Flight Measurements of the Flying Qualities of a Lockheed P-80A Airplane (Army No. 44-85099) - Stalling Characteristics

This report contains the flight-test results of the stalling characteristics measured during the flying-qualities investigation of the Lockheed P-8OA airplane (Army No. 44-85099). The tests were conducted in straight and turning flight with and without wing-tip tanks. These tests showed satisfactory stalling characteristics and adequate stall warning for all configurations and conditions tested

Player Rating Systems for Balancing Human Computation Games : Testing the Effect of Bipartiteness

Human Computation Games (HCGs) aim to engage volunteers to solve information tasks, yet suffer from low sustained engagement themselves. One potential reason for this is limited difficulty balance, as tasks difficulty is unknown and they cannot be freely changed. In this paper, we introduce the use of player rating systems for selecting and sequencing tasks as an approach to difficulty balancing in HCGs and game genres facing similar challenges. We identify the bipartite structure of user-task graphs as a potential issue of our approach: users never directly match users, tasks never match tasks. We therefore test how well common rating systems predict outcomes in bipartite versus non-bipartite chess data sets and log data of the HCG Paradox. Results indicate that bipartiteness does not negatively impact prediction accuracy: common rating systems outperform baseline predictions in HCG data, supporting our approach’s viability. We outline limitations of our approach and future work

Adapting Cognitive Task Analysis to Elicit the Skill Chain of a Game

Playing a game is a complex skill that comprises a set of more basic skills which map onto the component mechanics of the game. Basic skills and mechanics typically build and depend on each other in a nested learning hierarchy, which game designers have modelled as skill chains of skill atoms. For players to optimally learn and enjoy a game, it should introduce skill atoms in the ideal sequence of this hierarchy or chain. However, game designers typically construct and use hypothetical skill chains based solely on design intent, theory, or personal observation, rather than empirical observation of players. To address this need, this paper presents an adapted cognitive task analysis method for eliciting the empirical skill chain of a game. A case study illustrates and critically reflects the method. While effective in foregrounding overlooked low-level skills required by a game, its efficiency and generalizability remain to be proven

Effect of Loading Condition on Traction Coefficient Between Shoes and Artificial Turf Surfaces

Background. The interaction between a shoe and a turf surface is highly complex and difficult to characterize. Over the three decades since artificial turf was introduced, researchers have attempted to understand the traction caused by the interaction. However, some of the methodologies used for traction measurements have not capitalized on advances in currently available technology for testing and most testing conditions have not simulated realistic physiological loads. Method of Approach. To assess the effect of test condition on traction results, the newly designed TurfBuster testing device was used to collect traction data on FieldTurf™ brand artificial turf under varying conditions. Four cleated athletic shoes were tested under eight different vertical loads ranging from 222-1780 N. The static, dynamic, and peak traction coefficient values were calculated and averaged over three trials for each shoe and condition. Results. In all but the lowest vertical load condition, the static traction coefficient was less than the dynamic traction coefficient. There was a distinct separation found between 666 N and 888 N loading conditions for all three variables measured. Below the load condition of 666 N only one significant difference was found in all comparisons across and within shoe styles. Above 888 N multiple differences were found across shoe styles, but differences were not found within a shoe style until a load of at least 1554 N. Conclusions. At loads below 666 N the cleats perform almost identically at all three variables measured, static, dynamic, and peak traction coefficients. At loads above 888 N, shoe traction was different among the cleat styles for all traction variables. However, at loads between 888 N and 1334 N there were no differences found within a shoe style. This implies that each shoe has no performance difference in loads representative of up to one bodyweight. Due to these results the measurement of traction characteristics between cleated shoes and FieldTurf should be conducted at a load of at least 888 N to determine differences across shoe styles and loads ranging from 888 N to at least 1554 N to determine individual shoe characteristics

A quantum Bose-Hubbard model with evolving graph as toy model for emergent spacetime

We present a toy model for interacting matter and geometry that explores quantum dynamics in a spin system as a precursor to a quantum theory of gravity. The model has no a priori geometric properties, instead, locality is inferred from the more fundamental notion of interaction between the matter degrees of freedom. The interaction terms are themselves quantum degrees of freedom so that the structure of interactions and hence the resulting local and causal structures are dynamical. The system is a Hubbard model where the graph of the interactions is a set of quantum evolving variables. We show entanglement between spatial and matter degrees of freedom. We study numerically the quantum system and analyze its entanglement dynamics. We analyze the asymptotic behavior of the classical model. Finally, we discuss analogues of trapped surfaces and gravitational attraction in this simple model.Comment: 23 pages, 6 figures; updated to published versio

Gamifying research : Strategies, opportunities, challenges, ethics

From social sciences to biology and physics, gamified systems and games are increasingly being used as contexts and tools for research: as "petri dishes" for observing macro-social and economic dynamics; as sources of "big" and/or ecologically valid user behavior and health data; as crowdsourcing tools for research tasks; or as a means to motivate e.g. survey completion. However, this gamification of research comes with significant ethical ramifications. This workshop therefore explores opportunities, challenges, best practices, and ethical issues arising from different strategies of gamifying research

Engagement Effects of Player Rating System-Based Matchmaking for Level Ordering in Human Computation Games

Human computation games lack established ways of balancing the difficulty of tasks or levels served to players, potentially contributing to their low engagement rates. Traditional player rating systems have been suggested as a potential solution: using them to rate both players and tasks could estimate player skill and task difficulty and fuel player-task matchmaking. However, neither the effect of difficulty balancing on engagement in human computation games nor the use of player rating systems for this purpose has been empirically tested. We therefore examined the engagement effects of using the Glicko-2 player rating system to order tasks in the human computation game Paradox. An online experiment (n=294) found that both matchmaking-based and pure difficulty-based ordering of tasks led to significantly more attempted and completed levels than random ordering. Additionally, both matchmaking and random ordering led to significantly more di cult tasks being completed than pure difficulty-based ordering. We conclude that poor balancing contributes to poor engagement in human computation games, and that player rating system-based difficulty rating may be a viable and efficient way of improving both