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Literatura académica sobre el tema "Spectral residual methods"

Autor: Grafiati

Publicado: 10 de marzo de 2023

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Artículos de revistas sobre el tema "Spectral residual methods"

Canuto, Claudio y Alfio Quarteroni. "Preconditioned minimal residual methods for chebyshev spectral calculations". Journal of Computational Physics 60, n.º 2 (septiembre de 1985): 315–37. http://dx.doi.org/10.1016/0021-9991(85)90010-5.

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TSUCHIDA, Satoshi, Soichiro TANAKA y Takayuki ODAJIMA. "Spectral Pattern Index for Logarithmic Residual and the similar methods." Journal of the Japan society of photogrammetry and remote sensing 32, n.º 1 (1993): 25–35. http://dx.doi.org/10.4287/jsprs.32.25.

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Wong, Yau Shu, Thomas A. Zang y M. Yousuff Hussaini. "Preconditioned conjugate residual methods for the solution of spectral equations". Computers & Fluids 14, n.º 2 (enero de 1986): 85–95. http://dx.doi.org/10.1016/0045-7930(86)90001-0.

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Schiff, N. D., K. P. Purpura y J. D. Victor. "Gating of Local Network Signals Appears as Stimulus-Dependent Activity Envelopes in Striate Cortex". Journal of Neurophysiology 82, n.º 5 (1 de noviembre de 1999): 2182–96. http://dx.doi.org/10.1152/jn.1999.82.5.2182.

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Neuronal activity often is treated as a composition of a stimulus-driven component and a second component that corrupts the signal, adding or deleting spikes at random. Standard quantitative methods such as peristimulus histograms and Fourier analysis use stimulus-locked averaging to enhance detection of the driven component of neuronal responses and de-emphasize the “noise.” However, neural activity also includes bursts, oscillations, and other episodic events that standard averaging methods overlook. If this activity is stimulus independent, it can be characterized by standard power spectral analysis (or autocorrelation). But activity that is excited by (but not temporally locked to) the visual stimulus cannot be characterized by averaging or standard spectral analysis. Phase-locked spectral analysis (PLSA) is a new method that examines this “residual” activity—the difference between the individual responses to each cycle of a periodic stimulus and their average. With PLSA, residual activity is characterized in terms of temporal envelopes and their carriers. Previously, PLSA demonstrated broadband interactions between periodic visual stimuli and fluctuations in the local field potential of macaque V1. In the present study, single-unit responses (SUA) from parafoveal V1 in anesthetized macaque monkey are examined with this technique. Recordings were made from 21 neurons, 6 of which were recorded in pairs along with multiunit activity (MUA) from separate electrodes and 8 of which were recorded along with MUA from the same electrode. PLSA was applied to responses to preferred (orientation, direction, and spatial frequency) and nonpreferred drifting gratings. For preferred stimuli, all cells demonstrated broadband (1–10 Hz and higher) residual activity that waxed and waned with the stimulus cycle, suggesting that changes in the residual activity are introduced routinely by visual stimulation. Moreover, some reconstructed envelopes indicate that the residual activity was sharply gated by the stimulus cycle. Oscillations occasionally were seen in the power spectrum of single units. Phase-locked cross-spectra were determined for 3 SUA/SUA pairs and 11 SUA/MUA pairs. Residual activity in the cross-spectra was generally much less than the residual activity determined separately from each neuron. The reduction in the residual activity in the cross-spectra suggests that nearby neurons may gate inputs from distinct and relatively independent neuronal subpopulations that together generate the background rhythms of striate cortex.

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Li, Shaodan, Shiyu Fu y Dongbo Zheng. "Rural Built-Up Area Extraction from Remote Sensing Images Using Spectral Residual Methods with Embedded Deep Neural Network". Sustainability 14, n.º 3 (24 de enero de 2022): 1272. http://dx.doi.org/10.3390/su14031272.

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A rural built-up area is one of the most important features of rural regions. Rapid and accurate extraction of rural built-up areas has great significance to rural planning and urbanization. In this paper, the spectral residual method is embedded into a deep neural network to accurately describe the rural built-up areas from large-scale satellite images. Our proposed method is composed of two processes: coarse localization and fine extraction. Firstly, an improved Faster R-CNN (Regions with Convolutional Neural Network) detector is trained to obtain the coarse localization of the candidate built-up areas, and then the spectral residual method is used to describe the accurate boundary of each built-up area based on the bounding boxes. In the experimental part, we firstly explored the relationship between the sizes of built-up areas and the kernels in the spectral residual method. Then, the comparing experiments demonstrate that our proposed method has better performance in the extraction of rural built-up areas.

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Kim, Cheolsun, Dongju Park y Heung-No Lee. "Compressive Sensing Spectroscopy Using a Residual Convolutional Neural Network". Sensors 20, n.º 3 (21 de enero de 2020): 594. http://dx.doi.org/10.3390/s20030594.

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Compressive sensing (CS) spectroscopy is well known for developing a compact spectrometer which consists of two parts: compressively measuring an input spectrum and recovering the spectrum using reconstruction techniques. Our goal here is to propose a novel residual convolutional neural network (ResCNN) for reconstructing the spectrum from the compressed measurements. The proposed ResCNN comprises learnable layers and a residual connection between the input and the output of these learnable layers. The ResCNN is trained using both synthetic and measured spectral datasets. The results demonstrate that ResCNN shows better spectral recovery performance in terms of average root mean squared errors (RMSEs) and peak signal to noise ratios (PSNRs) than existing approaches such as the sparse recovery methods and the spectral recovery using CNN. Unlike sparse recovery methods, ResCNN does not require a priori knowledge of a sparsifying basis nor prior information on the spectral features of the dataset. Moreover, ResCNN produces stable reconstructions under noisy conditions. Finally, ResCNN is converged faster than CNN.

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Liu, Qin, Letong Han, Rui Tan, Hongfei Fan, Weiqi Li, Hongming Zhu, Bowen Du y Sicong Liu. "Hybrid Attention Based Residual Network for Pansharpening". Remote Sensing 13, n.º 10 (18 de mayo de 2021): 1962. http://dx.doi.org/10.3390/rs13101962.

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Pansharpening aims at fusing the rich spectral information of multispectral (MS) images and the spatial details of panchromatic (PAN) images to generate a fused image with both high resolutions. In general, the existing pansharpening methods suffer from the problems of spectral distortion and lack of spatial detail information, which might prevent the accuracy computation for ground object identification. To alleviate these problems, we propose a Hybrid Attention mechanism-based Residual Neural Network (HARNN). In the proposed network, we develop an encoder attention module in the feature extraction part to better utilize the spectral and spatial features of MS and PAN images. Furthermore, the fusion attention module is designed to alleviate spectral distortion and improve contour details of the fused image. A series of ablation and contrast experiments are conducted on GF-1 and GF-2 datasets. The fusion results with less distorted pixels and more spatial details demonstrate that HARNN can implement the pansharpening task effectively, which outperforms the state-of-the-art algorithms.

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He, S., H. Jing y H. Xue. "SPECTRAL-SPATIAL MULTISCALE RESIDUAL NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (30 de mayo de 2022): 389–95. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-389-2022.

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Abstract. In recent years, deep neural networks (DNN) are commonly adopted for hyperspectral image (HSI) classification. As the most representative supervised DNN model, convolutional neural networks (CNNs) have outperformed most algorithms. But the main problem of CNN-based methods lies in the over-smoothing phenomenon. Meanwhile, mainstream methods usually require a large number of samples and a large amount of computation. A multi-task learning spectral-spatial multiscale residual network (SSMRN) is proposed to learn features of objects effectively. In the implementation of the SSMRN, a multiscale residual convolutional neural network (MRCNN) is proposed as spatial feature extractors and a band grouping-based bi-directional gated recurrent unit (Bi-GRU) is utilized as spectral feature extractors. To evaluate the effectiveness of the SSMRN, extensive experiments are conducted on public benchmark data sets. The proposed method can retain the detailed boundary of different objects better and yield a competitive performance compared with two state-of-the-art methods especially when the training samples are inadequate.

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Meng, Zhe, Lingling Li, Xu Tang, Zhixi Feng, Licheng Jiao y Miaomiao Liang. "Multipath Residual Network for Spectral-Spatial Hyperspectral Image Classification". Remote Sensing 11, n.º 16 (13 de agosto de 2019): 1896. http://dx.doi.org/10.3390/rs11161896.

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Convolutional neural networks (CNNs) have recently shown outstanding capability for hyperspectral image (HSI) classification. In this work, a novel CNN model is proposed, which is wider than other existing deep learning-based HSI classification models. Based on the fact that very deep residual networks (ResNets) behave like an ensemble of relatively shallow networks, our proposed network, called multipath ResNet (MPRN), employs multiple residual functions in the residual blocks to make the network wider, rather than deeper. The proposed network consists of shorter-medium paths for efficient gradient flow and replaces the stacking of multiple residual blocks in ResNet with fewer residual blocks but more parallel residual functions in each of it. Experimental results on three real hyperspectral data sets demonstrate the superiority of the proposed method over several state-of-the-art classification methods.

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Shamsipour, Pejman, Michel Chouteau y Denis Marcotte. "Data analysis of potential field methods using geostatistics". GEOPHYSICS 82, n.º 2 (1 de marzo de 2017): G35—G44. http://dx.doi.org/10.1190/geo2015-0631.1.

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Processing of potential field data is commonly done by spectral methods because of their low computational complexity. However, we have studied some geostatistical methods to process the potential field data, and we find the advantages of using these spatial methods. First, we investigate transformation of data by kriging using a gravimetric model of covariance, we compare this approach with the spectral method, and we find its advantage when the data were sparse and not on a regular grid using a synthetic example as well as a field data example. Then, we use factorial kriging for noise reduction and separation of the regional and residual components. This method does not have some of the practical limitations that the spectral-based methods encounter. Finally, we determine the flexibility of interpolation using nonstationary covariances.

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Tesis sobre el tema "Spectral residual methods"

Casper, Brent. "DEVELOPMENT OF AN EXTRACTION METHOD FOR THE MASS SPECTRAL ANALYSIS OF ORGANIC GUNSHOT RESIDUE FROM CLOTHING". UKnowledge, 2015. http://uknowledge.uky.edu/chemistry_etds/48.

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This dissertation will focus on the extraction of volatile organic compounds associated with gunshot residue from articles of clothing, followed by analysis with mass spectrometry. During the discharge of a weapon, a cloud of volatile organic gunshot residue (OGSR) is dispersed around a firearm. This will create a high probability of transfer between the OGSR and the clothing of individuals who are near a discharged weapon. The first part of this dissertation will be the development of a method for removal of volatile OGSR from articles of clothing. Extraction of OGSR will be completed by solid phase microextraction (SPME), followed by separation and analysis by gas chromatography-mass spectrometry (GC/MS). Many parameters will require optimization for proper extraction of OGSR from articles of clothing. Following development of a SPME procedure, figures of merit were determined such as linearity and limits of detection/quantification, obtaining levels of detection of 0.206 ng/cm2 on a 100 cm2 cotton cloth. Applications of this extraction method were investigated including the determination of the distance OGSR travels from a discharged weapon and the extraction of OGSR with different clothing materials by SPME. The second part of this dissertation will focus on the development of an on-line solvent extraction method for removal of OGSR from articles of clothing, followed by analysis with paper spray mass spectrometry. Issues using SPME of certain types of clothing materials required the development of an alternative method for removal of OGSR from articles of clothing. Use of an on-line solvent extraction technique of OGSR from articles of clothing followed by analysis with paper spray mass spectrometry allowed for detection of OGSR at comparable levels to a headspace SPME procedure. Use of paper spray with an ion trap mass spectrometer permitted the soft ionization of OGSR compounds followed by tandem mass spectrometry to obtain structural information. Extraction of OGSR from articles of clothing has potential to determine if an individual was present during the discharge of a firearm. Extraction of OGSR from articles of clothing will provide an alternative to traditional methods of gunshot residue analysis currently in use.

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Cali, José. "Etude des paramètres microscopiques de la piézorésistivité de couches minces polycristallines de silicium dopé bore". Université Joseph Fourier (Grenoble), 1996. http://www.theses.fr/1996GRE10055.

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L'elaboration de films minces de silicium polycristallin, obtenus par recuit thermique a 575c du silicium amorphe hydrogene depose par pecvd et dope in-situ au bore, a permis de mener une etude en fonction du dopage sur l'evolution des proprietes mecaniques (contraintes residuelles, constantes elastiques) et physico-chimiques (concentration d'hydrogene, indice de refraction) du materiau au cours du recuit. En particulier, nous montrons que le changement de signe de la courbure des plaques au cours du recuit est du a la desorption de l'hydrogene du film qui se produit a une temperature proche de la temperature de depot et independamment de la concentration de bore. Des mesures de diffraction de rayons x sous incidence rasante ont egalement permis de comparer la distribution des contraintes residuelles et les parametres mecaniques microscopiques a ceux macroscopiques deduits du releve de la deformee et des mesures de nano-indentation. En modelisant la reponse optique dans la gamme de l'infra-rouge moyen du silicium polycristallin par le modele de drude, nous avons determine sans contact les parametres microscopiques du transport dans le grain. Des mesures de piezoreflectivite infra-rouge nous ont ensuite permis de suivre l'evolution des parametres de transport sous contrainte statique imposee par un module de flexion quatre points. Nous en deduisons un facteur de jauge sensiblement constant dans notre gamme de dopage de l'ordre de 23 5 en bon accord avec celui obtenu d'apres des mesures de piezoresistivite

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Sgattoni, Cristina. "Solving systems of nonlinear equations via spectral residual methods". Doctoral thesis, 2021. http://hdl.handle.net/2158/1238325.

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This thesis addresses the numerical solution of systems of nonlinear equations via spectral residual methods. Spectral residual methods are iterative procedures, they use the residual vector as search direction and a spectral steplength, i.e., a steplength that is related to the spectrum of the average matrices associated to the Jacobian matrix of the system. Such procedures are widely studied and employed since they are derivative-free and low-cost per iteration. The first aim of the work is to analyze the properties of the spectral residual steplengths and study how they affect the performance of the methods. This aim is addressed both from a theoretical and experimental point of view. The main contributions in this direction are: the theoretical analysis of the steplengths proposed in the literature and of their impact on the methods behaviour; the analysis of the performance of spectral methods with various rules for updating the steplengths. We propose and extensively test different steplength strategies. Rules based on adaptive strategies that suitably combine small and large steplengths result by far more effective than rules based on static choices of the steplength. Numerical experience is conducted on sequences of nonlinear systems arising from rolling contact models which play a central role in many important applications, such as rolling bearings and wheel-rail interaction. Solving these models gives rise to sequences which consist of a large number of medium-size nonlinear systems and represent a relevant benchmark test set for the purpose of the thesis. The second purpose of the thesis is to propose a variant of the derivative-free spectral residual method used in the first part and obtain a general scheme globally convergent under more general conditions. The robustness of the new method is potentially improved with respect to the previous version. Numerical experiments are conducted both on the problems arising in rolling contact models and on a set of problems commonly used for testing solvers for nonlinear systems.

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Liou, Chu Pheuil. "Tests d'ajustement reposant sur les méthodes d'ondelettes dans les modèles ARMA avec un terme d'erreur qui est une différence de martingales conditionnellement hétéroscédastique". Thèse, 2019. http://hdl.handle.net/1866/22551.

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Libros sobre el tema "Spectral residual methods"

Sanghrajka, Anish y Deborah M. Eastwood. Developmental dysplasia of the hip. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199550647.003.013017.

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♦ Developmental dysplasia of the hip represents a spectrum of hip pathology with or without hip instability♦ Controversy continues regarding the relative roles of clinical and ultrasound screening programmes♦ Early diagnosis and prompt, appropriate treatment is important♦ All treatment methods risk compromising the vascularity of the developing femoral head♦ Residual dysplasia may require an aggressive surgical approach.

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Capítulos de libros sobre el tema "Spectral residual methods"

Dozier, Haley y James V. Lambers. "Krylov Subspace Spectral Methods with Coarse-Grid Residual Correction for Solving Time-Dependent, Variable-Coefficient PDEs". En Lecture Notes in Computational Science and Engineering, 317–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65870-4_22.

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Priya, K. y K. K. Rajkumar. "Hyperspectral and Multispectral Image Fusion Using Deep Convolutional Neural Network - ResNet Fusion". En Hyperspectral Imaging - A Perspective on Recent Advances and Applications [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.105455.

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In recent years, deep learning HS-MS fusion has become a very active research tool for the super resolution of hyperspectral image. The deep conventional neural networks (CNN) help to extract more detailed spectral and spatial features from the hyperspectral image. In CNN, each convolution layer takes the input from the previous layer which may cause the problems of information loss as the depth of the network increases. This loss of information causes vanishing gradient problems, particularly in the case of very high-resolution images. To overcome this problem in this work we propose a novel HS–MS ResNet fusion architecture with help of skip connection. The ResNet fusion architecture contains residual block with different stacked convolution layer, in this work we tested the residual block with two-, three-, and four- stacked convolution layers. To strengthens the gradients and for decreases negative effects from gradient vanishing, we implemented ResNet fusion architecture with different skip connections like short, long, and dense skip connection. We measure the strength and superiority of our ResNet fusion method against traditional methods by using four public datasets using standard quality measures and found that our method shows outstanding performance than all other compared methods.

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Matandabuzo, Mzukisi y Delford Dovorogwa. "Activated Carbons from Waste Tyre Pyrolysis: Application". En Recent Perspectives in Pyrolysis Research. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.99131.

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The development of better and efficient methods of consuming less and/or wasting little resource materials is becoming more important. In this study, pyrolytic waste tyre carbon black residue and commercial grade activated carbon were characterized and evaluated against adsorption of mercury vapor. The performance of the raw carbon black residue and the activated carbon against mercury vapor generated in the laboratory was determined using a designed reactor system. The adsorption of Hg+ was investigated at temperatures ranging from 200 to 280°C for 6 hours. Batch experiments were conducted for the different carbon residue samples and characterization analysis were done before and after adsorption using the spectroscopic, microscopic, and structural techniques to elucidate the structural arrangements and properties of the carbonaceous materials. Spectroscopic analysis of these carbonaceous residues showed a C=C stretching vibration attributed to the lignocellulose aromatic ring at 1657–2000 cm−1. Comparatively, it was also observed that the Infrared spectrum of raw carbon black exhibits less functional groups as compared to the H2SO4-AC and H2O2-AC carbonaceous residues prepared.

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Ferrell, Jeff. "Drift Method". En Drift. University of California Press, 2018. http://dx.doi.org/10.1525/california/9780520295544.003.0008.

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This chapter argues that to chase after drifters is to chase after ghosts. As victims of social death—as people degraded by the forced withdrawal of mutuality and shared respect from their lives—drifters are caught in spirals of spectral visibility and social invisibility that constitute them as desaparecidos (the disappeared). Consequently, the study of drifters requires what the author calls ghost method. Ghost method is attuned to the presence of absence and to excavating various forms of absence: not there, no longer there, and soon to be gone. It focuses on the residues of social and cultural life and on the ways in which drifters haunt ruins and inhabit spaces in between (interstitial spaces).

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"Understanding the Molecular Information Contained in the Infrared Spectra of Colombian Vacuum Residua by Principal Component Analysis". En Analytical Methods in Petroleum Upstream Applications, 298–323. CRC Press, 2015. http://dx.doi.org/10.1201/b18109-20.

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Orrego-Ruiz, Jorge, Daniel Molina, Enrique Mejía-Ospino y Alexander Guzmán. "Understanding the Molecular Information Contained in the Infrared Spectra of Colombian Vacuum Residua by Principal Component Analysis". En Analytical Methods in Petroleum Upstream Applications, 275–300. CRC Press, 2015. http://dx.doi.org/10.1201/b18109-21.

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Tankala, Manikyala Rao, Samuel Stella, Prayek Sandepogu, Kondaveeti Nanda Gopal, Ramesh Babu Mamillapalli y Devarakonda Rambabu. "A Robust Method for Classification and Localization of Satellite Cyclonic Images Over the Bay of Bengal and the Arabian Sea Using Deep Learning". En Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis, 217–33. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3981-4.ch014.

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According to recent findings, deep learning algorithm outperforms in many tasks like image classification, image segmentation, image recognition, etc. in the field of computer vision. With the help of deep learning, classification tasks on remote sensing image data can attain better performance compared to traditional approaches. This chapter primarily demonstrates how residual neural networks are used to classify satellite images of cyclones in the Bay of Bengal (BoB) and the Arabian Sea (Arab Sea). The authors further discovered the cyclones' locations and investigated using satellite images in the infrared and visible bands of electromagnetic spectrum. From the evaluation metrics, the neural network looks to be capable of correctly identifying the cyclonic storm utilising Gradient Class Activation Mapping (Grad-CAM). Satellite images of both cyclone storm and non-cyclone storm are analysed for cyclonic storm recognition and classification.

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McKnight, Rebecca, Jonathan Price y John Geddes. "Eating disorders". En Psychiatry. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198754008.003.0035.

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The term ‘eating disorder’ describes a range of conditions characterized by abnormal eating habits and methods of weight control which lead to a significant impairment of psychological, social, and physical functioning. Eating disorders are serious, complex conditions; they are not simply a problem of eating too much or too little, or an attempt to achieve the perfect physique. Anorexia nervosa has the highest mortality of any psychiatric disorder, and it is notoriously difficult both to engage eating- disordered patients, and to treat them successfully. There is a positive association between early diagnosis and prognosis, so the skills to recognize an eating disorder— whether they present with psychological or physical symptoms— are essential for all clinicians. At the time of writing, the description of eating disorders within diagnostic classification systems has been undergoing considerable change. Under the ICD- 10 and DSM- IV classification systems, three main eating disorders were recognized (Fig. 27.1): … 1 anorexia nervosa; 2 bulimia nervosa; 3 eating disorder not otherwise specified (EDNOS). … However, this classification has been shown to have various difficulties: … ● The majority of cases were attracting an ‘EDNOS’ label, whereas it was supposed to be a residual category (Fig. 27.1). ● EDNOS contained within it the subdiagnosis ‘binge eating disorder’ (BED). Recent research has demonstrated BED accounts for approximately 10 per cent of eating disorders in clinical cohorts. ● The categorical nature of the system does not allow for the fact that most eating disorders change over time, and frequently move back and forth along the spectrum of presentations. ● The DSM- 5 classification system (see ‘Further reading’) has tried to tackle the first two of these difficulties, and the upcoming ICD- 11 will echo these changes (Table 27.1) There is now a separate category for BED, and three other defined conditions. This is a positive change, but has only reduced the ‘NOS/ unspecified’ percentage to some extent, and has not considered the changeable nature of eating disorder symptomatology. Hopefully in the future a solution to the difficulty of turning a spectrum of pathology into a categorical system will emerge.

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Wilson, M. T. y J. Torres. "Stopped-flow spectroscopy". En Spectrophotometry and Spectrofluorimetry. Oxford University Press, 2000. http://dx.doi.org/10.1093/oso/9780199638130.003.0012.

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There was a time, fortunately some years ago now, when to undertake rapid kinetic measurements using a stopped-flow spectrophotometer verged on the heroic. One needed to be armed with knowledge of amplifiers, light sources, oscilloscopes etc. and ideally one’s credibility was greatly enhanced were one to build one’s own instrument. Analysis of the data was similarly difficult. To obtain a single rate constant might involve a wide range of skills in addition to those required for the chemical/biochemical manipulation of the system and could easily include photography, developing prints and considerable mathematical agility. Now all this has changed and, from the point of view of the scientist attempting to solve problems through transient kinetic studies, a good thing too! Very high quality data can readily be obtained by anyone with a few hours training and the ability to use a mouse and ‘point and click’ programs. Excellent stopped -flow spectrophotometers can be bought which are reliable, stable, sensitive and which are controlled by computers able to signal-average and to analyse, in seconds, kinetic progress curves in a number of ways yielding rate constants, amplitudes, residuals and statistics. Because it is now so easy, from the technical point of view, to make measurement and to do so without an apprenticeship in kinetic methods, it becomes important to make sure that one collects data that are meaningful and open to sensible interpretation. There are a number of pitfalls to avoid. The emphasis of this article is, therefore, somewhat different to that written by Eccleston (1) in an earlier volume of this series. Less time will be spent on consideration of the hardware, although the general principles are given, but the focus will be on making sure that the data collected means what one thinks it means and then how to be sure one is extracting kinetic parameters from this in a sensible way. With the advent of powerful, fast computers it has now become possible to process very large data sets quickly and this has paved the way for the application of ‘rapid scan’ devices (usually, but not exclusively, diode arrays), which allow complete spectra to be collected at very short time intervals during a reaction.

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"niques were prepared using pentane as the solvent. Similar methods were used in preparing calibration samples with the mold release, solder flux, and hydraulic oil samples. All contaminated coupons were gentl y heated in an oven at 50°C for several days to remove both semi-volatile and volatile components. This served to stabi-lize the contaminants, allowing for quantification by weighing. Once the weights became stable, the coupons were cooled and weighed to determine the amount of contaminant present on the surface. When not being weighed or examined, the coupons were kept in a desiccator. 3. RESULTS AND DISCUSSION Grazing-angle incidence reflectance spectroscopy acts to enhance the detection sensitivity for thin layers of residue predominantly through improved coupling of th e electric field intensity of the incident beam with the vibrating dipoles of the surface contaminant layer perpendicular to the metallic surface. Some additional enhancement of the infrared absorption spectrum will also occur due to a length-ening of the effective path length through the absorbing thin film layer [4-6]. If the optical properties of both thin film and substrate are known (or can be de-termined), the reflection-absorption spectrum can be calculated as a function of film thickness and angle of incidence. This capability is particularly useful for in-terpreting experimental data and designing optical instrumentation. Computer codes written at Sandia [7] performed these calculations for a variety of materials. 3.1. FTIR measurements FTIR reflectance data for the full drawing-agent sample set were obtained at NFESC and Sandia using angles of incidence of 75 and 60° for average film thickness ranging from 0.1 to 1 |im, and aluminum substrates with surface finish ranging from 600 to 80 grit. Since the surface finishing operation produced a highly directional roughness, measurements were made both longitudinally and transversely with respect to the polishing grooves. R values were determined at". En Surface Contamination and Cleaning, 17–20. CRC Press, 2003. http://dx.doi.org/10.1201/9789047403289-5.

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Actas de conferencias sobre el tema "Spectral residual methods"

"Spectral Solutions of a Combined Multifluid--population Balance ModelDescribing Bubbly Flow - A Numerical Study of weighted Residual Methods". En 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004477401020107.

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Wu, Hangkong, Dingxi Wang, Xiuquan Huang, Hong Yan y Jianling Li. "Investigation of Spectral Vanishing Viscosity for Stabilizing and Accelerating Solution of Time Spectral Equation System". En ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-76011.

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Time spectral method (TSM), as a very effective frequency domain method for analyzing temporal periodic flow field, is more popular than other frequency domain methods such as the nonlinear harmonic method (NLHM), the linear harmonic method (LHM) and the classic harmonic balance method. This is due to the fact that it is much easier to be implemented in an existing steady flow solver. But the aliasing errors caused by the nonlinear terms in the Euler/Navier-Stokes equations can have an adverse effect on the convergence rate. On the worse side, it can even lead to solution instability. This paper will present investigation of the application of the time spectral vanishing viscosity (SVV) method to stabilizing the solution of time spectral method. The spectral vanishing viscosity method has long been investigated for stabilizing spectral solution of conservation laws in space. Its application to time spectral solution of unsteady flow equations is very limited. In this investigation, the accuracy and time cost of the time spectral method with the SVV will be compared with that without the SVV and the traditional time domain dual time stepping method (DT). The stiffness of the SVV and the time spectral source terms is relieved by implicitly integrating the source terms in time using the block Jacobi method (BJ). To accelerate the convergence rate, the Lower Upper Symmetric Gauss Seidel (LU-SGS) method is used as the residual smoother for a multi-stage Runge-Kutta time integration. The following points can be drawn from this investigation: 1. Time spectral vanishing viscosity method can accelerate convergence rate and reduce time cost. 2. Time spectral vanishing viscosity method can improve the solution accuracy and fewer harmonics can be used to analyze the flow field with the SVV than without the SVV.

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Liu, Yu, Pooya Ghaderi y Andrew J. Dick. "High Fidelity Methods for Modeling Nonlinear Wave Propagation in One-Dimensional Waveguides". En ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88162.

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In this paper, two new methods are proposed to study wave propagation in materials with constitutive law that have nonlinear terms. In the first method, the gauge transformation is used to derive the dynamic shape function. A perturbation method is then applied in order to derive an equation for the wavenumber. The influence of the nonlinearity takes the form of a dependence of the wavenumber on the magnitude of the corresponding frequency component. Under the small amplitude and weak nonlinearity assumptions of the perturbation method, the wavenumber is incorporated into the spectral finite element method (SFEM). The second approach is a numerical method based on alternating frequency-time (AFT) iterations. The nonlinear term represented as a residual nonlinear force term is reduced through the alternating iterations between the time-domain and the frequency-domain. Finally, response behaviors under impact loading predicted with these methods are studied and compared to equivalent linear response behavior.

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Huang, Xiuquan y Ding Xi Wang. "Stabilizing and Accelerating Solution of Harmonic Balance Equation System Using the LU-SGS and Block Jacobi Methods". En ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-57292.

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The paper presents the combination of the Lower Upper Symmetric Gauss Seidel (LU-SGS) method and the block Jacobi method for stabilizing and accelerating the solution of a harmonic balance equation system. First the baseline LU-SGS procedure for a harmonic balance equation system with explicit discretization of the time spectral source term is derived. The LU-SGS method, different from its original application as an implicit time marching scheme, is used as an implicit residual smoother, allowing big CFL numbers (in order of 1000s), within the Runge-Kutta explicit time marching loops. Then the block Jacobi method is introduced to augment solution stability for the solution of a harmonic balance equation system under situation where grid reduced frequency is in the order of 10. Results are presented to show the effectiveness of the combination of LU-SGS and the block Jacobi method on the solution stabilization and acceleration. The influence of the number of Jacobi iterations on solution convergence is also investigated.

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Lu, Yi, Xin Yuan y W. N. Dawes. "Investigation of 3D Internal Flow Using New Flux-Reconstruction High Order Method". En ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-69270.

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The new godunov-type high order method via flux-reconstruction, are capable of unifiying several popular methods including the discontinuous Galerkin, staggered-grid multi-domain method, or the spectral difference/spectral volume methods into a single family. Compared to discontinuous galerkin method, this new method retain the arbitrary order and compact properties but written in differential form and without mass matrix. The flux-reconstrcution method using general unstructured 2D/3D mesh including triangles, quadrilaterals, tetrahedrons, pyramids, prisms and hexahedrons are implemented. Compared to discontinuous galerkin method, FR is differential form without any quandature, so it runs faster and is easier to implement on GPU to achieve higher speed up ratio. The present paper investigates three different solving methods for this new method in order to cut down the hugh computational cost and memory requirement for fully implicit methods. Explicit multi-stage Runge-Kutta, nonlinear Lower-Upper Symmetry Gauss-Seidel (LU-SGS) and generalized minimal residual (GMRES) with matrix-free preconditioning methods are implemented and all these three methods use p-multigrid to smooth low-frequency errors on lower order. The results of 2D steady-state external/internal viscous flows are presented and the convergence properties for different solving method are compared. Efficiency and robustness are improved through symmetric Gauss-Seidel (SGS) iterations as preconditioning, a remarkable feature of the present GMRES+SGS method is that the storage of the full Jacobian matrix can be eliminated and only its diagonal stored. A laplacian artificial viscosity is tested to capture shock in one element and performs well for this new high order method, an L2 projection method is used to improve the perfomance of aliasing error in conservative form. The one equation Spalart-Allmaras turbulence model is unsed to solve the Raynolds average navier-stokes equations. MPI is used for parallel simulations for ralatively complex 3D internal flow when using high order method. Compared to other high order methods, results in this paper show that Flux-Reconstruction methods with efficient solving method performs well for 2D/3D general unstructured mesh in wide range of reynorlds number, and is also potential for “real geometry” simulations.

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Luz, A. M. G., D. Balint y K. Nikbin. "A Multiscale NDT System for Damage Detection in Thermal Barrier Coatings". En ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10694.

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Progress in aero-engines and land-based gas turbines is continuously linked with a rise of the operating temperature. TBCs are multilayered structures which function together to effectively lower the temperature of its load-bearing superalloy substrate while simultaneously providing oxidation protection against high temperature combustion environments during operation. They typically comprise of a ceramic top coat for thermal insulation and a metallic bond coat that provides oxidation/corrosion resistance and enhances the adhesion of the YSZ to the superalloy substrate. Due to high-temperature oxidation of the bond coat, a thermally grown oxide (TGO) scale of continuous Al2O3 is formed between the ceramic top coat and the bond coat. The formation and growth of the TGO increases the mismatch of thermal expansion coefficients among the multilayered TBC and induce high thermal stresses leading to spallation of the YSZ coat from the underlying metal. Hence, nondestructive diagnostic tools that could reliably probe the subsurface damage state of TBCs are essential to take full advantage of these systems. In this contribution, a new concept of multiscale NDT system is presented. The instrument uses a combination of imaging-based methods with photoluminescence piezospectroscopy, a laser-based method. Imaging-based methods like mid-infrared reflectance, laser optical backscatter and infrared tomography were used to predict the overall lifetime of the coated component. When TBCs approach the end of life, micro-crack nucleation and propagation at the top coat/bond coat interface increases the amount of reflected light. This rise in reflectance was correlated with the lifetime of the component using a neural network that merges the mean and standard deviation value of the gray level. Photoluminescence piezospectroscopy was subsequently used to give information about the structural integrity of the hot spots identified in the image analysis. This laser-based technique measures in-situ the residual stress in the TGO at room temperature. Damage leads to a relaxation of the local stress which is in turn reflected in the luminescence spectrum shape. However, presently there is no agreement on the best spectral parameters that should be used as a measure of the damage accumulation in the coatings. Therefore, the evolution of luminescence spectrum from as-manufactured to critically damaged TBCs was determined using the finite element method. This approach helped to identify the most suitable spectral parameters for damage detection, improving the reliability of photoluminescence piezospectroscopy as a failure assessment tool for TBCs.

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Gutman, William M., William A. Peterson y Dennis M. Garvey. "Spatial frequency shifts in Fourier transform spectra". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.ftt2.

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High resolution atmospheric transmission spectra collected with a Fourier transform instrument sometimes exhibit small systematic shifts in the apparent positions of spectral features. Although small, these shifts result in line shape distortions such as "S-curving" when, in the data reduction, one spectrum must be divided by another. The origin of the shifting is in small residual angular deviations between the laser reference and measurement beams and the mechanical axis of the spectrometer. Thermal distortion of the instrument resulting from temperature gradients that change from spectrum to spectrum during a data acquisition operation are the source of the angular deviation. The authors typically measure spectra under field conditions by using trailer-mounted instruments. The level of temperature control necessary to eliminate shifting is not possible under these conditions. Strategies must be found to reduce or eliminate the effects during processing. The processing method that is explored here is to measure the relative shift between the individual spectra and then to interpolate one of them to the precise spatial frequency values present in the other prior to point-by-point division. Relatively simple interpolation schemes yield significant reduction of the distortion when applied to simulated data, and smaller but still good reduction when applied to measured spectra.

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Wang, Jinli, Yongmei Liu, Li Wang, Haiou Guan, Songhuai Du, Juan Su, Yating Cai y Tingting Fan. "Spectrum analysis method of residual current based on Hilbert-Huang transform". En 2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2016. http://dx.doi.org/10.1109/pmaps.2016.7764118.

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Fei Yang, Jingwen Dai y Dan Liu. "A novel eye localization method based on spectral residual model". En 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4593958.

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Zhang, Qian, Yulin Huang, Rufei Wang, Jifang Pei, Weibo Huo y Junjie Wu. "Ship Targets Detection with Dual Downscaling Spectral Residual Method in SAR Image". En 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR). IEEE, 2019. http://dx.doi.org/10.1109/apsar46974.2019.9048331.

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Informes sobre el tema "Spectral residual methods"

Anderson, Gerald L. y Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, diciembre de 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.

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