Professional basketball teams, NY Stars versus Milwaukee Does

General note: Title and date provided by Bettye Lane.

Professional Basketball teams, the NY Stars and the Milwaukee Does

General note: Title and date provided by Bettye Lane.

High accuracy mobile robot positioning using an external large volume metrology instrument

A method of accurately controlling the position of a mobile robot using an external Large Volume Metrology (LVM) instrument is presented in this paper. Utilizing a LVM instrument such as the laser tracker in mobile robot navigation, many of the most difficult problems in mobile robot navigation can be simplified or avoided. Using the real- Time position information from the laser tracker, a very simple navigation algorithm, and a low cost robot, 5mm repeatability was achieved over a volume of 30m radius. A surface digitization scan of a wind turbine blade section was also demonstrated, illustrating possible applications of the method for manufacturing processes. © Springer-Verlag Berlin Heidelberg 2010.

Relational work in synchronous text-based CMC of virtual teams

Based on close examinations of instant message (IM) interactions, this chapter argues that an interactional sociolinguistic approach to computer-mediated language use could provide explanations for phenomena that previously could not be accounted for in computer-mediated discourse analysis (CMDA). Drawing on the theoretical framework of relational work (Locher, 2006), the analysis focuses on non-task oriented talk and its function in forming and establishing communication norms in the team, as well as micro-level phenomena, such as hesitation, backchannel signals and emoticons. The conclusions of this preliminary research suggest that the linguistic strategies used for substituting audio-visual signals are strategically used in discursive functions and have an important role in relational work

Engaged work teams

The Handbook presents comprehensive and global perspectives to help researchers and practitioners identify, understand, evaluate and apply the key theories, models, measures and interventions associated with employee engagement. It provides many new insights, practical applications and areas for future research. It will serve as an important platform for ongoing research and practice on employee engagement.

Game-Theoretically Allocating Resources to Catch Evaders and Payments to Stabilize Teams

Allocating resources optimally is a nontrivial task, especially when multiple

self-interested agents with conflicting goals are involved. This dissertation

uses techniques from game theory to study two classes of such problems:

allocating resources to catch agents that attempt to evade them, and allocating

payments to agents in a team in order to stabilize it. Besides discussing what

allocations are optimal from various game-theoretic perspectives, we also study

how to efficiently compute them, and if no such algorithms are found, what

computational hardness results can be proved.

The first class of problems is inspired by real-world applications such as the

TOEFL iBT test, course final exams, driver's license tests, and airport security

patrols. We call them test games and security games. This dissertation first

studies test games separately, and then proposes a framework of Catcher-Evader

games (CE games) that generalizes both test games and security games. We show

that the optimal test strategy can be efficiently computed for scored test

games, but it is hard to compute for many binary test games. Optimal Stackelberg

strategies are hard to compute for CE games, but we give an empirically

efficient algorithm for computing their Nash equilibria. We also prove that the

Nash equilibria of a CE game are interchangeable.

The second class of problems involves how to split a reward that is collectively

obtained by a team. For example, how should a startup distribute its shares, and

what salary should an enterprise pay to its employees. Several stability-based

solution concepts in cooperative game theory, such as the core, the least core,

and the nucleolus, are well suited to this purpose when the goal is to avoid

coalitions of agents breaking off. We show that some of these solution concepts

can be justified as the most stable payments under noise. Moreover, by adjusting

the noise models (to be arguably more realistic), we obtain new solution

concepts including the partial nucleolus, the multiplicative least core, and the

multiplicative nucleolus. We then study the computational complexity of those

solution concepts under the constraint of superadditivity. Our result is based

on what we call Small-Issues-Large-Team games and it applies to popular

representation schemes such as MC-nets.

Athlete Perceptions of Intra-Group Conflict in Sport Teams

The study of conflict has been of primary interest in various fields such as organisational psychology for decades (e.g. Barki & Hartwick, 2004). In sport psychology, however, conflict research has been almost nonexistent (Lavoi, 2007) with few exceptions (e.g. Holt et al., 2012; Sullivan & Feltz, 2001). The importance of understanding conflict in sport and in groups, however, has been acknowledged because it has potentially serious implications for group outcomes (Lavoi, 2007). The present study investigated competitive sport athletes’ perceptions of intra-group conflict in sport. Ten intercollegiate athletes: (N=5 males, N=5 females; Mage=25.00, SD=2.87) participated in semi-structured interviews. Athletes perceived the nature of conflict to manifest itself in several ways including: (a) disagreements; (b) negative emotions; and (c) interference/antagonistic behaviors. In addition, conflict episodes were perceived to arise in task and social situations. The findings are discussed in terms of their contributions to current perspectives on intra-group conflict in sport.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

The effects of conflict in driving forward innovation in shared leadership management consultant teams

It is argued in this study that current investigations of the role of conflict in shared leadership teams and, thus, teams in which all members have the opportunity to participate in its decision-making process are insufficient as they have focused on the downsides of these conflicts. This study demonstrates that task conflict is beneficial in that it can have positive effects on innovation in teams. It shows that particularly in shared leadership management consultant teams task conflict can stimulate innovation. Therefore, this research investigates the relationships among shared leadership, conflict and innovation. The research develops and empirically tests a conceptual model which demonstrates the relationships between these concepts and for which the inclusion of multiple research methods was essential. The sequential explanatory approach included a combination of quantitative and qualitative methods, the order of which can be adapted for other domains of application. The conceptual model was first tested with a sample of 329 management consultants. This was followed by 25, in-depth, face-to-face interviews conducted with individual survey respondents. In addition, weekly meetings of a management consultant team in action were video recorded over several months. This allowed for an in-depth explanation of the findings from the survey by providing an understanding of the underlying processes. The inclusion of observational methods provided a validating role and explained how and why conflicts contributed to the development of team innovation, through the analysis of subtleties and fleeting disagreements in a real-life management consultant team. The results deliver an assessment of the theoretical model and demonstrate that task conflict can allow for additional innovation in management consultant teams operating under a shared leadership structure. A practical model and guidelines for management consultant teams wanting to enhance their innovatory capacities are provided. In addition, a novel-user methodology which includes video observations is developed, with recommendations and steps aiding researchers aiming to employ a similar combination of methods. An original contribution to knowledge is made regarding the positive effects that task conflict can have towards innovation in shared leadership teams. Collaboration and trust are identified as important mediators between shared leadership and task conflict and significant regarding the development of innovation. The effectiveness of shared leadership in reducing negative relationship conflict and the benefits of both shared leadership and task conflict in enhancing innovation are demonstrated.

Pose estimation of a humanoid robot using images from a mobile external camera

NOGUEIRA, Marcelo B. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. Pose Estimation of a Humanoid Robot Using Images from an Mobile Extern Camera. In: IFAC WORKSHOP ON MULTIVEHICLE SYSTEMS, 2006, Salvador, BA. Anais... Salvador: MVS 2006, 2006.

Multimodal attention system for an interactive robot

[EN]Social robots are receiving much interest in the robotics community. The most important goal for such robots lies in their interaction capabilities. An attention system is crucial, both as a filter to center the robot’s perceptual resources and as a mean of letting the observer know that the robot has intentionality. In this paper a simple but flexible and functional attentional model is described. The model, which has been implemented in an interactive robot currently under development, fuses both visual and auditive information extracted from the robot’s environment, and can incorporate knowledge-based influences on attention.