969 resultados para Texture Analysis
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The relationship between protein profiles of Gluteus medius (GM) muscles of raw hams obtained from 4 pure breed pigs (Duroc, Large White, Landrace, and Piétrain) with the final quality of the Semimembranosus and Biceps femoris muscles of dry-cured hams was investigated. As expected, Duroc hams showed higher levels of marbling and intramuscular fat content than the other breeds. Piétrain hams were the leanest and most conformed, and presented the lowest salt content in dry-cured hams. Even if differences in the quality traits (colour, water activity, texture, composition, intramuscular fat, and marbling) of dry-cured hams were observed among the studied breeds, only small differences in the sensory attributes were detected. Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) was used to obtain the soluble protein profiles of GM muscles. Some associations between protein peaks obtained with SELDI-TOF-MS and quality traits, mainly colour (b*) and texture (F0, Y2, Y90) were observed. Candidate protein markers for the quality of processed dry-cured hams were identified
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Context: In the milder form of primary hyperparathyroidism (PHPT), cancellous bone, represented by areal bone mineral density at the lumbar spine by dual-energy x-ray absorptiometry (DXA), is preserved. This finding is in contrast to high-resolution peripheral quantitative computed tomography (HRpQCT) results of abnormal trabecular microstructure and epidemiological evidence for increased overall fracture risk in PHPT. Because DXA does not directly measure trabecular bone and HRpQCT is not widely available, we used trabecular bone score (TBS), a novel gray-level textural analysis applied to spine DXA images, to estimate indirectly trabecular microarchitecture. Objective: The purpose of this study was to assess TBS from spine DXA images in relation to HRpQCT indices and bone stiffness in radius and tibia in PHPT. Design and Setting: This was a cross-sectional study conducted in a referral center. Patients: Participants were 22 postmenopausal women with PHPT. Main Outcome Measures: Outcomes measured were areal bone mineral density by DXA, TBS indices derived from DXA images, HRpQCT standard measures, and bone stiffness assessed by finite element analysis at distal radius and tibia. Results: TBS in PHPT was low at 1.24, representing abnormal trabecular microstructure (normal ≥1.35). TBS was correlated with whole bone stiffness and all HRpQCT indices, except for trabecular thickness and trabecular stiffness at the radius. At the tibia, correlations were observed between TBS and volumetric densities, cortical thickness, trabecular bone volume, and whole bone stiffness. TBS correlated with all indices of trabecular microarchitecture, except trabecular thickness, after adjustment for body weight. Conclusion: TBS, a measurement technology readily available by DXA, shows promise in the clinical assessment of trabecular microstructure in PHPT.
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An experiment was carried out to determine the root distribution of four grapevine rootstocks (Salt Creek, Dogridge, Courdec 1613, IAC 572) in a coarse texture soil of a commercial growing area in Petrolina County, São Francisco Valley, Brazil. Rootstocks were grafted to a seedless table grape cv. Festival, and irrigated by microsprinkler. Roots were quantified by the trench wall method aided by digital image analysis. Results indicated that roots reached 1 m depth, but few differences among rootstocks were found. All of them presented at least 90 % of the roots distributed until 0.6 m depth, with a greater root presence in the first 0.4 m. The upper 0.6 m can be taken into account as the effective rooting depth for soil and water management.
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Tämä diplomityö liittyy Spektrikuvien tutkimiseen tilastollisen kuvamallin näkökulmasta. Diplomityön ensimmäisessä osassa tarkastellaan tilastollisten parametrien jakaumien vaikutusta väreihin ja korostumiin erilaisissa valaistusolosuhteissa. Havaittiin, että tilastollisten parametrien väliset suhteet eivät riipu valaistusolosuhteista, mutta riippuvat kuvan häiriöttömyydestä. Ilmeni myös, että korkea huipukkuus saattaa aiheutua värikylläisyydestä. Lisäksi työssä kehitettiin tilastolliseen spektrimalliin perustuvaa tekstuurinyhdistämisalgoritmia. Sillä saavutettiin hyviä tuloksia, kun tilastollisten parametrien väliset riippuvuussuhteet olivat voimassa. Työn toisessa osassa erilaisia spektrikuvia tutkittiin käyttäen itsenäistä komponenttien analyysia (ICA). Seuraavia itsenäiseen komponenttien analyysiin tarkoitettuja algoritmia tarkasteltiin: JADE, kiinteän pisteen ICA ja momenttikeskeinen ICA. Tutkimuksissa painotettiin erottelun laatua. Paras erottelu saavutettiin JADE- algoritmilla, joskin erot muiden algoritmien välillä eivät olleet merkittäviä. Algoritmi jakoi kuvan kahteen itsenäiseen, joko korostuneeseen ja korostumattomaan tai kromaattiseen ja akromaattiseen, komponenttiin. Lopuksi pohditaan huipukkuuden suhdetta kuvan ominaisuuksiin, kuten korostuneisuuteen ja värikylläisyyteen. Työn viimeisessä osassa ehdotetaan mahdollisia jatkotutkimuskohteita.
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This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.
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Nitrate is the main form of nitrogen associated with water contamination; the high mobility of this species in soil justifies the concern regarding nitrogen management in agricultural soils. Therefore, the objective of this research was to assess the effect of companion cation on nitrate displacement, by analyzing nitrate transport parameters through Breakthrough Curves (BTCs) and their settings made by numerical model (STANMOD). The experiment was carried out in the Soil and Water Quality Laboratory of the Department of Biosystems Engineering, "Luiz de Queiroz" College of Agriculture in Piracicaba (SP), Brazil. It was performed using saturated soil columns in steady-state flow condition, in which two different sources of inorganic nitrate Ca(NO3)2 and NH4NO3 were applied at a concentration of 50 mg L-1 NO3-. Each column was filled with either a Red-Yellow Oxisol (S1) or an Alfisol (S2). Results are indicative that the companion ion had no effect on nitrate displacement. However, nitrate transport was influenced by soil texture, particle aggregation, solution speed in soil and organic matter presence. Nitrate mobility was higher in the Alfisol (S2).
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Samples of ketchup available on the Brazilian market, one traditional (sweetened with sucrose) and three light versions (sweetened with aspartame, acesulfame-K and a blend of cyclamate, saccharin and stevia) were evaluated for their physicochemical characteristics and sensory profile (Quantitative Descriptive Analysis). Four main groups of attributes were generated: appearance, oral texture, aroma and flavor. The samples presented significant differences in all attributes, except for syneresis and overripe tomato flavor. The highest means for sweetener and bitter tastes and aftertastes were observed for the samples sweetened with acesulfame-K and the blend of sweeteners. Although different characteristics were observed among the products evaluated and, despite the differences in the formulations, the light ketchup sweetened with aspartame was the one that presented properties most similar to those of the traditional ketchup.
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It is important to understand how changes in the product formulation can modify its characteristics. Thus, the objective of this study was to investigate the effect of whey protein concentrate (WPC) on the texture of fat-free dairy desserts. The correlation between instrumental and sensory measurements was also investigated. Four formulations were prepared with different WPC concentrations (0, 1.5, 3.0, and 4.5 wt. (%)) and were evaluated using the texture profile analysis (TPA) and rheology. Thickness was evaluated by nine trained panelists. Formulations containing WPC showed higher firmness, elasticity, chewiness, and gumminess and clearly differed from the control as indicated by principal component analysis (PCA). Flow behavior was characterized as time-dependent and pseudoplastic. Formulation with 4.5% WPC at 10 °C showed the highest thixotropic behavior. Experimental data were fitted to Herschel-Bulkley model. The addition of WPC contributed to the texture of the fat-free dairy dessert. The yield stress, apparent viscosity, and perceived thickness in the dairy desserts increased with WPC concentration. The presence of WPC promotes the formation of a stronger gel structure as a result of protein-protein interactions. The correlation between instrumental parameters and thickness provided practical results for food industries.
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The cellular structure of healthy food products, with added dietary fiber and low in calories, is an important factor that contributes to the assessment of quality, which can be quantified by image analysis of visual texture. This study seeks to compare image analysis techniques (binarization using Otsu’s method and the default ImageJ algorithm, a variation of the iterative intermeans method) for quantification of differences in the crumb structure of breads made with different percentages of whole-wheat flour and fat replacer, and discuss the behavior of the parameters number of cells, mean cell area, cell density, and circularity using response surface methodology. Comparative analysis of the results achieved with the Otsu and default ImageJ algorithms showed a significant difference between the studied parameters. The Otsu method demonstrated the crumb structure of the analyzed breads more reliably than the default ImageJ algorithm, and is thus the most suitable in terms of structural representation of the crumb texture.
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Abstract Caprine Coalho cheese presents great potential for a typical protected designation of origin, considering that this traditional Brazilian cheese presents a slightly salty and acid flavor, combined with a unique texture. This study optimized the HS-SPME-GC-MS methodology for volatile analysis of Coalho cheese, which can be used as a tool to help in the identification of the distinctive aroma profile of this cheese. The conditions of equilibrium time, extraction temperature and time were optimized using the statistical tool factorial experimental design 23, and applying the desirability function. After the evaluation, it was concluded that the optimum extraction conditions comprised equilibrium and extraction time of 20 and 40 minutes, respectively; and ideal extraction temperature of 45 °C. The optimum extraction of volatile compounds in goat Coalho cheese captured 32 volatile compounds: 5 alcohols, 5 esters, 3 ketones, 6 acids, 3 aldehydes, 3 terpenes, and 7 hydrocarbons.
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La texture est un élément clé pour l’interprétation des images de télédétection à fine résolution spatiale. L’intégration de l’information texturale dans un processus de classification automatisée des images se fait habituellement via des images de texture, souvent créées par le calcul de matrices de co-occurrences (MCO) des niveaux de gris. Une MCO est un histogramme des fréquences d’occurrence des paires de valeurs de pixels présentes dans les fenêtres locales, associées à tous les pixels de l’image utilisée; une paire de pixels étant définie selon un pas et une orientation donnés. Les MCO permettent le calcul de plus d’une dizaine de paramètres décrivant, de diverses manières, la distribution des fréquences, créant ainsi autant d’images texturales distinctes. L’approche de mesure des textures par MCO a été appliquée principalement sur des images de télédétection monochromes (ex. images panchromatiques, images radar monofréquence et monopolarisation). En imagerie multispectrale, une unique bande spectrale, parmi celles disponibles, est habituellement choisie pour générer des images de texture. La question que nous avons posée dans cette recherche concerne justement cette utilisation restreinte de l’information texturale dans le cas des images multispectrales. En fait, l’effet visuel d’une texture est créé, non seulement par l’agencement particulier d’objets/pixels de brillance différente, mais aussi de couleur différente. Plusieurs façons sont proposées dans la littérature pour introduire cette idée de la texture à plusieurs dimensions. Parmi celles-ci, deux en particulier nous ont intéressés dans cette recherche. La première façon fait appel aux MCO calculées bande par bande spectrale et la seconde utilise les MCO généralisées impliquant deux bandes spectrales à la fois. Dans ce dernier cas, le procédé consiste en le calcul des fréquences d’occurrence des paires de valeurs dans deux bandes spectrales différentes. Cela permet, en un seul traitement, la prise en compte dans une large mesure de la « couleur » des éléments de texture. Ces deux approches font partie des techniques dites intégratives. Pour les distinguer, nous les avons appelées dans cet ouvrage respectivement « textures grises » et « textures couleurs ». Notre recherche se présente donc comme une analyse comparative des possibilités offertes par l’application de ces deux types de signatures texturales dans le cas spécifique d’une cartographie automatisée des occupations de sol à partir d’une image multispectrale. Une signature texturale d’un objet ou d’une classe d’objets, par analogie aux signatures spectrales, est constituée d’une série de paramètres de texture mesurés sur une bande spectrale à la fois (textures grises) ou une paire de bandes spectrales à la fois (textures couleurs). Cette recherche visait non seulement à comparer les deux approches intégratives, mais aussi à identifier la composition des signatures texturales des classes d’occupation du sol favorisant leur différentiation : type de paramètres de texture / taille de la fenêtre de calcul / bandes spectrales ou combinaisons de bandes spectrales. Pour ce faire, nous avons choisi un site à l’intérieur du territoire de la Communauté Métropolitaine de Montréal (Longueuil) composé d’une mosaïque d’occupations du sol, caractéristique d’une zone semi urbaine (résidentiel, industriel/commercial, boisés, agriculture, plans d’eau…). Une image du satellite SPOT-5 (4 bandes spectrales) de 10 m de résolution spatiale a été utilisée dans cette recherche. Puisqu’une infinité d’images de texture peuvent être créées en faisant varier les paramètres de calcul des MCO et afin de mieux circonscrire notre problème nous avons décidé, en tenant compte des études publiées dans ce domaine : a) de faire varier la fenêtre de calcul de 3*3 pixels à 21*21 pixels tout en fixant le pas et l’orientation pour former les paires de pixels à (1,1), c'est-à-dire à un pas d’un pixel et une orientation de 135°; b) de limiter les analyses des MCO à huit paramètres de texture (contraste, corrélation, écart-type, énergie, entropie, homogénéité, moyenne, probabilité maximale), qui sont tous calculables par la méthode rapide de Unser, une approximation des matrices de co-occurrences, c) de former les deux signatures texturales par le même nombre d’éléments choisis d’après une analyse de la séparabilité (distance de Bhattacharya) des classes d’occupation du sol; et d) d’analyser les résultats de classification (matrices de confusion, exactitudes, coefficients Kappa) par maximum de vraisemblance pour conclure sur le potentiel des deux approches intégratives; les classes d’occupation du sol à reconnaître étaient : résidentielle basse et haute densité, commerciale/industrielle, agricole, boisés, surfaces gazonnées (incluant les golfs) et plans d’eau. Nos principales conclusions sont les suivantes a) à l’exception de la probabilité maximale, tous les autres paramètres de texture sont utiles dans la formation des signatures texturales; moyenne et écart type sont les plus utiles dans la formation des textures grises tandis que contraste et corrélation, dans le cas des textures couleurs, b) l’exactitude globale de la classification atteint un score acceptable (85%) seulement dans le cas des signatures texturales couleurs; c’est une amélioration importante par rapport aux classifications basées uniquement sur les signatures spectrales des classes d’occupation du sol dont le score est souvent situé aux alentours de 75%; ce score est atteint avec des fenêtres de calcul aux alentours de11*11 à 15*15 pixels; c) Les signatures texturales couleurs offrant des scores supérieurs à ceux obtenus avec les signatures grises de 5% à 10%; et ce avec des petites fenêtres de calcul (5*5, 7*7 et occasionnellement 9*9) d) Pour plusieurs classes d’occupation du sol prises individuellement, l’exactitude dépasse les 90% pour les deux types de signatures texturales; e) une seule classe est mieux séparable du reste par les textures grises, celle de l’agricole; f) les classes créant beaucoup de confusions, ce qui explique en grande partie le score global de la classification de 85%, sont les deux classes du résidentiel (haute et basse densité). En conclusion, nous pouvons dire que l’approche intégrative par textures couleurs d’une image multispectrale de 10 m de résolution spatiale offre un plus grand potentiel pour la cartographie des occupations du sol que l’approche intégrative par textures grises. Pour plusieurs classes d’occupations du sol un gain appréciable en temps de calcul des paramètres de texture peut être obtenu par l’utilisation des petites fenêtres de traitement. Des améliorations importantes sont escomptées pour atteindre des exactitudes de classification de 90% et plus par l’utilisation des fenêtres de calcul de taille variable adaptées à chaque type d’occupation du sol. Une méthode de classification hiérarchique pourrait être alors utilisée afin de séparer les classes recherchées une à la fois par rapport au reste au lieu d’une classification globale où l’intégration des paramètres calculés avec des fenêtres de taille variable conduirait inévitablement à des confusions entre classes.
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The present study addresses to understand the sedimentological properties of the coasts of kodungallur and chellanam, central Kerala to bring out the relationship between the textural, mineralogical and geochemical characters with that of the respective environment. The grain size study of the beach ridge sediments from different pits has been investigated at close intervals, which enables to understand the grain size variations with depth. The sediment samples from various pits of the beach ridges indicate that the sediments range primarily from medium to very fine sand, well to moderately sorted, fine to coarse skewed and leptokurtic to platykurtic. The study area is considered as a prograding coast. Variations in grain size down the pit give three phases of beach building activities i.e.; a coarsening upward sequence in the bottom layers, a fining upward in the middle and coarsening upward in the top. Beach ridges are formed by swash built sediments with cross bedding and setting lag type sediments with seaward dipping/horizontal units. Geochemical signatures in the study area have been brought out through the analysis of major and trace elements. Iron is significantly enriched and its control over many trace elements is evident. Copper, chromium, cobalt, lithium, lead and zinc show decreasing trend with depth, while sodium, potassium,strontium,nickel and organic carbon increases. The association of many trace elements with organic carbon has also been established. Dissolution of trace elements in anoxic environment, at depth and reprecipitation in the oxic layers, at near or subsurface, are the major mechanism that brought out the variation of certain environmentally sensitive elements
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Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.
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The continental shelf of southwest coast of India (Kerala) is broader and . flatter compared to that of the east coast. The unique characteristic feature of the study area (innershelf between Narakkal and Purakkad) is the intermittent appearance of 'mud banks' at certain locations during southwest monsoon. The strong seasonality manifests significant changes in the wind, waves, currents, rainfall, drainage etc., along this area. Peculiar geomorphological variation with high, mid and lowlands in the narrow strip of the hinterland, the geological formations mainly consisting of rocks of metamorphic origin and the humid tropical weathering conditions play significant role in regulating the shelf sedimentation. A complementary pattern of distri bution is observed for clay that shows an abundance in the nearshore. Silt, to a major extent, depicts semblance with clay distribution . Summation of the total asymmetry of grain size distribution are inferred from the variation of skewness and kurtosis.Factor I implies a low energy regime where the transportation and deposition phases are controlled mostly by pelagic suspension process as the factor loadings are dominant on finer phi sizes. The second Factor is inferred to be the result of a high energy regime which gives higher loadings on coarser size fractions. The third Factor which might be a transition phase (medium energy regime) representing the resultant flux of coastal circulation of the re-suspension/deposition and an onshoreoffshore advection by reworking and co-deposition of relict and modern sediments. The spatial variations of the energy regime based on the three end-member factor model exhibits high energy zone in the seaward portion transcending to a low energy one towards the coast.From the combined analysis of granulometry and SEM studies, it is concluded that the sandy patches beyond 20 m depth are of relict nature. They are the resultant responses of beach activity during the lower stand of sea level in the Holocene. Re-crystallisation features on the quartz grains indicate that they were exposed to subaerial weathering process subsequent to thei r deposition
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Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.