Is the Written Component of Tootling Effective? A Comparison of the Group Contingency to a Comparison Writing Procedure

Previous tootling literature has demonstrated positive effects of the intervention when implemented in settings from elementary school (e.g., Skinner, Cashwell, & Skinner, 2000) to high school (e.g., Lum et al., 2019). Several studies have shown meaningful effects for the tootling intervention on increasing class-wide academically engaged behavior (AEB) and decreasing disruptive behaviors (DB) (e.g., Cihak et al., 2009). However, no studies in the current literature have examined the effects of the individual components of the tootling intervention on class-wide behaviors. The current study sought to examine the effects of the written component of the tootling intervention on class-wide levels of AEB and DB by comparing traditional tootling to a comparison writing procedure and a no-treatment control condition. Although this study demonstrated variable results, it is the first study to shed light on the importance of looking at the individual components of the tootling intervention. The results and outcomes of the study are discussed

La ville médiévale et ses marges, regards croisés de l'historien à l'archéologue.

National audienceLa perception des faubourgs de la ville médiévale par les historiens et les archéologues

The Compliance Training for Children Model on Child Compliance: A Meta-Analysis

The current study was the first study to conduct a systematic review and meta-analysis of the literature on The Compliance Training for Children Model developed at The University of Southern Mississippi. Twenty-five studies incorporating treatment components from the model (e.g., effective instruction delivery, time-in, time-out, and contingent praise) were included in the study and evaluated for their effects on levels of child compliance. Results of the study yielded predominately large effect size calculations. A moderator analysis was conducted to evaluate treatment components, intervention setting, primary interventionist, and What Works Clearinghouse Standards (WWC, 2010) as potential moderator variables. Findings determined that treatment components, intervention setting, and primary interventionist yielded statistically significant effects. Limitations and future directions for the study are discussed

Inaugural Remarks, Annual Meeting, Atlanta, Ga. October 15, 1973

https://egrove.olemiss.edu/aicpa_assoc/1941/thumbnail.jp

A Bargaining Game for Personalized, Energy Efficient Split Learning over Wireless Networks

Split learning (SL) is an emergent distributed learning framework which can mitigate the computation and wireless communication overhead of federated learning. It splits a machine learning model into a device-side model and a server-side model at a cut layer. Devices only train their allocated model and transmit the activations of the cut layer to the server. However, SL can lead to data leakage as the server can reconstruct the input data using the correlation between the input and intermediate activations. Although allocating more layers to a device-side model can reduce the possibility of data leakage, this will lead to more energy consumption for resource-constrained devices and more training time for the server. Moreover, non-iid datasets across devices will reduce the convergence rate leading to increased training time. In this paper, a new personalized SL framework is proposed. For this framework, a novel approach for choosing the cut layer that can optimize the tradeoff between the energy consumption for computation and wireless transmission, training time, and data privacy is developed. In the considered framework, each device personalizes its device-side model to mitigate non-iid datasets while sharing the same server-side model for generalization. To balance the energy consumption for computation and wireless transmission, training time, and data privacy, a multiplayer bargaining problem is formulated to find the optimal cut layer between devices and the server. To solve the problem, the Kalai-Smorodinsky bargaining solution (KSBS) is obtained using the bisection method with the feasibility test. Simulation results show that the proposed personalized SL framework with the cut layer from the KSBS can achieve the optimal sum utilities by balancing the energy consumption, training time, and data privacy, and it is also robust to non-iid datasets.Comment: Accepted by IEEE WCNC 202

Establishing criterion validity for the French version of the Screening BAT: A comparison of 30 aphasic patient's performance on the Screening BAT and the MT-­‐86 alpha and beta

International audienceThe aim of the present study was to provide data on the validity of the Screening BAT through the comparison of the scores of 30 French aphasic patients on the French version of the Screening BAT with the scores obtained on the Montreal-Toulouse Protocol (MT86) in its long and short version (M1-alpha and M1-bêta). The MT86-alpha is a short version which has been standardised with 60 healthy participants (Dordain et al. 1983). The MT86-bêta is a more detailed test battery and has been standardised in several steps between 1990 and 1993 (Béland & Lecours, 1990; Béland et al, 1993). The M1-bêta still is the standard for aphasia assessment in large parts of France, Belgium and francophone Canada, while the M1-alpha is frequently used with patients in the acute phase. Both tests are based on a large choice of task involving all linguistic levels and modalities, very similar to the BAT and the Screening BAT. For the present study, 30 aphasic patients in the chronic phase (without specific knowledge of other languages) were recruited in order to be able to respond to the long version of the MT-86-bêta. Patients had a mean age of 66,4 years (ranging from 49-88, SD 12,89), there were 17 men and 13 women and most of them (except 4) had more than 9 years of education. 22 were affected by non-fluent aphasia, 8 by fluent aphasia. Mean onset of aphasia was 5 years (ranging from 8 month to 25 years and one month). All patients responded to the French version of the Screening BAT and the M1-alpha in one session, to the M1-beta in another session. Sessions 1 and 2 were counterbalanced across participants and conducted with an interval of minimum 2 and maximum 8 weeks. We present correlations obtained between the three tests and between the subtests included in each. The discussion will focus on the patients’ linguistic profile established with the three tests

Investigation of spectral-based techniques for classification of wideband transient signals in additive white Gaussian noise

ABSTRACT Spectral-based classification schemes designed to separate various wide band transient signals in added noise have been identified and their performances compared along with those obtained using a back-propagation neural network implementation. The spectral-based measures used include: the normalized cross- correlation coefficient; the modified normalized cross-correlation coefficient, and; the divergence and the Bhattacharyya distance. Noise was added to the signals to create signal to noise ratios of 0 dB to -20 dB. Results show that as noise levels increase, the modified normalized cross-correlation coefficient spectral measure remains the most robust scheme.http://archive.org/details/investigationofs1094542935Naval Postgraduate School authorApproved for public release; distribution is unlimited

“Contrived”: The Voting Rights Act Pretext for the Trump Administration’s Failed Attempt to Add a Citizenship Question to the 2020 Census

A Pretext . . . For What? In March 2018, Commerce Secretary Wilbur Ross announced that the Trump Administration would add a question to the 2020 census asking the citizenship status of all persons in the United States. The question, Secretary Ross asserted, would generate “complete and accurate [citizenship] data” that the Department of Justice (DOJ) could use to better enforce Section 2 of the Voting Rights Act of 1965 (VRA)—a law that sometimes requires states and localities to draw districts in which voters of color make up a majority of the voting age population (so-called “majority-minority” districts)