Achievement Goal Theory Review: An Application to School Psychology

Achievement Goal Theory (AGT) is one of the most popular theoretical frameworks in motivation research. Despite its application to a variety of contexts, including, school, work, and sport, it has not yet been referenced in the field of school psychology. First, we review the theoretical underpinnings as told through the theory’s evolving models, explore its impacts on cognition, emotion, and behavior, and introduce a multiple goals perspective. Second, we outline the leading research supporting AGT, both in terms of structural and individual intervention studies. Third, we apply the principles of AGT to the primary tasks of school psychology professionals, including assessment, intervention, and consultation practices. The students we support can greatly benefit from gearing our approaches toward ones that foster self-improvement and interest.

Optimising Hardware Accelerated Neural Networks with Quantisation and a Knowledge Distillation Evolutionary Algorithm

This paper compares the latency, accuracy, training time and hardware costs of neural networks compressed with our new multi-objective evolutionary algorithm called NEMOKD, and with quantisation. We evaluate NEMOKD on Intel’s Movidius Myriad X VPU processor, and quantisation on Xilinx’s programmable Z7020 FPGA hardware. Evolving models with NEMOKD increases inference accuracy by up to 82% at the cost of 38% increased latency, with throughput performance of 100–590 image frames-per-second (FPS). Quantisation identifies a sweet spot of 3 bit precision in the trade-off between latency, hardware requirements, training time and accuracy. Parallelising FPGA implementations of 2 and 3 bit quantised neural networks increases throughput from 6 k FPS to 373 k FPS, a 62× speedup.

STORM SURGE FORECAST MODEL USING GENETIC PROGRAMMING

Stormsurge is a typical genuine fiasco coming from the ocean. Therefore, an accurate forecast of surges is a vital assignment to dodge property misfortunes and decrease the chance of tropical storm surges. Genetic Programming (GP) is an evolution-based model learning technique that can simultaneously find the functional form and the numeric coefficients for the model. Moreover, GP has been widely applied to build models for predictive problems. However, GP has seldom been applied to the problem of storm surge forecasting. In this paper, a new method to use GP for evolving models for storm surge forecasting is proposed. Experimental results on data-sets collected from the Tottori coast of Japan show that GP can become more accurate storm surge forecasting models than other standard machine learning methods. Moreover, GP can automatically select relevant features when evolving storm surge forecasting models, and the models developed by GP are interpretable.

391 Linking Nutrition, Production, and Environmental Aspects of Ruminant Livestock Production

The relationship between nutrition, production and environmental aspects of ruminant livestock production systems is a complex and highly nuanced subject that has long suffered from oversimplification and assumptions associated within these practices. However, with the advent of new and evolving models and a growing understanding of these complexities and their interactions with each other, there has been a large and welcome growth in recent literature regarding new and emerging technologies, and insights that will allow for appropriate and impactful changes in livestock management that will affect overall change for the benefit of society as a whole. The primary means through which environmental impacts may be modified are separated into four distinct, but interconnected mechanisms, which include 1) improvements in use of dietary nutrients, 2) use of dietary additives that impact certain functions in the digestive tracts of the animal, 3) improvements in genetics, and 4) improvements in productive efficiency. While it is obvious that there are significant overlaps between these practices, it is imperative to consider all these aspects to prevent “leakage” of impacts to other industries and processes. In this presentation, we will review recent developments in all of these areas with a specific emphasis on the use of energy in ruminant production systems.