911 resultados para Technicolor and Composite Models


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This research focused on operation of a manpower pool within a service business unit in Company X and aimed to identify how the operation should be improved in order to get most out of it concerning the future prospects of the service business unit. This was done by analyzing the current state of the manpower pool related operations in means of project business, project management and business models. The objective was to deepen the understanding and to highlight possible areas of improvement. The research was conducted as a qualitative single-case study utilizing also an action research method; the research approach was a combination of conceptual, action-oriented and constructive approaches. The primary data was collected with executing a comprehensive literature review and semi-structured theme interviews. The main results described how the manpower pool operates as part of the service business unit in project business by participating in different types of delivery projects; process flows for the project types were mapped. Project management was analyzed especially from the resource management point of view, and an Excel-based skills analysis model was constructed for this purpose. Utilization of operational business models was also studied to define strategic direction for development activities. The results were benchmarked against two competitors in order to specify lessons to be learnt from their use of operational business models.

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The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

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In this doctoral thesis, a power conversion unit for a 10 kWsolid oxide fuel cell is modeled, and a suitable control system is designed. The need for research was identified based on an observation that there was no information available about the characteristics of the solid oxide fuel cell from the perspective of power electronics and the control system, and suitable control methods had not previously been studied in the literature. In addition, because of the digital implementation of the control system, the inherent characteristics of the digital system had to be taken into account in the characteristics of the solid oxide fuel cell (SOFC). The characteristics of the solid oxide fuel cell as well the methods for the modeling and control of the DC/DC converter and the grid converter are studied by a literature survey. Based on the survey, the characteristics of the SOFC as an electrical power source are identified, and a solution to the interfacing of the SOFC in distributed generation is proposed. A mathematical model of the power conversion unit is provided, and the control design for the DC/DC converter and the grid converter is made based on the proposed interfacing solution. The limit cycling phenomenon is identified as a source of low-frequency current ripple, which is found to be insignificant when connected to a grid-tied converter. A method to mitigate a second harmonic originating from the grid interface is proposed, and practical considerations of the operation with the solid oxide fuel cell plant are presented. At the theoretical level, the thesis discusses and summarizes the methods to successfully derive a model for a DC/DC converter, a grid converter, and a power conversion unit. The results of this doctoral thesis can also be used in other applications, and the models and methods can be adopted to similar applications such as photovoltaic systems. When comparing the results with the objectives of the doctoral thesis, we may conclude that the objectives set for the work are met. In this doctoral thesis, theoretical and practical guidelines are presented for the successful control design to connect a SOFC-based distributed generation plant to the utility grid.

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State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

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The significance of services as business and human activities has increased dramatically throughout the world in the last three decades. Becoming a more and more competitive and efficient service provider while still being able to provide unique value opportunities for customers requires new knowledge and ideas. Part of this knowledge is created and utilized in daily activities in every service organization, but not all of it, and therefore an emerging phenomenon in the service context is information awareness. Terms like big data and Internet of things are not only modern buzz-words but they are also describing urgent requirements for a new type of competences and solutions. When the amount of information increases and the systems processing information become more efficient and intelligent, it is the human understanding and objectives that may get separated from the automated processes and technological innovations. This is an important challenge and the core driver for this dissertation: What kind of information is created, possessed and utilized in the service context, and even more importantly, what information exists but is not acknowledged or used? In this dissertation the focus is on the relationship between service design and service operations. Reframing this relationship refers to viewing the service system from the architectural perspective. The selected perspective allows analysing the relationship between design activities and operational activities as an information system while maintaining the tight connection to existing service research contributions and approaches. This type of an innovative approach is supported by research methodology that relies on design science theory. The methodological process supports the construction of a new design artifact based on existing theoretical knowledge, creation of new innovations and testing the design artifact components in real service contexts. The relationship between design and operations is analysed in the health care and social care service systems. The existing contributions in service research tend to abstract services and service systems as value creation, working or interactive systems. This dissertation adds an important information processing system perspective to the research. The main contribution focuses on the following argument: Only part of the service information system is automated and computerized, whereas a significant part of information processing is embedded in human activities, communication and ad-hoc reactions. The results indicate that the relationship between service design and service operations is more complex and dynamic than the existing scientific and managerial models tend to view it. Both activities create, utilize, mix and share information, making service information management a necessary but relatively unknown managerial task. On the architectural level, service system -specific elements seem to disappear, but access to more general information elements and processes can be found. While this dissertation focuses on conceptual-level design artifact construction, the results provide also very practical implications for service providers. Personal, visual and hidden activities of service, and more importantly all changes that take place in any service system have also an information dimension. Making this information dimension visual and prioritizing the processed information based on service dimensions is likely to provide new opportunities to increase activities and provide a new type of service potential for customers.

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Third party logistics, and third party logistics providers and the services they offer have grown substantially in the last twenty years. Even though there has been extensive research on third party logistics providers, and regular industry reviews within the logistics industry, a closer research in the area of partner selection and network models in the third party logistics industry is missing. The perspective taken in this study was of expanding the network research into logistics service providers as the focal firm in the network. The purpose of the study is to analyze partnerships and networks in the third party logistics industry in order to define how networks are utilized in third party logistics markets, what have been the reasons for the partnerships, and whether there are benefits for the third party logistics provider that can be achieved through building networks and partnerships. The theoretical framework of this study was formed based on common theories in studying networks and partnerships in accordance with models of horizontal and vertical partnerships. The theories applied to the framework and context of this study included the strategic network view and the resource-based view. Applying these two network theories to the position and networks of third party logistics providers in an industrial supply chain, a theoretical model for analyzing the horizontal and vertical partnerships where the TPL provider is in focus was structured. The empirical analysis of TPL partnerships consisted of a qualitative document analysis of 33 partnership examples involving companies present in the Finnish TPL markets. For the research, existing documents providing secondary data on types of partnerships, reasons for the partnerships, and outcomes of the partnerships were searched from available online sources. Findings of the study revealed that third party logistics providers are evident in horizontal and vertical interactions varying in geographical coverage and the depth and nature of the relationship. Partnership decisions were found to be made on resource based reasons, as well as from strategic aspects. The discovered results of the partnerships in this study included cost reduction and effectiveness in the partnerships for improving existing services. In addition in partnerships created for innovative service extension, differentiation, and creation of additional value were discovered to have emerged as results of the cooperation. It can be concluded that benefits and competitive advantage can be created through building partnerships in order to expand service offering and seeking synergies.

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The Guayana Shield, located in north-eastern South America, consists of a highly complex and composite mosaic of landscape elements. Amongst these, inselbergs are very conspicuous, because of their peculiar shape and their unusual associated vegetation. Geologically, these rock outcrops are part of the underlying ancient igneous-metamorphic basement and occur mainly in the lowlands of the periphery of the shield. As azonal habitats, inselbergs harbour a highly specialized flora. The characteristic vegetation is composed of lithophytic and savanna-like plant communities, as well as low dry forests. As a whole, the vegetation of an inselberg may be interpreted as a mosaic of marginal habitats. Therefore a large number of taxa find suitable niches in a quite condensed space. Gradients of soil depth and water availability are the main factors determining the floristic composition. A preliminary floristic inventory of the Venezuelan inselberg flora comprises 614 vascular plant species. 24% of them are endemic to the Guayana region, 15% are endemic to inselbergs of the Guayana region. The distribution patterns of these latter, eco-endemic species allows to distinguish a northern and a southern inselberg district. The two districts overlap in the Átures area, in the surroundings of Puerto Ayacucho, where a true centre of endemism is located. The distinction into two districts is emphasised by different phytogeographic relations. The southern inselberg district shows connections to the "tepui" flora, whereas the northern district reveals phytogeographic relations to the Caribbean region as well as to the Brazilian Shield. Possible explanations for the floristic interchange across the equator are discussed.

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1. Fish oils are rich in the long-chain n-3 polyunsaturated fatty acids (PUFAs), eicosapentaenoic (20:5n-3) and docosahexaenoic (22:6n-3) acids. Linseed oil and green plant tissues are rich in the precursor fatty acid, a-linolenic acid (18:3n-3). Most vegetable oils are rich in the n-6 PUFA linoleic acid (18:2n-6), the precursor of arachidonic acid (20:4n-6). 2. Arachidonic acid-derived eicosanoids such as prostaglandin E2 are pro-inflammatory and regulate the functions of cells of the immune system. Consumption of fish oils leads to replacement of arachidonic acid in cell membranes by eicosapentaenoic acid. This changes the amount and alters the balance of eicosanoids produced. 3. Consumption of fish oils diminishes lymphocyte proliferation, T-cell-mediated cytotoxicity, natural killer cell activity, macrophage-mediated cytotoxicity, monocyte and neutrophil chemotaxis, major histocompatibility class II expression and antigen presentation, production of pro-inflammatory cytokines (interleukins 1 and 6, tumour necrosis factor) and adhesion molecule expression. 4. Feeding laboratory animals fish oil reduces acute and chronic inflammatory responses, improves survival to endotoxin and in models of autoimmunity and prolongs the survival of grafted organs. 5. Feeding fish oil reduces cell-mediated immune responses. 6. Fish oil supplementation may be clinically useful in acute and chronic inflammatory conditions and following transplantation. 7. n-3 PUFAs may exert their effects by modulating signal transduction and/or gene expression within inflammatory and immune cells.

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This thesis studies how the case company could digitalize its supply chain and what kind of advantages this would create in the light of supply chain efficiency. The case company manufactures several pulp products that are used for paper, fabrics and packaging products by customers worldwide. The paper and pulp industry has been paying more and more attention to increasing supply chain efficiency with new operating and service models made possible by today’s information technology. The main focus of this study is on the supply chain between the case company and its key customers and the goal is to find ways to make the operations between them as efficient as possible. The study relays heavily on collaboration techniques and digitalization technologies. In addition to a theoretical framework, the study includes several empirical studies that offer real-life examples of how these theories and technologies are applied in operating environments similar to the case company. A plan with strategic and operational levels is created according to the findings of the previous sections to support the case company’s future operations. The plan is based on an RFID-supported collaboration model that aims to advance information sharing between the supply chain partners. The time for an RFID-investment is sought to be very optimal and the benefits of such system to be noteworthy, but challenging to measure in monetary terms.

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Cardiopulmonary reflexes are activated via changes in cardiac filling pressure (volume-sensitive reflex) and chemical stimulation (chemosensitive reflex). The sensitivity of the cardiopulmonary reflexes to these stimuli is impaired in the spontaneously hypertensive rat (SHR) and other models of hypertension and is thought to be associated with cardiac hypertrophy. The present study investigated whether the sensitivity of the cardiopulmonary reflexes in SHR is restored when cardiac hypertrophy and hypertension are reduced by enalapril treatment. Untreated SHR and WKY rats were fed a normal diet. Another groups of rats were treated with enalapril (10 mg kg-1 day-1, mixed in the diet; SHRE or WKYE) for one month. After treatment, the volume-sensitive reflex was evaluated in each group by determining the decrease in magnitude of the efferent renal sympathetic nerve activity (RSNA) produced by acute isotonic saline volume expansion. Chemoreflex sensitivity was evaluated by examining the bradycardia response elicited by phenyldiguanide administration. Cardiac hypertrophy was determined from the left ventricular/body weight (LV/BW) ratio. Volume expansion produced an attenuated renal sympathoinhibitory response in SHR as compared to WKY rats. As compared to the levels observed in normotensive WKY rats, however, enalapril treatment restored the volume expansion-induced decrease in RSNA in SHRE. SHR with established hypertension had a higher LV/BW ratio (45%) as compared to normotensive WKY rats. With enalapril treatment, the LV/BW ratio was reduced to 19% in SHRE. Finally, the reflex-induced bradycardia response produced by phenyldiguanide was significantly attenuated in SHR compared to WKY rats. Unlike the effects on the volume reflex, the sensitivity of the cardiac chemosensitive reflex to phenyldiguanide was not restored by enalapril treatment in SHRE. Taken together, these results indicate that the impairment of the volume-sensitive, but not the chemosensitive, reflex can be restored by treatment of SHR with enalapril. It is possible that by augmenting the gain of the volume-sensitive reflex control of RSNA, enalapril contributed to the reversal of cardiac hypertrophy and normalization of arterial blood pressure in SHR.

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This article is a transcription of an electronic symposium sponsored by the Brazilian Society of Neuroscience and Behavior (SBNeC). Invited researchers from the European Union, North America and Brazil discussed two issues on anxiety, namely whether panic is a very intense anxiety or something else, and what aspects of clinical anxiety are reproduced by animal models. Concerning the first issue, most participants agreed that generalized anxiety and panic disorder are different on the basis of clinical manifestations, drug response and animal models. Also, underlying brain structures, neurotransmitter modulation and hormonal changes seem to involve important differences. It is also common knowledge that existing animal models generate different types of fear/anxiety. A challenge for future research is to establish a good correlation between animal models and nosological classification.

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Meandering rivers have been perceived to evolve rather similarly around the world independently of the location or size of the river. Despite the many consistent processes and characteristics they have also been noted to show complex and unique sets of fluviomorphological processes in which local factors play important role. These complex interactions of flow and morphology affect notably the development of the river. Comprehensive and fundamental field, flume and theoretically based studies of fluviomorphological processes in meandering rivers have been carried out especially during the latter part of the 20th century. However, as these studies have been carried out with traditional field measurements techniques their spatial and temporal resolution is not competitive to the level achievable today. The hypothesis of this study is that, by exploiting e increased spatial and temporal resolution of the data, achieved by combining conventional field measurements with a range of modern technologies, will provide new insights to the spatial patterns of the flow-sediment interaction in meandering streams, which have perceived to show notable variation in space and time. This thesis shows how the modern technologies can be combined to derive very high spatial and temporal resolution data on fluvio-morphological processes over meander bends. The flow structure over the bends is recorded in situ using acoustic Doppler current profiler (ADCP) and the spatial and temporal resolution of the flow data is enhanced using 2D and 3D CFD over various meander bends. The CFD are also exploited to simulate sediment transport. Multi-temporal terrestrial laser scanning (TLS), mobile laser scanning (MLS) and echo sounding data are used to measure the flow-based changes and formations over meander bends and to build the computational models. The spatial patterns of erosion and deposition over meander bends are analysed relative to the measured and modelled flow field and sediment transport. The results are compared with the classic theories of the processes in meander bends. Mainly, the results of this study follow well the existing theories and results of previous studies. However, some new insights regarding to the spatial and temporal patterns of the flow-sediment interaction in a natural sand-bed meander bend are provided. The results of this study show the advantages of the rapid and detailed measurements techniques and the achieved spatial and temporal resolution provided by CFD, unachievable with field measurements. The thesis also discusses the limitations which remain in the measurement and modelling methods and in understanding of fluvial geomorphology of meander bends. Further, the hydro- and morphodynamic models’ sensitivity to user-defined parameters is tested, and the modelling results are assessed against detailed field measurement. The study is implemented in the meandering sub-Arctic Pulmanki River in Finland. The river is unregulated and sand-bed and major morphological changes occur annually on the meander point bars, which are inundated only during the snow-melt-induced spring floods. The outcome of this study applies to sandbed meandering rivers in regions where normally one significant flood event occurs annually, such as Arctic areas with snow-melt induced spring floods, and where the point bars of the meander bends are inundated only during the flood events.

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Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

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Leishmaniasis is a disease caused by protozoa of the genus Leishmania, and visceral leishmaniasis is a form in which the inner organs are affected. Since knowledge about immunity in experimental visceral leishmaniasis is poor, we present here a review on immunity and immunosuppression in experimental visceral leishmaniasis in mouse and hamster models. We show the complexity of the mechanisms involved and differences when compared with the cutaneous form of leishmaniasis. Resistance in visceral leishmaniasis involves both CD4+ and CD8+ T cells, and interleukin (IL)-2, interferon (IFN)- gamma, and IL-12, the latter in a mechanism independent of IFN- gamma and linked to transforming growth factor (TGF)-ß production. Susceptibility involves IL-10 but not IL-4, and B cells. In immune animals, upon re-infection, the elements involved in resistance are different, i.e., CD8+ T cells and IL-2. Since one of the immunopathological consequences of active visceral leishmaniasis in humans is suppression of T-cell responses, many studies have been conducted using experimental models. Immunosuppression is mainly Leishmania antigen specific, and T cells, Th2 cells and adherent antigen-presenting cells have been shown to be involved. Interactions of the co-stimulatory molecule family B7-CTLA-4 leading to increased level of TGF-ß as well as apoptosis of CD4+ T cells and inhibition of macrophage apoptosis by Leishmania infection are other components participating in immunosuppression. A better understanding of this complex immune response and the mechanisms of immunosuppression in experimental visceral leishmaniasis will contribute to the study of human disease and to vaccine development.

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The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.