It is our great pleasure to welcome you to the 2012 ACM International Conference on Human-Computer Interaction with Mobile Devices and Services -- MobileHCI 2012.
MobileHCI is the world's leading conference in the field of Human Computer Interaction concerned with portable and personal devices and with the services to which they enable access. Mobile HCI provides a multidisciplinary forum for academics, hardware and software developers, designers and practitioners to discuss the challenges and potential solutions for effective interaction with and through mobile devices, applications, and services.
The conference continues to attract a significant number of submissions; this year we received 212 valid paper submissions. We have continued our commitment to improve the quality of the review process. A senior program committee of 38 internationally renowned scientists from academia and industry was assembled. Each paper received 3 or more high-quality peer reviews, as well as an additional meta review by the assigned PC member. Following last year's successful cross-Atlantic, split committee meeting, the 38 committee members assembled in two locations (Palo Alto and Berlin) that were linked by audio and video connections. This provided an opportunity for the papers and reviews to be discussed in detail and all final decisions to be agreed upon by the Program Committee as a whole.
The outcome of this process was that 54 of the 212 submissions were accepted (25%) for inclusion in the final Program, to be presented in San Francisco in September 2012. Of these, 39 were full papers and 15 were notes. A shepherding process was also used in which 6 of the 54 accepted papers were revised and improved under the expert guidance of a dedicated committee member. In our commitment to continually improving the quality of the Program, 8 papers/notes were given special recognition of excellence by being nominated for consideration as a Best Paper. A jury, consisting of 5 members of the Program Committee, was established to judge which of these papers represented the highest caliber of research in the field to be deserving of the Best Paper award. The final decision is to be revealed at the conference itself.https://dl.acm.org/ft_gateway.cfm?id=2371664&dwn=1
The problem of searching the elements of a set that are close to a given query element under some similarity criterion has a vast number of applications in many branches of computer science, from pattern recognition to textual and multimedia information retrieval. We are interested in the rather general case where the similarity criterion defines a metric space, instead of the more restricted case of a vector space. Many solutions have been proposed in different areas, in many cases without cross-knowledge. Because of this, the same ideas have been reconceived several times, and very different presentations have been given for the same approaches. We present some basic results that explain the intrinsic difficulty of the search problem. This includes a quantitative definition of the elusive concept of "intrinsic dimensionality." We also present a unified view of all the known proposals to organize metric spaces, so as to be able to understand them under a common framework. Most approaches turn out to be variations on a few different concepts. We organize those works in a taxonomy that allows us to devise new algorithms from combinations of concepts not noticed before because of the lack of communication between different communities. We present experiments validating our results and comparing the existing approaches. We finish with recommendations for practitioners and open questions for future development.https://dl.acm.org/ft_gateway.cfm?id=502808&dwn=1
On behalf of the organizing committee, we are pleased to welcome you to ACM MobiHoc 2016 held in Paderborn, Germany on July 5--8, 2016. ACM MobiHoc is a premier international symposium dedicated to addressing challenges in dynamic networks and computing. It aims bringing together researchers and practitioners from a broad spectrum of networking research to present the most up-to-date results and achievements in the field.https://dl.acm.org/ft_gateway.cfm?id=2942358&dwn=1
Agent-Based Models are used to model dynamic systems such as stock markets, societies, and complex biological systems that are difficult to model analytically using partial differential equations. Many agent-based modeling software are designed for serial von-Neumann computer architectures. That limits the speed and scalability of these systems. Systemic computation (SC) is designed to be a model of natural behavior and, at the same time, a non Von-Neumann architecture with its characteristics similar to multi-agent system. Here we propose a novel method based on an Artificial Immune System (AIS) and implemented on a systemic computer, which is designed to adapt itself over continuous arrival of data to cope with changing patterns of noise without requirement for feedback, as a result of its own experience. Experiments with heartbeat data collected from a clinical trial in hospitals using a digital stethoscope shows the algorithm performs up to 3.60% better in the precision rate of murmur and 3.96% better in the recall rate of murmur than other standard anomaly detector approaches such as Multiple Kernel Anomaly Detection (MKAD).https://dl.acm.org/ft_gateway.cfm?id=2605442&dwn=1
We describe the results of two ethnographic-style studies that investigated consumer use of photos and music respectively. Although the studies were designed, executed, and analyzed separately, in our findings we discovered striking similarities between the ways in which our participants used personally captured photos and commercially purchased music. These findings have implications for the design of future systems with respect to handling and sharing content in photo or music form. We discuss making allowances for satisficing behavior, sharing media as a way to reminisce or to communicate an experience (tell a story), getting sidetracked while browsing, and similarities in organizing behaviors.https://dl.acm.org/ft_gateway.cfm?id=1124871&dwn=1
We have developed the Artifact Map as a tool for context analysis. In a first step, this tool supports and structures the early process of, "hunting for stories" by collecting, describing and mapping all artifacts on a floor map as an anchor. Subsequently, this visible, tangible surrogate paper context is collaboratively extended and used in interviews. Doing so, users are aided in making tacit knowledge explicit, analyzing and reflecting creatively about all aspects of their workaday world. Preparing and working with the Artifact map helps to immerse quickly in a complex context, to find interesting research and design questions, and to establish a common language. Collaborative, social and work processes are jointly sketched on the map, later visually informing further design. Preparing and working with the Artifact Map is both a structured analysis process and an exploratory ethnographic method, with potential to reveal hidden issues that a normal rapid analysis would not disclose. This paper describes the preparation, use, and method in detail. We also report on our results using the Artifact Map to improve our understanding of the context of a vessel traffic center.https://dl.acm.org/ft_gateway.cfm?id=2399035&dwn=1
We introduce crowd experience as an emergent field in interaction design research. Crowds as social phenomena are already well-established as a research theme in sociology and social psychology. However, the understanding of crowds as users of technology is so far unexplored. Based on the existing literature on crowd behavior, we identify three distinct qualities of crowd experience, which we introduce to interaction design: imitation, emergence, and self-organization. These three qualities informed the design of the research prototype, BannerBattle, which is an interactive display to support crowd experiences at football stadiums. Based on findings in the case study, we discuss how crowd theory complements and challenges existing experience-centered design approaches. We suggest that crowd theory is an important resource when designing technology to support crowd experiences. Moreover, a focus on crowd experience may nuance and expand the already well-established field of experience-centered design research.https://dl.acm.org/ft_gateway.cfm?id=2399052&dwn=1
Databases of moving objects are important for air traffic control, ground traffic, and battlefield configurations. We introduce the (historical and spatial) range close-pair query for moving objects as an important problem for such databases. The purpose of a range close-pair query for moving objects is to find pairs of objects that were closer than ε during time interval $I$ and within spatial range R, where ε, I and R are user-specified parameters.This paper solves the range close-pair query using two components: the retrieval component and the close-pair identification component. The retrieval component breaks up long trajectories into trajectory segments, which are produced in increasing time order, without the need for sorting. The retrieval component takes advantage of a new index mechanism, the Multiple TSB-tree. The segments are then pipelined to the close-pair identification component. The identification component introduces a novel spatial sweep that sweeps by time and one spatial dimension at the same time. Extensive experimental results are provided, demonstrating the advantages of the new approach when considering close pairs.https://dl.acm.org/ft_gateway.cfm?id=1097067&dwn=1
Given a point set P⊆R2, a subset Q⊆ P is an ε-kernel of P if for every slab W containing Q, the (1+ε)-expansion of W also contains P. We present a data-stream algorithm for maintaining an ε-kernel of a stream of points in R2 that uses O(1/√ ε) space and takes O(log (1/ε)) amortized time to process each point. This is the first space-optimal data-stream algorithm for this problem.https://dl.acm.org/ft_gateway.cfm?id=1247071&dwn=1
The plane sweep algorithm, although widely used in computational geometry, does not parallelize efficiently, rendering it incapable of benefiting from recent trends of multi-core CPUs and general-purpose GPUs. Instead of the plane sweep, some researchers have proposed the uniform grid as a foundation for parallel algorithms of computational geometry, but long-standing robustness and performance issues have deterred its wider adoption, at least in the case of overlay analysis. To remedy that, we have developed previously missing methods to perform snap rounding and compute efficiently the winding number of overlay faces on the uniform grid, and we have implemented them as part of an extensible geometry engine to perform polygon overlay with OpenMP on CPUs and CUDA on GPUs. The overall algorithm works on any polygon configuration, either degenerate, overlapping, self-overlapping, disjoint, or with holes. On typical data, it features time and space complexities of O(N + K) where N is the number of edges and K the number of intersections. Its single-threaded performance not only rivals the plane sweep, it achieves a parallel efficiency of 0.9 on our quad-core CPU, with an additional speedup of over 4 on our GPU, a result that should extrapolate to distributed computing and other geometric operations.https://dl.acm.org/ft_gateway.cfm?id=2525352&dwn=1