Relevant bibliographies by topics / Kagome layers

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Kagome layers'

Author: Grafiati
Published: 21 December 2024

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Journal articles on the topic "Kagome layers"

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Xie, Sheng-Yi, Xian-Bin Li, Wei Quan Tian, Nian-Ke Chen, Yeliang Wang, Shengbai Zhang, and Hong-Bo Sun. "A novel two-dimensional MgB6 crystal: metal-layer stabilized boron kagome lattice." Physical Chemistry Chemical Physics 17, no. 2 (2015): 1093–98. http://dx.doi.org/10.1039/c4cp03728f.

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Based on first-principles calculations, we designed for the first time a boron-kagome-based two-dimensional MgB6 crystal, in which two boron kagome layers sandwich a triangular magnesium layer.
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Gautam, Rinoj, and Sridhar Idapalapati. "Compressive Properties of Additively Manufactured Functionally Graded Kagome Lattice Structure." Metals 9, no. 5 (May 3, 2019): 517. http://dx.doi.org/10.3390/met9050517.

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Cellular lattice structures have important applications in aerospace, automobile and defense industries due to their high specific strength, modulus and energy absorption. Additive manufacturing provides the design freedom to fabricate complex cellular structures. This study investigates the compressive properties and deformation behavior of a Ti-6Al-4V unit Kagome structure fabricated by selective laser melting. Further, the mechanical performance of multi-unit and multi-layer Kagome structure of acrylonitrile butadiene styrene (ABS) ABS-M30™ manufactured by fused deposition modeling is explored. The effect of a number of layers of Kagome structure on the compressive properties is investigated. This paper also explores the mechanical properties of functionally graded and uniform density Kagome structure. The stiffness of the structure decreased with the increase in the number of layers whereas no change in peak load was observed. The functionally graded Kagome structure provided 35% more energy absorption than the uniform density structure.
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Yang, Yuxin, Wenhui Fan, Qinghua Zhang, Zhaoxu Chen, Xu Chen, Tianping Ying, Xianxin Wu, et al. "Discovery of Two Families of Vsb-Based Compounds with V-Kagome Lattice." Chinese Physics Letters 38, no. 12 (December 1, 2021): 127102. http://dx.doi.org/10.1088/0256-307x/38/12/127102.

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We report the structure and physical properties of two newly discovered compounds AV8Sb12 and AV6Sb6 (A = Cs, Rb), which have C 2 (space group: Cmmm) and C 3 (space group: R 3 ¯ m ) symmetry, respectively. The basic V-kagome unit appears in both compounds, but stacking differently. A V2Sb2 layer is sandwiched between two V3Sb5 layers in AV8Sb12, altering the V-kagome lattice and lowering the symmetry of kagome layer from hexagonal to orthorhombic. In AV6Sb6, the building block is a more complex slab made up of two half-V3Sb5 layers that are intercalated by Cs cations along the c-axis. Transport property measurements demonstrate that both compounds are nonmagnetic metals, with carrier concentrations at around 1021 cm−3. No superconductivity has been observed in CsV8Sb12 above 0.3 K under in situ pressure up to 46 GPa. Compared to CsV3Sb5, theoretical calculations and angle-resolved photoemission spectroscopy reveal a quasi-two-dimensional electronic structure in CsV8Sb12 with C 2 symmetry and no van Hove singularities near the Fermi level. Our findings will stimulate more research into V-based kagome quantum materials.
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Lee, Jeong-Eun, Ulrich Burkhardt, and Alexander Christoph Komarek. "Synthesis of a New Ruthenate Ba26Ru12O57." Crystals 10, no. 5 (April 30, 2020): 355. http://dx.doi.org/10.3390/cryst10050355.

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Single crystals of Ba 26 Ru 12 O 57 were grown by the floating zone method. The crystal structure is formed by an alternating stacking of pseudo-hexagonal Ru single layers and double layers. The Ru ions within the double layers are dimerized (Ru 2 O 9 ) whereas the Ru ions within the single layers arrange in a distorted Kagome lattice of trigonal bipyramidally coordinated RuO 5 polyhedra. Additionally, this Kagome lattice is “decorated” with RuO 6 octahedra that are situated in the central free spaces within this Kagome lattice. According to the composition, the oxidation state of most of the Ru ions should be formally close to 5+.
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Wulff, L., and Hk Müller-Buschbaum. "Isolierte trigonale SrO6 – Prismen verknüpfen Kagome-Netze im Strontium-Manganat(IV)-Tellurat(VI): SrMnTeO6 / Kagomé Layers Connected by Isolated Trigonal SrO6 Prisms in the Strontium Manganate(IV) Tellurate(VI): SrMnTeO6 L." Zeitschrift für Naturforschung B 53, no. 3 (March 1, 1998): 283–86. http://dx.doi.org/10.1515/znb-1998-0305.

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Abstract Single crystals of the hitherto unknown compound SrMnTeO6 have been prepared from Sr(OH)2 ·8H2O , MnCO3(aq) and TeO2 in air by crystallization below the melt range. X-ray investigations showed hexagonal symmetry, space group D33h -P6̅2m, lattice constants a = 5.143( 1), c = 5.384(2) A, Z = 1. SrMnTeO6 is characterized by staggered [(Mn/Te)6O18] Kagome layers along [001]. These layers are connected by Sr2+ ions, resulting in SrO6 prisms isolated from each other. The structure is discussed with respect to the connection of Kagome nets in the quaternary oxides of the Ba3Ln4O9 type.
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Yin, Qiangwei, Zhijun Tu, Chunsheng Gong, Shangjie Tian, and Hechang Lei. "Structures and physical properties of v-based kagome metals csv6sb6 and csv8sb12 *." Chinese Physics Letters 38, no. 12 (December 1, 2021): 127401. http://dx.doi.org/10.1088/0256-307x/38/12/127401.

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We report two new members of V-based kagome metals CsV6Sb6 and CsV8Sb12. The most striking structural feature of CsV6Sb6 is the V kagome bilayers. For CsV8Sb12, there is an intergrowth of two-dimensional V kagome layers and one-dimensional V chains, and the latter ones lead to the orthorhombic symmetry of this material. Further measurements indicate that these two materials exhibit metallic and Pauli paramagnetic behaviors. More importantly, different from CsV3Sb5, the charge density wave state and superconductivity do not emerge in CsV6Sb6 and CsV8Sb12 when temperature is above 2 K. Small magnetoresistance with saturation behavior and linear field dependence of Hall resistivity at high field and low temperature suggest that the carriers in both materials should be uncompensated with much different concentrations. The discovery of these two new V-based kagome metals sheds light on the exploration of correlated topological materials based on kagome lattice.
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Aidoudi, Farida H., Lewis J. Downie, Russell E. Morris, Mark A. de Vries, and Philip Lightfoot. "A hybrid vanadium fluoride with structurally isolated S = 1 kagome layers." Dalton Trans. 43, no. 17 (2014): 6304–7. http://dx.doi.org/10.1039/c4dt00452c.

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Yang, Ming, Su-Yun Zhang, Wen-Bin Guo, Ying-Ying Tang, and Zhang-Zhen He. "Spin-frustration in a new spin-1/2 oxyfluoride system (Cu13(VO4)4(OH)10F4) constructed by alternatively distorted kagome-like and triangular lattices." Dalton Transactions 44, no. 35 (2015): 15396–99. http://dx.doi.org/10.1039/c5dt02752g.

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Sun, Yu-Wei, Zhan-Wei Li, and Zhao-Yan Sun. "Multiple 2D crystal structures in bilayered lamellae from the direct self-assembly of 3D systems of soft Janus particles." Physical Chemistry Chemical Physics 24, no. 13 (2022): 7874–81. http://dx.doi.org/10.1039/d1cp05894k.

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Multiple highly-ordered 2D crystal structures, including a triangular lattice, kagome lattice, and even a Frank–Kasper σ phase, are found within the layers of bilayered lamellae self-assembled directly from 3D systems of soft Janus particles.
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Mu, Chao, Qiangwei Yin, Zhijun Tu, Chunsheng Gong, Ping Zheng, Hechang Lei, Zheng Li, and Jianlin Luo. "Tri-hexagonal charge order in kagome metal CsV3Sb5 revealed by 121Sb nuclear quadrupole resonance." Chinese Physics B 31, no. 1 (January 1, 2022): 017105. http://dx.doi.org/10.1088/1674-1056/ac422c.

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We report 121Sb nuclear quadrupole resonance (NQR) measurements on kagome superconductor CsV3Sb5 with T c = 2.5 K. 121Sb NQR spectra split after a charge density wave (CDW) transition at 94 K, which demonstrates a commensurate CDW state. The coexistence of the high temperature phase and the CDW phase between 91 K and 94 K manifests that it is a first order phase transition. The CDW order exhibits tri-hexagonal deformation with a lateral shift between the adjacent kagome layers, which is consistent with 2 × 2 × 2 superlattice modulation. The superconducting state coexists with CDW order and shows a conventional s-wave behavior in the bulk state.
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Dissertations / Theses on the topic "Kagome layers"

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Hadrane, Bachchar. "Vanadates de métaux de transition à feuillets kagomé : effets de la microstructure et des substitutions cationiques sur les propriétés structurales, vibrationnelles, optiques et magnétiques." Electronic Thesis or Diss., Nantes Université, 2024. http://www.theses.fr/2024NANU4029.

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Cette thèse explore les effets de la microstructure et des substitutions cationiques sur les propriétés structurales, vibrationnelles, optiques et magnétiques de matériaux vanadates à feuillets Kagomé de cobalt et de zinc, dont les structures cristallines sont similaires à celles de minéraux (karpenkoite, martyite et vesignieite). La structure cristalline du pyrovanadate microstructuré Co3V2O7(OH)2·nH2O, préparé via la voie hydrothermale est résolue. Ses propriétés physicochimiques et magnétiques sont étudiées et comparées à celles reportées dans la littérature. L’effet de la substitution des ions Co2+ haut-spin par des ions Zn2+ est analysé pour une nouvelle solution solide microstructurée (Co1-xZnx)3V2O7(OH)2·wH2O. Les essais de synthèse du matériau Co3V2O7(OH)2·nH2O nanostructuré par coprécipitation à pression ambiante conduisent à un nouveau pyrovanadate microstructuré de formulation approchée NH4Co2.5V2O7(OH)2·H2O. Par ailleurs, l’orthovanadate BaCo3(VO4)2(OH)2 microstructuré est obtenu en utilisant Co3V2O7(OH)2·nH2O comme précurseur et ses propriétés sont comparées à celles d’échantillons nanostructurés récemment obtenus. Une telle comparaison est également réalisée pour le nouvel orthovanadate isostructural BaZn3(VO4)2(OH)2, préparé sous formes micro- et nanocristallisée. L’effet de la substitution cationique Co/Zn est étudié pour une nouvelle solution solide microstructurée Ba(Co1-xZnx)3(VO4)2(OH)2 et pour des échantillons nanostructurés de compositions similaires. Ce travail ouvre des possibilités d’études d’autres solutions solides analogues, comme Ba(Co1-xNix)3(VO4)2(OH)2
This thesis explores the effects of microstructure and cationic substitutions on the structural, vibrational, optical, and magnetic properties of cobalt or zinc Kagome layered vanadate materials, whose crystalline structures are similar to those of minerals (karpenkoite, martyite, and vesignieite). The crystalline structure of the microstructured pyrovanadate Co3V2O7(OH)2·nH2O , prepared by the hydrothermal route, was solved. Its physicochemical and magnetic properties were studied and compared with those reported in the literature. The effect of the substitution of Zn2+ ions for high-spin Co2+ ions is analysed for a new microstructured solid solution (Co1-xZnx)3V2O7(OH)2·wH2O. Synthesis attempts of the nanostructured Co3V2O7(OH)2·nH2O material led to a new microstructured pyrovanadate with an approximate formula NH4Co2.5V2O7(OH)2·H2O. In addition, the microstructured orthovanadate BaCo3(VO4)2(OH)2 is obtained using Co3V2O7(OH)2·nH2O as a precursor and its properties are compared with those of recently obtained nanostructured samples. Such a comparison is also carried out for the new isostructural orthovanadate BaZn3(VO4)2(OH)2, prepared in micro- and nanocrystallised forms. The effect of Co/Zn cationic substitution is studied for a new microstructured solid solution Ba(Co1-xZnx)3(VO4)2(OH)2 and for nanostructured samples of similar compositions. This work opens up the possibility of studying other analogous solid solutions, such as Ba(Co1-xNix)3(VO4)2(OH)2
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Allison, Morgan Charles. "Chemistry of Layered AB3Si2Sn7O16 Stannides." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20154.

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The AB3Si2Sn7O16 phases (sg: P3 ̅m1) are a series of layered semiconductor oxides built from sheets of oxygen-linked A(SnO)6 octahedra and 3d transition metal rich tin-centred kagomé lattices separated by SiO4 tetrahedra. Oxide materials possessing novel geometrically frustrated architectures such as the triangular arrangement of ising spins in the kagomé lattice has garnered considerable recent interest from the materials science field due to the observation of quantum spin liquid states. These states are of interest to scientists, as they will help to connect the gap in understanding between the electronic ground states of matter and crystal structure. In a more practical sense, they are also interesting as they are among the most promising candidates for the building blocks of quantum computers. The novel architecture of SiO4-separated tin and transition metal rich layers in the AB3Si2Sn7O16 structure promises to allow for the synthesis of a significant number of chemically tuneable geometrically-frustrated oxides, however, only limited information on the crystal chemistry of this structure type exists which in turn hinders practical investigation of the links between structure and material properties. This investigation helps to bridge this gap by detailing the changes in chemical and magnetic behaviour as different sites in the tin-oxide framework are systematically substituted by different third, fourth and fifth row elements. Determination of the changes in the final structures and elemental composition will be determined using a combination of powder diffraction measurements and magnetic probes.
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Book chapters on the topic "Kagome layers"

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Paul, Geo, Amitava Choudhury, E. V. Sampathkumaran, and C. N. R. Rao. "Organically Templated Mixed-Valent Iron Sulfates Possessing Kagome and Other Types of Layered Networks." In World Scientific Series in 20th Century Chemistry, 492–95. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812835734_0064.

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Sharaff, Aakanksha, Ramya Allenki, and Rakhi Seth. "Deep Learning Based Sentiment Analysis for Phishing SMS Detection." In Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, 864–91. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6303-1.ch046.

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Sentiment analysis works on the principle of categorizing and identifying the text-based content and the process of classifying documents into one of the predefined classes commonly known as text classification. Hackers deploy a strategy by sending malicious content as an advertisement link and attack the user system to gain information. For protecting the system from this type of phishing attack, one needs to classify the spam data. This chapter is based on a discussion and comparison of various classification models that are used for phishing SMS detection through sentiment analysis. In this chapter, SMS data is collected from Kaggle, which is classified as ham or spam; while implementing the deep learning techniques like Convolutional Neural Network (CNN), CNN with 7 layers, and CNN with 11 layers, different results are generated. For evaluating these results, different machine learning techniques are used as a baseline algorithm like Naive Bayes, Decision Trees, Support Vector Machine (SVM), and Artificial Neural Network (ANN). After evaluation, CNN showed the highest accuracy of 99.47% as a classification model.
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Sharaff, Aakanksha, Ramya Allenki, and Rakhi Seth. "Deep Learning Based Sentiment Analysis for Phishing SMS Detection." In Advances in Data Mining and Database Management, 1–28. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8061-5.ch001.

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Sentiment analysis works on the principle of categorizing and identifying the text-based content and the process of classifying documents into one of the predefined classes commonly known as text classification. Hackers deploy a strategy by sending malicious content as an advertisement link and attack the user system to gain information. For protecting the system from this type of phishing attack, one needs to classify the spam data. This chapter is based on a discussion and comparison of various classification models that are used for phishing SMS detection through sentiment analysis. In this chapter, SMS data is collected from Kaggle, which is classified as ham or spam; while implementing the deep learning techniques like Convolutional Neural Network (CNN), CNN with 7 layers, and CNN with 11 layers, different results are generated. For evaluating these results, different machine learning techniques are used as a baseline algorithm like Naive Bayes, Decision Trees, Support Vector Machine (SVM), and Artificial Neural Network (ANN). After evaluation, CNN showed the highest accuracy of 99.47% as a classification model.
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Bhanumathi M, Ravi Rithika, Roshni R, and Sona Selvaraj. "Underwater Fish Species Classification Using Alexnet." In Advances in Parallel Computing Algorithms, Tools and Paradigms. IOS Press, 2022. http://dx.doi.org/10.3233/apc220056.

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There has been a constant need for the classification of fish species for a better understanding of the underwater ecological balance. Identifying the characteristics of different fish species plays a significant role in knowing the insights of marine ecology and is a great deal to many fisheries and industries. Manually classifying fish species is time-consuming and requires high sampling efforts. The behaviour of fishes can be well understood using an automated system that accurately classifies various fish species effectively. The classification of underwater images has difficulties like background noise interruption, image disruption, lower quality of images, occlusion. The proposed model lights up on the assortment of fish species using Alexnet. The knowledge of the previously trained model is given to the alexnet for improving the system. The performance of our improved model is demonstrated with real-world data from a research organization called Kaggle. CNN has used several layers trained for precise identification of the distinct features of a species and classify them accordingly. This paper ensures increased accuracy than the existing systems.
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Balaji, G. N., A. K. P. Kovendan, Kirti Nayak, R. Venkatesan, and D. Yuvaraj. "Multi-Cancer Detection Using Deep Learning Techniques." In Advances in Medical Technologies and Clinical Practice, 281–304. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3719-6.ch014.

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Cancer is one of the main causes of death for people worldwide. Breast, lung, colon, brain and lymphoma are some of the most common types of cancer. Successful treatment can significantly increase the chances of survival. Enhancing the probability of a successful cancer treatment requires initial identification and treatment. In this paper a model is proposed using denset121 pretrained model with modified dense net block and softmax function as output layer. There are two subgroups of the total number of diseases: task 1 and task 2. Task1 include breast, kidney, cervical, leukemia while task2 include lung, oral, lymphoma, brain.A person suffering from the disease of task 1 may also suffer from a disease belonging to task 2. This model is examined using a dataset with multiple cancers, which is publicly available on Kaggle. The suggested method performs with an accuracy of 99.31% for task 1 as well as 97.02% for task 2, respectively, when analyzed alongside the most recent techniques.
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Bhor, Samruddhi, Rutuja Ganage, Hrushikesh Pathade, Omkar Domb, and Shilpa Khedkar. "Automated Bird Species Identification using Audio Signal Processing and Neural Network." In Artificial Intelligence, Machine Learning and User Interface Design, 92–107. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815179606124010007.

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Many bird species are rare nowadays, and when they are found, they are difficult to classify. As an example, in various scenarios, birds include different sizes, forms, colors, and a person's viewpoint from different angles. Although domain specialists can classify birds manually, with increasing volumes of data, this becomes a tiresome and time-consuming procedure. Using our approach, we can reliably and quickly identify bird species. It is now feasible to track the number of birds as well as their activity using automated bird species recognition and machine learning algorithms. Convolutional neural networks (CNN) were chosen above standard classifiers such as SVM, Random Forest, and SMACPY. For this system, we used the “BirdCLEF 2021” dataset from Kaggle. The input dataset will be preprocessed, which will involve framing, silence removal, and reconstruction, which will be supplied as input to a convolutional neural network, followed by CNN modification, testing, and classification. To avoid overfitting, we add a dropout layer. Preprocessing includes importing the Librosa library. MFCC is a program that extracts distinct characteristics from audio files (Mel-Frequency-Cepstral-Coefficients). The MFCC summarizes the frequency distribution over the window size, allowing for sound frequency and temporal analysis. The result is then compared with respect to the pre-trained data, and output is shown, and birds are classified based on their classes.
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Conference papers on the topic "Kagome layers"

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Phani, A. Srikantha, and Norman A. Fleck. "Elastic Boundary Layers in Two-Dimensional Isotropic Lattices." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35234.

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The phenomenon of elastic boundary layers under quasistatic loading is investigated using the Floquet-Bloch formalism for two-dimensional, isotropic, periodic lattices. The elastic boundary layer is a region of localised elastic deformation, confined to the free-edge of a lattice. Boundary layer phenomena in three isotropic lattice topologies are investigated: the semi-regular Kagome lattice, the regular hexagonal lattice and the regular fully-triangulated lattice. The boundary layer depth is on the order of the strut length for the hexagonal and the fully-triangulated lattices. For the Kagome lattice, the depth of boundary layer scales inversely with the relative density. Thus, the boundary layer in a Kagome lattice of low relative density spans many cells.
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Menezes, Richardson Santiago Teles, Angelo Marcelino Cordeiro, Rafael Magalhães, and Helton Maia. "Classification of Paintings Authorship Using Convolutional Neural Network." In Congresso Brasileiro de Inteligência Computacional. SBIC, 2021. http://dx.doi.org/10.21528/cbic2021-116.

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In this paper, state-of-the-art architectures of Convolutional Neural Networks (CNNs) are explained and compared concerning authorship classification of famous paintings. The chosen CNNs architectures were VGG-16, VGG-19, Residual Neural Networks (ResNet), and Xception. The used dataset is available on the website Kaggle, under the title “Best Artworks of All Time”. Weighted classes for each artist with more than 200 paintings present in the dataset were created to represent and classify each artist’s style. The performed experiments resulted in an accuracy of up to 95% for the Xception architecture with an average F1-score of 0.87, 92% of accuracy with an average F1-score of 0.83 for the ResNet in its 50-layer configuration, while both of the VGG architectures did not present satisfactory results for the same amount of epochs, achieving at most 60% of accuracy.
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Rathod, Kanchan Yadav, and Tanuja Pattanshetti. "YouTube Music Recommendation System Based on Face Expression." In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-r8573m.

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Nowadays face recognition system is widely used in every field of computer vision applications such as Face lock-in smartphones, surveillance, smart attendance system, and driverless car technology. Because of this, the demand for face recognition systems is increasing day by day in the research field. The aim of this project is to develop a system that will recommend music based on facial expressions. The face-recognition system consists of object detection and identifying facial features from input images, and the face recognition system can be made more accurate with the use of convolutional neural networks. Layers of convolution neural network are used for the expression detection and are optimized with Adam to reduce overall loss and improve accuracy. YouTube song playlist recommendation is an application of a face recognition system based on a neural network. We use streamlit-webrtc to design the web frame for the song recommendation system. For face detection, we used the Kaggle-FER2013 dataset, and images in the dataset are classified into seven natural emotions of a person. The system captures the emotional state of a person in real-time and generates a playlist of youtube songs based on that emotion.
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Karthika, S., and M. Durgadevi. "Predicting and Classifying Diabetic Retinopathy (DR) Using 5-Class Label Based on Pre-Trained Deep Learning Models." In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-5z45nx.

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Diabetic Retinopathy (DR) is a condition in which damage to the eyes occurs as a result of diabetes mellitus. It is the most frequent diabetes-related eye condition. It can also cause full blindness and vision loss. With effective eye treatment, the majority of new occurrences of diabetic retinopathy can be reduced. Early detection helps to avoid total vision loss. However, detecting it early can be difficult because it may not present symptoms in the early stages. The wide selection of fundus imaging makes classification challenging, mainly in Proliferative_DR, which includes the formation of new vessels in retina and bleeding. Pre-trained deep learning model is used on the publicly accessible retinal fundus image dataset on kaggle in this paper (APTOS 2019 Blindness Detection). Pre-processing and augmentation procedures are used to increase the accuracy of the models that have been pre-trained. The training accuracy of 8-Layer Convolutional Neural Network (CNN) and MobileNetV2 obtained is 83.07% and 85.21%. Testing accuracy achieved 71.93% using CNN & MobileNetV2 is 83.42%. The most often employed measures, such as the F1 Score, precision, and recall is used to ignore class level of label disagreement, which aids in diagnosing all phases of diabetic retinopathy. The results using a confusion matrix is analyzed, which is useful for categorising different stages of diabetic retinopathy according to severity. It also takes into account the degree of mismatch between the actual and anticipated labels.
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