From Cards to Code: How Extreme Programming Re-Embodies Programming as a Collective Practice

This paper discusses Extreme Programming (XP), a relatively new and increasingly popular ‘user-centred’ software design approach. Extreme Programming proposes that collaborative software development should be centred on the practices of programming. That proposal contrasts strongly with more heavily instrumented, formalised and centrally managed software engineering methodologies. The paper maps the interactions of an Extreme Programming team involved in building a commercial organisational knowledge management system. Using ethnographic techniques, it analyses how this particular style of software development developed in a given locality, and how it uniquely hybridised documents, conversations, software tools and office layout in that locality. It examines some of the many artifices, devices, techniques and talk that come together as a complicated contemporary software system is produced. It argues that XP's emphasis on programming as the core activity and governing metaphor can only be understood in relation to competing overtly formal software engineering approaches and the organisational framing of software development. XP, it suggests, gains traction by re-embodying the habits of programming as a collective practice. This revised version was published online in August 2006 with corrections to the Cover Date.     

Mobile context-based framework for threat monitoring in urban environment with social threat monitor

Engaging users in threat reporting is important in order to improve threat monitoring in urban environments. Today, mobile applications are mostly used to provide basic reporting interfaces. With a rapid evolution of mobile devices, the idea of context awareness has gained a remarkable popularity in recent years. Modern smartphones and tablets are equipped with a variety of sensors including accelerometers, gyroscopes, pressure gauges, light and GPS sensors. Additionally, the devices become computationally powerful which allows for real-time processing of data gathered by their sensors. Universal access to the Internet via WiFi hot-spots and GSM network makes mobile devices perfect platforms for ubiquitous computing. Although there exist numerous frameworks for context-aware systems, they are usually dedicated to static, centralized, client-server architectures. There is still space for research in the field of context modeling and reasoning for mobile devices. In this paper, we propose a lightweight context-aware framework for mobile devices that uses data gathered by mobile device sensors and performs on-line reasoning about possible threats based on the information provided by the Social Threat Monitor system developed in the INDECT project.     

Distributed formation control with relaxed motion requirements

Heterogeneous formation shape control with interagent bearing and distance constraints involves the design of a distributed control law that ensures the formation moves such that these interagent constraints are achieved and maintained. This paper looks at the design of a distributed control scheme to solve different formation shape control problems in an ambient two‐dimensional space with bearing, distance and mixed bearing and distance constraints. The proposed control law allows the agents in the formation to move in any direction on a half‐plane and guarantees that despite this freedom, the proposed shape control algorithm ensures convergence to a formation shape meeting the prescribed constraints. This work provides an interesting and novel contrast to much of the existing work in formation control where distance‐only constraints are typically maintained and where each agent's motion is typically restricted to follow a very particular path. A stability analysis is sketched, and a number of illustrative examples are also given. Copyright © 2014 John Wiley & Sons, Ltd.     

Examining the Effectiveness of Gamification in Human Computation

Within the human computation paradigm, gamification is increasingly gaining interest. This is because an enjoyable experience generated by game features can be a powerful approach to attract participants. Although potentially useful, little research has been conducted into understanding the effectiveness of gamification in human computation. In this experimental study, we operationalized effectiveness as perceived engagement and user acceptance and examined it by comparing the performance of a gamified human computation system against a non-gamified version. We also investigate the determinants of acceptance and how their effects differ between these two systems. Analysis of our data found that participants experienced more engagement and showed higher behavioral intentions toward the gamified system. Moreover, perceived output quality and perceived engagement were significant determinants of acceptance of the gamified system. In contrast, determinants for acceptance of the non-gamified system were perceived output quality and perceived usability.     

Hexabromocyclododecane: current understanding of chemistry, environmental fate and toxicology and implications for global management

Hexabromocyclododecane (HBCD) is a globally produced brominated flame retardant (BFR) used primarily as an additive FR in polystyrene and textile products and has been the subject of intensified research, monitoring and regulatory interest over the past decade. HBCD is currently being evaluated under the Stockholm Convention on Persistent Organic Pollutants. HBCD is hydrophobic (i.e., has low water solubility) and thus partitions to organic phases in the aquatic environment (e.g., lipids, suspended solids). It is ubiquitous in the global environment with monitoring data generally exhibiting the expected relationship between proximity to known sources and levels; however, temporal trends are not consistent. Estimated degradation half-lives, together with data in abiotic compartments and long-range transport potential indicate HBCD may be sufficiently persistent and distributed to be of global concern. The detection of HBCD in biota in the Arctic and in source regions and available bioaccumulation data also support the case for regulatory scrutiny. Toxicity testing has detected reproductive, developmental and behavioral effects in animals where exposures are sufficient. Recent toxicological advances include a better mechanistic understanding of how HBCD can interfere with the hypothalamic-pituitary-thyroid axis, affect normal development, and impact the central nervous system; however, levels in biota in remote locations are below known effects thresholds. For many regulatory criteria, there are substantial uncertainties that reduce confidence in evaluations and thereby confound management decision-making based on currently available information.     

Animatronic shader lamps avatars

Applications such as telepresence and training involve the display of real or synthetic humans to multiple viewers. When attempting to render the humans with conventional displays, non-verbal cues such as head pose, gaze direction, body posture, and facial expression are difficult to convey correctly to all viewers. In addition, a framed image of a human conveys only a limited physical sense of presence—primarily through the display’s location. While progress continues on articulated robots that mimic humans, the focus has been on the motion and behavior of the robots rather than on their appearance. We introduce a new approach for robotic avatars of real people: the use of cameras and projectors to capture and map both the dynamic motion and the appearance of a real person onto a humanoid animatronic model. We call these devices animatronic Shader Lamps Avatars (SLA). We present a proof-of-concept prototype comprised of a camera, a tracking system, a digital projector, and a life-sized styrofoam head mounted on a pan-tilt unit. The system captures imagery of a moving, talking user and maps the appearance and motion onto the animatronic SLA, delivering a dynamic, real-time representation of the user to multiple viewers.     

Rapid design closure of microwave components by means of feature‐based optimization and adjoint sensitivities

In this article, fast design closure of microwave components using feature‐based optimization (FBO) and adjoint sensitivities is discussed. FBO is one of the most recent optimization techniques that exploits a particular structure of the system response to “flatten” the functional landscape handled during the optimization process, which leads to reducing its computational complexity. When combined with gradient‐based search involving adjoint sensitivities, the design cost becomes even lower, allowing us to find the optimum design using just a few electromagnetic (EM) simulations of the structure at hand. Here, operation and performance of the algorithm is demonstrated using a waveguide filter and a miniaturized microstrip rat‐race coupler (RRC). Comparative studies indicate considerable savings that can be achieved even compared with adjoint‐based gradient search. In case of RRC, numerical results are supported by experimental validation.     

Multi‐objective design optimization of antennas for reflection,size, and gain variability using kriging surrogates and generalized domain segmentation

Cost‐efficient multi‐objective design optimization of antennas is presented. The framework exploits auxiliary data‐driven surrogates, a multi‐objective evolutionary algorithm for initial Pareto front identification, response correction techniques for design refinement, as well as generalized domain segmentation. The purpose of this last mechanism is to reduce the volume of the design space region that needs to be sampled in order to construct the surrogate model, and, consequently, limit the number of training data points required. The recently introduced segmentation concept is generalized here to allow for handling an arbitrary number of design objectives. Its operation is illustrated using an ultra‐wideband monopole optimized for best in‐band reflection, minimum gain variability, and minimum size. When compared with conventional surrogate‐based approach, segmentation leads to reduction of the initial Pareto identification cost by over 20%. Numerical results are supported by experimental validation of the selected Pareto‐optimal antenna designs.     

Issues in sampling and estimating continuous-time models with stochastic disturbances

The standard continuous time state space model with stochastic disturbances contains the mathematical abstraction of continuous time white noise. To work with well defined, discrete time observations, it is necessary to sample the model with care. The basic issues are well known, and have been discussed in the literature. However, the consequences have not quite penetrated the practice of estimation and identification. One example is that the standard model of an observation, being a snapshot of the current state plus noise independent of the state, cannot be reconciled with this picture. Another is that estimation and identification of time continuous models require a more careful treatment of the sampling formulas. We discuss and illustrate these issues in the current contribution. An application of particular practical importance is the estimation of models based on irregularly sampled observations.