Multi-criteria ranking and source apportionment of fine particulate matter in Brisbane, Australia

This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

Characterisation of soils with the use of instrumental techniques : a multivariate forensic study

The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

Analysis of the build-up of semi and non volatile organic compounds on urban roads

Vehicular traffic in urban areas may adversely affect urban water quality through the build-up of traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) on road surfaces. The characterisation of the build-up processes is the key to developing mitigation measures for the removal of such pollutants from urban stormwater. An in-depth analysis of the build-up of SVOCs and NVOCs was undertaken in the Gold Coast region in Australia. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the SVOC and NVOC build-up under combined traffic scenarios of low, moderate, and high traffic in different land uses. It was found that congestion in the commercial areas and use of lubricants and motor oils in the industrial areas were the main sources of SVOCs and NVOCs on urban roads, respectively. The contribution from residential areas to the build-up of such pollutants was hardly noticeable. It was also revealed through this investigation that the target SVOCs and NVOCs were mainly attached to particulate fractions of 75 to 300 µm whilst the redistribution of coarse fractions due to vehicle activity mainly occurred in the >300 µm size range. Lastly, under combined traffic scenario, moderate traffic with average daily traffic ranging from 2300 to 5900 and average congestion of 0.47 was found to dominate SVOC and NVOC build-up on roads.

Analysis of build-up of heavy metals and volatile organics on urban roads in Gold Coast, Australia

Urban water quality can be significantly impaired by the build-up of pollutants such as heavy metals and volatile organics on urban road surfaces due to vehicular traffic. Any control strategy for the mitigation of traffic related build-up of heavy metals and volatile organic pollutants should be based on the knowledge of their build-up processes. In the study discussed in this paper, the outcomes of a detailed experiment investigation into build-up processes of heavy metals and volatile organics are presented. It was found that traffic parameters such as average daily traffic, volume over capacity ratio and surface texture depth had similar strong correlations with the build-up of heavy metals and volatile organics. Multicriteria decision analyses revealed that the 1 - 74 um particulate fraction of total suspended solids (TSS) could be regarded as a surrogate indicator for particulate heavy metals in build-up and this same fraction of total organic carbon could be regarded as a surrogate indicator for particulate volatile organics build-up. In terms of pollutants affinity, TSS was found to be the predominant parameter for particulate heavy metals build-up and total dissolved solids was found to be the predominant parameter for he potential dissolved particulate fraction in heavy metals build-up. It was also found that land use did not play a significant role in the build-up of traffic generated heavy metals and volatile organics.

Effects of climate change on the wash-off of volatile organic compounds from urban roads

The predicted changes in rainfall characteristics due to climate change could adversely affect stormwater quality in highly urbanised coastal areas throughout the world. This in turn will exert a significant influence on the discharge of pollutants to estuarine and marine waters. Hence, an in-depth analysis of the effects of such changes on the wash-off of volatile organic compounds (VOCs) from urban roads in the Gold Coast region in Australia was undertaken. The rainfall characteristics were simulated using a rainfall simulator. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the VOC wash-off under climate change. It was found that low, low to moderate and high rain events due to climate change will affect the wash-off of toluene, ethylbenzene, meta-xylene, para-xylene and ortho-xylene from urban roads in Gold Coast. Total organic carbon (TOC) was identified as predominant carrier of toluene, meta-xylene and para-xylene in <1µm to 150µm fractions and for ethylbenzene in 150µm to >300µm fractions under such dominant rain events due to climate change. However, ortho-xylene did not show such affinity towards either TOC or TSS (total suspended solids) under the simulated climatic conditions.

Developing a fuzzy multi-criteria decision-making model for selecting design-build operational variations

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Improving megasite management performance through incentives : lessons learned from the Shanghai Expo construction

As the biggest expo site in history, construction of the Shanghai Expo site faced a lot of challenges, including involvement of lots of investors, megaconstruction scale, concurrent construction mode, involvement of more than 40,000 migrant workers, and extremely tight completion deadlines, among others. Consequently, these challenges imposed great obstacles on accomplishing the safety, quality, and environmental goals. Through a case study of the Shanghai Expo construction, this paper paper presents the design and implementation of multicriteria incentives in megaprojects to accomplish the safety, quality, and environmental goals. Both quantitative and qualitative findings were triangulated to demonstrate the outcome of the incentives. Six critical success factors (CSFs) for the incentives, rule design, process orientation, top management support, training and promotion, communication in process, and process learning and improvement are identified and validated through case study data and content analysis. It is believed that the findings of this paper can enhance understanding of multicriteria incentive schemes in general and provide insights in implementing these incentive schemes in future megaprojects, particularly in the People’s Republic of China (PRC).

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Propuestas para una segmentación estratégica del mercado ecológico

[ES] La creciente concienciación medioambiental y la necesidad de atender a las nuevas demandas ecológicas del mercado, obligan a las empresas a desarrollar instrumentos de análisis para ahondar en su conocimiento. La segmentación de mercados es un instrumento analítico válido para inferir características diferenciales de los consumidores ecológicos y adecuar la estrategia de marketing a las preferencias de los segmentos detectados. En este trabajo analizamos las limitaciones de los criterios de segmentación tradicionales y las ventajas de las segmentaciones multicriterio para recoger la complejidad inherente al consumidor ecológico y definir la estrategia de marketing ecológico. Así mismo, presentamos algunas de las segmentaciones del mercado ecológico más relevantes.

Sistema de suporte à decisão espacial aplicado à análise da vulnerabilidade dos recursos hídricos na bacia Guapi-Macacu / RJ.

No contexto do planejamento e gestão dos recursos hídricos em bacias hidrográficas, é crescente a demanda por informações consistentes relativas ao estado do ambiente e pressões ambientais de forma integrada, para que possam informar à população e subsidiar atividades do setor público e privado. Essa demanda pode ser satisfeita com a modelagem e integração em um Sistema de Informações Geográficas (SIG), com propriedades e funções de processamento que permitem sua utilização em ambiente integrado. Desta forma, neste trabalho é apresentada uma metodologia para a avaliação muticriterial dos recursos hídricos de bacias hidrográficas, que vai desde a seleção de indicadores e definição dos pesos, até a execução de avaliações e espacialização de resultados. Esta metodologia é composta por duas fases: avaliação da vulnerabilidade dos recursos hídricos de uma bacia hidrográfica a partir do uso de sistemas de suporte à decisão espacial, e, avaliação da qualidade das águas através da adaptação de um Índice de Qualidade das Águas. Foi adotada uma base de conhecimento, sistemas de suporte à decisão, SIG e uma ferramenta computacional que integra estes resultados permitindo a geração de análises com cenários da vulnerabilidade dos recursos hídricos. Em paralelo, a qualidade das águas das sub-bacias hidrográficas foi obtida a partir da adaptação do cálculo do Índice de Qualidade das águas proposto pela Companhia de Tecnologia de Saneamento Ambiental (CETESB) e aplicação do Índice de Toxidez. Os resultados mostraram sub-bacias com seus recursos hídricos mais ou menos vulneráveis, bem como sub-bacias com toxidez acima da legislação. A avaliação integrada entre áreas mais vulneráveis e que apresentam menor qualidade e/ou maior toxidez poderá nortear a tomada de decisão e projetos visando a conservação dos recursos hídricos em bacias hidrográficas.

SIG aplicado na identificação de áreas potenciais aos investimentos habitacionais Estudo de caso: porção oeste do Município do Rio de Janeiro.

A expansão industrial e o desenvolvimento territorial na porção oeste do Município do Rio de Janeiro trazem inúmeras modificações no cenário socioeconômico da região e adjacências. O destaque de investimentos na indústria de transformação é a implantação da Companhia Siderúrgica do Atlântico (CSA), que se mostra como o maior empreendimento privado em realização no país. Investimentos públicos e privados no setor de infraestrutura estão previstos, considerando as características naturais e a localização geográfica privilegiada da região. A influência do porto de Itaguaí e a construção do Arco Metropolitano configuram um corredor de desenvolvimento com reflexos positivos logísticos e socioeconômicos, não só para o estado do Rio de Janeiro, mas também para outros estados brasileiros. Os impactos da reordenação do espaço urbano, com a possibilidade de incremento populacional nas proximidades do novo eixo rodoviário e industrial, tende a gerar um aumento da demanda por serviços no setor terciário. Dessa forma, o planejamento territorial se faz obrigatório, apoiado por geotecnologias. O objetivo da pesquisa foi atender às necessidades do setor habitacional, analisando fatores relevantes e condições favoráveis à implantação de novas construções habitacionais. Baseando-se em dados provenientes do censo do IBGE de 2010 e do Instituto de Urbanismo Pereira Passos (IPP), a Tecnologia da Informação integrada com os dados de mapas digitais e imagens de satélite de alta resolução (World View-2), permitiram uma análise geral do contexto do crescimento regional. Além da análise das variáveis existentes nos dados socioeconômicos, outras variáveis de pesquisa foram empregadas em ambiente SIG, tais como: segurança, proximidades de logradouros principais, existências de escolas e hospitais municipais e estaduais, distância dos centros industriais e de shopping. Após as análises multicriteriais de dados socioeconômicos e bases cartográficas, relatórios na forma de mapas foram emitidos, com a finalidade de orientar o poder público e as construtoras nas tomadas de decisões.

Mapeamento digital de áreas suscetíveis a escorregamento na parte continental do município de Angra dos Reis, RJ.

O presente trabalho tem como objetivo analisar a classificação resultante do emprego da Avaliação de Multicritérios, utilizando a técnica AHP (Analytic Hierarchy Process), em ambiente SIG, para o mapeamento de áreas suscetíveis à escorregamento no município de Angra dos Reis. O estudo exigiu duas imagens Landsat 7 TM, obtidas respectivamente em 14/08/2006 e 17/06/2005. O produto gerado será comparado com os dados já existentes disponibilizados pela Defesa Civil do município, servindo de auxílio às ações no processo de gestão territorial, dando suporte ao planejamento e execução de projetos ambientais e de engenharia e apoio a tomadas de decisões governamentais, evitando novos desastres como os ocorridos em 31/12/2009 e 01/01/2010.