991 resultados para Cooperation networks
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In this paper, multi-hop cooperative networks implementing channel state information (CSI)-assisted amplify-and-forward (AF) relaying in the presence of in-phase and quadrature-phase (I/Q) imbalance are investigated. We propose a compensation algorithm for the I/Q imbalance. The performance of the multi-hop CSI-assisted AF cooperative networks with and without compensation for I/Q imbalance in Nakagami-m fading environment is evaluated in terms of average symbol error probability. Numerical results are provided and show that the proposed compensation method can effectively mitigate the impact of I/Q imbalance.
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The dorsal striatum (DS) is involved in various forms of learning and memory such as procedural learning, habit learning, reward-association and emotional learning. We have previously reported that bilateral DS lesions disrupt tone fear conditioning (TFC), but not contextual fear conditioning (CFC) [Ferreira TL, Moreira KM, Ikeda DC, Bueno OFA, Oliveira MGM (2003) Effects of dorsal striatum lesions in tone fear conditioning and contextual fear conditioning. Brain Res 987:17-24]. To further elucidate the participation of DS in emotional learning, in the present study, we investigated the effects of bilateral pretest (postraining) electrolytic DS lesions on TFC. Given the well-acknowledged role of the amygdala in emotional learning, we also examined a possible cooperation between DS and the amygdala in TFC, by using asymmetrical electrolytic lesions, consisting of a unilateral lesion of the central amygdaloid nucleus (CeA) combined to a contralateral DS lesion. The results show that pre-test bilateral DS lesions disrupt TFC responses, suggesting that DS plays a role in the expression of TFC. More importantly, rats with asymmetrical pre-training lesions were impaired in TFC, but not in CFC tasks. This result was confirmed with muscimol asymmetrical microinjections in DS and CeA, which reversibly inactivate these structures. On the other hand, similar pretest lesions as well as unilateral electrolytic lesions of CeA and DS in the same hemisphere did not affect TFC. Possible anatomical substrates underlying the observed effects are proposed. Overall, the present results underscore that other routes, aside from the well-established CeA projections to the periaqueductal gray, may contribute to the acquisition/consolidation of the freezing response associated to a TFC task. It is suggested that CeA may presumably influence DS processing via a synaptic relay on dopaminergic neurons of the substantia nigra compacta and retrorubral nucleus. The present observations are also in line with other studies showing that TFC and CFC responses are mediated by different anatomical networks. (C) 2008 IBRO. Published by Elsevier Ltd. All rights reserved.
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This paper exposes the development of markets-as-networks theory from formal inception in the mid-1970s until 2010 state-of-the-art, en route presenting its historical roots. This largely European-based theory challenges the conventional, dichotomous view of the business world as including firms and markets, arguing for the existence of relational governance structures (the so-called ‘‘interfirm cooperation’’) in addition to hierarchical and transactional ones.
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Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.
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Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.
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Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.
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Includes Bibliography
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Taking into account the changes in the market scenario by virtue of globalization, Institutes of Higher Education (IES) as well as other organizations seek their competitive stability. For that reason, it is up to organizations to adopt innovative models of management for their operations aimed at improving results. Company networks consist of a model that is perfect for uniting efforts through cooperation among partners in a given business, which can involve ties of different natures. This paper shows the development and the application of an auxiliary technique to analyze the intensity, nature and importance of internal and external relations in the formation of results for a company network. For such, a multiple case study was conducted at two IES in the State of São Paulo and their networks of partners and employees in order to observe their specificities and organizational strategies. The study demonstrated the existence of specific performance criteria (pillars) for each IES and its network, resulting from its competitive reality. It reveals evidence that the education pillar is strengthened in both cases, and the research pillar is growing, although it is the weakest. The outreach pillar is the most robust in the public IES and the financial sustainability pillar is relevant for the private IES, and it was only detected in this IES.
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Unlike traditional wireless networks, characterized by the presence of last-mile, static and reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by collections of mobile and static terminals that exchange data by enabling each other's communication. Supporting multi-hop communication in a MANET is a challenging research area because it requires cooperation between different protocol layers (MAC, routing, transport). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. Conversely, the contention at MAC layer may cause a routing protocol to respond by initiating new routes queries and routing table updates. Multi-hop communication may also benefit the presence of pseudo-centralized virtual infrastructures obtained by grouping nodes into clusters. Clustering structures may facilitate the spatial reuse of resources by increasing the system capacity: at the same time, the clustering hierarchy may be used to coordinate transmissions events inside the network and to support intra-cluster routing schemes. Again, MAC and clustering protocols could be considered mutually cooperative protocol layers: the clustering scheme could support MAC layer coordination among nodes, by shifting the distributed MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the system benefits of the clustering scheme could be emphasized by the pseudo-centralized MAC layer with the support for differentiated access priorities and controlled contention. In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering and routing protocols in MANETs. As main contribution, we study and analyze the integration of MAC and clustering schemes to support multi-hop communication in large-scale ad hoc networks. A novel clustering protocol, named Availability Clustering (AC), is defined under general nodes' heterogeneity assumptions in terms of connectivity, available energy and relative mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol, named Differentiated Distributed Coordination Function (DDCF), whose focus is to implement adaptive access differentiation based on the node roles, which have been assigned by the upper-layer's clustering scheme. We extensively simulate the proposed clustering scheme by showing its effectiveness in dominating the network dynamics, under some stressing mobility models and different mobility rates. Based on these results, we propose a possible application of the cross-layer MAC+Clustering scheme to support the fast propagation of alert messages in a vehicular environment. At the same time, we investigate the integration of MAC and routing protocols in large scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by extending the AOMDV protocol with a novel load-balancing approach to concurrently distribute the traffic among the multiple paths. We also study the composition effect of a IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF), used to reduce the effects of self-contention among frames at the MAC layer. The protocol framework is modelled and extensively simulated for a large set of metrics and scenarios. For both the schemes, the simulation results reveal the benefits of the cross-layer MAC+routing and MAC+clustering approaches over single-layer solutions.
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Many of developing countries are facing crisis in water management due to increasing of population, water scarcity, water contaminations and effects of world economic crisis. Water distribution systems in developing countries are facing many challenges of efficient repair and rehabilitation since the information of water network is very limited, which makes the rehabilitation assessment plans very difficult. Sufficient information with high technology in developed countries makes the assessment for rehabilitation easy. Developing countries have many difficulties to assess the water network causing system failure, deterioration of mains and bad water quality in the network due to pipe corrosion and deterioration. The limited information brought into focus the urgent need to develop economical assessment for rehabilitation of water distribution systems adapted to water utilities. Gaza Strip is subject to a first case study, suffering from severe shortage in the water supply and environmental problems and contamination of underground water resources. This research focuses on improvement of water supply network to reduce the water losses in water network based on limited database using techniques of ArcGIS and commercial water network software (WaterCAD). A new approach for rehabilitation water pipes has been presented in Gaza city case study. Integrated rehabilitation assessment model has been developed for rehabilitation water pipes including three components; hydraulic assessment model, Physical assessment model and Structural assessment model. WaterCAD model has been developed with integrated in ArcGIS to produce the hydraulic assessment model for water network. The model have been designed based on pipe condition assessment with 100 score points as a maximum points for pipe condition. As results from this model, we can indicate that 40% of water pipeline have score points less than 50 points and about 10% of total pipes length have less than 30 score points. By using this model, the rehabilitation plans for each region in Gaza city can be achieved based on available budget and condition of pipes. The second case study is Kuala Lumpur Case from semi-developed countries, which has been used to develop an approach to improve the water network under crucial conditions using, advanced statistical and GIS techniques. Kuala Lumpur (KL) has water losses about 40% and high failure rate, which make severe problem. This case can represent cases in South Asia countries. Kuala Lumpur faced big challenges to reduce the water losses in water network during last 5 years. One of these challenges is high deterioration of asbestos cement (AC) pipes. They need to replace more than 6500 km of AC pipes, which need a huge budget to be achieved. Asbestos cement is subject to deterioration due to various chemical processes that either leach out the cement material or penetrate the concrete to form products that weaken the cement matrix. This case presents an approach for geo-statistical model for modelling pipe failures in a water distribution network. Database of Syabas Company (Kuala Lumpur water company) has been used in developing the model. The statistical models have been calibrated, verified and used to predict failures for both networks and individual pipes. The mathematical formulation developed for failure frequency in Kuala Lumpur was based on different pipeline characteristics, reflecting several factors such as pipe diameter, length, pressure and failure history. Generalized linear model have been applied to predict pipe failures based on District Meter Zone (DMZ) and individual pipe levels. Based on Kuala Lumpur case study, several outputs and implications have been achieved. Correlations between spatial and temporal intervals of pipe failures also have been done using ArcGIS software. Water Pipe Assessment Model (WPAM) has been developed using the analysis of historical pipe failure in Kuala Lumpur which prioritizing the pipe rehabilitation candidates based on ranking system. Frankfurt Water Network in Germany is the third main case study. This case makes an overview for Survival analysis and neural network methods used in water network. Rehabilitation strategies of water pipes have been developed for Frankfurt water network in cooperation with Mainova (Frankfurt Water Company). This thesis also presents a methodology of technical condition assessment of plastic pipes based on simple analysis. This thesis aims to make contribution to improve the prediction of pipe failures in water networks using Geographic Information System (GIS) and Decision Support System (DSS). The output from the technical condition assessment model can be used to estimate future budget needs for rehabilitation and to define pipes with high priority for replacement based on poor condition. rn
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In the Iron Range Strike of 1916, working-class wives picketed alongside their husbands in a conflict-ridden and dangerous setting. Mine deputies abused immigrant women on the picket lines and in their homes, with several disquieting reports receiving statewide attention in Minnesota. Many middle-class reformers in the Twin Cities grew sympathetic to the plight of northern mining families and became controversially involved the labor struggle. Some middleclass women worked alongside working-class wives and radical organizers from the Industrial Workers of the World (IWW). At the center of this gendered analysis is the cross-class cooperation between an upper-middle class woman, Lenora Austin Hamlin, a radical reformer, Elizabeth Gurley Flynn, and the story of a working-class housewife, Mikla Masonovich. This study will ask how authentic, prevalent, and unproblematic their stories of cross-class cohesive action actually were. In answering this, it will address and identify those factors that impeded women’s potential for unity. “Flash in the Pan” argues that as a result of both real and perceived differences, these networks of women remained isolated, inhibiting each from gaining sufficient power to work cohesively, and marginalizing their influence. Drawing upon a variety of sources, including media representations in newspapers, and archives of social, labor and women’s organizations, this regional study lends state-level insight into the larger gender-labor historiography.
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Using the relational dyad as unit of analysis this study examines the effects of perceived influence and friendship ties on the formation and maintenance of cooperative relationships between corporate top executives. Specifically, it is argued that perceived influence as well as friendship ties between any two managers will enhance the likelihood that these managers collaborate with each other. Additionally, a negative interaction effect between perceived influence and friendship on cooperation is proposed. The empirical analyses draw on network data that have been collected among all members of the top two organizational levels for the strategy-making process in two multinational firms headquartered in Germany. Applying logistic regression based on QAP the empirical results support our hypotheses on the direct effects between perceived influence, friendship ties, and cooperative relationships in both companies. In addition, we find at least partial support for our assumption that perceived influence and friendship interact negatively with respect to their effect on cooperation. Seemingly, perceived influence is partially substituted by managerial friendship ties.
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In Korea, trade with Japan has had a deficit since the normalization of Japan-Korea diplomatic relations in 1965. Korea’s trade balance with Japan has remained in deficit since then, although Korean companies have become bigger compared to Japanese companies. My hypothesis is that the problem has been caused because Korea introduced technologies from Japan. However, in recent years Korean companies could not introduce technologies through technical cooperation with Japan like in the 1990s. In addition, the Korean government seemed to encourage domestic production for import substitution. Nevertheless, the deficit has continued. I thought it necessary to check my hypothesis in order to discover whether or not it was persuasive.