Fundamental Limits of Nonintrusive Load Monitoring

Provided an arbitrary nonintrusive load monitoring (NILM) algorithm, we seek bounds on the probability of distinguishing between scenarios, given an aggregate power consumption signal. We introduce a framework for studying a general NILM algorithm, and analyze the theory in the general case. Then, we specialize to the case where the error is Gaussian. In both cases, we are able to derive upper bounds on the probability of distinguishing scenarios. Finally, we apply the results to real data to derive bounds on the probability of distinguishing between scenarios as a function of the measurement noise, the sampling rate, and the device usage.Comment: Submitted to the 3rd ACM International Conference on High Confidence Networked Systems (HiCoNS

High Confidence Networked Control for Next Generation Air Transportation Systems

This paper addresses the design of a secure and fault-tolerant air transportation system in the presence of attempts to disrupt the system through the satellite-based navigation system. Adversarial aircraft are assumed to transmit incorrect position and intent information, potentially leading to violations of separation requirements among aircraft. We propose a framework for the identification of adversaries and malicious aircraft, and then for air traffic control in the presence of such deliberately erroneous data. The framework consists of three mechanisms that allow each aircraft to detect attacks and to resolve conflicts: fault detection and defense techniques to improve Global Positioning System (GPS)/inertial navigation, detection and defense techniques using the Doppler/received signal strength, and a fault-tolerant control algorithm. A Kalman filter is used to fuse high frequency inertial sensor information with low frequency GPS data. To verify aircraft position through GPS/inertial navigation, we propose a technique for aircraft localization utilizing the Doppler effect and received signal strength from neighboring aircraft. The control algorithm is designed to minimize flight times while meeting safety constraints. Additional separation is introduced to compensate for the uncertainty of surveillance information in the presence of adversaries. We evaluate the effect of air traffic surveillance attacks on system performance through simulations. The results show that the proposed mechanism robustly detects and corrects faults generated by the injection of malicious data. Moreover, the proposed control algorithm continuously adapts operations in order to mitigate the effects these faults. The ability of the proposed approaches to defend against attacks enables reliable air traffic operations even in highly adversarial surveillance conditions.National Science Foundation (U.S.) (CNS-931843)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N0014-08-0696)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-09-1-1051)United States. Office of Naval Research (Grant N00014-12-1-0609)United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (Grant FA9550-10-1-0567

Reconstructing propagation networks with natural diversity and identifying hidden sources

Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct complex networks on which stochastic spreading dynamics take place. We apply the methodology to a large number of model and real networks, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing. Further, we demonstrate that a hidden source that triggers the spreading process but is externally inaccessible can be ascertained and located with high confidence in the absence of direct routes of propagation from it. Our approach thus establishes a paradigm for tracing and controlling epidemic invasion and information diffusion in complex networked systems.Comment: 20 pages and 5 figures. For Supplementary information, please see http://www.nature.com/ncomms/2014/140711/ncomms5323/full/ncomms5323.html#

ImpaCT2: learning at home and school: case studies

Strand 3 explored the nature of teaching and learning involving ICT in various settings, with a focus on the views of pupils, teachers, and parents. Working in 15 of the 60 schools selected for Strands 1 and 2, this project focused on: learning and teaching environments; learning and teaching styles; and the impact of networked technologies on the perceptions of teachers, managers, pupils and parents. ImpaCT2 was a major longitudinal study (1999-2002) involving 60 schools in England, its aims were to: identify the impact of networked technologies on the school and out-of-school environment; determine whether or not this impact affected the educational attainment of pupils aged 8 - 16 years (at Key Stages 2, 3, and 4); and provide information that would assist in the formation of national, local and school policies on the deployment of ICT

A networked voting rule for democratic representation

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates. We show that a general relation between committee size and representatives exists in the form of an inverse square root law and that the normalized committee size approximately scales with the inverse of the community size, allowing the scalability to very large populations. These findings are not strongly influenced by the different networks used to describe the individuals interactions, except for the presence of few individuals with very high connectivity which can have a marginally negative effect in the committee selection process.Comment: Submitted for publicatio

ImpaCT2 academic report: part 4 - case study evaluations

This report explored the ways in which the integration of ICT and networked technologies into the curriculum tends to produce changes in the patterns of teaching and learning. ImpaCT2 was a major longitudinal study (1999-2002) involving 60 schools in England, its aims were to: identify the impact of networked technologies on the school and out-of-school environment; determine whether or not this impact affected the educational attainment of pupils aged 8 - 16 years (at Key Stages 2, 3, and 4); and provide information that would assist in the formation of national, local and school policies on the deployment of ICT

Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

ImpacT2 project: preliminary study 1: establishing the relationship between networked technology and attainment

This report explored teaching practices, beliefs and teaching styles and their influences on ICT use and implementation by pupils. Additional factors explored included the value of school and LEA policies and teacher competence in the use of ICT in classroom settings. ImpaCT2 was a major longitudinal study (1999-2002) involving 60 schools in England, its aims were to: identify the impact of networked technologies on the school and out-of-school environment; determine whether or not this impact affected the educational attainment of pupils aged 816 years (at Key Stages 2, 3, and 4); and provide information that would assist in the formation of national, local and school policies on the deployment of IC

Event-triggered Learning

The efficient exchange of information is an essential aspect of intelligent collective behavior. Event-triggered control and estimation achieve some efficiency by replacing continuous data exchange between agents with intermittent, or event-triggered communication. Typically, model-based predictions are used at times of no data transmission, and updates are sent only when the prediction error grows too large. The effectiveness in reducing communication thus strongly depends on the quality of the prediction model. In this article, we propose event-triggered learning as a novel concept to reduce communication even further and to also adapt to changing dynamics. By monitoring the actual communication rate and comparing it to the one that is induced by the model, we detect a mismatch between model and reality and trigger model learning when needed. Specifically, for linear Gaussian dynamics, we derive different classes of learning triggers solely based on a statistical analysis of inter-communication times and formally prove their effectiveness with the aid of concentration inequalities