Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants.

BACKGROUND: Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. METHODS: We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m(2) [underweight], 18·5 kg/m(2) to <20 kg/m(2), 20 kg/m(2) to <25 kg/m(2), 25 kg/m(2) to <30 kg/m(2), 30 kg/m(2) to <35 kg/m(2), 35 kg/m(2) to <40 kg/m(2), ≥40 kg/m(2) [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. FINDINGS: We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m(2) (95% credible interval 21·3-22·1) in 1975 to 24·2 kg/m(2) (24·0-24·4) in 2014 in men, and from 22·1 kg/m(2) (21·7-22·5) in 1975 to 24·4 kg/m(2) (24·2-24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m(2) in central Africa and south Asia to 29·2 kg/m(2) (28·6-29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m(2) (21·4-22·3) in south Asia to 32·2 kg/m(2) (31·5-32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5-17·4) to 8·8% (7·4-10·3) in men and from 14·6% (11·6-17·9) to 9·7% (8·3-11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8-29·2) in men and 24·0% (18·9-29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4-4·1) in 1975 to 10·8% (9·7-12·0) in 2014 in men, and from 6·4% (5·1-7·8) to 14·9% (13·6-16·1) in women. 2·3% (2·0-2·7) of the world's men and 5·0% (4·4-5·6) of women were severely obese (ie, have BMI ≥35 kg/m(2)). Globally, prevalence of morbid obesity was 0·64% (0·46-0·86) in men and 1·6% (1·3-1·9) in women. INTERPRETATION: If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia. FUNDING: Wellcome Trust, Grand Challenges Canada.

Quantitative market and sales forecast accuracy analysis

The main objective of this master’s thesis was to quantitatively study the reliability of market and sales forecasts of a certain company by measuring bias, precision and accuracy of these forecasts by comparing forecasts against actual values. Secondly, the differences of bias, precision and accuracy between markets were explained by various macroeconomic variables and market characteristics. Accuracy and precision of the forecasts seems to vary significantly depending on the market that is being forecasted, the variable that is being forecasted, the estimation period, the length of the estimated period, the forecast horizon and the granularity of the data. High inflation, low income level and high year-on-year market volatility seems to be related with higher annual market forecast uncertainty and high year-on-year sales volatility with higher sales forecast uncertainty. When quarterly market size is forecasted, correlation between macroeconomic variables and forecast errors reduces. Uncertainty of the sales forecasts cannot be explained with macroeconomic variables. Longer forecasts are more uncertain, shorter estimated period leads to higher uncertainty, and usually more recent market forecasts are less uncertain. Sales forecasts seem to be more uncertain than market forecasts, because they incorporate both market size and market share risks. When lead time is more than one year, forecast risk seems to grow as a function of root forecast horizon. When lead time is less than year, sequential error terms are typically correlated, and therefore forecast errors are trending or mean-reverting. The bias of forecasts seems to change in cycles, and therefore the future forecasts cannot be systematically adjusted with it. The MASE cannot be used to measure whether the forecast can anticipate year-on-year volatility. Instead, we constructed a new relative accuracy measure to cope with this particular situation.

Economical and operational analysis of outsourced warehouse function

The target of the thesis was to find out has the decision to outsource part of Filtronic LK warehouse function been profitable. Furthermore, another thesis target was to demonstrate current logistics processes between TPLP and company and find out the targets for developing these processes. The decision to outsource part of logistical funtions have been profitable during the first business year. Partnership includes always business risks. Risk increases high asset specific investments. In the other hand investment to partnership increases mutual trust and commitment between parties. By developing partnership risks and opportunitic behaviour can be decreased. The potential of managing material and data flows between logistic service provider and company observed. By analyzing inventory effiency were highlighted the need for decreasing the capital invested to inventories. The recommendations for managing outsourced logistical funtions were established such as improving partnership, process development, performance measurement and invoice checking.

Investment risks in Russia: A Finnish perspective

Purpose of this study is to analyze the effect of Russia's economic environment changes in the total return indexes of Finnish companies. The research data consisted of Finnish publicly listed companies, which have made physical investments to Russia, and operating in the area. The study used six different variables to model the Russian operating environment. The data consists of total return indexes of Finnish companies. From those we calculated the monthly mean interval between timeline of 1 January 2000 to 31 December 2009. Sample period is divided into two different parts. Variables impact on companies' total return indices is tested by regression analysis. By F-test we tested significance of model and squared coefficient correlation told us how much model explains from changes. Goodness of the β-coefficient is tested in the model by t-test. The research results shows that the Russian operating environment, or changes in which the active Finnish companies in total return indices. On partial sample periods results were not so significant.

Computational modeling for irrigated agriculture planning. Part II: risk analysis

Techniques of evaluation of risks coming from inherent uncertainties to the agricultural activity should accompany planning studies. The risk analysis should be carried out by risk simulation using techniques as the Monte Carlo method. This study was carried out to develop a computer program so-called P-RISCO for the application of risky simulations on linear programming models, to apply to a case study, as well to test the results comparatively to the @RISK program. In the risk analysis it was observed that the average of the output variable total net present value, U, was considerably lower than the maximum U value obtained from the linear programming model. It was also verified that the enterprise will be front to expressive risk of shortage of water in the month of April, what doesn't happen for the cropping pattern obtained by the minimization of the irrigation requirement in the months of April in the four years. The scenario analysis indicated that the sale price of the passion fruit crop exercises expressive influence on the financial performance of the enterprise. In the comparative analysis it was verified the equivalence of P-RISCO and @RISK programs in the execution of the risk simulation for the considered scenario.

Approaches to Supply Chain Risk Management: Identification, Analysis and Control

Supply chain risk management has emerged as an increasingly important issue in logistics as disruptions in the supply chain have become critical issues for many companies. The scientific literature on the subject is developing and in many respects the understanding of it is still in its infancy. Thus, there is a need for more information in order for scholars and practitioners to understand the causalities and interrelations that characterise the phenomenon. The aim of this dissertation is to narrow this gap by exploring key aspects of supply chain risk management through two maritime supply chains in the immediate region of the Gulf of Finland. The study contributes to the field in three different ways. Firstly, it facilitates the identification of risks on different levels of the supply chain through a systematic analysis of the processes and actors, and of the cognitive barriers that limit the actors’ visibility and their understanding of the operations and the risks involved. There is a clear need to increase collaboration and information exchange in order to improve visibility in the chain. Risk management should be a collaborative effort among the individual actors, aimed at obtaining a holistic picture. Secondly, the study contributes to the literature on risk analysis through the use of systemic frameworks that illustrate the causalities and linkages in the system, thereby making it easier to perceive the vulnerabilities. Thirdly, the study enhances current knowledge of risk control in identifying actor roles, risk visibility and risk controllability as being among the key factors determining risk-management effectiveness against supply-chain vulnerability. This dissertation is divided into two parts. The first part gives a general overview of the relevant literature, the research design and the conclusions of the study, and the second part comprises six research publications. Case-study methodology with systematic combining approach is used, where in-depth interviews, questionnaires and expert panel sessions are the main data collection methods. The study illustrates the current state of risk management in multimodal maritime supply chains, and develops frameworks for further analysis. The results imply that there are major differences between organizations in their ability to execute supply chain risk management. Further collaboration should be considered in order to facilitate the development of systematic and effective management processes.

Management of commercial property derived risks in the market context of the Russian Federation

The objective of the thesis is to examine the current state of risk management and to determine an appropriate risk management policy for commercial property derived risks in the Russian branch of a Finnish retail trade company. The employed research methodologies are comparative in-depth interviews and empirical value at risk analysis, including portfolio risk decomposition to determine the inter-currency characteristics. For a multinational retail trade company, the commercial property derived risks open up as a diverse combination of financial and non-financial risks with four distinctive interest groups. The research results indicate that geographical diversification across currency regimes provides diversification benefits. The Russian ruble is the most significant single risk component when considering the net investments outside the euro-zone. Decreasing the Russian ruble and Swedish krona exposures are the most effective methods to reduce translation derived risk. Exchange rate volatility varies over time according to idiosyncratic currency regime characteristics, and cost-effective risk management requires comprehensive analysis of the business environment. Profound and proactive risk management methods are found to be pivotal for companies with cross-border operations in order to succeed among international competitors.

Enterprise applications migration to the cloud: risks and opportunities

Millions of enterprises move their applications to a cloud every year. According to Forrester Research “the global cloud computing market will grow from a $40.7 billion in 2011 to $241 billion in 2020”. Due to increased interests and demand broad range of providers and solutions have appeared in the market. It is vital to be able to predict possible problems correctly and to classify and mitigate risks associated with the migration process. The study will show the main criteria that should be taken into consideration while making decision of moving enterprise applications to the cloud and choosing appropriate vendor. The main goal of the research is to identify main problems during the migration to a cloud and propose a solution for their prevention and mitigation of consequences in case of occurrence. The research provides an overview of existing cloud solutions and deployment models for enterprise applications. It identifies decision drivers of an applications migration to a cloud and potential risks and benefits associated with this. Finally, the best practices for the successful enterprise-to-cloud migration based on the case studies analysis are formulated.

Randomized controlled trials of serotonin-norepinephrine reuptake inhibitor in treating major depressive disorder in children and adolescents: a meta-analysis of efficacy and acceptability

New generation antidepressant therapies, including serotonin-norepinephrine reuptake inhibitor (SNRIs), were introduced in the late 1980s; however, few comprehensive studies have compared the benefits and risks of various contemporary treatments for major depressive disorder (MDD) in young patients. A comprehensive literature search of PubMed, Cochrane, Embase, Web of Science, and PsycINFO databases was conducted from 1970 to January 2015. Only clinical trials that randomly assigned one SNRI or placebo to patients aged 7 to 18 years who met the diagnostic criteria for major depressive disorder were included. Treatment success, dropout rate, and suicidal ideation/attempt outcomes were measured. Primary efficacy was determined by pooling the risk ratios (RRs) of treatment response and remission. Acceptability was determined by pooling the RRs of dropouts for all reasons and for adverse effects as well as suicide-risk outcomes. Five trials with a total of 973 patients were included. SNRIs were not significantly more effective than placebo for treatment response but were for remission. The comparison of patients taking SNRIs that dropped out for all reasons and those taking placebo did not reach statistical significance. Significantly more patients taking SNRIs dropped out for adverse effects than those taking placebo. No significant difference was found in suicide-related risk outcomes. SNRI therapy does not display a superior efficacy and is not better tolerated compared to placebo in these young patients. However, duloxetine has a potential beneficial effect for depression in young populations, showing a need for further research.

Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

Performance improvement in mediterranean operations using risk management analysis : Case study of Containerships Group Ltd

Emerging markets of Northern Africa and Turkey provide growth opportunities for logistics service companies in the middle of low growth environment of European Union. The purpose of this research is to explore and analyze the risk factors in container shipping industry and third party logistics (3PL) services. The research empirically examined the risk factors, which are related within the interaction between these two parties in emerging markets of Mediterranean area. The previous studies have provided a valuable insight into the operational risks faced by container shipping industries. However, most of these studies have focused on one or several operational risk factors from a single point of view, and no studies have inclusively examined the possible operational risks faced in the container shipping industry from dual perspective of 3PL provider and its customers. A questionnaire has been deployed to collect related data; and the impacts of the risks were then be assessed and ranked using the method of risk mapping. Respondents were located in Turkey, Algeria, Tunisia, and Libya. Research presents the most important risk factors identified, and compares them between 3PL provider and its customers. The research also provide some risk mitigation strategies for the key risk factors, and tried to figure out a common risk picture, which guides the managers in both sides to have a better decisions and as a result, improve the performance of the container shipping operations. Challenge during project execution time was that customers identified vast amount of more risks than what was the case with logistics service operator.

A case study of the Ottawa Valley whitewater rafting industry : standards and risks

This qualitative case study identifies and discusses the standards and risk management practices of the Ottawa Valley whitewater rafting industry and the impacts of the government enforced Special-purpose Vessels Regulations are discussed. Data collection occurred using a single case study design, which included interviews and document analysis. This study found that internal, industry, and actual standards are influenced through a variety of sources. These standards were found to affect the risk management practices of commercial whitewater rafting providers. In general, these standards promoted a high level of risk management within the Ottawa Valley rafting industry. The Special-purpose Vessels Regulations were found to be non-influential in raising the risk management standards of the Ottawa Valley whitewater rafting industry.

Consequence modelling,vulnerability assessment and fuzzy fault tree analysis of hazardous storages in an industrial area

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation .

Modelling and Analysis of Recurrent Event Data with Multiple Causes

This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival data is a term used for describing data that measures the time to occurrence of an event.In survival studies, the time to occurrence of an event is generally referred to as lifetime.Recurrent event data are commonly encountered in longitudinal studies when individuals are followed to observe the repeated occurrences of certain events. In many practical situations, individuals under study are exposed to the failure due to more than one causes and the eventual failure can be attributed to exactly one of these causes.The proposed model was useful in real life situations to study the effect of covariates on recurrences of certain events due to different causes.In Chapter 3, an additive hazards model for gap time distributions of recurrent event data with multiple causes was introduced. The parameter estimation and asymptotic properties were discussed .In Chapter 4, a shared frailty model for the analysis of bivariate competing risks data was presented and the estimation procedures for shared gamma frailty model, without covariates and with covariates, using EM algorithm were discussed. In Chapter 6, two nonparametric estimators for bivariate survivor function of paired recurrent event data were developed. The asymptotic properties of the estimators were studied. The proposed estimators were applied to a real life data set. Simulation studies were carried out to find the efficiency of the proposed estimators.