PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

Soil Moisture Deficit as a predictor of the trend in soil water status of grass fields

Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Spatial allocation of material flow analysis in residential developments: a case study of Kildare County, Ireland

Studies of urban metabolism provide important insights for environmental management of cities, but are not widely used in planning practice due to a mismatch of data scale and coverage. This paper introduces the Spatial Allocation of Material Flow Analysis (SAMFA) model as a potential decision support tool aimed as a contribution to overcome some of these difficulties and describes its pilot use at the county level in the Republic of Ireland. The results suggest that SAMFA is capable of identifying hotspots of higher material and energy use to support targeted planning initiatives, while its ability to visualise different policy scenarios supports more effective multi-stakeholder engagement. The paper evaluates this pilot use and sets out how this model can act as an analytical platform for the industrial ecology–spatial planning nexus.

An Intelligent Threat Prevention Framework with Heterogeneous Information

Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.

British Society of Gastroenterology guidelines on the diagnosis and management of Barrett's oesophagus

These guidelines provide a practical and evidence-based resource for the management of patients with Barrett's oesophagus and related early neoplasia. The Appraisal of Guidelines for Research and Evaluation (AGREE II) instrument was followed to provide a methodological strategy for the guideline development. A systematic review of the literature was performed for English language articles published up until December 2012 in order to address controversial issues in Barrett's oesophagus including definition, screening and diagnosis, surveillance, pathological grading for dysplasia, management of dysplasia, and early cancer including training requirements. The rigour and quality of the studies was evaluated using the SIGN checklist system. Recommendations on each topic were scored by each author using a five-tier system (A+, strong agreement, to D+, strongly disagree). Statements that failed to reach substantial agreement among authors, defined as >80% agreement (A or A+), were revisited and modified until substantial agreement (>80%) was reached. In formulating these guidelines, we took into consideration benefits and risks for the population and national health system, as well as patient perspectives. For the first time, we have suggested stratification of patients according to their estimated cancer risk based on clinical and histopathological criteria. In order to improve communication between clinicians, we recommend the use of minimum datasets for reporting endoscopic and pathological findings. We advocate endoscopic therapy for high-grade dysplasia and early cancer, which should be performed in high-volume centres. We hope that these guidelines will standardise and improve management for patients with Barrett's oesophagus and related neoplasia.

Pathways Project Final Report Volume 1: Field Investigation and Catchment Conceptual Models

viii
Executive Summary
The Pathways Project field studies were targeted at improving the understanding of contaminant transport along different hydrological pathways in Irish catchments, including their associated impacts on water quality and river ecology. The contaminants of interest were phosphorus, nitrogen and sediment. The working Pathways conceptual model included overland flow, interflow, shallow groundwater flow, and deep groundwater flow. This research informed the development of a set of Catchment Management Support Tools (CMSTs) comprising an Exploratory Tool, Catchment Characterization Tool (CCT) and Catchment Modelling Tool (CMT) as outlined in Pathways Project Final Reports Volumes 3 and 4.
In order to inform the CMST, four suitable study catchments were selected following an extensive selection process, namely the Mattock catchment, Co. Louth/Meath; Gortinlieve catchment, Co. Donegal; Nuenna catchment, Co. Kilkenny and the Glen Burn catchment, Co. Down. The Nuenna catchment is well drained as it is underlain by a regionally important karstified limestone aquifer with permeable limestone tills and gravels, while the other three catchments are underlain by poorly productive aquifers and low permeability clayey tills, and are poorly drained.
All catchments were instrumented, and groundwater, surface and near-surface water and aquatic ecology were monitored for a period of two years. Intensive water quality sampling during rainfall events was used to investigate the pathways delivering nutrients. The proportion of flow along each pathway was determined using chemical and physical hydrograph separation techniques, supported by numerical modelling.
The outcome of the field studies broadly supported the use of the initial four-pathway conceptual model used in the Pathways CMT (time-variant model). The artificial drainage network was found to be a significant contributing pathway in the poorly drained catchments, at low flows and during peak flows in wet antecedent conditions. The transition zone (TZ), i.e. the broken up weathered zone at the top of the bedrock, was also found to be an important pathway. It was observed to operate in two contrasting hydrogeological scenarios: in groundwater discharge zones the TZ can be regarded as being part of the shallow groundwater pathway, whereas in groundwater recharge zones it behaves more like interflow.
In the catchments overlying poorly productive aquifers, only a few fractures or fracture zones were found to be hydraulically active and the TZ, where present, was the main groundwater pathway. In the karstified Nuenna catchment, the springs, which are linked to conduits as well as to a diffuse fracture network, delivered the majority of the flow. These findings confirm the two-component groundwater contribution from bedrock but suggest that the size and nature of the hydraulically active fractures and the nature of the TZ are the dominant factors at the scale of a stream flow event.
Diffuse sources of nitrate were found to be typically delivered via the subsurface pathways, especially in the TZ and land drains in the poorly productive aquifer catchments, and via the bedrock groundwater in the Nuenna. Phosphorus was primarily transported via overland flow in both particulate and soluble forms. Where preferential flow paths existed in the soil and subsoil, soluble P, and to a lesser extent particulate P, were also transported via the TZ and in drains and ditches. Arable land was found to be the most important land use for
ix
the delivery of sediment, although channel bank and in-stream sources were the most significant in the Glen Burn catchment. Overland flow was found to be the predominant transport sediment pathway in the poorly productive catchments. These findings informed the development of the transport and attenuation equations used in the CCT and CMT. From an assessment of the relationship between physico-chemical and biological conditions, it is suggested that in the Nuenna, Glen Burn and Gortinlieve catchments, a relationship may exist between biological water quality and nitrogen concentrations, as well as with P. In the Nuenna, there was also a relationship between macroinvertebrate status and alkalinity.
Further research is recommended on the transport and delivery of phosphorus in groundwater, the transport and attenuation dynamics in the TZ in different hydrogeological settings and the relationship between macroinvertebrates and co-limiting factors. High resolution temporal and spatial sampling was found to be important for constraining the conceptual understanding of nutrient and sediment dynamics which should also be considered in future studies.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Robust implantable antenna for in-body communications

A compact implantable printed meandered folded dipole antenna with a volume of 101.8 mm3 and robust performance is presented for operation in the 2.4 GHz medical ISM bands. The implant antenna is shown to maintain its return loss performance in the 2360???2400 MHz, 2400???2483.5 MHz and 2483.5???2500 MHz frequency bands, simulated in eleven different body tissue types with a broad range of electrical properties. Bandwidth and resonant frequency changes are reported for the same antenna implanted in high water content tissues such as muscle and skin as well as low water content tissues such as subcutaneous fat and bone. The antenna was also shown to maintain its return loss performance as it was moved towards a tissue boundary within a simulated phantom testbed.

Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Perception and software architecture for mobile robotics

When developing software for autonomous mobile robots, one has to inevitably tackle some kind of perception. Moreover, when dealing with agents that possess some level of reasoning for executing their actions, there is the need to model the environment and the robot internal state in a way that it represents the scenario in which the robot operates. Inserted in the ATRI group, part of the IEETA research unit at Aveiro University, this work uses two of the projects of the group as test bed, particularly in the scenario of robotic soccer with real robots. With the main objective of developing algorithms for sensor and information fusion that could be used e ectively on these teams, several state of the art approaches were studied, implemented and adapted to each of the robot types. Within the MSL RoboCup team CAMBADA, the main focus was the perception of ball and obstacles, with the creation of models capable of providing extended information so that the reasoning of the robot can be ever more e ective. To achieve it, several methodologies were analyzed, implemented, compared and improved. Concerning the ball, an analysis of ltering methodologies for stabilization of its position and estimation of its velocity was performed. Also, with the goal keeper in mind, work has been done to provide it with information of aerial balls. As for obstacles, a new de nition of the way they are perceived by the vision and the type of information provided was created, as well as a methodology for identifying which of the obstacles are team mates. Also, a tracking algorithm was developed, which ultimately assigned each of the obstacles a unique identi er. Associated with the improvement of the obstacles perception, a new algorithm of estimating reactive obstacle avoidance was created. In the context of the SPL RoboCup team Portuguese Team, besides the inevitable adaptation of many of the algorithms already developed for sensor and information fusion and considering that it was recently created, the objective was to create a sustainable software architecture that could be the base for future modular development. The software architecture created is based on a series of di erent processes and the means of communication among them. All processes were created or adapted for the new architecture and a base set of roles and behaviors was de ned during this work to achieve a base functional framework. In terms of perception, the main focus was to de ne a projection model and camera pose extraction that could provide information in metric coordinates. The second main objective was to adapt the CAMBADA localization algorithm to work on the NAO robots, considering all the limitations it presents when comparing to the MSL team, especially in terms of computational resources. A set of support tools were developed or improved in order to support the test and development in both teams. In general, the work developed during this thesis improved the performance of the teams during play and also the e ectiveness of the developers team when in development and test phases.

The assessment of the practicability of the SOCOPSE project

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

Tourism planning informatization

The Tourism activity, due to its own characteristics, causes high environmental impact and its development should be influenced by the environmental characteristics of each region. The Information Systems, mainly those which represent the geographical information, will permit the development of a design, allowing the Decision-Maker the consult, the management and the presentation of decision schemes based on the defined measures of the Tourism Planning of a region. As the information associated with this design should be real and update, the Internet should be used as a means of access to the information of the region. The design presents the schemes associated to each decision, offering competitive advantages to the Decision-Makers involved in the decision process, since it is possible to evaluate, foresee and control the future environmental impacts of Tourism.

GIS on tourism planning: preventing the impacts caused by the developing tourism activity in a specific site

The environment is one of the greatest concerns of humankind. Nowadays, the activities which improve or destroy it must be assessed and controlled by efficient means which should permit the control of environmental impact caused by the development of these activities. This document presents an information system implementation, as a Decision Support system, allowing the Decision Maker to evaluate, foresee and control the future environmental impact of Tourism through consultation, the management and the presentation of decision schemes based on defined measures of a regional tourism planning.

Using data envelopment analysis to assess the efficiency of social security systems: the case of income protection in old age

As the number of pensioners in Europe rises relative to the number of people in employment, the gap between the contributions and the benefit levels increases, and consequently ensuring adequate pensions on a sustainable basis has become a major challenge. This study aims to explore the potential of using the Data Envelopment Analysis (DEA) technique in order to access the efficiency of the income protection in old age, one of the most important branches of Social Security. To this effect, we collected data from the 27 European Union Member States regarding this branch. Our results show important differences among the Member States and stress the importance of identifying best practices to achieve more adequate, sustainable and modernised pension systems. Our results also highlight the importance of using DEA as a decision support tool for policy makers.