Business intelligence has fundamentally changed how many companies conduct their business. The focus of academic literature has however been on volume-operation companies that provide services to millions of customers. Complex-systems companies have fewer customers and pursue customer needs by providing more customized products and services. The knowledge in the research society is limited to volume-operation companies and there a need for more case studies regarding how companies actually use their information systems, specifically complex-systems companies. This work looks at a case of a complex-systems company with the overall aim to see how complex-systems companies may take advantage of business intelligence. A framework was used to measure BI maturity; expressed future needs were compared to future trends in BI literature and BI usage in specific areas was analyzed with the help of a framework from BI literature. The results indicate that the company is somewhere between Aspirational and Experienced with respect to BI maturity. BI is used for reporting a variety of key performance indicators and the main analysis tool for various calculations is Excel. The expressed future needs are mainly strategy-driven and technology-driven and often involve better and faster access to information. The difference in the business models of volume-operations companies and complex-systems companies could influence the BI maturity and help to explain the maturity difference between these two types of companies. Furthermore, the results indicate that there is a difference between the roles of BI tools in complex-systems companies compared to volume-operations.

Humanity is facing a series of challenges, including climate change, biodiversity loss, decreasing availability of cheap fossil fuel energy and social inequality that, when taken together, constitute a sustainability crisis. Agricultural systems are vitally important for the survival of humanity and must be moved towards greater sustainability. In Vietnam, the challenges facing the agriculture sector are immediate and pressing. These challenges include the need to improve the livelihoods of millions of smallholder farmers, improve food safety and protect already heavily burdened ecosystems. In response to these challenges, a number of alternative agriculture approaches, including safe vegetable production and organic farming have emerged. While the use of chemical fertilizers and pesticides are not permitted in certified organic agriculture, the requirements for safe vegetable production are not nearly as stringent. Chemical fertilizers and some low toxicity pesticides are allowed in safe vegetable production as long as pesticide residues are below proscribed limits. This research assesses the contributions that safe vegetable production and organic agriculture are making to the development of more sustainable agroecosystems in Vietnam. Organic production is still in early stages of development, with the majority of the projects directed towards production for export. Safe vegetables in contrast are produced primarily for the domestic market and demand is driven by consumer concerns over excessive pesticide use in conventional vegetable production. A sustainability assessment that explores the effect that safe vegetable production is having on eight major criteria for sustainability is applied in Cu Chi District, Ho Chi Minh City. Research methods included semi-structured interviews and group discussions with safe vegetable farmers together with interviews of other key actors from the agricultural sector in Vietnam. Along with the goal of protecting human health, farmers are interested in safe vegetable production because of improved economic returns made possible by reduced inputs and greater market access. While safe vegetable production is contributing to greater agroecosystem sustainability, further improvements are needed in some areas, specifically in the use of agrochemicals. There are encouraging signs in relation to pesticides, with some farmers reducing their pesticide use and moving towards less-toxic pesticides. Further movement towards sustainability could be fostered by a shift to the use of pesticides only as a last resort, a further shift from chemical to organic fertilizers, and improved capacity of farmers to experiment with and adapt safe vegetable production techniques.

Spatio-temporal systems with heterogeneity in their structure and behavior have two major problems. The first one is that such systems extend over very large spatial and temporal domains and consume a lot of resources to simulate that they are infeasible to study with current platforms. The second one is that the data available for understanding such systems is limited. This also makes it difficult to get the data for validation of their constituent processes while simultaneously considering their global behavior. For example, the valley fever fungus considered in this dissertation is spread over a large spatial grid in the arid Southwest and typically needs to be simulated over several decades of time to obtain useful information. It is also hard to get the temperature and moisture data at every grid point of the spatial domain over the region of study. In order to address the first problem, we develop a method based on the discrete event system specification which exploits the heterogeneity in the activity of the spatio-temporal system and which has been shown to be effective in solving relatively simple partial differential equation systems. The benefit of addressing the first problem is that it now makes it feasible to address the second problem.We address the second problem by making use of a multilevel methodology based on modeling and simulation and systems theory. This methodology helps us in the construction of models with different resolutions (base and lumped models). This allows us to refine an initially constructed lumped model with detailed physics-based process models and assess whether they improve on the original lumped models. For that assessment, we use the concept of experimental frame to delimit where the improvement is needed. This allows us to work with the available data, improve the component models in their own experimental frame and then move them to the overall frame. In this dissertation, we develop a multilevel methodology and apply it to a valley fever model. Moreover, we study the model's behavior in a particular experimental frame of interest, namely the formation of new sporing sites.

Seguint una concepció clàssica de la Intel•ligència Artificial (aquella que es posava com horitzó una definició dels mecanismes cognitius i la seva implementació en computadors), aquesta tesi s'endinsa en el problema de l'organització del coneixement. En especial, es posa atenció a la memòria semàntica i el coneixement lingüístic, intentant esbrinar de quina forma emergeixen les relacions semàntiques entre paraules. Per assolir aquests objectius es recorre a tres fonts principals: la utilització de dades empíriques provinents de la psicolingüística i la neuropsicologia; l'ús de la metodologia de sistemes complexes (física estadística) per la construcció de models i simulació de dinàmiques; i finalment l'aprofitament de les tecnologies al nostre abast tant per l'obtenció de noves dades (Internet) com una capacitat d'emmagatzemament suficient i velocitat de processament per al tractament de dades massives. D'aquest punt de vista arrelat en la Ciència Cognitiva en poden sorgir aplicacions fortament vinculades a problemes vigents en l'àmbit de Ciències de la Computació, com són l'extracció d'informació no supervisada, l'enriquiment de bases de dades i recursos lingüístics electrònics (Wikipedia, WordNet, etc.) i la millora de sistemes de consulta (query-based systems). Al Capítol 2 s'estableixen les bases metodològiques que han servit per construir la resta del treball. El Capítol 3 es dedica a aclarir (i) quina mena de dades s'han emprat (i s'empren) en l'estudi a gran escala del llenguatge i els fenòmens cognitius que l'envolten; i (ii) es revisen els treballs més destacables que s'han fet fins al moment actual al voltant del llenguatge i la cognició. Al Capítol 4 s'introdueix el Random Inheritance Model, que representa un intent per comprendre com emergeixen la similitud semàntica entre paraules i les categories semàntiques. Els resultats es comparen amb dades empíriques basades en les respostes de subjectes humans. Al Capítol 5 presentem un model de degradació semàntica que emula processos neurodegeneratius i prediu acuradament, a nivell qualitatiu, les observacions experimentals amb malalts d'Alzheimer que s'han fet en l'àmbit de la neuropsicologia. En aquests processos degeneratius convergeixen interessos multidisciplinars, que van de la mateixa cognició al fenomen de percolació en física estadística. El Capítol 6 queda finalment dedicat a una reflexió global d'aquesta memòria. / Following a classical conception of Artificial Intelligence (one that aims a definition of cognitive mechanisms and their implementation in computers), this thesis explores the problem of knowledge organization. In particular, it draws attention to the linguistic and semantic memory, trying to find out how semantic relations emerge between words. To achieve these objectives, we rely on three main sources: use of empirical data from psycholinguistics and neuropsychology; the use of complex systems (statistical physics) methodology to build and simulate dynamic models; and finally the utilization of technologies at our disposal both for obtaining new data (Internet) as well as sufficient storage capacity and processing speed for massive data manipulation. From this point of view, rooted in Cognitive Science, many applications may arise, some of them strongly linked to current problems in the field of Computer Science, such as unsupervised information extraction, enrichment of databases and language electronic resources (Wikipedia, WordNet, etc.). and improve consultation systems (query-based systems). In Chapter 2 the methodologies that have helped build the rest of the work are established. Chapter 3 is devoted to clarify (i) the kind of data that have been used in the large-scale study of language and cognitive phenomena around it, and (ii) review some of the major contributions to the date about language and cognition. In Chapter 4 the Random Inheritance Model is introduced, which represents an attempt to understand how does semantic similarity between words and semantic categories emerge. Results are compared with empirical data obtained from responses with human subjects. In Chapter 5 we present a model of semantic degradation which emulates neurodegenerative processes, and predicts experimental observations from Alzheimer's Disease patients in the field of neuropsychology. In the study of such degenerative processes different multidisciplinary interests converge, ranging from cognition itself to percolation theory in statistical physics. Chapter 6 is finally devoted to a global reflection of this memory.

This paper provides an overview on the evolutionary theory of the firm. The specific feature of the evolutionary approach is that it explains the adaptive behaviors of firms through the tension between innovation and selection. It is suggested that the evolutionary theory can provide a useful basis for a theory of the firm which is concerned with change over time and development. (author's abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisor: Mary F. Wheeler. Vita. Includes bibliographical references. Also available from UMI.

O presente trabalho explora como duas abordagens gerais da complexidade - ciências da complexidade e pensamento complexo - estão influenciando e podem vir a influenciar a gestão de sistemas organizacionais produtivos. Constata-se um aumento de publicações que relacionam a Complexidade à Gestão. Por meio de análise de conteúdo de trabalhos acadêmicos internacionais e nacionais identifica-se uma diminuição na ênfase inicial sobre teoria do caos e fractais e uma tendência recente na exploração da dinâmica de redes, ao mesmo tempo em que modelos baseados em agentes são cada vez mais explorados (associados à idéia de sistemas adaptativos complexos - SAC). Na produção nacional nota-se também a presença de idéias de cunho mais filosófico relacionadas à complexidade, notoriamente as do pensamento complexo do francês Edgar Morin. Com base na história do pensamento científico são identificados fundamentos do paradigma mecanicista dominante e fatores que estão contribuindo para transição de fase desse paradigma, relacionados ao aumento de complexidade na ciência e ao surgimento das ciências da complexidade. Estas ciências são caracterizadas como um processo evolutivo da Teoria Geral de Sistemas e possuem uma diversidade de contribuições em evolução, as quais têm sido utilizadas como referência para teorias e modelos de gestão de sistemas organizacionais produtivos. Explora-se a importância do desenvolvimento de um pensamento \'mais\' complexo e sua relação com a gestão. Apresenta-se uma discussão crítica sobre o uso de conceitos relacionados à complexidade, ressaltando-se que não existe um modelo de uma \'Teoria Geral da Complexidade\'. Avalia-se como esses conceitos são e podem vir a ser aplicados na Engenharia de Produção, por meio de: estudo de caso sobre o desenvolvimento e implementação de um sistema auto-organizado de solução de problemas em uma empresa de Agrobusiness; análise crítica, sob a ótica da complexidade, de trabalhos da área; e apresentação de propostas teóricas para aplicação do pensamento complexo. Conclui-se que as perspectivas da complexidade estão diretamente relacionadas a uma mudança de paradigma - na abrangência de um supra-paradigma, nos moldes de Kuhn - que passou do seu ponto de retorno, e que tais perspectivas afetarão cada vez mais a gestão de sistemas produtivos. / The present work explores how two general approaches of complexity - complexity sciences and complex thought - are influencing and may come to influence productive organizational systems management. An increase in publications relating Complexity to Management can be observed. By analyzing the content of international and Brazilian academic works, a decrease in the initial emphasis on the chaos theory and fractals is identified as well as a recent trend in the exploration of networks dynamics, at the same time at which models based on agents are more and more explored (associated to the idea of complex adaptative systems - CAS). In the Brazilian production, also noticed is the presence of ideas of a more philosophical characteristic related to complexity, notoriously those of complex thought by the French Edgar Morin. Based on the history of scientific thought, foundations of the dominant mechanicist paradigm are identified as well as factors that are contributing to this paradigm phase transition, concerning the increase in complexity in science and to the emergence of complexity sciences. These sciences are characterized as an evolutive process of the General Theory of Systems and count on a wide range of contributions in evolution, which have been used as a reference for theories and models of productive organizational systems management. The importance of the development of a \'more\' complex thought and its relationship with management are explored. A critical discussion is presented on the use of concepts related to complexity, pointing out that there is not a model for a \'General Theory of Complexity\'. How these concepts are and may come to be applied in Production Engineering is evaluated, by means of: case study on the development and implementation of a problem-solving self-organized system in an Agribusiness company; critical analysis, under the complexity view, of works in the area; and presentation of theoretical proposals for applying complex thought. It is concluded that the perspectives of complexity are directly related to a change in paradigm - in the comprehensiveness of a supra-paradigm, following Kuhn\'s models - which went beyond its turning point, and that these perspectives will more and more affect productive systems management.

Orientador: Marcus Aloízio Martinez de Aguiar / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-17T22:18:58Z (GMT). No. of bitstreams: 1 Hisi_AndreiaNaluSoares_D.pdf: 5934176 bytes, checksum: da28bbee37b83ef238c0e0210999475e (MD5) Previous issue date: 2011 / Resumo: Todos os organismos vivos interagem com indivíduos de sua e de outras espécies, formando uma rede complexa de interações que tem um papel importante na preservação da biodiversidade. Entender o comportamento subjacente e a estabilidade destes sistemas é de fundamental importância na conservação destes recursos. Neste trabalho estudamos uma rede com apenas quatro espécies, composta por dois pares predador-presa conectados, no qual o predador do primeiro par interage com presa do segundo par. A intensidade desta interação é um importante parâmetro do modelo. Exploramos o comportamento do sistema sob diferentes intensidades de acoplamento e estudamos a dinâmica de sobrevivência e extinção. Analisamos situações em que as quatro espécies têm uma população inicial inferior ao seu valor de equilíbrio, simulando situações de catástrofe em que estas abundâncias são reduzidas devido à ação humana ou mudanças ambientais. Este tipo de condição inicial faz que as populações oscilem antes de reequilibrarem, por vezes reduzindo seu valor para apenas uma pequena fração da população inicial, levando na prática à sua extinção. Nessas análises efeitos inesperados foram observados, como a sobrevivência da presa mais predada. A partir desse estudo, expandimos a rede de dois pares de predadores e presas para três, quatro e cinco pares, seguindo os mesmos conceitos de análise. Por fim, realizamos um breve estudo de uma rede de intera¸c¿oes pré-histórica, extinta no final do Pleistoceno / Abstract: All living organisms interact with individuals of its own species and also with those of other species, forming a complex network of interactions that have an important role in the preservation of the biodiversity. Understanding the underlying behavior and stability of these systems is of fundamental importance to the conservation of these resources. In this work we consider a network with only four species, comprising two predator-prey pairs connected, where the predator of the first pair interacts with the prey of the second pair. The intensity of this interaction is an important parameter of the model. We explore the system behavior under different intensities of coupling and study the dynamics of survival and extinction. We analyze situations in which the four species have initial populations smaller than the corresponding equilibrium values, simulating catastrophic events in which these abundances are reduced due to human action or environmental changes. This type of initial condition makes the populations oscillate before re-equilibrating, sometimes reducing its value to only a small fraction of the initial population, bringing them in practice to extinction. In these analysis we found unexpected effects, such as the survival of the prey that is most preyed. From this study, we expanded the network of two pairs of predators and preys to three, four and five pairs, following the same methods of analysis. Finally, we conducted a brief survey of a prehistoric network extinct in the late Pleistocene / Doutorado / Física Geral / Doutora em Ciências

La description et la compréhension d'un système passe souvent par la construction d'un modèle mathématique. Ce dernier constitue un point de vue particulier sur le système (structurel, dynamique, etc.). Constituer des modèle splus complets, c'est-à-dire multi-point-de-vue, atteint rapidement les limites des formalismes qui les supportent. Une solution alternative passe par le couplage de plusieurs modèles «simples». Dans le cas où chaque modèle correspond à un niveau de description du système, comme le niveau de la molécule, le niveau de la cellule, le niveau de l'organe, pour un système biologique, nous parlerons de modélisation multi-niveau. Ces niveaux sont organisés et interagissent. Nous pensons que la modélisation multi-niveau ouvre une voie prometteuse pour l'étude des systèmes complexes, traditionnellement durs à modéliser.Nous explorons trois voies pour la compréhension du fonctionnement de ces modèles en nous restreignant à la question de la relation entre global et local, c'est à dire entre l'individu et la population. La première voie est formelle et passe par la définition mathématique de «modèle» indépendamment du formalisme qui le supporte, par la présentation des différents types de modèles que l'on peut construire et par la définition explicite des relations qu'ils entretiennent.La seconde voie est portée par l'activité, définie dans le cadre de mgs, un langage de programmation spatiale, dont le modèle de calcul est fondé sur la réécriture des collections topologiques au moyen de transformations. Nous fournissons une méthode constructive pour l'obtention d'une description de plus haut niveau (une abstraction) des systèmes étudiés en déterminant automatiquement quelle est la sous-collection active sans la nécessité de faire référence à la sous-collection quiescente.La dernière voie est pratique, elle passe par la programmation de otb, un outil de simulation parallèle pour l'étude de la morphogénèse dans une population de bactéries ecoli. Pour otb, nous avons conçu un algorithme générique de calcul parallèle d'un automate cellulaire en deux dimensions, adapté aux cartesgraphiques grand public. Le modèle embarqué dans otb correspond au couplage de trois modèles correspondant chacun à un niveau de description du système: le modèle physique, qui décrit la dynamique des collisions entre bactéries, le modèle chimique, qui décrit la réaction et la diffusion des morphogènes, et le modèle de prise de décision, qui décrit l'interaction entre les bactéries et leur support / We often build mathematical models to describe and understand what a systemdoes.Each model gives a specific point of view on the system (structure, dynamics,etc.).Building more comprehensive models that encompass many different points of viewis limited by the formalism they are written in.Coupling “simple” models to form a bigger one is an alternative.If each model corresponds to a level of description of the system, e.g., themolecular level, the cellular level, the organ level in biology, then we callthis technique multi-level modelling.Levels of description are organized and interact with each other.We think that multi-level modelling is a promising technique to model complexsystems, which are known to be difficult to model.We have opened three distinct research tracks to investigate the link betweenlocal and global properties, for instance between those of an entity and itspopulation — a classical opposition in complex systems.On the first track, we give precise definitions of a model — independentlyof its underlying formalism, of a system and of some of the relations modelshave (validation, abstraction, composition).We also introduce different classes of models and show how they relate to someclassical definitions (dynamic models, spatial models, etc.)On the second track, we look at mgs, a spatial programming language based onthe rewriting of topological collections by means of transformation functions.We present a constructive method giving us access to a higher level ofdescription of the system (an abstraction). This method automatically computesthe active sub-collection of a model, without any knowledge about the quiescentsub-collection, and follows it for each time step.Finally, on the third track, we present otb, a parallel simulator for thestudy of morphogenesis in a population of ecoli bacteria. We provide a genericalgorithm for the parallel simulation of two-dimensional cellular automataon general-purpose graphics cards.otb itself is built around a multi-level model for the population of bacteria.This model is the result of the coupling of three “simple” (base) models: aphysical model, describing how bacteria collide, a chemical model, describinghow morphogenes react and diffuse, and a decision model, describing how bacteriaand their environment interact

There is a potential as well as a growing interest amongst researchers to utilise simulation in optimising maintenance systems. The state of the art in simulation-based optimisation of maintenance was established by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. In general, approaches to optimise maintenance varied significantly in the literature. Overall, these studies highlight the need for a framework that unifies the approach to optimising maintenance systems. Framework requirements were established through two main sources of published research. Surveys on maintenance simulation optimisation were examined to document comments on the approaches authors follow while optimising maintenance systems. In addition, advanced and future maintenance strategies were documented to ensure it can be accommodated in the proposed framework. The proposed framework was developed using a standard flowchart tool due to its familiarity and ability to depict decision structures clearly. It provides a systematic methodology that details the steps required to connect the simulation model to an optimisation engine. Not only it provides guidance in terms of formulating the optimal problem for the maintenance system at hand but it also provides support and assistance in defining the optimisation scope and investigating applicable maintenance strategies. Additionally, it considers current issues relating to maintenance systems both in research and in practice such as uncertainty, complexity and multi-objective optimisation. The proposed framework cannot be applied using existing approaches for modelling maintenance. Existing modelling approaches using simulation have a number of limitations: The maintenance system is modelled separately from other inter-related systems such as production and spare parts logistics. In addition, these approaches are used to model one maintenance strategy only. A novel approach for modelling maintenance using Discrete Event Simulation is proposed. The proposed approach enables the modelling of interactions amongst various maintenance strategies and their effects on the assets in non-identical multi-unit systems. Using the proposed framework and modelling approach, simulation-based optimisation was conducted on an academic case and two industrial cases that are varied in terms of sector, size, number of manufacturing processes and level of maintenance documentation. Following the structured framework enabled discussing and selecting the suitable optimisation scope and applicable maintenance strategies as well as formulating a customised optimal problem for each case. The results of the study suggest that over-looking the optimisation of maintenance strategies may lead to sub-optimal solutions. In addition, this research provides insights for non-conflicting objectives in maintenance systems.