Search results for: Color Structure-Texture Image Decomposition
2846 Modeling and Energy Analysis of Limestone Decomposition with Microwave Heating
Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira
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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing
Procedia PDF Downloads 1752845 Numerical Investigation of Turbulent Flow Control by Suction and Injection on a Subsonic NACA23012 Airfoil by Proper Orthogonal Decomposition Analysis and Perturbed Reynolds Averaged Navier‐Stokes Equations
Authors: Azam Zare
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Separation flow control for performance enhancement over airfoils at high incidence angle has become an increasingly important topic. This work details the characteristics of an efficient feedback control of the turbulent subsonic flow over NACA23012 airfoil using forced reduced‐order model based on the proper orthogonal decomposition/Galerkin projection and perturbation method on the compressible Reynolds Averaged Navier‐Stokes equations. The forced reduced‐order model is used in the optimal control of the turbulent separated flow over a NACA23012 airfoil at Mach number of 0.2, Reynolds number of 5×106, and high incidence angle of 24° using blowing/suction controlling jets. The Spallart-Almaras turbulence model is implemented for high Reynolds number calculations. The main shortcoming of the POD/Galerkin projection on flow equations for controlling purposes is that the blowing/suction controlling jet velocity does not show up explicitly in the resulting reduced order model. Combining perturbation method and POD/Galerkin projection on flow equations introduce a forced reduced‐order model that can predict the time-varying influence of the blowing/suction controlling jet velocity. An optimal control theory based on forced reduced‐order system is used to design a control law for a nonlinear reduced‐order model, which attempts to minimize the vorticity content in the turbulent flow field over NACA23012 airfoil. Numerical simulations were performed to help understand the behavior of the controlled suction jet at 12% to 18% chord from leading edge and a pair of blowing/suction jets at 15% to 18% and 24% to 30% chord from leading edge, respectively. Analysis of streamline profiles indicates that the blowing/suction jets are efficient in removing separation bubbles and increasing the lift coefficient up to 22%, while the perturbation method can predict the flow field in an accurate Manner.Keywords: flow control, POD, Galerkin projection, separation
Procedia PDF Downloads 1492844 Digital Watermarking Based on Visual Cryptography and Histogram
Authors: R. Rama Kishore, Sunesh
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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.Keywords: digital watermarking, visual cryptography, histogram, butter worth filter
Procedia PDF Downloads 3582843 Classifier for Liver Ultrasound Images
Authors: Soumya Sajjan
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Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix
Procedia PDF Downloads 4112842 Damage Micromechanisms of Coconut Fibers and Chopped Strand Mats of Coconut Fibers
Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.
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The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism
Procedia PDF Downloads 4592841 Uni-Mode Uniqueness Conditions for Candecomp/Parafac of N-Way Arrays with Linearly Dependent Loadings
Authors: Ling Zhang, Weikai Li
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Recently three sufficient conditions for the three-way Candecomp/Parafac (CP) model which ensure uniqueness in one of the three modes(“uni-mode uniqueness”) are given. In this paper, we generalize these uniqueness conditions to n ≤ 3 and give a sufficient conditions for the n-way Candecomp/Parafac (CP) model, which ensure uniqueness in one of the n modes.Keywords: uni-mode uniqueness, candecomp/parafac, n-way arrays, decomposition, tensor
Procedia PDF Downloads 3442840 Retina Registration for Biometrics Based on Characterization of Retinal Feature Points
Authors: Nougrara Zineb
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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.Keywords: fovea, optic disc, registration, retinal images
Procedia PDF Downloads 2662839 An Advanced Automated Brain Tumor Diagnostics Approach
Authors: Berkan Ural, Arif Eser, Sinan Apaydin
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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition
Procedia PDF Downloads 4182838 Investigation of New Gait Representations for Improving Gait Recognition
Authors: Chirawat Wattanapanich, Hong Wei
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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.Keywords: convolutional image, lower knee, gait
Procedia PDF Downloads 2022837 Systematic Evaluation of Convolutional Neural Network on Land Cover Classification from Remotely Sensed Images
Authors: Eiman Kattan, Hong Wei
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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.Keywords: CNNs, hyperparamters, remote sensing, land cover, land use
Procedia PDF Downloads 1682836 Low Sulfur Diesel-Like Fuel From Quick Remediation Process of Waste Oil Sludge
Authors: Isam A. H. Al Zubaidy
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A quick process may be needed to get the benefit the big generated quantity of waste oil sludge (WOS). The process includes the mixing process of WOS with commercial diesel fuel. Different ratios of WOS to diesel fuel were prepared ranging 1:1 to 20:1 by mass. The mixture was continuously mixing for 10 minutes using bench type overhead stirrer and followed by filtration process to separate the soil waste from filtrate oil product. The quantity and the physical properties of the oil filtrate were measured. It was found that the addition of up to 15% WOS to diesel fuel was accepted without dramatic changes to the properties of diesel fuel. The amount of waste oil sludge was decreased by about 60% by mass. This means that about 60 % of the mass of sludge was recovered as light fuel oil. The physical properties of the resulting fuel from 10% sludge mixing ratio showed that the specific gravity, ash content, carbon residue, asphaltene content, viscosity, diesel index, cetane number, and calorific value were affected slightly. The color was changed to light black color. The sulfur content was increased also. This requires other processes to reduce the sulfur content of the resulting light fuel. A new desulfurization process was achieved using adsorption techniques with activated biomaterial to reduce the sulfur content to acceptable limits. Adsorption process by ZnCl₂ activated date palm kernel powder was effective for improvement of the physical properties of diesel like fuel. The final sulfur content was increased to 0.185 wt%. This diesel like fuel can be used in all tractors, buses, tracks inside and outside the refineries. The solid remaining seems to be smooth and can be mixed with asphalt mixture for asphalting the roads or can be used with other materials as an asphalt coating material for constructed buildings. Through this process, valuable fuel has been recovered, and the amount of waste material had decreased.Keywords: oil sludge, diesel fuel, blending process, filtration process
Procedia PDF Downloads 1182835 Kinetic Study of Municipal Plastic Waste
Authors: Laura Salvia Diaz Silvarrey, Anh Phan
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Municipal Plastic Waste (MPW) comprises a mixture of thermoplastics such as high and low density polyethylene (HDPE and LDPE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET). Recycling rate of these plastics is low, e.g. only 27% in 2013. The remains were incinerated or disposed in landfills. As MPW generation increases approximately 5% per annum, MPW management technologies have to be developed to comply with legislation . Pyrolysis, thermochemical decomposition, provides an excellent alternative to convert MPW into valuable resources like fuels and chemicals. Most studies on waste plastic kinetics only focused on HDPE and LDPE with a simple assumption of first order decomposition, which is not the real reaction mechanism. The aim of this study was to develop a kinetic study for each of the polymers in the MPW mixture using thermogravimetric analysis (TGA) over a range of heating rates (5, 10, 20 and 40°C/min) in N2 atmosphere and sample size of 1 – 4mm. A model-free kinetic method was applied to quantify the activation energy at each level of conversion. Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) equations jointly with Master Plots confirmed that the activation energy was not constant along all the reaction for all the five plastic studied, showing that MPW decomposed through a complex mechanism and not by first-order kinetics. Master plots confirmed that MPW decomposed following a random scission mechanism at conversions above 40%. According to the random scission mechanism, different radicals are formed along the backbone producing the cleavage of bonds by chain scission into molecules of different lengths. The cleavage of bonds during random scission follows first-order kinetics and it is related with the conversion. When a bond is broken one part of the initial molecule becomes an unsaturated one and the other a terminal free radical. The latter can react with hydrogen from and adjacent carbon releasing another free radical and a saturated molecule or reacting with another free radical and forming an alkane. Not every time a bonds is broken a molecule is evaporated. At early stages of the reaction (conversion and temperature below 40% and 300°C), most products are not short enough to evaporate. Only at higher degrees of conversion most of cleavage of bonds releases molecules small enough to evaporate.Keywords: kinetic, municipal plastic waste, pyrolysis, random scission
Procedia PDF Downloads 3542834 Statistical Feature Extraction Method for Wood Species Recognition System
Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof
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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images
Procedia PDF Downloads 4252833 Late Roman-Byzantine Glass Bracelet Finds at Amorium and Comparison with Other Cultures
Authors: Atilla Tekin
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Amorium was one of the biggest cities of Byzantine Empire, located under and around the modern village of Hisarköy, Emirdağ, Afyonkarahisar Province, Turkey. It was situated on the routes of trades and Byzantine military road from Constantinople to Cilicia. In addition, it was on the routes of trades and a center of bishopric. After Arab invasion, Amorium gradually lost importance. The research consists of 1372 pieces of glass bracelet finds from mostly at 1998- 2009 excavations. Most of them were found as glass bracelets fragments. The fragments are of various size, forms, colors, and decorations. During the research, they were measured and grouped according to their crossings, at first. After being photographed, they were sketched by Adobe Illustrator and decoupaged by Photoshop. All forms, colors, and decorations were specified and compared to each other. Thus, they have been tried to be dated and uncovered the place of manufacture. The importance of the research is presenting the perception of image and admiration and comparing with other cultures.Keywords: Amorium, glass bracelets, image, Byzantine empire, jewelry
Procedia PDF Downloads 1962832 CT Medical Images Denoising Based on New Wavelet Thresholding Compared with Curvelet and Contourlet
Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi
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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)
Procedia PDF Downloads 4412831 Traffic Sign Recognition System Using Convolutional Neural NetworkDevineni
Authors: Devineni Vijay Bhaskar, Yendluri Raja
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We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve
Procedia PDF Downloads 1222830 Objects Tracking in Catadioptric Images Using Spherical Snake
Authors: Khald Anisse, Amina Radgui, Mohammed Rziza
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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection
Procedia PDF Downloads 4022829 Imagology: The Study of Multicultural Imagery Reflected in the Heart of Elif Shafak’s 'The Bastard of Istanbul'
Authors: Mohammad Reza Haji Babai, Sepideh Ahmadkhan Beigi
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Internationalization and modernization of the globe have played their roles in the process of cultural interaction between globalized societies and, consequently, found their way to the world of literature under the name of ‘imagology’. Imagology has made it possible for the reader to understand the author’s thoughts and judgments of others. The present research focuses on the intercultural images portrayed in the novel of a popular Turkish-French writer, Elif Shafak, about the lifestyle, traditions, habits, and social norms of Turkish, Americans, and Armenians. The novel seeks to articulate a more intricate multicultural memory of Turkishness by grieving over the Armenian massacre. This study finds that, as a mixture of multiple lifestyles and discourses, The Bastard of Istanbul reflects not only images of oriental culture but also occidental cultures. This means that the author has attempted to maintain selfhood through historical and cultural recollection, which resulted in constructing the self and another identity.Keywords: imagology, Elif Shafak, The Bastard of Istanbul, self-image, other-image
Procedia PDF Downloads 1412828 Antibacterial and Antioxidant Capacity of Fabric Treated with Purple-Fleshed Sweet Potato Extract
Authors: Kyung Hwa Hong, Eunmi Koh
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Wool and cotton fabrics are pretreated by a tannic acid aqueous solution to increase their dyeability and then dyed by Purple-Fleshed Sweet Potato (PSP) extract. The dyed fabrics are then investigated by various analysis techniques. The results revealed that wool and cotton fabrics can be dyed bluish red through the pretreatment and dyeing process. Both wool and cotton fabrics only pretreated with tannic acid display decreased L* value but no significant changes in a* and b* values as the concentration of tannic acid increases. And, as expected, the pretreated fabrics are even darker and show a richer purple color after the dyeing process with the PSP extract. With regard to the colorfastness of wool and cotton fabrics dyed by PSP extract in cleaning circumstances, such as dry-cleaning (for wool) and washing (for cotton), the wool and cotton fabrics had a 4.0 and 4.0 grade of colorfastness to dry-cleaning and washing, respectively. However, they both exhibited significantly inferior colorfastness to light (grade of 1.5). Thus, it was found that there is still a need for improvement with regard to color fastness, particularly against light. On the other hand, the wool and cotton fabrics also showed antibacterial and antioxidant characteristics. In addition, both the wool and cotton fabrics showed potential antibacterial ability (>99%) against Staphylococcus aureus; however, they showed somewhat insufficient antibacterial ability (60.8% for wool and 94.8% for cotton) against Klebsiella pneumoniae. Also, their antioxidant abilities increased up to ca. 90% with an increase in the tannic acid concentration (up to 0.5%). However, after the dyeing process, the antibacterial and antioxidant ability tended to decrease. This is assumed to have occurred because functional moieties such as phenolic acids were detached from the pretreated fabrics into the hot water (the dyeing solution) during the dyeing process. Therefore, further study would be necessary to derive the optimum treatment and dyeing conditions so as to maximize the coloring effect and functionalities of the fabrics.Keywords: antibacterial activity, antioxidant activity, purple-fleshed sweet potato, fabrics
Procedia PDF Downloads 2922827 Characterization of Anisotropic Deformation in Sandstones Using Micro-Computed Tomography Technique
Authors: Seyed Mehdi Seyed Alizadeh, Christoph Arns, Shane Latham
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Geomechanical characterization of rocks in detail and its possible implications on flow properties is an important aspect of reservoir characterization workflow. In order to gain more understanding of the microstructure evolution of reservoir rocks under stress a series of axisymmetric triaxial tests were performed on two different analogue rock samples. In-situ compression tests were coupled with high resolution micro-Computed Tomography to elucidate the changes in the pore/grain network of the rocks under pressurized conditions. Two outcrop sandstones were chosen in the current study representing a various cementation status of well-consolidated and weakly-consolidated granular system respectively. High resolution images were acquired while the rocks deformed in a purpose-built compression cell. A detailed analysis of the 3D images in each series of step-wise compression tests (up to the failure point) was conducted which includes the registration of the deformed specimen images with the reference pristine dry rock image. Digital Image Correlation (DIC) technique based on the intensity of the registered 3D subsets and particle tracking are utilized to map the displacement fields in each sample. The results suggest the complex architecture of the localized shear zone in well-cemented Bentheimer sandstone whereas for the weakly-consolidated Castlegate sandstone no discernible shear band could be observed even after macroscopic failure. Post-mortem imaging a sister plug from the friable rock upon undergoing continuous compression reveals signs of a shear band pattern. This suggests that for friable sandstones at small scales loading mode may affect the pattern of deformation. Prior to mechanical failure, the continuum digital image correlation approach can reasonably capture the kinematics of deformation. As failure occurs, however, discrete image correlation (i.e. particle tracking) reveals superiority in both tracking the grains as well as quantifying their kinematics (in terms of translations/rotations) with respect to any stage of compaction. An attempt was made to quantify the displacement field in compression using continuum Digital Image Correlation which is based on the reference and secondary image intensity correlation. Such approach has only been previously applied to unconsolidated granular systems under pressure. We are applying this technique to sandstones with various degrees of consolidation. Such element of novelty will set the results of this study apart from previous attempts to characterize the deformation pattern in consolidated sands.Keywords: deformation mechanism, displacement field, shear behavior, triaxial compression, X-ray micro-CT
Procedia PDF Downloads 1892826 Image Instance Segmentation Using Modified Mask R-CNN
Authors: Avatharam Ganivada, Krishna Shah
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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision
Procedia PDF Downloads 732825 Effect of Different Level of Pomegranate Molasses on Performance, Egg Quality Trait, Serological and Hematological Parameters in Older Laying Hens
Authors: Ismail Bayram, Aamir Iqbal, E. Eren Gultepe, Cangir Uyarlar, Umit Ozcınar, I. Sadi Cetingul
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The current study was planned with the objective to explore the potential of pomegranate molasses (PM) on performance, egg quality and blood parameters in older laying hens. A total of 240 Babcock white laying hens (52 weeks old) were divided into 5 groups (n=48) with 8 subgroups having 6 hens in each. Pomegranate molasses was added in the drinking water to experimental groups with 0 %, 0.1%, 0.25 %, 0.5%, and 1%, respectively during one month. In our results, egg weight values were remained the same in all pomegranate molasses supplemented groups except 1% group over control. However, feed consumption, egg production, feed conversion ratio (FCR), egg mass, egg yolk cholesterol, body weights, and water consumption remained unaffected (P > 0.05). During mid-study (15 Days) analyses, egg quality parameters such as Haugh unit, eggshell thickness, albumin index, yolk index, and egg yolk color were remained non-significant (P > 0.05) while after final (30 Days) egg analyses, only egg yolk color had positively (P < 0.05) increased in 0.5% group. Moreover, Haugh unit, eggshell thickness, and albumin index were not significantly (P > 0.05) affected by the supplementation of pomegranate molasses. Regarding serological parameters, pomegranate molasses did not show any positive effect on cholesterol, total protein, LDL, HDL, GGT, AST, ALT, and glucose level. Similarly, pomegranate molasses also showed non-significant (P > 0.05) results on different blood parameters such as HCT, RBC, MCV, MCH, MCHC, PLT, RDWC, MPV except hemoglobin level. Only hemoglobin level was increased in all experimental groups over control showing that pomegranate molasses can be used as an enhancer in animals with low hemoglobin level.Keywords: pomegranate molasses, laying hen, egg yield, blood parameters
Procedia PDF Downloads 1692824 Fuzzy Wavelet Model to Forecast the Exchange Rate of IDR/USD
Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik
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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet
Procedia PDF Downloads 5712823 Geological Mapping of Gabel Humr Akarim Area, Southern Eastern Desert, Egypt: Constrain from Remote Sensing Data, Petrographic Description and Field Investigation
Authors: Doaa Hamdi, Ahmed Hashem
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The present study aims at integrating the ASTER data and Landsat 8 data to discriminate and map alteration and/or mineralization zones in addition to delineating different lithological units of Humr Akarim Granites area. The study area is located at 24º9' to 24º13' N and 34º1' to 34º2'45"E., covering a total exposed surface area of about 17 km². The area is characterized by rugged topography with low to moderate relief. Geologic fieldwork and petrographic investigations revealed that the basement complex of the study area is composed of metasediments, mafic dikes, older granitoids, and alkali-feldspar granites. Petrographic investigations revealed that the secondary minerals in the study area are mainly represented by chlorite, epidote, clay minerals and iron oxides. These minerals have specific spectral signatures in the region of visible near-infrared and short-wave infrared (0.4 to 2.5 µm). So that the ASTER imagery processing was concentrated on VNIR-SWIR spectrometric data in order to achieve the purposes of this study (geologic mapping of hydrothermal alteration zones and delineate possible radioactive potentialities). Mapping of hydrothermal alterations zones in addition to discriminating the lithological units in the study area are achieved through the utilization of some different image processing, including color band composites (CBC) and data transformation techniques such as band ratios (BR), band ratio codes (BRCs), principal component analysis(PCA), Crosta Technique and minimum noise fraction (MNF). The field verification and petrographic investigation confirm the results of ASTER imagery and Landsat 8 data, proposing a geological map (scale 1:50000).Keywords: remote sensing, petrography, mineralization, alteration detection
Procedia PDF Downloads 1642822 Immobilized Iron Oxide Nanoparticles for Stem Cell Reconstruction in Magnetic Particle Imaging
Authors: Kolja Them, Johannes Salamon, Harald Ittrich, Michael Kaul, Tobias Knopp
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Superparamagnetic iron oxide nanoparticles (SPIONs) are nanoscale magnets which can be biologically functionalized for biomedical applications. Stem cell therapies to repair damaged tissue, magnetic fluid hyperthermia for cancer therapy and targeted drug delivery based on SPIONs are prominent examples where the visualization of a preferably low concentrated SPION distribution is essential. In 2005 a new method for tomographic SPION imaging has been introduced. The method named magnetic particle imaging (MPI) takes advantage of the nanoparticles magnetization change caused by an oscillating, external magnetic field and allows to directly image the time-dependent nanoparticle distribution. The SPION magnetization can be changed by the electron spin dynamics as well as by a mechanical rotation of the nanoparticle. In this work different calibration methods in MPI are investigated for image reconstruction of magnetically labeled stem cells. It is shown that a calibration using rotationally immobilized SPIONs provides a higher quality of stem cell images with fewer artifacts than a calibration using mobile SPIONs. The enhancement of the image quality and the reduction of artifacts enables the localization and identification of a smaller number of magnetically labeled stem cells. This is important for future medical applications where low concentrations of functionalized SPIONs interacting with biological matter have to be localized.Keywords: biomedical imaging, iron oxide nanoparticles, magnetic particle imaging, stem cell imaging
Procedia PDF Downloads 4642821 The Relationship among Perceived Risk, Product Knowledge, Brand Image and the Insurance Purchase Intention of Taiwanese Working Holiday Youths
Authors: Wan-Ling Chang, Hsiu-Ju Huang, Jui-Hsiu Chang
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In 2004, the Ministry of Foreign Affairs Taiwan launched ‘An Arrangement on Working Holiday Scheme’ with 15 countries including New Zealand, Japan, Canada, Germany, South Korea, Britain, Australia and others. The aim of the scheme is to allow young people to work and study English or other foreign languages. Each year, there are 30,000 Taiwanese youths applied for participating in the working holiday schemes. However, frequent accidents could cause huge medical expenses and post-delivery fee, which are usually unaffordable for most families. Therefore, this study explored the relationship among perceived risk toward working holiday, insurance product knowledge, brand image and insurance purchase intention for Taiwanese youths who plan to apply for working holiday. A survey questionnaire was distributed for data collection. A total of 316 questionnaires were collected for data analyzed. Data were analyzed using descriptive statistics, independent samples T-test, one-way ANOVA, correlation analysis, regression analysis and hierarchical regression methods of analysis and hypothesis testing. The results of this research indicate that perceived risk has a negative influence on insurance purchase intention. On the opposite, product knowledge has brand image has a positive influence on the insurance purchase intention. According to the mentioned results, practical implications were further addressed for insurance companies when developing a future marketing plan.Keywords: insurance product knowledges, insurance purchase intention, perceived risk, working holiday
Procedia PDF Downloads 2502820 Evaluation of Forensic Pathology Practice Outside Germany – Experiences From 20 Years of Second Look Autopsies in Cooperation with the Institute of Legal Medicine Munich
Authors: Michael Josef Schwerer, Oliver Peschel
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Background: The sense and purpose of forensic postmortem examinations are undoubtedly the same in Institutes of Legal Medicine all over the world. Cause and manner of death must be determined, persons responsible for unnatural death must be brought to justice, and accidents demand changes in the respective scenarios to avoid future mishaps. The latter particularly concerns aircraft accidents, not only regarding consequences from criminal or civil law but also in pursuance of the International Civil Aviation Authority’s regulations, which demand lessons from mishap investigations to improve flight safety. Irrespective of the distinct circumstances of a given casualty or the respective questions in subsequent death investigations, a forensic autopsy is the basis for all further casework, the clue to otherwise hidden solutions, and the crucial limitation for final success when not all possible findings have been properly collected. This also implies that the targeted work of police forces and expert witnesses strongly depends on the quality of forensic pathology practice. Deadly events in foreign countries, which lead to investigations not only abroad but also in Germany, can be challenging in this context. Frequently, second-look autopsies after the repatriation of the deceased to Germany are requested by the legal authorities to ensure proper and profound documentation of all relevant findings. Aims and Methods: To validate forensic postmortem practice abroad, a retrospective study using the findings in the corresponding second-look autopsies in the Institute of Legal Medicine Munich over the last 20 years was carried out. New findings unreported in the previous autopsy were recorded and judged for their relevance to solving the respective case. Further, the condition of the corpse at the time of the second autopsy was rated to discuss artifacts mimicking evidence or the possibility of lost findings resulting from, e.g., decomposition. Recommendations for future handling of death cases abroad and efficient autopsy practice were pursued. Results and Discussion: Our re-evaluation confirmed a high quality of autopsy practice abroad in the vast majority of cases. However, in some casework, incomplete documentation of pathology findings was revealed along with either insufficient or misconducted dissection of organs. Further, some of the bodies showed missing parts of some organs, most probably resulting from sampling for histology studies during the first postmortem. For the aeromedical evaluation of a decedent’s health status prior to an aviation mishap, particularly lost or obscured findings in the heart, lungs, and brain impeded expert testimony. Moreover, incomplete fixation of the body or body parts for repatriation was seen in several cases. This particularly involved previously dissected organs deposited back into the body cavities at the end of the first autopsy. Conclusions and Recommendations: Detailed preparation in the first forensic autopsy avoids the necessity of a second-look postmortem in the majority of cases. To limit decomposition changes during repatriation from abroad, special care must be taken to include pre-dissected organs in the chemical fixation process, particularly when they are separated from the blood vessels and just deposited back into the body cavities.Keywords: autopsy practice, second-look autopsy, retrospective study, quality standards, decomposition changes, repatriation
Procedia PDF Downloads 492819 Twin Deficits Hypothesis: The Case of Turkey
Authors: Mehmet Mucuk, Ayşen Edirneligil
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Budget and current account deficits are main problems for all countries. There are different approaches about the relationship between budget deficit and current account deficit. While Keynesian view accepts that there is a casual link between these variables, Ricardian equivalence hypothesis rejects it. The aim of this study is to analyze the validity of Keynesian view for Turkish Economy using VAR analysis with the monthly data in the period of 2006-2014. In this context, it will be used Johansen Cointegration Test, Impulse-Response Function and Variance Decomposition Tests.Keywords: budget deficit, current account deficit, Turkish economy, twin deficits
Procedia PDF Downloads 4252818 Direct Composite Veneers as Treatment of Anterior Teeth: Case Report
Authors: Amerah Alsalem
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Aim: Laminate veneers are restorations which are envisioned to correct existing abnormalities, esthetic deficiencies, and discolorations. Laminate veneer restorations may be processed in two different ways: direct or indirect. Materials and methods: Direct composite laminate veneers require minimal preparation compared to indirect composite veneers, cost less and are easier to repair, so are useful in young patients. However, composites can have inherent limitations such as shrinkage, limited toughness; color instability and susceptibility to wear that reduce the lifespan of the restoration and cause postoperative complications. Every new material or method introduced to the field of dentistry aims to achieve esthetics and successful dental treatments with minimal invasiveness. Therefore, direct laminate veneer restorations have been developed for advanced esthetic problems of anterior teeth. Tooth discolorations, rotated teeth, coronal fractures, congenital or acquired malformations, diastemas, discolored restorations, palatally positioned teeth, the absence of lateral incisors, abrasions and erosions are the main indications for direct laminate veneer restorations. Result: Direct veneers, as esthetic procedures, have become treatment alternatives for patients with esthetic problems of anterior teeth in recent years. The cost, social and time factors have to be considered. Although ceramic laminate veneer restorations have some advantages like color stability and high resistance against abrasion, they have also some disadvantages, including high cost and long chair time. Moreover, they have some problems such as the necessity of an additional adhesive cement. Conclusion: Although there are still some disadvantages, especially discolorations and fragility, with the development of new composite resins, direct laminate veneer restorations can be a treatment option for patients with esthetic problems of anterior teeth, when applied judiciously with good patient hygiene motivation.Keywords: direct, veneers, composite, anterior
Procedia PDF Downloads 2822817 Examining Factors Influencing Career Choice Among Young Muslim Arab Women in Nursing
Authors: Merav Ben Natan, Miriam Abo El Hadi, Fardus Zoubi
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Aim: This study investigates the factors that motivate young Muslim Arab women to pursue nursing careers, focusing on the impact of nurse uniforms, the COVID-19 pandemic, and perceptions of nurses and the nursing profession. The aim is to draw insights that can inform policy strategies. Background: The global shortage of nursing professionals is a pressing concern, even in regions like Israel. Attracting and retaining young Muslim Arab women in nursing is essential for addressing this shortage. To better understand their career decisions, it is crucial to examine the influence of nurse uniforms, the pandemic, and perceptions related to nurses and the nursing profession. Methods: This cross-sectional study employed digital questionnaires, which were administered to 200 Muslim Arab women between the ages of 20 and 30 in Israel. Results: Only 29.2% of the participants indicated an interest in pursuing a nursing career. The study findings revealed a noteworthy positive correlation between the pandemic's impact and the intention to pursue nursing. Further analysis, using linear regression, elucidated the role of factors such as the white nurse uniform, perceptions of nurses, and the image of the nursing profession in influencing career choices in nursing. Discussion: This study underscores the significance of nurse uniforms, the image of nurses, and the perception of the nursing profession in shaping the career choices of young Muslim Arab women in nursing. Policy interventions should prioritize raising awareness about diverse nursing roles, expanding nurses' responsibilities, and highlighting their invaluable contributions to society.Keywords: nursing image, uniform, nursing career, nurse profession
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