Online Distributed Sensor Selection

A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to constraints (e.g., on power and bandwidth). In many applications the utility function is not known a priori, must be learned from data, and can even change over time. Furthermore for large sensor networks solving a centralized optimization problem to select sensors is not feasible, and thus we seek a fully distributed solution. In this paper, we present Distributed Online Greedy (DOG), an efficient, distributed algorithm for repeatedly selecting sensors online, only receiving feedback about the utility of the selected sensors. We prove very strong theoretical no-regret guarantees that apply whenever the (unknown) utility function satisfies a natural diminishing returns property called submodularity. Our algorithm has extremely low communication requirements, and scales well to large sensor deployments. We extend DOG to allow observation-dependent sensor selection. We empirically demonstrate the effectiveness of our algorithm on several real-world sensing tasks

The Induction Of Beginning Teachers In Western Australian Catholic Primary Schools

The survey study was primarily exploratory and descriptive in nature and attempted to report on the perceptions of beginning teachers entering the Catholic primary schools in Western Australia in 1991. Their perceptions on the form of induction they received, and how their pre-service teacher education equipped them for this transition were attained. In addition, data from Catholic primary school principals, Catholic Education Office of Western Australia administrators and teacher institutions administrators were collected in relation to perceptions of the transitions from teacher training to teacher employment. The main sources of data collection were questionnaires and interviews. The data collated indicated that most principals and administrators support the conclusions expressed in the literature that most graduates are satisfactorily prepared for the teaching role. However, this is only the start of an ongoing process of pre-service, induction and professional development. Few of the beginning teachers in the population were given any concessions in their initial months of teaching and few received an effective, ongoing induction plan to ease them into their teaching careers. The literature on induction is prescribed to support the importance of developing school based comprehensive induction plans for the beginning teachers who enter the workforce each year. Finally, based on the results of the survey study and literature, a framework of a model for induction was prescribed to assist in the development of a comprehensive, system based induction policy for Western Australian Catholic primary school

Training Gaussian Mixture Models at Scale via Coresets

How can we train a statistical mixture model on a massive data set? In this work we show how to construct coresets for mixtures of Gaussians. A coreset is a weighted subset of the data, which guarantees that models fitting the coreset also provide a good fit for the original data set. We show that, perhaps surprisingly, Gaussian mixtures admit coresets of size polynomial in dimension and the number of mixture components, while being independent of the data set size. Hence, one can harness computationally intensive algorithms to compute a good approximation on a significantly smaller data set. More importantly, such coresets can be efficiently constructed both in distributed and streaming settings and do not impose restrictions on the data generating process. Our results rely on a novel reduction of statistical estimation to problems in computational geometry and new combinatorial complexity results for mixtures of Gaussians. Empirical evaluation on several real-world datasets suggests that our coreset-based approach enables significant reduction in training-time with negligible approximation error

Perceptual adaptation by normally hearing listeners to a simulated "hole" in hearing

Simulations of cochlear implants have demonstrated that the deleterious effects of a frequency misalignment between analysis bands and characteristic frequencies at basally shifted simulated electrode locations are significantly reduced with training. However, a distortion of frequency-to-place mapping may also arise due to a region of dysfunctional neurons that creates a "hole" in the tonotopic representation. This study simulated a 10 mm hole in the mid-frequency region. Noise-band processors were created with six output bands (three apical and three basal to the hole). The spectral information that would have been represented in the hole was either dropped or reassigned to bands on either side. Such reassignment preserves information but warps the place code, which may in itself impair performance. Normally hearing subjects received three hours of training in two reassignment conditions. Speech recognition improved considerably with training. Scores were much lower in a baseline (untrained) condition where information from the hole region was dropped. A second group of subjects trained in this dropped condition did show some improvement; however, scores after training were significantly lower than in the reassignment conditions. These results are consistent with the view that speech processors should present the most informative frequency range irrespective of frequency misalignment. 0 2006 Acoustical Society of America

The human right to water and sanitation: Using natural language processing to uncover patterns in academic publishing

After years of advocacy and international negotiation, the General Assembly of the United Nations voted to officially recognize a stand-alone human right to water and sanitation on 28 July 2010. Since, academic scholarship has continued to grow in an effort to understand the implications of the codification of this human right. Yet, with this growth, it has become impractical if not impossible for scholars to keep up with the advancement of academic knowledge or to make sense of it in a systematic way. In short, to date, we know very little about the trends in the literature as they have unfolded over the past thirty years and the topics to which scholars have devoted significant attention within the broader field, particularly over time. This is an important area of inquiry, as developing a comprehensive understanding of where prior literature has focused and where it appears to be going offers scholars an opportunity to identify areas in need of refinement and/or increased attention. Given the practicalities of reading thousands of research papers each year, this project utilizes natural language processing (NLP) to identify topics and trends in academic literature on the human right to water and sanitation (HRtWS). NLP provides the opportunity to digest large quantities of text data through machine learning, culminating with descriptive information on trends and topics in the field since 1990. The results of this exercise show that the research related to the human right to water and sanitation has grown exponentially, particularly over the last decade, illustrates the multidisciplinary nature of the literature, and demonstrates the diversity of topics in the field

Understanding the experiences of engaging in a community-based, physical-activity focused secondary stroke prevention program

Research has evidenced that regular exercise can provide physical and physiological benefits for people living with stroke. Our study aims to explore the experiences of people living with stroke when participating in a community physical activity programme. This programme was created to offer targeted physical activity and education interventions following the discharge of patients from the healthcare pathway. This qualitative study involved semi-structured interviews with 16 participants living with stroke who were recruited from individuals who had engaged with the activity programme. A reflexive thematic analysis was conducted on the data, and four overarching themes were developed: (i) Feelings of appreciation, (ii) Interactions with other patients, (iii) Positive contributions of trained instructors, and iv) Personal progress. Generally, participants reported very positive perceptions of the exercise programme, and were very grateful for the opportunity that the exercise classes provided. We hope that these findings will offer practical suggestions for healthcare providers who might develop similar activity programmes for clinical populations

Community Sense and Response Systems

The proliferation of smartphones and other internet-enabled, sensor-equipped consumer devices enables us to sense and act upon the physical environment in unprecedented ways. This thesis considers Community Sense-and-Response (CSR) systems, a new class of web application for acting on sensory data gathered from participants' personal smart devices. The thesis describes how rare events can be reliably detected using a decentralized anomaly detection architecture that performs client-side anomaly detection and server-side event detection. After analyzing this decentralized anomaly detection approach, the thesis describes how weak but spatially structured events can be detected, despite significant noise, when the events have a sparse representation in an alternative basis. Finally, the thesis describes how the statistical models needed for client-side anomaly detection may be learned efficiently, using limited space, via coresets. The Caltech Community Seismic Network (CSN) is a prototypical example of a CSR system that harnesses accelerometers in volunteers' smartphones and consumer electronics. Using CSN, this thesis presents the systems and algorithmic techniques to design, build and evaluate a scalable network for real-time awareness of spatial phenomena such as dangerous earthquakes.</p

Instrumented tools and objects : design, algorithms, and applications to assembly tasks

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.We developed an instrumented tool system comprised of wireless nodes and sensor systems to facilitate distributed robotic assembly tasks. This robotic system was deployed on two separate robotic assembly scenarios: one scenario used programmable autonomous beacons to facilitate precise localization of an assembly robot within a mock airplane wing, while the second used programmable assembly components to simplify sensing and coordination in a distributed, multi-robot assembly task. An instrumented tool system comprised of two types of programmable nodes (beacons and assembly components) and two types of robot-mounted sensors was designed, implemented, and tested. On-board microprocessors allow each element of the system to perform sensing and communicate over an infrared communication protocol. Algorithms for sensing and distributed communication were developed to perform local sensing tasks between assembly robots and instrumented materials.by Matthew N. Faulkner.M.Eng

Effect of Absent Tactile Sensation on Multi-digit Coordination Underlying Hand Control

We investigated the effect of anesthesia, causing absent tactile sensation feedback, on multi-digit coordination underlying hand control. The purpose of the study is to expand our understanding on the essential role of tactile sensation feedback in the sensorimotor integration process by examining the motor coordination patterns during multi-digit forces production tasks. We hypothesized that absent tactile sensation feedback would interrupt the force sharing pattern at local and non-local digits. Twelve participants were utilized for data collection and statistical analysis (25.6 ± 4.1 years old, 6 males and 6 females), right-handed (according to their preferred hand use for writing and eating) and had no significant hand injury within the last five years. All participants performed a maximal voluntary contraction (MVC), ramp, and step task, pre- and post-anesthesia. In general, participants presented lower maximal force production in all MVC conditions after anesthesia, total MVC force was not distributed evenly among individual digits, and when sensory function of the MVC involved digits are uniformly absent or intact, force sharing pattern across the individual digits would be maintained. When the instructed finger (master finger) was index, other fingers (enslaved fingers) barely produced force. However, other enslaved fingers showed relatively higher forces when the master finger was ring or little finger. When required force level increased, performance error was increased accordingly. The findings from the current study confirmed our hypothesis that absent tactile sensation feedback (somatosensory feedback) will not only affect force production at local digits, but also at non-local digits as well