Neural Architectures for Control

The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs

Variation in Environmental Risk Perceptions and Information Sources among Three Communities in El Paso

The authors report the results of a pilot study of environmental risk and sources of environmental information in three socio-economically and culturally distinct communities in Texas

Cyber violence: What do we know and where do we go from here?

This paper reviews the existing literature on the relationship between social media and violence, including prevalence rates, typologies, and the overlap between cyber and in-person violence. This review explores the individual-level correlates and risk factors associated with cyber violence, the group processes involved in cyber violence, and the macro-level context of online aggression. The paper concludes with a framework for reconciling conflicting levels of explanation and presents an agenda for future research that adopts a selection, facilitation, or enhancement framework for thinking about the causal or contingent role of social media in violent offending. Remaining empirical questions and new directions for future research are discussed

Time-averaged aerodynamic loads on the vane sets of the 40- by 80-foot and 80- by 120-foot wind tunnel complex

Time-averaged aerodynamic loads are estimated for each of the vane sets in the National Full-Scale Aerodynamic Complex (NFAC). The methods used to compute global and local loads are presented. Experimental inputs used to calculate these loads are based primarily on data obtained from tests conducted in the NFAC 1/10-Scale Vane-Set Test Facility and from tests conducted in the NFAC 1/50-Scale Facility. For those vane sets located directly downstream of either the 40- by 80-ft test section or the 80- by 120-ft test section, aerodynamic loads caused by the impingement of model-generated wake vortices and model-generated jet and propeller wakes are also estimated

Training in the Use of Psychotherapy Outcome Assessment Measures at Psychology Internship Sites

American Psychological Association accredited psychology internship training programs (N = 407) were surveyed concerning their attitudes, beliefs, and practices with regard to outcome assessment measures. Results indicated that 47% of surveyed sites use outcome measures for assessment, and 66% used these measures for diagnostic purposes. In addition, 79% of respondents supported using outcome assessment measures to evaluate client progress, 61% supported training interns in the use of outcome assessment measures, and 87% felt outcome assessment measures would increase in importance in the future. The discrepancy between support for outcome assessment measures and actual use is discussed and recommendations provided

Advanced Solid-State Array Spectrometer (ASAS) data sets from the 1990 field season: A unique look at two forested ecosystems

The Advanced Solid-state Array Spectrometer (ASAS) is a pointable imaging spectrometer which uses a solid-state array to acquire imagery of terrestrial targets in 29 spectral bands from .4 to .8 microns. Performance and calibration of the instrument are described. The ASAS data sets obtained in 1990 provide a unique look at forest canopies from two different forest regions of the North America continent under varying temporal, spectral, and bidirectional conditions. These data sets will be used to study such parameters as the albedo of forest canopies, the dynamics of scene radiation due to factors such as canopy architecture, moisture stress, leaf chemistry, topography, and understory composition

Mothers' education but not fathers' education, household assets or land ownership is the best predictor of child health inequalities in rural Uganda

Background: Health and nutrition inequality is a result of a complex web of factors that include socio-economic inequalities. Various socio-economic indicators exist however some do not accurately predict inequalities in children. Others are not intervention feasible. Objective: To examine the association of four socio-economic indicators namely: mothers' education, fathers' education, household asset index, and land ownership with growth stunting, which is used as a proxy for health and nutrition inequalities among infants and young children. Methods: This was a cross-sectional survey conducted in the rural district of Hoima, Uganda. Two-stage cluster sampling design was used to obtain 720 child/mother pairs. Information on indicators of household socio-economic status and child anthropometry was gathered by administering a structured questionnaire to mothers in their home settings. Regression modelling was used to determine the association of socio-economic indicators with stunting. Results: One hundred seventy two (25%) of the studied children were stunted, of which 105 (61%) were boys (p < 0.001). Bivariate analysis indicated a higher prevalence of stunting among children of: non-educated mothers compared to mothers educated above primary school (odds ratio (OR) 2.5, 95% confidence interval (CI) 1.4–4.4); non-educated fathers compared to fathers educated above secondary school (OR 1.7, 95% CI 0.8–3.5); households belonging in the "poorest" quintile for the asset index compared to the "least poor" quintile (OR 2.1, 95% CI 1.2–3.7); Land ownership exhibited no differentials with stunting. Simultaneously adjusting all socio-economic indicators in conditional regression analysis left mothers' education as the only independent predictor of stunting with children of non-educated mothers significantly more likely to be stunted compared to those of mothers educated above primary school (OR 2.1, 95% CI 1.1–3.9). More boys than girls were significantly stunted in poorer than wealthier socio-economic strata. Conclusions: Of four socio-economic indicators, mothers' education is the best predictor for health and nutrition inequalities among infants and young children in rural Uganda. This suggests a need for appropriate formal education of the girl child aimed at promoting child health and nutrition. The finding that boys are adversely affected by poverty more than their female counterparts corroborates evidence from previous studies.publishedVersio