Search results for: texture and pixel
501 Exploring Structure of Human Chromosomes Using Fluorescence Lifetime Imaging
Authors: A. Bhartiya, S. Botchway, M. Yusuf, I. Robinson
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Chromatin condensation is maintained by DNA-based proteins and some divalent cations (Mg²⁺, Ca²⁺, etc.). Condensation process during cell division maintains structural and functional organizations of chromosomes by transferring genetic information correctly to daughter cells. Fluorescence Lifetime Imaging (FLIM) technique measures the fluorescence decay of fixed human chromosomes by calculating the lifetime of fluorophores at a pixel x of the arrival of each photon as a function of time delay t, following excitation with a laser pulse. Fixed metaphase human chromosomes were labelled with DNA-binding dye, DAPI and later DAPI fluorescence lifetime measured using multiphoton microscopy. 5 out of 23 pairs of human chromosomes shown shorter lifetime at the centromere region, differentiating proportion of compaction along the length of chromosomes. Different lifetime was observed in a condensed and de-condensed chromosome. It clearly indicates the involvement of divalent cations in the process of condensation.Keywords: divalent cations, FLIM (Fluorescence Lifetime Imaging), human chromosomes, multiphoton microscopy
Procedia PDF Downloads 288500 Petrographic Properties of Sedimentary-Exhalative Type Ores of Filizchay Polymetallic Deposit
Authors: Samir Verdiyev, Fuad Huseynov, Islam Guliyev, Coşqun İsmayıl
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The Filizchay polymetallic deposit is located on the southern slope of the Greater Caucasus Mountain Range, northwest of Azerbaijan in the Balaken district. Filizchay is the largest polymetallic deposit in the region and the second-largest polymetallic deposit in Europe. The mineral deposits in the region are associated with two different geodynamic evolutions that began with the Mesozoic collision along the Eurasian continent and the formation of a magmatic arc after the collision and continued with subduction in the Cenozoic. The bedrocks associated with Filizchay mineralization are Early Jurassic aged. The stratigraphic sequence of the deposit is consisting of black metamorphic clay shales, sandstones, and ore layers. Shales, sandstones, and siltstones are encountered in the upper and middle sections of the ore body, while only shales are observed at the lowest ranges. The ore body is mainly layered by the geometric structure of the bedrock; folding can be observed in the ore layers along with the bedrock foliation, and just in few points indirect laying due to the metamorphism. This suggests that the Filizchay ore mineralization is syngenetic, which is proved by the mineralization by the bedrock. To determine the ore petrography properties of the Filizchay deposit, samples were collected from the region where the ore is concentrated, and a polished section was prepared. These collected samples were examined under the mineralogical microscope to reveal the paragenesis of the mineralization and to explain the relation of ore minerals to each other. In this study, macroscopically observed minerals and textures of these minerals were used in the cores revealed during drilling exploration made by AzerGold CJS company. As a result of all these studies, it has been determined that there are three main mineralization types in the Filizchay deposit: banded, massive, and veinlet ores. The mineralization is in the massive pyrite; furthermore, the basis of the ore-mass contains pyrite, chalcopyrite, sphalerite, and galena. The pyrite in some parts of the ore body transformed to pyrrhotite as a result of metamorphism. Pyrite-chalcopyrite, pyrite-sphalerite-galena, pyrite-pyrrhotite mineral assemblages were determined during microscopic studies of mineralization. The replacement texture is more developed in Filizchay ores. The banded polymetallic type mineralization and near bedrocks are cut by quartz-carbonate veins. The geotectonic position and lithological conditions of the Filizchay deposit, the texture, and interrelationship of the sulfide mineralization indicate that it is a sedimentary-exhalative type of Au-Cu-Ag-Zn-Pb polymetallic deposit that is genetically related to the massive sulfide deposits.Keywords: Balaken, Filizchay, metamorphism, polymetallic mineralization
Procedia PDF Downloads 212499 Difference Expansion Based Reversible Data Hiding Scheme Using Edge Directions
Authors: Toshanlal Meenpal, Ankita Meenpal
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A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.Keywords: information hiding, wedge direction, difference expansion, integer transform
Procedia PDF Downloads 484498 Assessment of Planet Image for Land Cover Mapping Using Soft and Hard Classifiers
Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi
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Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers
Procedia PDF Downloads 188497 Oil Pollution Analysis of the Ecuadorian Rainforest Using Remote Sensing Methods
Authors: Juan Heredia, Naci Dilekli
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The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing
Procedia PDF Downloads 164496 Rainfall Estimation Using Himawari-8 Meteorological Satellite Imagery in Central Taiwan
Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen
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The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.Keywords: estimation, Himawari-8, rainfall, satellite imagery
Procedia PDF Downloads 194495 Quantification of Magnetic Resonance Elastography for Tissue Shear Modulus using U-Net Trained with Finite-Differential Time-Domain Simulation
Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang
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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation
Procedia PDF Downloads 68494 The Relation Between Protein-Protein and Polysaccharide-Protein Interaction on Aroma Release from Brined Cheese Model
Authors: Mehrnaz Aminifar
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The relation between textural parameters and casein network on release of aromatic compounds was investigated over 90-days of ripening. Low DE maltodextrin and WPI were used to modify the textural properties of low fat brined cheese. Hardness, brittleness and compaction of casein network were affected by addition of maltodextrin and WPI. Textural properties and aroma release from cheese texture were affected by interaction of WPI protein-cheese protein and maltodexterin-cheese protein.Keywords: aroma release, brined cheese, maltodexterin, WPI
Procedia PDF Downloads 355493 Morphological and Optical Properties of (Al, In) Doped ZnO Thin Films Textured (103) by Sol-Gel Method
Authors: S. Benzitouni, M. Zaabat, A. Mahdjoub, A. Benaboud, T.Saidani
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To improve the physical properties of ZnO nanostructures textured (103) by sol-gel dip coating method, Al and In are used as dopant with different weight ratios (5%, 10%). The comparative study between Al doped ZnO thin films (AZO) and In doped ZnO (IZO) are made by different analysis technic. XRD showed that the films are Pollycristallins with hexagonal wûrtzite structure and preferred orientation (002) and (103). UV-Vis spectroscopy showed that all films have a high transmission (> 85%); the interference fringes are only observed for IZO. The optical gap is reduced due to the introduction of In (minimum value is 3.12 eV), but increased in the presence of Al (maximum value is 3.34 eV). The thickness of the layers was obtained by modeling (using Forouhi Bloomer method). AFM used to observe the surface texture of the films and determined grain size and surface roughness (RMS) which varies in a small range [3.14 to 1.25] nm.Keywords: ZnO, optical gap, roughness (RMS), nanostructures
Procedia PDF Downloads 326492 Soils Properties of Alfisols in the Nicoya Peninsula, Guanacaste, Costa Rica
Authors: Elena Listo, Miguel Marchamalo
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This research studies the soil properties located in the watershed of Jabillo River in the Guanacaste province, Costa Rica. The soils are classified as Alfisols (T. Haplustalfs), in the flatter parts with grazing as Fluventic Haplustalfs or as a consequence of bad drainage as F. Epiaqualfs. The objective of this project is to define the status of the soil, to use remote sensing as a tool for analyzing the evolution of land use and determining the water balance of the watershed in order to improve the efficiency of the water collecting systems. Soil samples were analyzed from trial pits taken from secondary forests, degraded pastures, mature teak plantation, and regrowth -Tectona grandis L. F.- species developed favorably in the area. Furthermore, to complete the study, infiltration measurements were taken with an artificial rainfall simulator, as well as studies of soil compaction with a penetrometer, in points strategically selected from the different land uses. Regarding remote sensing, nearly 40 data samples were collected per plot of land. The source of radiation is reflected sunlight from the beam and the underside of leaves, bare soil, streams, roads and logs, and soil samples. Infiltration reached high levels. The majority of data came from the secondary forest and mature planting due to a high proportion of organic matter, relatively low bulk density, and high hydraulic conductivity. Teak regrowth had a low rate of infiltration because the studies made regarding the soil compaction showed a partial compaction over 50 cm. The secondary forest presented a compaction layer from 15 cm to 30 cm deep, and the degraded pasture, as a result of grazing, in the first 15 cm. In this area, the alfisols soils have high content of iron oxides, a fact that causes a higher reflectivity close to the infrared region of the electromagnetic spectrum (around 700mm), as a result of clay texture. Specifically in the teak plantation where the reflectivity reaches values of 90 %, this is due to the high content of clay in relation to others. In conclusion, the protective function of secondary forests is reaffirmed with regards to erosion and high rate of infiltration. In humid climates and permeable soils, the decrease of runoff is less, however, the percolation increases. The remote sensing indicates that being clay soils, they retain moisture in a better way and it means a low reflectivity despite being fine texture.Keywords: alfisols, Costa Rica, infiltration, remote sensing
Procedia PDF Downloads 696491 Landslide Hazard Assessment Using Physically Based Mathematical Models in Agricultural Terraces at Douro Valley in North of Portugal
Authors: C. Bateira, J. Fernandes, A. Costa
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The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards
Procedia PDF Downloads 178490 A Study on the Mechanism of the Regeneration of ‘Villages-in-City’ under Rapid Urbanization: Cases Study of Luojiazhuang
Authors: Mengying Du, Xiang Chen
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‘villages-in-city’ is the unique product of rapid urbanization in China which embodies the contradiction between historical context and urbanization. This article mainly analyzes the corresponding strategy to the common problems such as urban texture, historical context, community structure, and industry pattern during the regeneration of ‘villages-in-city’ of Luojiazhuang. Taking government investment, community demands, the trend of urban renewal and transformation models of the ‘villages-in-city’ into consideration, the author propose a mechanism to balance those factors, and to achieve mutual confirmation with the instance of Luojiazhuang.Keywords: community demands, historical context, villages-in-city, urbanization
Procedia PDF Downloads 309489 Experimental Analysis of the Origins of the Anisotropy Behavior in the 2017 AA Aluminum Alloy
Authors: May Abdelghani
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The present work is devoted to the study of the microstructural anisotropy in mechanical cyclic behavior of the 2017AA aluminum alloy which is widely used in the aerospace industry. The main purpose of the study is to investigate the microstructural origins of this anisotropy already confirmed in our previous work in 2017AA aluminum alloy. To do this, we have used the microstructural analysis resources such as Scanning Electron Microscope (SEM) to see the differences between breaks from different directions of cyclic loading. Another resource of investigation was used in this study is that the EBSD method, which allows us to obtain a mapping of the crystallographic texture of our material. According to the obtained results in the microscopic analysis, we are able to identify the origins of the anisotropic behavior at the macroscopic scale.Keywords: fatigue damage, cyclic behavior, anisotropy, microstructural analysis
Procedia PDF Downloads 412488 A Method against Obsolescence of Three-Dimensional Archaeological Collection. Two Cases of Study from Qubbet El-Hawa Necropolis, Aswan, Egypt
Authors: L. Serrano-Lara, J.M Alba-Gómez
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Qubbet el–Hawa Project has been documented archaeological artifacts as 3d models by laser scanning technique since 2015. Currently, research has obtained the right methodology to develop a high accuracy photographic texture for each geometrical 3D model. Furthermore, the right methodology to attach the complete digital surrogate into a 3DPDF document has been obtained; it is used as a catalogue worksheet that brings archaeological data and, at the same time, allows us to obtain precise measurements, volume calculations and cross-section mapping of each scanned artifact. This validated archaeological documentation is the first step for dissemination, application as Qubbet el-Hawa Virtual Museum, and, moreover, multi-sensory experience through 3D print archaeological artifacts. Material culture from four funerary complexes constructed in West Aswan has become physical replicas opening the archaeological research process itself and offering creative possibilities on museology or educational projects. This paper shares a method of acquiring texture for scanning´s output product in order to achieve a 3DPDF archaeological cataloguing, and, on the other hand, to allow the colorfully 3D printing of singular archaeological artifacts. The proposed method has undergone two concrete cases, a polychrome wooden ushabti, and, a cartonnage mask belonging to a lady, bought recovered on intact tomb QH34aa. Both 3D model results have been implemented on three main applications, archaeological 3D catalogue, public dissemination activities, and the 3D artifact model in a bachelor education program. Due to those three already mentioned applications, productive interaction among spectator and three-dimensional artifact have been increased; moreover, functionality as archaeological documentation has been consolidated. Finding the right methodology to assign a specific color to each vector on the geometric 3D model, we had been achieved two essential archaeological applications. Firstly, 3DPDF as a display document for an archaeological catalogue, secondly, the possibility to obtain a colored 3d printed object to be displayed in public exhibitions. Obsolescences 3D models have become updated archaeological documentation of QH43aa tomb cultural material. Therefore, Qubbet el-Hawa Project has been actualized the educational potential of its results thanks to a multi-sensory experience that arose from 3d scanned´s archaeological artifacts.Keywords: 3D printed, 3D scanner, Middle Kingdom, Qubbet el-Hawa necropolis, virtual archaeology
Procedia PDF Downloads 143487 Bed Evolution under One-Episode Flushing in a Truck Sewer in Paris, France
Authors: Gashin Shahsavari, Gilles Arnaud-Fassetta, Alberto Campisano, Roberto Bertilotti, Fabien Riou
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Sewer deposits have been identified as a major cause of dysfunctions in combined sewer systems regarding sewer management, which induces different negative consequents resulting in poor hydraulic conveyance, environmental damages as well as worker’s health. In order to overcome the problematics of sedimentation, flushing has been considered as the most operative and cost-effective way to minimize the sediments impacts and prevent such challenges. Flushing, by prompting turbulent wave effects, can modify the bed form depending on the hydraulic properties and geometrical characteristics of the conduit. So far, the dynamics of the bed-load during high-flow events in combined sewer systems as a complex environment is not well understood, mostly due to lack of measuring devices capable to work in the “hostile” in combined sewer system correctly. In this regards, a one-episode flushing issue from an opening gate valve with weir function was carried out in a trunk sewer in Paris to understanding its cleansing efficiency on the sediments (thickness: 0-30 cm). During more than 1h of flushing within 5 m distance in downstream of this flushing device, a maximum flowrate and a maximum level of water have been recorded at 5 m in downstream of the gate as 4.1 m3/s and 2.1 m respectively. This paper is aimed to evaluate the efficiency of this type of gate for around 1.1 km (from the point -50 m to +1050 m in downstream from the gate) by (i) determining bed grain-size distribution and sediments evolution through the sewer channel, as well as their organic matter content, and (ii) identifying sections that exhibit more changes in their texture after the flush. For the first one, two series of sampling were taken from the sewer length and then analyzed in laboratory, one before flushing and second after, at same points among the sewer channel. Hence, a non-intrusive sampling instrument has undertaken to extract the sediments smaller than the fine gravels. The comparison between sediments texture after the flush operation and the initial state, revealed the most modified zones by the flush effect, regarding the sewer invert slope and hydraulic parameters in the zone up to 400 m from the gate. At this distance, despite the increase of sediment grain-size rages, D50 (median grain-size) varies between 0.6 mm and 1.1 mm compared to 0.8 mm and 10 mm before and after flushing, respectively. Overall, regarding the sewer channel invert slope, results indicate that grains smaller than sands (< 2 mm) are more transported to downstream along about 400 m from the gate: in average 69% before against 38% after the flush with more dispersion of grain-sizes distributions. Furthermore, high effect of the channel bed irregularities on the bed material evolution has been observed after the flush.Keywords: bed-load evolution, combined sewer systems, flushing efficiency, sediments transport
Procedia PDF Downloads 404486 Evaluation of the Incorporation of Modified Starch in Puff Pastry Dough by Mixolab Rheological Analysis
Authors: Alejandra Castillo-Arias, Carlos A. Fuenmayor, Carlos M. Zuluaga-Domínguez
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The connection between health and nutrition has driven the food industry to explore healthier and more sustainable alternatives. Key strategies to enhance nutritional quality and extend shelf life include reducing saturated fats and incorporating natural ingredients. One area of focus is the use of modified starch in baked goods, which has attracted significant interest in food science and industry due to its functional benefits. Modified starches are commonly used for their gelling, thickening, and water-retention properties. Derived from sources like waxy corn, potatoes, tapioca, or rice, these polysaccharides improve thermal stability and resistance to dough. The use of modified starch enhances the texture and structure of baked goods, which is crucial for consumer acceptance. In this study, it was evaluated the effects of modified starch inclusion on dough used for puff pastry elaboration, measured with Mixolab analysis. This technique assesses flour quality by examining its behavior under varying conditions, providing a comprehensive profile of its baking properties. The analysis included measurements of water absorption capacity, dough development time, dough stability, softening, final consistency, and starch gelatinization. Each of these parameters offers insights into how the flour will perform during baking and the quality of the final product. The performance of wheat flour with varying levels of modified starch inclusion (10%, 20%, 30%, and 40%) was evaluated through Mixolab analysis, with a control sample consisting of 100% wheat flour. Water absorption, gluten content, and retrogradation indices were analyzed to understand how modified starch affects dough properties. The results showed that the inclusion of modified starch increased the absorption index, especially at levels above 30%, indicating a dough with better handling qualities and potentially improved texture in the final baked product. However, the reduction in wheat flour resulted in a lower kneading index, affecting dough strength. Conversely, incorporating more than 20% modified starch reduced the retrogradation index, indicating improved stability and resistance to crystallization after cooling. Additionally, the modified starch improved the gluten index, contributing to better dough elasticity and stability, providing good structural support and resistance to deformation during mixing and baking. As expected, the control sample exhibited a higher amylase index, due to the presence of enzymes in wheat flour. However, this is of low concern in puff pastry dough, as amylase activity is more relevant in fermented doughs, which is not the case here. Overall, the use of modified starch in puff pastry enhanced product quality by improving texture, structure, and shelf life, particularly when used at levels between 30% and 40%. This research underscores the potential of modified starches to address health concerns associated with traditional starches and to contribute to the development of higher-quality, consumer-friendly baked products. Furthermore, the findings suggest that modified starches could play a pivotal role in future innovations within the baking industry, particularly in products aiming to balance healthfulness with sensory appeal. By incorporating modified starch into their formulations, bakeries can meet the growing demand for healthier, more sustainable products while maintaining the indulgent qualities that consumers expect from baked goods.Keywords: baking quality, dough properties, modified starch, puff pastry
Procedia PDF Downloads 26485 Transparency Phenomenon in Kuew Teow
Authors: Muhammad Heikal Ismail, Law Chung Lim, Hii Ching Lik
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In maintaining food quality and shelf life, drying is employed in food industry as the most reliable perseverance technique. In this way, heat pump drying and hot air drying of fresh rice noodles was deduced to freeze drying in achieving quality attributes of oil content Scanning Electron Microscope (SEM) images, texture, and colour. Soxthlet analysis shows freeze dried noodles contain more than 10 times oil content, distinct pores of SEM images, higher hardness by more than three times, and wider colour changes by average more than two times to both methods to explain the less transparency physical outlook of freeze dried samples.Keywords: freeze drying, heat pump drying, noodles, Soxthlet
Procedia PDF Downloads 486484 Application of Deep Learning in Colorization of LiDAR-Derived Intensity Images
Authors: Edgardo V. Gubatanga Jr., Mark Joshua Salvacion
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Most aerial LiDAR systems have accompanying aerial cameras in order to capture not only the terrain of the surveyed area but also its true-color appearance. However, the presence of atmospheric clouds, poor lighting conditions, and aerial camera problems during an aerial survey may cause absence of aerial photographs. These leave areas having terrain information but lacking aerial photographs. Intensity images can be derived from LiDAR data but they are only grayscale images. A deep learning model is developed to create a complex function in a form of a deep neural network relating the pixel values of LiDAR-derived intensity images and true-color images. This complex function can then be used to predict the true-color images of a certain area using intensity images from LiDAR data. The predicted true-color images do not necessarily need to be accurate compared to the real world. They are only intended to look realistic so that they can be used as base maps.Keywords: aerial LiDAR, colorization, deep learning, intensity images
Procedia PDF Downloads 168483 Forest Fire Burnt Area Assessment in a Part of West Himalayan Region Using Differenced Normalized Burnt Ratio and Neural Network Approach
Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman
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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.Keywords: categorical data, log linear modeling, neural network, shifting cultivation
Procedia PDF Downloads 56482 Traffic Light Detection Using Image Segmentation
Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra
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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks
Procedia PDF Downloads 176481 Estimating Poverty Levels from Satellite Imagery: A Comparison of Human Readers and an Artificial Intelligence Model
Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson
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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania
Procedia PDF Downloads 107480 Using the Timepix Detector at CERN Accelerator Facilities
Authors: Andrii Natochii
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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.Keywords: beam monitoring, channeling, particle tracking, Timepix detector
Procedia PDF Downloads 181479 Medical Image Classification Using Legendre Multifractal Spectrum Features
Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui
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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification
Procedia PDF Downloads 515478 Bitplanes Gray-Level Image Encryption Approach Using Arnold Transform
Authors: Ali Abdrhman M. Ukasha
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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption
Procedia PDF Downloads 440477 Physical, Textural and Sensory Properties of Noodles Supplemented with Tilapia Bone Flour (Tilapia nilotica)
Authors: Supatchalee Sirichokworrakit
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Fishbone of Nile tilapia (Tilapia nilotica), waste from the frozen Nile tilapia fillet factory, is one of calcium sources. In order to increase fish bone powder value, this study aimed to investigate the effect of tilapia bone flour (TBF) addition (5, 10, 15% by flour weight) on cooking quality, texture and sensory attributes of noodles. The results indicated that tensile strength, color value (a*) and water absorption of noodles significantly decreased (p≤0.05) as the levels of TBF increased from 0-15%. While cooking loss, cooking time and color values (L* and b*) of noodles significantly increased (p≤0.05). Sensory evaluation indicated that noodles with 5% TBF received the highest overall acceptability score.Keywords: tilapia bone flour, noodles, cooking quality, calcium
Procedia PDF Downloads 405476 Bitplanes Image Encryption/Decryption Using Edge Map (SSPCE Method) and Arnold Transform
Authors: Ali A. Ukasha
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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption
Procedia PDF Downloads 501475 Dynamic Background Updating for Lightweight Moving Object Detection
Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo
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Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference
Procedia PDF Downloads 342474 Clustering Based Level Set Evaluation for Low Contrast Images
Authors: Bikshalu Kalagadda, Srikanth Rangu
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The important object of images segmentation is to extract objects with respect to some input features. One of the important methods for image segmentation is Level set method. Generally medical images and synthetic images with low contrast of pixel profile, for such images difficult to locate interested features in images. In conventional level set function, develops irregularity during its process of evaluation of contour of objects, this destroy the stability of evolution process. For this problem a remedy is proposed, a new hybrid algorithm is Clustering Level Set Evolution. Kernel fuzzy particles swarm optimization clustering with the Distance Regularized Level Set (DRLS) and Selective Binary, and Gaussian Filtering Regularized Level Set (SBGFRLS) methods are used. The ability of identifying different regions becomes easy with improved speed. Efficiency of the modified method can be evaluated by comparing with the previous method for similar specifications. Comparison can be carried out by considering medical and synthetic images.Keywords: segmentation, clustering, level set function, re-initialization, Kernel fuzzy, swarm optimization
Procedia PDF Downloads 352473 Investigation of Martensitic Transformation Zone at the Crack Tip of NiTi under Mode-I Loading Using Microscopic Image Correlation
Authors: Nima Shafaghi, Gunay Anlaş, C. Can Aydiner
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A realistic understanding of martensitic phase transition under complex stress states is key for accurately describing the mechanical behavior of shape memory alloys (SMAs). Particularly regarding the sharply changing stress fields at the tip of a crack, the size, nature and shape of transformed zones are of great interest. There is significant variation among various analytical models in their predictions of the size and shape of the transformation zone. As the fully transformed region remains inside a very small boundary at the tip of the crack, experimental validation requires microscopic resolution. Here, the crack tip vicinity of NiTi compact tension specimen has been monitored in situ with microscopic image correlation with 20x magnification. With nominal 15 micrometer grains and 0.2 micrometer per pixel optical resolution, the strains at the crack tip are mapped with intra-grain detail. The transformation regions are then deduced using an equivalent strain formulation.Keywords: digital image correlation, fracture, martensitic phase transition, mode I, NiTi, transformation zone
Procedia PDF Downloads 354472 Effect of Pulsed Electrical Field on the Mechanical Properties of Raw, Blanched and Fried Potato Strips
Authors: Maria Botero-Uribe, Melissa Fitzgerald, Robert Gilbert, Kim Bryceson, Jocelyn Midgley
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French fry manufacturing involves a series of processes in which structural properties of potatoes are modified to produce crispy french fries which consumers enjoy. In addition to the traditional french fry manufacturing process, the industry is applying a relatively new process called pulsed electrical field (PEF) to the whole potatoes. There is a wealth of information on the technical treatment conditions of PEF, however, there is a lack of information about its effect on the structural properties that affect texture and its synergistic interactions with the other manufacturing steps of french fry production. The effect of PEF on starch gelatinisation properties of Russet Burbank potato was measured using a Differential Scanning Calorimeter. Cation content (K+, Ca2+ and Mg2+) was determined by inductively coupled plasma optical emission spectrophotometry. Firmness, and toughness of raw and blanched potatoes were determined in an uniaxial compression test. Moisture content was determined in a vacuum oven and oil content was measured using the soxhlet system with hexane. The final texture of the french fries – crispness - was determined using a three bend point test. Triangle tests were conducted to determine if consumers were able to perceive sensory differences between French fries that were PEF treated and those without treatment. The concentration of K+, Ca2+ and Mg2+ decreased significantly in the raw potatoes after the PEF treatment. The PEF treatment significantly increased modulus of elasticity, compression strain, compression force and toughness in the raw potato. The PEF-treated raw potato were firmer and stiffer, and its structure integrity held together longer, resisted higher force before fracture and stretched further than the untreated ones. The strain stress relationship exhibited by the PEF-treated raw potato could be due to an increase in the permeability of the plasmalema and tonoplasm allowing Ca2+ and Mg2+ cations to reach the cell wall and middle lamella, and be available for cross linking with the pectin molecule. The PEF-treated raw potato exhibited a slightly higher onset gelatinisation temperatures, similar peak temperatures and lower gelatinisation ranges than the untreated raw potatoes. The final moisture content of the french fries was not significantly affected by the PEF treatment. Oil content in the PEF- treated potatoes was lower than the untreated french fries, however, not statistically significant at 5 %. The PEF treatment did not have an overall significant effect on french fry crispness (modulus of elasticity), flexure stress or strain. The triangle tests show that most consumers could not detect a difference between French fries that received a PEF treatment from those that did not.Keywords: french fries, mechanical properties, PEF, potatoes
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