132 resultados para Partial feedback linearisation


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Context. The VLT-FLAMES Tarantula Survey has an extensive view of the copious number of massive stars in the 30 Doradus (30 Dor) star forming region of the Large Magellanic Cloud. These stars play a crucial role in our understanding of the stellar feedback in more distant, unresolved star forming regions. Aims. The first comprehensive census of hot luminous stars in 30 Dor is compiled within a 10 arcmin (150 pc) radius of its central cluster, R136. We investigate the stellar content and spectroscopic completeness of the early type stars. Estimates were made for both the integrated ionising luminosity and stellar wind luminosity. These values were used to re-assess the star formation rate (SFR) of the region and determine the ionising photon escape fraction. Methods. Stars were selected photometrically and combined with the latest spectral classifications. Spectral types were estimated for stars lacking spectroscopy and corrections were made for binary systems, where possible. Stellar calibrations were applied to obtain their physical parameters and wind properties. Their integrated properties were then compared to global observations from ultraviolet (UV) to far-infrared (FIR) imaging as well as the population synthesis code, Starburst99. Results. Our census identified 1145 candidate hot luminous stars within 150 pc of R136 of which >700 were considered to be genuine early type stars and contribute to feedback. We assess the survey to be spectroscopically complete to 85% in the outer regions (>5 pc) but only 35% complete in the region of the R136 cluster, giving a total of 500 hot luminous stars in the census which had spectroscopy. Only 31 were found to be Wolf-Rayet (W-R) or Of/WN stars, but their contribution to the integrated ionising luminosity and wind luminosity was ~ 40% and ~ 50%, respectively. Similarly, stars with M > 100 M (mostly H-rich WN stars) also showed high contributions to the global feedback, ~ 25% in both cases. Such massive stars are not accounted for by the current Starburst99 code, which was found to underestimate the integrated ionising luminosity of R136 by a factor ~ 2 and the wind luminosity by a factor ~ 9. The census inferred a SFR for 30 Dor of 0.073 ± 0.04 M yr . This was generally higher than that obtained from some popular SFR calibrations but still showed good consistency with the far-UV luminosity tracer as well as the combined Hα and mid-infrared tracer, but only after correcting for Hα extinction. The global ionising output was also found to exceed that measured from the associated gas and dust, suggesting that ~6 % of the ionising photons escape the region. Conclusions. When studying the most luminous star forming regions, it is essential to include their most massive stars if one is to determine a reliable energy budget. Photon leakage becomes more likely after including their large contributions to the ionising output. If 30 Dor is typical of other massive star forming regions, estimates of the SFR will be underpredicted if this escape fraction is not accounted for.

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This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

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This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods. 

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This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

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A multiuser scheduling multiple-input multiple-output (MIMO) cognitive radio network (CRN) with space-time block coding (STBC) is considered in this paper, where one secondary base station (BS) communicates with one secondary user (SU) selected from K candidates. The joint impact of imperfect channel state information (CSI) in BS → SUs and BS → PU due to channel estimation errors and feedback delay on the outage performance is firstly investigated. We obtain the exact outage probability expressions for the considered network under the peak interference power IP at PU and maximum transmit power Pm at BS which cover perfect/imperfect CSI scenarios in BS → SUs and BS → PU. In addition, asymptotic expressions of outage probability in high SNR region are also derived from which we obtain several important insights into the system design. For example, only with perfect CSIs in BS → SUs, i.e., without channel estimation errors and feedback delay, the multiuser diversity can be exploited. Finally, simulation results confirm the correctness of our analysis.

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OBJECTIVES: This study aimed to compare two different tooth replacement strategies for partially dentate older patients; namely functionally orientated treatment according to the principles of the shortened dental arch (SDA) and conventional treatment using removable partial dentures (RPDs) using a randomised controlled clinical trial. The primary outcome measure for this study was impact on oral health-related quality of life (OHRQoL) measured using the short form of the oral health impact profile (OHIP-14).

METHODS: Patients aged 65 years and older were randomly allocated to two different treatment groups: the RPD group and the SDA group. For the RPD group each patient was restored to complete arches with cobalt-chromium RPDs used to replace missing teeth. For the SDA group, patients were restored to a premolar occlusion of 10 occluding pairs of natural and replacement teeth using resin bonded bridgework (RBB). OHRQoL was measured using the OHIP-14 questionnaire administered at baseline, 1 month, 6 months and 12 months after treatment intervention.

RESULTS: In total, 89 patients completed the RCT: 44 from the RPD group and 45 from the SDA group. Analysis using a mixed model of covariance (ANCOVA) illustrated that treatment according to the SDA concept resulted in significantly better mean OHIP-14 scores compared with RPD treatment (p<0.05). This result was replicated in both treatment centres used in the study.

CONCLUSIONS: In terms of impact on OHRQoL, treatment based on the SDA concept achieved significantly better results than that based on RPDs 12 months after treatment intervention (trial registration no. ISRCTN26302774).

CLINICAL SIGNIFICANCE: Functionally orientated treatment delivery resulted in significantly better outcomes compared to removable dentures in terms of impact on OHRQoL.

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OBJECTIVES: The aims of this study were to conduct a randomised controlled clinical trial (RCT) of partially dentate older adults comparing functionally orientated treatment based on the SDA concept with conventional treatment using RPDs to replace missing natural teeth. The two treatment strategies were evaluated according to their impact on nutritional status measured using haematological biomarkers.

METHODS: A randomised controlled clinical trial (RCT) was conducted of partially dentate patients aged 65 years and older (Trial Registration no. ISRCTN26302774). Each patient provided haematological samples which were screened for biochemical markers of nutritional status. Each sample was tested in Cork University Hospital for serum Albumin, serum Cholesterol, Ferritin, Folate, Vitamin B12 and 25-hydroxycholecalciferol (Vitamin D).

RESULTS: A mixed model analysis of covariance (ANCOVA) indicated that for Vitamin B12 (p=0.9392), serum Folate (p=0.5827), Ferritin (p=0.6964), Albumin (p=0.8179), Serum Total Cholesterol (p=0.3670) and Vitamin D (p=0.7666) there were no statistically significant differences recorded between the two treatment groups. According to the mixed model analysis of covariance (ANCOVA) for Vitamin D there was a significant difference between levels recorded at post-operative time points after treatment intervention (p=0.0470). There was an increase of 7% in 25-hydroxycholecalciferol levels recorded at 6 months compared to baseline (p=0.0172). There was no further change in recorded levels at 12 months (p=0.6482) and these increases were similar within the two treatment groups (p>0.05).

CONCLUSIONS: The only measure which illustrated consistent significant improvements in nutritional status for either group were Vitamin D levels. However no significant difference was recorded between the two treatment groups.

CLINICAL SIGNIFICANCE: Functionally orientated prosthodontic rehabilitation for partially dentate older patients was no worse than conventional removable partial dentures in terms of impact on nutritional status.

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Background: In a selective group of patients accelerated partial breast irradiation (APBI) might be applied after conservative breast surgery to reduce the amount of irradiated healthy tissue. The role of volumetric modulated arc therapy (VMAT) and voluntary moderately deep inspiration breath-hold (vmDIBH) techniques in further reducing irradiated healthy – especially heart – tissue is investigated.

Material and methods: For 37 partial breast planning target volumes (PTVs), three-dimensional conformal radiotherapy (3D-CRT) (3 – 5 coplanar or non-coplanar 6 and/or 10 MV beams) and VMAT (two partial 6 MV arcs) plans were made on CTs acquired in free-breathing (FB) and/or in vmDIBH. Dose-volume parameters for the PTV, heart, lungs, and breasts were compared. 

Results: Better dose conformity was achieved with VMAT compared to 3D-CRT (conformity index 1.24 0.09 vs. 1.49 0.20). Non-PTV ipsilateral breast receiving 50% of the prescribed dose was on average reduced by 28% in VMAT plans compared to 3D-CRT plans. Mean heart dose (MHD) reduced from 2.0 (0.1 – 5.1) Gy in 3D-CRT(FB) to 0.6 (0.1 – 1.6) Gy in VMAT(vmDIBH). VMAT is benefi cial for MHD reduction if MHD with 3D-CRT exceeds 0.5Gy. Cardiac dose reduction as a result of VMAT increases with increasing initial MHD, and adding vmDIBH reduces the cardiac dose further. Mean dose to the ipsilateral lung decreased from 3.7 (0.7 – 8.7) to 1.8 (0.5 – 4.0) Gy with VMAT(vmDIBH) compared to 3D-CRT(FB). VMAT resulted in a slight increase in the contralateral breast dose (DMean ) always remaining 1.9 Gy). 

Conclusions: For APBI patients, VMAT improves PTV dose conformity and delivers lower doses to the ipsilateral breast and lung compared to 3D-CRT. This goes at the cost of a slight but acceptable increase of the contralateral breast dose. VMAT reduces cardiac dose if MHD exceeds 0.5 Gy for 3D-CRT. Adding vmDIBH results in a further reduction of heart and ipsilateral lung dose. 

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Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.

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This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.