Search results for: pixel entropy

Authors: Kaewmart Pongakkasira

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This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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Authors: Okike Benjamin, Garba E J. D.

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Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt.

Keywords: image encryption, matrices, pixel, matrix transpose

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Authors: Abhijith N. V., Abhijit Pattnayak, Deepak Kumar

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Nowadays, a group of alloys, namely high entropy alloys (HEA), because of their excellent properties. However, the fabrication of HEAs requires multistage techniques, especially mill-ing, sieving, compaction, sintering, inert media, etc. These processes are laborious, costly, time-oriented, and unsuitable for commercial application. This study adopted a single-stage process-based HVOF thermal spray to develop HEA coating on SS304L substrates. The wear behavior of the deposited HEA coating was explored under different milling time durations (5h, 10h, and 15h, respectively). The effect of feedstock preparation, microstructure, surface chemistry, and mechanical and metallurgical properties on wear resistance was also investigated. The microstructure and composition of both coating and feedstock were evaluated by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis. Finally, the phase distribution was correlated by X-ray diffraction (XRD ) analysis. The results showed that 15h milled powder coating indicated better tribological than the base substrate and 5h,10h milled powder coating. A chemically stable Body Centered Cubic (BCC) solid solution phase was generated within the 15h milled powder-coated system, which resulted in superior tribological properties.

Keywords: high entropy alloys coating, wear mechanism, HVOF coating, microstructure

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Authors: S. Aouabdi, M. Taibi

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The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.

Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics

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Authors: Jyun-Hao Liao, Chien-Ju Chen, Chia-Jui Yu, Meng Chyi Wu, Chia-Ching Wu

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In this letter, we reported the fabrication of InGaAs micro-photodiode sensor array with the rapid thermal diffusion (RTD) technique. The spin-on dopant source Zn was used to form the p-type region in InP layer. Through the RTD technique, the InP/InGaAs heterostructure was formed. We improved our fabrication on the p-i-n photodiode to micro size which pixel is 7.8um, and the pitch is 12.8um. The proper SiNx was deposited to form the passivation layer. The leakage current of single pixel decrease to 3.3pA at -5V, and 35fA at -10mV. The leakage current densities of each voltage are 21uA/cm² at -5V and 0.223uA/cm² at -10mV. As we focus on the wavelength from 0.9um to 1.7um, the optimized Si/Al₂O₃ bilayers are deposited to form the AR-coating.

Keywords: InGaAs, micro sensor array, p-i-n photodiode, rapid thermal diffusion, Zn diffusion

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Authors: Yisau Adelaja Odusote, Olakanmi Felix Akinto

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The associative tendency between like atoms in molten Cd-Ga and Cd-In alloy systems has been studied by using the Quasi-Chemical Approximation Model (QCAM). The concentration dependence of the microscopic functions (the concentration-concentration fluctuations in the long-wavelength limits, Scc(0), the chemical short-range order (CSRO) parameter α1 as well as the chemical diffusion) and the mixing properties as the free energy of mixing, GM, enthalpy of mixing and entropy of mixing of the two molten alloys have been determined. Thermodynamic properties of both systems deviate positively from Raoult's law, while the systems are characterized by positive interaction energy. The role of atomic size ratio on the alloying properties was discussed.

Keywords: homo-pairs, interchange energy, enthalpy, entropy, Cd-Ga, Cd-In

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Authors: Jing Lin, Zou Yiming, Goei Ronn, Li Yun, Amanda Ong Jiamin, Alfred Tok Iing Yoong

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High-entropy alloy (HEA) coatings comprise multiple (five or more) principal elements that give superior mechanical, electrical, and thermal properties. However, the current synthesis methods of HEA coating still face huge challenges in facile and controllable preparation, as well as conformal integration, which seriously restricts their potential applications. Herein, we report a controllable synthesis of conformal quinary HEA coating consisting of noble metals (Rh, Ru, Ir, Pt, and Pd) by using the atomic layer deposition (ALD) with a post-annealing approach. This approach realizes low temperature (below 200 °C), precise control (nanoscale), and conformal synthesis (over complex substrates) of HEA coating. Furthermore, the resulting quinary HEA coating shows promising potential as a platform for catalysis, exhibiting substantially enhanced electrocatalytic hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performances as compared to other noble metal-based structures such as single metal coating or multi-layered metal composites.

Keywords: high-entropy alloy, thin-film, catalysis, water splitting, atomic layer deposition

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Authors: K. P. Shinde, M. V. Tien, H. Lin, H.-R. Park, S.-C.Yu, K. C. Chung, D.-H. Kim

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Magnetic refrigeration provides an attractive alternative cooling technology due to its potential advantages such as high cooling efficiency, environmental friendliness, low noise, and compactness over the conventional cooling techniques based on gas compression. Magnetocaloric effect (MCE) occurs by changes in entropy (ΔS) and temperature (ΔT) under external magnetic fields. We have been focused on identifying materials with large MCE in two temperature regimes, not only room temperature but also at cryogenic temperature for specific technological applications, such as space science and liquefaction of hydrogen in fuel industry. To date, the commonly used materials for cryogenic refrigeration are based on hydrated salts. In the present work, we report giant MCE in rare earth Ho2O3 nanopowder at cryogenic temperature. HoN nanoparticles with average size of 30 nm were prepared by using plasma arc discharge method with gas composition of N2/H2 (80%/20%). The prepared HoN was sintered in air atmosphere at 1200 oC for 24 hrs to convert it into oxide. Structural and morphological properties were studied by XRD and SEM. XRD confirms the pure phase and cubic crystal structure of Ho2O3 without any impurity within error range. It has been discovered that Holmium oxide exhibits giant MCE at low temperature without magnetic hysteresis loss with the second-order antiferromagnetic phase transition with Néels temperature around 2 K. The maximum entropy change was found to be 25.2 J/kgK at an applied field of 6 T.

Keywords: magnetocaloric effect, Ho₂O₃, magnetic entropy change, nanopowder

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Zhibo Zhao, Horst Hahn, Robert Kruk, Abhisheck Sarkar

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High entropy oxides (HEOs), based on the incorporation of multiple-principal cations into the crystal lattice, offer the possibility to explore previously inaccessible oxide compositions and unconventional properties. Here it is demonstrated that despite the chemical complexity of HEOs external stimuli, such as epitaxial strain, can selectively stabilize certain magneto-electronic states. Epitaxial (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄-HEO thin films are grown in three different strain states: tensile, compressive, and relaxed. A unique coexistence of rocksalt and spinel-HEO phases, which are fully coherent with no detectable chemical segregation, is revealed by transmission electron microscopy. This dual-phase coexistence appears as a universal phenomenon in (Co₀.₂Cr₀.₂Fe₀.₂Mn₀.₂Ni₀.₂)₃O₄ epitaxial films. Prominent changes in the magnetic anisotropy and domain structure highlight the strain-induced bidirectional control of magnetic properties in HEOs. When the films are relaxed, their magnetization behavior is isotropic, similar to that of bulk materials. However, under tensile strain, the hardness of the out-of-plane (OOP) axis increases significantly. On the other hand, compressive straining results in an easy OOP magnetization and a maze-like magnetic domain structure, indicating perpendicular magnetic anisotropy. Generally, this study emphasizes the adaptability of the high entropy design strategy, which, when combined with coherent strain engineering, opens additional prospects for fine-tuning properties in oxides.

Keywords: high entropy oxides, thin film, strain tuning, perpendicular magnetic anistropy

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Authors: Geetika Barman, B. S. Daya Sagar

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In this article, we proposed a pixel-wise classification of hyperspectral images using a mathematical morphology operator-based distance metric called “dilation distance” and “erosion distance”. This method involves measuring the spatial distance between the spectral features of a hyperspectral image across the bands. The key concept of the proposed approach is that the “dilation distance” is the maximum distance a pixel can be moved without changing its classification, whereas the “erosion distance” is the maximum distance that a pixel can be moved before changing its classification. The spectral signature of the hyperspectral image carries unique class information and shape for each class. This article demonstrates how easily the dilation and erosion distance can measure spatial distance compared to other approaches. This property is used to calculate the spatial distance between hyperspectral image feature vectors across the bands. The dissimilarity matrix is then constructed using both measures extracted from the feature spaces. The measured distance metric is used to distinguish between the spectral features of various classes and precisely distinguish between each class. This is illustrated using both toy data and real datasets. Furthermore, we investigated the role of flat vs. non-flat structuring elements in capturing the spatial features of each class in the hyperspectral image. In order to validate, we compared the proposed approach to other existing methods and demonstrated empirically that mathematical operator-based distance metric classification provided competitive results and outperformed some of them.

Keywords: dilation distance, erosion distance, hyperspectral image classification, mathematical morphology

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Anthony R. Hassan, Jacob A. Gbadeyan

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In this paper, the analysis of a reactive hydromagnetic Poiseuille fluid flow under each of sensitized, Arrhenius and bimolecular chemical kinetics through a channel in the presence of heat source is carried out. An exothermic reaction is assumed while the concentration of the material is neglected. Adomian Decomposition Method (ADM) together with Pade Approximation is used to obtain the solutions of the governing nonlinear non – dimensional differential equations. Effects of various physical parameters on the velocity and temperature fields of the fluid flow are investigated. The entropy generation analysis and the conditions for thermal criticality are also presented.

Keywords: chemical kinetics, entropy generation, thermal criticality, adomian decomposition method (ADM) and pade approximation

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Authors: Marzena Tokarewicz, Malgorzata Gradzka-Dahlke

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High-entropy alloys (HEAs) have gained significant attention due to their great potential as functional and structural materials. HEAs have very good mechanical properties (in particular, alloys based on CoCrNi). They also show the ability to maintain their strength at high temperatures, which is extremely important in some applications. AlCoCrFeNi alloy is one of the most studied high-entropy alloys. Scientists often study the effect of changing the aluminum content in this alloy because it causes significant changes in phase presence and microstructure and consequently affects its hardness, ductility, and other properties. Research conducted by the authors also investigates the effect of aluminium content in AlₓCoCrFeNi alloy on its microstructure and mechanical properties. AlₓCoCrFeNi alloys were prepared by vacuum induction melting. The obtained samples were examined for chemical composition, microstructure, and microhardness. The three-point bending method was carried out to determine the bending strength, bending modulus, and conventional bending yield strength. The obtained results confirm the influence of aluminum content on the properties of AlₓCoCrFeNi alloy. Most studies on AlₓCoCrFeNi alloy focus on the determination of mechanical properties in compression or tension, much less in bending. The achieved results provide valuable information on the bending properties of AlₓCoCrFeNi alloy and lead to interesting conclusions.

Keywords: bending properties, high-entropy alloys, induction melting, microstructure

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Authors: Minakshi Mainaji Sonawane, Bharti W. Gawali, Sudhir Mendhekar, Ramesh R. Manza

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People's lives and health are severely impacted by skin diseases. A new study proposes an effective method for identifying the different forms of skin diseases. Image denoising is a technique for improving image quality after it has been harmed by noise. The proposed technique is based on the usage of the wavelet transform. Wavelet transform is the best method for analyzing the image due to the ability to split the image into the sub-band, which has been used to estimate the noise ratio at the noisy image. According to experimental results, the proposed method presents the best values for MSE, PSNR, and Entropy for denoised images. we can found in Also, by using different types of wavelet transform filters is make the proposed approach can obtain the best results 23.13, 20.08, 50.7 for the image denoising process

Keywords: MSE, PSNR, entropy, Gaussian filter, DWT

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

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Authors: Navdeep Goel, Salvador Gabarda

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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Dalibor Štys, Kryštof M. Stys, Maryia Chkalova, Petr Kouba, Aliaxandr Pautsina, Dalibor Štys Jr., Jana Pečenková, Denis Durniev, Tomáš Náhlík, Petr Císař

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In this article, a construction and some properties of the 5iD viewer, the system recording simultaneously five views of a given experimental object is reported. Properties of the system are demonstrated on the analysis of fish schooling behavior. It is demonstrated the method of instrument calibration which allows inclusion of image distortion and it is proposed and partly tested also the method of distance assessment in the case that only two opposite cameras are available. Finally, we demonstrate how the state trajectory of the behavior of the fish school may be constructed from the entropy of the system.

Keywords: 3D positioning, school behavior, distance calibration, space vision, space distortion

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Authors: Essebti Dhahri

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We present a new refrigerant La₀.₇Ca₀.₁₅Sr₀.₁₅Mn₁₋ₓGaₓO₃ (x = 0.0-0.1) manganites. These compounds were prepared by the sol-gel method. The refinement of the X-ray diffraction reveals that all samples crystallize in a rhombohedral structure (space group R3 ̅c). Detailed measurements of the magnetization as a function of temperature and magnetic applied field M (µ₀H, T) were carried out. From the M(µ₀H, T) curves, we have calculated the magnetic entropy change (ΔSM) according to the Maxwell relation. The temperature dependence of the magnetization M(T) reveals a decrease of M when increasing the x content. The magnetic entropy change (ΔSM) reaches a maximum value near room temperature. It was also found that this compound exhibits a large magnetocaloric effect MCE which increases when decreasing Ga concentration. So, the studied compounds could be considered potential materials for magnetic refrigeration application.

Keywords: magnetic measurements, Rietveld refinement, magnetic refrigeration, magnetocaloric effect

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Authors: Mario Alejandro Grisales, M. Daniela Chimá, Gilberto Bejarano Gaitán

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High entropy alloys (HEA) and nitride (HEN) are currently very attractive to the automotive, aerospace, metalworking and materials forming manufacturing industry, among others, for exhibiting higher mechanical properties, wear resistance, and thermal stability than binary and ternary alloys. In this work medium-entropy coatings of TiTaZrNb and the nitrides of (TiTaZrNb)Nx were synthesized on to AISI 420 and M2 steel samples by the direct current magnetron sputtering technique. The influence of the bias voltage supplied to the substrate on the microstructure, chemical- and phase composition of the matrix coating was evaluated, and the effect of nitrogen flow on the microstructural, mechanical and tribological properties of the corresponding nitrides was studied. A change in the crystalline structure from BCC for TiTaZrNb coatings to FCC for (TiTaZrNb)Nx was observed, that is associated with the incorporation of nitrogen into the matrix and the consequent formation of a solid solution of (TiTaZrNb)Nx. An increase in hardness and residual stresses was observed with increasing bias voltage for TiTaZrNb, reaching 12.8 GPa for the coating deposited with a bias of -130V. In the case of (TiTaZrNb)Nx nitride, a greater hardness of 23 GPa is achieved for the coating deposited with a N2 flow of 12 sccm, which slightly drops to 21.7 GPa for that deposited with N2 flow of 15 sccm. The slight reduction in hardness could be associated with the precipitation of the TiN and ZrN phases that are formed at higher nitrogen flows. The specific wear rate of the deposited coatings ranged between 0.5xexp13 and 0.6xexp13 N/m2. The steel substrate exhibited an average hardness of 2.0 GPa and a specific wear rate of 203.2exp13 N/m2. Both the hardness and the specific wear rate of the synthesized nitride coatings were higher than that of the steel substrate, showing a protective effect of the steel against wear.

Keywords: medium entropy coatings, hard coatings, magnetron sputtering, tribology, wear resistance

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Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: image compression, color image, q-coder, quantization, edge-detection

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Authors: Prangya P. Sahoo, B. S. Murty

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The present study deals with phase evolution of oxide dispersed CoCrFeMnNi high entropy alloy as a function of amount of added Y2O3 during mechanical alloying and analysis of grain growth kinetics of CoCrFeMnNi high entropy alloy without and with oxide dispersion. Mechanical alloying of CoCrFeMnNi resulted in a single FCC phase. However, evolution of chromium carbide was observed after heat treatment between 1073 and 1473 K. Comparison of grain growth time exponents and activation energy barrier is also reported. Micro structural investigations, using electron microscopy and EBSD techniques, were carried out to confirm the enhanced grain growth resistance which is attributed to the presence oxide dispersoids.

Keywords: grain growth kinetics, mechanical alloying, oxide dispersion, phase evolution

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Authors: D. M. S. Bandara, Yunqi Lei, Ye Luo

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Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.

Keywords: arnold cat map, biometric encryption, block cipher, elliptic curve cryptography, fingerprint encryption, Koblitz’s encoding

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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Authors: Lukáš Klein, Karel Žídek

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Hyperspectral imaging counts among the most frequently used multidimensional sensing methods. While there are many approaches to capturing a hyperspectral data cube, optical compression is emerging as a valuable tool to reduce the setup complexity and the amount of data storage needed. Hyperspectral compressive imagers have been created in the past; however, they have primarily focused on relatively narrow sections of the electromagnetic spectrum. A broader spectral study of samples can provide helpful information, especially for applications involving the harmonic generation and advanced material characterizations. We demonstrate a broadband hyperspectral microscope based on the single-pixel camera principle. Captured spatially encoded data are processed to reconstruct a hyperspectral cube in a combined visible and near-infrared spectrum (from 400 to 2500 nm). Hyperspectral cubes can be reconstructed with a spectral resolution of up to 3 nm and spatial resolution of up to 7 µm (subject to diffraction) with a high compressive ratio.

Keywords: compressive imaging, hyperspectral imaging, near-infrared spectrum, single-pixel camera, visible spectrum

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Authors: Hao Zhang, Hongyang Yu

Abstract:

Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.

Keywords: RGB-D, SLAM, dense depth, depth map

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

Abstract:

In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Lorena Mihelac, Janez Povh

Abstract:

In 2017, we conducted a research study using data consisting of 160 musical excerpts from different musical styles, to analyze the impact of entropy of the harmony on the acceptability of music. In measuring the entropy of harmony, we were interested in unigrams (individual chords in the harmonic progression) and bigrams (the connection of two adjacent chords). In this study, it has been found that 53 musical excerpts out from 160 were evaluated by participants as very complex, although the entropy of the harmonic progression (unigrams and bigrams) was calculated as low. We have explained this by particularities of chord progression, which impact the listener's feeling of complexity and acceptability. We have evaluated the same data twice with new participants in 2018 and with the same participants for the third time in 2019. These three evaluations have shown that the same 53 musical excerpts, found to be difficult and complex in the study conducted in 2017, are exhibiting a high feeling of complexity again. It was proposed that the content of these musical excerpts, defined as “irregular,” is not meeting the listener's expectancy and the basic perceptual principles, creating a higher feeling of difficulty and complexity. As the “irregularities” in these 53 musical excerpts seem to be perceived by the participants without being aware of it, affecting the pleasantness and the feeling of complexity, they have been defined as “subliminal irregularities” and the 53 musical excerpts as “irregular.” In our recent study (2019) of the same data (used in previous research works), we have proposed a new measure of the complexity of harmony, “regularity,” based on the irregularities in the harmonic progression and other plausible particularities in the musical structure found in previous studies. We have in this study also proposed a list of 10 different particularities for which we were assuming that they are impacting the participant’s perception of complexity in harmony. These ten particularities have been tested in this paper, by extending the analysis in our 53 irregular musical excerpts from harmony to melody. In the examining of melody, we have used the computational model “Information Dynamics of Music” (IDyOM) and two information-theoretic measures: entropy - the uncertainty of the prediction before the next event is heard, and information content - the unexpectedness of an event in a sequence. In order to describe the features of melody in these musical examples, we have used four different viewpoints: pitch, interval, duration, scale degree. The results have shown that the texture of melody (e.g., multiple voices, homorhythmic structure) and structure of melody (e.g., huge interval leaps, syncopated rhythm, implied harmony in compound melodies) in these musical excerpts are impacting the participant’s perception of complexity. High information content values were found in compound melodies in which implied harmonies seem to have suggested additional harmonies, affecting the participant’s perception of the chord progression in harmony by creating a sense of an ambiguous musical structure.

Keywords: entropy and information content, harmony, subliminal (ir)regularity, IDyOM

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