Active Learning and Best-Response Dynamics

We examine an important setting for engineered systems in which low-power distributed sensors are each making highly noisy measurements of some unknown target function. A center wants to accurately learn this function by querying a small number of sensors, which ordinarily would be impossible due to the high noise rate. The question we address is whether local communication among sensors, together with natural best-response dynamics in an appropriately-defined game, can denoise the system without destroying the true signal and allow the center to succeed from only a small number of active queries. By using techniques from game theory and empirical processes, we prove positive (and negative) results on the denoising power of several natural dynamics. We then show experimentally that when combined with recent agnostic active learning algorithms, this process can achieve low error from very few queries, performing substantially better than active or passive learning without these denoising dynamics as well as passive learning with denoising

Cognitive Cost in Route Choice with Real-Time Information: An Exploratory Analysis

Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper presents a model that is consistent with a general network topology and can potentially be estimated based on revealed preference data. It explicitly takes into account the information acquisition and the subsequent path choice. The decision to acquire information is assumed to be based on the cognitive cost involved in the search and the expected benefit defined as the expected increase in utility after the search. A latent class model is proposed, where the decision to search or not to search and the depth of the search are latent and only the final path choices are observed. A synthetic data set is used for the purpose of validation and ease of illustration. The data are generated from the postulated cognitive-cost model, and estimation results show that the true values of the parameters can be recovered with enough variability in the data. Two other models with simplifying assumptions of no information and full information are also estimated with the same set of data with significantly biased path choice utility parameters. Prediction results show that a smaller cognitive cost encourages information search on risky and fast routes and thus higher shares on those routes. As a result, the expected average travel time decreases and the variability increases. The no-information and full-information models are extreme cases of the more general cognitive-cost model in some cases, but not generally so, and thus the increasing ease of information acquisition does not necessarily warrant a full-information model

Effect of questionnaire length, personalisation and reminder type on response rate to a complex postal survey: randomised controlled trial.

BACKGROUND: Minimising participant non-response in postal surveys helps to maximise the generalisability of the inferences made from the data collected. The aim of this study was to examine the effect of questionnaire length, personalisation and reminder type on postal survey response rate and quality and to compare the cost-effectiveness of the alternative survey strategies. METHODS: In a pilot study for a population study of travel behaviour, physical activity and the environment, 1000 participants sampled from the UK edited electoral register were randomly allocated using a 2×2 factorial design to receive one of four survey packs: a personally addressed long (24 page) questionnaire pack, a personally addressed short (15 page) questionnaire pack, a non-personally addressed long questionnaire pack or a non-personally addressed short questionnaire pack. Those who did not return a questionnaire were stratified by initial randomisation group and further randomised to receive either a full reminder pack or a reminder postcard. The effects of the survey design factors on response were examined using multivariate logistic regression. RESULTS: An overall response rate of 17% was achieved. Participants who received the short version of the questionnaire were more likely to respond (OR=1.48, 95% CI 1.06 to 2.07). In those participants who received a reminder, personalisation of the survey pack and reminder also increased the odds of response (OR=1.44, 95% CI 1.01 to 1.95). Item non-response was relatively low, but was significantly higher in the long questionnaire than the short (9.8% vs 5.8%; p=.04). The cost per additional usable questionnaire returned of issuing the reminder packs was £23.1 compared with £11.3 for the reminder postcards. CONCLUSIONS: In contrast to some previous studies of shorter questionnaires, this trial found that shortening a relatively lengthy questionnaire significantly increased the response. Researchers should consider the trade off between the value of additional questions and a larger sample. If low response rates are expected, personalisation may be an important strategy to apply. Sending a full reminder pack to non-respondents appears a worthwhile, albeit more costly, strategy.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Influence of magnetic field upon electrode kinetics and ionic transport

Performance properties in lithium-ion, sodium-ion, and zero excess metal batteries are currently limited by the sluggish ion diffusion and inhomogeneity of the transport ion flux, resulting in poor formation, low rates, and short cycle lives. In this work, a magnetic field is applied to the cell by the incorporation of a NdFeB magnetic spacer, and the effect upon the kinetics and transport properties at each electrode is studied using galvanic charge and discharge, electrochemical impedance spectroscopy, and intermittent titration techniques. Stabilization of the anode-free or zero excess sodium and lithium metal cells is achieved during formation, and upon cycling. Reduced cell overpotential is observed with resulting higher areal capacities, with improved ionic diffusion through the electrode. Upon cycling metallic dendritic structures are suppressed due to the inhomogeneity of ion flux, and the likely competing kinetics of plating at a metallic tip and the surrounding surface. At the NMC electrode, improved kinetics are observed with lower charge-transfer resistance (Rct) due to the reshaped and aligned domain in the ferromagnetic Ni of NMC cathode. Pulsed current methods further confirm enhanced cationic diffusion in the anode graphite materials, particularly at high mass loading of 4 mA h cm−2 and high C rates. Consequently, the combination of enhanced reaction kinetics on the ferromagnetic cathode and improved diffusion kinetics in the porous anode leads to excellent full-cell performance compared to control groups. This study highlights the potential of magnetic fields in enhancing diffusion and reaction kinetics for rechargeable batteries (Li, Na, K, Mg, etc.), and may provide routes for extending cycle life, reconditioning cells, and improving formation protocols

SenseBack - An implantable system for bidirectional neural interfacing

Chronic in-vivo neurophysiology experiments require highly miniaturized, remotely powered multi-channel neural interfaces which are currently lacking in power or flexibility post implantation. In this article, to resolve this problem we present the SenseBack system, a post-implantation reprogrammable wireless 32-channel bidirectional neural interfacing that can enable chronic peripheral electrophysiology experiments in freely behaving small animals. The large number of channels for a peripheral neural interface, coupled with fully implantable hardware and complete software flexibility enable complex in-vivo studies where the system can adapt to evolving study needs as they arise. In complementary ex-vivo and in-vivo preparations, we demonstrate that this system can record neural signals and perform high-voltage, bipolar stimulation on any channel. In addition, we demonstrate transcutaneous power delivery and Bluetooth 5 data communication with a PC. The SenseBack system is capable of stimulation on any channel with ±20 V of compliance and up to 315 μA of current, and highly configurable recording with per-channel adjustable gain and filtering with 8 sets of 10-bit ADCs to sample data at 20 kHz for each channel. To the best of our knowledge this is the first such implantable research platform offering this level of performance and flexibility post-implantation (including complete reprogramming even after encapsulation) for small animal electrophysiology. Here we present initial acute trials, demonstrations and progress towards a system that we expect to enable a wide range of electrophysiology experiments in freely behaving animals