999 resultados para regional feature


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In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

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This study examines consumer adoption of 3G mobile technology in China. The qualitative study involved 45 in-depth interviews undertaken in three major Chinese cities to explore the beliefs and attitudes which determine Chinese consumers’ acceptance of the mobile technological innovation. The findings are compared and contrasted against those reported in Western studies. The variations underpinning adoption of 3G between consumers in the three regional cities were identified. Specifically, it was found that the regions differed in terms of the relative importance of the identified adoption determinants, such as perceived social outcomes for using the innovation and the effects of social influence on the adoption. These findings provide subtle insight into the nature of Chinese consumers’ responses to new mobile technologies and a better understanding of variations among regional Chinese consumers.

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The belief that regions play a role in determining national economic development and that advantages are found at the local and regional level has been the focus of economic geography and development studies over the last 10 years. However, this issue has historically been dominated by economic perspectives, industrial firms, and public bodies. In recent years the social economy is starting to receive greater attention in creating regional advantage as well as ameliorating regional disadvantage. The social economy includes the impact of the third sector such as social enterprises. This paper proposes that understanding the role and function of social enterprise will enable a more nuanced understanding of the socio-economic aspects of regional development. Drawing upon Oliver’s (1997) framework for sustainable competitive advantage it is argued that this established management framework provides a valuable foundation for examining the organisational resources that social enterprise need to operate effectively, as well as the socio-economic resources they produce for regional communities.

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Thermal-infrared images have superior statistical properties compared with visible-spectrum images in many low-light or no-light scenarios. However, a detailed understanding of feature detector performance in the thermal modality lags behind that of the visible modality. To address this, the first comprehensive study on feature detector performance on thermal-infrared images is conducted. A dataset is presented which explores a total of ten different environments with a range of statistical properties. An investigation is conducted into the effects of several digital and physical image transformations on detector repeatability in these environments. The effect of non-uniformity noise, unique to the thermal modality, is analyzed. The accumulation of sensor non-uniformities beyond the minimum possible level was found to have only a small negative effect. A limiting of feature counts was found to improve the repeatability performance of several detectors. Most other image transformations had predictable effects on feature stability. The best-performing detector varied considerably depending on the nature of the scene and the test.

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It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

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Our cross-national field study of wine entrepreneurship in the “wrong” places provides some redress to the focus of the “regional advantage” literature on places that have already won and on the firms that benefit from “clusters” and other centers of industry advantage. Regional “disadvantage” is at best a shadowy afterthought to this literature. By poking around in these shadows, we help to synthesize and extend the incipient yet burgeoning literature on entrepreneurial “resourcefulness” and we contribute to the developing body of insights and theory pertinent to the numerous but often ignored firms and startups that mostly need to worry about how they will compete at all now if they are ever to have of chance of “winning” in the future. The core of our findings suggests that understandable – though contested – processes of ingenuity underlie entrepreneurial responses to regional disadvantage. Because we study entrepreneurship that from many angles simply does not make sense, we are also able to proffer a novel perspective on entrepreneurial sensemaking.

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This paper investigates the determinants of China’s regional innovation capacity (RIC) and variations in these determinants between different types of regions. Based on the framework of national innovation capacity (NIC) and research on innovation system, this paper develops a framework of RIC in the Chinese context. Using panel data from 1991 to 2009, clustering analysis is first employed to classify regions according to their innovation development path. Panel data regressions with fixed effect model are conducted to explore the determinants of RIC and how these vary across the different regional clusters. We find that the 30 regions can be clustered into three groups, and there are considerable differences in the drivers of RIC between these different regional groups.

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Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

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It has been over 50 years since the topic of branding first appeared in the marketing literature. Research relating to destination branding has however emerged only since the late 1990s, with the first journal article published in 1998 (see Pritchard & Morgan, 1998) and the first book published in 2002 (see Morgan, Pritchard, & Pride, 2002). While a growing number of academic tourism conferences have focused on ‘destination marketing’ as a theme during the past decade (for a list of proceedings see Pike, 2004), Gnoth (1998) claimed the special track he convened at the 1997 American Marketing Science conference, represented the first meeting of practitioners and academics on the topic of destination branding. The initiative of Macau's Instituto De Formacao Turistica (IFT), in conjunction with Perdue University, to convene the first conference on destination branding, was thus new territory and a test of academic interest in the topic. Ultimately the decision was justified with around 100 delegates from 22 countries, including destination branding pioneers Pritchard & Morgan, travelling to the inaugural meeting...

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The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

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China has experienced an extraordinary level of economic development since the 1990s, following excessive competition between different regions. This has resulted in many resource and environmental problems. Land resources, for example, are either abused or wasted in many regions. The strategy of development priority zoning (DPZ), proposed by the Chinese National 11th Five-Year Plan, provides an opportunity to solve these problems by coordinating regional development and protection. In line with the rational utilization of land, it is proposed that the DPZ strategy should be integrated with regional land use policy. As there has been little research to date on this issue, this paper introduces a system dynamic (SD) model for assessing land use change in China led by the DPZ strategy. Land use is characterized by the prioritization of land development, land utilization, land harness and land protection (D-U-H-P). By using the Delphi method, a corresponding suitable prioritization of D-U-H-P for the four types of DPZ, including optimized development zones (ODZ), key development zones (KDZ), restricted development zones (RDZ), and forbidden development zones (FDZ) are identified. Suichang County is used as a case study in which to conduct the simulation of land use change under the RDZ strategy. The findings enable a conceptualization to be made of DPZ-led land use change and the identification of further implications for land use planning generally. The SD model also provides a potential tool for local government to combine DPZ strategy at the national level with land use planning at the local level.

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Public health decision making is critically dependant on accurate, timely and reliable information. There is a widespread belief that most of the national and sub-national health information systems fail in providing much needed information support for evidence based health planning and interventions. This situation is more acute in developing nations where resources are either stagnant or decreasing, coupled with the situations of demographic transition and double burden of diseases. Literature abounds with publications, which provide information on misguided health interventions in developing nations, leading to failure and waste of resources. Health information system failure is widely blamed for this situation. Nevertheless, there is a dearth of comprehensive evaluations of existing national or sub-national health information systems, especially in the region of South-East Asia. This study makes an attempt to bridge this knowledge gap by evaluating a regional health information system in Sri Lanka. It explores the strengths and weaknesses of the current health information system and related causative factors in a decentralised health system and then proposes strategic recommendations for reform measures. A mix methodological and phased approach was adopted to reach the objectives. An initial self administered questionnaire survey was conducted among health managers to study their perceptions in relation to the regional health information system and its management support. The survey findings were used to establish the presence of health information system failure in the region and also as a precursor to the more in-depth case study which was followed. The sources of data for the case study were literature review, document analysis and key stake holder interviews. Health information system resources, health indicators, data sources, data management, data quality, and information dissemination were the six major components investigated. The study findings reveal that accurate, timely and reliable health information is unavailable and therefore evidence based health planning is lacking in the studied health region. Strengths and weaknesses of the current health information system were identified and strategic recommendations were formulated accordingly. It is anticipated that this research will make a significant and multi-fold contribution for health information management in developing countries. First, it will attempt to bridge an existing knowledge gap by presenting the findings of a comprehensive case study to reveal the strengths and weaknesses of a decentralised health information system in a developing country. Second, it will enrich the literature by providing an assessment tool and a research method for the evaluation of regional health information systems. Third, it will make a rewarding practical contribution by presenting valuable guidelines for improving health information systems in regional Sri Lanka.

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This paper reports on a mixed-methods study of social exclusion experiences among 233 resettled refugees living in urban and regional Queensland, Australia. The findings reported here are drawn from the SettleMEN project, a longitudinal investigation of health and settlement experiences among recently arrived adult men from refugee backgrounds conducted between 2008 and 2010. Using questionnaire surveys and semi-structured interviews, we examine four key dimensions of social exclusion: production, consumption, social relations, and services. We show that, overall, participants experienced high levels of social exclusion across all four dimensions. Participants living in regional areas were significantly more likely to be excluded from production, social relations, and services. We argue that there is a pressing need to tackle barriers to economic participation and discrimination in order to promote the social inclusion of men from refugee backgrounds.