850 resultados para Wavelet Packet and Support Vector Machine
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Melanoma is a type of skin cancer and is caused by the uncontrolled growth of atypical melanocytes. In recent decades, computer aided diagnosis is used to support medical professionals; however, there is still no globally accepted tool. In this context, similar to state-of-the-art we propose a system that receives a dermatoscopy image and provides a diagnostic if the lesion is benign or malignant. This tool is composed with next modules: Preprocessing, Segmentation, Feature Extraction, and Classification. Preprocessing involves the removal of hairs. Segmentation is to isolate the lesion. Feature extraction is considering the ABCD dermoscopy rule. The classification is performed by the Support Vector Machine. Experimental evidence indicates that the proposal has 90.63 % accuracy, 95 % sensitivity, and 83.33 % specificity on a data-set of 104 dermatoscopy images. These results are favorable considering the performance of diagnosis by traditional progress in the area of dermatology
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Background: Type 1 Diabetes (T1D) management often worsens as children become adolescents. This can be a difficult time for parents as they hand over responsibility of diabetes management to their adolescent. Objectives: To look at the experiences of parents with a child with T1D as they move to adolescence and take more responsibility for their diabetes management. To find out about parents’ experience of support during this transition. Subjects: Three parents of adolescents with T1D. Participants were recruited from the NHS Highland Paediatric Diabetes Service. Methods: Participants took part in a one-to-one semi-structured interview with a researcher. Interpretative Phenomenological Analysis was used to analyse the interviews and find common themes across the interviews. Results: Participants experienced worry throughout their child’s transition to adolescence. They found it difficult to let their child take responsibility for their diabetes but acknowledged that their involvement caused tensions with their adolescent. Participants’ experience was that there were a number of practical adjustments to be made with a diagnosis of T1D and educating the network around their child was important. The participants reported that the diagnosis of T1D had an impact on the whole family and not just the child with the diagnosis. The parents felt well supported medically but said that the amount of time before their first clinic appointment felt too long. All participants had concerns about their adolescent moving to the adult diabetic service. Conclusions: Participants experienced worry relating to aspects of their adolescents T1D that they could not control, but were aware of the tensions caused by trying to keep elements of control. Areas of future research were identified.
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This paper analyses the implementation characteristics of the Family Education and Support program, a theory-driven, needs-based, and evidence-based positive parenting program originally developed for the Andalusian family preservation services. The implementation process of 34 trials of the FAF program with 155 participants was analyzed. Cluster analyses were also performed to explore variability in implementation conditions from a comprehensive perspective. Results showed different implementation profiles that moderated the FAF effectiveness (namely lengthier interventions, higher program fidelity, and practitioners' positive perceptions and satisfaction with the program). The relevance of examining implementation process across several trials is discussed in order to distinguish core and non-core FAF components, as well as the need for combining faithful and adaptable implementations that guarantee the ecologic validity of evidence-based positive parenting programs.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Administração, 2016.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade Gama, Programa de Pós-Graduação em Engenharia Biomédica, 2015.
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Attachment and interpersonal theory suggest a sequential pattern of relationships beginning in the earliest stage of development and progressing to social and eventually romantic relationships. Theoretically, cross-sex experiences have an important role in the progression of interpersonal relationships. Despite the prevalence of these theories about the nature of romantic relationship development, the linkage of cross-sex experience (CSE) to romantic relationships has not been established. Indeed, it is an intuitive assumption, especially within Western society and these theories do not consider socio-cultural factors that may influence CSE and relationship satisfaction. This study addresses the varying contextual factors that may contribute to relationship satisfaction and adjustment, aside from CSE, and is divided into two parts. Study 1, addresses CSE, relationship satisfaction, and adjustment in a unique population, ultra-Orthodox Jews. Among this population, social or romantic CSE is limited and sexes are effectively segregated. Study 2, expanded the study to a larger sample of U.S. college students, to assess the linkage of CSE to romantic relationship satisfaction in a more typical Western population. It included social norm and support variables to address the contextual nature of relationship development and satisfaction. Results demonstrated clear differences in the relation between CSE and relationship satisfaction in the two samples. In the first sample CSE was unrelated to relationship satisfaction; nevertheless, relationship satisfaction was associated with adjustment as it is for more typical populations with greater CSE. These results suggested the importance of specifying how social norms and social support relate to CSE, relationship satisfaction and adjustment. The results from the second sample were consistent with the theoretical framework upon which the social/romantic literature is based. CSE was directly connected to relationship satisfaction. As anticipated, CSE, relationship satisfaction, and adjustment also varied as a function of social norms and support. These findings further validate the influence of socio-cultural factors on relationship satisfaction and adjustment. This study contributes to the romantic relationship literature and broadens our understanding of the complex nature of interpersonal and romantic relationships.^
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The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.
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The general aim of this dissertation is to describe and analyse patterns of informal care and support for carers in Sweden. One specific aim is to study patterns of informal care from a broad population perspective in terms of types of care and types of carer. A typology of four different care categories based on what carers do revealed that women were much more likely than men to be involved at the ‘heavy end’ of caring, i.e. providing personal care in combination with a variety of other caring tasks. Men were more likely than women to provide some kind of practical help (Study I). Another aim is to investigate which support services are received by which types of informal caregiver. Relatively few informal caregivers in any care category were found to be receiving any kind of support from municipalities or voluntary organizations, for example training or financial assistance (Study II). The same study also examines which kinds of help care recipients receive in addition to that provided by informal carers. It appears that people in receipt of personal care from an informal caregiver quite often also receive help from the public care system, in this case mostly municipal services. However, the majority of those receiving personal, informal care did not receive any help from the public care system or from voluntary organizations or for-profit agencies (Study II). The empirical material in studies I and II comprises survey data from telephone interviews with a random sample of residents in the County of Stockholm aged between 18 and 84. In a number of countries there is a growing interest among social scientists and social policymakers in examining the types of support services that might be needed by people who provide informal care for older people and others. A further aim of the present dissertation is therefore to describe and analyse the carer support that is provided by municipalities and voluntary organizations in Sweden. The dissertation examines whether this support is aimed directly or indirectly at caregivers and discusses whether the Swedish government’s special financial investment in help for carers actually led to any changes in the support provided by municipalities and voluntary organisations. The main types of carer support offered by the municipalities were payment for care-giving, relief services and day care. The chief forms of carer support provided by the voluntary organizations were support groups, training groups, and a number of services aimed primarily at the elderly care recipients (Study III). Patterns of change in municipal carer support could be discerned fairly soon. The Swedish government’s special allocation to municipalities and voluntary organisations appears to have led to an increase in the number of municipalities providing direct support for carers, such as training, information material and professional caregiver consultants. On the other hand, only minor changes could be discerned in the pattern of carer support services provided by the voluntary organizations. This demonstrates stability and the relatively low impact that policy initiatives seem to have on voluntary organizations as providers (Study IV). In studies III and IV the empirical material consists of survey data from mail questionnaires sent to municipalities and voluntary organizations in the County of Stockholm. In the fields of social planning and social work there appears to be a need to clarify the aims of support services for informal carers. Should the support be direct or indirect? Should it be used to supplement or substitute caregivers? In this process of reappraisal it will be important to take the needs of both caregivers and care recipients into account when developing existing and new forms of support. How informal caregivers and care recipients interact with the care system as a whole is undeniably a fertile field for further research.
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La machine à vecteurs de support à une classe est un algorithme non-supervisé qui est capable d’apprendre une fonction de décision à partir de données d’une seule classe pour la détection d’anomalie. Avec les données d’entraînement d’une seule classe, elle peut identifier si une nouvelle donnée est similaire à l’ensemble d’entraînement. Dans ce mémoire, nous nous intéressons à la reconnaissance de forme de dynamique de frappe par la machine à vecteurs de support à une classe, pour l’authentification d’étudiants dans un système d’évaluation sommative à distance à l’Université Laval. Comme chaque étudiant à l’Université Laval possède un identifiant court, unique qu’il utilise pour tout accès sécurisé aux ressources informatiques, nous avons choisi cette chaîne de caractères comme support à la saisie de dynamique de frappe d’utilisateur pour construire notre propre base de données. Après avoir entraîné un modèle pour chaque étudiant avec ses données de dynamique de frappe, on veut pouvoir l’identifier et éventuellement détecter des imposteurs. Trois méthodes pour la classification ont été testées et discutées. Ainsi, nous avons pu constater les faiblesses de chaque méthode dans ce système. L’évaluation des taux de reconnaissance a permis de mettre en évidence leur dépendance au nombre de signatures ainsi qu’au nombre de caractères utilisés pour construire les signatures. Enfin, nous avons montré qu’il existe des corrélations entre le taux de reconnaissance et la dispersion dans les distributions des caractéristiques des signatures de dynamique de frappe.
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Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.
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Se describe la variante homocigota c.320-2A>G de TGM1 en dos hermanas con ictiosis congénita autosómica recesiva. El clonaje de los transcritos generados por esta variante permitió identificar tres mecanismos moleculares de splicing alternativos.
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In this work we compare Grapholita molesta Busck (Lepidoptera: Tortricidae) populations originated from Brazil, Chile, Spain, Italy and Greece using power spectral density and phylogenetic analysis to detect any similarities between the population macro- and the molecular micro-level. Log-transformed population data were normalized and AR(p) models were developed to generate for each case population time series of equal lengths. The time-frequency/scale properties of the population data were further analyzed using wavelet analysis to detect any population dynamics frequency changes and cluster the populations. Based on the power spectral of each population time series and the hierarchical clustering schemes, populations originated from Southern America (Brazil and Chile) exhibit similar rhythmic properties and are both closer related with populations originated from Greece. Populations from Spain and especially Italy, have higher distance by terms of periodic changes on their population dynamics. Moreover, the members within the same cluster share similar spectral information, therefore they are supposed to participate in the same temporally regulated population process. On the contrary, the phylogenetic approach revealed a less structured pattern that bears indications of panmixia, as the two clusters contain individuals from both Europe and South America. This preliminary outcome will be further assessed by incorporating more individuals and likely employed a second molecular marker.
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Il riconoscimento delle condizioni del manto stradale partendo esclusivamente dai dati raccolti dallo smartphone di un ciclista a bordo del suo mezzo è un ambito di ricerca finora poco esplorato. Per lo sviluppo di questa tesi è stata sviluppata un'apposita applicazione, che combinata a script Python permette di riconoscere differenti tipologie di asfalto. L’applicazione raccoglie i dati rilevati dai sensori di movimento integrati nello smartphone, che registra i movimenti mentre il ciclista è alla guida del suo mezzo. Lo smartphone è fissato in un apposito holder fissato sul manubrio della bicicletta e registra i dati provenienti da giroscopio, accelerometro e magnetometro. I dati sono memorizzati su file CSV, che sono elaborati fino ad ottenere un unico DataSet contenente tutti i dati raccolti con le features estratte mediante appositi script Python. A ogni record sarà assegnato un cluster deciso in base ai risultati prodotti da K-means, risultati utilizzati in seguito per allenare algoritmi Supervised. Lo scopo degli algoritmi è riconoscere la tipologia di manto stradale partendo da questi dati. Per l’allenamento, il DataSet è stato diviso in due parti: il training set dal quale gli algoritmi imparano a classificare i dati e il test set sul quale gli algoritmi applicano ciò che hanno imparato per dare in output la classificazione che ritengono idonea. Confrontando le previsioni degli algoritmi con quello che i dati effettivamente rappresentano si ottiene la misura dell’accuratezza dell’algoritmo.
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The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.