophy or social theory, but draws upon established 20th century philosophy of language and phenomenology. Much of this material is likely to be unfamiliar to ‘the average programmer’ and, although Dourish presents it well, it may still be challenging to the reader. However, its use is one of the book’s main contributions. He uses it to ground a conceptual framework and a corresponding set of principles for system design practice. He aims to do justice to the sociality and heterogeneity of interactive media, and to avoid putting theory above practice—or vice versa. His ideal is balance: “the ability to develop systemsthat resonate with, rather than restrict (or, worse, refute), the social organization of action”. The term ‘tangible computing’ is used very broadly in this book. The chapter on this theme covers the designs of Hiroshi Ishii’s group at MIT’s Media Lab, but also ubiquitous computing work such as the badges, tabs and LiveBoards of Xerox PARC, and augmented reality systems such as Pierre Wellner’s DigitalDesk. Although ‘UbiComp’ is more fashionable nowadays, Dourish chooses a term that helps him focus more on our perception and “the ways we experience the everyday world” than on computation and technology. Much of this discussion centres on exemplary systems, and the way that an increasing number and variety of computational devices and sensors are distributed in our environment. This contrasts with older systems that used very few media and which were encapsulated in the beige box of the traditional PC. The following chapter is on social computing: “the application of sociological understanding to the design of interactive systems”. This stands in contrast to the more traditional tendency for designers to treat people as isolated system users, with little account taken of organisational and social context. Dourish draws upon some influential studies of existing technology such as that of an air traffic control room by Hughes et al., and the ethnography of a print shop by Bowers, Button and Sharrock. Compared to the previous chapter, exemplary systems are scarce. There are none of the previous chapter’s attractive images of exotic displays and devices, so beloved in undergraduate lectures and conference presentations, as this chapter addresses systems’ internal structure rather than external interaction. Dourish has developed more systems in the ‘social’ category than the ‘tangible’, and here he offers as examples Mansfield et al.’s Orbit and some of his own work: using a system design technique, computational reflection, to offer users an account of deep system structure. In describing this particular technique, Dourish touches on the essence of the entire book: What is radical is the relationship it proposes between technical design and social understandings. It argues that the most fruitful place to forge these relationships is at a foundational level, one that attempts to take sociological insights into the heart of the process and fabric of design. (p. 87)

In the past decade, multi-touch-sensitive interactive surfaces have transitioned from pure research prototypes in the lab, to commercial products with wide-spread adoption. One of the longer term visions of this research follows the idea of ubiquitous computing, where everyday surfaces in our environment are made interactive. However, most of current interfaces remain firmly tied to the traditional flat rectangular displays of the today's computers and while they benefit from the directness and the ease of use, they are often not much more than touch-enabled standard desktop interfaces.
 In this paper, we argue for explorations that transcend the traditional notion of the flat display, and envision interfaces that are curved, three-dimensional, or that cross the boundary between the digital and physical world. In particular, we present two research directions that explore this idea: (a) exploring the three-dimensional interaction space above the display and (b) enabling gestural and touch interactions on curved devices for novel interaction possibilities. To illustrate both of these, we draw examples from our own work and the work of others, and guide the reader through several case studies that highlight the challenges and benefits of such novel interfaces. The implications on media requirements and collaboration aspects are discussed in detail, and, whenever possible, we highlight promising directions of future research. We believe that the compelling application design for future non-flat user interfaces will greatly depend on exploiting the unique characteristics of the given form factor.