913 resultados para fusion probability


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This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

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We report the application of a novel scaffold design in a sheep thoracic spine model for spine deformity correction. The combination of the calcium-phosphate coated polycaprolactone scaffolds with recombinant human bone morphogenic protein-2 (rhBMP-2) are intended as a future bone graft substitute in ensuring the stability of bony intervertebral fusion. A solid free-form fabrication process based on melt extrusion has been utilized in the manufacturing of these scaffolds. To date there are no studies examining the use of such biodegradable implants in a sheep thoracic spine model. The success of anterior scoliosis surgery in humans depends on achieving a solid bony fusion between adjacent vertebrae after the intervertebral discs have been surgically cleared and the disc spaces filled with graft material. Due to limited availability of autograft, there is much current interest in the development of synthetic scaffolds in combination with growth factors such as recombinant human bone morphogenetic protein (rhBMP-2) to achieve a solid bony fusion following scoliosis surgery.

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The relationship between radiologic union and clinical outcome in thoracoscopic scoliosis surgery is not clear, as apparent non-union of a spinal fusion does not always correspond to a poor clinical result. The aim of this study was to evaluate CT fusion rates 2yrs after thoracoscopic surgery, and to explore the relationship between fusion scores and rod diameter, graft type, fusion level, implant failure, and lateral position in the disc space. This study suggests that moderate fusion scores secure successful clinical outcomes in thoracoscopic scoliosis surgery.

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The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.

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This paper presents an innovative prognostics model based on health state probability estimation embedded in the closed loop diagnostic and prognostic system. To employ an appropriate classifier for health state probability estimation in the proposed prognostic model, the comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault levels of three faults in HP-LNG pump. Two sets of impeller-rubbing data were employed for the prediction of pump remnant life based on estimation of discrete health state probability using an outstanding capability of SVM and a feature selection technique. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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Syntaxin 11 (Stx11) is a SNARE protein enriched in cells of the immune system. Loss or mutation of Stx11 results in familial hemophagocytic lymphohistiocytosis type-4 (FHL-4), an autosomal recessive disorder of immune dysregulation characterized by high levels of inflammatory cytokines along with defects in T-cell and natural killer cell function. We show here Stx11 is located on endosomalmembranes including late endosomes and lysosomes in macrophages. While Stx11 did not form a typical trans-SNARE complex, it did bind to the Q-SNARE Vti1b and was able to regulate the availability of Vti1b to form the Q-SNARE complexes Stx6/Stx7/Vtib and Stx7/Stx8/Vti1b. The mutant form of Stx11 sequestered Vti1b from forming the Q-SNARE complex that mediates late endosome to lysosome fusion. Depletion of Stx11 in activated macrophages leads to an accumulation of enlarged late endocytic compartments, increased trafficking to the cell surface and inhibition of late endosome to lysosome fusion. These phenotypes arerescued by the expression of an siRNA-resistant Stx11 construct in Stx11-depleted cells. Our results suggest that by regulating the availability of Vti1b, Stx11 regulates trafficking steps between late endosomes, lysosomes and the cell surface in macrophages.

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Study Design. A sheep study designed to compare the accuracy of static radiographs, dynamic radiographs, and computed tomographic (CT) scans for the assessment of thoracolumbar facet joint fusion as determined by micro-CT scanning. Objective. To determine the accuracy and reliability of conventional imaging techniques in identifying the status of thoracolumbar (T13-L1) facet joint fusion in a sheep model. Summary of Background Data. Plain radiographs are commonly used to determine the integrity of surgical arthrodesis of the thoracolumbar spine. Many previous studies of fusion success have relied solely on postoperative assessment of plain radiographs, a technique lacking sensitivity for pseudarthrosis. CT may be a more reliable technique, but is less well characterized. Methods. Eleven adult sheep were randomized to either attempted arthrodesis using autogenous bone graft and internal fixation (n = 3) or intentional pseudarthrosis (IP) using oxidized cellulose and internal fixation (n = 8). After 6 months, facet joint fusion was assessed by independent observers, using (1) plain static radiography alone, (2) additional dynamic radiographs, and (3) additional reconstructed spiral CT imaging. These assessments were correlated with high-resolution micro-CT imaging to predict the utility of the conventional imaging techniques in the estimation of fusion success. Results. The capacity of plain radiography alone to correctly predict fusion or pseudarthrosis was 43% and was not improved using plain radiography and dynamic radiography with also a 43% accuracy. Adding assessment by reformatted CT imaging to the plain radiography techniques increased the capacity to predict fusion outcome to 86% correctly. The sensitivity, specificity, and accuracy of static radiography were 0.33, 0.55, and 0.43, respectively, those of dynamic radiography were 0.46, 0.40, and 0.43, respectively, and those of radiography plus CT were 0.88, 0.85, and 0.86, respectively. Conclusion. CT-based evaluation correlated most closely with high-resolution micro-CT imaging. Neither plain static nor dynamic radiographs were able to predict fusion outcome accurately. © 2012 Lippincott Williams & Wilkins.

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Fusion techniques have received considerable attention for achieving lower error rates with biometrics. A fused classifier architecture based on sequential integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in this paper that the performance of this architecture can be improved by modelling the correlation between classifier decisions. Correlation modelling also enables better tuning of fusion model parameters, ‘N’, the number of classifiers and ‘M’, the number of attempts/samples, and facilitates the determination of error bounds for false rejects and false accepts for each specific user. Error trade-off performance of the architecture is evaluated using HMM based speaker verification on utterances of individual digits. Results show that performance is improved for the case of favourable correlated decisions. The architecture investigated here is directly applicable to speaker verification from spoken digit strings such as credit card numbers in telephone or voice over internet protocol based applications. It is also applicable to other biometric modalities such as finger prints and handwriting samples.

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Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

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Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.

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Unmanned Aircraft Systems (UAS) are one of a number of emerging aviation sectors. Such new aviation concepts present a significant challenge to National Aviation Authorities (NAAs) charged with ensuring the safety of their operation within the existing airspace system. There is significant heritage in the existing body of aviation safety regulations for Conventionally Piloted Aircraft (CPA). It can be argued that the promulgation of these regulations has delivered a level of safety tolerable to society, thus justifying the “default position” of applying these same standards, regulations and regulatory structures to emerging aviation concepts such as UAS. An example of this is the proposed “1309” regulation for UAS, which is based on the 1309 regulation for CPA. However, the absence of a pilot on-board an unmanned aircraft creates a fundamentally different risk paradigm to that of CPA. An appreciation of these differences is essential to the justification of the “default position” and in turn, to ensure the development of effective safety standards and regulations for UAS. This paper explores the suitability of the proposed “1309” regulation for UAS. A detailed review of the proposed regulation is provided and a number of key assumptions are identified and discussed. A high-level model characterising the expected number of third party fatalities on the ground is then used to determine the impact of these assumptions. The results clearly show that the “one size fits all” approach to the definition of 1309 regulations for UAS, which mandates equipment design and installation requirements independent of where the UAS is to be operated, will not lead to an effective management of the risks.

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Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

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Study Design. Analysis of a case series of 24 Lenke 1C adolescent idiopathic scoliosis (AIS) patients receiving selective thoracoscopic anterior scoliosis correction. Objective. To report the behaviour of the compensatory lumbar curve in a group of Lenke IC AIS patients following thoracoscopic anterior scoliosis correction, and to compare the results of this study with previously published data. Summary of Background Data. Several prior studies have reported spontaneous lumbar curve correction for both anterior and posterior selective fusion in Lenke 1C/King-Moe II patients; however to our knowledge no previous studies have reported outcomes of thoracoscopic anterior correction for this curve type. Methods. All AIS patients with a curve classification of Lenke 1C and a minimum of 24 months follow-up were retrieved from a consecutive series of 190 AIS patients who underwent thoracoscopic anterior instrumented fusion. Cobb angles of the major curve, instrumented levels, compensatory lumbar curve, and T5-T12 kyphosis were recorded, as well as coronal spinal balance, T1 tilt angle and shoulder balance. All radiographic parameters were measured before surgery and at 2, 6, 12 and 24 months after surgery. Results. Twenty-four female patients with right thoracic curves had a mean thoracic Cobb angle of 53.0° before surgery, decreasing to 24.9° two years after surgery. The mean lumbar compensatory Cobb angle was 43.5° before surgery, spontaneously correcting to 25.4° two years after surgery, indicating balance between the thoracic and lumbar scoliotic curves. The lumbar correction achieved (41.8%) compares favourably to previous studies. Conclusions. Selective thoracoscopic anterior fusion allows spontaneous lumbar curve correction and achieves coronal balance of main thoracic and compensatory lumbar curves, good cosmesis and patient satisfaction. Correction and balance are maintained 24 months after surgery.

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Synthetic scaffolds combined with growth factors have the potential to replace allograft or autograft as a graft material for spinal interbody fusion. Such tissue engineering approaches may be useful in Adolescent Idiopathic Scoliosis (AIS) surgery, however there are no studies to date examining the use of such biodegradable implants in combination with biologics in a thoracic spine model. This in vivo study examines the use of biodegradable polycaprolactone (PCL) based scaffolds with rhBMP-2 as a bone graft substitute in a sheep thoracic fusion model, where an anterior approach is used to simulate minimally invasive surgical deformity correction in the setting of AIS.