An adaptive neuro-fuzzy propagation model for LoRaWAN

This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the training complexity of artificial neural network (ANN)-based models. Therefore, the size of the training dataset is reduced by 70% compared to an ANN model. The proposed model consists of an efficient clustering method to identify the optimum number of the fuzzy nodes to avoid overfitting, and a hybrid training algorithm to train and optimize the ANFIS parameters. Finally, the proposed model is benchmarked with extensive practical data, where superior accuracy is achieved compared to deterministic models, and better generalization is attained compared to ANN models. The proposed model outperforms the nondeterministic models in terms of accuracy, has the flexibility to account for new modeling parameters, is easier to use as it does not require a model for propagation environment, is resistant to data collection inaccuracies and uncertain environmental information, has excellent generalization capability, and features a knowledge-based implementation that alleviates the training process. This work will facilitate network planning and propagation prediction in complex scenarios

Time-Series Evidence of the Effect of the Minimum Wage on Youth Employment and Unemployment

While previous time series studies have quite consistently found that the minimum wage reduces teenage employment, the extent of this reduction is much less certain. Moreover, because few previous studies report results of more than one specification, the causes of differences in estimated impacts are not well understood. Less consensus is evident on the effect of the minimum wage on teenage unemployment, or its relative impact on black and white teenagers. The purpose of this paper is both to update earlier work and to analyze the sensitivity of estimated minimum wage effects to alternative specification choices. In addition to providing estimates of the effect of minimum wage increases on aggregate employment and unemployment rates of teenagers, we explore several related issues: the relative importance of changing the level and coverage of the minimum wage; the timing of responses to a change in the minimum; effects on part-time and full-time work; effects on young adults (age 20-24).

The Effect of the Minimum Wage on Employment and Unemployment: A Survey

In this paper, we survey theoretical models of the effect of the minimum wage and, in somewhat greater detail, evidence of its effect on employment and unemployment. Our discussion of the theory emphasizes recent work using two-sector and heterogeneous-worker models. We then summarize and evaluate the large literature on employment and unemployment effects of the minimum on teenagers. Finally, we survey the evidence of the effect of the minimum wage on adult employment, and on employment in low-wage industries and areas.

Determining best predictors of animal performance in feedlot steers

Two studies were performed in a feedlot environment to determine the long-term effects of heat events on animal performance and well-being. Experiments in this thesis were designed to pinpoint ambient variables that most strongly elicit animal thermoregulatory responses. These animal responses included core temperature (Tcore) alone in the first study, and both Tcore and animal respiration rate (RR) in the second. Both experiments went a step further by using both ambient conditions and animal responses to predict feed intake (FI) response to heat stress. The ability to predict FI based on measurable independent variables could be very helpful to beef producers who are otherwise subject to environmental stressors and loss in animal production. The first study followed 26 crossbred Angus steers during 42 days of a central Missouri summer in 2011 (July 12 through August 22), and was strictly aimed at predicting Tcore and FI using ambient information. Animals were housed at the University of Missouri Beef Research and Teaching Farm (BRTF) in Columbia, Missouri and had ad libitum access to feed and water, with [about]50% shade coverage over the pens. All variables were automatically measured and recorded throughout the entire study period. Linear and polynomial regression analyses of variance (ANOVA, JMP statistical software; SAS Institute; Cary, NC) were used. Both ambient and mean herd Tcore readings were averaged by hour to analyze the relationship between environment and Tcore during daytime (0700 to 1700 CST)

A deterministic algorithm for experimental design applied to tomographic and microseismic monitoring surveys

SUMMARY Most general experimental design algorithms are either: (i) stochastic and hence give different designs each time they are run with finite computing power, or (ii) deterministic but converge to results that depend on an initial or reference design, taking little or no account of the range of all other possible designs. In this paper we introduce an approximation to standard measures of experimental design quality that enables a new algorithm to be used. The algorithm is simple, deterministic and the resulting experimental design is influenced by the full range of possible designs, thus addressing problems (i) and (ii) above. Although the designs produced are not guaranteed to be globally optimal, they significantly increase the magnitude of small eigenvalues in the model–data relationship (without requiring that these eigenvalues be calculated). This reduces the model uncertainties expected post-experiment. We illustrate the method on simple tomographic and microseismic location examples with varying degrees of seismic attenuation

HD 4915: A Maunder Minimum Candidate

We study the magnetic activity cycle of HD 4915 using the \ion{Ca}{2} H \& K emission line strengths measured by Keck I/HIRES spectrograph. The star has been observed as a part of California Planet Search Program from 2006 to present. We note decreasing amplitude in the magnetic activity cycle, a pattern suggesting the star's entry into a Magnetic Grand Minimum (MGM) state, reminiscent of the Sun's Maunder and Dalton Minima. We recommend further monitoring of the star to confirm the grand minimum nature of the dynamo, which would provide insight into the state of the Sun's chromosphere and the global magnetic field during its grand minima. We also recommend continued observations of H \& K emission lines, and ground or space based photometric observations to estimate the sunspot coverage.Comment: To be submitted to AAS Journals; comments welcom

Experimental demonstration of a surface-electrode multipole ion trap

We report on the design and experimental characterization of a surface-electrode multipole ion trap. Individual microscopic sugar particles are confined in the trap. The trajectories of driven particle motion are compared with a theoretical model, both to verify qualitative predictions of the model, and to measure the charge-to-mass ratio of the confined particle. The generation of harmonics of the driving frequency is observed as a key signature of the nonlinear nature of the trap. We remark on possible applications of our traps, including to mass spectrometry.Comment: Preprint format, 15 pages, 9 figures. Accepted into Journal of Applied Physic

Interferometric modeling of wave propagation in inhomogeneous elastic media using time reversal and reciprocity

Time reversal of arbitrary, elastodynamic wavefields in partially open media can be achieved by measuring the wavefield on a surface surrounding the medium and applying the time reverse of those measurements as a boundary condition. We use a representation theorem to derive an expression for the time-reversed wavefield at arbitrary points in the interior. When this expression is used to compute, in a second point, the time-reversed wavefield originating from a point source, the time-reversed Green’s function between the two points is observed. By invoking reciprocity, we obtain an expression that is suitable for modeling of wave propagation through the medium. From this we develop an efficient and flexible two-stage modeling scheme. In the initial phase, the model is illuminated systematically from a surface surrounding the medium using a sequence of conventional forward-modeling runs. Full waveforms are stored for as many points in the interior as possible. In the second phase, Green’s functions between arbitrary points in the volume can be computed by crosscorrelation and summation of data computed in the initial phase. We illustrate the method with a simple acoustic example and then apply it to a complex region of the elastic Pluto model. It is particularly efficient when Green’s functions are desired between a large number of points, but where there are few common source or receiver points. The method relies on interference of multiply scattered waves, but it is stable. We show that encoding the boundary sources using pseudonoise sequences and exciting them simultaneously, akin to daylight imaging, is inefficient and in all explored cases leads to relatively high-noise levels