Let me be learned: decision support aiding public participation

With best practice flood risk management processes rightly emphasising the need for a collaborative, transparent and inclusive approach to improve community resilience, this paper explores a new Engagement Decision Support System (EDSS) as a mechanism to assist in this process. This paper presents the need, theory and development of a flood risk management EDSS and presents trial results, where the tool has been successfully utilised for three catchments in New South Wales, Australia. The results from these trials indicate that a well-structured, engagement focused decision support system can provide a mechanism for and empower the public to learn about, prioritise and make informed decisions about floodplain management options for their local catchment in a transparent objective facilitated process

Evaluation of Giga-bit Ethernet Instrumentation for SalSA Electronics Readout (GEISER)

An instrumentation prototype for acquiring high-speed transient data from an array of high bandwidth antennas is presented. Multi-kilometer cable runs complicate acquisition of such large bandwidth radio signals from an extensive antenna array. Solutions using analog fiber optic links are being explored, though are very expensive. We propose an inexpensive solution that allows for individual operation of each antenna element, operating at potentially high local self-trigger rates. Digitized data packets are transmitted to the surface via commercially available Giga-bit Ethernet hardware. Events are then reconstructed on a computer farm by sorting the received packets using standard networking gear, eliminating the need for custom, very high-speed trigger hardware. Such a system is completely scalable and leverages the hugh capital investment made by the telecommunications industry. Test results from a demonstration prototype are presented.Comment: 8 pages, to be submitted to NIM

Multi-Hypothesis Interactions in Game-Theoretic Motion Planning

We present a novel method for handling uncertainty about the intentions of non-ego players in dynamic games, with application to motion planning for autonomous vehicles. Equilibria in these games explicitly account for interaction among other agents in the environment, such as drivers and pedestrians. Our method models the uncertainty about the intention of other agents by constructing multiple hypotheses about the objectives and constraints of other agents in the scene. For each candidate hypothesis, we associate a Bernoulli random variable representing the probability of that hypothesis, which may or may not be independent of the probability of other hypotheses. We leverage constraint asymmetries and feedback information patterns to incorporate the probabilities of hypotheses in a natural way. Specifically, increasing the probability associated with a given hypothesis from $0$ to $1$ shifts the responsibility of collision avoidance from the hypothesized agent to the ego agent. This method allows the generation of interactive trajectories for the ego agent, where the level of assertiveness or caution that the ego exhibits is directly related to the easy-to-model uncertainty it maintains about the scene.Comment: For associated mp4 file, see https://youtu.be/x7VtYDrWTW

The Computation of Approximate Generalized Feedback Nash Equilibria

We present the concept of a Generalized Feedback Nash Equilibrium (GFNE) in dynamic games, extending the Feedback Nash Equilibrium concept to games in which players are subject to state and input constraints. We formalize necessary and sufficient conditions for (local) GFNE solutions at the trajectory level, which enable the development of efficient numerical methods for their computation. Specifically, we propose a Newton-style method for finding game trajectories which satisfy the necessary conditions, which can then be checked against the sufficiency conditions. We show that the evaluation of the necessary conditions in general requires computing a series of nested, implicitly-defined derivatives, which quickly becomes intractable. To this end, we introduce an approximation to the necessary conditions which is amenable to efficient evaluation, and in turn, computation of solutions. We term the solutions to the approximate necessary conditions Generalized Feedback Quasi Nash Equilibria (GFQNE), and we introduce numerical methods for their computation. In particular, we develop a Sequential Linear-Quadratic Game approach, in which a locally approximate LQ game is solved at each iteration. The development of this method relies on the ability to compute a GFNE to inequality- and equality-constrained LQ games, and therefore specific methods for the solution of these special cases are developed in detail. We demonstrate the effectiveness of the proposed solution approach on a dynamic game arising in an autonomous driving application

Recognition of micro-array protein crystals images using multi-scale representations

Micro-array protein crystal images are now routinely acquired automatically by CCD cameras. High-throughput automatic classification of protein crystals requires to alleviation of the time-consuming task of manual visual inspection. We propose a classification framework combined with a multi-scale image processing method for recognizing protein crystals and precipitates versus clear drops. The main two points of the processing method are the multi-scale Laplacian pyramid filters and histogram analysis techniques to find an effective feature vector. The processing steps include: 1. Tray well cropping using Radon Transform; 2. Droplet cropping using an ellipsoid Hough Transform; 3. Multi-scale image separation with Laplacian pyramidal filters; 4. Feature vector extraction from the histogram of the multi-scale boundary images. The feature vector combines geometric and texture features of each image and provides input to a feed forward binomial neural network classifier. Using human (expert crystallographers) classified images as ground truth, the current experimental results gave 86% true positive and 94% true negative rates (average true percentage is 90%) using an image database which contained over 2,000 images. To enable NESG collaborators to carry our crystal classification, a web-based Matlab server was also developed. Users at other locations on the internet can input micro-array crystal image folders and parameters for training and testing processes through a friendly web interface. Recognition results are shown on the client side website and may be downloaded by a remote user as an Excel spreadsheet file

High-speed Recognition of Micro-array Genomic Images Using Multi-scale Representations

This project is part of the Northeast Structural Genomics Consortium (NESG). The goal of this consortium is to develop efficient and integrated technologies for high-throughput (HTP) protein production and 3D structure determination. This project focuses on the design of an image analysis system to classify protein crystal structures in a production oriented environment. The method performs classification of microscopic images as clear droplets versus non-clear droplets (precipitates and crystals). Using expert classification for ground truth, current results show high classification accuracy with a large image datasets

Field measurements of beach-dune dynamic profiles to assess erosion hazard on the coast of NSW, Australia

The coast of New South Wales (NSW), Australia is about 2000 km long and consists of 721 sandy beaches (68%), rock coastline (32%), and more than 185 estuaries. It is most populated in Australia and one of the NSW greatest assets with significant economic, social and environmental values. The NSW coast has epsodically been ravaged by severe storms together with large ocean waves and high water levels, resulting in severe dune-beach erosion/recession, damaging coastal infrastructure and properties and degrading coastal ecosystems. With potential changes to storm-wave climate and rising sea level, coastal erosion hazards on the NSW coast are likely to worsen in the future. This study was undertaken to collect essential field data on beachdune profiles and sediment grain-size distributions over more than 200 sandy beaches to assess NSW coastal erosion hazard. For each of the selected beaches, three beach-dune profiles of shore-normal transects at 50m apart were surveyed by RTK-GPS, and three sediment samples only on the first transect line were also colleced from the dune, dry beach/berm and swash zone by using a simple hand grabbing method. A sediment grain size analyzer, Malvern Mastersizer 2000E, was used to obtain sediment grain size distributions. It is found that the 618 sediment samples analysed consist of fine sand (10%), medium sand (82%) and coarse sand (8%), and that the dune sand d50 correlates well with the dry-beach sand d50 and is about 8% smaller, but less well correlates with the swash sand d50 and is about 15% smaller. The beach orientation was estimated from the direction of the shore-normal transect lines and generally ranges from 90o to 150o. The beaches surveyed are found to have erosion problems when they weredirectly exposed to predominant waves in the south-east direction and also when the dune toe elevations were lower than 3~3.5m (AHD). A conceptual model is also developed to assess likelihood storm erosion of a beach-dune system

Synthesis of Ultrafine Β′-Alumina Powders via Flame Spray Pyrolysis of Polymeric Precursors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66387/1/j.1151-2916.1998.tb02506.x.pd

BUSINESS STRATEGIES OF SELECTED FOOD ESTABLISHMENTS BEFORE AND DURING PANDEMIC: BASIS FOR BUSINESS CONTINUITY PLAN

This study was conducted to determine the various strategies used by selected food establishments in Dipolog City. The goal of this research is to develop a business continuity plan that will then be useful for small businesses in the food establishments in Dipolog City. The study employed a descriptive qualitative approach to obtain the data needed. Five (5) food establishments participated in the study through a face-to-face interview. The research looked into the various strategies utilized by food establishments before and throughout the pandemic. The information gathered from the literature is used to (1) understand the effect of the COVID-19 pandemic on food establishments, (2) provide a deeper understanding of the strategies used and the capabilities in responding to the impacts of the COVID-19 pandemic, and (3) developed a business continuity plan that will then be useful for small businesses in the food industry in Dipolog City. Through systemically utilizing the company's assets, resources, and capabilities, the owners can develop and retain a competitive edge. This is done by aligning the firm with its environment. According to the results of the study business owners must develop a vision, objective, and goals for strategic plans inside a business, formulate the pricing of items at break-even profit level, offer incentives and promos at least once a month, offer flexible scheduling, and then reward and motivate employee development for the business to continue thriving even if there are unforeseen events that can hinder its operation

Circulating Fluidized Bed Combustion-Build-Up and Validation of a Three-Dimensional Model

This paper presents the validated simulation of a full-scale circulating fluidized bed boiler as obtained via a comprehensive three-dimensional CFB process model. The model is utilized in boiler design and scale-up as well as to study and optimize boiler performance. Feedstock characterization tests, which are also presented, are used to provide data for those parts of the process where up-to-date modeling is not fully reliable, thus enabling the model to provide accurate results