Search results for: Magnetic Resonance Images MRI

Authors: Delara Kazempour, Mashallah Abasi Dezfuli, Reza Javidan

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Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform.

Keywords: video compression, contourlet transform, discrete cosine transform, wavelet transform

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Authors: Navneet Dabra, Jasbir S. HUndal

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Hetero-structured nano-composite thin film of Ba0.5Sr0.5TiO3/Bi0.9La0.1Fe0.9Mn0.1O3 (BST/BLFM) has been prepared by chemical solution deposition method with various BST to BLFM thickness ratios. These films have been deposited over on p-type Si (100) substrate. These samples exhibited low leakage current, large grain size and uniform distribution of particles. The maximum remanent polarization (Pr) was achieved in the heterostructures with thickness ratio of 2.65. The dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H), ferromagnetic exchange interaction and magnetoelectric measurements were carried out. Field Emission Scanning Electron Microscopy has been employed to investigate the surface morphology of these heterostructured nano-composite films.

Keywords: magnetoelectric, Schottky emission, interface coupling, dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H)

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Ana Maria Reis d'Azevedo Breda, Catarina Maria Neto da Cruz

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The role of images/illustrations in communicating meanings and triggering emotions assumes an increasingly relevant role in contemporary texts, regardless of the age group for which they are intended or the nature of the texts that host them. It is no coincidence that children's books are full of illustrations and that the image/text ratio decreases as the age group grows. The vast majority of children's books can be considered multimodal texts containing text and images/illustrations interacting with each other to provide the young reader with a broader and more creative understanding of the book's narrative. This interaction is very diverse, ranging from images/illustrations that are not essential for understanding the storytelling to those that contribute significantly to the meaning of the story. Usually, these books are also read by adults, namely by parents, educators, and teachers who act as mediators between the book and the children, explaining aspects that are or seem to be too complex for the child's context. It should be noted that there are books labeled as children's books that are clearly intended for both children and adults. In this work, following a qualitative and interpretative methodology based on written productions, participant observation, and field notes, we will describe the perceptions of future teachers of the 1st cycle of basic education, attending a master's degree at a Portuguese university, about the role of the image in literary and non-literary texts, namely in mathematical texts, and how these can constitute precious resources for emotional regulation and for the design of creative didactic situations. The analysis of the collected data allowed us to obtain evidence regarding the evolution of the participants' perception regarding the crucial role of images in children's literature, not only as an emotional regulator for young readers but also as a creative source for the design of meaningful didactical situations, crossing other scientific areas, other than the mother tongue, namely mathematics.

Keywords: children’s literature, emotions, multimodal texts, soft skills

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Ting-Ting Wen, Jung-Ruey Tsai

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This paper reports a method for the replication of micro-scale structures. By using electromagnetic force-assisted imprinting system with magnetic soft stamp written square-microlens cavity, a photopolymer square-microlens structures can be rapidly fabricated. Under the proper processing conditions, the polymeric square-microlens structures with feature size of width 100.3um and height 15.2um across a large area can be successfully fabricated. Scanning electron microscopy (SEM) and surface profiler observations confirm that the micro-scale polymer structures are produced without defects or distortion and with good pattern fidelity over a 60x60mm2 area. This technique shows great potential for the efficient replication of the micro-scale structure array at room temperature and with high productivity and low cost.

Keywords: square-microlens structures, electromagnetic force-assisted imprinting, magnetic soft stamp

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Authors: Ahmed Nour El Islam Ayad, Tahar Rouibah, Wafa Krika, Houari Boudjella, Larab Moulay, Farid Benhamida, Selma Benmoussa

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The purpose of this study is to evaluate the electromagnetic field of an underground cable of very high voltage perforated by nail. The aim of this work shows a numerical simulation of the electromagnetic field of 400 kV line after perforation through a ferrous nail in four positions for the pinch pin at different distances. From results for a longitudinal section, we observe and evaluate the distribution and the variation of the electromagnetic field in the cable and the earth. When the nail approaches the underground power cable, the distribution of the magnetic field changes and takes several forms, the magnetic field increase and become very important when the nail breaks the metal screen and will produce a significant leak of the electric field, characterized by a large electric arc and or electric discharge to earth and then a fault in the electrical network. These electromagnetic analysis results help to detect defects in underground cables.

Keywords: underground, electromagnetic, nail, defect

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Authors: Nazish Saleem Abbas, Muhammad Haris Jamil, Hamid Sharif

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Digital watermarking is a technique that allows an individual to add and hide secret information, copyright notice, or other verification message inside a digital audio, video, or image. Today, with the advancement of technology, modern healthcare systems manage patients’ diagnostic information in a digital way in many countries. When transmitted between hospitals through the internet, the medical data becomes vulnerable to attacks and requires security and confidentiality. Digital watermarking techniques are used in order to ensure the authenticity, security and management of medical images and related information. This paper proposes a watermarking technique that embeds a watermark in medical images imperceptibly and securely. In this work, digital watermarking on medical images is carried out using the Least Significant Bit (LSB) with the Discrete Cosine Transform (DCT). The proposed methods of embedding and extraction of a watermark in a watermarked image are performed in the frequency domain using LSB by XOR operation. The quality of the watermarked medical image is measured by the Peak signal-to-noise ratio (PSNR). It was observed that the watermarked medical image obtained performing XOR operation between DCT and LSB survived compression attack having a PSNR up to 38.98.

Keywords: watermarking, image processing, DCT, LSB, PSNR

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Authors: Tunahan Sapmaz, Harun Etçi, İbrahim Şenol, Yasemin Öner

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Rotor bar dimensions have a great influence on the air-gap magnetic flux density. Therefore, poor selection of this parameter during the machine design phase causes the air-gap magnetic flux density to be distorted. Thus, it causes noise, torque fluctuation, and losses in the induction motor. On the other hand, the change in rotor bar dimensions will change the resistance of the conductor, so the current will be affected. Therefore, the increase and decrease of rotor bar current affect operation, starting torque, and efficiency. The aim of this study is to examine the effect of rotor bar dimensions on the electromagnetic performance criteria of the induction motor. Modeling of the induction motor is done by the finite element method (FEM), which is a very powerful tool. In FEM, the results generally focus on performance criteria such as torque, torque fluctuation, efficiency, and current.

Keywords: induction motor, finite element method, optimization, rotor bar

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Authors: Z. Mortezaie, H. Hassanpour, S. Asadi Amiri

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Captured images may suffer from Gaussian blur due to poor lens focus or camera motion. Unsharp masking is a simple and effective technique to boost the image contrast and to improve digital images suffering from Gaussian blur. The technique is based on sharpening object edges by appending the scaled high-frequency components of the image to the original. The quality of the enhanced image is highly dependent on the characteristics of both the high-frequency components and the scaling/gain factor. Since the quality of an image may not be the same throughout, we propose an adaptive unsharp masking method in this paper. In this method, the gain factor is computed, considering the gradient variations, for individual pixels of the image. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed unsharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.

Keywords: unsharp masking, blur image, sub-region gradient, image enhancement

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Authors: Hannah Nagel, Hayley Lang, Albert Sole Guitart, Natasha Lean, Rachel Allavena, Cleide Sprohnie-Barrera, Alex Young

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Aggressive neoplasia of the hoof is a rare occurrence in horses and has been only sporadically described in the literature. In the few cases reported intra-hoof wall, aggressive neoplasia has been documented radiographically and has been described with variable imaging characteristics. These include a well-defined osteolytic area, a smoothly outlined semi-circular defect, an extensive draining tract beneath the hoof wall, as well as an additional large area of osteolysis or an extensive central lytic region. A 20-year-old Quarterhorse gelding and a 10-year-old Thoroughbred gelding were both presented for chronic reoccurring lameness in the left forelimb and left hindlimb, respectively. Both of the cases displayed radiographic lesions that have been previously described but also displayed osteoproliferative expansile regions of additional bone formation. Changes associated with hoof neoplasia are often non-specific due to the nature and capacity of bone to react to pathological insult, which is either to proliferate or be absorbed. Both cases depict and describe imaging findings seen on radiography, contrast radiography, computed tomography, and magnetic resonance imaging before reaching a histological diagnosis of malignant melanoma and squamous cell carcinoma. Although aggressive hoof wall neoplasia is rare, there are some imaging features which may raise our index of suspicion for an aggressive hoof wall lesion. This case report documents two horses with similar imaging findings who underwent multiple assessments, surgical interventions, and imaging modalities with a final diagnosis of malignant neoplasia.

Keywords: horse, hoof, imaging, radiography, neoplasia

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Authors: Mohammad Javaherian, Siamak Bashardoust Tajali, Monavvar Hadizadeh

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Objective: This systematic review study was conducted to evaluate the effects of Pulsed Electromagnetic (PEMF) and Static Magnetic Fields (SMG) on pain relief and functional improvement in patients with musculoskeletal Low Back Pain (LBP). Methods: Seven electronic databases were searched by two researchers independently to identify the published Randomized Controlled Trials (RCTs) on the efficacy of pulsed electromagnetic, static magnetic, and therapeutic nuclear magnetic fields. The identified databases for systematic search were Ovid Medline®, Ovid Cochrane RCTs and Reviews, PubMed, Web of Science, Cochrane Library, CINAHL, and EMBASE from 1968 to February 2016. The relevant keywords were selected by Mesh. After initial search and finding relevant manuscripts, all references in selected studies were searched to identify second hand possible manuscripts. The published RCTs in English would be included to the study if they reported changes on pain and/or functional disability following application of magnetic fields on chronic musculoskeletal low back pain. All studies with surgical patients, patients with pelvic pain, and combination of other treatment techniques such as acupuncture or diathermy were excluded. The identified studies were critically appraised and the data were extracted independently by two raters (M.J and S.B.T). Probable disagreements were resolved through discussion between raters. Results: In total, 1505 abstracts were found following the initial electronic search. The abstracts were reviewed to identify potentially relevant manuscripts. Seventeen possibly appropriate studies were retrieved in full-text of which 48 were excluded after reviewing their full-texts. Ten selected articles were categorized into three subgroups: PEMF (6 articles), SMF (3 articles), and therapeutic nuclear magnetic fields (tNMF) (1 article). Since one study evaluated tNMF, we had to exclude it. In the PEMF group, one study of acute LBP did not show significant positive results and the majority of the other five studies on Chronic Low Back Pain (CLBP) indicated its efficacy on pain relief and functional improvement, but one study with the lowest sessions (6 sessions during 2 weeks) did not report a significant difference between treatment and control groups. In the SMF subgroup, two articles reported near significant pain reduction without any functional improvement although more studies are needed. Conclusion: The PEMFs with a strength of 5 to 150 G or 0.1 to 0.3 G and a frequency of 5 to 64 Hz or sweep 7 to 7KHz can be considered as an effective modality in pain relief and functional improvement in patients with chronic low back pain, but there is not enough evidence to confirm their effectiveness in acute low back pain. To achieve the appropriate effectiveness, it is suggested to perform this treatment modality 20 minutes per day for at least 9 sessions. SMFs have not been reported to be substantially effective in decreasing pain or improving the function in chronic low back pain. More studies are necessary to achieve more reliable results.

Keywords: pulsed electromagnetic field, static magnetic field, magnetotherapy, low back pain

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Authors: Z. Nougrara, J. Meunier

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In this paper, we present a new approach for extracting roads, there road network and its nodes from satellite image representing regions in Algeria. Our approach is related to our previous research work. It is founded on the information theory and the mathematical morphology. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. The main interest of this study is to solve the problem of the automatic mapping from satellite images. This study is thus applied for that the geographical representation of the images is as near as possible to the reality.

Keywords: nodes, road network, satellite image, updating a road map

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Authors: A. V. Trukhanov, S. V. Trukhanov, L. V. Panina, V. G. Kostishin, V. A. Turchenko

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It has been shown that BaFe₁₂O₁₉ is a perspective room-temperature multiferroic material. A large spontaneous polarization was observed for the BaFe₁₂O₁₉ ceramics revealing a clear ferroelectric hysteresis loop. The maximum polarization was estimated to be approximately 11.8 μC/cm². The FeO₆ octahedron in its perovskite-like hexagonal unit cell and the shift of Fe³⁺ off the center of octahedron are suggested to be the origin of the polarization in BaFe₁₂O₁₉. The magnetic field induced electric polarization has been also observed in the doped BaFe_12-x-δSc_xM_δO₁₉ (δ=0.05) at 10 K and in the BaSc_xFe_12−xO₁₉ and SrSc_xFe_12−xO₁₉ (x = 1.3–1.7) M-type hexaferrites. The investigated BaFe_12-xD_xO₁₉ (x=0.1, D-Al³⁺, In³⁺) samples have been obtained by two-step “topotactic” reactions. The powder neutron investigations of the samples were performed by neutron time of flight method at High Resolution Fourier Diffractometer.

Keywords: substituted hexaferrites, ferrimagnetics, ferroelectrics, neutron powder diffraction, crystal and magnetic structures

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Authors: Barun Raychaudhuri

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A methodology is proposed for estimating the optical attenuation and proportional depth variation of shallow inland water. The process is demonstrated with EO-1 Hyperion hyperspectral and IRS-P6 LISS-3 multispectral images of Kolkata city nearby area centered around 22º33′ N 88º26′ E. The attenuation coefficient of water was found to change with fine resolution of wavebands and in presence of suspended organic matter in water.

Keywords: hyperion, hyperspectral, Kolkata, water depth

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Authors: Keerthilatha Pai, Sakshi Kamra

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Objectives: Determining the position of the mandibular canal prior to implant placement and surgeries of the posterior mandible are important to avoid the nerve injury. The visibility of the mandibular canal varies according to the imaging modality. Although panoramic radiography is the most common, slowly cone beam computed tomography is replacing it. This study was conducted with an aim to determine and compare the visibility of superior and inferior borders of the mandibular canal in digital panoramic radiograph, reformatted panoramic radiograph and cross-sectional images of cone beam computed tomography. Study design: digital panoramic, reformatted panoramic radiograph and cross sectional CBCT images of 25 human mandibles were evaluated for the visibility of the superior and inferior borders of the mandibular canal according to a 5 point scoring criteria. Also, the canal was evaluated as completely visible, partially visible and not visible. The mean scores and visibility percentage of all the imaging modalities were determined and compared. The interobserver and intraobserver agreement in the visualization of the superior and inferior borders of the mandibular canal were determined. Results: The superior and inferior borders of the mandibular canal were completely visible in 47% of the samples in digital panoramic, 63% in reformatted panoramic and 75.6% in CBCT cross-sectional images. The mandibular canal was invisible in 24% of samples in digital panoramic, 19% in reformatted panoramic and 2% in cross-sectional CBCT images. Maximum visibility was seen in Zone 5 and least visibility in Zone 1. On comparison of all the imaging modalities, CBCT cross-sectional images showed better visibility of superior border in Zones 2,3,4,6 and inferior border in Zones 2,3,4,6. The difference was statistically significant. Conclusion: CBCT cross-sectional images were much superior in the visualization of the mandibular canal in comparison to reformatted and digital panoramic radiographs. The inferior border was better visualized in comparison to the superior border in digital panoramic imaging. The mandibular canal was maximumly visible in posterior one-third region of the mandible and the visibility decreased towards the mental foramen.

Keywords: cone beam computed tomography, mandibular canal, reformatted panoramic radiograph, visualization

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: Wael Elsaady, S. Olutunde Oyadiji, Adel Nasser

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The non-linear flow characteristics of magnetorheological (MR) fluids in MR dampers are studied via a coupled numerical approach that incorporates a two-phase flow model. The approach couples the Finite Element (FE) modelling of the damper magnetic circuit, with the Computational Fluid Dynamics (CFD) analysis of the flow field in the damper. The two-phase flow CFD model accounts for the effect of fluid compressibility due to the presence of liquid and gas in the closed domain of the damper. The dynamic mesh model included in ANSYS/Fluent CFD solver is used to simulate the movement of the MR damper piston in order to perform the fluid excitation. The two-phase flow analysis is studied by both Volume-Of-Fluid (VOF) model and mixture model that are included in ANSYS/Fluent. The CFD models show that the hysteretic behaviour of MR dampers is due to the effect of fluid compressibility. The flow field shows the distributions of pressure, velocity, and viscosity contours. In particular, it shows the high non-Newtonian viscosity in the affected fluid regions by the magnetic field and the low Newtonian viscosity elsewhere. Moreover, the dependence of gas volume fraction on the liquid pressure inside the damper is predicted by the mixture model. The presented approach targets a better understanding of the complicated flow characteristics of viscoplastic fluids that could be applied in different applications.

Keywords: viscoplastic fluid, magnetic FE analysis, computational fluid dynamics, two-phase flow, dynamic mesh, user-defined functions

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Authors: Dr., Suchita Daokar

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Background: Successful orthodontic treatment has always relied on anchorage. The stability of the implants depends on bone quantity, mini-implant design, and placement conditions. Out of the various methods of gaining stability, Platelet concentrations are gaining popularity for various reasons. PRF is a minimally invasive method, and there are various studies that has shown its role in enhancing the stability of general implants. However, there is no literature found regarding the effect of PRF in enhancing the stability of the orthodontic implant. Therefore, this study aimed to evaluate and assess the efficacy of PRF on the stability of the orthodontic implant. Methods: The study comprised of 9 subjects aged above 18 years of age. The split mouth technique was used; Group A (where implants were coated before insertion) and group B (implant were normally inserted). The stability of the implant was measured using resonance frequency analysis at insertion (T0), 24 hours (T1), 2 weeks (T2), at 4 weeks (T3), at 6 weeks (T4), and 8 weeks (T5) after insertion. Result: Statistically significant findings were found when group A was compared to group B using ANOVA test (p<0.05). The stability of the implant of group A at each time interval was greater than group B. The implant stability was high at T0 and reduces at T2, and increasing through T3 to T5. The stability was highest at T5. Conclusion: A chairside, minimally invasive procedure ofPRF coating on implants have shown promising results in improving the stability of orthodontic implants and providing scope for future studies.

Keywords: Orthodontic implants, stablity, resonance Frequency Analysis, pre

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Authors: Ghulam Mustafa Kamal, Xiaohua Wang, Bin Yuan, Abdullah Ijaz Hussain, Jie Wang, Shahzad Ali Shahid Chatha, Xu Zhang, Maili Liu

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Organic food products are becoming increasingly popular in recent years, as consumers have turned more health conscious and environmentally aware. A lot of consumers have understood that the organic foods are healthier than conventionally produced food stuffs. Price difference between conventional and organic foods is very high. So, it is very common to cheat the consumers by mislabeling and adulteration. Our study describes the 1H NMR based approach to characterize and differentiate soy sauce prepared from organically and conventionally grown raw materials (wheat and soybean). Commercial soy sauce samples fermented from organic and conventional raw materials were purchased from local markets. Principal component analysis showed clear separation among organic and conventional soy sauce samples. Orthogonal partial least squares discriminant analysis showed a significant (p < 0.01) separation among two types of soy sauce yielding leucine, isoleucine, ethanol, glutamate, lactate, acetate, β-glucose, sucrose, choline, valine, phenylalanine and tyrosine as important metabolites contributing towards this separation. Abundance ratio of 13C to 12C was also evaluated by 1H NMR spectroscopy which showed an increased ratio of 13C isotope in organic soy sauce samples indicating the organically grown wheat and soybean used for the preparation of organic soy sauce. Results of the study can be helpful to the end users to select the soy sauce of their choice. This information could also pave the way to further trace and authenticate the raw materials used in production of soy sauce.

Keywords: 1H NMR, multivariate analysis, organic, conventional, 13C isotopic ratio, soy sauce

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Authors: Jooyoung Park, Junkyeong Kim, Aoqi Zhang, Seunghee Park

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Non-destructive testing on cable is in great demand due to safety accidents at sites where many equipments using cables are installed. In this paper, the quantitative change of the obtained signal was analyzed using a magnetic flux leakage (MFL) method. A two-dimensional simulation was conducted with a FEM model replicating real elevator cables. The simulation data were compared for three parameters (depth of defect, width of defect and inspection velocity). Then, an experiment on same conditions was carried out to verify the results of the simulation. Signals obtained from both the simulation and the experiment were transformed to characterize the properties of the damage. Throughout the results, a cable damage detection based on an MFL method was confirmed to be feasible. In further study, it is expected that the MFL signals of an entire specimen will be gained and visualized as well.

Keywords: magnetic flux leakage (mfl), cable damage detection, non-destructive testing, numerical simulation

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Authors: J. Plocek, P. Holec, S. Kubickova, B. Pacakova, I. Matulkova, A. Mantlikova, I. Němec, D. Niznansky, J. Vejpravova

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This article presents summary on preparation and characterization of zinc, copper, cadmium and cobalt chromite nano crystals, embedded in an amorphous silica matrix. The ZnCr2O4/SiO2, CuCr2O4/SiO2, CdCr2O4/SiO2 and CoCr2O4/SiO2 nano composites were prepared by a conventional sol-gel method under acid catalysis. Final heat treatment of the samples was carried out at temperatures in the range of 900–1200 °C to adjust the phase composition and the crystallite size, respectively. The resulting samples were characterized by Powder X-ray diffraction (PXRD), High Resolution Transmission Electron Microscopy (HRTEM), Raman/FTIR spectroscopy and magnetic measurements. Formation of the spinel phase was confirmed in all samples. The average size of the nano crystals was determined from the PXRD data and by direct particle size observation on HRTEM; both results were correlated. The mean particle size (reviewed by HRTEM) was in the range from ~ 4 to 46 nm. The results showed that the sol-gel method can be effectively used for preparation of the spinel chromite nano particles embedded in the silica matrix and the particle size is driven by the type of the cation A2+ in the spinel structure and the temperature of the final heat treatment. Magnetic properties of the nano crystals were found to be just moderately modified in comparison to the bulk phases.

Keywords: sol-gel method, nanocomposites, Rietveld refinement, Raman spectroscopy, Fourier transform infrared spectroscopy, magnetic properties, spinel, chromite

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Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

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This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

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Authors: Aarushi Agarwal, Tara Singh, I.L Singh, Anju Lata Singh, Trayambak Tiwari

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Simple discrimination in near absence of attention has been widely observed. Dual-task studies with natural scenes studies have been claimed as being preattentive in nature that facilitated categorization simultaneously with the attentional demanding task. So in this study, multiple images at the periphery are presented, initiating parallel processing in near absence of attention. For the central demanding task rotated letters were presented in both conditions, while in periphery natural and animal images were presented. To understand the breakpoint of ability to perform in near absence of attention one, two and three peripheral images were presented simultaneously with central task and subjects had to respond when all belong to the same category. Individual participant performance did not show a significant difference in both conditions central and peripheral task when the single peripheral image was shown. In case of two images high-level parallel processing could take place with little attentional resources. The eye tracking results supports the evidence as no major saccade was made in a large number of trials. Three image presentations proved to be a breaking point of the capacities to perform outside attentional assistance as participants showed a confused eye gaze pattern which failed to make the natural and animal image discriminations. Thus, we can conclude attention and awareness being independent mechanisms having limited capacities.

Keywords: attention, dual task pardigm, parallel processing, break point, saccade

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Authors: Abhimanyu Thakur, Youngjin Lee

Abstract:

Glioma is a lethal brain cancer whose early diagnosis and prognosis are limited due to the dearth of a suitable technique for its early detection. Current approaches, including magnetic resonance imaging (MRI), computed tomography (CT), and invasive biopsy for the diagnosis of this lethal disease, hold several limitations, demanding an alternative method. Recently, extracellular vesicles (EVs) have been used in numerous biomarker studies, majorly exosomes and microvesicles (MVs), which are found in most of the cells and biofluids, including blood, cerebrospinal fluid (CSF), and urine. Remarkably, glioma cells (GMs) release a high number of EVs, which are found to cross the blood-brain-barrier (BBB) and impersonate the constituents of parent GMs including protein, and lncRNA; however, biophysical properties of EVs have not been explored yet as a biomarker for glioma. We isolated EVs from cell culture conditioned medium of GMs and regular primary culture, blood, and urine of wild-type (WT)- and glioma mouse models, and characterized by nano tracking analyzer, transmission electron microscopy, immunogold-EM, and differential light scanning. Next, we measured the biophysical parameters of GMs-EVs by using atomic force microscopy. Further, the functional constituents of EVs were examined by FTIR and Raman spectroscopy. Exosomes and MVs-derived from GMs, blood, and urine showed distinction biophysical parameters (roughness, adhesion force, and stiffness) and different from that of regular primary glial cells, WT-blood, and -urine, which can be attributed to the characteristic functional constituents. Therefore, biophysical features can be potential diagnostic biomarkers for glioma.

Keywords: glioma, extracellular vesicles, exosomes, microvesicles, biophysical properties

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Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Raghvendra Singh Yadav, Ivo Kuritka, Jarmila Vilcakova, Pavel Urbanek, Michal Machovsky, David Skoda, Milan Masar

Abstract:

The elastomer nanocomposites were synthesized by solution mixing method with an elastomer as a matrix and in situ thermally reduced graphene oxide (RGO) and spinel ferrite NiFe₂O₄ nanoparticles as filler. Spinel ferrite NiFe₂O₄ nanoparticles were prepared by the starch-assisted sol-gel auto-combustion method. The influence of filler on the microstructure, morphology, dielectric, electrical and magnetic properties of Reduced Graphene Oxide-Nickel Ferrite-Elastomer nanocomposite was characterized by X-ray diffraction, Raman spectroscopy, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, X-ray photoelectron spectroscopy, the Dielectric Impedance analyzer, and vibrating sample magnetometer. Scanning electron microscopy study revealed that the fillers were incorporated in elastomer matrix homogeneously. The dielectric constant and dielectric tangent loss of nanocomposites was decreased with the increase of frequency, whereas, the dielectric constant increases with the addition of filler. Further, AC conductivity was increased with the increase of frequency and addition of fillers. Furthermore, the prepared nanocomposites exhibited ferromagnetic behavior. This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: polymer-matrix composites, nanoparticles as filler, dielectric property, magnetic property

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Authors: Kumar Divyendra

Abstract:

Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Safia Akram

Abstract:

In this article, the effects of peristaltic transport with double-diffusive convection in nanofluids through an asymmetric channel with different waveforms is presented. Mathematical modelling for two-dimensional and two directional flows of a Jeffrey fluid model along with double-diffusive convection in nanofluids are given. Exact solutions are obtained for nanoparticle fraction field, concentration field, temperature field, stream functions, pressure gradient and pressure rise in terms of axial and transverse coordinates under the restrictions of long wavelength and low Reynolds number. With the help of computational and graphical results the effects of Brownian motion, thermophoresis, Dufour, Soret, and Grashof numbers (thermal, concentration, nanoparticles) on peristaltic flow patterns with double-diffusive convection are discussed.

Keywords: nanofluid particles, peristaltic flow, Jeffrey fluid, magnetic field, asymmetric channel, different waveforms

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