Hiring consultants

"Revised 5/81/2M"This publication should guide recreators (individuals directly or indirectly responsible for delivering recreational services) in deciding both when and how to choose a professional consultant

Liability of recreators

"Revised 1/81/2M

Community-school cooperation for recreation

"Revised 11/81/2M"The purpose of this guide is to provide information to help improve and increase cooperation among schools and park or recreation departments in Missouri communities

Park boards of Missouri

"Revised 8/80/2M

Model bylaws for Missouri administrative park boards, organized under Sections 90.500-90.570 Missouri State Statutes

"3 /81/2M"These bylaws are appropriate for Missouri communities served by administrative boards without full time professional leadership, established under sections 90.500 - 90.570 Missouri State Statutes

Model ordinance for Missouri administrative park boards, organized under Sections 90.500-90.570 Missouri State Statues

"3 /81/2M

Community recreation mainstreaming : the inclusion of handicapped individuals in regular recreation programs

"2/81/2M"This guide probes the methods removing barriers to handicapped individuals and the benefits of that process. Any individual or group interested in improving the quality of life in their community should find this guide useful

Infering Air Quality from Traffic Data using Transferable Neural Network Models

This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy requirements. Measurement equipment tends to be expensive to purchase and maintain. Therefore, a model based approach capable of accurate determination of pollution levels is highly beneficial. The objective of this study was to develop a neural network model to accurately infer pollution levels from existing data sources in Leicester, UK. Neural Networks are models made of several highly interconnected processing elements. These elements process information by their dynamic state response to inputs. Problems which were not solvable by traditional algorithmic approaches frequently can be solved using neural networks. This paper shows that using a simple neural network with traffic and meteorological data as inputs, the air quality can be estimated with a good level of generalisation and in near real-time. By applying these models to links rather than nodes, this methodology can directly be used to inform traffic engineers and direct traffic management decisions towards enhancing local air quality and traffic management simultaneously.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech