Journal articles: 'Multi-Level Fast Multipole'

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Amini, S., and A. T. J. Profit. "Multi-level fast multipole solution of the scattering problem." Engineering Analysis with Boundary Elements 27, no. 5 (May 2003): 547–64. http://dx.doi.org/10.1016/s0955-7997(02)00161-3.

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Lee, Hyunsoo, Jae-Won Rim, Il-Suek Koh, and Seung-Mo Seo. "Computational Complexity of BiCGstab(l) in Multi-Level Fast Multipole Method(MLFMM) and Efficient Choice of l." Journal of Korean Institute of Electromagnetic Engineering and Science 29, no. 3 (March 2018): 167–70. http://dx.doi.org/10.5515/kjkiees.2018.29.3.167.

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Pan, X. M., and X. Q. Sheng. "A Highly Efficient Parallel Approach of Multi-level Fast Multipole Algorithm." Journal of Electromagnetic Waves and Applications 20, no. 8 (January 2006): 1081–92. http://dx.doi.org/10.1163/156939306776930321.

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Yun, Dal-jae, Haewon Jung, Hoon Kang, Woo-Yong Yang, and Dong-Wook Seo. "Acceleration of the Multi-Level Fast Multipole Algorithm Using K-Means Clustering." Electronics 9, no. 11 (November 16, 2020): 1926. http://dx.doi.org/10.3390/electronics9111926.

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The multilevel fast multipole algorithm (MLFMA) using K-means clustering to accelerate electromagnetic scattering analysis for large complex targets is presented. By replacing the regular cube grouping with the K-means clustering, the addition theorem is more accurately approximated. The convergence rate of an iterative solver is thus improved significantly. However, irregular centroid locations as a result of the K-means clustering increase the amount of explicit transfer function calculations, compared with the regular cubes. In the MLFMA, a multilevel hierarchical structure is applied to the finite multipole method (FMM) to reduce transfer function calculations. Therefore, the MLFMA is suitable for applying K-means clustering. Simulation results with both canonical and realistic targets show an improvement in the computation time of the proposed algorithm.

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Nam, Jeong-Hun, Jeong-Un You, and Il-Suek Koh. "Large Complex Impedance and Dielectric Inhomogeneous Structure Scattering Analysis Based on Multi-Level Fast Multipole Method and Iterative Physical Optics." Journal of Korean Institute of Electromagnetic Engineering and Science 32, no. 10 (October 2021): 916–24. http://dx.doi.org/10.5515/kjkiees.2021.32.10.916.

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Burgschweiger, Ralf, Martin Ochmann, Ingo Schäfer, and Bodo Nolte. "Optimization and limitations of a preconditioned multi-level fast multipole algorithm for acoustical calculations." Journal of the Acoustical Society of America 131, no. 4 (April 2012): 3512. http://dx.doi.org/10.1121/1.4709276.

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Chaillat, Stéphanie, Marc Bonnet, and Jean-François Semblat. "A multi-level fast multipole BEM for 3-D elastodynamics in the frequency domain." Computer Methods in Applied Mechanics and Engineering 197, no. 49-50 (September 2008): 4233–49. http://dx.doi.org/10.1016/j.cma.2008.04.024.

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Grasso, Eva, Stéphanie Chaillat, Marc Bonnet, and Jean-François Semblat. "Application of the multi-level time-harmonic fast multipole BEM to 3-D visco-elastodynamics." Engineering Analysis with Boundary Elements 36, no. 5 (May 2012): 744–58. http://dx.doi.org/10.1016/j.enganabound.2011.11.015.

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Fu, Liwei, Max Daiber-Huppert, Karsten Frenner, and Wolfgang Osten. "Simulation of realistic speckle fields by using surface integral equation and multi-level fast multipole method." Optics and Lasers in Engineering 162 (March 2023): 107438. http://dx.doi.org/10.1016/j.optlaseng.2022.107438.

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Yoo, Jeong-Un, and Il-Suek Koh. "Comparison of Linear Iteration Schemes to Improve the Convergence of Iterative Physical Optics for an Impedance Scatterer." Journal of Electromagnetic Engineering and Science 23, no. 1 (January 31, 2023): 78–80. http://dx.doi.org/10.26866/jees.2023.1.l.12.

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The conventional iterative physical optics (IPO) method updates the surface current based on the Jacobi iteration scheme, which typically diverges for large objects. To control the convergence property of the IPO method, other iteration schemes, such as Gauss–Seidel and successive over-relaxation, can be used. In this study, we compare the convergence properties of three iteration schemes for scatterings by five scatterers comprising electrically perfect or imperfect conductors modeled with an impedance material. The accuracy of the IPO method is compared with that of the multi-level fast multipole method.

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Wu, Haijun, Yijun Liu, Weikang Jiang, and Wenbo Lu. "A Fast Multipole Boundary Element Method for Three-Dimensional Half-Space Acoustic Wave Problems Over an Impedance Plane." International Journal of Computational Methods 12, no. 01 (January 23, 2015): 1350090. http://dx.doi.org/10.1142/s0219876213500904.

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A high-frequency fast multipole boundary element method (FMBEM) based on the Burton–Miller formulation is proposed for three-dimensional acoustic wave problems over an infinite plane with impedance boundary conditions. The Green's function for the sound propagation over an impedance plane is employed explicitly in the boundary integral equation (BIE). To deal with the integral appearing in the half-space Green's function, the downward pass in the FMBEM is divided into two parts to compute contributions from the real domain to the real and image domains, respectively. A piecewise analytical method is proposed to compute the moment-to-local (M2L) translator from the real domain to the image domain accurately. An algorithm based on the multi-level tree structure is designed to compute the M2L translators efficiently. Correspondingly, the direct coefficient can also be computed efficiently by taking advantage of the algorithm of the efficient M2L. A flexible generalized minimal residual (fGMRES) is applied to accelerating the solution when the convergence is very slow. Numerical examples are presented to demonstrate the accuracy and efficiency of the developed FMBEM. Good solutions and high acceleration ratios compared with the conventional boundary element method clearly show the potential of the FMBEM for large-scale 3D acoustic wave problems over an infinite impedance plane which are of practical significance.

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Pons, Alejandro, Alvaro Somolinos, Ivan González, and Felipe Cátedra. "Fast Computation by MLFMM-FFT with NURBS in Large Volumetric Dielectric Structures." Electronics 10, no. 13 (June 28, 2021): 1560. http://dx.doi.org/10.3390/electronics10131560.

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A refinement for the computation of the rigorous part of the multi-level fast multipole method (MLFMM) of analyzing volumetric objects is presented. A scheme based on the fast Fourier technique (FFT) is proposed with the objective of reducing the computational resources required to accurately analyze large homogeneous and non-homogeneous dielectric volumes. In order to reduce the memory requirements, the storage of the near-field terms of the method of moments (MoM) matrix is performed only for the positions corresponding to a parallelepiped with the size of the level 1 block of the MLFMM, computed with the vacuum permittivity, taking advantage of the Toeplitz symmetry present in regular hexahedral meshes. The FFT avoids applying the near-field MoM matrix in the iterative solution process. The application of this approach results in huge improvements in terms of memory usage, but also a speeds up the iterative solution process because the use of three-dimensional (3D) FFTs is very efficient for computing convolutions when the number of unknowns of the problems becomes very large as happens in volumetric problems. We also propose a new approach for the numerical treatment of the transition of the dielectric permittivity between different dielectrics or between a dielectric and a free space. To validate the computation technique, the radar cross section (RCS) of several dielectric bodies is computed using the classical MLFMM approach and it is compared with the presented FFT-based-MLFMM solution. The results demonstrate that the efficient memory and computation time usage of the proposed approach.

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Pang, Mingjie, Han Wang, and Hai Lin. "Iterative MLFMA-MADBT Technique for Analysis of Antenna Mounted on Large Platforms." Applied Sciences 11, no. 1 (December 25, 2020): 148. http://dx.doi.org/10.3390/app11010148.

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A hybrid technique combining the multi-level fast multipole algorithm (MLFMA) and the modified adaptive division beam tracing (MADBT) is presented to analyze the radiation patterns of the antennas mounted on large-scale complex platforms. In this technique, the MLFMA is used to characterize the antenna and the transition region that cannot be analyzed accurately by high-frequency asymptotic methods. The MADBT method is used to analyze the contribution of the platforms to the entire radiation pattern by tracing all beams effectively. By applying the beam-based MADBT method instead of the conventional current-based physical optics (PO) method to the platforms, the multi-bounce effects inside the platforms are considered, which enhances the accuracy of the radiation patterns, especially for the complex platforms with corner reflector. An iteration method is proposed to model the interaction between the antennas and the platforms strictly. The proposed iterative MLFMA-MADBT method is mesh-independent and can avoid the matrix-vector production (MVP) of the iterative MLFMA-PO method in each iteration. These characters significantly reduce the memory and time consumption in computation while keeping high accuracy. Numerical results are presented to demonstrate the accuracy and efficiency of the proposed hybrid technique.

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Wang, Bin, and Qiang Wang. "Numerical Optimization of Electromagnetic Performance and Aerodynamic Performance for Subsonic S-Duct Intake." Aerospace 9, no. 11 (October 28, 2022): 665. http://dx.doi.org/10.3390/aerospace9110665.

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In order to improve the performance of subsonic unmanned aerial vehicle (UAV), a knapsack S-duct intake has been designed. The influences of an S-bend diffuser on aerodynamic performance and electromagnetic performance were analyzed firstly. The viscous flow field has been simulated by solving Favre averaged Navier–Stokes equations using a shear stress transport (SST) k-ω turbulence model. The surface current has been simulated by solving Maxwell equations using a multi-level fast multipole method (MLFMM). The multi-objective optimization of the S-duct intake was studied by using the diffuser as the optimized object. The parametric expression of the diffuser model was realized using the fourth order function geometric representation technique. The efficient model based on the Kriging model and non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) were used to accelerate the optimization progress. By analyzing the results of an optimal intake chosen from the Pareto front, the total pressure distortion (TPD) index DC60 has decreased by 0.24 at the designed Mach number of 0.9, and the average Radar Cross Section (RCS) has decreased by 2db at the frequency of 3GHz. The optimized S-duct intake could have both excellent aerodynamic performance and electromagnetic performance at various complex conditions.

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Wolf, William R., João Luiz F. Azevedo, and Sanjiva K. Lele. "Convective effects and the role of quadrupole sources for aerofoil aeroacoustics." Journal of Fluid Mechanics 708 (August 10, 2012): 502–38. http://dx.doi.org/10.1017/jfm.2012.327.

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AbstractThe present investigation of aerofoil self-noise generation and propagation concerns the effects of mean flow and quadrupole sources on the broadband noise that arises from the interaction of turbulent boundary layers with the aerofoil trailing edge and the tonal noise that arises from vortex shedding generated by laminar boundary layers and trailing-edge bluntness. Compressible large-eddy simulations (LES) are conducted for a NACA0012 aerofoil with rounded trailing edge for four flow configurations with different angles of incidence, boundary layer tripping configurations and free-stream Mach numbers. The Reynolds number based on the aerofoil chord is fixed at ${\mathit{Re}}_{c} = 408\hspace{0.167em} 000$. The acoustic predictions are performed by the Ffowcs Williams & Hawkings (FWH) acoustic analogy formulation and incorporate convective effects. Surface and volume integrations of dipole and quadrupole source terms appearing in the FWH equation are performed using a three-dimensional wideband multi-level adaptive fast multipole method (FMM) in order to accelerate the calculations of aeroacoustic integrals. In order to validate the numerical solutions, flow simulation and acoustic prediction results are compared to experimental data available in the literature and good agreement is observed in terms of both aerodynamic and aeroacoustic results. For low-Mach-number flows, quadrupole sources can be neglected in the FWH equation and mean flow effects appear only for high frequencies. However, for higher speeds, convection effects are relevant for all frequencies and quadrupole sources have a more pronounced effect for medium and high frequencies. The convective effects are most readily observed in the upstream direction.

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Xi, Rui, Hu Jun, and Nie Zaiping. "Solving Scattering from Multiple Conducting Objects by Hybrid Multi-Level Fast Multi-Pole Algorithm with Generalized Forward-and-Backward Method." Electromagnetics 28, no. 8 (November 18, 2008): 572–81. http://dx.doi.org/10.1080/02726340802428747.

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Su, Chang, Xiaohong Guan, Youtian Du, Qian Wang, and Fei Wang. "A fast multi-level algorithm for community detection in directed online social networks." Journal of Information Science 44, no. 3 (March 14, 2017): 392–407. http://dx.doi.org/10.1177/0165551517698305.

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The discovery of underlying community structures plays a significant role in online social network (OSN) analysis. Many previous methods suffer from inaccuracy or incompleteness in community descriptions because of the multiple factors affecting OSNs and the high computational complexity caused by the large scale of these networks. We present a new community detection approach that focuses on two aspects. First, it relies on a combination of user interests and cohesiveness in describing community structures. Second, it introduces a multi-level community discovery algorithm for large-scale OSN datasets. The algorithm consists of three steps: (1) network coarsening based on the combination of two categories of properties, (2) stochastic inference to find an initial community assignment over the coarsest network and (3) projection and refinement of this assignment to obtain the final community detection result by solving a semi-supervised learning problem. The combination of user interests and cohesiveness leads to a complete and well-interpreted description of the communities embedded in OSNs, and the multi-level algorithm speeds up the computation process and improves the likelihood of finding the global optimal solution by reducing the parameter space. Experiments conducted on both synthetic and real datasets demonstrate the effectiveness and efficiency of our method.

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IWAI, T., C. W. HONG, and P. GREIL. "FAST PARTICLE PAIR DETECTION ALGORITHMS FOR PARTICLE SIMULATIONS." International Journal of Modern Physics C 10, no. 05 (July 1999): 823–37. http://dx.doi.org/10.1142/s0129183199000644.

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New algorithms with O(N) complexity have been developed for fast particle-pair detections in particle simulations like the discrete element method (DEM) and molecular dynamic (MD). They exhibit robustness against broad particle size distributions when compared with conventional boxing methods. Almost similar calculation speeds are achieved at particle size distributions from is mono-size to 1:10 while the linked-cell method results in calculations more than 20 times. The basic algorithm, level-boxing, uses the variable search range according to each particle. The advanced method, multi-level boxing, employs multiple cell layers to reduce the particle size discrepancy. Another method, indexed-level boxing, reduces the size of cell arrays by introducing the hash procedure to access the cell array, and is effective for sparse particle systems with a large number of particles.

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Rosas-Cervantes, Vinicio Alejandro, Quoc-Dong Hoang, Soon-Geul Lee, and Jae-Hwan Choi. "Multi-Robot 2.5D Localization and Mapping Using a Monte Carlo Algorithm on a Multi-Level Surface." Sensors 21, no. 13 (July 4, 2021): 4588. http://dx.doi.org/10.3390/s21134588.

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Most indoor environments have wheelchair adaptations or ramps, providing an opportunity for mobile robots to navigate sloped areas avoiding steps. These indoor environments with integrated sloped areas are divided into different levels. The multi-level areas represent a challenge for mobile robot navigation due to the sudden change in reference sensors as visual, inertial, or laser scan instruments. Using multiple cooperative robots is advantageous for mapping and localization since they permit rapid exploration of the environment and provide higher redundancy than using a single robot. This study proposes a multi-robot localization using two robots (leader and follower) to perform a fast and robust environment exploration on multi-level areas. The leader robot is equipped with a 3D LIDAR for 2.5D mapping and a Kinect camera for RGB image acquisition. Using 3D LIDAR, the leader robot obtains information for particle localization, with particles sampled from the walls and obstacle tangents. We employ a convolutional neural network on the RGB images for multi-level area detection. Once the leader robot detects a multi-level area, it generates a path and sends a notification to the follower robot to go into the detected location. The follower robot utilizes a 2D LIDAR to explore the boundaries of the even areas and generate a 2D map using an extension of the iterative closest point. The 2D map is utilized as a re-localization resource in case of failure of the leader robot.

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RAJAEI, RAMIN, MAHMOUD TABANDEH, and MAHDI FAZELI. "SOFT ERROR RATE ESTIMATION FOR COMBINATIONAL LOGIC IN PRESENCE OF SINGLE EVENT MULTIPLE TRANSIENTS." Journal of Circuits, Systems and Computers 23, no. 06 (May 14, 2014): 1450091. http://dx.doi.org/10.1142/s0218126614500911.

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Fast and accurate estimation of soft error rate in VLSI circuits is an essential step in a soft error tolerant ASIC design. In order to have a cost effective protection against radiation effects in combinational logics, an accurate and fast method for identification of most susceptive gates and paths is needed. In this paper, an efficient, fast and accurate method for soft error propagation probability (SEPP) estimation is presented and its performance is evaluated. This method takes into account all three masking factors in multi cycles. It also considers multiple event transients as a new challenge in soft error tolerant VLSI circuit design. Compared with Monte Carlo (MC) simulation-based fault injection method, our SEPP estimation method has a high level of accuracy (with less than 2% difference) while offering 1000× speedup as compared with MC-based simulation.

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Cui, Mao Qiao, Hai Yan Huang, Fu Lai Wang, and Yong Qiu. "Multi-Objective Optimization Design of Steel Frames Based on Multiple Attribute Decision-Making Method." Applied Mechanics and Materials 368-370 (August 2013): 830–37. http://dx.doi.org/10.4028/www.scientific.net/amm.368-370.830.

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This paper describes in detail a multi-objective optimization strategy and decision-making method in the process of steel frame optimization design. A step-by-step analysis process integrating optimization algorithm and model analysis is proposed to solve the present problem. A multi-objective algorithm method using fast Non-dominated Sorting Genetic Algorithm is employed to obtain the Pareto-optimal solution set through an evolutionary optimization process. A high-level multiple attribute decision-making method based on intuitionistic fuzzy set theory is adopted to rank these solutions from the best to worst, and to determine the best solution. An example is used to demonstrate the proposed optimization model and decision-making method.

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Lee, Dong-Gyu. "Fast Drivable Areas Estimation with Multi-Task Learning for Real-Time Autonomous Driving Assistant." Applied Sciences 11, no. 22 (November 13, 2021): 10713. http://dx.doi.org/10.3390/app112210713.

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Autonomous driving is a safety-critical application that requires a high-level understanding of computer vision with real-time inference. In this study, we focus on the computational efficiency of an important factor by improving the running time and performing multiple tasks simultaneously for practical applications. We propose a fast and accurate multi-task learning-based architecture for joint segmentation of drivable area, lane line, and classification of the scene. An encoder–decoder architecture efficiently handles input frames through shared representation. A comprehensive understanding of the driving environment is improved by generalization and regularization from different tasks. The proposed method learns end-to-end through multi-task learning on a very challenging Berkeley Deep Drive dataset and shows its robustness for three tasks in autonomous driving. Experimental results show that the proposed method outperforms other multi-task learning approaches in both speed and accuracy. The computational efficiency of the method was over 93.81 fps at inference, enabling execution in real-time.

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Mao, Huachao, Wenxuan Jia, Yuen-Shan Leung, Jie Jin, and Yong Chen. "Multi-material stereolithography using curing-on-demand printheads." Rapid Prototyping Journal 27, no. 5 (June 2, 2021): 861–71. http://dx.doi.org/10.1108/rpj-05-2020-0104.

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Purpose This paper aims to present a multi-material additive manufacturing (AM) process with a newly developed curing-on-demand method to fabricate a three-dimensional (3D) object with multiple material compositions. Design/methodology/approach Unlike the deposition-on-demand printing method, the proposed curing-on-demand printheads use a digital light processing (DLP) projector to selectively cure a thin layer of liquid photocurable resin and then clean the residual uncured material effectively using a vacuuming and post-curing device. Each printhead can individually fabricate one type of material using digitally controlled mask image patterns. The proposed AM process can accurately deposit multiple materials in each layer by combining multiple curing-on-demand printheads together. Consequently, a three-dimensional object can be fabricated layer-by-layer using the developed curing-on-demand printing method. Findings Effective cleaning of uncured resin is realized with reduced coated resin whose height is in the sub-millimeter level and improved vacuum cleaning performance with the uncleaned resin less than 10 µm thick. Also, fast material swapping is achieved using the compact design of multiple printheads. Originality/value The proposed multi-material stereolithography (SL) process enables 3D printing components using more viscous materials and can achieve desired manufacturing characteristics, including high feature resolution, fast fabrication speed and low machine cost.

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Prejbeanu, Răzvan Gabriel. "A Sensor-Based System for Fault Detection and Prediction for EV Multi-Level Converters." Sensors 23, no. 9 (April 22, 2023): 4205. http://dx.doi.org/10.3390/s23094205.

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Power electronic converters and alternating current motors are the actual driving solution applied to electric vehicles (EVs). Multilevel inverters with high performance are modern and the basis for powering and driving EVs. Fault component detection in multilevel power converters requires the use of a smart sensor-based strategy and an optimal fault analysis and prediction method. An innovative method for the detection and prediction of defects in multilevel inverters for EVs is proposed in this article. This method is based on an algorithm able to determine in a fast and efficient way the faults in a multilevel inverter in different possible topologies. Moreover, the fault detection is achieved not only for a single component, but even for several components, if these faults occur simultaneously. The detection mechanism is based on the analysis of the output current and voltage from the inverter, with the possibility of distinguishing between single and multiple faults of the power electronic components. High-performance simulation programs are used to define and verify the method model. Additionally, with this model, harmonic analysis can be performed to check the correctness of the system’s operation, and different fault scenarios can be simulated. Thus, significant results were obtained by simulation on various topologies of multilevel converters. Further, a test bench was developed in order to verify some failure situations on a three-level inverter.

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Adamowicz, Marek, Zbigniew Krzemiński, and Paweł Stec. "Dual Active Bridge (DAB) DC-DC converter for multilevel propulsion converters for electrical multiple units (EMU)." MATEC Web of Conferences 180 (2018): 04002. http://dx.doi.org/10.1051/matecconf/201818004002.

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Semiconductor power devices made from silicon carbide (SiC) reached a level of technology enabling their widespread use in power converters. Two different approaches to implementation of modern traction converters in electric multiple units (EMU) have been presented in recent years: (i) 3.3-kV SiC MOSFET-based three-level PWM inverter with regenerative braking and (ii) 6.5-kV IGBT-based fourquadrant power electronic traction transformer (PETT). The former has successfully reached optimized dimensions and efficiency but still requires a bulky line frequency transformer for multisystem applications. The latter characterizes inherent galvanic isolation from AC traction, which is realized by cascaded system of power electronic cells containing medium frequency transformers (MFT). The downsizing of the 6.5-kV IGBT-based cells is, however, problematic. The present paper proposes a different approach, that involves the use of a fast switching 1.2-kV SiC MOSFETS. The SiC-based PETT proposed in the paper is dedicated first for the DC traction. For multi-system application the input voltage of the proposed PETT can be adjusted using weight-optimized adjusting autotransformer. Thanks to utilization of fast-switching SiCbased power modules the weight and size of the power electronic cells can be optimized in a convenient way.

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Zhu, X., and T. Wiegelmann. "Toward a fast and consistent approach to modeling solar magnetic fields in multiple layers." Astronomy & Astrophysics 658 (January 28, 2022): A37. http://dx.doi.org/10.1051/0004-6361/202141505.

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Aims. We aim to develop a fast and consistent extrapolation method for modeling multiple layers of the solar atmosphere. Methods. The new approach combines the magnetohydrostatic (MHS) extrapolation, which models the solar low atmosphere in a flat box, together with the nonlinear force-free field (NLFFF) extrapolation, which models the solar corona with a chromospheric vector magnetogram deduced from the MHS extrapolation. We tested our code with a snapshot of a radiative magnetohydrodynamic simulation of a solar flare and we conducted quantitative comparisons based on several metrics. Results. Following a number of test runs, we found an optimized configuration for the combination of two extrapolations with a 5.8-Mm-high box for the MHS extrapolation and a magnetogram at a height of 1 Mm for the NLFFF extrapolation. The new approach under this configuration has the capability to reconstruct the magnetic fields in multi-layers accurately and efficiently. Based on figures of merit that are used to assess the performance of different extrapolations (NLFFF extrapolation, MHS extrapolation, and the combined one), we find the combined extrapolation reaches the same level of accuracy as the MHS extrapolation and they are both better than the NLFFF extrapolation. The combined extrapolation is moderately efficient for application to magnetograms with high resolution.

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Sha, MaiChao, RuiJin Zhu, and XueJiao Gong. "Fixed frequency Finite Control Set Model Predictive Control For Three-level APF." E3S Web of Conferences 233 (2021): 04028. http://dx.doi.org/10.1051/e3sconf/202123304028.

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Active power filter can compensate harmonic and reactive power, Three level neutral point clamp (ANPC) has the characteristics of low output harmonic and low device loss. The control of three-level active power filter needs to consider multiple objectives. Finite control set model predictive control (FCS-MPC) is a new method which can add constraints and multi-objective control. According to the limit of the switch state, it can track the reference current, which has the characteristics of fast dynamic response and good compensation effect. This method not only keeps the neutral point voltage balance, but also solves the problem of unstable switching frequency.

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Ye, Qin, Pengcheng Shi, Kunyuan Xu, Popo Gui, and Shaoming Zhang. "A Novel Loop Closure Detection Approach Using Simplified Structure for Low-Cost LiDAR." Sensors 20, no. 8 (April 17, 2020): 2299. http://dx.doi.org/10.3390/s20082299.

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Reducing the cumulative error is a crucial task in simultaneous localization and mapping (SLAM). Usually, Loop Closure Detection (LCD) is exploited to accomplish this work for SLAM and robot navigation. With a fast and accurate loop detection, it can significantly improve global localization stability and reduce mapping errors. However, the LCD task based on point cloud still has some problems, such as over-reliance on high-resolution sensors, and poor detection efficiency and accuracy. Therefore, in this paper, we propose a novel and fast global LCD method using a low-cost 16 beam Lidar based on “Simplified Structure”. Firstly, we extract the “Simplified Structure” from the indoor point cloud, classify them into two levels, and manage the “Simplified Structure” hierarchically according to its structure salience. The “Simplified Structure” has simple feature geometry and can be exploited to capture the indoor stable structures. Secondly, we analyze the point cloud registration suitability with a pre-match, and present a hierarchical matching strategy with multiple geometric constraints in Euclidean Space to match two scans. Finally, we construct a multi-state loop evaluation model for a multi-level structure to determine whether the two candidate scans are a loop. In fact, our method also provides a transformation for point cloud registration with “Simplified Structure” when a loop is detected successfully. Experiments are carried out on three types of indoor environment. A 16 beam Lidar is used to collect data. The experimental results demonstrate that our method can detect global loop closures efficiently and accurately. The average global LCD precision, accuracy and negative are approximately 0.90, 0.96, and 0.97, respectively.

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Sandmann, S., S. Divanbeigi, and H. Garbe. "Reflexionseigenschaften von Windenergieanlagen im Funkfeld von Funknavigations- und Radarsystemen." Advances in Radio Science 13 (November 3, 2015): 9–18. http://dx.doi.org/10.5194/ars-13-9-2015.

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Abstract. Die hier behandelte Untersuchung befasst sich mit den Störungen des elektrischen Feldes einer Doppler Very High Frequency Omnidirectional Radio Range Navigationsanlage (DVOR) in der Gegenwart von Windenergieanlagen (WEA). Hierfür wird die Feldstärke auf 25 konzentrischen Kreisbahnen, sog. Orbit Flights verschiedener Höhen und mit verschiedenen Radien rund um die DVOR-Anlage numerisch simuliert. Insbesondere werden die Einflüsse diverser Parameter der WEA wie deren Anzahl, Position, Rotorwinkel, Turmhöhe und Rotordurchmesser auf die Feldverteilung herausgestellt, sowie die Anwendbarkeit der Simulationsmethode Physical Optics (PO) durch Vergleich der Simulationsergebnisse mit denen der Multi Level Fast Multipol Method (MLFMM) untersucht.

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Sivaprakasam, T., and M. Ramasamy. "Design of System Level Architecture of Multi-Core with Array Mapping Based on Floating Processing Factor-Fast Fourier Transform for Health Informatics Application." Journal of Medical Imaging and Health Informatics 11, no. 10 (October 1, 2021): 2639–45. http://dx.doi.org/10.1166/jmihi.2021.3852.

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In FFT algorithms memory access patterns prevent multiple architectures from achieving high machine use, particularly when parallel processing is needed to achieve the desired efficiency rates. Beginning with the extremely powerful FFT heart, the on-chip memory hierarchy for the multicored FFT processor, is co-designed and linked on-chip. We have shown that the Floating Processing Factor (FPPE) proposed achieves greater operating rate and lower power for the application of health informatics. This test mechanism aids in omission of faulty cores and autonomous detection also makes elegant multi-core architecture degradation feasible. Experimental results illustrate that the anticipated design is scalable widely in terms of performance overhead and hardware overhead which makes it appropriate to many-cores with more than a thousand processing cores through Low Power and High Speed.

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Thienpont, Joshua R., Jennifer B. Korosi, Kathryn E. Hargan, Trisha Williams, David C. Eickmeyer, Linda E. Kimpe, Michael J. Palmer, John P. Smol, and Jules M. Blais. "Multi-trophic level response to extreme metal contamination from gold mining in a subarctic lake." Proceedings of the Royal Society B: Biological Sciences 283, no. 1836 (August 17, 2016): 20161125. http://dx.doi.org/10.1098/rspb.2016.1125.

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Giant Mine, located in the city of Yellowknife (Northwest Territories, Canada), is a dramatic example of subarctic legacy contamination from mining activities, with remediation costs projected to exceed $1 billion. Operational between 1948 and 2004, gold extraction at Giant Mine released large quantities of arsenic and metals from the roasting of arsenopyrite ore. We examined the long-term ecological effects of roaster emissions on Pocket Lake, a small lake at the edge of the Giant Mine lease boundary, using a spectrum of palaeoenvironmental approaches. A dated sedimentary profile tracked striking increases (approx. 1700%) in arsenic concentrations coeval with the initiation of Giant Mine operations. Large increases in mercury, antimony and lead also occurred. Synchronous changes in biological indicator assemblages from multiple aquatic trophic levels, in both benthic and pelagic habitats, indicate dramatic ecological responses to extreme metal(loid) contamination. At the peak of contamination, all Cladocera, a keystone group of primary consumers, as well as all planktonic diatoms, were functionally lost from the sediment record. No biological recovery has been inferred, despite the fact that the bulk of metal(loid) emissions occurred more than 50 years ago, and the cessation of all ore-roasting activities in Yellowknife in 1999.

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Cano, Jose Alejandro. "Formulations for joint order picking problems in low-level picker-to-part systems." Bulletin of Electrical Engineering and Informatics 9, no. 2 (April 1, 2020): 834–42. http://dx.doi.org/10.11591/eei.v9i2.2110.

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This article introduces several mathematical formulations for the joint order picking problem (JOPP) in low-level picker-to-part warehousing systems. In order to represent real warehousing environments, the proposed models minimize performance measures such as travel distance, travel time and tardiness, considering multi-block warehouses, due dates, and multiple pickers. The number of constraints and decision variables required for each proposed model is calculated, demonstrating the complexity of solving medium and long-sized problems in reasonable computing time using exact methods. The proposed models can be followed as a reference for new solution methods that yield efficient and fast solutions.

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Tejada, Eduardo, Rosane Minghim, and Luis Gustavo Nonato. "On Improved Projection Techniques to Support Visual Exploration of Multi-Dimensional Data Sets." Information Visualization 2, no. 4 (December 2003): 218–31. http://dx.doi.org/10.1057/palgrave.ivs.9500054.

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Projection (or dimensionality reduction) techniques have been used as a means to handling the growing dimensionality of data sets as well as providing a way to visualize information coded into point relationships. Their role is essential in data interpretation and simultaneous use of different projections and their visualizations improve data understanding and increase the level of confidence in the result. For that purpose, projections should be fast to allow multiple views of the same data set. In this work we present a novel fast technique for projecting multi-dimensional data sets into bidimensional (2D) spaces that preserves neighborhood relationships. Additionally, a new technique for improving 2D projections from multi-dimensional data is presented, that helps reduce the inherent loss of information yielded by dimensionality reduction. The results are stimulating and are presented in the form of comparative visualizations against known and new 2D projection techniques. Based on the projection improvement approach presented here, a new metric for quality of projection is also given, that matches well the visual perception of quality. We discuss the implication of using improved projections in visual exploration of large data sets and the role of interaction in visualization of projected subspaces.

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Lu, Tong, Sizu Hou, and Yan Xu. "Ultra-Short-Term Load Forecasting for Customer-Level Integrated Energy Systems Based on Composite VTDS Models." Processes 11, no. 8 (August 16, 2023): 2461. http://dx.doi.org/10.3390/pr11082461.

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A method is proposed to address the challenging issue of load prediction in user-level integrated energy systems (IESs) using a composite VTDS model. Firstly, an IES multi-dimensional load time series is decomposed into multiple intrinsic mode functions (IMFs) using variational mode decomposition (VMD). Then, each IMF, along with other influential features, is subjected to data dimensionality reduction and clustering denoising using t-distributed stochastic neighbor embedding (t-SNE) and fast density-based spatial clustering of applications with noise (FDBSCAN) to perform major feature selection. Subsequently, the reduced and denoised data are reconstructed, and a time-aware long short-term memory (T-LSTM) artificial neural network is employed to fill in missing data by incorporating time interval information. Finally, the selected multi-factor load time series is used as input into a support vector regression (SVR) model optimized using the quantum particle swarm optimization (QPSO) algorithm for load prediction. Using measured load data from a specific user-level IES at the Tempe campus of Arizona State University, USA, as a case study, a comparative analysis between the VTDS method and other approaches is conducted. The results demonstrate that the method proposed in this study achieved higher accuracy in short-term forecasting of the IES’s multiple loads.

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Zamkov, Mikhail. "(Keynote) Colloidal Quantum Shells: An Emerging Class of 2D Semiconductors." ECS Meeting Abstracts MA2022-02, no. 20 (October 9, 2022): 899. http://dx.doi.org/10.1149/ma2022-0220899mtgabs.

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Low-dimensional colloidal semiconductors are inexpensive to process and offer a broad spectrum of attractive quantum-mechanical properties. The notorious problem of these nanostructures lies in their limited performance under high energetic loads, when more than one exciton per particle is created. Multiple excitons undergo fast Auger recombination, causing efficiently roll-off in energy-intensive applications, including high-brightness LEDs, X-ray scintillators, and solar cells. This presentation will discuss an emerging type of low-dimensional semiconductors, known as colloidal quantum shells that allow avoiding such multi-exciton (MX) energy losses. The geometry of quantum shells benefits from the spatial separation of multiple excitons, which leads to extraordinary improvements to MX lifetimes and MX quantum yield. We will compare quantum shells with other nanoscale geometries in three categories: Auger suppression, multi-exciton level structure, and solution-processed film conductivity, highlighting the potential benefits quantum shells can contribute to various applications. Theoretical analysis discussing the role of the quantum shell geometry in suppressing Auger recombination will also be presented.

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Theiler, P. W., J. D. Wegner, and K. Schindler. "Fast registration of laser scans with 4-point congruent sets - what works and what doesn't." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3 (August 7, 2014): 149–56. http://dx.doi.org/10.5194/isprsannals-ii-3-149-2014.

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Sampling-based algorithms in the mould of RANSAC have emerged as one of the most successful methods for the fully automated registration of point clouds acquired by terrestrial laser scanning (TLS). Sampling methods in conjunction with 3D keypoint extraction, have shown promising results, e.g. the recent K-4PCS (Theiler et al., 2013). However, they still exhibit certain improbable failures, and are computationally expensive and slow if the overlap between scans is low. Here, we examine several variations of the basic K-4PCS framework that have the potential to improve its runtime and robustness. Since the method is inherently parallelizable, straight-forward multi-threading already brings down runtimes to a practically acceptable level (seconds to minutes). At a conceptual level, replacing the RANSAC error function with the more principled MSAC function (Torr and Zisserman, 2000) and introducing a minimum-distance prior to counter the near-field bias reduce failure rates by a factor of up to 4. On the other hand, replacing the repeated evaluation of the RANSAC error function with a voting scheme over the transformation parameters proved not to be generally applicable for the scan registration problem. All these possible extensions are tested experimentally on multiple challenging outdoor and indoor scenarios.

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Bush, S. H., H. A. Parsons, J. L. Palmer, R. Chacko, Z. Li, C. Scott, and E. Bruera. "Single- versus multiple-item assessment of quality of life in patients with advanced cancer." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): e20528-e20528. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e20528.

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e20528 Background: The main objective of palliative cancer care is to improve quality of life (QOL). As multiple dimensions impact on the construct of QOL, multi-dimensional instruments are usually used in its measurement. These are time consuming and burdensome for repeated use. Recent authors have suggested that brief single-item global assessments can provide a reliable measure of QOL. We assessed the performance of the Edmonton Symptom Assessment System ‘feeling of well-being’ item (ESAS WB) using the Functional Assessment of Cancer Therapy - General (FACT-G) instrument as a gold standard. Methods: After obtaining IRB approval, we reviewed the data from 213 advanced cancer patients who had participated in six studies from March 2006 to June 2008 and determined the level of association between baseline ESAS WB and FACT-G total score and subscale domains (Physical (Pwb), Social/Family (Swb), Emotional (Ewb), and Functional (Fwb) Well-Being) and also the 9 ESAS symptom intensity scores using Spearman correlation coefficients. We also calculated the change between the baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score and determined their level of association using a Pearson correlation coefficient. In addition, we predicted the change in FACT-G as predicted by the change in ESAS WB score using regression analysis. Results: Mean age was 60 (SD 12) years and 48% were female. At T1, the Spearman correlation coefficient of ESAS WB and FACT-G was -0.48 (p<0.0001). Spearman correlation coefficients for ESAS WB and FACT-G subscale domains and ESAS symptom intensity scores were also highly significant (p<0.0001) for all physical and emotional symptoms (other than p=0.003 for nausea) except for FACT Swb (p=0.08). The Pearson correlation coefficient for difference between T1 and T2 in ESAS WB and FACT-G for 146 patients was -0.36 (p<0.0001). The regression analysis was highly significant (p<0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference (MID) was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. Conclusions: ESAS WB is a practical instrument for clinical use and best reflects the Pwb, Ewb and Fwb domains of FACT-G as compared to Swb. No significant financial relationships to disclose.

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Ford, Michele, and Michael Gillan. "Power resources and supranational mechanisms: The global unions and the OECD Guidelines." European Journal of Industrial Relations 27, no. 3 (January 25, 2021): 307–25. http://dx.doi.org/10.1177/0959680120988238.

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This article uses the power resources approach to analyse the Global Union Federations’ (GUFs) use of the specific instances mechanism associated with the OECD Guidelines for Multinational Enterprises. While this mechanism has serious limitations, it has proved to be a useful tool when combined with public campaigns and the exercise of other power resources at multiple scales. This is so, we argue, because the fact that multi-national enterprises themselves operate across national boundaries creates an incentive to engage power resources at a supranational level, as well as within the countries where they, or their suppliers, are present. As this finding suggests, consideration of unions’ power resources benefits from deeper consideration of the multi-scalar and interrelated character of union action and of the role that intermediary coordinating organizations like GUFs play in supporting the exercise of power at the supranational level.

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Li, Shuo, Fang Liu, and Licheng Jiao. "Self-Training Multi-Sequence Learning with Transformer for Weakly Supervised Video Anomaly Detection." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (June 28, 2022): 1395–403. http://dx.doi.org/10.1609/aaai.v36i2.20028.

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Weakly supervised Video Anomaly Detection (VAD) using Multi-Instance Learning (MIL) is usually based on the fact that the anomaly score of an abnormal snippet is higher than that of a normal snippet. In the beginning of training, due to the limited accuracy of the model, it is easy to select the wrong abnormal snippet. In order to reduce the probability of selection errors, we first propose a Multi-Sequence Learning (MSL) method and a hinge-based MSL ranking loss that uses a sequence composed of multiple snippets as an optimization unit. We then design a Transformer-based MSL network to learn both video-level anomaly probability and snippet-level anomaly scores. In the inference stage, we propose to use the video-level anomaly probability to suppress the fluctuation of snippet-level anomaly scores. Finally, since VAD needs to predict the snippet-level anomaly scores, by gradually reducing the length of selected sequence, we propose a self-training strategy to gradually refine the anomaly scores. Experimental results show that our method achieves significant improvements on ShanghaiTech, UCF-Crime, and XD-Violence.

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Xiao, Yang, Wen, and Jiang. "A Unified Multiple-Target Positioning Framework for Intelligent Connected Vehicles." Sensors 19, no. 9 (April 26, 2019): 1967. http://dx.doi.org/10.3390/s19091967.

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Future intelligent transport systems depend on the accurate positioning of multipletargets in the road scene, including vehicles and all other moving or static elements. The existingself-positioning capability of individual vehicles remains insufficient. Also, bottlenecks indeveloping on-board perception systems stymie further improvements in the precision and integrityof positioning targets. Vehicle-to-everything (V2X) communication, which is fast becoming astandard component of intelligent and connected vehicles, renders new sources of informationsuch as dynamically updated high-definition (HD) maps accessible. In this paper, we propose aunified theoretical framework for multiple-target positioning by fusing multi-source heterogeneousinformation from the on-board sensors and V2X technology of vehicles. Numerical and theoreticalstudies are conducted to evaluate the performance of the framework proposed. With a low-costglobal navigation satellite system (GNSS) coupled with an initial navigation system (INS), on-boardsensors, and a normally equipped HD map, the precision of multiple-target positioning attainedcan meet the requirements of high-level automated vehicles. Meanwhile, the integrity of targetsensing is significantly improved by the sharing of sensor information and exploitation of mapdata. Furthermore, our framework is more adaptable to traffic scenarios when compared withstate-of-the-art techniques.

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Candelieri, Antonio, and Francesco Archetti. "Sparsifying to optimize over multiple information sources: an augmented Gaussian process based algorithm." Structural and Multidisciplinary Optimization 64, no. 1 (April 5, 2021): 239–55. http://dx.doi.org/10.1007/s00158-021-02882-7.

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AbstractOptimizing a black-box, expensive, and multi-extremal function, given multiple approximations, is a challenging task known as multi-information source optimization (MISO), where each source has a different cost and the level of approximation (aka fidelity) of each source can change over the search space. While most of the current approaches fuse the Gaussian processes (GPs) modelling each source, we propose to use GP sparsification to select only “reliable” function evaluations performed over all the sources. These selected evaluations are used to create an augmented Gaussian process (AGP), whose name is implied by the fact that the evaluations on the most expensive source are augmented with the reliable evaluations over less expensive sources. A new acquisition function, based on confidence bound, is also proposed, including both cost of the next source to query and the location-dependent approximation of that source. This approximation is estimated through a model discrepancy measure and the prediction uncertainty of the GPs. MISO-AGP and the MISO-fused GP counterpart are compared on two test problems and hyperparameter optimization of a machine learning classifier on a large dataset.

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Lu, Kaili, Enhai Liu, Rujin Zhao, Hong Tian, and Hui Zhang. "A Fast Star Identification Algorithm of Star Sensors in the LIS Mode." Remote Sensing 14, no. 7 (April 5, 2022): 1739. http://dx.doi.org/10.3390/rs14071739.

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In the South Atlantic Anomaly (SAA) area, due to the influence of transient noise caused by space radiation, a star sensor can easily stay in the lost-in-space (LIS) mode for a long time. To solve this problem, this paper proposes a fast star identification (FSI) algorithm. First, a noise suppression method based on scale assessment and neighborhood comparison is developed. Next, a fast and accurate search technique of multiple main stars based on the k-vector technique is used to realize star identification. The search technique builds a self-defined attribute database of stars, and a fast search method of a repeated star identity is proposed to realize the positioning of the main star. Lastly, the final main stars are obtained through the comparison of field of view and verification of angular distance. The experimental results showed that when the star sensor works at a speed of 0.1°/s and the level of transient noise signals is lower than 900, the successful identification rate is higher than 70%. In addition, compared with the triangle algorithm, match group algorithm, and multi-pole algorithm (MPA), the proposed FSI algorithm has the advantages of a higher successful identification rate and a faster execution speed.

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Amieur, Khalissa Derbal, Kamel Boukhalfa, and Zaia Alimazighi. "Geo-Multi-Agent System Based Webmapping Approach Using Multiple Representation and Generalisation Driven by Domain Ontology." International Journal of Information Technology and Web Engineering 8, no. 4 (October 2013): 48–64. http://dx.doi.org/10.4018/ijitwe.2013100104.

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Geographic Information (GI) is currently available at any time, from anywhere on the surface of the earth, for any person connected to internet. Some applications of design, implementation, generation and dissemination of maps on the web are recognized as “Webmapping” application, geographic web services or more generally on demand-map making tools. All these web applications aims the satisfaction of user needs by providing personalized maps in a fast response time with a good quality. However, the complexity and diversity of aspects taking into account have lead researchers to focus on one aspect at the expense of others. Consequently, few works have addressed all these aspects simultaneously. The authors propose in this paper, a Webmapping approach organized into two main tasks: (1) query analysis driven by domain ontology in analyzing a query launched by a user on a web browser and (2) map generation process. The first step allows extracting and formalizing user needs through two map determinants factors: the Level of Detail (LoD) and Point of View (PoV) and the second, exploit an hybrid approach “Multi Representation and Generalization” in storing and generating geographical data with integrating Multi-Agent technology in all steps of processing. To evaluate the effectiveness of our proposal, a first tool prototype implementing our approach is so developed using a geographic vector dataset provided by national cartographic agency.

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Florea, Horatiu, Andra Petrovai, Ion Giosan, Florin Oniga, Robert Varga, and Sergiu Nedevschi. "Enhanced Perception for Autonomous Driving Using Semantic and Geometric Data Fusion." Sensors 22, no. 13 (July 5, 2022): 5061. http://dx.doi.org/10.3390/s22135061.

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Environment perception remains one of the key tasks in autonomous driving for which solutions have yet to reach maturity. Multi-modal approaches benefit from the complementary physical properties specific to each sensor technology used, boosting overall performance. The added complexity brought on by data fusion processes is not trivial to solve, with design decisions heavily influencing the balance between quality and latency of the results. In this paper we present our novel real-time, 360∘ enhanced perception component based on low-level fusion between geometry provided by the LiDAR-based 3D point clouds and semantic scene information obtained from multiple RGB cameras, of multiple types. This multi-modal, multi-sensor scheme enables better range coverage, improved detection and classification quality with increased robustness. Semantic, instance and panoptic segmentations of 2D data are computed using efficient deep-learning-based algorithms, while 3D point clouds are segmented using a fast, traditional voxel-based solution. Finally, the fusion obtained through point-to-image projection yields a semantically enhanced 3D point cloud that allows enhanced perception through 3D detection refinement and 3D object classification. The planning and control systems of the vehicle receives the individual sensors’ perception together with the enhanced one, as well as the semantically enhanced 3D points. The developed perception solutions are successfully integrated onto an autonomous vehicle software stack, as part of the UP-Drive project.

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Emerson, John, and Yllias Chali. "Transformer-Based Multi-Hop Question Generation (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (June 26, 2023): 16206–7. http://dx.doi.org/10.1609/aaai.v37i13.26963.

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Question generation is the parallel task of question answering, where given an input context and, optionally, an answer, the goal is to generate a relevant and fluent natural language question. Although recent works on question generation have experienced success by utilizing sequence-to-sequence models, there is a need for question generation models to handle increasingly complex input contexts to produce increasingly detailed questions. Multi-hop question generation is a more challenging task that aims to generate questions by connecting multiple facts from multiple input contexts. In this work, we apply a transformer model to the task of multi-hop question generation without utilizing any sentence-level supporting fact information. We utilize concepts that have proven effective in single-hop question generation, including a copy mechanism and placeholder tokens. We evaluate our model’s performance on the HotpotQA dataset using automated evaluation metrics, including BLEU, ROUGE and METEOR and show an improvement over the previous work.

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Marković, Milan, Jelena J. Stanković, Panagiota Digkoglou, and Ivana Marjanović. "Evaluation of Social Protection Performance in EU Countries: Multiple-criteria Decision Analysis (MCDA)." Problemy Ekorozwoju 17, no. 2 (June 10, 2022): 124–32. http://dx.doi.org/10.35784/pe.2022.2.13.

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The paper aims to rank European Union (EU) countries according to the composite index, which uses selected social protection indicators from the relevant database at EU level – Eurostat. The total score of social performance for 2020 was determined using the CRITIC-TOPSIS framework. The study showed that Austria, Luxembourg and Germany, respectively, had the best level of social protection, while Latvia, Romania and Spain were at the bottom, as the countries with the worst values of indicators. The importance of research is reflected in the fact that the social component of sustainable development is still not sufficiently researched, especially when it comes to the application of multi-criteria analysis methods in the empirical analysis of social sustainability. In this regard, de- pending on the obtained performance values, socio-economic policymakers can redesign existing measures and programs, as well as the amounts of social transfers to certain EU member states. The authors expect that the results of the study will help build higher social standards and well-being in the EU.

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Usanov, Vladimir I., Stepan A. Kvyatkovskiy, Andrey A. Andrianov, and Ilya S. Kuptsov. "Multi-criteria evaluation and ranking of potential scenarios for the development of Russian two-component nuclear energy system with thermal and sodium-cooled fast reactors." Nuclear Energy and Technology 7, no. 3 (September 14, 2021): 165–72. http://dx.doi.org/10.3897/nucet.7.72391.

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The paper presents the results from a multi-criteria comparative evaluation of potential deployment scenarios for Russian nuclear power with thermal and sodium-cooled fast reactors in a closed nuclear fuel cycle (the so-called two-component nuclear energy system). The comparison and the ranking were performed taking into account the recommendations and using the IAEA/INPRO software tools for comparative evaluation of nuclear energy systems, including tools for sensitivity/uncertainty analysis with respect to weighting factors. Ten potential Russian nuclear power deployment scenarios with different shares of thermal and sodium-cooled fast reactors were considered, including options involving the use of MOX fuel in VVER reactors. Eight key indicators were used, estimated as of 2100 and structured into a three-level objectives tree. The comparative evaluation and the ranking were carried out based on the multi-attribute value theory. The model for assessing the key indicators was developed using the IAEA/INPRO MESSAGE-NES energy system planning software tool. The information base for the study was formed by publications of experts from JSC SSC RF-IPPE, NRC Kurchatov Institute and NRNU MEPhI. The presented results show that it is possible to enhance significantly the sustainability of the Russian nuclear energy system, when considering multiple performance indicators, through the intensive deployment of sodium-cooled fast reactors and the transition to a closed nuclear fuel cycle. Tasks have been outlined for the follow-up studies to make it possible to obtain more rigorous conclusions regarding the preferred options for the evolution of a two-component nuclear energy system.

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Sun, Yajing, Yue Hu, Luxi Xing, Jing Yu, and Yuqiang Xie. "History-Adaption Knowledge Incorporation Mechanism for Multi-Turn Dialogue System." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8944–51. http://dx.doi.org/10.1609/aaai.v34i05.6425.

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Keeping the conversation consistent and avoiding its repetition are two key factors to construct an intelligent multi-turn knowledge-grounded dialogue system. Although some works tend to combine history with external knowledge such as personal background information to boost dialogue quality, they are prone to ignore the fact that incorporating the same knowledge multiple times into the conversation leads to repetition. The main reason is the lack of effective control over the use of knowledge on the conversation level. So we design a history-adaption knowledge incorporation mechanism to build an effective multi-turn dialogue model. Our proposed model addresses repetition by recurrently updating the knowledge from the conversation level and progressively incorporating it into the history step-by-step. And the knowledge-grounded history representation also enhances the conversation consistency. Experimental results show that our proposed model significantly outperforms several retrieval-based models on some benchmark datasets. The human evaluation demonstrates that our model can maintain conversation consistent and reduce conversation repetition.

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Hao, Guoqing, Dejun Feng, Junjie Wang, Zimeng Zhou, and Ling Wang. "Track False-Target Deception Method Based on Phase-Switched Screen." Electronics 12, no. 13 (July 7, 2023): 2996. http://dx.doi.org/10.3390/electronics12132996.

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Track processing is the foundation of radar multi-target tracking, and the processing performance for jamming has particular research significance when it comes to protecting high-value targets. At present, passive jamming using a modulated metasurface exhibits a fast response and a flexible operation mode. However, most research in this area has been carried out at the radar signal processing level and less at the data processing level. In this paper, a range of false target track deception method based on a phase-switched screen (PSS) is proposed, and the relationship between the matched filtering output, radar detection, and track processing is derived. This method uses PSS to generate multiple false targets with controlled spatial distribution and magnitude, which can form high-fidelity false tracking tracks. The number of false tracking tracks can be flexibly altered by controlling the modulation parameters. The simulation results validate the effectiveness of the proposed method.

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Albahli, Saleh, and Ghulam Nabi Ahmad Hassan Yar. "Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study." Journal of Medical Internet Research 23, no. 2 (February 10, 2021): e23693. http://dx.doi.org/10.2196/23693.

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Background COVID-19 has spread very rapidly, and it is important to build a system that can detect it in order to help an overwhelmed health care system. Many research studies on chest diseases rely on the strengths of deep learning techniques. Although some of these studies used state-of-the-art techniques and were able to deliver promising results, these techniques are not very useful if they can detect only one type of disease without detecting the others. Objective The main objective of this study was to achieve a fast and more accurate diagnosis of COVID-19. This study proposes a diagnostic technique that classifies COVID-19 x-ray images from normal x-ray images and those specific to 14 other chest diseases. Methods In this paper, we propose a novel, multilevel pipeline, based on deep learning models, to detect COVID-19 along with other chest diseases based on x-ray images. This pipeline reduces the burden of a single network to classify a large number of classes. The deep learning models used in this study were pretrained on the ImageNet dataset, and transfer learning was used for fast training. The lungs and heart were segmented from the whole x-ray images and passed onto the first classifier that checks whether the x-ray is normal, COVID-19 affected, or characteristic of another chest disease. If it is neither a COVID-19 x-ray image nor a normal one, then the second classifier comes into action and classifies the image as one of the other 14 diseases. Results We show how our model uses state-of-the-art deep neural networks to achieve classification accuracy for COVID-19 along with 14 other chest diseases and normal cases based on x-ray images, which is competitive with currently used state-of-the-art models. Due to the lack of data in some classes such as COVID-19, we applied 10-fold cross-validation through the ResNet50 model. Our classification technique thus achieved an average training accuracy of 96.04% and test accuracy of 92.52% for the first level of classification (ie, 3 classes). For the second level of classification (ie, 14 classes), our technique achieved a maximum training accuracy of 88.52% and test accuracy of 66.634% by using ResNet50. We also found that when all the 16 classes were classified at once, the overall accuracy for COVID-19 detection decreased, which in the case of ResNet50 was 88.92% for training data and 71.905% for test data. Conclusions Our proposed pipeline can detect COVID-19 with a higher accuracy along with detecting 14 other chest diseases based on x-ray images. This is achieved by dividing the classification task into multiple steps rather than classifying them collectively.

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Journal articles on the topic 'Multi-Level Fast Multipole'

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