We describe the design of a hybrid system -- a combination of a Dynamic Graphical Model (DGM) with a Deep Neural Network (DNN) -- to identify activities performed during synthetic biology experiments. The purpose is to provide real-time feedback to experimenters, thus helping to reduce human errors and improve experimental reproducibility. The data consists of unlabeled videos of recorded experiments and "weakly supervised" information (i.e., "theoretical" and asynchronous knowledge of sets of high level activity sequences in the experiment) used to train the system. Multiple activity sequences are modeled using a trellis, and deep features are extracted from video images. Model performance is accessed using real-time online statistical inference. The trellis incorporates variations during experiment execution, making our model very general and capable of high performance.

Always-on continuous sensing apps drain the battery quickly because they prevent the main processor from sleeping. Instead, sensor hub hardware, available in many smartphones today, can run continuous sensing at lower power while keeping the main processor idle. However, developers have to divide functionality between the main processor and the sensor hub. We implement MobileHub, a system that automatically rewrites applications to leverage the sensor hub without additional programming effort. MobileHub uses a combination of dynamic taint tracking and machine learning to learn when it is safe to leverage the sensor hub without affecting application semantics. We implement MobileHub in Android and prototype a sensor hub on a 8-bit AVR micro-controller. We experiment with 20 applications from Google Play. Our evaluation shows that MobileHub significantly reduces power consumption for continuous sensing apps.

Indoor object localization can enable many ubicomp applications, such as asset tracking and object-related activity recognition. Most location and tracking systems rely on either battery-powered devices which create cost and maintenance issues or cameras which have accuracy and privacy issues. This paper introduces a system that is able to detect the 3D position and motion of a battery-free RFID tag embedded with an ultrasound detector and an accelerometer. Combining tags' acceleration with location improves the system's power management and supports activity recognition. We characterize the system's localization performance in open space as well as implement it in a smart wet lab application. The system is used to track real-time location and motion of the tags in the wet lab as well as recognize pouring actions performed on the objects to which the tag is attached. The median localization accuracy is 7.6cm -- (3.1, 5, 1.9)cm for each (x, y, z) axis -- with max update rates of 15 Sample/s using single RFID reader antenna.

Every year, loose objects inside cars during crashes cause hundreds of serious injuries and even deaths. In this paper, we describe findings from a study of 25 cars and drivers, examining the objects present in the car cabin, the reasons for them being there, and driver awareness of the potential dangers of these objects. With an average of 4.3 potentially dangerous loose objects in a car's cabin, our findings suggest that despite being generally aware of potential risks, considerations of convenience, easy access, and lack of in-the-moment awareness lead people to continue to place objects in dangerous locations in cars. Our study highlights opportunities for addressing this problem by tracking and reminding people about loose objects in cars.

Ensemble is a system that uses a collection of trusted personal devices to provide proximity-based authentication in pervasive environments. Users are able to securely pair their personal devices with previously unknown devices by simply placing them close to each other (e.g., users can pair their phones by just bringing them into proximity). Ensemble leverages a user's growing collection of trusted devices, such as phones, music players, computers and personal sensors to observe transmissions made by pairing devices. These devices analyze variations in received signal strength (RSS) in order to determine whether the pairing devices are in physical proximity to each other. We show that, while individual trusted devices can not properly distinguish proximity in all cases, a collection of trusted devices can do so reliably. Our Ensemble prototype extends Diffie-Hellman key exchange with proximity-based authentication. Our experiments show that an Ensemble-enabled collection of Nokia N800 Internet Tablets can detect devices in close proximity and can reliably detect attackers as close as two meters away.

We introduce Whack Gestures, an inexact and inattentive interaction technique. This approach seeks to provide a simple means to interact with devices with minimal attention from the user -- in particular, without the use of fine motor skills or detailed visual attention (requirements found in nearly all conventional interaction techniques). For mobile devices, this could enable interaction without "getting it out," grasping, or even glancing at the device. This class of techniques is suitable for a small number of simple but common interactions that could be carried out in an extremely lightweight fashion without disrupting other activities. With Whack Gestures, users can interact by striking a device with the open palm or heel of the hand. We briefly discuss the development and use of a preliminary version of this technique and show that implementations with high accuracy and a low false positive rate are feasible.

The four papers in this special section are extended versions of papers presented at the Seventh Annual International Conference on Mobile Systems, Applications, and Services (MobiSys 2009), held in June 2009 in Krakow, Poland.

We present Bonfire, a self-contained mobile computing system that uses two laptop-mounted laser micro-projectors to project an interactive display space to either side of a laptop keyboard. Coupled with each micro-projector is a camera to enable hand gesture tracking, object recognition, and information transfer within the projected space. Thus, Bonfire is neither a pure laptop system nor a pure tabletop system, but an integration of the two into one new nomadic computing platform. This integration (1) enables observing the periphery and responding appropriately, e.g., to the casual placement of objects within its field of view, (2) enables integration between physical and digital objects via computer vision, (3) provides a horizontal surface in tandem with the usual vertical laptop display, allowing direct pointing and gestures, and (4) enlarges the input/output space to enrich existing applications. We describe Bonfire's architecture, and offer scenarios that highlight Bonfire's advantages. We also include lessons learned and insights for further development and use.

Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people's activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, UbiFit Garden, which uses these technologies and a personal, mobile display to encourage physical activity. We conducted a 3-week field trial in which 12 participants used the system and report findings focusing on their experiences with the sensing and activity inference. We discuss key implications for systems that use on-body sensing and activity inference to encourage physical activity.

Users’ ability to accurately recall frequent, habitual activities is fundamental to a number of disciplines, from health sciences to machine learning. However, few, if any, studies exist that have assessed optimal sampling strategies for in situ self-reports. In addition, few technologies exist that facilitate benchmarking self-report accuracy for routine activities. We report on a study investigating the effect of sampling frequency of self-reports of two routine activities (sitting and walking) on recall accuracy and annoyance. We used a novel wearable sensor platform that runs a real time activity inference engine to collect in situ ground truth. Our results suggest that a sampling frequency of five to eight times per day may yield an optimal balance of recall and annoyance. Additionally, requesting self-reports at regular, predetermined times increases accuracy while minimizing perceived annoyance since it allows participants to anticipate these requests. We discuss our results and their implications for future studies.

When a mobile user dials 911, a key to arriving to the emergency scene promptly is knowing the location of the mobile user. This paper presents SkyLoc, a GSM fingerprinting-based localization system that runs on a mobile phone and identifies the current floor of a user in tall multi-floor buildings. Knowing the floor in a tall building significantly reduces the area that emergency service personnel have to canvas to locate the individuals in need. We evaluated our system in three multi-floor buildings located in Washington DC, Seattle and Toronto. Our system identifies the floor correctly in up to 73% of the cases and is within 2 floors in 97% of the cases. The system is robust as it works for different network operators, when the training and testing sets were collected with different hardware and up to one month apart. In addition, we show that feature selection techniques that select a subset of highly relevant radio sources for fingerprint matching nearly double the localization accuracy of our system

Location-based computing (LBC) is becoming increasing important in both industry and academia. A key challenge is the pervasive deployment of LBC technologies; to be effective they must run on a wide variety of client platforms, including laptops, PDAs, and mobile phones, so that location data can be acquired anywhere and accessed by any application. Moreover, as a nascent area, LBC is experiencing rapid innovation in sensing technologies, the positioning algorithms themselves, and the applications they support. Lastly, as a newcomer, LBC must integrate with existing communications and application technologies, including web browsers and location data interchange standard.This paper describes our experience in developing the Place Lab architecture, a widely used first-generation open source toolkit for client-side location sensing. Using a layered, pattern-based architecture, it supports modular development in any dimension of LBC, enabling the field to move forward more rapidly as these innovations are shared with the community as pluggable components. Our experience shows the benefits of domain-specific abstractions, and how we overcame high-level language constraints to support a wide array of platforms in this emerging space. We also describe our experience in re-engineering parts of the architecture based on the needs of the user community, including insights on software licensing issues.

Advances in location-enhanced technology are making it easier for us to be located by others. These new technologies present a difficult privacy tradeoff, as disclosing one's location to another person or service could be risky, yet valuable. To explore whether and what users are willing to disclose about their location to social relations, we conducted a three-phased formative study. Our results show that the most important factors were who was requesting, why the requester wanted the participant's location, and what level of detail would be most useful to the requester. After determining these, participants were typically willing to disclose either the most useful detail or nothing about their location. From our findings, we reflect on the decision process for location disclosure. With these results, we hope to influence the design of future location-enhanced applications and services.

Location systems have long been identified as an important component of emerging mobile applications. Most research on location systems has focused on precise location in indoor environments. However, many location applications (for example, location-aware web search) become interesting only when the underlying location system is available ubiquitously and is not limited to a single office environment. Unfortunately, the installation and calibration overhead involved for most of the existing research systems is too prohibitive to imagine deploying them across, say, an entire city. In this work, we evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system. We compare a suite of wireless-radio-based positioning algorithms to understand how they can be adapted for such ubiquitous deployment with minimal calibration. In particular, we study the impact of this limited calibration on the accuracy of the positioning algorithms. Our experiments show that we can estimate a user's position with a median positioning error of 13-40 meters (depending upon the characteristics of the environment). Although this accuracy is lower than existing positioning systems, it requires substantially lower calibration overhead and provides easy deployment and coverage across large metropolitan areas.

Recent research has shown that one can use Distributed Hash Tables (DHTs) to build scalable, robust and efficient applications. One question that is often left unanswered is that of simplicity of implementation and deployment. In this paper, we explore a case study of building an application for which ease of deployment dominated the need for high performance. The application we focus on is Place Lab, an end-user positioning system. We evaluate whether it is feasible to use DHTs as an application-independent building block to implement a key component of Place Lab: its "mapping infrastructure." We present Prefix Hash Trees, a data structure used by Place Lab for geographic range queries that is built entire on top of a standard DHT. By strictly layering Place Lab's data structures on top of a generic DHT service, we were able to decouple the deployment and management of Place Lab from that of the underlying DHT. We identify the characteristics of Place Lab that made it amenable for deploying in this layered manner, and comment on its effect on performance.

In an evolving software system, components must be able to change independently while remaining compatible with their peers. One obstacle to independent evolution is the brittle parameter problem: the ability of two components to communicate can depend on a number of inessential details of the types, structure, and/or contents of the values communicated. If these details change, then the components can no longer communicate, even if the essential parts of the message remain unaffected.We present HydroJ, an extension of Java that addresses this problem. In HydroJ, components communicate using self-describing, semi-structured messages, and programmers use pattern matching to define the handling of messages. This design stems from two central ideas: first, that self-describing messages reduce dependence on inessential message format details; and second, that object-oriented pattern matching naturally focuses on the essential information in a message and is insensitive to inessential information.We have developed these ideas in the context of Rain, a distributed, heterogeneous messaging system for ubiquitous computing. To evaluate the design, we have constructed a prototype HydroJ compiler, implemented some Rain services in HydroJ, studied the evolution of an existing Rain service over time, and formalized HydroJ's key features in a core language.

This paper describes the software architecture for our pen-based electronic whiteboard system, called Flatland. The design goal of Flatland is to support various activities on personal office whiteboards, while maintaining the outstanding ease of use and informal appearance of conventional whiteboards. The GUI framework of existing window systems is too complicated and heavy-weight to achieve this goal, and so we designed a new architecture that works as a kind of window system for penbased applications. Our architecture is characterized by its use of freeform strokes as the basic primitive for both input and output, flexible screen space segmentation, pluggable applications that can operate on each segment, and built-in history management mechanisms. This architecture is carefully designed to achieve simple, unified coding and high extensibility, which was essential to the iterative prototyping of the Flatland interface. While the current implementation is optimized for large office whiteboards, this architecture is useful for the implementation of a range of various pen-based systems.

Traditionally, designers organize software system as active end-points (e.g.applications) linked by passive infrastructures (e.g.networks).Increasingly, however, networks and infrastructures are becoming active components that contribute directly to application behavior.Amongst the various problems that this presents is the question of how such active infrastructures should be programmed.We have been developing an active document management system called Placeless Documents.Its programming model is organized in terms of properties that actively contribute to the functionality and behavior of the documents to which they are attached.This paper discusses active properties and their use as a programming model for active infrastructures.We have found that active properties enable the creation of persistent, autonomous active entities in document systems, independent of specific repositories and applications, but present challenges for managing problems of composition.

A number of recent systems have provided rich facilities for manipulating the timelines of applications. Such timelines represent the history of an application's use in some session, and captures the effects of the user's interactions with that application. Applications can use timeline manipulation techniques prosaically as a way to provide undo and redo within an application context; more interestingly, they can use these same techniques to make an application's history directly manipulable in richer ways by users. This paper presents a number of extensions to current techniques for representing and managing application timelines. The first extension captures causal relationships in timelines via a nested transaction mechanism. This extension addresses a common problem in history-based applications, namely, how to represent application state as a set of atomic, incremental operations. The second extension presents a model for "multi-level" time, in which the histories of a set of inter-related artifacts can be represented by both "local" and "global" timelines. This extension allows the histories of related objects in an application to be manipulated independently from one another.

Document properties are a compelling infrastructure on which to develop document management applications. A property-based approach avoids many of the problems of traditional heierarchical storage mechanisms, reflects document organizations meaningful to user tasks, provides a means to integrate the perspectives of multiple individuals and groups, and does this all within a uniform interaction framework. Document properties can reflect not only categorizations of documents and document use, but also expressions of desired system activity, such as sharing criteria, replication management, and versioning. Augmenting property-based document management systems with active properties that carry executable code enables the provision of document-based services on a property infrastructure. The combination of document properties as a uniform mechanism for document management, and active properties as a way of delivering document services, represents a new paradigm for document management infrastructures. The Placeless Documents system is an experimental prototype developed to explore this new paradigm. It is based on the seamless integration of user-specific, active properties. We present the fundamental design approach, explore the challenges and opportunities it presents, and show our architectures deals with them.

Programmable Embodied Agents are portable, wireless, interactive devices embodying specific, differentiable, interactive characteristics. They take the form of identifiable characters who reside in the physical world and interact directly with users. They can act as an out-of-band communication channel between users, as proxies for system components or other users, or in a variety of other roles. Traditionally, research into such devices has been based on costly custom hardware. In this paper, we report on our explorations of the space of physical character-based interfaces built on recently available stock consumer hardware platforms, structured around an initial framework of applications.

Flatland is an augmented whiteboard interface designed for informal office work. Our research investigates approaches to building an augmented whiteboard in the context of continuous, long term office use. In particular, we pursued three avenues of research based on input from user studies: techniques for the management of space on the board, the ability to flexibly apply behaviors to support varied application semantics, and mechanisms for managing history on the board. Unlike some previously reported whiteboard systems, our design choices have been influenced by a desire to support long-term, informal use in an individual office setting.

Most document or information management systems rely on hierarchies to organise documents (e.g. files, email messages or web bookmarks). However, the rigid structures of hierarchical schemes do not mesh well with the more fluid nature of everyday document practices. This paper describes Presto, a prototype system that allows users to organise their documents entirely in terms of the properties those documents hold for users. Properties provide a uniform mechanism for managing, coding, searching, retrieving and interacting with documents. We concentrate in particular on the challenges that property-based approaches present and the architecture we have developed to tackle them.

Traditional document systems use hierarchical filing structures as the basis for organizing, storing and retrieving documents. However, this structure is very limited in comparison with the rich and varied forms of document interaction and category management in everyday document use. Presto is a prototype document management system providing rich interaction with documents through meaningful, user-level document attributes, such as “Word file,” “published paper,” “shared with Jim,” “about Presto,” or “currently in progress” Document attributes capture the multiple different roles that a single document might play, and they allow users to rapidly reorganize their document space for the task at hand. They also provide a basis for novel document systems design and new approaches to document management and interaction. In this article, we outline the motivations behind this approach, describe the principal components of our implementation, discuss architectural consequences, and show how these support new forms of interactions with large personal document spaces.

The calendar queue is an important implementation of a priority queue which is particularly useful in discrete event simulators. In this paper we present an analysis of the static calendar queue which maintains N active events. A step of the discrete event simulator removes and processes the event with the smallest associated time and inserts a new event whose associated time is the time of the removed event plus a random increment with mean /spl mu/. We demonstrate that for the infinite bucket calendar queue the optimal bucket width is approximately /spl delta//sub opt/=/spl radic/(2b/c)/spl mu//N where b is the time to process an empty bucket and c the incremental time to process a list element. With bucket width chosen to be /spl delta//sub opt/, the expected time to process an event is approximately minimized at the constant c+/spl radic/(2bc)+d, where d is the fixed time to process an event. We show that choosing the number of buckets to be O(N) yields a calendar queue with performance equal to or almost equal to the performance of the infinite bucket calendar queue.>

In this paper, we investigate the practicat performance of lock-free techniques that provide synchronization on shared-memory multiprocessors.Our goal is to provide a technique to allow designers of new protocols to quickly determine an algorithm's performance characteristics.We develop a simple analytical performance model based on the architectural observations that memory accesses are expensive, synchronization instructions are more expensive, and that optimistic synchronization policies result in wasted communicationbandwidth which can slow the system as a whole.Using our model, we evaluate the performance of five existing lock-free synchronization protocols.We validate our analysis by comparing our results with simulations of a parallel machine.G;ven this analysis, we identify those protocols which show promise of good performance in practice.In addition, we note that no existing protocols provide insensitivity to common delays while still offering performance equivalent to locks.Accordingly, we introduce a protocol, based on a combination of existing lock-free techniques, which satisfies these criteria.