Exploring MARS: developing indoor and outdoor user interfaces to a mobile augmented reality system

We describe an experimental mobile augmented reality system (MARS) testbed that employs different user interfaces to allow outdoor and indoor users to access and manage information that is spatially registered with the real world. Outdoor users can experience spatialized multimedia presentations that are presented on a head-tracked, see-through, head-worn display used in conjunction with a hand-held pen-based computer. Indoor users can get an overview of the outdoor scene and communicate with outdoor users through a desktop user interface or a head- and hand-tracked immersive augmented reality user interface.     

Predicting user personality by mining social interactions in Facebook

Adaptive applications may benefit from having models of users? personality to adapt their behavior accordingly. There is a wide variety of domains in which this can be useful, i.e., assistive technologies, e-learning, e-commerce, health care or recommender systems, among others. The most commonly used procedure to obtain the user personality consists of asking the user to fill in questionnaires. However, on one hand, it would be desirable to obtain the user personality as unobtrusively as possible, yet without compromising the reliability of the model built. On the other hand, our hypothesis is that users with similar personality are expected to show common behavioral patterns when interacting through virtual social networks, and that these patterns can be mined in order to predict the tendency of a user personality. With the goal of inferring personality from the analysis of user interactions within social networks, we have developed TP2010, a Facebook application. It has been used to collect information about the personality traits of more than 20,000 users, along with their interactions within Facebook. Based on all the collected data, automatic classifiers were trained by using different machine-learning techniques, with the purpose of looking for interaction patterns that provide information about the users? personality traits. These classifiers are able to predict user personality starting from parameters related to user interactions, such as the number of friends or the number of wall posts. The results show that the classifiers have a high level of accuracy, making the proposed approach a reliable method for predicting the user personality     

From telephones to iPhones: applying systems thinking to networked, interoperable products

An expanding array of consumer products have the facility to have things added in and plugged on, their firmware upgraded, and as yet un-thought of future capability supported. In short, more and more products can be connected to something and/or someone, and in doing so are slowly adapting to the current day state of modernity that is called ‘the information age’. Inevitably, this brings with it changes in the way that products should be thought about and designed. The purpose of this paper is to try and help product designers and Ergonomists to get a grip on all the complexity and non-linearity that the information age brings with it, and help make themselves and their increasingly networked and interoperable products at home in it. Our case study, Apple's new iPhone, serves as a pertinent example.     

Modeling user behavior data in systems of engagement

The proliferation of mobile devices has changed the way digital information is consumed and its efficacy measured. These personal devices know a lot about user behavior from embedded sensors along with monitoring the daily activities users perform through various applications on these devices. This data can be used to get a deep understanding of the context of the users and provide personalized services to them. However, there are a lot of challenges in capturing, modeling, storing, and processing such data from these systems of engagement, both in terms of achieving the right balance of redundancy in the captured and stored data, along with ensuring the usefulness of the data for analysis. There are additional challenges in balancing how much of the captured data should be processed through client or server applications. In this article, we present the modeling of user behavior in the context of personalized education which has generated a lot of recent interest. More specifically, we present an architecture and the issues of modeling student behavior data, captured from different activities the student performs during the process of learning. The user behavior data is modeled and sent to the cloud-enabled backend where detailed analytics are performed to understand different aspects of a student, such as engagement, difficulties, and preferences and to also analyze the quality of the data.     

A complex event routing infrastructure for distributed systems

With the growing number of mega services and cloud computing platforms, industrial organizations are utilizing distributed data centers at increasing rates. Rather than the request/reply model, these centers use an event-based communication model. Traditionally, the event-based middleware and the Complex Event Processing (CEP) engine are viewed as two distinct components within a distributed system’s architecture. This division adds additional system complexity and reduces the ability for consuming applications to fully utilize the CEP toolset. This article will address these issues by proposing a novel event-based middleware solution. We introduce Complex Event Routing Infrastructure (CERI), a single event-based infrastructure that serves as an event bus and provides first class integration of CEP. An unstructured peer-to-peer network is exploited to allow for efficient event transmission. To reduce network flooding, superpeers and overlay network partitioning are introduced. Additionally, CERI provides each client node the capability of local complex query evaluation. As a result, applications can offload internal logic to the query evaluation engine in an efficient manner. Finally, as more client nodes and event types are added to the system, the CERI can scale up. Because of these favorable scaling properties, CERI serves as a foundational step in bringing event-based middleware and CEP closer together into a single unified infrastructure component.     

Complex agent networks: An emerging approach for modeling complex systems

Complexity and complex systems are all around us: from molecular and cellular systems in biology up to economics and human societies. There is an urgent need for methods that can capture the multi-scale spatio-temporal characteristics of complex systems. Recent emphasis has centered on two methods in particular, those being complex networks and agent-based models. In this paper we look at the combination of these two methods and identify “Complex Agent Networks”, as a new emerging computational paradigm for complex system modeling. We argue that complex agent networks are able to capture both individual-level dynamics as well as global-level properties of a complex system, and as such may help to obtain a better understanding of the fundamentals of such systems.     

Enabling collaborative work: Work in progress

Mobile handheld and wearable computer systems to support fieldworkers (e.g. aircraft mechanics) doing a variety of tasks have been designed and studied by Carnegie Mellon University (CMU) researchers since 1991. We developed an initial research agenda and found some important results associated with the design and use of such systems. This article summarises some of the key findings from CMU's research and describes the results from one heuritic usability study about mobile handheld and wearable computer systems. Based on these research results, we put forward a new research agenda addressing important issues still to be resolved.     

User modeling in dialog systems: Potentials and hazards

In order to be capable of exhibiting a wide range of cooperative behavior, a computer-based dialog system must have available assumptions about the current user's goals, plans, background knowledge and (false) beliefs, i.e., maintain a so-called user model. Apart from cooperativity aspects, such a model is also necessary for intelligent coherent dialog behavior in general. This article surveys recent research on the problem of how such a model can be constructed, represented and used by a system during its interaction with the user. Possible applications, as well as potential problems concerning the advisability of application, are then discussed. Finally, a number of guidelines are presented which should be observed in future research to reduce the risk of a potential misuse of user modeling technology.     

Uncertainty handling in rule-based mobile context-aware systems

Uncertainty handling is one of the most important aspects of modelling of context-aware systems. It has direct impact on the adaptability, understood as an ability of the system to adjust to changing environmental conditions or hardware configuration (missing data), changing user habits (ambiguous concepts), or imperfect information (low quality sensors). In mobile context-aware systems, data is most often acquired from device’s hardware sensors (like GPS, accelerometer), virtual sensors (like activity recognition sensor provided by the Google API) or directly from the user. Uncertainty of such data is inevitable, and therefore it is obligatory to provide mechanisms for modelling and processing it. In this paper, we propose three complementary methods for dealing with most common uncertainty types present in mobile context-aware systems. We combine modified certainty factors algebra, probabilistic interpretation of rule-based model, and time-parametrised operators into a comprehensive toolkit for modelling and building robust mobile context-aware systems. Presented approach was implemented and evaluated on the practical use-case.     

Agent-based computational economics: modeling economies as complex adaptive systems

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization to economics of the basic complex adaptive systems paradigm. This paper outlines the main objectives and defining characteristics of the ACE methodology, and discusses several active research areas.     

ALGINEER: Algorithmic design of complex systems

The design of complex systems has been the forte of and therefore limited to engineers while algorithms have only aided in the representation and optimization of the design options. This human-centric approach has several limitations that leads to sub-optimal design results. In this work, a novel algorithmic design framework ALGINEER is proposed with a concept-proof implementation that overcomes the limitations. ALGINEER formalizes the design processes to isolate the design process from the design problem. It implements genetic algorithms and machine learning to explore the complete solution space, achieve trade-off among many design objectives, and demonstrate design behavior and learning akin to engineers. It is modular, scalable and empowers engineers to concentrate more on problem formulation. The work also suggests future research possibilities towards extending ALGINEER’s abilities.     

Social weight: designing to minimise the social consequences arising from technology use by the mobile professional

This paper defines the concept of social weight as a design consideration and presents the e-SUIT, a social weight research platform incorporated covertly within a traditional business suit. The e-SUIT allows its user to strike a balance between a given technology's derived benefit and its social consequence. As the e-SUIT is designed for research within a business context, it is built upon commercially available enterprise software. This work is a first step towards subjecting the empirical social interactive phenomena of wearable technology to quantitative design analysis. Proof of concept testing shows access to commercially available enterprise applications with a distinct, user selectable, strata of social weight.     

Information systems as social systems: Implications for developing countries

Abstract

Computer‐based information systems should be conceptualised as social systems in which technology is only one of the dimensions. This broader perspective on information systems offers opportunities for a deeper understanding of their development and use. The social systems approach is illustrated in the paper by two research projects in the UK on the evaluation of information systems and information systems strategy formulation. The relevance of the UK research to a developing country context is discussed and it is argued that methodologies which aim to provide an understanding of the organisational, social and political context are highly suitable for organisations in developing countries. Some implications are drawn for research, education and practice related to information systems in developing countries.     

The effectiveness of office information systems: a social action perspective

Abstract. The purpose of this paper is to show that a number of basic issues have not been adequately addressed in existing office information systems research. Prominent among these are the nature and role of offices, the goals of office information systems development, and the nature of its organizational and managerial consequences. It is proposed that office information systems should be analysed as social action systems the behaviour of which is strongly affected by socially determined forces and constraints such as the behaviour-channelling influences of authority, norms, customs, habits and precedence. Four types of social action are discussed: instrumental, strategic, communicative and discursive. Three contexts for perceiving and analysing the effects of social action in offices are introduced: technology, language and organization. Office information systems changes affect elements and relationships in these three contexts in different ways. By cross-relating social action types and contexts, nine classes of object systems are identified. Each object system class implies a different category of effectiveness concerns which in turn implies different office information system design requirements. The paper notes that the existing research literature has primarily been concerned with only three of the nine object systems. For more effective office information systems development, however, the other systems also need to be considered. The paper concludes by exploring how this may be done.     

A high performance framework for modeling and simulation of large-scale complex systems

Due to the quick advances in the scale of problem domain of complex systems under investigation, the complexity of multi-input component models used to construct logical processes (LP) has significantly increased. High-performance computing technologies have therefore been extensively used to enable parallel simulation execution. However, the traditional multi-process parallel method (MPM) executes LPs in parallel on multi-core platforms, which ignores the intrinsic parallel capabilities of multi-input component models. In this study, a vectorized component model (VCM) framework has been proposed. The design aims to better utilize the parallelism of multi-input component models. A two-level composite parallel method (CPM) has then been constructed within the framework, which can sustain complex system simulation applications consisting of multi-input component models. CPM first employs MPM to dispatch LPs onto a multi-core computing platform. It then maps VCMs to the multiple-core platform for parallel execution. Experimental results indicate that (1) the proposed VCM framework can better utilize the parallelism of multi-input component models, and (2) CPM can significantly improve the performance comparing to the traditional MPM. The results also show that CPM can effectively cope with the size and complexity of complex simulation applications with multi-input component models.     

GemCell: A generic platform for modeling multi-cellular biological systems

The mass and complexity of biological information requires computer-aided simulation and analysis to help scientists achieve understanding and guide experimentation. Although living organisms are composed of cells, actual genomic and proteomic data have not yet led to a satisfactory model of working cell in silico. We have set out to devise a user-friendly generic platform, GemCell, for Generic Executable Modeling of Cells, based on whole, functioning cells. Starting with the cell simplifies life, because all cells expresses essentially five generic types of behavior: replication, death, movement (including change of shape and adherence), export (secretion, signaling, etc.) and import (receiving signals, metabolites, phagocytosis, etc.). The details of these behaviors are specified in GemCell for particular kinds of cells as part of a database of biological specifics (the DBS), which specifies the cell properties and functions that depend on the cell’s history, state, environment, etc. The DBS is designed in an intuitive fashion, so users are able to easily insert their data of interest. The generic part of GemCell, built using Statecharts, is a fully dynamic model of a cell, its interactions with the environment and its resulting behavior, individually and collectively. Model specificity emerges from the DBS, so that model execution is carried out by the statecharts executing with the aid of specific data extracted from the DBS dynamically. Our long term goal is for GemCell to serve as a broadly applicable platform for biological modeling and analysis, supporting user-friendly in silico experimentation, animation, discovery of emergent properties, and hypothesis testing, for a wide variety of biological systems.     

Considerate home notification systems: A user study of acceptability of notifications in a living-room laboratory

Recent field experiments on acceptability of notifications in the home showed that people generally want to be informed of urgent messages as soon as possible, whereas non-urgent messages should not be presented at all. A possible way to improve the acceptability of a notification might be to adjust the presentation mode and the timing of notifications to the message content and to the state of the user. For example, acceptability might be improved by considering user activities when selecting the best time to present the message. The relation between acceptability, presentation mode and timing has not been formally studied in a controlled home setting before. This paper presents the results of a user study, in which 10 participant couples were asked to engage in everyday home activities, and to subjectively rate factors that were expected to influence acceptability. The study was situated in a living-room laboratory in which the user activities and the timing of notifications were controlled. Questionnaire data was evaluated using cluster analysis in order to construct a semantic model that describes the relationship between user, system and environment. The key findings in the present study are: (1) acceptability could be improved by adjusting the level of intrusiveness of the presentation to message urgency: urgent messages should be presented intrusively, medium-urgent messages unobtrusively, and (2) non-urgent messages should be postponed until the message urgency has increased, or skipped if the message urgency never exceeds the predefined presentation threshold. Surprisingly, the user activities at the time of notification were not found to influence acceptability. These findings have resulted in a model of acceptability of notifications for the design of future home notification systems.     

On principles in engineering of distributed computing systems

Engineering of distributed computing systems requires understanding of principles of complex systems, which have not been yet identified. To address the situation we use a concept of structural complexity and present results of computational experiments suggesting the possibility of a general optimality condition of complex systems. The optimality condition introduces the structural complexity of a system as a key to its optimization.     

Fostering artificial societies using social learning and social control in parallel emergency management systems

How can we foster and grow artificial societies so as to cause social properties to emerge that are logical, consistent with real societies, and are expected by designers? We propose a framework for fostering artificial societies using social learning mechanisms and social control approaches. We present the application of fostering artificial societies in parallel emergency management systems. Then we discuss social learning mechanisms in artificial societies, including observational learning, reinforcement learning, imitation learning, and advice-based learning. Furthermore, we discuss social control approaches, including social norms, social policies, social reputations, social commitments, and sanctions.