935 resultados para hierarchical winner-take-all


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System compositional approach to model construction and research of informational processes, which take place in biological hierarchical neural networks, is being discussed. A computer toolbox has been successfully developed for solution of tasks from this scientific sphere. A series of computational experiments investigating the work of this toolbox on olfactory bulb model has been carried out. The well-known psychophysical phenomena have been reproduced in experiments.

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Before and after its accession to the WTO in 2001, China has undergone a far-reaching investment liberalisation. As part of this, existing restrictions on foreign ownership structure and mandatory export and technology transfer requirements imposed on foreign firms have been lifted in a number of industries. Against this background we identify the causal effects of foreign acquisitions on export market entry and technology take-off and evaluate whether the level of foreign ownership plays a role in stimulating these changes. Using doubly robust propensity score reweighted bivariate probit regressions to control for the selection bias associated with firm level foreign acquisition incidences, we uncover strong but heterogeneous positive effects on export activity for all types of foreign ownership structure. We also find that minority foreign owned acquisition targets experience higher likelihood of R&D, providing evidence that joint ventures can contribute positively to China's "science and technology take-off".

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Significant numbers of homes within the UK are at risk of flooding. Although community level flood protection schemes are the first line of defence for mitigating flood risk, not all properties are protectable. Property-Level Flood Protection (PLFP) provides those unprotected homeowners with an approach for protecting their homes from flooding. This study sought to establish why property-level flood protection is needed and secondly assess the extent of take up using Worcester as the study area. An exploratory questionnaire survey was conducted to achieve these objectives. After consultation of available literature it was established that the introduction of PLFP protection provided numerous benefits including limiting the health & psychological effects flooding poses, the direct financial benefits and also the possible influence on gaining flood insurance. Despite the benefits and the recognition given to PLFP by the government it was found that the overall take up of the measures was low, findings which were further backed up by data collected in the study area of Worcester with only 23% of the sample having introduced PLFP measures. Reasoning for the low take up numbers typically included; unawareness of the measures, low risk of flood event, installation costs and inability to introduce due to tenancy. Age was noted as a significant impacting factor in the study area with none of the respondents under 25 suggesting they had “a good amount of knowledge of PLFP measures” even when they claimed their properties to be at risk of flooding. Guidance and support is especially recommended to those who are unable to manage their own flood risk for e.g. social housing/rental tenants.

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Abstract How employees make sense of change is a very complex process. Recently, academics have neglected to research sense making activities in a micro culture implementation context, through the eyes of front line employees. In contrast to a macro view, a micro perspective limits researchers to only look at an individual, departmental or group level. By doing so, we can zoom in on the details of sense making processes that employees use in their daily work life. A macro (organisational) view is based on the notion that there is a general integrated culture that can be found in all organisational units and departments. It is assumed that culture can be researched by using the entire organisation as one single research entity. This thesis challenges this assumption. In case of planned change it is usually the management community who are in charge of the change intervention. Because of their formal hierarchical position, they have the power to abort or initiate change programs. It is perhaps therefore that researchers tend to be focused on the management community rather than on lower level organisational members, such as front line employees. Apart from the micro view, scholars also neglected to research culture change implementation through the eyes of front line employees. This thesis is an attempt to fill these two gaps that currently exists in academic change management publications. The main research question is therefore: From a micro point of view how do front-line employees make sense of the impact of culture change, during the implementation phase? This thesis starts with a literature review which exposes the two main gaps. The most important outcome of this review is that only 2% of the research articles dealt with culture implementation, through the eyes of front line employees. A conceptual research model is built on the integrated sense making theory of Weber and Manning (2001) and the micro variables of Raelin and Cataldo (2011). These theories emphasize elements of sense making in a daily working context. It is likely that front line employees can identify themselves with research elements such as tasks, skills practices, involvement and behaviour. Front line employees were selected, because as lower level organisational members they are usually the change recipients. They are further away from the change initiating scene (usually the management of an organisation) and form a potential sense making ‘hotspot’ that could provide new academic insights. In order to carry out the primary research, two case organisations were selected in the leisure industry. A participative case study research method was chosen. This meant that the researcher worked in the concerning departments of the case organisations. The goal was to observe and interview front line employees, while they were performing their jobs. The most important advantage of this approach is that the researcher temporarily becomes one with the organisation and is therefore able to acquire both formal and informal narratives that front line employees use during sense making activities. It was found that front line employees make sense of organisational change by using a practical approach. They make sense of the change program by carrying out new tasks, developing new skills and sharing best practices. The most noticeable conclusion was that sense making activities predominantly take place at an individual level in relation to change acceptance. Organisational members tend to create a mental equation in order to weigh the advantages against the disadvantages. They evaluate whether the concerning change program is beneficial to them or not. For future research a sense making scheme model is suggested that is based on two methods: an introspection and an action method.

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Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

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An effective strategy is critical for the successful development of e-Government. The leading nations in the e-Government rankings include Sweden, Norway, Denmark and Finland. Their leading role makes them interesting to study when looking for reasons to successful e-Government. The purpose of this research paper is to describe the e-Government development strategies of Nordic countries, which rank highly on the international stage. In particular it aims to study the foci of these strategies. The approach is a document study of the e-Government development strategies of Sweden, Denmark, Norway and Finland was carried out using a qualitative content analysis inductive method. The results show that the major focus of Nordic e-Government strategies is on public sector reforms. Other focus areas include economic reforms and, to a lesser extent, e-Democracy efforts. Sweden, Finland and Norway have set ambitious policy goals in order to achieve global leadership in e-Government development. In response to the question posed by this paper’s title, we can say that Nordic e-Government strategies, except for Norway, focus more on reforming public sector services than on economic reforms.  E-Democracy reforms are hardly focused on at all. Practical implications: Public sector policy makers can relate their policy foci to some of the more successful e-Government countries in the world. Research implications/originality is that this paper can apart from the findings also provide a means on how to identify the actual foci of a country’s e-Government policy.

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Football (soccer) is endorsed as a health-promoting physical activity worldwide. When football programs are introduced as part of general health promotion programs, equal access and limitation of pre-participation disparities with regard to injury risk are important. The aim of this study was to explore if disparity with regard to parents' educational level, player body mass index (BMI), and self-reported health are determinants of football injury in community-based football programs, separately or in interaction with age or gender. Methodology/Principal Findings Four community football clubs with 1230 youth players agreed to participate in the cross-sectional study during the 2006 season. The study constructs (parents' educational level, player BMI, and self-reported health) were operationalized into questionnaire items. The 1-year prevalence of football injury was defined as the primary outcome measure. Data were collected via a postal survey and analyzed using a series of hierarchical statistical computations investigating associations with the primary outcome measure and interactions between the study variables. The survey was returned by 827 (67.2%) youth players. The 1-year injury prevalence increased with age. For youths with parents with higher formal education, boys reported more injuries and girls reported fewer injuries than expected; for youths with lower educated parents there was a tendency towards the opposite pattern. Youths reporting injuries had higher standardized BMI compared with youths not reporting injuries. Children not reporting full health were slightly overrepresented among those reporting injuries and underrepresented for those reporting no injury. Conclusion Pre-participation disparities in terms of parents' educational level, through interaction with gender, BMI, and self-reported general health are associated with increased injury risk in community-based youth football. When introduced as a general health promotion, football associations should adjust community-based youth programs to accommodate children and adolescents with increased pre-participation injury risk.

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We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

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Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.

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Meso-/microporous zeolites combine the charactersitics of well-defined micropores of zeolite with efficient mass transfer consequences of mesopores to increase the efficiency of the catalysts in reactions involving bulky molecules. Different methods such as demetallation and templating have been explored for the synthesis of meso-/microporous zeolites. However, they all have limitations in production of meso-/microporous zeolites with tunable textural and catalytic properties using few synthesis steps. To address this challenge, a simple one-step dual template synthesis approach has been developed in this work to engineer lamellar meso-/microporous zeolites structures with tunable textural and catalytic properties. First, one-step dual template synthesis of meso-/microporous mordenite framework inverted (MFI) zeolite structures was investigated. Tetrapropyl ammonium hydroxide (TPAOH) and diquaternary ammonium surfactant ([C22H45-N+(CH3)2-C6H12-N+(CH3)2-C6H13]Br2, C22-6-6) were used as templates to produce micropores and mesopores, respectively. The variation in concentration ratios of dual templates and hydrothermal synthesis conditions resulted in production of multi-lamellar MFI and the hybrid lamellar-bulk MFI (HLBM) zeolite structures. The relationship between the morphology, porosity, acidity, and catalytic properties of these catalysts was systematically studied. Then, the validity of the proposed synthesis approach for production of other types of zeolites composites was examined by creating a meso-/microporous bulk polymorph A (BEA)-lamellar MFI (BBLM) composite. The resulted composite samples showed higher catalytic stability compared to their single component zeolites. The studies demonstrated the high potential of the one-step dual template synthesis procedure for engineering the textural and catalytic properties of the synthesized zeolites.

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Overrecentdecades,remotesensinghasemergedasaneffectivetoolforimprov- ing agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hierarchically structured, the determination of optimal study scales is mandatory in understanding these processes and their interactions. The concept of multi-scale/multi- resolution inherent to OBIA methodologies allows the scale problem to be dealt with. But for that multi-scale and hierarchical segmentation algorithms are required. The question that remains unsolved is to determine the suitable scale segmentation that allows different objects and phenomena to be characterized in a single image. In this work, an adaptation of the Simple Linear Iterative Clustering (SLIC) algorithm to perform a multi-scale hierarchi- cal segmentation of satellite images is proposed. The selection of the optimal multi-scale segmentation for different regions of the image is carried out by evaluating the intra- variability and inter-heterogeneity of the regions obtained on each scale with respect to the parent-regions defined by the coarsest scale. To achieve this goal, an objective function, that combines weighted variance and the global Moran index, has been used. Two different kinds of experiment have been carried out, generating the number of regions on each scale through linear and dyadic approaches. This methodology has allowed, on the one hand, the detection of objects on different scales and, on the other hand, to represent them all in a sin- gle image. Altogether, the procedure provides the user with a better comprehension of the land cover, the objects on it and the phenomena occurring.

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We demonstrate cascaded 100-Gb/s sub-channel add/drop from a 1-Tb/s multi-band OFDM super-channel having 2-GHz inter-sub-channel guard-bands within a recirculating loop via a hierarchical ROADM using high-resolution filters, showcasing 1000-km transmission reach and five ROADM node passages for the add/drop sub-channel when hybrid Raman-EDFA is implemented.

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There is still much discussion on the most appropriate location, size and shape of marine protected areas (MPAs). These three factors were analyzed for a small coastal MPA, the Luiz Saldanha Marine Park (LSMP), for which a very limited amount of local ecological information was available when implemented in 1998. Marxan was used to provide a number of near-optimal solutions considering different levels of protection for the various conservation features and different costs. These solutions were compared with the existing no-take area of the LSMP. Information on 11 habitat types and distribution models for 3 of the most important species for the local artisanal fisheries was considered. The human activities with the highest economic and ecological impact in the study area (commercial and recreational fishing and scuba diving) were used as costs. The results show that the existing no-take area is actually located in the best area. However, the no-take area offers limited protection to vagile fish and covers a very small proportion of some of the available habitats. An increase in the conservation targets led to an increase in the number of no-take areas. The comparative framework used in this study can be applied elsewhere, providing relevant information to local stakeholders and managers in order to proceed with adaptive management. (C) 2015 Elsevier B.V. All rights reserved.

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According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e.,many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from withinpatches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.