Search results for: lattice architectures

Authors: Roumaissa Derdour, Lebbal Mohamed Redha

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We present a study of the transmission of the all-optical logic gate using a structure connected with a triangular photonic crystal lattice that is improved. The proposed logic gate consists of a photonic crystal nano-resonator formed by changing the size of the air holes. In addition to the simplicity, the response time is very short, and the designed nano-resonator increases the bit rate of the logic gate. The two-dimensional finite difference time domain (2DFDTD) method is used to simulate the structure; the transmission obtained is about 98% with very negligible losses. The proposed photonic crystal AND logic gate is widely used in future integrated optical microelectronics.

Keywords: logic gates, photonic crystals, optical integrated circuits, resonant cavities

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Authors: Nikhil Kumar, Aparna Singh

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Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

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Authors: E. Kaygan, A. Gatto

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A numerical study of a design concept for actively controlling wing twist is described in this paper. The concept consists of morphing elements which were designed to provide a rigid and seamless skin while maintaining structural rigidity. The wing structure is first modeled in CATIA V5 then imported into ANSYS for structural analysis. Athena Vortex Lattice method (AVL) is used to estimate aerodynamic response as well as aerodynamic loads of morphing wings, afterwards a structural optimization performed via ANSYS Static. Overall, the results presented in this paper show that the concept provides efficient wing twist while preserving an aerodynamically smooth and compliant surface. Sufficient structural rigidity in bending is also obtained. This concept is suggested as a possible alternative for morphing skin applications. 

Keywords: aircraft, morphing, skin, twist

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Authors: Ersan Aktas, Eren Turanoğuz

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In this study, the quad-electrical rotor driven unmanned aerial vehicle system is designed and modeled using fundamental dynamic equations. After that, mechanical, electronical and control system of the air vehicle are designed and implemented. Brushless motor speeds are altered via electronic speed controllers in order to achieve desired controllability. The vehicle's fundamental Euler angles (i.e., roll angle, pitch angle, and yaw angle) are obtained via AHRS sensor. These angles are provided as an input to the control algorithm that run on soft the processor on the electronic card. The vehicle control algorithm is implemented in the electronic card. Controller is designed and improved for each Euler angles. Finally, flight tests have been performed to observe and improve the flight characteristics.

Keywords: quadrotor, UAS applications, control architectures, PID

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Authors: Namhyun An, Byungho Lee, Hwauk Lee, Youngmin Lee, Deuk Young Kim, Sejoon Lee

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In this study, the Cr-doped ZnO thin films have been deposited by reactive magnetron sputtering method with different Cr-contents (1.0at.%, 2.5at.% and 12.5at.%) and their ferromagnetic properties have been characterized. All films revealed clear ferromagnetism above room temperature. However, the spontaneous magnetization of the films was observed to depend on the Cr contents in the films. Namely, the magnitude of effective magnetic moment (per each Cr ion) was exponentially decreased with increasing the Cr contents. We attributed the decreased spontaneous magnetization to the degraded crystal magnetic anisotropy. In other words, we found out that the high concentration of magnetic ions causes the lattice distortion in the magnetic ion-doped thin film, and it consequently degrades ferromagnetic channeling in the solid-state material system.

Keywords: Cr-doped ZnO, ferromagnetic properties, magnetization, sputtering, thin film

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Authors: Susan E Orlovich

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Ongoing, effective teacher professional learning is acknowledged as a critical influence on teacher practice. However, it is unclear whether the elements of effective professional learning result in transformed teacher practice in the classroom. This research project is interested in 4C teacher professional learning. The professional learning practices to assist teachers in transforming their practice to integrate the 4C capabilities seldom feature in the academic literature. The 4Cs are a shorthand way of representing the concepts of communication, collaboration, creativity, and critical reflection and refer to the capabilities needed for deeper learning, personal growth, and effective participation in society. The New South Wales curriculum review (2020) acknowledges that identifying, teaching, and assessing the 4C capabilities are areas of challenge for teachers. However, it also recognises that it is essential for teachers to build the confidence and capacity to understand, teach and assess the capabilities necessary for learners to thrive in the 21st century. This qualitative research project explores the professional learning experiences of sixteen teachers in four different primaries (K-6) settings in Sydney, Australia, who are learning to integrate, teach and assess the 4Cs. The project draws on the Theory of Practice Architecture as a framework to analyse and interpret teachers' experiences in each site. The sixteen participants in the study are teachers from four primary settings and include early career, experienced, and teachers in leadership roles (including the principal). In addition, some of the participants are also teachers who are learning within a Community of Practice (CoP) as their school setting is engaged in a 4C professional learning, Community of Practice. Qualitative and arts-informed research methods are utilised to examine the cultural-discursive, social-political, and material-economic practice arrangements of the site, explore how these arrangements may have shaped the professional learning experiences of teachers, and in turn, influence the teaching practices of the 4Cs in the setting. The research is in the data analysis stage (October 2022), with preliminary findings pending. The research objective is to investigate the elements of the professional learning experiences undertaken by teachers to teach the 4Cs in the primary setting. The lens of practice architectures theory is used to identify the influence of the practice architectures on critical praxis in each site and examine how the practice arrangements enable or constrain the teaching of 4C capabilities. This research aims to offer deep insight into the practice arrangements which may enable or constrain teacher professional learning in the 4Cs. Such insight from this study may contribute to a better understanding of the practices that enable teachers to transform their practice to achieve the integration, teaching, and assessment of the 4C capabilities.

Keywords: 4Cs, communication, collaboration, creativity, critical reflection, teacher professional learning

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Authors: Gitanjali Pagare, Hansa Devi, S. P. Sanyal

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Full-potential linearized augmented plane wave (FLAPW) method has been employed within the generalized gradient approximation (GGA) and local spin density approximation (LSDA) as the exchange correlation potential to investigate elastic properties of LaX (X = Cd and Hg) in their B2-type (CsCl) crystal structure. The calculated ground state properties such as lattice constant (a0), bulk modulus (B) and pressure derivative of bulk modulus (B') agree well with the available experimental results. The second order elastic constants (C11, C12 and C44) have been calculated. The ductility or brittleness of these intermetallic compounds is predicted by using Pugh’s rule B/GH and Cauchy’s pressure (C12-C44). The calculated results indicate that LaHg is the ductile whereas LaCd is brittle in nature.

Keywords: ductility/brittleness, elastic constants, equation of states, FP-LAPW method, intermetallics

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Authors: I. Benkaddour, Y. Benkaddour, A. Benk Addour

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The structural, elastic, Thermal, electronic, and magnetic properties of intermetallic RMn₂Ge₂ (R= Ca, Y, Nd) are investigated by density functional theory (DFT), using the full potential –linearised augmented plane wave method (FP-LAPW). In this approach, the local-density approximation (LDA) is used for the exchange-correlation (XC) potential. The equilibrium lattice constant and magnetic moment agree well with the experiment. The density of states shows that these phases are conductors, with contribution predominantly from the R and Mn d states. We have determined the elastic constants C₁₁, C₁₂, C₁₃, C₄₄, C₃₃, andC₆₆ at ambient conditions in, which have not been established neither experimentally nor theoretically. Thermal properties, including the relative expansion coefficients and the heat capacity, have been estimated using a quasi-harmonic Debye model.

Keywords: RMn₂Ge₂, intermetallic, first-principles, density of states, mechanical properties

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Authors: M. A. Ghebouli, A. Bouhemadou, H. Choutri, L. Louaila

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Some physical properties of the cubic perovskites CsXF3 (X = Sr, Ca, and Hg) have been investigated using pseudopotential plane–wave (PP-PW) method based on the density functional theory (DFT). The calculated lattice constants within GGA (PBE) and LDA (CA-PZ) agree reasonably with the available experiment data. The elastic constants and their pressure derivatives are predicted using the static finite strain technique. We derived the bulk and shear moduli, Young’s modulus, Poisson’s ratio and Lamé’s constants for ideal polycrystalline aggregates. The analysis of B/G ratio indicates that CsXF3 (X = Ca, Sr, and Hg) are ductile materials. The thermal effect on the volume, bulk modulus, heat capacities CV, CP, and Debye temperature was predicted.

Keywords: perovskite, PP-PW method, elastic constants, electronic band structure

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Authors: H. Nematifar, D. Sanavi Khoshnoud, S. Feyz

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Bi0.82La0.2Fe1-xCrxO3 (BLFCxO, x = 0.0, 0.02, 0.05 and 0.08) nanoparticles were successfully synthesized by a sol-gel method. The X-ray diffraction (XRD) patterns indicate that the lattice parameters decrease for x ≤ 0.05, firstly, and then they increase for x > 0.05. A transformation from rhombohedral structure to orthorhombic structure occurs at x = 0.08. The transmission electron microscopy (TEM) analysis shows that the average nanoparticle size is about 60-70 nm. The remnant magnetisation (Mr) increases gradually with x to 0.02, then decreases with further increasing x up to 0.05, and finally enchases abruptly in x = 0.08. The coercivity (HC) increases gradually with x to 0.05, and then significantly reduced with increasing Cr substitution. The magnetic ordering temperature (TN) decreases with Cr doping concentration. The M-H curves of all samples exhibit a wasp-waist hysteresis loop in low magnetic region. This property can play an important role for the applications of some multiferroic nano-device.

Keywords: BiFeO3, sol-gel preparation, nanoparticles, magnetic materials, thermal analysis

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Valentina Adduci

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The developing research aims to define in general the criteria of environmental sustainability of rural buildings in Puglia and particularly in the manor farm. The main part of the study analyzes the relationship / dependence between the rural building and the landscape which, after many stratifications, results clearly identified and sometimes also characterized in a positive way. The location of the manor farm, in fact, is often conditioned by the infrastructural network and by the structure of the agricultural landscape. The manor farm, without the constraints due to the urban pattern’s density, was developed in accordance with a logical settlement that gives priority to the environmental aspects. These vernacular architectures are the most valuable example of how our ancestors have planned their dwellings according to nature. The 237 farms, analysis’ object, have been reported in cartography through the GIS system; a symbol has been assigned to each of them to identify the architectural typology and a different color for the historical period of construction. A datasheet template has been drawn up, and it has made possible a deeper understanding of each manor farm. This method provides a faster comparison of the most recurring characters in all the considered buildings, except for those farms which benefited from special geographical conditions, such as proximity to the road network or waterways. Below there are some of the most frequently constants derived from the statistical study of the examined buildings: southeast orientation of the main facade; placement of the sheep pen on the ground tilted and exposed to the south side; larger windowed surface on the south elevation; smaller windowed surface on the north elevation; presence of shielding vegetation near the more exposed elevations to the solar radiation; food storage’s rooms located on the ground floor or in the basement; animal shelter located in north side of the farm; presence of tanks and wells, sometimes combined with a very accurate channeling storm water system; thick layers of masonry walls, inside of which were often obtained hollow spaces to house stairwells or depots for the food storage; exclusive use of local building materials. The research aims to trace the ancient use of bioclimatic constructive techniques in the Apulian rural architecture and to define those that derive from an empirical knowledge and those that respond to an already encoded design. These constructive expedients are especially useful to obtain an effective passive cooling, to promote the natural ventilation and to built ingenious systems for the recovery and the preservation of rainwater and are still found in some of the manor farms analyzed, most of them are, today, in a serious state of neglect.

Keywords: bioclimatic devices, farmstead, rural landscape, sustainability

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Authors: Jerzy F. Janik, Mariusz Drygas, Miroslaw M. Bucko

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A simple precursor system has been recently developed in our laboratory for the conversion of affordable microcrystalline gallium antimonide GaSb to a range of nanocrystalline powders of gallium nitride GaN – a wide bandgap semiconductor indispensable in modern optoelectronics. The process relies on high temperature nitridation reactions of GaSb with ammonia. Topochemical relationships set up by the cubic lattice of GaSb result in some metastable cubic GaN formed in addition to the stable hexagonal GaN. A prior application of high energy ball milling to the initially microcrystalline GaSb precursor is shown to alter the nitridation output.

Keywords: nanocrystalline, gallium nitride, GaN, gallium antimonide, GaSb, nitridation, ball milling

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Authors: Malgorzata Schwab, Ashis Kumer Biswas

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In this concept paper, we explore the topic of Reversibility in Neural Networks leveraged for Network Integrity Verification and crafted the term ''Trusted Neural Network'' (TNN), paired with the API abstraction around it, to embrace the idea formally. This newly proposed high-level generalizable TNN model builds upon the Invertible Neural Network architecture, trained simultaneously in both forward and reverse directions. This allows for the original system inputs to be compared with the ones reconstructed from the outputs in the reversed flow to assess the integrity of the end-to-end inference flow. The outcome of that assessment is captured as an Integrity Score. Concrete implementation reflecting the needs of specific problem domains can be derived from this general approach and is demonstrated in the experiments. The model aspires to become a useful practice in drafting high-level systems architectures which incorporate AI capabilities.

Keywords: trusted, neural, invertible, API

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Ammar Z. Alshemary, Yi-Fan Goh, Rafaqat Hussain

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Magnesium (Mg2+), strontium (Sr2+) and sulphate ions (SO42-) were successfully substituted into hydroxyapatite (Ca10-x-y MgxSry(PO4)6-z(SO4)zOH2-z) structure through ion exchange process at cationic and anionic sites. Mg2+and Sr2+ ions concentrations were varied between (0.00-0.10), keeping concentration of SO42- ions at z=0.05. [Mg (NO3)2], [Sr (NO3)2] and (Na2SO4) were used as Mg2+, Sr2+, and SO42- sources respectively. The synthesized white precipitate were subjected to heat treatment at 500ºC and finally characterized by X-ray diffraction (XRD) and Fourier Transform infra-red spectroscopy (FTIR). The results showed that the substitution of Mg2+, Sr2+ and SO42- ions into the HA lattice resulted in an increase in the broadness and reduction of XRD peaks. This confirmed that the crystallinity was reduced due to the substitution of ions. Similarly, FTIR result showed the effect of substitution on phosphate bands as well as exchange of hydroxyl group by SO42- ions to balance the charges on HA surface.

Keywords: hydroxyapatite, substitution, characterization, XRD, FTIR

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Taro Komori, Toshiki Gushi, Akihito Anzai, Taku Hirose, Kaoru Toko, Shinji Isogami, Takashi Suemasu

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Ferrimagnetic antiperovskite Mn₄₋ₓNiₓN thin film exhibits both small saturation magnetization and rather large perpendicular magnetic anisotropy (PMA) when x is small. Both of them are suitable features for application to current induced domain wall motion devices using spin transfer torque (STT). In this work, we successfully grew antiperovskite 30-nm-thick Mn₄₋ₓNiₓN epitaxial thin films on MgO(001) and STO(001) substrates by MBE in order to investigate their crystalline qualities and magnetic and magneto-transport properties. Crystalline qualities were investigated by X-ray diffraction (XRD). The magnetic properties were measured by vibrating sample magnetometer (VSM) at room temperature. Anomalous Hall effect was measured by physical properties measurement system. Both measurements were performed at room temperature. Temperature dependence of magnetization was measured by VSM-Superconducting quantum interference device. XRD patterns indicate epitaxial growth of Mn₄₋ₓNiₓN thin films on both substrates, ones on STO(001) especially have higher c-axis orientation thanks to greater lattice matching. According to VSM measurement, PMA was observed in Mn₄₋ₓNiₓN on MgO(001) when x ≤ 0.25 and on STO(001) when x ≤ 0.5, and MS decreased drastically with x. For example, MS of Mn₃.₉Ni₀.₁N on STO(001) was 47.4 emu/cm³. From the anomalous Hall resistivity (ρAH) of Mn₄₋ₓNiₓN thin films on STO(001) with the magnetic field perpendicular to the plane, we found out Mr/MS was about 1 when x ≤ 0.25, which suggests large magnetic domains in samples and suitable features for DW motion device application. In contrast, such square curves were not observed for Mn₄₋ₓNiₓN on MgO(001), which we attribute to difference in lattice matching. Furthermore, it’s notable that although the sign of ρAH was negative when x = 0 and 0.1, it reversed positive when x = 0.25 and 0.5. The similar reversal occurred for temperature dependence of magnetization. The magnetization of Mn₄₋ₓNiₓN on STO(001) increases with decreasing temperature when x = 0 and 0.1, while it decreases when x = 0.25. We considered that these reversals were caused by magnetic compensation which occurred in Mn₄₋ₓNiₓN between x = 0.1 and 0.25. We expect Mn atoms of Mn₄₋ₓNiₓN crystal have larger magnetic moments than Ni atoms do. The temperature dependence stated above can be explained if we assume that Ni atoms preferentially occupy the corner sites, and their magnetic moments have different temperature dependence from Mn atoms at the face-centered sites. At the compensation point, Mn₄₋ₓNiₓN is expected to show very efficient STT and ultrafast DW motion with small current density. What’s more, if angular momentum compensation is found, the efficiency will be best optimized. In order to prove the magnetic compensation, X-ray magnetic circular dichroism will be performed. Energy dispersive X-ray spectrometry is a candidate method to analyze the accurate composition ratio of samples.

Keywords: compensation, ferrimagnetism, Mn₄N, PMA

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: Vinita Choudhary

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Solidly Acoustic Resonators (SMR) based on ZnO piezoelectric material operating at a frequency of 3.96 GHz and 6.49% coupling factor are used to characterize liquids with different viscosities. This behavior of the sensor is analyzed using Finite Element Modeling. Device architectures encapsulate bulk acoustic wave resonators with MO/SiO₂ Bragg mirror reflector and the silicon substrate. The proposed SMR is based on the mass loading effect response of the sensor to the change in the resonant frequency of the resonator that is caused by the increased density due to the absorption of liquids (water, acetone, olive oil) used in theoretical calculation. The sensitivity of sensors ranges from 0.238 MHz/mPa.s to 83.33 MHz/mPa.s, supported by the Kanazawa model. Obtained results are also compared with previous works on BAW viscosity sensors.

Keywords: solidly mounted resonator, bragg mirror, kanazawa model, finite element model

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: B. Bahloul

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This study investigates the structural, electronic, and optical properties of LiH and NaH compounds, as well as their ternary mixed crystals LiₓNa1-ₓH, adopting a face-centered cubic structure with space group Fm-3m (number 225). The structural and electronic characteristics are examined using density functional theory (DFT), while empirical methods, specifically the modified Moss relation, are employed for analyzing optical properties. The exchange-correlation potential is determined through the generalized gradient approximation (PBEsol-GGA) within the density functional theory (DFT) framework, utilizing the projected augmented wave pseudopotentials (PAW) approach. The Quantum Espresso code is employed for conducting these calculations. The calculated lattice parameters at equilibrium volume and the bulk modulus for x=0 and x=1 exhibit good agreement with existing literature data. Additionally, the LiₓNa1-ₓH alloys are identified as having a direct band gap.

Keywords: DFT, structural, electronic, optical properties

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Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

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The growing popularity of systems based on unmanned aerial vehicles (UAVs) is highlighting their vulnerability, particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS, which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper, we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signals. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: visual odometry, autonomous uav, position measurement, autonomous outdoor flight

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Authors: D. Majumdar, M. Baskey, S. K. Saha

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Graphene has already been identified as a promising material for future carbon based electronics. To develop graphene technology, the fabrication of a high quality P-N junction is a great challenge. In the present work, we have described a simple and general technique to grow single crystalline polyaniline (PANI) films on graphene sheets using in situ polymerization via the oxidation-reduction of aniline monomer and graphene oxide, respectively, to fabricate a high quality P-N junction, which shows diode-like behavior with a remarkably low turn-on voltage (60 mV) and high rectification ratio (1880:1) up to a voltage of 0.2 Volt. The origin of these superior electronic properties is the preferential growth of a highly crystalline PANI film as well as lattice matching between the d-values [~2.48 Å] of graphene and {120} planes of PANI.

Keywords: epitaxial growth, PANI, reduced graphene oxide, rectification ratio

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Authors: Salima Tabti, Amel Djedouani., Djouhra Aggoun, Ismail Warad

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The reaction of copper (II) with 4-hydroxy-3-[(2E)-3-(1H-indol-3-yl)prop-2-enoyl]-6-methyl-2H-pyran-2-one (HL) lead to a new complexe: Cu(L)₂(DMF)₂. The crystal structure of the Cu(L)₂(DMF)₂ complex have been determined by X-ray diffraction methods. The Cu(II) lying on an inversion centre is coordinated to six oxygen atoms forming an octahedral elongated. Additionally, the electrochemical behavior of the metal complexe was investigated by cyclic voltammetry at a glassy carbon electrode (GC) in CH₃CN solution, showing the quasi-reversible redox process ascribed to the reduction of the MII/MI couple. The X-ray single crystal structure data of the complex was matched excellently with the optimized monomer structure of the desired compound; Hirschfeld surface analysis supported the packed crystal lattice 3D network intermolecular forces.

Keywords: chalcones, cyclic voltametry, X-ray, Hirschfeld surface

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Authors: S. Vasundra, D. Venkatesh

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Wireless networks have gone through an extraordinary growth in the past few years, and will keep on playing a crucial role in future data communication. The present wireless networks aim to make communication possible anywhere and anytime. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Since an ad hoc network may consist of a large number of mobile hosts, this imposes a significant challenge on the design of an effective and efficient routing protocol that can work well in an environment with frequent topological changes. This paper proposes improved ant colony optimization (IACO) technique. It also maintains load balancing in wireless networks. The simulation results show that the proposed IACO performs better than existing routing techniques.

Keywords: wireless networks, ant colony optimization, load balancing, architecture

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Authors: T. Teruzzi, S. Antonietti, C. Mosca, C. Paglia

Abstract:

This paper discusses the causes of the structural failure in a tower crane. The structural collapse occurred at the upper joints of the extension element used to increase the height of the crane. The extension element consists of a steel lattice structure made with angular profiles and plates joined to the tower element by arc welding. Macroscopic inspection of the sections showed that the break was always observed on the angular profiles at the weld bead edge. The case study shows how, using mechanical characterization, chemical analysis of the steel and macroscopic and microscopic metallographic examinations, it was possible to obtain significant evidence that identified the mechanism causing the breakage. The analyses identified the causes of the structural failure as the use of materials that were not suitable for welding and poor performance in the welding joints.

Keywords: failure, metals, weld, microstructure

Procedia PDF Downloads 91

Authors: Nikhil V. Nayak, P. P. Revankar, M. B. Gorawar

Abstract:

Wind energy has been shown to be one of the most viable sources of renewable energy. With current technology, the low cost of wind energy is competitive with more conventional sources of energy such as coal. Most airfoil blades available for commercial grade wind turbines incorporate a straight span-wise profile and airfoil shaped cross sections. This paper is aimed at studying and designing a wind-solar hybrid system for light load application. The tools like qblade and solidworks are used to model and analyze the wind turbine system, the material used for the blade and hub is balsa wood and the tower a lattice type. The expected power output is 100 W for an average wind speed of 4.5 m/s.

Keywords: renewable energy, hybrid, airfoil blades, wind speeds, make-in-india, camber, QBlade, solidworks, balsa wood

Procedia PDF Downloads 282

Authors: Diego Aguirre, Olac Fuentes

Abstract:

In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

Procedia PDF Downloads 106