991 resultados para network mapping


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Value network has been studied greatly in the academic research, but a tool for value network mapping is missing. The objective of this study was to design a tool (process) for value network mapping in cross-sector collaboration. Furthermore, the study addressed a future perspective of collaboration, aiming to map the value network potential. During the study was investigated and pondered how to get the full potential of collaboration, by creating new value in collaboration process. These actions are parts of mapping process proposed in the study. The implementation and testing of the mapping process were realized through a case study of cross-sector collaboration in welfare services for elderly in the Eastern Finland. Key representatives in elderly care from public, private and third sectors were interviewed and a workshop with experts from every sector was also conducted in this regard. The value network mapping process designed in this study consists of specific steps that help managers and experts to understand how to get a complex value network map and how to enhance it. Furthermore, it make easier the understanding of how new value can be created in collaboration process. The map can be used in order to motivate participants to be engaged with responsibility in collaboration and to be fully committed in their interactions. It can be also used as a motivator tool for those organizations that intend to engage in collaboration process. Additionally, value network map is a starting point in many value network analyses. Furthermore, the enhanced value network map can be used as a performance measurement tool in cross-sector collaboration.

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A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

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Network virtualization is a promising technique for building the Internet of the future since it enables the low cost introduction of new features into network elements. An open issue in such virtualization is how to effect an efficient mapping of virtual network elements onto those of the existing physical network, also called the substrate network. Mapping is an NP-hard problem and existing solutions ignore various real network characteristics in order to solve the problem in a reasonable time frame. This paper introduces new algorithms to solve this problem based on 0–1 integer linear programming, algorithms based on a whole new set of network parameters not taken into account by previous proposals. Approximative algorithms proposed here allow the mapping of virtual networks on large network substrates. Simulation experiments give evidence of the efficiency of the proposed algorithms.

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The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

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A tese tem como objectivo principal a criação de um modelo equivalente eléctrico da rede de nervuras de algumas folhas vegetais e analisar o seu comportamento a estímulos eléctricos, analisando-se também a respectiva resposta em frequência. A motivação desta tese passa pela observação dos sistemas existentes na natureza. Neste caso, as folhas vegetais e analisar se são sistemas de ordem fraccionária ou não. Para a sua elaboração, fez-se uma breve abordagem à estrutura das plantas, sob o ponto de vista da botânica e elaborou-se um método de fotografia das amostras, mapeamento da rede de nervuras e medição dos segmentos que compõem essa mesma rede. A tese termina com um capítulo de resultados experimentais.

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Tutkimus kartoitetaan tulevaisuuden älykotiliiketoiminnan palvelutuottaja-verkostoa. Lisäksi delphi-prosessia seuraten, pyritään kyselyn kautta vali-doimaan tulevaisuudesta tehty skenaario. Kysely tehtiin 42 yrityksen stra-tegiasta vastaavalle johtajalle. Selvitettäviä asioita olivat skenaarion liike-toiminnallinen kiinnostavuus, toteutumiskelpoisuus ja yrityksen siinä ha-luama rooli. Lisäksi selvitettiin mm. yritysten yhteistyökyvykkyyttä, innova-tiivisuutta, asiakassuuntautuneisuutta ja teknologinen valmiutta. Pääpaino oli selvittää verkoston muodostaja eli johtaja yritys. Kysely validoi kaikkien vastanneiden osalta tulevan skenaarion. Tulosten perusteella pystyttiin erottamaan 12 potentiaalista johtajaa. Nämä erottui-vat kyselyn kaikilla osa-alueilla parempina kuin muut yritykset. Potentiaali-set johtajat näkivät tulevaisuuden optimistisempana kuin muut ja lisäksi ne harjoittavat jo nyt liiketoimintaa, joka on lähellä kuvattua älykotipalveluver-kostoa. Tuloksia voidaan hyödyntää muodostettaessa palveluverkostoa uusille markkinoille. Kuvatun mallin toteutuminen vaatii kuitenkin julkisen sektorin palvelutoiminnan uudistusta, sillä se sisältää useita rinnakkaisia prosesseja julkisen terveydenhuollon kanssa.

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Cross-sector collaboration and partnerships have become an emerging and desired strategy in addressing huge social and environmental challenges. Despite its popularity, cross-sector collaboration management has proven to be very challenging. Even though cross-sector collaboration and partnership management have been widely studied and discussed in recent years, their effectiveness as well as their ability to create value with respect to the problems they address has remained very challenging. There is little or no evidence of their ability to create value. Regarding all these challenges, this study aims to explore how to manage cross-sector collaborations and partnerships to be able to improve their effectiveness and to create more value for all partners involved in collaboration as well as for customers. The thesis is divided into two parts. The first part comprises an overview of relevant literature (including strategic management, value networks and value creation theories), followed by presenting the results of the whole thesis and the contribution made by the study. The second part consists of six research publications, including both quantitative and qualitative studies. The chosen research strategy is triangulation, as the study includes four types of triangulation: (1) theoretical triangulation, (2) methodological triangulation, (3) data triangulation and (4) researcher triangulation. Two publications represent conceptual development, which are based on secondary data research. One publication is a quantitative study, carried out through a survey. The other three publications represent qualitative studies, based on case studies, where data was collected through interviews and workshops, with participation of managers from all three sectors: public, private and the third (nonprofit). The study consolidates the field of “strategic management of value networks,” which is proposed to be applied in the context of cross-sector collaboration and partnerships, with the aim of increasing their effectiveness and the process of value creation. Furthermore, the study proposes a first definition for the strategic management of value networks. The study also proposes and develops two strategy tools that are recommended to be used for the strategic management of value networks in cross-sector collaboration and partnerships. Taking a step forward, the study implements the strategy tools in practice, aiming to show and to demonstrate how new value can be created by using the developed strategy tools for the strategic management of value networks. This study makes four main contributions. (1) First, it brings a theoretical contribution by providing new insights and consolidating the field of strategic management of value networks, also proposing a first definition for the strategic management of value networks. (2) Second, the study makes a methodical contribution by proposing and developing two strategy tools for value networks of cross-sector collaboration: (a) value network mapping, a method that allows us to assess the current and the potential value network and (b) the Value Network Scorecard, a method of performance measurement and performance prediction in cross-sector collaboration. (3) Third, the study has managerial implications, offering new solutions and empirical evidence on how to increase the effectiveness of cross-sector collaboration and also allow managers to understand how new value can be created in cross-sector partnerships and how to get the full potential of collaboration. (4) And fourth, the study also has practical implications, allowing managers to understand how to use in practice the strategy tools developed in this study, providing discussions on the limitations regarding the proposed tools as well as general limitations involved in the study.

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Organizations have been facing several challenges to survive in a world in constant transformation. In light of that, new management models need to be incorporated to the organizational dynamics in order to achieve competitive advantages. The inter-firm networks establish a particular form means of cooperation as a fundamental element, as there can be ties of diverse nature to justify the relationships. These are interorganizations or inter-firms, formed by people who maintain the relationships to improve the overall performance of the network and of the participants. Thus, the Education Institutions, considered as organizations, which have the objective to disseminate knowledge and form professionals who contribute to the growth of a nation, also make use of this type of arrangement. Considering the raised questions, this article aims to demonstrate the applicability of a business network mapping technique at Higher Education Institutions. It also presents the possibility to perform the comparative analysis of the intensity of the relationship observed in a private and in a public institution, in the State of São Paulo. By applying the comparative analysis, this study also presents the relationship among the people involved at strategic and tactical levels of each institution, taking into account each one s peculiarities.

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Chronic stress is associated with hippocampal atrophy and cognitive dysfunction. This study investigates how long-lasting administration of corticosterone as a mimic of experimentally induced stress affects psychometric performance and the expression of the phosphatidylethanolamine binding protein (PEBP1) in the adult hippocampus of one-year-old male rats. Psychometric investigations were conducted in rats before and after corticosterone treatment using a holeboard test system. Rats were randomly attributed to 2 groups (n = 7) for daily subcutaneous injection of either 26.8 mg/kg body weight corticosterone or sesame oil (vehicle control). Treatment was continued for 60 days, followed by cognitive retesting in the holeboard system. For protein analysis, the hippocampal proteome was separated by 2D electrophoresis (2DE) followed by image processing, statistical analysis, protein identification via peptide mass fingerprinting and gel matching and subsequent functional network mapping and molecular pathway analysis. Differential expression of PEBP1 was additionally quantified by Western blot analysis. Results show that chronic corticosterone significantly decreased rat hippocampal PEBP1 expression and induced a working and reference memory dysfunction. From this, we derive the preliminary hypothesis that PEBP1 may be a novel molecular mediator influencing cognitive integrity during chronic corticosterone exposure in rat hippocampus.

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The performance of feed-forward neural networks in real applications can be often be improved significantly if use is made of a-priori information. For interpolation problems this prior knowledge frequently includes smoothness requirements on the network mapping, and can be imposed by the addition to the error function of suitable regularization terms. The new error function, however, now depends on the derivatives of the network mapping, and so the standard back-propagation algorithm cannot be applied. In this paper, we derive a computationally efficient learning algorithm, for a feed-forward network of arbitrary topology, which can be used to minimize the new error function. Networks having a single hidden layer, for which the learning algorithm simplifies, are treated as a special case.

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It is well known that the addition of noise to the input data of a neural network during training can, in some circumstances, lead to significant improvements in generalization performance. Previous work has shown that such training with noise is equivalent to a form of regularization in which an extra term is added to the error function. However, the regularization term, which involves second derivatives of the error function, is not bounded below, and so can lead to difficulties if used directly in a learning algorithm based on error minimization. In this paper we show that, for the purposes of network training, the regularization term can be reduced to a positive definite form which involves only first derivatives of the network mapping. For a sum-of-squares error function, the regularization term belongs to the class of generalized Tikhonov regularizers. Direct minimization of the regularized error function provides a practical alternative to training with noise.

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Design is being performed on an ever-increasing spectrum of complex practices arising in response to emerging markets and technologies, co-design, digital interaction, service design and cultures of innovation. This emerging notion of design has led to an expansive array of collaborative and facilitation skills to demonstrate and share how such methods can shape innovation. The meaning of these design things in practice can't be taken for granted as matters of fact, which raises a key challenge for design to represent its role through the contradictory nature of matters of concern. This paper explores an innovative, object-oriented approach within the field of design research, visually combining an actor-network theory framework with situational analysis, to report on the role of design for fledgling companies in Scotland, established and funded through the knowledge exchange hub Design in Action (DiA). Key findings and visual maps are presented from reflective discussions with actors from a selection of the businesses within DiA's portfolio. The suggestion is that any notions of strategic value, of engendering meaningful change, of sharing the vision of design, through design things, should be grounded in the reflexive interpretations of matters of concern that emerge.

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Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic "discipline". In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this "community of practice". Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the "who's following who?" graph allows us to highlight the structure of the network's relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.

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Webben är en enorm källa för information. Innehållet på webbsidorna är en synlig typ av information, men webben innehåller även information av en annan typ, en mera gömd typ i form av sambanden och nätverken som hyperlänkarna skapar mellan webbsajterna och –sidorna som de kopplar ihop. Forskningsområdet webometri ämnar, bland annat, att skapa ny kunskap ur denna gömda information som finns inbyggt i hyperlänkarna samt att skapa förståelse för hurudana fenomen och förhållanden utanför webben kan finnas representerade i hyperlänkarna. Målet med denna forskning var att öka förståelse för användningen av hyperlänkar på webben och speciellt kommunernas användning av hyperlänkar. Denna forskning undersökte hur kommunerna i Egentliga Finland skapade och mottog hyperlänkar samt hurudana nätverk formades av dessa hyperlänkar. Forskningen kartlade nätverk av direkta länkar mellan kommunerna och av samlänkar till och från kommunerna och undersökte ifall dessa nätverk kunde användas för att undersöka geopolitiska förhållanden och samarbete mellan kommunerna i Egentliga Finland. De övergripande forskningsfrågorna som har besvarats i denna forskning är: 1) Från ett webometriskt perspektiv, hur använder kommunerna i Egentliga Finland webben? 2) Kan hyperlänkar (direkta länkar och samlänkar) användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommuner? 3) Vilka är de viktigaste motiveringarna för att skapa länkar mellan, till och från kommunernas webbsajter? Denna forskning kom till ovanligt tydliga resultat för en webometrisk forskning, både när det gäller upptäckta geografiska faktorer som påverkar hyperlänkningarna och de klassificerade motivationerna för att skapa länkarna. Resultaten visade att de direkta hyperlänkarna mellan kommunerna kan användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommunerna för att de direkta länkarna var motiverade av officiella orsaker och de var klart påverkade av distansen mellan kommunerna och av de ekonomiska regionerna. Samlänkningarna in till kommunerna visade sig fungera som ett mått för geografisk likhet mellan kommunerna, medan samlänkningarna ut från kommunerna visade potential för att kunna användas till för att kartlägga kommunernas gemensamma intressen. Forskningen kontribuerade även till utvecklandet av forskningsområdet webometri. En del av de viktigaste kontributionerna av denna forskning var utvecklandet av nya metoder för webometrisk forskning samt att öka kunskap om hur existerande metoder från nätverksanalys kan användas effektivt för webometrisk forskning. Resultaten från denna forskning och de utvecklade metoderna kan användas för snabba kartläggningar av diverse förhållanden mellan olika organisationer och företag genom att använda information gratis tillgängligt på webben.

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Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.