948 resultados para BAYESIAN NETWORK
Resumo:
We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 inverse fb. We select events consistent with a signature of a single charged lepton, missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to $150 GeV/c^2, respectively.
Resumo:
The role of oxide surface chemical composition and solvent on ion solvation and ion transport of ``soggy sand'' electrolytes are discussed here. A ``soggy sand'' electrolyte system comprising dispersions of hydrophilic/hydrophobic functionalized aerosil silica in lithium perchlorate methoxy polyethylene glycol solution was employed for the study. Static and dynamic rheology measurements show formation of an attractive particle network in the case of the composite with unmodified aerosil silica (i.e., with surface silanol groups) as well as composites with hydrophobic alkane groups. While particle network in the composite with hydrophilic aerosil silica (unmodified) were due to hydrogen bonding, hydrophobic aerosil silica particles were held together via van der Waals forces. The network strength in the latter case (i.e., for hydrophobic composites) were weaker compared with the composite with unmodified aerosil silica. Both unmodified silica as well as hydrophobic silica composites displayed solid-like mechanical strength. No enhancement in ionic conductivity compared to the liquid electrolyte was observed in the case of the unmodified silica. This was attributed to the existence of a very strong particle network, which led to the ``expulsion'' of all conducting entities from the interfacial region between adjacent particles. The ionic conductivity for composites with hydrophobic aerosil particles displayed ionic conductivity dependent on the size of the hydrophobic chemical moiety. No spanning attractive particle network was observed for aerosil particles with surfaces modified with stronger hydrophilic groups (than silanol). The composite resembled a sol, and no percolation in ionic conductivity was observed.
Resumo:
Most of the existing research within the business network approach is based on companies that are operating on different levels within the same value chain, as a buyer and a supplier. Intercompetitor cooperation, i.e. cooperation between companies occupying the same level within different value chains, has not been studied to the same extent. Moreover scholars within the business network approach have usually described industrial relationships as long term, consisting of mutual commitment and trust. Industrial relationships are not static, but dynamic, and they contain situations of both harmony and conflict. There is consequently a need for more research both concerning intercompetitor cooperation and conflicts. The purpose of this study is to develop our theoretical and empirical understanding of the nature of conflicts in intercompetitor cooperation from a business network perspective. The focus of the study lies on issue and intensity of conflict. The issue of a conflict can be divided into cause and topic, while the intensity comprises the importance and outcome of a conflict. The empirical part of the study is based on two case studies of groups of cooperating competitors from two different industries. The applied research method is interviews. According to the findings of this study causes of conflicts in intercompetitor cooperation can be divided into three groups: focus, awareness and capacity. Topics of conflict can be related to domain, delivery, advertising or cooperation. Moreover the findings show that conflict situations may be grouped into not important, important or very important. Some conflicts may also be of varying importance, meaning that the importance varies from one point of time to another. Based on the findings of the study the outcome or status of a conflict can be analyzed both on a concrete and general level. The findings also indicate that several conflicts are partly hidden, which means that only one or some of the involved actors perceive the conflict. Furthermore several conflict situations can be related to external network actors.
Resumo:
In today’s business one can say that competition does not take place inside the network, but between networks. Change and dynamics are central issues in network studies, and a company, due its changing environment, can identify opportunities and threats and respond to them accordingly. These opportunities are vital, but also complex and demanding for the management. Earlier research has identified a shortcoming in explanations of how the micro-level interactions to macro-level patterns are connected. The IMP-group has been trying to fill this research gap with research on interactions within business networks. In this area of research lies the focus of research on relationships between organizations. Adaptation in cooperation is a central concept within business network research. Adaptation has been dealt with in previous literature, but the focus of the studies has mainly been outside this phenomenon, and it has mostly had a supporting role. Most literature has also described the buyers' point of view in studied supply networks, whereas much less attention has been paid to the suppliers' view on them. This study focuses on this research gap. The results of the study stress that adaptation should be included to a greater extent in the strategy work of companies. The adaptations should be carefully planned and, as far as possible, made consciously. Conscious, well-planned adaptations can be seen as investments into present and future relationships, and resources should be invested into something that does not increase the company’s dependence, but divides the power in the relationship between the companies. Adaptations should be planned so that they result in a more offensive way of responding to the demands that are placed upon the companies. In this way, the actions can be viewed and analyzed in accordance with whether the actions make the company weaker or stronger.
Resumo:
Despite thirty years of research in interorganizational networks and project business within the industrial networks approach and relationship marketing, collective capability of networks of business and other interorganizational actors has not been explicitly conceptualized and studied within the above-named approaches. This is despite the fact that the two approaches maintain that networking is one of the core strategies for the long-term survival of market actors. Recently, many scholars within the above-named approaches have emphasized that the survival of market actors is based on the strength of their networks and that inter-firm competition is being replaced by inter-network competition. Furthermore, project business is characterized by the building of goal-oriented, temporary networks whose aims, structures, and procedures are clarified and that are governed by processes of interaction as well as recurrent contracts. This study develops frameworks for studying and analysing collective network capability, i.e. collective capability created for the network of firms. The concept is first justified and positioned within the industrial networks, project business, and relationship marketing schools. An eclectic source of conceptual input is based on four major approaches to interorganizational business relationships. The study uses qualitative research and analysis, and the case report analyses the empirical phenomenon using a large number of qualitative techniques: tables, diagrams, network models, matrices etc. The study shows the high level of uniqueness and complexity of international project business. While perceived psychic distance between the parties may be small due to previous project experiences and the benefit of existing relationships, a varied number of critical events develop due to the economic and local context of the recipient country as well as the coordination demands of the large number of involved actors. The study shows that the successful creation of collective network capability led to the success of the network for the studied project. The processes and structures for creating collective network capability are encapsulated in a model of governance factors for interorganizational networks. The theoretical and management implications are summarized in seven propositions. The core implication is that project business success in unique and complex environments is achieved by accessing the capabilities of a network of actors, and project management in such environments should be built on both contractual and cooperative procedures with local recipient country parties.
Resumo:
The aim of the current study is to examine the influence of the channel external environment on power, and the effect of power on the distribution network structure within the People’s Republic of China. Throughout the study a dual research process was applied. The theory was constructed by elaborating the main theoretical premises of the study, the channel power theories, the political economy framework and the distribution network structure, but these marketing channel concepts were expanded with other perspectives from other disciplines. The main method applied was a survey conducted among 164 Chinese retailers, complemented by interviews, photographs, observations and census data from the field. This multi-method approach enabled not only to validate and triangulate the quantitative results, but to uncover serendipitous findings as well. The theoretical contribution of the current study to the theory of marketing channels power is the different view it takes on power. First, earlier power studies have taken the producer perspective, whereas the current study also includes a distributor perspective to the discussion. Second, many power studies have dealt with strongly dependent relationships, whereas the current study examines loosely dependent relationships. Power is dependent on unequal distribution of resources rather than based on high dependency. The benefit of this view is in realising that power resources and power strategies are separate concepts. The empirical material of the current study confirmed that at least some resources were significantly related to power strategies. The study showed that the dimension resources composed of technology, know-how and knowledge, managerial freedom and reputation was significantly related to non-coercive power. Third, the notion of different outcomes of power is a contribution of this study to the channels power theory even though not confirmed by the empirical results. Fourth, it was proposed that channel external environment other than the resources would also contribute to the channel power. These propositions were partially supported thus providing only partial contribution to the channel power theory. Finally, power was equally distributed among the different types of actors. The findings from the qualitative data suggest that different types of retailers can be classified according to the meaning the actors put into their business. Some are more business oriented, for others retailing is the only way to earn a living. The findings also suggest that in some actors both retailing and wholesaling functions emerge, and this has implications for the marketing channels structure.
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This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.
Resumo:
We provide a comparative performance analysis of network architectures for beacon enabled Zigbee sensor clusters using the CSMA/CA MAC defined in the IEEE 802.15.4 standard, and organised as (i) a star topology, and (ii) a two-hop topology. We provide analytical models for obtaining performance measures such as mean network delay, and mean node lifetime. We find that the star topology is substantially superior both in delay performance and lifetime performance than the two-hop topology.
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In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.
Resumo:
Both management scholars and economic geographers have studied knowledge and argued that the ability to transfer knowledge is critical to competitive success. Networks and other forms for cooperation are often the context when analyzing knowledge transfer within management research, while economic geographers focus on the role of the cluster for knowledge transfer and creation. With the common interest in knowledge transfer, few attempts to interdisciplinary research have been made. The aim of this paper is to outline the knowledge transfer concepts in the two strands of literature of management and economic geography (EG). The paper takes an analytical approach to review the existing contributions and seek to identify the benefits of further interaction between the disciplines. Furthermore, it offers an interpretation of the concepts of cluster and network, and suggests a clearer distinction between their respective definitions. The paper posits that studies of internal networks transcending national borders and clusters are not necessarily mutually exclusive when it comes to transfer of knowledge and the learning process of the firm. Our conclusion is that researchers in general seem to increasingly acknowledge the importance of studying both the effect of and the need for geographical proximity and external networks for the knowledge transfer process, but that there exists equivocalness in defining clusters and networks.
Resumo:
Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems