902 resultados para Dynamic search fireworks algorithm with covariance mutation
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This study aims at exploring the potential impact of forest protection intervention on rural households’ private fuel tree planting in Chiro district of eastern Ethiopia. The study results revealed a robust and significant positive impact of the intervention on farmers’ decisions to produce private household energy by growing fuel trees on their farm. As participation in private fuel tree planting is not random, the study confronts a methodological issue in investigating the causal effect of forest protection intervention on rural farm households’ private fuel tree planting through non-parametric propensity score matching (PSM) method. The protection intervention on average has increased fuel tree planting by 503 (580.6%) compared to open access areas and indirectly contributed to slowing down the loss of biodiversity in the area. Land cover/use is a dynamic phenomenon that changes with time and space due to anthropogenic pressure and development. Forest cover and land use changes in Chiro District, Ethiopia over a period of 40 years was studied using remotely sensed data. Multi temporal satellite data of Landsat was used to map and monitor forest cover and land use changes occurred during three point of time of 1972,1986 and 2012. A pixel base supervised image classification was used to map land use land cover classes for maps of both time set. The result of change detection analysis revealed that the area has shown a remarkable land cover/land use changes in general and forest cover change in particular. Specifically, the dense forest cover land declined from 235 ha in 1972 to 51 ha in 1986. However, government interventions in forest protection in 1989 have slowed down the drastic change of dense forest cover loss around the protected area through reclaiming 1,300 hectares of deforested land through reforestation program up to 2012.
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De nombreux problèmes liés aux domaines du transport, des télécommunications et de la logistique peuvent être modélisés comme des problèmes de conception de réseaux. Le problème classique consiste à transporter un flot (données, personnes, produits, etc.) sur un réseau sous un certain nombre de contraintes dans le but de satisfaire la demande, tout en minimisant les coûts. Dans ce mémoire, on se propose d'étudier le problème de conception de réseaux avec coûts fixes, capacités et un seul produit, qu'on transforme en un problème équivalent à plusieurs produits de façon à améliorer la valeur de la borne inférieure provenant de la relaxation continue du modèle. La méthode que nous présentons pour la résolution de ce problème est une méthode exacte de branch-and-price-and-cut avec une condition d'arrêt, dans laquelle nous exploitons à la fois la méthode de génération de colonnes, la méthode de génération de coupes et l'algorithme de branch-and-bound. Ces méthodes figurent parmi les techniques les plus utilisées en programmation linéaire en nombres entiers. Nous testons notre méthode sur deux groupes d'instances de tailles différentes (gran-des et très grandes), et nous la comparons avec les résultats donnés par CPLEX, un des meilleurs logiciels permettant de résoudre des problèmes d'optimisation mathématique, ainsi qu’avec une méthode de branch-and-cut. Il s'est avéré que notre méthode est prometteuse et peut donner de bons résultats, en particulier pour les instances de très grandes tailles.
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The purpose of this dissertation is to examine three distributional issues in macroeconomics. First I explore the effects fiscal federalism on economic growth across regions in China. Using the comprehensive official data set of China for 31 regions from 1952 until 1999, I investigate a number of indicators used by the literature to measure federalism and find robust support for only one such measure: the ratio of local total revenue to local tax revenue. Using a difference-in-difference approach and exploiting the two-year gap in the implementation of a tax reform across different regions of China, I also identify a positive relationship between fiscal federalism and regional economic growth. The second paper hypothesizes that an inequitable distribution of income negatively affects the rule of law in resource-rich economies and provides robust evidence in support of this hypothesis. By investigating a data set that contains 193 countries and using econometric methodologies such as the fixed effects estimator and the generalized method of moments estimator, I find that resource-abundance improves the quality of institutions, as long as income and wealth disparity remains below a certain threshold. When inequality moves beyond this threshold, the positive effects of the resource-abundance level on institutions diminish quickly and turn negative eventually. This paper, thus, provides robust evidence about the endogeneity of institutions and the role income and wealth inequality plays in the determination of long-run growth rates. The third paper sets up a dynamic general equilibrium model with heterogeneous agents to investigate the causal channels which run from a concern for international status to long-run economic growth. The simulation results show that the initial distribution of income and wealth play an important role in whether agents gain or lose from globalization.
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Paleotopographic models of the West Antarctic margin, which are essential for robust simulations of paleoclimate scenarios, lack information on sediment thickness and geodynamic conditions, resulting in large uncertainties. A new total sediment thickness grid spanning the Ross Sea-Amundsen Sea-Bellingshausen Sea basins is presented and is based on all the available seismic reflection, borehole, and gravity modeling data offshore West Antarctica. This grid was combined with NGDC's global 5 arc minute grid of ocean sediment thickness (Whittaker et al., 2013, doi:10.1002/ggge.20181) and extends the NGDC grid further to the south. Sediment thickness along the West Antarctic margin tends to be 3-4 km larger than previously assumed. The sediment volume in the Bellingshausen, Amundsen, and Ross Sea basins amounts to 3.61, 3.58, and 2.78 million km³, respectively. The residual basement topography of the South Pacific has been revised and the new data show an asymmetric trend over the Pacific-Antarctic Ridge. Values are anomalously high south of the spreading ridge and in the Ross Sea area, where the topography seems to be affected by persistent mantle processes. In contrast, the basement topography offshore Marie Byrd Land cannot be attributed to dynamic topography, but rather to crustal thickening due to intraplate volcanism. Present-day dynamic topography models disagree with the presented revised basement topography of the South Pacific, rendering paleotopographic reconstructions with such a limited dataset still fairly uncertain.
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Este artículo analiza una dinámica de intervenciones de Estados Unidos en América Latina que no ha atraído suficientemente la atención de los historiadores. En los años treinta y cuarenta, cuando Europa se hundía en una nueva confrontación bélica, ciertos sectores del gobierno y del mundo empresarial norteamericano intentaron articular una nueva relación con los países del continente basada en una propuesta de multilateralismo que se había configurado dentro de la Sociedad de Naciones (SN). Estos estadounidenses intentaron establecer una dinámica de relaciones triangulares con los gobiernos latinoamericanos y los organismos técnicos de la SN. Gracias a ello, como se mostrará en este artículo para el caso del funcionamiento del Comité Fiscal de la Sociedad de Naciones, los latinoamericanos fueron capaces de influir en el tipo de políticas que debían emanar de esta relación triangular. La importancia de esta historia no es menor. La relación triangular entre Estados Unidos, América Latina y la SN sirvió de base para la reconstrucción de la gobernanza global liderada por los Estados Unidos tras la guerra.
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Taxonomies have gained a broad usage in a variety of fields due to their extensibility, as well as their use for classification and knowledge organization. Of particular interest is the digital document management domain in which their hierarchical structure can be effectively employed in order to organize documents into content-specific categories. Common or standard taxonomies (e.g., the ACM Computing Classification System) contain concepts that are too general for conceptualizing specific knowledge domains. In this paper we introduce a novel automated approach that combines sub-trees from general taxonomies with specialized seed taxonomies by using specific Natural Language Processing techniques. We provide an extensible and generalizable model for combining taxonomies in the practical context of two very large European research projects. Because the manual combination of taxonomies by domain experts is a highly time consuming task, our model measures the semantic relatedness between concept labels in CBOW or skip-gram Word2vec vector spaces. A preliminary quantitative evaluation of the resulting taxonomies is performed after applying a greedy algorithm with incremental thresholds used for matching and combining topic labels.
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Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.
Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.
Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.
Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.
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Background: Lethal-7 (let-7) is a tumour suppressor miRNA which acts by down-regulating several oncogenes including KRAS. A single-nucleotide polymorphism (rs61764370, T > G base substitution) in the let-7 complementary site 6 (LCS-6) of KRAS mRNA has been shown to predict prognosis in early-stage colorectal cancer (CRC) and benefit from anti-epidermal growth factor receptor monoclonal antibodies in metastatic CRC. Patients and methods: We analysed rs61764370 in EXPERT-C, a randomised phase II trial of neoadjuvant CAPOX followed by chemoradiotherapy, surgery and adjuvant CAPOX plus or minus cetuximab in locally advanced rectal cancer. DNA was isolated from formalin-fixed paraffin-embedded tumour tissue and genotyped using a PCR-based commercially available assay. Kaplan–Meier method and Cox regression analysis were used to calculate survival estimates and compare treatment arms. Results: A total of 155/164 (94.5%) patients were successfully analysed, of whom 123 (79.4%) and 32 (20.6%) had the LCS-6 TT and LCS-6 TG genotype, respectively. Carriers of the G allele were found to have a statistically significantly higher rate of complete response (CR) after neoadjuvant therapy (28.1% versus 10.6%; P = 0.020) and a trend for better 5-year progression-free survival (PFS) [77.4% versus 64.5%: hazard ratio (HR) 0.56; P = 0.152] and overall survival (OS) rates (80.3% versus 71.9%: HR 0.59; P = 0.234). Both CR and survival outcomes were independent of the use of cetuximab. The negative prognostic effect associated with KRAS mutation appeared to be stronger in patients with the LCS-6 TT genotype (HR PFS 1.70, P = 0.078; HR OS 1.79, P = 0.082) compared with those with the LCS-6 TG genotype (HR PFS 1.33, P = 0.713; HR OS 1.01, P = 0.995). Conclusion: This analysis suggests that rs61764370 may be a biomarker of response to neoadjuvant treatment and an indicator of favourable outcome in locally advanced rectal cancer possibly by mitigating the poor prognosis of KRAS mutation. In this setting, however, this polymorphism does not appear to predict cetuximab benefit.
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Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.
Proposition de nouvelles fonctionnalités WikiSIG pour supporter le travail collaboratif en Geodesign
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L’émergence du Web 2.0 se matérialise par de nouvelles technologies (API, Ajax…), de nouvelles pratiques (mashup, geotagging…) et de nouveaux outils (wiki, blog…). Il repose principalement sur le principe de participation et de collaboration. Dans cette dynamique, le Web à caractère spatial et cartographique c’est-à-dire, le Web géospatial (ou GéoWeb) connait lui aussi de fortes transformations technologiques et sociales. Le GéoWeb 2.0 participatif se matérialise en particulier par des mashups entre wikis et géobrowsers (ArgooMap, Geowiki, WikiMapia, etc.). Les nouvelles applications nées de ces mashups évoluent vers des formes plus interactives d’intelligence collective. Mais ces applications ne prennent pas en compte les spécificités du travail collaboratif, en particulier la gestion de traçabilité ou l’accès dynamique à l’historique des contributions. Le Geodesign est un nouveau domaine fruit de l’association des SIG et du design, permettant à une équipe multidisciplinaire de travailler ensemble. Compte tenu de son caractère émergent, le Geodesign n’est pas assez défini et il requiert une base théorique innovante, de nouveaux outils, supports, technologies et pratiques afin de s’adapter à ses exigences complexes. Nous proposons dans cette thèse de nouvelles fonctionnalités de type WikiSIG, bâties sur les principes et technologies du GéoWeb 2.0 et visant en particulier à supporter la dimension collaborative du processus de Geodesign. Le WikiSIG est doté de fonctionnalités wiki dédiées à la donnée géospatiale (y compris dans sa composante géométrique : forme et localisation) permettant d’assurer, de manière dynamique, la gestion documentée des versions des objets et l’accès à ces versions (et de leurs métadonnées), facilitant ainsi le travail collaboratif en Geodesign. Nous proposons également la deltification qui consiste en la capacité de comparer et d’afficher les différences entre deux versions de projets. Finalement la pertinence de quelques outils du géotraitement et « sketching » est évoquée. Les principales contributions de cette thèse sont d’une part d’identifier les besoins, les exigences et les contraintes du processus de Geodesign collaboratif, et d’autre part de proposer des nouvelles fonctionnalités WikiSIG répondant au mieux à la dimension collaborative du processus. Pour ce faire, un cadre théorique est dressé où nous avons identifié les exigences du travail collaboratif de Geodesign et proposé certaines fonctionnalités WikiSIG innovantes qui sont par la suite formalisés en diagrammes UML. Une maquette informatique est aussi développée de façon à mettre en oeuvre ces fonctionnalités, lesquelles sont illustrées à partir d’un cas d’étude simulé, traité comme preuve du concept. La pertinence de ces fonctionnalités développées proposées est finalement validée par des experts à travers un questionnaire et des entrevues. En résumé, nous montrons dans cette thèse l’importance de la gestion de la traçabilité et comment accéder dynamiquement à l’historique dans un processus de Geodesign. Nous proposons aussi d’autres fonctionnalités comme la deltification, le volet multimédia supportant l’argumentation, les paramètres qualifiant les données produites, et la prise de décision collective par consensus, etc.
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Introdução: Os efeitos a longo prazo de exercícios de Pilates têm sido bem documentados, não entanto os seus efeitos imediatos no controlo postural estático e dinâmico de jovens adultos com dor lombar não específica permanecem por desvendar. Objetivo: Avaliar os efeitos imediatos de uma sessão composta por 4 exercícios de Pilates Clínico no controlo postural estático e dinâmico de jovens adultos com dor lombar não específica. Métodos: 46 estudantes universitários com dor lombar não específica participaram no estudo randomizado e controlado. Os participantes foram randomizados para um grupo de Pilates (n = 23, 10 do sexo masculino, idade: 21,8 ± 3,2 anos; peso: 64,5 ± 11,5 kg; altura: 1,70 ± 0,1 m) e um grupo controlo (n = 23, 9 do sexo masculino; idade: 22,8 ± 3,6 anos; peso: 62,5 ± 9,9 kg; altura: 1,68 ± 0,1 m). O controlo postural estático foi avaliado com uma plataforma de forças e o controlo postural dinâmico com o Star Excursion Balance Test, antes e depois da intervenção ou período de repouso. Para avaliar o controlo postural estático, os participantes estavam em posição ortostática, o mais quietos possível durante 90s, com os olhos fechados em superfície instável. A intervenção durou 20 minutos e consistiu em 4 exercícios de Pilates Clínico: single leg stretch (nível 1), pelvic press (nível 1), swimming (nível 1) e kneeling opposite arm and leg reach. Resultados: No momento de avaliação inicial, não foram encontradas diferenças estatisticamente significativas entre os grupos em nenhuma das variáveis. Após a intervenção, o grupo Pilates melhorou em todos as variáveis do controlo postural estático (COPx: 5,7 ± 1,0 para 5,1 ± 0,7 cm, p = 0,005; COPy: 4,4 ± 1,0 para 3,8 ± 0,7 cm, p < 0,001; comprimento total: 255,2 ± 55,9 para 210,5 ± 42,7 cm, p < 0,001 ; área: 11,5 ± 3,4 para 9,7 ± 2,7 cm2, p = 0,002 e velocidade : 2,8 ± 0,6 para 2,3 ± 0,5 cm/s, p < 0,001) e no Star Excursion Balance Test (anterior: 65,3 ± 8,3 para 68,6 ± 6,4%, p = 0,001; póstero-medial: 82,6 ± 11,7 para 89,5 ± 9,7%, p < 0,001; póstero-lateral: 83,9 ± 11,0 para 87,6 ± 10,2%, p < 0,001 e composite: 86,2 ± 12,4 para 91,1 ± 11,0%, p < 0,001). O grupo de controlo só melhorou na velocidade (2,8 ± 0,5 para 2,6 ± 0,5 cm/s, p = 0,009) e comprimento total (248,5 ± 45,3 para 237,3 ± 47,2 cm, p = 0,009) no controlo postural estático. No entanto, as melhorias no grupo Pilates foram significativamente maiores do que as do grupo de controlo. Conclusão: Os exercícios de Pilates Clínico melhoraram, no imediato, o controlo postural estático e dinâmico em jovens adultos com dor lombar não específica.
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Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.
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O seio maxilar é o seio paranasal mais susceptível a invasões bacterianas, tanto pelo óstio nasal, como pela cavidade oral. As sinusites maxilares têm como causas mais frequentes, as infecções víricas, rinites alérgicas ou não alérgicas, variações anatómicas, diabetes mellitus, fumar, nadar, mergulhar, escalar a altas atitudes, e as infecções e tratamentos dentários. A pesquisa bibliográfica, foi realizada sem quaisquer limitações temporais, com restrição linguística a Português, Espanhol e Inglês, sendo excluídos os artigos de outros idiomas; em vários livros e revistas, assim como artigos científicos obtidos, entre Maio e Julho de 2015, nos motores de busca Pubmed, ScienceDirect, Scielo, Elsevier e B-on. A sinusite maxilar odontogénica é uma doença infecto-inflamatória, habitualmente associada à ruptura da membrana de Schneider e a processos infecciosos dentários crónicos. Causa hiperplasia e hipertrofia da mucosa, o que origina sinais e sintomas próprios, assim como mudanças radiográficas perceptíveis. Existem diferentes etiologias de causa odontogénica: cárie, doença periodontal, quistos odontogénicos e iatrogenia – tratamento endodôntico não cirúrgico, cirurgia endodôntica, comunicações oro-antrais, implantes dentários, elevação do seio maxilar, cirurgia pré-protética e cirurgia ortognática – sendo que a iatrogenia é a mais comum (cerca de 56%). Esta patologia afecta com mais frequência indivíduos dos 42,7 aos 51, 7 anos, e preferencialmente a região molar, seguida dos pré-molares e em alguns casos, caninos. Os organismos que dominam na fase aguda e crónica, são sensivelmente os mesmos, mas em número diferente, e existe uma conexão entre a flora comensal periapical e a flora patogénica em caso de sinusite maxilar odontogénica. O diagnóstico é essencialmente clínico, no entanto existem diferentes exames complementares para confirmarem ou formarem o diagnóstico. Pela grande acessibilidade ao método radiográfico, torna-se fundamental que o médico dentista saiba diferencial as diversas patologias que afectam o seio maxilar. O tratamento abrange a eliminação da causa dentária e o tratamento farmacológico, da infecção, essencialmente à base de antibióticos, e da dor se esta existir. E o tratamento cirúrgico, que contempla a punção-lavagem sinusal, antrostomia intranasal, técnica de Caldwell-Luc e cirurgia sinusal endoscópica. Concluindo, o médico dentista deve ter um amplo conhecimento sobre esta patologia para que a possa reconhecer, tratar ou preveni-la.
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This work explores regulation of forward speed, step length, and slope walking for the passive-dynamic class of bipedal robots. Previously, an energy-shaping control for regulating forward speed has appeared in the literature; here we show that control to be a special case of a more general time-scaling control that allows for speed transitions in arbitrary time. As prior work has focused on potential energy shaping for fully actuated bipeds, we study in detail the shaping of kinetic energy for bipedal robots, giving special treatment to issues of underactuation. Drawing inspiration from features of human walking, an underactuated kinetic-shaping control is presented that provides efficient regulation of walking speed while adjusting step length. Previous results on energetic symmetries of bipedal walking are also extended, resulting in a control that allows regulation of speed and step length while walking on any slope. Finally we formalize the optimal gait regulation problem and propose a dynamic programming solution seeded with passive-dynamic limit cycles. Observations of the optimal solutions generated by this method reveal further similarities between passive dynamic walking and human locomotion and give insight into the structure of minimum-effort controls for walking.
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We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.