Protective barriers are often deployed to safely guide sea turtle hatchlings to the ocean but the barriers are contentious for they impede foot and vehicle traffic of beach users. Our goal is to develop a wireless system that can detect sea turtle hatching to enable "just in time deployment" of barriers, and notify tourists so they can watch sea turtles emerge from nests, generating awareness and compassion for these endangered species. We report on the development of a sensor and data acquisition system capable of detecting nest hatching activity in the harsh environment of a beach, including sensor selection, wireless networking, low-power design, data processing and environmental packaging. Field tests confirm the suitability of a low-cost low-power three-axis accelerometer and mobile networks for detecting and remotely communicating sea turtle hatching activity.

Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. The non-von Neumann nature of the TrueNorth architecture necessitates a novel approach to efficient system design. To this end, we have developed a set of abstractions, algorithms, and applications that are natively efficient for TrueNorth. First, we developed repeatedly-used abstractions that span neural codes (such as binary, rate, population, and time-to-spike), long-range connectivity, and short-range connectivity. Second, we implemented ten algorithms that include convolution networks, spectral content estimators, liquid state machines, restricted Boltzmann machines, hidden Markov models, looming detection, temporal pattern matching, and various classifiers. Third, we demonstrate seven applications that include speaker recognition, music composer recognition, digit recognition, sequence prediction, collision avoidance, optical flow, and eye detection. Our results showcase the parallelism, versatility, rich connectivity, spatio-temporality, and multi-modality of the TrueNorth architecture as well as compositionality of the corelet programming paradigm and the flexibility of the underlying neuron model.

Citizen science projects can collect a wealth of scientific data, but that data is only helpful if it is actually used. While previous citizen science research has mostly focused on designing effective capture interfaces and incentive mechanisms, in this paper we explore the application of HCI methods to ensure that the data itself is useful. To provide a focus for this exploration we designed and implemented Creek Watch, an iPhone application and website that allow volunteers to report information about waterways in order to aid water management programs. Working with state and local officials and private groups involved in water monitoring, we conducted a series of contextual inquiries to uncover what data they wanted, what data they could immediately use, and how to most effectively deliver that data to them. We iteratively developed the Creek Watch application and website based on our findings and conducted evaluations of it with both contributors and consumers of water data, including scientists at the city water resources department. Our study reveals that the data collected is indeed useful for their existing practices and is already in use in water and trash management programs. Our results suggest the application of HCI methods to design the data for the end users is just as important as their use in designing the user interface.

This article reports on a public school that is succeeding in encouraging Latino high school students to select Computer Science (CS) as a major. The students attend a charter high school designed to encourage low-income Latino students to attend college and attain proficiency in English, Spanish, and computers. Using data from surveys and by analyzing test scores, the authors quantify the characteristics of students who are likely to choose CS as a major. A survey of 139 tenth- through twelfth-grade Latino students is used to determine factors that influence CS major selection. The survey includes questions from a previous study (836 high school math students from 9 public and private schools) as a control. Additional questions measure student interest in 20 STEM, business, and humanities subjects. Standardized test scores are correlated with factors affecting choice of CS as a major. Environment and intervention programs in, after, and outside of school are examined to consider their impact on student development. The article provides a quantitative and qualitative analysis of the relationship among academic environment and performance, subject interests, gender, and teaching methods that influence the interest of Latino high school students in choosing CS as a major.

"Shopping Buddy" is a wireless multi-media terminal that clips onto a conventional shopping cart that allows customers to scan items as they shop, providing self-checkout at the cart. Cart tracking technology enables delivery of real-time locationbased content, including "you are here" navigation map, coupons and recipes. A new cart tracking technology is developed using a cart-mounted camera viewing ceiling-mounted retro-reflective bar codes. Tag acquisition and decoding is designed to run on an inexpensive microprocessor to meet stringent system cost, size and power constraints. The image is quantized and compressed "on-the-fly" to minimize memory and processing requirements. Field testing in a retail store demonstrates system robustness under a variety of lighting conditions, delivering 5 cm spatial resolution accuracy.

Pen computing as a fieId broadly includes computers and applications in which a pen is the main input device. This field continues to draw a lot of attention from researchers because there are a number of applications where the pen is the most convenient form of input. These include: 1. preparing a first draft of a document and concentrating on content creation; 2. a socially acceptable form of capturing information in meetings, that is quieter than typing and creates minimal visual barrier; 3. applications that need privacy; 4. entering letters in ideographic languages like Chinese and Japanese and non-letter entries like graphics, music and gestures; and 5. interaction with multi-modal systems. The advent of electronic tablets in the late 1950s precipitated considerable activity in the area of pen computing. This interest ebbed in the 1970's, and was renewed in the 1980's, primarily due to advances in pen hardware technology and improvement in user-interfaces and handwriting recognition algorithms. There are still however, a number of challenges that need to be addressed before pen computing can address the needs listed above to a acceptable level of user satisfaction. In the paper, an overview of three aspects of pen computing are presented: pen input hardware, handwriting recognition and pen computer applications.

A non-contact sensor based on the interaction of a person with electric fields for human-computer interface is investigated. Two sensing modes are explored: an external electric field shunted to ground through a human body, and an external electric field transmitted through a human body to stationary receivers. The sensors are low power (milliwatts), high resolution (millimeter) low cost (a few dollars per channel), have low latency (millisecond), high update rate (1 kHz), high immunity to noise (>72 dB), are not affected by clothing, surface texture or reflectivity, and can operate on length scales from microns to meters. Systems incorporating the sensors include a finger mouse, a room that knows the location of its occupant, and people-sensing furniture. Haptic feedback using passive materials is described. Also discussed are empirical and analytical approaches to transform sensor measurements into position information. KEYWORDS: user interface, input device, gesture interface, non-...

This paper reports on the development of a hand to machine interface device that provides real-time gesture, position and orientation information. The key element is a glove and the device as a whole incorporates a collection of technologies. Analog flex sensors on the glove measure finger bending. Hand position and orientation are measured either by ultrasonics, providing five degrees of freedom, or magnetic flux sensors, which provide six degrees of freedom. Piezoceramic benders provide the wearer of the glove with tactile feedback. These sensors are mounted on the light-weight glove and connected to the driving hardware via a small cable.