Privacy-preserving proximity detection with secure multi-party computational geometry

Over the last years, Location-Based Services (LBSs) have become popular due to the global use of smartphones and improvement in Global Positioning System (GPS) and other positioning methods. Location-based services employ users' location to offer relevant information to users or provide them with useful recommendations. Meanwhile, with the development of social applications, location-based social networking services (LBSNS) have attracted millions of users because the geographic position of users can be used to enhance the services provided by those social applications. Proximity detection, as one type of location-based function, makes LBSNS more flexible and notifies mobile users when they are in proximity. Despite all the desirable features that such applications provide, disclosing the exact location of individuals to a centralized server and/or their social friends might put users at risk of falling their information in wrong hands, since locations may disclose sensitive information about people including political and religious affiliations, lifestyle, health status, etc. Consequently, users might be unwilling to participate in such applications. To this end, private proximity detection schemes enable two parties to check whether they are in close proximity while keeping their exact locations secret. In particular, running a private proximity detection protocol between two parties only results in a boolean value to the querier. Besides, it guarantees that no other information can be leaked to the participants regarding the other party's location. However, most proposed private proximity detection protocols enable users to choose only a simple geometric range on the map, such as a circle or a rectangle, in order to test for proximity. In this thesis, we take inspiration from the field of Computational Geometry and develop two privacy-preserving proximity detection protocols that allow a mobile user to specify an arbitrary complex polygon on the map and check whether his/her friends are located therein. We also analyzed the efficiency of our solutions in terms of computational and communication costs. Our evaluation shows that compared to the similar earlier work, the proposed solution increases the computational efficiency by up to 50%, and reduces the communication overhead by up to 90%. Therefore, we have achieved a significant reduction of computational and communication complexity

Neo: Virtual Object Modeling using Commodity Hardware

Recent developments in augmented reality technology have paved way for newapplications in a wide range of areas. These include the commercial markets,medicine applications, military applications and education. The technology pro-vides immersive images to enhance our perception of the world. Augmentedreality addresses challenges related to problem-solving by seamlessly integrat-ing digital images into real-world images.In the context of construction and maintenance industry, project inspections canbe time-consuming and tedious. These inspections involve usages of expensiveand specialized hardware. Some inspections even use physical blueprints anddrawings along with standardized measurement tools. This approach can posepractical challenges and be prone to errors.In this thesis we present Neo, a surface reconstruction system on commodityhardware. It utilizes augmented reality technology by scanning physical sur-roundings and reconstructs them as virtual objects. They are displayed on topof the camera’s live preview of the real world. By using a pipeline architecturewe model the physical surroundings in terms of their shapes and visual appear-ances. Cyber-physical information about the reconstructed virtual models areannotated in real-time. Evaluations of the system show us potentials to createrealistic copies of physical object

Kinetic collision detection for balls rolling on a plane

This abstract presents a first step towards kinetic col- lision detection in 3 dimensions. In particular, we design a compact and responsive kinetic data struc- ture (KDS) for detecting collisions between n balls of arbitrary sizes rolling on a plane. The KDS has size O(n log n) and can handle events in O(log n) time. The structure processes O(n2) events in the worst case, assuming that the objects follow low-degree al- gebraic trajectories. The full paper [1] presents ad- ditional results for convex fat 3-dimensional objects that are free-flying in R3

CIRSS vertical data integration, San Bernardino study

The creation and use of a vertically integrated data base, including LANDSAT data, for local planning purposes in a portion of San Bernardino County, California are described. The project illustrates that a vertically integrated approach can benefit local users, can be used to identify and rectify discrepancies in various data sources, and that the LANDSAT component can be effectively used to identify change, perform initial capability/suitability modeling, update existing data, and refine existing data in a geographic information system. Local analyses were developed which produced data of value to planners in the San Bernardino County Planning Department and the San Bernardino National Forest staff

Human-aware navigation for autonomous mobile robots for intra-factory logistics

This paper presents a human-aware navigation system for mobile robots targeted to cooperative assembly in intra-factory logistics scenarios. To improve overall efficiency of the operator-robot ensemble, assembly stations and operators are modelled as cost functions in a layered cost map supporting the robot navigation system. At each new sensory update, the system uses each operator’s estimated location to affect the cost map accordingly. To promote predictability and comfort in the human operator, the cost map is affected according to the Proxemics theory, properly adapted to take into account the layout activity space of the station in which the operator is working. Knowledge regarding which task and station are being handled by the operator are assumed to be given to the robot by the factory’s computational infrastructure. To foster integration in existing robots, the system is implemented on top of the navigation system of the Robot Operating System (ROS).info:eu-repo/semantics/acceptedVersio

City of Redlands Safe Routes to Schools Shadow Mapping

The City of Redlands seeks to improve the tree canopy coverage over key pedestrian zones with the intention of providing more shade to pedestrians in support of the Safe Routes to School Program. An analysis of the current canopy and the shaded sidewalks allowed city planners to distinguish those areas that are both “walkable” and in need of more shade. LIDAR data can generate a detailed and accurate measurement of the city’s canopy index, and was used to determine the total shadow coverage of trees and buildings. Overlaid with priority sidewalks, this map identified pedestrian zones in need of shade. The results allow the City of Redlands to more clearly understand the current canopy near school zones, and determine areas with a deficit of shade coverage

Investigating the efficacy of a proposed marine protected area for the Endangered humphead wrasse Cheilinus undulatus at a remote island group in Seychelles

The humphead wrasse Cheilinus undulatus is an iconic, ecologically important and Endangered fish species associated with coral reefs in the Indo-Pacific region. Due to its large size and complex life history characteristics, it is vulnerable to overfishing and has undergone substantial population declines in parts of its range. Knowledge of the species’ movement ecology is currently limited to only 2 previous studies, and very little is known about populations in the western Indian Ocean. The present study aimed to use passive acoustic telemetry to investigate the importance of a remote coral reef to a population of humphead wrasse in the Republic of Seychelles, and subsequently assess the efficacy of a proposed marine protected area at this location for protection of the species. Tagged fish (n = 20) exhibited persistent (\u3e500 d) site fidelity, with low dispersal distances (mean ± SD: 6.44 ± 4.0 km) and restricted core activity spaces (50% Brownian bridge kernel utilization density: 0.91 ± 0.61 km2). Additionally, the study site was home to a group of large (total length 97.9 ± 20.6 cm) and currently unexploited humphead wrasse that showed long-term predictable site fidelity and thus could be vulnerable to over-exploitation. The establishment of a proposed no-take marine protected area at the study site would encompass the core home range area of all tagged humphead wrasse and could effectively conserve this stronghold of Endangered fish to ensure the persistence of the species in Seychelles waters

Mountain Lion Resource Selection in the California Central Coast: Modeling Habitat Suitability for a Large Carnivore in a Rapidly Changing Environment

Land use conversion toward agriculture such as orchards and vineyards can have severe negative impacts on habitat and wildlife, particularly large carnivores, globally through habitat fragmentation and loss. The mountain lion (Puma concolor) population in the California Central Coast is thought to provide “stepping-stone” connectivity between several severely genetically compromised coastal populations throughout the Santa Cruz Mountains and several mountain ranges in Southern California; however, the California Central Coast is one of the fastest-developing regions of California with little protection against future land use conversion. Conserving areas of and corridors between high-quality mountain lion habitat through conservation easements should be prioritized. Our results showed that this is especially important in areas currently zoned for agriculture and residential but not fully developed yet. Conserving quality habitat is not only beneficial to mountain lions, but also many species underneath their ecological “umbrella.” In my first chapter, I performed a literature review detailing what ecologists currently understand about human impacts on wildlife, with an emphasis on large carnivores, through habitat fragmentation and loss, land conversion, and human-carnivore conflict. I also reflected on mountain lion ecology and management in California and North America as a whole, before reviewing analytical methods most commonly used to study their home ranges and resource selection. In my second chapter, I used GPS collar data from seven GPS-collared mountain lions on the Fort Hunter Liggett Army Base in Monterey County, California to compare minimum convex polygon, kernel density isopleth, and adaptive-local convex hull methods to elucidate the strengths and weaknesses of each when estimating wildlife home ranges and utilization distributions. Following this, I used the GPS data to create a resource selection function to model predicted resource selection patterns of the mountain lions on the Army Base before projecting my model out to the counties comprising the greater California Central Coast. I then overlaid this habitat suitability map with zoning and land protection status maps from each county. My results provide a clear visual representation of not only mountain lion habitat suitability throughout the Central Coast, but areas wildlife and land managers should prioritize for conservation in relation to adjacent areas of varying zoning and protection statuses