BARTER:promoting local spending behavior

In the wake of the 2008 economic collapse, there is renewed interest in strategies for ensuring the future economic success of nations in a globalized marketplace. One of the main ideas being championed by governments is to promote growth by encouraging local spending, although it is not clear how to motivate this behavioral shift. Local currency initiatives are increasingly popular, though due to certain practicalities are rarely successful in fostering long term and widespread change in spending behaviors. We report on the development of a persuasive system (BARTER) that leverages mobile and ubiquitous technology to overcome some of the limitations of local currencies, while also providing users with the insight needed to determine for themselves how local spending may benet their community

Multisensor Out Of Sequence Data Fusion for Estimating the State of Discrete Control Systems

The fusion center of a complex control system estimates its state with the information provided by different sensors. Physically distributed sensors, communication networks, pre-processing algorithms, multitasking, etc, introduce non-systematic delays in the arrival of information to the fusion center, making the information available out-of-sequence (OOS). For real-time control systems, the state has to be efficiently estimated with all the information received so far. So, several solutions of the OOS problem for dynamic multiple-input multiple-output (MIMO) discrete control systems traditionally solved by the Kalman filter (KF) have been proposed recently. This paper presents two new streamlined algorithms for the linear and non-linear case. IFAsyn, the linear algorithm, is equivalent to other optimal solutions but more general, efficient and easy to implement. EIFAsyn, the nonlinear one, is a new solution of the OOS problem in the extended KF (EKF) framework

National Eclipse Weather Experiment use and evaluation of a citizen science tool for schools outreach

The National Eclipse Weather Experiment (NEWEx) was a citizen science project for atmospheric data collection from the partial solar eclipse of 20th March 2015. Its role as a tool for schools’ outreach is discussed here, in seeking to bridge the gap between self-identification with the role of a scientist and engagement with science, technology, engineering and maths (STEM) subjects. (The science data generated has had other uses beyond this, explored elsewhere.) We describe the design of webforms for weather data collection, and the use of several external partners for the dissemination of the project nationwide. We estimate that up to 3500 pupils and teachers took part in this experiment, through the 127 schools’ postcodes identified in the data submission. Further analysis revealed that 43.3% of the schools were primary schools and 35.4% secondary. 96.3% of participants reported themselves as “captivated” or “inspired” by NEWEx. We also found that 60% of schools who took part in the experiment lie within the highest quintiles of engagement with higher education, which emphasises the need for the scientific community to be creative when using citizen science to target minority audiences

The National Eclipse Weather Experiment: an assessment of citizen scientist weather observations

The National Eclipse Weather Experiment (NEWEx) was a citizen science project designed to assess the effects of the 20 March 2015 partial solar eclipse on the weather over the United Kingdom (UK). NEWEx had two principal objectives: to provide a spatial network of meteorological observations across the UK to aid the investigation of eclipse induced weather changes; and to develop a nationwide public engagement activity based participation of citizen scientists. In total NEWEx collected 15606 observations of air temperature, cloudiness, and wind speed and direction from 309 locations across the UK, over a 3 hour window spanning the eclipse period. The headline results were processed in near real-time, immediately published on-line, and featured in UK national press articles on the day of the eclipse. Here we describe the technical development of NEWEx and how the observations provided by the citizen scientists were analysed. By comparing the results of the NEWEx analyses with results from other investigations of the same eclipse using different observational networks, including measurements from the University of Reading’s Atmospheric Observatory, we demonstrate that NEWEx provided a fair representation of the change in the UK meteorological conditions throughout the eclipse. Despite the simplicity of the approach adopted, robust reductions in both temperature and wind speed during the eclipse were observed

HI asymmetry in the isolated galaxy CIG 85 (UGC 1547)

We present the results from the Giant Metrewave Radio Telescope (GMRT) interferometric HI and 20 cm radio continuum observations of CIG 85, an isolated asymmetric galaxy from the AMIGA (Analysis of the Interstellar Medium of Isolated GAlaxies) sample. Despite being an isolated galaxy, CIG 85 showed an appreciable optical and HI spectral asymmetry and therefore was an excellent candidate for resolved HI studies to understand the reasons giving rise to asymmetries in isolated galaxies. The galaxy was imaged in HI and 20 cm radio continuum using the GMRT. For a detailed discussion of the results we also made use of multi-wavelength data from archival SDSS, GALEX and Halpha imaging. We find the HI in CIG 85 to have a clumpy, asymmetric distribution which in the NW part is correlated with optical tail like features, but the HI velocity field displays a relatively regular rotation pattern. Evaluating all the observational evidence, we come to a conclusion that CIG 85 is most likely a case of a disturbed spiral galaxy which now appears to have the morphology of an irregular galaxy. Although it is currently isolated from major companions, the observational evidence is consistent with HI asymmetries, a highly disturbed optical disk and recent increase in star formation having been caused by a minor merger, remnants of which are now projected in front of the optical disk. If this is correct, the companion will be fully accreted by CIG 85 in the near future.Comment: 10 pages, 9 figures, accepted in A&

Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing method

Motion analysis of match-play in elite U12 to U16 age-group soccer players

The aim of this study was to quantify the motion demands of match-play in elite U12 to U16 age-group soccer players. Altogether, 112 players from two professional soccer clubs at five age-group levels (U12–U16) were monitored during competitive matches (n=14) using a 5 Hz non-differential global positioning system (NdGPS). Velocity thresholds were normalized for each age-group using the mean squad times for a flying 10 m sprint test as a reference point. Match performance was reported as total distance, high-intensity distance, very high-intensity distance, and sprint distance. Data were reported both in absolute (m) and relative (m min-1) terms due to a rolling substitute policy. The U15 (1.35±0.09 s) and U16 (1.31±0.06 s) players were significantly quicker than the U12 (1.58±0.10 s), U13 (1.52±0.07 s), and U14 (1.51±0.08 s) players in the flying 10 m sprint test (P U12, U13, U14), high-intensity distance (U16 > U12, U13, U14, U15), very high-intensity distance (U16 4 U12, U13), and sprint distance (U16 > U12, U13) than their younger counterparts (P<0.05). When the data are considered relative to match exposure, few differences are apparent. Training prescription for youth soccer players should consider the specific demands of competitive match-play in each age-group

Generic multisensor multitarget bias estimation architecture

Current bias estimation algorithms for air traffic control (ATC) surveillance are focused on radar sensors, but the integration of new sensors (especially automatic dependent surveillance-broadcast and wide area multilateration) demands the extension of traditional procedures. This study describes a generic architecture for bias estimation applicable to multisensor multitarget surveillance systems. It consists on first performing bias estimations using measurements from each target, of a subset of sensors, assumed to be reliable, forming track bias estimations. All track bias estimations are combined to obtain, for each of those sensors, the corresponding sensor bias. Then, sensor bias terms are corrected, to subsequently calculate the target or sensor-target pair specific biases. Once these target-specific biases are corrected, the process is repeated recursively for other sets of less reliable sensors, assuming bias corrected measures from previous iterations are unbiased. This study describes the architecture and outlines the methodology for the estimation and the bias estimation design processes. Then the approach is validated through simulation, and compared with previous methods in the literature. Finally, the study describes the application of the methodology to the design of the bias estimation procedures for a modern ATC surveillance application, specifically for off-line assessment of ATC surveillance performance

A contactless identification system based on hand shape features

This paper aims at studying the viability of setting up a contactless identification system based on hand features, with the objective of integrating this functionality as part of different services for smart spaces. The final identification solution will rely on a commercial 3D sensor (i.e. Leap Motion) for palm feature capture. To evaluate the significance of different hand features and the performance of different classification algorithms, 21 users have contributed to build a testing dataset. For each user, the morphology of each of his/her hands is gathered from 52 features, which include bones length and width, palm characteristics and relative distance relationships among fingers, palm center and wrist. In order to get consistent samples and guarantee the best performance for the device, the data collection system includes sweet spot control; this functionality guides the users to place the hand in the best position and orientation with respect to the device. The selected classification strategies - nearest neighbor, supported vector machine, multilayer perceptron, logistic regression and tree algorithms - have been evaluated through available Weka implementations. We have found that relative distances sketching the hand pose are more significant than pure morphological features. On this feature set, the highest correct classified instances (CCI) rate (>96%) is reached through the multilayer perceptron algorithm, although all the evaluated classifiers provide a CCI rate above 90%. Results also show how these algorithms perform when the number of users in the database change and their sensitivity to the number of training samples. Among the considered algorithms, there are different alternatives that are accurate enough for non-critical, immediate response applications