998 resultados para texture classification


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Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.

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The country has witnessed tremendous increase in the vehicle population and increased axle loading pattern during the last decade, leaving its road network overstressed and leading to premature failure. The type of deterioration present in the pavement should be considered for determining whether it has a functional or structural deficiency, so that appropriate overlay type and design can be developed. Structural failure arises from the conditions that adversely affect the load carrying capability of the pavement structure. Inadequate thickness, cracking, distortion and disintegration cause structural deficiency. Functional deficiency arises when the pavement does not provide a smooth riding surface and comfort to the user. This can be due to poor surface friction and texture, hydro planning and splash from wheel path, rutting and excess surface distortion such as potholes, corrugation, faulting, blow up, settlement, heaves etc. Functional condition determines the level of service provided by the facility to its users at a particular time and also the Vehicle Operating Costs (VOC), thus influencing the national economy. Prediction of the pavement deterioration is helpful to assess the remaining effective service life (RSL) of the pavement structure on the basis of reduction in performance levels, and apply various alternative designs and rehabilitation strategies with a long range funding requirement for pavement preservation. In addition, they can predict the impact of treatment on the condition of the sections. The infrastructure prediction models can thus be classified into four groups, namely primary response models, structural performance models, functional performance models and damage models. The factors affecting the deterioration of the roads are very complex in nature and vary from place to place. Hence there is need to have a thorough study of the deterioration mechanism under varied climatic zones and soil conditions before arriving at a definite strategy of road improvement. Realizing the need for a detailed study involving all types of roads in the state with varying traffic and soil conditions, the present study has been attempted. This study attempts to identify the parameters that affect the performance of roads and to develop performance models suitable to Kerala conditions. A critical review of the various factors that contribute to the pavement performance has been presented based on the data collected from selected road stretches and also from five corporations of Kerala. These roads represent the urban conditions as well as National Highways, State Highways and Major District Roads in the sub urban and rural conditions. This research work is a pursuit towards a study of the road condition of Kerala with respect to varying soil, traffic and climatic conditions, periodic performance evaluation of selected roads of representative types and development of distress prediction models for roads of Kerala. In order to achieve this aim, the study is focused into 2 parts. The first part deals with the study of the pavement condition and subgrade soil properties of urban roads distributed in 5 Corporations of Kerala; namely Thiruvananthapuram, Kollam, Kochi, Thrissur and Kozhikode. From selected 44 roads, 68 homogeneous sections were studied. The data collected on the functional and structural condition of the surface include pavement distress in terms of cracks, potholes, rutting, raveling and pothole patching. The structural strength of the pavement was measured as rebound deflection using Benkelman Beam deflection studies. In order to collect the details of the pavement layers and find out the subgrade soil properties, trial pits were dug and the in-situ field density was found using the Sand Replacement Method. Laboratory investigations were carried out to find out the subgrade soil properties, soil classification, Atterberg limits, Optimum Moisture Content, Field Moisture Content and 4 days soaked CBR. The relative compaction in the field was also determined. The traffic details were also collected by conducting traffic volume count survey and axle load survey. From the data thus collected, the strength of the pavement was calculated which is a function of the layer coefficient and thickness and is represented as Structural Number (SN). This was further related to the CBR value of the soil and the Modified Structural Number (MSN) was found out. The condition of the pavement was represented in terms of the Pavement Condition Index (PCI) which is a function of the distress of the surface at the time of the investigation and calculated in the present study using deduct value method developed by U S Army Corps of Engineers. The influence of subgrade soil type and pavement condition on the relationship between MSN and rebound deflection was studied using appropriate plots for predominant types of soil and for classified value of Pavement Condition Index. The relationship will be helpful for practicing engineers to design the overlay thickness required for the pavement, without conducting the BBD test. Regression analysis using SPSS was done with various trials to find out the best fit relationship between the rebound deflection and CBR, and other soil properties for Gravel, Sand, Silt & Clay fractions. The second part of the study deals with periodic performance evaluation of selected road stretches representing National Highway (NH), State Highway (SH) and Major District Road (MDR), located in different geographical conditions and with varying traffic. 8 road sections divided into 15 homogeneous sections were selected for the study and 6 sets of continuous periodic data were collected. The periodic data collected include the functional and structural condition in terms of distress (pothole, pothole patch, cracks, rutting and raveling), skid resistance using a portable skid resistance pendulum, surface unevenness using Bump Integrator, texture depth using sand patch method and rebound deflection using Benkelman Beam. Baseline data of the study stretches were collected as one time data. Pavement history was obtained as secondary data. Pavement drainage characteristics were collected in terms of camber or cross slope using camber board (slope meter) for the carriage way and shoulders, availability of longitudinal side drain, presence of valley, terrain condition, soil moisture content, water table data, High Flood Level, rainfall data, land use and cross slope of the adjoining land. These data were used for finding out the drainage condition of the study stretches. Traffic studies were conducted, including classified volume count and axle load studies. From the field data thus collected, the progression of each parameter was plotted for all the study roads; and validated for their accuracy. Structural Number (SN) and Modified Structural Number (MSN) were calculated for the study stretches. Progression of the deflection, distress, unevenness, skid resistance and macro texture of the study roads were evaluated. Since the deterioration of the pavement is a complex phenomena contributed by all the above factors, pavement deterioration models were developed as non linear regression models, using SPSS with the periodic data collected for all the above road stretches. General models were developed for cracking progression, raveling progression, pothole progression and roughness progression using SPSS. A model for construction quality was also developed. Calibration of HDM–4 pavement deterioration models for local conditions was done using the data for Cracking, Raveling, Pothole and Roughness. Validation was done using the data collected in 2013. The application of HDM-4 to compare different maintenance and rehabilitation options were studied considering the deterioration parameters like cracking, pothole and raveling. The alternatives considered for analysis were base alternative with crack sealing and patching, overlay with 40 mm BC using ordinary bitumen, overlay with 40 mm BC using Natural Rubber Modified Bitumen and an overlay of Ultra Thin White Topping. Economic analysis of these options was done considering the Life Cycle Cost (LCC). The average speed that can be obtained by applying these options were also compared. The results were in favour of Ultra Thin White Topping over flexible pavements. Hence, Design Charts were also plotted for estimation of maximum wheel load stresses for different slab thickness under different soil conditions. The design charts showed the maximum stress for a particular slab thickness and different soil conditions incorporating different k values. These charts can be handy for a design engineer. Fuzzy rule based models developed for site specific conditions were compared with regression models developed using SPSS. The Riding Comfort Index (RCI) was calculated and correlated with unevenness to develop a relationship. Relationships were developed between Skid Number and Macro Texture of the pavement. The effort made through this research work will be helpful to highway engineers in understanding the behaviour of flexible pavements in Kerala conditions and for arriving at suitable maintenance and rehabilitation strategies. Key Words: Flexible Pavements – Performance Evaluation – Urban Roads – NH – SH and other roads – Performance Models – Deflection – Riding Comfort Index – Skid Resistance – Texture Depth – Unevenness – Ultra Thin White Topping

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The evolution of coast through geological time scale is dependent on the transgression-regression event subsequent to the rise or fall of sea level. This event is accounted by investigation of the vertical sediment deposition patterns and their interrelationship for paleo-enviornmental reconstruction. Different methods like sedimentological (grain size and micro-morphological) and geochemical (elemental relationship) analyses as well as radiocarbon dating are generally used to decipher the sea level changes and paleoclimatic conditions of the Quaternary sediment sequence. For the Indian coast with a coastline length of about 7500 km, studies on geological and geomorphological signatures of sea level changes during the Quaternary were reported in general by researchers during the last two decades. However, for the southwest coast of India particularily Kerala which is famous for its coastal landforms comprising of estuaries, lagoons, backwaters, coastal plains, cliffs and barrier beaches, studies pertaining to the marine transgression-regression events in the southern region are limited. The Neendakara-Kayamkulam coastal stretch in central Kerala where the coast is manifested with shore parallel Kayamkulam Lagoon on one side and shore perpendicular Ashtamudi Estuary on the other side indicating existence of an uplifted prograded coastal margin followed by barrier beaches, backwater channels, ridge and runnel topography is an ideal site for studying such events. Hence the present study has been taken up in this context to address the gap area. The location for collection of core samples representing coastal plain, estuarylagoon and offshore regions have been identified based on published literature and available sedimentary records. The objectives of the research work are:  To study the lithological variations and depositional environments of sediment cores along the coastal plain, estuary-lagoon and offshore regions between Kollam and Kayamkulam in the central Kerala coast  To study the transportation and diagenetic history of sediments in the area  To investigate the geochemical characterization of sediments and to elucidate the source-sink relationship  To understand the marine transgression-regression events and to propose a conceptual model for the region The thesis comprises of 8 chapters. The first chapter embodies the preamble for the selection and significance of this research work. The study area is introduced with details on its physiographical, geological, geomorphological, rainfall and climate information. A review of literature, compiling the research on different aspects such as physico-chemical, geomorphological, tectonics, transgression-regression events are presented in the second chapter and they are broadly classified into three viz:- International, National and Kerala. The field data collection and laboratory analyses adopted in the research work are discussed in the third chapter. For collection of sediment core samples from the coastal plains, rotary drilling method was employed whereas for the estuary-lagoon and offshore locations the gravity/piston corer method was adopted. The collected subsurficial samples were analysed for texture, surface micro-texture, elemental analysis, XRD and radiocarbon dating techniques for age determination. The fourth chapter deals with the textural analysis of the core samples collected from various predefined locations of the study area. The result reveals that the Ashtamudi Estuary is composed of silty clay to clayey type of sediments whereas offshore cores are carpeted with silty clay to relict sand. Investigation of the source of sediments deposited in the coastal plain located on either side of the estuary indicates the dominance of terrigenous to marine origin in the southern region whereas it is predominantly of marine origin towards the north. Further the hydrodynamic conditions as well as the depositional enviornment of the sediment cores are elucidated based on statistical parameters that decipher the deposition pattern at various locations viz., coastal plain (open to closed basin), Ashtamudi Estuary (partially open to restricted estuary to closed basin) and offshore (open channel). The intensity of clay minerals is also discussed. From the results of radiocarbon dating the sediment depositional environments were deciphered.The results of the microtextural study of sediment samples (quartz grains) using Scanning Electron Microscope (SEM) are presented in the fifth chapter. These results throw light on the processes of transport and diagenetic history of the detrital sediments. Based on the lithological variations, selected quartz grains of different environments were also analysed. The study indicates that the southern coastal plain sediments were transported and deposited mechanically under fluvial environment followed by diagenesis under prolonged marine incursion. But in the case of the northern coastal plain, the sediments were transported and deposited under littoral environment indicating the dominance of marine incursion through mechanical as well as chemical processes. The quartz grains of the Ashtamudi Estuary indicate fluvial origin. The surface texture features of the offshore sediments suggest that the quartz grains are of littoral origin and represent the relict beach deposits. The geochemical characterisation of sediment cores based on geochemical classification, sediment maturity, palaeo-weathering and provenance in different environments are discussed in the sixth chapter. In the seventh chapter the integration of multiproxies data along with radiocarbon dates are presented and finally evolution and depositional history based on transgression–regression events is deciphered. The eighth chapter summarizes the major findings and conclusions of the study with recommendation for future work.

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Cochin estuarine system is among the most productive aquatic environment along the Southwest coast of India, exhibits unique ecological features and possess greater socioeconomic relevance. Serious investigations carried out during the past decades on the hydro biogeochemical variables pointed out variations in the health and ecological functioning of this ecosystem. Characterisation of organic matter in the estuary has been attempted in many investigations. But detailed studies covering the degradation state of organic matter using molecular level approach is not attempted. The thesis entitled Provenance, Isolation and Characterisation of Organic Matter in the Cochin Estuarine Sediment-“ A Diagenetic Amino Acid Marker Scenario” is an integrated approach to evaluate the source, quantity, quality, and degradation state of the organic matter in the surface sediments of Cochin estuarine system with the combined application of bulk and molecular level tools. Sediment and water samples from nine stations situated at Cochin estuary were collected in five seasonal sampling campaigns, for the biogeochemical assessment and their distribution pattern of sedimentary organic matter. The sampling seasons were described and abbreviated as follows: April- 2009 (pre monsoon: PRM09), August-2009 (monsoon: MON09), January-2010 (post monsoon: POM09), April-2010 (pre monsoon: PRM10) and September- 2012 (monsoon: MON12). In order to evaluate the general environmental conditions of the estuary, water samples were analysed for water quality parameters, chlorophyll pigments and nutrients by standard methods. Investigations suggested the fact that hydrographical variables and nutrients in Cochin estuary supports diverse species of flora and fauna. Moreover the sedimentary variables such as pH, Eh, texture, TOC, fractions of nitrogen and phosphorous were determined to assess the general geochemical setting as well as redox status. The periodically fluctuating oxic/ anoxic conditions and texture serve as the most significant variables controlling other variables of the aquatic environment. The organic matter in estuary comprise of a complex mixture of autochthonous as well as allochthonous materials. Autochthonous input is limited or enhanced by the nutrient elements like N and P (in their various fractions), used as a tool to evaluate their bioavailability. Bulk parameter approach like biochemical composition, stoichiometric elemental ratios and stable carbon isotope ratio was also employed to assess the quality and quantity of sedimentary organic matter in the study area. Molecular level charactersation of free sugars and amino acids were carried out by liquid chromatographic techniques. Carbohydrates are the products of primary production and their occurrence in sediments as free sugars can provide information on the estuarine productivity. Amino acid biogeochemistry provided implications on the system productivity, nature of organic matter as well as degradation status of the sedimentary organic matter in the study area. The predominance of carbohydrates over protein indicated faster mineralisation of proteinaceous organic matter in sediments and the estuary behaves as a detrital trap for the accumulation of aged organic matter. The higher lipid content and LPD/CHO ratio pointed towards the better food quality that supports benthic fauna and better accumulation of lipid compounds in the sedimentary environment. Allochthonous addition of carbohydrates via terrestrial run off was responsible for the lower PRT/CHO ratio estimated in thesediments and the lower ratios also denoted a detrital heterotrophic environment. Biopolymeric carbon and the algal contribution to BPC provided important information on the better understanding the trophic state of the estuarine system and the higher values of chlorophyll-a to phaeophytin ratio indicated deposition of phytoplankton to sediment at a rapid rate. The estimated TOC/TN ratios implied the combined input of both terrestrial and autochthonous organic matter to sedimentsAmong the free sugars, depleted levels of glucose in sediments in most of the stations and abundance of mannose at station S5 was observed during the present investigation. Among aldohexoses, concentration of galactose was found to be higher in most of the stationsRelative abundance of AAs in the estuarine sediments based on seasons followed the trend: PRM09-Leucine > Phenylalanine > Argine > Lysine, MON09-Lysine > Aspartic acid > Histidine > Tyrosine > Phenylalanine, POM09-Lysine > Histadine > Phenyalanine > Leucine > Methionine > Serine > Proline > Aspartic acid, PRM10-Valine > Aspartic acid > Histidine > Phenylalanine > Serine > Proline, MON12-Lysine > Phenylalanine > Aspartic acid > Histidine > Valine > Tyrsine > MethionineThe classification of study area into three zones based on salinity was employed in the present study for the sake of simplicity and generalized interpretations. The distribution of AAs in the three zones followed the trend: Fresh water zone (S1, S2):- Phenylalanine > Lysine > Aspartic acid > Methionine > Valine ῀ Leucine > Proline > Histidine > Glycine > Serine > Glutamic acid > Tyrosine > Arginine > Alanine > Threonine > Cysteine > Isoleucine. Estuarine zone (S3, S4, S5, S6):- Lysine > Aspartic acid > Phenylalanine > Leucine > Valine > Histidine > Methionine > Tyrosine > Serine > Glutamic acid > Proline > Glycine > Arginine > Alanine > Isoleucine > Cysteine > Threonine. Riverine /Industrial zone (S7, S8, S9):- Phenylalanine > Lysine > Aspartic acid > Histidine > Serine > Arginine > Tyrosine > Leucine > Methionine > Glutamic acid > Alanine > Glycine > Cysteine > Proline > Isoleucine > Threonine > Valine. The abundance of AAs like glutamic acid, aspartic acid, isoleucine, valine, tyrosine, and phenylalanine in sediments of the study area indicated freshly derived organic matter.

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As a result of the drive towards waste-poor world and reserving the non-renewable materials, recycling the construction and demolition materials become very essential. Now reuse of the recycled concrete aggregate more than 4 mm in producing new concrete is allowed but with natural sand a fine aggregate while. While the sand portion that represent about 30\% to 60\% of the crushed demolition materials is disposed off. To perform this research, recycled concrete sand was produced in the laboratory while nine recycled sands produced from construction and demolitions materials and two sands from natural crushed limestone were delivered from three plants. Ten concrete mix designs representing the concrete exposition classes XC1, XC2, XF3 and XF4 according to European standard EN 206 were produced with partial and full replacement of natural sand by the different recycled sands. Bituminous mixtures achieving the requirements of base courses according to Germany standards and both base and binder courses according to Egyptian standards were produced with the recycled sands as a substitution to the natural sands. The mechanical properties and durability of concrete produced with the different recycled sands were investigated and analyzed. Also the volumetric analysis and Marshall test were performed hot bituminous mixtures produced with the recycled sands. According to the effect of replacement the natural sand by the different recycled sands on the concrete compressive strength and durability, the recycled sands were classified into three groups. The maximum allowable recycled sand that can be used in the different concrete exposition class was determined for each group. For the asphalt concrete mixes all the investigated recycled sands can be used in mixes for base and binder courses up to 21\% of the total aggregate mass.

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Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

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Texture provides one cue for identifying the physical cause of an intensity edge, such as occlusion, shadow, surface orientation or reflectance change. Marr, Julesz, and others have proposed that texture is represented by small lines or blobs, called 'textons' by Julesz [1981a], together with their attributes, such as orientation, elongation, and intensity. Psychophysical studies suggest that texture boundaries are perceived where distributions of attributes over neighborhoods of textons differ significantly. However, these studies, which deal with synthetic images, neglect to consider two important questions: How can these textons be extracted from images of natural scenes? And how, exactly, are texture boundaries then found? This thesis proposes answers to these questions by presenting an algorithm for computing blobs from natural images and a statistic for measuring the difference between two sample distributions of blob attributes. As part of the blob detection algorithm, methods for estimating image noise are presented, which are applicable to edge detection as well.