Hide-and-Seek with Directional Sensing

We consider a game played between a hider, who hides a static object in one of several possible positions in a bounded planar region, and a searcher, who wishes to reach the object by querying sensors placed in the plane. The searcher is a mobile agent, and whenever it physically visits a sensor, the sensor returns a random direction, corresponding to a half-plane in which the hidden object is located. We first present a novel search heuristic and characterize bounds on the expected distance covered before reaching the object. Next, we model this game as a large-dimensional zero-sum dynamic game and we apply a recently introduced randomized sampling technique that provides a probabilistic level of security to the hider. We observe that, when the randomized sampling approach is only allowed to select a very small number of samples, the cost of the heuristic is comparable to the security level provided by the randomized procedure. However, as we allow the number of samples to increase, the randomized procedure provides a higher probabilistic security level.Comment: A short version of this paper (without proofs) will be presented at the 18th IFAC World Congress (IFAC 2011), Milan (Italy), August 28-September 2, 201

Improving Spatial Thinking Through Experiential-Based Learning Across International Higher Education Settings

Research in geographic education has a strong focus on the improvement of spatial thinking. For Millennials, spatial thinking curriculum could benefit from the inclusion of experiential-based learning activities. However, as universities are faced with larger class sizes, new approaches need to be incorporated by the instructors to offer improved learning environments. Courses introducing basic geography skills often incorporate lessons concerned with spatial thinking and global perspectives. Thus, the instruction of geographic tools such as Global Positioning Systems (GPS), longitude, latitude, and remote sensing offer prime opportunities for experiential-based learning in geographic pedagogy. This research aimed to employ a low-cost experiential-based learning method incorporating a geocaching activity to strengthen spatial thinking skills. The method was employed at universities in both the United States and Ethiopia with non-geography major students at different levels of study. The effectiveness of the method was measured utilizing the pre- and post- spatial thinking ability test (STAT). Additionally, the student’s perceptions and experience with the activity were further explored through a survey. The results suggest that the geocaching activity significantly (t(133)=-2.914, p=0.004) improved the spatial thinking of the grouping of all students. These students showed significant improvements in orientation and directional abilities (p=0.000), spatial overlay and dissolve (p=0.033), and points, networks, regions/ spatial shapes and patterns (p=0.003). Additionally, students suggested they strongly agree that they enjoyed the activity (85.83%) and that the activity stimulated their thinking more than a lecture (79.69%). The findings suggest that the incorporation of an experiential-learning activity in the undergraduate classroom may lead to improvements in student spatial thinking

Drone methodologies: Taking flight in human and physical geography

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordThe world of late seems oversaturated with stories about drones. These suddenly pervasive machines straddle a divide in geography, being simultaneously an important tool for proximal sensing in physical geography and technology with military origins that human geographers have critically engaged. This paper, a collaboration between a physical and a human geographer, is an exploration of the epistemological nexus that a critical drone methodology offers the discipline, and which we suggest provides a new opportunity for collaborative human/physical geography. Drawing on our own research with drones and that of others, we demonstrate how recent scholarship on vertical geographies and longstanding remote-sensing frameworks are challenged by drone methodologies where social, environmental and technological concerns are entangled with the politics of access to proximal airspace and, in doing so, define a new conceptual atmospheric zone within the Earth's atmospheric boundary layer – the “Nephosphere” – where drone experimentation occurs. We argue that engagement with non-military uses of drones is crucial for the discipline, now that we are entering an uncertain aerial future that will be replete with flying robots, and suggest drones are reconfiguring geographic imaginations. In short, we call on geographers to participate actively in the shaping of new drone methodologies where the values and perils of the technology can be critically debated from the starting point of the experiential, rather than the speculative

Privacy, security, and trust issues in smart environments

Recent advances in networking, handheld computing and sensor technologies have driven forward research towards the realisation of Mark Weiser's dream of calm and ubiquitous computing (variously called pervasive computing, ambient computing, active spaces, the disappearing computer or context-aware computing). In turn, this has led to the emergence of smart environments as one significant facet of research in this domain. A smart environment, or space, is a region of the real world that is extensively equipped with sensors, actuators and computing components [1]. In effect the smart space becomes a part of a larger information system: with all actions within the space potentially affecting the underlying computer applications, which may themselves affect the space through the actuators. Such smart environments have tremendous potential within many application areas to improve the utility of a space. Consider the potential offered by a smart environment that prolongs the time an elderly or infirm person can live an independent life or the potential offered by a smart environment that supports vicarious learning