The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

Towards a holistic modelling framework for embodied carbon and waste in the building lifecycle

As the building industry proceeds in the direction of low impact buildings, research attention is being drawn towards the reduction of carbon dioxide emission and waste. Starting from design and construction to operation and demolition, various building materials are used throughout the whole building lifecycle involving significant energy consumption and waste generation. Building Information Modelling (BIM) is emerging as a tool that can support holistic design-decision making for reducing embodied carbon and waste production in the building lifecycle. This study aims to establish a framework for assessing embodied carbon and waste underpinned by BIM technology. On the basis of current research review, the framework is considered to include functional modules for embodied carbon computation. There are a module for waste estimation, a knowledge-base of construction and demolition methods, a repository of building components information, and an inventory of construction materials’ energy and carbon. Through both static 3D model visualisation and dynamic modelling supported by the framework, embodied energy (carbon), waste and associated costs can be analysed in the boundary of cradle-to-gate, construction, operation, and demolition. The proposed holistic modelling framework provides a possibility to analyse embodied carbon and waste from different building lifecycle perspectives including associated costs. It brings together existing segmented embodied carbon and waste estimation into a unified model, so that interactions between various parameters through the different building lifecycle phases can be better understood. Thus, it can improve design-decision support for optimal low impact building development. The applicability of this framework is anticipated being developed and tested on industrial projects in the near future.

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

Designing and implementing livestock value chain studies: a practical aid for Highly Pathogenic and Emerging Disease (HPED) control

Value chain studies, including production system and market chain studies, are essential to value chain analysis, which when coupled with disease risk analysis is a powerful tool to identify key constraints and opportunities for disease control based on risk management in a livestock production and marketing system. Several production system and market chain studies have been conducted to support disease control interventions in South East Asia. This practical aid summarizes experiences and lessons learned from the implementation of such value chain studies in South East Asia. Based on these experiences it prioritizes the required data for the respective purpose of a value chain study and recommends data collection as well as data analysis tools. This practical aid is intended as an adjunct to the FAO value chain approach and animal diseases risk management guidelines document. Further practical advice is provided for more effective use of value chain studies in South and South East Asia as part of animal health decision support.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

An evaluation of decadal probability forecasts from state-of-the-art climate models

While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 years, nontrivial structural flaws still hinder their ability to forecast the decadal dynamics of the Earth system realistically. Contrasting the skill of these models not only with each other but also with empirical models can reveal the space and time scales on which simulation models exploit their physical basis effectively and quantify their ability to add information to operational forecasts. The skill of decadal probabilistic hindcasts for annual global-mean and regional-mean temperatures from the EU Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project is contrasted with several empirical models. Both the ENSEMBLES models and a “dynamic climatology” empirical model show probabilistic skill above that of a static climatology for global-mean temperature. The dynamic climatology model, however, often outperforms the ENSEMBLES models. The fact that empirical models display skill similar to that of today's state-of-the-art simulation models suggests that empirical forecasts can improve decadal forecasts for climate services, just as in weather, medium-range, and seasonal forecasting. It is suggested that the direct comparison of simulation models with empirical models becomes a regular component of large model forecast evaluations. Doing so would clarify the extent to which state-of-the-art simulation models provide information beyond that available from simpler empirical models and clarify current limitations in using simulation forecasting for decision support. Ultimately, the skill of simulation models based on physical principles is expected to surpass that of empirical models in a changing climate; their direct comparison provides information on progress toward that goal, which is not available in model–model intercomparisons.

A web application for follow-up of results from a mobile device test battery for parkinson’s disease patients

Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown. Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients. Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.

Visualization of spirography-based objective measures in Parkinson's disease

Objective: To investigate whether advanced visualizations of spirography-based objective measures are useful in differentiating drug-related motor dysfunctions between Off and dyskinesia in Parkinson’s disease (PD). Background: During the course of a 3 year longitudinal clinical study, in total 65 patients (43 males and 22 females with mean age of 65) with advanced PD and 10 healthy elderly (HE) subjects (5 males and 5 females with mean age of 61) were assessed. Both patients and HE subjects performed repeated and time-stamped assessments of their objective health indicators using a test battery implemented on a telemetry touch screen handheld computer, in their home environment settings. Among other tasks, the subjects were asked to trace a pre-drawn Archimedes spiral using the dominant hand and repeat the test three times per test occasion. Methods: A web-based framework was developed to enable a visual exploration of relevant spirography-based kinematic features by clinicians so they can in turn evaluate the motor states of the patients i.e. Off and dyskinesia. The system uses different visualization techniques such as time series plots, animation, and interaction and organizes them into different views to aid clinicians in measuring spatial and time-dependent irregularities that could be associated with the motor states. Along with the animation view, the system displays two time series plots for representing drawing speed (blue line) and displacement from ideal trajectory (orange line). The views are coordinated and linked i.e. user interactions in one of the views will be reflected in other views. For instance, when the user points in one of the pixels in the spiral view, the circle size of the underlying pixel increases and a vertical line appears in the time series views to depict the corresponding position. In addition, in order to enable clinicians to observe erratic movements more clearly and thus improve the detection of irregularities, the system displays a color-map which gives an idea of the longevity of the spirography task. Figure 2 shows single randomly selected spirals drawn by a: A) patient who experienced dyskinesias, B) HE subject, and C) patient in Off state. Results: According to a domain expert (DN), the spirals drawn in the Off and dyskinesia motor states are characterized by different spatial and time features. For instance, the spiral shown in Fig. 2A was drawn by a patient who showed symptoms of dyskinesia; the drawing speed was relatively high (cf. blue-colored time series plot and the short timestamp scale in the x axis) and the spatial displacement was high (cf. orange-colored time series plot) associated with smooth deviations as a result of uncontrollable movements. The patient also exhibited low amount of hesitation which could be reflected both in the animation of the spiral as well as time series plots. In contrast, the patient who was in the Off state exhibited different kinematic features, as shown in Fig. 2C. In the case of spirals drawn by a HE subject, there was a great precision during the drawing process as well as unchanging levels of time-dependent features over the test trial, as seen in Fig. 2B. Conclusions: Visualizing spirography-based objective measures enables identification of trends and patterns of drug-related motor dysfunctions at the patient’s individual level. Dynamic access of visualized motor tests may be useful during the evaluation of drug-related complications such as under- and over-medications, providing decision support to clinicians during evaluation of treatment effects as well as improve the quality of life of patients and their caregivers. In future, we plan to evaluate the proposed approach by assessing within- and between-clinician variability in ratings in order to determine its actual usefulness and then use these ratings as target outcomes in supervised machine learning, similarly as it was previously done in the study performed by Memedi et al. (2013).

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Gestão do conhecimento e criação de valor: um estudo exploratório em empresas brasileiras

Nos últimos dez anos a gestão do conhecimento tem crescido em importância tanto no meio acadêmico como empresarial. Ainda que alguns permaneçam céticos, sua relevância para a competitividade das organizações tem se tornado cada vez mais um ponto de concordância nos dois ambientes, como uma resposta aos desafios sociais e econômicos impostos. Estes desafios impulsionam a gestão do conhecimento vista como uma disciplina interdisciplinar focada nos agentes e no seu ambiente, e no processo de criação, mapeamento e transferência do conhecimento, com o objetivo final de gerar vantagens competitivas sustentáveis. Apesar de muitos estudos específicos, ainda são poucos os trabalhos que buscam avaliar a adoção da gestão do conhecimento como abordagem ampla, quase como um novo paradigma gerencial adaptado à nova realidade econômica vigente, assim como são poucos os estudos que buscam avaliar o impacto na criação de valor de estratégias focadas no conhecimento. Este trabalho visa preencher essa lacuna, avaliando a adoção de práticas, conceitos e atitudes vinculadas à gestão do conhecimento em empresas de grande e pequeno porte criadoras de valor, através de estudos de caso. Para isso, o trabalho partiu de uma ampla revisão da literatura em torno do tema para definir um conjunto de práticas associadas ao conceito de gestão do conhecimento, dividido em seis dimensões: estratégia, estrutura, tecnologia da informação, cultura e pessoas, sistemas de suporte e processos. A partir deste levantamento, instrumentos distintos – questionário e roteiro de entrevista - foram elaborados para estudar as grandes e pequenas empresas. A pesquisa de campo só foi realizada após a validação do instrumento por especialistas na área, que avaliaram cada item com relação a sua total, parcial ou marginal associação ao conceito de gestão do conhecimento. Os resultados mostram que, independente do tamanho, as empresas criadoras de valor adotam muitas das práticas associadas a gestão do conhecimento em cinco das seis dimensões estudadas. Além destes indícios, o trabalho também contribui ao deixar um rol de mais de duzentos e trinta itens validados com relação ao conceito de gestão do conhecimento, que podem ser testados e aperfeiçoados.

Geração de múltiplos critérios para apoio à decisão em dados geoprocessados. Um estudo de caso : a microbacia hidrográfica de Inhandava, em Maximiliano de Almeida, RS

Uma das questões mais debatidas na atualidade diz respeito à problemática ambiental. A impossibilidade da verificação de muitos dos possíveis efeitos da atividade agrícola no ambiente rural tem levado pesquisadores das mais diversas áreas a buscar alternativas viáveis para uma utilização sustentável do ambiente. O presente trabalho apresenta o desenvolvimento de uma metodologia diferenciada para lidar com a questão. Utilizou-se, para isto, um estudo de caso em uma unidade de planejamento, a saber, uma bacia hidrográfica, ou microbacia hidrográfica (MBH) como será explanado no decorrer do texto, localizada no município de Maximiliano de Almeida, no Estado do Rio Grande do Sul, com uma área de cerca de 11,96 km2. Para esta bacia foram aplicadas as técnicas vinculadas às Metodologias Multicritério em Apoio à Decisão (MCDA – Multicriteria Decision Aided) visando à formulação de critérios quando do uso do geoprocessamento. Assim, a partir de uma revisão bibliográfica geral sobre os aspectos relacionados ao assunto em pauta, foram realizados os procedimentos metodológicos pertinentes, vinculados ao uso de MCDA e geoprocessamento, os quais resultaram em mapas específicos. A análise dos mapas resultantes corroborou as hipóteses apresentadas. Os resultados obtidos servem, portanto, como indicativos para a utilização desta metodologia nas demais bacias hidrográficas trabalhadas pela Associação Riograndense de Empreendimentos de Assistência Técnica e Extensão Rural – EMATER/RS – tida como parceira neste trabalho.

Emprego de uma metodologia multicritério na avaliação do estudo de impacto ambiental de hidrelétricas

Esta pesquisa parte da constatação expressa na literatura analisada de que os métodos e técnicas utilizados na elaboração do Estudo de Impacto Ambiental - EIA de empreendimentos hidrelétricos têm se mostrado inadequados para apoiar o complexo processo de tomada de decisão, tanto no âmbito das empresas de consultoria, que elaboram o Estudo, como no dos órgãos ambientais, que analisam o EIA. Para investigar e confirmar esta questão, foram analisados a legislação vigente, Termos de Referência para a elaboração de EIAs e nove EIAs de hidrelétricas. Dentre eles, foram selecionados dois para estudo de caso. Constatou-se que são necessários três processos de avaliação na elaboração do EIA: dos impactos, das medidas mitigadoras e dos programas. Na avaliação de impactos, a técnica mais utilizada é a Matriz de Leopold, aplicada de forma correta em apenas um dos EIAs. Tornou-se evidente que os pontos fracos dessa avaliação podem ser reduzidos e até eliminados desde que o órgão ambiental melhore algumas exigências no Termo de Referência, de tal forma que levem a consultora a utilizar a referida técnica de forma correta ou a adotar um método ou técnica mais adequada. As avaliações das medidas mitigadoras e dos programas não são realizadas, invariavelmente. As razões para esta situação podem ser atribuídas tanto aos órgãos ambientais como às empresas de consultoria. Os primeiros, porque nem sempre elaboram o Termo de Referência integralmente de acordo com a Resolução CONAMA nº 001/86, deixando de especificar que as avaliações devem ser realizadas com métodos e técnicas válidos e confiáveis. Os segundos, porque não tomam a iniciativa de atender à legislação vigente, independente das instruções expressas no Termo de Referência. Essas avaliações constituemse nos pontos fracos mais relevantes a serem melhorados por órgãos ambientais e consultores. Ao considerar a avaliação dos programas ambientais como a problemática prioritária, a pesquisa investiga e reconhece que as metodologias multicritério, em especial as de apoio à tomada de decisão, pertencentes ao grupo Multicriteria Decision Aid - MCDA, apresentam grande potencialidade para a solução da problemática detectada. A escolha recaiu sobre a abordagem proposta por Ensslin, Montibeller Neto e Noronha (2001), que foi adaptada e submetida a um teste para investigar a sua validade e exeqüibilidade na avaliação dos programas do EIA de duas hidrelétricas no rio Ijuí – RS. Para isso, foram envolvidos quatro especialistas da empresa consultora que elaborou o EIA, para atuarem como avaliadores. Os resultados foram submetidos à apreciação dos próprios avaliadores, de técnicos do órgão ambiental estadual e de técnicos do órgão ambiental federal, que se manifestaram favoráveis à metodologia, em sua maioria.