PERFORMANCE OF THE MODEL CALLED ACQUANETXL IN THE ALLOCATION OF WATER IN COMPLEX WATER RESOURCE SYSTEMS

This article presents a tool for the allocation analysis of complex systems of water resources, called AcquaNetXL, developed in the form of spreadsheet in which a model of linear optimization and another nonlinear were incorporated. The AcquaNetXL keeps the concepts and attributes of a decision support system. In other words, it straightens out the communication between the user and the computer, facilitates the understanding and the formulation of the problem, the interpretation of the results and it also gives a support in the process of decision making, turning it into a clear and organized process. The performance of the algorithms used for solving the problems of water allocation was satisfactory especially for the linear model.

Radial measures of public services deficit for regional allocation of public funds

The goal of this paper is to present an optimal resource allocation model for the regional allocation of public service inputs. Theproposed solution leads to maximise the relative public service availability in regions located below the best availability frontier, subject to exogenous budget restrictions and equality ofaccess for equal need criteria (equity-based notion of regional needs). The construction of non-parametric deficit indicators is proposed for public service availability by a novel application of Data Envelopment Analysis (DEA) models, whose results offer advantages for the evaluation and improvement of decentralised public resource allocation systems. The method introduced in this paper has relevance as a resource allocation guide for the majority of services centrally funded by the public sector in a given country, such as health care, basic and higher education, citizen safety, justice, transportation, environmental protection, leisure, culture, housing and city planning, etc.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

An analysis of the effects of preferential trade policies through the estimation of quantitative models: the case of Portugal.

Doutoramento em Economia.

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

Architecture and morphogenesis of grain sorghum, Sorghum bicolor (L.) Moench

Plant architecture has been neglected in most studies of biomass allocation in crops. To help redress this situation for grain sorghum (Sorghum bicolor (L.) Moench), we used a 3D digitiser to measure the dimensions and orientations of vegetative and reproductive structures and derived thermal time-based functions for architectural changes during morphogenesis. Our plants, which were grown in a greenhouse, controlled environment cabinets and the field, covered a large, three-fold, size range when mature. This allowed us to detect some general architectural relationships and to fit morphogenetic functions common across the size range we observed. For example, the relationship between the lengths of successive fully-expanded leaves within a plant was nearly constant for all plants. The lengths of existing leaf blades were accurate predictors of the lengths of up to six subsequently-formed blades in our plants. Similar constant relationships were detected for internode lengths in the panicle and for heights above ground of the collars of successive leaves, even though these traits varied a lot between growth conditions. We suggest that such architectural relationships may be used to link the effect of previous growth conditions to future growth potential, and in that way to predict future partitioning. Our results provide the basis for a preliminary model of sorghum morphogenesis which could eventually become useful in conjunction with crop models by allowing resource acquisition to be related to changes in plant architecture during development. (C) 1999 Elsevier Science B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Contingent attentional capture or delayed allocation of attention?

Under certain circumstances, external stimuli will elicit an involuntary shift of spatial attention, referred to as attentional capture. According to the contingent involuntary orienting account (Folk, Remington, & Johnston, 1992), capture is conditioned by top-down factors that set attention to respond involuntarily to stimulus properties relevant to one's behavioral goals. Evidence for this comes from spatial cuing studies showing that a spatial cuing effect is observed only when cues have goal-relevant properties. Here, we examine alternative, decision-level explanations of the spatial cuing effect that attribute evidence of capture to postpresentation delays in the voluntary allocation of attention, rather than to on-line involuntary shifts in direct response to the cue. In three spatial cuing experiments, delayed-allocation accounts were tested by examining whether items at the cued location were preferentially processed. The experiments provide evidence that costs and benefits in spatial cuing experiments do reflect the on-line capture of attention. The implications of these results for models of attentional control are discussed.

Energy and delay trade-off of the GTS allocation mechanism in IEEE 802.15.4 for wireless sensor networks

The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks (LR-WPAN) including wireless sensor networks (WSNs). It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When in beaconenabled mode, the protocol can provide timeliness guarantees by using its Guaranteed Time Slot (GTS) mechanism. However, power-efficiency and timeliness guarantees are often two antagonistic requirements in wireless sensor networks. The purpose of this paper is to analyze and propose a methodology for setting the relevant parameters of IEEE 802.15.4-compliant WSNs that takes into account a proper trade-off between power-efficiency and delay bound guarantees. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters, using Network Calculus formalism. We then evaluate the delay bound guaranteed by a GTS allocation and express it as a function of the duty cycle. Based on the relation between the delay requirement and the duty cycle, we propose a power-efficient superframe selection method that simultaneously reduces power consumption and enables meeting the delay requirements of real-time flows allocating GTSs. The results of this work may pave the way for a powerefficient management of the GTS mechanism in an IEEE 802.15.4 cluster.

Factors that determine the level of care children and adolescents experiencing mental disorders receive

RESUMO: Resumo Uma prestação de serviços de saúde mental para crianças e adolescentes (CAMHS) oportuna, eficaz e baseada na evidência pode evitar incapacidade a longo prazo. No entanto, estes serviços são criticamente sub-financiados em todo o mundo. É um imperativo garantir que este precioso recurso não seja desperdiçado. Os governos e outras partes interessadas relevantes na área da saúde mental precisam de conhecer o estado de saúde mental da população, quais os recursos disponíveis e como melhor utilizar os recursos disponíveis para orientar uma política e decisões efectivas sobre os níveis de serviços. Objetivo: O objetivo deste artigo é explorar o papel da acuidade, gravidade e complexidade na determinação dos cuidados em saúde mental especializados recebidos por crianças e adolescentes que sofrem perturbações mentais. Métodos: Este estudo é exploratório envolvendo uma revisão sistemática da literatura. Foi realizada uma pesquisa com palavras-chave utilizando bases de dados PsychINFO, EMBASE, PubMed e MEDLINE. A literatura cinzenta também foi investigada com um enfoque nas abordagens sistémicas, organizacionais e políticas para a organização e comissionamento de CAMHS. Foram selecionados apenas documentos escritos em Inglês. Três países, Bélgica, Reino Unido e Estados Unidos, todos eles com modelos muito diferentes de organização de CAMHS, foram revistos para investigar de que forma os conceitos de acuidade, gravidade e complexidade foram utilizados na sua concepção de serviços para determinar o nível da assistência prestada. Resultados: Nem a Bélgica, nem o modelo norte-americano de CAMHS organização de serviço parecem estar alinhados com os principais conceitos na determinação do nível de prestação de serviços. O sistema de serviços do Reino Unido de CAMHS está mais estreitamente alinhado com esses conceitos e tem uma alocação de recursos mais equilibrada entre o hospital e a comunidade. O seu ponto fraco está na falta de flexibilidade entre os níveis de serviço e na falta de apoio para com o sector dos cuidados de saúde primários. Conclusões: A variabilidade na alocação de recursos a diferentes níveis especializados de CAMHS (em regime de internamento, ambulatório, e na comunidade) e o modelo diferente de estrutura de serviços entre os países estudados indica uma inconsistência na forma como as crianças e adolescentes que apresentam aos CAMHS são referenciados para os cuidados que recebem. Isto põe em questão se as crianças e adolescentes com perturbações mentais estão a receber o nível e tipo de cuidados concordantes com as suas necessidades. A concepção e o comissionamento de sistemas de CAMHS levam-nos à discussão de uma série de princípios fundamentais que devem ser considerados. O sistema perfeito no entanto, ainda está para ser encontrado. -------------------------------- ABSTRACT: Provision of timely, effective, evidence based mental health services to children and adolescents can prevent long term impairment, but they are critically underfunded across the globe. There is an imperative to ensure this precious resource is not wasted. Governments and other relevant mental health stakeholders need to know the mental health status of the population, what resources are available and how best to use the resources available to guide effective policy and decisions about service levels. Aim: The aim of this paper is to explore the role of acuity, severity and complexity in determining the specialist mental health care that children and adolescents experiencing mental disorders receive. Methods: This study is exploratory involving a systematic scan of the literature. A key word search was conducted using databases PSYCHINFO, EMBASE, PUBMED and MEDLINE. Grey literature was also searched to focus on systemic, organisational and policy approaches to the organisation and commissioning of CAMHS. Only documents written in English were selected. Three countries Belgium, UK and the US all with very different models of service organisation for CAMHS were reviewed to investigate how well the concepts of acuity, severity and complexity were used to determine the level of care delivered in their service design. Findings: Neither the Belgium nor the US model of CAMHS service organisation appear to align with the key concepts driving intensity of level of service provision. The UK CAMHS service system most closely aligns with the concepts. It has a more balanced resource allocation between hospital and community. Its downfall is in its lack of flexibility between service levels and its lack of support for the primary care sector. Conclusions: The variability in resource allocation to different service levels (inpatient, outpatient, community) within specialist CAMHS and the differing model of service structure across countries indicates an inconsistency in how children and adolescents presenting to CAMHS are allocated to the care they receive. This puts into question whether children and adolescent with mental disorders are receiving a level and type of care commensurate with their needs. In commissioning and designing CAMHS systems a number of key principles that should be considered are discussed. The perfect system however, is yet to be found.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.

Fair Allocation of Production Externalities: Recent Results

We survey recent axiomatic results in the theory of cost-sharing. In this litterature, a method computes the individual cost shares assigned to the users of a facility for any profile of demands and any monotonic cost function. We discuss two theories taking radically different views of the asymmetries of the cost function. In the full responsibility theory, each agent is accountable for the part of the costs that can be unambiguously separated and attributed to her own demand. In the partial responsibility theory, the asymmetries of the cost function have no bearing on individual cost shares, only the differences in demand levels matter. We describe several invariance and monotonicity properties that reflect both normative and strategic concerns. We uncover a number of logical trade-offs between our axioms, and derive axiomatic characterizations of a handful of intuitive methods: in the full responsibility approach, the Shapley-Shubik, Aumann-Shapley, and subsidyfree serial methods, and in the partial responsibility approach, the cross-subsidizing serial method and the family of quasi-proportional methods.