An automated classification approach to ranking photospheric proxies of magnetic energy build-up

We study the photospheric magnetic field of ~2000 active regions in solar cycle 23 to search for parameters indicative of energy build-up and subsequent release as a solar flare. We extract three sets of parameters: snapshots in space and time- total flux, magnetic gradients, and neutral lines; evolution in time- flux evolution; structures at multiple size scales- wavelet analysis. This combines pattern recognition and classification techniques via a relevance vector machine to determine whether a region will flare. We consider classification performance using all 38 extracted features and several feature subsets. Classification performance is quantified using both the true positive rate and the true negative rate. Additionally, we compute the true skill score which provides an equal weighting to true positive rate and true negative rate and the Heidke skill score to allow comparison to other flare forecasting work. We obtain a true skill score of ~0.5 for any predictive time window in the range 2-24hr, with a TPR of ~0.8 and a TNR of ~0.7. These values do not appear to depend on the time window, although the Heidke skill score (<0.5) does. Features relating to snapshots of the distribution of magnetic gradients show the best predictive ability over all predictive time windows. Other gradient-related features and the instantaneous power at various wavelet scales also feature in the top five ranked features in predictive power. While the photospheric magnetic field governs the coronal non-potentiality (and likelihood of flaring), photospheric magnetic field alone is not sufficient to determine this uniquely. Furthermore we are only measuring proxies of the magnetic energy build up. We still lack observational details on why energy is released at any particular point in time. We may have discovered the natural limit of the accuracy of flare predictions from these large scale studies

Less Is Mo-town: Goals and Tools for “Smart Shrinkage” Land Use Planning in Rust Belt Cities like Detroit

Article published in the Michigan State University School of Law Student Scholarship Collection

Logarithmic entropy--corrected holographic dark energy with non--minimal kinetic coupling

In this paper, we have considered a cosmological model with the non--minimal kinetic coupling terms and investigated its cosmological implications with respect to the logarithmic entropy-- corrected holographic dark energy (LECHDE). The correspondence between LECHDE in flat FRW cosmology and the phantom dark energy model with the aim to interpret the current universe acceleration is also examined.Comment: 11 pages, 2 figures; Can. J. Phys. Vol. 90, 201

Prediction of shear strength of reinforced concrete beams using adaptive neuro-fuzzy inference system and artificial neural network

AbstractIn this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to predict the shear strength of Reinforced Concrete (RC) beams, and the models are compared with American Concrete Institute (ACI) and Iranian Concrete Institute (ICI) empirical codes. The ANN model, with Multi-Layer Perceptron (MLP), using a Back-Propagation (BP) algorithm, is used to predict the shear strength of RC beams. Six important parameters are selected as input parameters including: concrete compressive strength, longitudinal reinforcement volume, shear span-to-depth ratio, transverse reinforcement, effective depth of the beam and beam width. The ANFIS model is also applied to a database and results are compared with the ANN model and empirical codes. The first-order Sugeno fuzzy is used because the consequent part of the Fuzzy Inference System (FIS) is linear and the parameters can be estimated by a simple least squares error method. Comparison between the models and the empirical formulas shows that the ANN model with the MLP/BP algorithm provides better prediction for shear strength. In adition, ANN and ANFIS models are more accurate than ICI and ACI empirical codes in prediction of RC beams shear strength

Supporting the reflective practice of tutors: what do tutors reflect on?

Effective self-reflection is a key component of excellent teaching. We describe the types of self-reflection identified in tutors’ reflective statements following a peer observation of teaching exercise. We used an adapted version of the categories developed by Grushka et al. (2005) to code text from 20 written statements as technical (26% of comments), practical (36% of comments) and critical (33% of comments). Tutors also wrote about the affective aspects of the exercise and the majority of such comments were positive. Most tutors reflected in a holistic way about their teaching, noting the importance of getting the technical aspects right while also being concerned about pedagogical matters and issues beyond the classroom. The exercise was an effective way to prompt tutors to reflect on their teaching and helped tutors articulate and formalise their learning from the peer observation activity. Suggestions for further exploration of the reflective practice of tutors are provided

Interacting F(R,T)F(R,T) gravity with modified Chaplygin gas

In this paper, we have studied $F(R,T)$ gravity as an arbitrary function of curvature and torsion scalars in Friedmann--Lema\^{\i}tre--Robertson--Walker (FLRW) background. Then, we have considered interacting model between $F(R,T)$ gravity and modified Chaplygin gas. The novelty of this model is that the Universe includes both cases curvature and torsion, and one dominated by a Chaplygin gas. In order to calculate cosmological solutions, we obtained Friedmann equations and also equation of state (EoS) parameter of dark energy. By employing interacting model we considered the total energy density and the total pressure of Universe as the combination of components of dark energy and Chaplygin gas. Subsequently, we reconstructed the model by an origin of a scalar field entitled quintessence model with a field potential. The field potential has been calculated in terms of free parameters of $F(R,T)$ gravity and modified Chaplygin gas. In what follows, we used a parametrization, and the cosmological parameters have been written in terms of redshift $z$. Next, we plotted cosmological parameters with respect to three variable of cosmic time, redshift $z$ and $e$-folding number $N=ln(a)$, and the figures showed us an accelerated expansion of Universe. Also, we have described the scenario in three status early time, late time and future time by $e$-folding number. Finally, the stability of scenario has been investigated by a useful function named sound speed, and the graph of sound speed versus $e$-folding number has been showed us that there is the stability in late time.Comment: 16 pages, 5 figures. arXiv admin note: text overlap with arXiv:1410.417