983 resultados para WHITTAKER MODULE
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The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].
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We analyzed 37 patients who underwent segmental wide resection of bone tumors and reconstruction with a modular titanium endoprosthesis at the Orthopaedic Oncology Group, between 1992 and 1998. Twelve patients were male and 25 were female, with a mean age of 30 years (9 - 81). The mean follow-up was 14 months (2 - 48). The diagnoses were: osteosarcoma (14 cases), metastatic carcinoma (10), Ewing's sarcoma (4), giant cell tumor (4), malignant fibrous histiocytoma (3), chondrosarcoma (1), and aneurysmal bone cyst (1). Eleven articulated total knee, 8 partial proximal femur with bipolar acetabulum, 8 partial proximal humerus, 3 total femur, 2 partial proximal tibia, 2 diaphyseal femur, 2 diaphyseal humerus, and 1 total proximal femur with cementless acetabulum endoprosthesis implant procedures were done. The complications related to the procedure included: infection (5 cases), dislocation (3), module loosening (1), and ulnar nerve paresthesia (1). We used the following criteria for the clinical evaluation: presence of pain, range of motion, reconstruction stability, surgical and oncologic complications, and patient acceptance. The results were good in 56.8% of the cases, regular in 32.4% and poor in 10.8%.
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Mutable state can be useful in certain algorithms, to structure programs, or for efficiency purposes. However, when shared mutable state is used in non-local or nonobvious ways, the interactions that can occur via aliases to that shared memory can be a source of program errors. Undisciplined uses of shared state may unsafely interfere with local reasoning as other aliases may interleave their changes to the shared state in unexpected ways. We propose a novel technique, rely-guarantee protocols, that structures the interactions between aliases and ensures that only safe interference is possible. We present a linear type system outfitted with our novel sharing mechanism that enables controlled interference over shared mutable resources. Each alias is assigned separate, local roles encoded in a protocol abstraction that constrains how an alias can legally use that shared state. By following the spirit of rely-guarantee reasoning, our rely-guarantee protocols ensure that only safe interference can occur but still allow many interesting uses of shared state, such as going beyond invariant and monotonic usages. This thesis describes the three core mechanisms that enable our type-based technique to work: 1) we show how a protocol models an alias’s perspective on how the shared state evolves and constrains that alias’s interactions with the shared state; 2) we show how protocols can be used while enforcing the agreed interference contract; and finally, 3) we show how to check that all local protocols to some shared state can be safely composed to ensure globally safe interference over that shared memory. The interference caused by shared state is rooted at how the uses of di↵erent aliases to that state may be interleaved (perhaps even in non-deterministic ways) at run-time. Therefore, our technique is mostly agnostic as to whether this interference was the result of alias interleaving caused by sequential or concurrent semantics. We show implementations of our technique in both settings, and highlight their di↵erences. Because sharing is “first-class” (and not tied to a module), we show a polymorphic procedure that enables abstract compositions of protocols. Thus, protocols can be specialized or extended without requiring specific knowledge of the interference produce by other protocols to that state. We show that protocol composition can ensure safety even when considering abstracted protocols. We show that this core composition mechanism is sound, decidable (without the need for manual intervention), and provide an algorithm implementation.
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Autor proof
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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.
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Félix, Halperin, and Lemaire have shown that the rational module category Mcat and the rational Toomer invariant coincide for simply connected Poincaré duality complexes. We establish an analogue of this result for the sectional category of a fibration.
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versão acessível em http://ace2015.info/wp-content/uploads/2015/11/ACE_2015_submission_148.pdf
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Dissertação de mestrado integrado em Arquitectura
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Dissertação de mestrado integrado em Arquitectura
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores
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Dissertação de mestrado integrado em Engenharia Mecânica
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores
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OBJECTIVE: Bipolar spectrum disorders (BSDs) are prevalent and frequently unrecognized and undertreated. This report describes the development and validation of the Brazilian version of the bipolar spectrum diagnostic scale (B-BSDS), a screening instrument for bipolar disorders, in an adult psychiatric population. METHOD: 114 consecutive patients attending an outpatient psychiatric clinic completed the B-BSDS. A research psychiatrist, blind to the B-BSDS scores, interviewed patients by means of a modified version of the mood module of the Structured Clinical Interview for DSM-IV ("gold standard"). Subthreshold bipolar disorders were defined as recurrent hypomania without a major depressive episode or with fewer symptoms than those required for threshold hypomania. RESULTS: The internal consistency of the B-BSDS evaluated with Cronbach's alpha coefficient was 0.89 (95% CI; 0.86-0.91). On the basis of the modified SCID, 70 patients (61.4%) of the sample received a diagnosis of BSDs. A B-BSDS screening score of 16 or more items yielded: sensitivity of 0.79 (95% CI; 0.72-0.85), specificity of 0.77 (95% CI; 0.70-0.83), a positive predictive value of 0.85 (95% CI; 0.78-0.91) and a negative predictive value of 0.70 (95% CI; 0.63-0.75). CONCLUSION: The present data demonstrate that the B-BSDS is a valid instrument for the screening of BSDs.
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Dissertação de mestrado integrado em Engenharia Civil